hypothesis for feasibility study

Guide to Conducting a Feasibility Study

What is an operating model.

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So you’re thinking of a launching a new venture? Entering a new market? Launching a new product? It’s estimated that only one in fifty business ideas are actually commercially viable and so you’ll want to understand the viability of any proposed project before you invest your time, energy and money into it. That’s why you need a feasibility study.

Why do you need a feasibility study  .

With such a low success rate of new business ventures a business feasibility study is the best way to learn whether you have an idea that could work and guard against wastage of further investment. If the results are positive, then the outcome of the feasibility study can be used as the basis for a full business plan allowing your to proceed with a clearer view of the risks involved and move forward quicker. If it’s negative then you’ve skilfully avoided wasting time and money on a venture that wouldn’t have worded out.

What is a feasibility study?  

A feasibility study aims to make a recommendation as to the likely success of a venture. At the heart of any feasibility study is a hypothesis or question that you want to answer.  Examples include “is there a demand for a X new product or product feature”, “should we enter Y market” and “should we launch Z new venture”.

How to conduct a feasibility study?  

Once you’ve got a clear hypothesis or question that you want to answer, you need to look at five areas that will impact the feasibility of your idea. Let’s look at each of these in turn:

Market Feasibility

Is the market in question attractive? Are there high barrier to entry? Is it of a size that will support our ambitions? Is it growing? Are there any regulatory or legislative requirements to enter or participate in the market?

Technical Feasibility

What technical skills/ability/knowledge/equipment is required? Do you have or could you source the technical expertise required? Do you fully understand the technical requirements underpinning your hypothesis? Could you manufacture / develop the product or service with the resources you have available?

Business Model Feasibility

How will the idea make money? How will you attract users? What costs will you have to pay? Have you modelled the financials? Do you have access to the funding needed? What legal entity structure would you need?

Management Model Feasibility

Who will lead the venture? Do you have the skills and expertise required to manage and operate the venture/product/market? Does the team have the time needed to deliver the venture? If not, can they be recruited or are their skills hard to find?

Exit Feasibility

Do you have a plan to exit the venture and do you need one?

When competing a feasibility study each of the above areas should have a recommendation as to whether it’s feasible or not from that specific perspective factoring in the resources you have available.  This should conclude with a recommendation based on the analysis as to if the venture is or isn’t feasible and the key data points that underpin that recommendation.

Remember that a great feasibility study should not just give you a go / no-go decision. It should provide either a spring board to move forward, highlighting the key areas to focus on to achieve success or a useful analysis highlighting the key obstacles that make the venture unfeasible and should be considered for any future ideas. Even if the answer is no, it’s not a wasted effort, the analysis will leave you better informed for future decisions.

A feasibility study is an essential tool for anyone looking at a new venture. It’s very easy to get excited by a new idea of proposition and steam ahead spending time and money without having a clear view as to whether it’s viable or not. A feasibility study should be your first stop to maximise the returns on your time, energy and investment.

Best of luck with your feasibility studies!

Chris Purcell @ Prussel & Co

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How to conduct a feasibility study: Template and examples

Opportunities are everywhere. Some opportunities are small and don’t require many resources. Others are massive and need further analysis and evaluation.

One of your key responsibilities as a product manager is to evaluate the potential success of those opportunities before investing significant money, time, and resources. A feasibility study, also known as a feasibility assessment or feasibility analysis, is a critical tool that can help product managers determine whether a product idea or opportunity is viable, feasible, and profitable.

So, what is a feasibility analysis? Why should product managers use it? And how do you conduct one?

What is a feasibility study?

A feasibility study is a systematic analysis and evaluation of a product opportunity’s potential to succeed. It aims to determine whether a proposed opportunity is financially and technically viable, operationally feasible, and commercially profitable.

A feasibility study typically includes an assessment of a wide range of factors, including the technical requirements of the product, resources needed to develop and launch the product, the potential market gap and demand, the competitive landscape, and economic and financial viability.

Based on the analysis’s findings, the product manager and their product team can decide whether to proceed with the product opportunity, modify its scope, or pursue another opportunity and solve a different problem.

Conducting a feasibility study helps PMs ensure that resources are invested in opportunities that have a high likelihood of success and align with the overall objectives and goals of the product strategy .

What are feasibility analyses used for?

Feasibility studies are particularly useful when introducing entirely new products or verticals. Product managers can use the results of a feasibility study to:

• Assess the technical feasibility of a product opportunity — Evaluate whether the proposed product idea or opportunity can be developed with the available technology, tools, resources, and expertise
• Determine a project’s financial viability — By analyzing the costs of development, manufacturing, and distribution, a feasibility study helps you determine whether your product is financially viable and can generate a positive return on investment (ROI)
• Evaluate customer demand and the competitive landscape — Assessing the potential market size, target audience, and competitive landscape for the product opportunity can inform decisions about the overall product positioning, marketing strategies, and pricing
• Identify potential risks and challenges — Identify potential obstacles or challenges that could impact the success of the identified opportunity, such as regulatory hurdles, operational and legal issues, and technical limitations
• Refine the product concept — The insights gained from a feasibility study can help you refine the product’s concept, make necessary modifications to the scope, and ultimately create a better product that is more likely to succeed in the market and meet users’ expectations

How to conduct a feasibility study

The activities involved in conducting a feasibility study differ from one organization to another. Also, the threshold, expectations, and deliverables change from role to role.

For a general set of guidelines to help you get started, here are some basic steps to conduct and report a feasibility study for major product opportunities or features.

1. Clearly define the opportunity

Imagine your user base is facing a significant problem that your product doesn’t solve. This is an opportunity. Define the opportunity clearly, support it with data, talk to your stakeholders to understand the opportunity space, and use it to define the objective.

2. Define the objective and scope

Each opportunity should be coupled with a business objective and should align with your product strategy.

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Determine and clearly communicate the business goals and objectives of the opportunity. Align those objectives with company leaders to make sure everyone is on the same page. Lastly, define the scope of what you plan to build.

3. Conduct market and user research

Now that you have everyone on the same page and the objective and scope of the opportunity clearly defined, gather data and insights on the target market.

Include elements like the total addressable market (TAM) , growth potential, competitors’ insights, and deep insight into users’ problems and preferences collected through techniques like interviews, surveys, observation studies, contextual inquiries, and focus groups.

4. Analyze technical feasibility

Suppose your market and user research have validated the problem you are trying to solve. The next step should be to, alongside your engineers, assess the technical resources and expertise needed to launch the product to the market.

Dig deeper into the proposed solution and try to comprehend the technical limitations and estimated time required for the product to be in your users’ hands.

5. Assess financial viability

If your company hasa product pricing team, work closely with them to determine the willingness to pay (WTP) and devise a monetization strategy for the new feature.

Conduct a comprehensive financial analysis, including the total cost of development, revenue streams, and the expected return on investment (ROI) based on the agreed-upon monetization strategy.

6. Evaluate potential risks

Now that you have almost a complete picture, identify the risks associated with building and launching the opportunity. Risks may include things like regulatory hurdles, technical limitations, and any operational risks.

7. Decide, prepare, and share

Based on the steps above, you should end up with a report that can help you decide whether to pursue the opportunity or not. Either way, prepare your findings, including any recommended modifications to the product scope, and present your final findings and recommendations to your stakeholders.

Make sure to prepare an executive summary for your C-suite; they will be the most critical stakeholders and the decision-makers at the end of the meeting.

Feasibility study example

Imagine you’re a product manager at a digital software company that specializes in building project management tools.

Your team has identified a potential opportunity to expand the product offering by developing a new AI-based feature that can automatically prioritize tasks for users based on their deadlines, workload, and importance.

To assess the viability of this opportunity, you can conduct a feasibility study. Here’s how you might approach it according to the process described above:

• Clearly define the opportunity — In this case, the opportunity is the development of an AI-based task prioritization feature within the existing project management software
• Define the objective and scope — The business objective is to increase user productivity and satisfaction by providing an intelligent task prioritization system. The scope includes the integration of the AI-based feature within the existing software, as well as any necessary training for users to understand and use the feature effectively
• Conduct market and user research — Investigate the demand for AI-driven task prioritization among your target audience. Collect data on competitors who may already be offering similar features and determine the unique selling points of your proposed solution. Conduct user research through interviews, surveys, and focus groups to understand users’ pain points regarding task prioritization and gauge their interest in the proposed feature
• Analyze technical feasibility — Collaborate with your engineering team to assess the technical requirements and challenges of developing the AI-based feature. Determine whether your team has the necessary expertise to implement the feature and estimate the time and resources required for its development
• Assess financial viability — Work with your pricing team to estimate the costs associated with developing, launching, and maintaining the AI-based feature. Analyze the potential revenue streams and calculate the expected ROI based on various pricing models and user adoption rates
• Evaluate potential risks — Identify any risks associated with the development and implementation of the AI-based feature, such as data privacy concerns, potential biases in the AI algorithm, or the impact on the existing product’s performance
• Decide, prepare, and share — Based on your analysis, determine whether the AI-based task prioritization feature is a viable opportunity for your company. Prepare a comprehensive report detailing your findings and recommendations, including any necessary modifications to the product scope or implementation plan. Present your findings to your stakeholders and be prepared to discuss and defend your recommendations

Feasibility study template

The following feasibility study template is designed to help you evaluate the feasibility of a product opportunity and provide a comprehensive report to inform decision-making and guide the development process.

Remember that each study will be unique to your product and market, so you may need to adjust the template to fit your specific needs.

• Briefly describe the product opportunity or feature you’re evaluating
• Explain the problem it aims to solve or the value it will bring to users
• Define the business goals and objectives for the opportunity
• Outline the scope of the product or feature, including any key components or functionality
• Summarize the findings from your market research, including data on the target market, competitors, and unique selling points
• Highlight insights from user research, such as user pain points, preferences, and potential adoption rates
• Detail the technical requirements and challenges for developing the product or feature
• Estimate the resources and expertise needed for implementation, including any necessary software, hardware, or skills
• Provide an overview of the costs associated with the development, launch, and maintenance of the product or feature
• Outline potential revenue streams and calculate the expected ROI based on various pricing models and user adoption rates
• Identify any potential risks or challenges associated with the development, implementation, or market adoption of the product or feature
• Discuss how these risks could impact the success of the opportunity and any potential mitigation strategies
• Based on your analysis, recommend whether to proceed with the opportunity, modify the scope, or explore other alternatives
• Provide a rationale for your recommendation, supported by data and insights from your research
• Summarize the key findings and recommendations from your feasibility study in a concise, easily digestible format for your stakeholders

Overcoming stakeholder management challenges

The ultimate challenge that faces most product managers when conducting a feasibility study is managing stakeholders .

Stakeholders may interfere with your analysis, jumping to conclude that your proposed product or feature won’t work and deeming it a waste of resources. They may even try to prioritize your backlog for you.

Here are some tips to help you deal with even the most difficult stakeholders during a feasibility study:

• Use hard data to make your point — Never defend your opinion based on your assumptions. Always show them data and evidence based on your user research and market analysis
• Learn to say no — You are the voice of customers, and you know their issues and how to monetize them. Don’t be afraid to say no and defend your team’s work as a product manager
• Build stakeholder buy-in early on — Engage stakeholders from the beginning of the feasibility study process by involving them in discussions and seeking their input. This helps create a sense of ownership and ensures that their concerns and insights are considered throughout the study
• Provide regular updates and maintain transparency — Keep stakeholders informed about the progress of the feasibility study by providing regular updates and sharing key findings. This transparency can help build trust, foster collaboration, and prevent misunderstandings or misaligned expectations
• Leverage stakeholder expertise — Recognize and utilize the unique expertise and knowledge that stakeholders bring to the table. By involving them in specific aspects of the feasibility study where their skills and experience can add value, you can strengthen the study’s outcomes and foster a more collaborative working relationship

Final thoughts

A feasibility study is a critical tool to use right after you identify a significant opportunity. It helps you evaluate the potential success of the opportunity, analyze and identify potential challenges, gaps, and risks in the opportunity, and provides a data-driven approach in the market insights to make an informed decision.

By conducting a feasibility study, product teams can determine whether a product idea is profitable, viable, feasible, and thus worth investing resources into. It is a crucial step in the product development process and when considering investments in significant initiatives such as launching a completely new product or vertical.

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What Is a Feasibility Study? How to Conduct One for Your Project

Table of Contents

What is a feasibility study, what’s the importance of a feasibility study, what is included in a feasibility study report, types of feasibility study.

• 7 Steps To Do a Feasibility Study

Feasibility Study Examples

Why is a feasibility study so important in project management? For one, the feasibility study or feasibility analysis is the foundation upon which your project plan resides. That’s because the feasibility analysis determines the viability of your project. Now that you know the importance, read on to learn what you need to know about feasibility studies.

A feasibility study is simply an assessment of the practicality of a proposed project plan or method. This is done by analyzing technical, economic, legal, operational and time feasibility factors. Just as the name implies, you’re asking, “Is this feasible?” For example, do you have or can you create the technology that accomplishes what you propose? Do you have the people, tools and resources necessary? And, will the project get you the ROI you expect?

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Feasibility study template

Use this free Feasibility Study Template for Word to manage your projects better.

A project feasibility study should be done during the project management life cycle after the business case has been completed. So, that’s the “what” and the “when” but how about the “why?” Why is it important to conduct a feasibility study?

An effective feasibility study points a project in the right direction by helping decision-makers have a holistic view of the potential benefits, disadvantages, barriers and constraints that could affect its outcome. The main purpose of a feasibility study is to determine whether the project can be not only viable but also beneficial from a technical, financial, legal and market standpoint.

The findings of your project feasibility study are compiled in a feasibility report that usually includes the following elements.

• Executive summary
• Description of product/service
• Technology considerations
• Product/service marketplace
• Marketing strategy
• Organization/staffing
• Financial projections
• Findings and recommendations

Free Feasibility Study Template

Use this free feasibility study template for Word to begin your own feasibility study. It has all the fundamental sections for you to get started, and it’s flexible enough to adapt to your specific needs. Download yours today.

There are many things to consider when determining project feasibility, and there are different types of feasibility studies you might conduct to assess your project from different perspectives.

Pre-Feasibility Study

A pre-feasibility study, as its name suggests, it’s a process that’s undertaken before the feasibility study. It involves decision-makers and subject matter experts who will prioritize different project ideas or approaches to quickly determine whether the project has fundamental technical, financial, operational or any other evident flaws. If the project proposal is sound, a proper feasibility study will follow.

Technical Feasibility Study

A technical feasibility study consists in determining if your organization has the technical resources and expertise to meet the project requirements . A technical study focuses on assessing whether your organization has the necessary capabilities that are needed to execute a project, such as the production capacity, facility needs, raw materials, supply chain and other inputs. In addition to these production inputs, you should also consider other factors such as regulatory compliance requirements or standards for your products or services.

Economic Feasibility Study

Also called financial feasibility study, this type of study allows you to determine whether a project is financially feasible. Economic feasibility studies require the following steps:

• Before you can start your project, you’ll need to determine the seed capital, working capital and any other capital requirements, such as contingency capital. To do this, you’ll need to estimate what types of resources will be needed for the execution of your project, such as raw materials, equipment and labor.
• Once you’ve determined what project resources are needed, you should use a cost breakdown structure to identify all your project costs.
• Identify potential sources of funding such as loans or investments from angel investors or venture capitalists.
• Estimate the expected revenue, profit margin and return on investment of your project by conducting a cost-benefit analysis , or by using business forecasting techniques such as linear programming to estimate different future outcomes under different levels of production, demand and sales.
• Estimate your project’s break-even point.
• Conduct a financial benchmark analysis with industrial averages and specific competitors in your industry.
• Use pro forma cash flow statements, financial statements, balance sheets and other financial projection documents.

Legal Feasibility Study

Your project must meet legal requirements including laws and regulations that apply to all activities and deliverables in your project scope . In addition, think about the most favorable legal structure for your organization and its investors. Each business legal structure has advantages and disadvantages when it comes to liability for business owners, such as limited liability companies (LLCs) or corporations, which reduce the liability for each business partner.

Market Feasibility Study

A market feasibility study determines whether your project has the potential to succeed in the market. To do so, you’ll need to analyze the following factors:

• Industry overview: Assess your industry, such as year-over-year growth, identify key direct and indirect competitors, availability of supplies and any other trends that might affect the future of the industry and your project.
• SWOT analysis: A SWOT analysis allows organizations to determine how competitive an organization can be by examining its strengths, weaknesses and the opportunities and threats of the market. Strengths are the operational capabilities or competitive advantages that allow an organization to outperform its competitors such as lower costs, faster production or intellectual property. Weaknesses are areas where your business might be outperformed by competitors. Opportunities are external, such as an underserved market, an increased demand for your products or favorable economic conditions. Threats are also external factors that might affect your ability to do well in the market such as new competitors, substitute products and new technologies.
• Market research: The main purpose of market research is to determine whether it’s possible for your organization to enter the market or if there are barriers to entry or constraints that might affect your ability to compete. Consider variables such as pricing, your unique value proposition, customer demand, new technologies, market trends and any other factors that affect how your business will serve your customers. Use market research techniques to identify your target market, create buyer personas, assess the competitiveness of your niche and gauge customer demand, among other things.

7 Steps to Do a Feasibility Study

If you’re ready to do your own feasibility study, follow these 7 steps. You can use this free feasibility study template to help you get started.

1. Conduct a Preliminary Analysis

Begin by outlining your project plan . You should focus on an unserved need, a market where the demand is greater than the supply and whether the product or service has a distinct advantage. Then, determine if the feasibility factors are too high to clear (i.e. too expensive, unable to effectively market, etc.).

2. Prepare a Projected Income Statement

This step requires working backward. Start with what you expect the income from the project to be and then what project funding is needed to achieve that goal. This is the foundation of an income statement. Factor in what services are required and how much they’ll cost and any adjustments to revenues, such as reimbursements, etc.

Related: Free Project Management Templates

3. Conduct a Market Survey or Perform Market Research

This step is key to the success of your feasibility study, so make your market analysis as thorough as possible. It’s so important that if your organization doesn’t have the resources to do a proper one, then it is advantageous to hire an outside firm to do so.

Market research will give you the clearest picture of the revenues and return on investment you can realistically expect from the project. Some things to consider are the geographic influence on the market, demographics, analyzing competitors, the value of the market and what your share will be and if the market is open to expansion (that is, in response to your offer).

4. Plan Business Organization and Operations

Once the groundwork of the previous steps has been laid, it’s time to set up the organization and operations of the planned project to meet its technical, operational, economic and legal feasibility factors. This isn’t a superficial, broad-stroke endeavor. It should be thorough and include start-up costs, fixed investments and operating costs.

These costs address things such as equipment, merchandising methods, real estate, personnel, supply availability, overhead, etc.

5. Prepare an Opening Day Balance Sheet

This includes an estimate of the assets and liabilities, one that should be as accurate as possible. To do this, create a list that includes items, sources, costs and available financing. Liabilities to consider are such things as leasing or purchasing land, buildings and equipment, financing for assets and accounts receivables.

6. Review and Analyze All Data

All of these steps are important, but the review and analysis are especially important to ensure that everything is as it should be and that nothing requires changing or tweaking. Take a moment to look over your work one last time.

Reexamine your previous steps, such as the income statement, and compare them with your expenses and liabilities. Is it still realistic? This is also the time to think about risk and come up with any contingency plans .

7. Make a Go/No-Go Decision

You’re now at the point to make a decision about whether or not the project is feasible. That sounds simple, but all the previous steps lead to this decision-making moment. A couple of other things to consider before making that binary choice are whether the commitment is worth the time, effort and money and whether it aligns with the organization’s strategic goals and long-term aspirations.

Here are some simple feasibility study examples so you have a better idea of what a feasibility study is used for in different industries.

Construction Feasibility Study

For this construction feasibility study example, let’s imagine a large construction company that’s interested in starting a new project in the near future to generate profits.

• Pre-Feasibility Study: The first step is to conduct a preliminary feasibility study. It can be as simple as a meeting where decision-makers will prioritize projects and discuss different project ideas to determine which poses a bigger financial benefit for the organization.
• Technical Feasibility Study: Now it’s time to estimate what resources are needed to execute the construction project, such as raw materials, equipment and labor. If there’s work that can’t be executed by the company with its current resources, a subcontractor will be hired to fill the gap.
• Economic Feasibility Study: Once the construction project management team has established what materials, equipment and labor are needed, they can estimate costs. Cost estimators use information from past projects, construction drawings and documents such as a bill of quantities to come up with an accurate cost estimate. Then, based on this estimate, a profit margin and financial forecasts will be analyzed to determine if there’s economic feasibility.
• Legal Feasibility Study: Now the company needs to identify all potential regulations, building codes and laws that might affect the project. They’ll need to ask for approval from the local government so that they can begin the construction project .
• Market Feasibility Study: Market feasibility will be determined depending on the nature of the project. For this feasibility example, let’s assume a residential construction project will be built. To gauge market potential, they’ll need to analyze variables such as the average income of the households in the city, crime rate, population density and any trends in state migration.

Manufacturing Feasibility Study

Another industry that uses feasibility studies is manufacturing. It’s a test run of the steps in the manufacturing production cycle to ensure the process is designed properly. Let’s take a look at what a manufacturing feasibility study example would look like.

• Feasibility Study: The first step is to look at various ideas and decide which is the best one to pursue. You don’t want to get started and have to stop. That’s a waste of time, money and effort. Look at what you intend to manufacture, does it fill an unserved need, is the market able to support competition and can you manufacture a quality product on time and within your budget?
• Financial Feasibility Study: Find out if your estimated income from the sale of this product is going to cover your costs, both direct and indirect costs. Work backward from the income you expect to make and the expenses you’ll spend for labor, materials and production to determine if the manufacturing of this product is financially feasible.
• Market Feasibility Study: You’ve already determined that there’s a need that’s not being served, but now it’s time to dig deeper to get realistic projections of revenue. You’ll want to define your target demographic, analyze the competitive landscape, determine the total market volume and what your market share will be and estimate what market expansion opportunities there are.
• Technical Feasibility Study: This is where you’ll explore the production , such as what resources you’ll need to produce your product. These findings will inform your financial feasibility study as well as labor, material, equipment, etc., costs have to be within your budget. You’ll also figure out the processes you’ll use to produce and deliver your product to the market, including warehousing and retail distribution.

There could be other feasibility studies you’ll have to make depending on the product and the market, but these are the essential ones that all manufacturers have to look at before they can make an educated decision as to whether to go forward or abandon the idea.

Best Practices for a Feasibility Study

• Use project management software like ProjectManager to organize your data and work efficiently and effectively
• Use templates or any data and technology that gives you leverage
• Involve the appropriate stakeholders to get their feedback
• Use market research to further your data collection
• Do your homework and ask questions to make sure your data is solid

If your project is feasible, then the real work begins. ProjectManager helps you plan more efficiently. Our online Gantt chart organizes tasks, sets deadlines, adds priority and links dependent tasks to avoid delays. But unlike other Gantt software, we calculate the critical path for you and set a baseline to measure project variance once you move into the execution phase.

Watch a Video on Feasibility Studies

There are many steps and aspects to a project feasibility study. If you want yours to be accurate and forecast correctly whether your project is doable, then you need to have a clear understanding of all its moving parts.

Jennifer Bridges, PMP, is an expert on all aspects of project management and leads this free training video to help you get a firm handle on the subject.

Here’s a screenshot for your reference!

Pro tip: When completing a feasibility study, it’s always good to have a contingency plan that you test to make sure it’s a viable alternative.

ProjectManager Improves Your Feasibility Study

A feasibility study is a project, so get yourself a project management software that can help you execute it. ProjectManager is an award-winning software that can help you manage your feasibility study through every phase.

Once you have a plan for your feasibility study, upload that task list to our software and all your work is populated in our online Gantt chart. Now you can assign tasks to team members, add costs, create timelines, collect all the market research and attach notes at the task level. This gives people a plan to work off of, and a collaborative platform to collect ideas and comments.

If you decide to implement the project, you already have it started in our software, which can now help you monitor and report on its progress. Try it for yourself with this free 30-day trial.

Transcription

Today we’re talking about How to Conduct A Feasibility Study, but first of all, I want to start with clarifying what a feasibility study is.

Feasibility Analysis Definition

Basically, it’s an assessment of the practicality of a proposed plan or method. Basically, we’ll want to want to know, is this feasible. Some of the questions that may generate this or we can hear people asking are, “Do we have or can we create the technology to do this? Do we have the people resource who can produce this and will we get our ROI, our Return On Investment?”

When to Do a Feasibility Study

So when do we do the feasibility study? So it’s done during a project lifecycle and it’s done after the business case because the business case outlines what we’re proposing. Is it a product or service that we’re proposing?

So why do we do this? The reason we do this is that we need to determine the factors that will make the business opportunity a success.

How to Conduct a Feasibility Study

Well, let’s talk about a few steps that we do in order to conduct the feasibility study.

Well, first of all, we conduct a preliminary analysis of what all’s involved in the business case and what we’re analyzing and what we’re trying to determine is feasible.

Then we prepare a projected income statement. We need to know what are the income streams, how are we gonna make money on this. Where’s the revenue coming from? We also need to conduct a market survey.

We need to know, is this a demand? Is there a market for this? Are customers willing to use this product or use this service?

The fourth one is to plan the business organization and operations. What is the structure, what kind of resources do we need? What kind of staffing requirements do we have?

We also want to prepare an opening day balance sheet. What are the…how again, what are the expenses, what’s the revenue and to ensure that being able to determine if we’re gonna make our ROI.

So we want to review and analyze all of the data that we have and with that, we’re going to determine, we’re going to make a go, no-go decision. Meaning, are we going to do this project or this business opportunity or not.

Well, here are some of the best practices to use during your feasibility study.

One is to use templates, tools and surveys that exist today. The great news is, data is becoming more and more prevalent. There are all kinds of technologies. There are groups that they do nothing but research. Things that we can leverage today.

We want to involve the appropriate stakeholders to ensure that input is being considered from the different people involved.

We also want to use again the market research to ensure we’re bringing in good, reliable data.

Do your homework, meaning act like is if this is your project, if it’s your money. So do your homework and do it well and make sure you give credible data.

What Is a Feasibility Report?

So ultimately in the end what we’re doing is, we’re producing and we’re providing a feasibility report. So in that report, think of this is like a template.

So what you’re gonna do is give it an executive summary of the business opportunity that you’re evaluating and the description of the product or the service.

You want to look at different technology considerations. Is it technology that you’re going to use? Are you going to build the technology?

What kind of product and service marketplace and being able again, to identify the specific market you’re going to be targeting? Also, what is the marketing strategy you’re going to use to target the marketplace?

And also what’s the organizational structure? What are the staffing requirements? What people do you need to deliver the product or service and even support it?

So also we want to know the schedule to be able to have the milestones to ensure that as we’re building things, that as we’re spending money that we’re beginning to bring in income to pay and knowing when we’re going to start recuperating some of the funding. Again, which also ties into the financial projections.

Ultimately in this report, you’re going to provide the findings and the recommendations.

Again, we’ll probably talk about technology. Are you going to build it? Are you going to buy it? What are the marketing strategies for the specific marketplace organization? You may have some recommendations for whether you’re going to insource the staff, maybe you are going to outsource some staff and what that looks like and also financial recommendation.

If you’ve been looking for an all-in-one tool that can help with your feasibility study, consider ProjectManager. We offer five project views and countless features that make it seamless to plan projects, organize tasks and stay connected with your team. See what our software can do for you by taking this free 30-day trial.

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Make It So: How to Conduct a Feasibility Study for Better Project Planning

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Reading time: about 7 min

The most successful companies have ambitious goals. Whether you’re launching a new product or delving into a new market, growth requires some level of testing and risk. Sometimes, it means taking on projects or initiatives without knowing exactly how it will come to life or whether it will ultimately benefit the business.

Still, successful business leaders know that time and resources are the most valuable assets for any company. And smart project managers work to make sure both are being maximized for the good of the business. Understanding the feasibility and potential ROI on a project before it ever gets started will not only help you make the most of your time—but maximize your business results. 

Determining feasibility 

This is the initiation stage of the project management lifecycle. At this stage, you determine your objectives, identify your major project deliverables, and decide whether the project can reasonably be completed with good results. This is where a feasibility study comes into play.

What is a feasibility study? 

Simply put, a feasibility study is an assessment of the practicality of a proposed plan or method. Just as the name implies, the study answers the question, “Is this project feasible?” 

To determine this, start by answering the who, what, when, when, and how of your project. Conduct an analysis to determine who needs to be involved in the project , what needs to be done, when it needs to be completed, and how everything will come together to make the project successful. This process of evaluation is at the core of a feasibility study, a common process to complete when results are uncertain and stakes are high.

Feasibility study example: Company A is looking to invest in a new software-as-a-service (SaaS) solution. First, the stakeholders in the investment will analyze what technology or workflow problem the investment will address. The team will also take contractual or subscription costs into account, plus what resources will be required for training and implementation. The study may also need to gauge what kind of change management will be required to gain buy-in. Those conducting the study evaluate all the project data, as well as pros and cons. Finally, they can make an informed decision on whether the investment is a go. 

Types of feasibility studies

There are five types of feasibility studies, each of which provides a different lens to help you evaluate whether your business idea or project is viable: 

1. Economic feasibility

When budgets are at play, it’s important to determine whether the investment will be worth it. Simply put, will your project be profitable? With an economic feasibility study, you run a cost-benefit analysis to determine how much value the project will bring to the business.

2. Technical feasibility

This broad concept can be applied to many types of projects, from software development to construction. Validate the technical resources and capabilities needed to convert the ideas into a working project or system.

3. Operational feasibility

Even the most strategic, well-intentioned projects can go astray if they’re too difficult to bring together, or don’t directly address or solve the problem at hand. An operational analysis helps you understand how well the proposed project will address the problem. 

4. Schedule feasibility

Also referred to as time visibility, this type of feasibility study can help you determine how reasonable the project’s timeline is when measured against existing projects and available resources. Proper evaluation at this step can also help you avoid unpredictable or extra costs. 

5. Legal feasibility

Legal feasibility analysis helps you understand if your proposed plan conforms to legal and ethical requirements. These requirements may include zoning laws, data protection acts, or privacy laws. 

How to conduct a feasibility study

Think about the last time you needed to solve a problem—either at home or at work. If it was a familiar problem, you likely already had a previous experience or game plan to guide your progress. New types of problems or circumstances, however, require new, creative ways of thinking and innovative solutions. 

When determining how to approach a business need, problem, or opportunity, it’s important to determine whether your plan of attack is feasible, and what steps needed to be taken to be successful. But how do you separate a feasible project from a misguided one? 

Here are seven steps to determine if your project is feasible: 

1. Analyze the problem

First, conduct a preliminary analysis of project requirements to assess the practicality and viability of the proposed plan. Do you have the technology and resources required to get the project off the ground? How will you measure and determine the ROI of the project? Understanding your business goals and objectives before you start the project will help keep everyone aligned and working toward the same goal. 

2. Evaluate the budget

The quickest way to derail any new project or initiative is to misuse or waste budget. Especially when budgets are limited, your stakeholders want to know whether the money you spend will make a difference to the bottom line. Determine how much budget you have available for the project—and identify the projected revenue streams. How will this project result in a monetary return on investment?

3. Do your research

Next, take a deeper look at the market. Is there a demand for your product or business plan? For smaller projects, what roadblocks will you face along the way? What are your competitors doing? If your project goals are too narrow, or they don’t align to larger business goals, it might be wise to reevaluate your approach. 

4. Make a plan

Armed with your research, create an action plan to bring your project to life. What resources—people, processes, and tech—will you need to complete the project? A work breakdown structure (WBS) , which breaks down projects into smaller, more manageable pieces that you can reasonably evaluate and assign to teams, can be used to build this plan. 

There are plenty of diagrams available to better manage a project. Similar to a WBS, Program, Evaluation, and Review Technique (PERT) charts and Gantt charts can be used to break projects into smaller more digestible tasks to determine how long each step of the project will take. A PERT chart better illustrates the interdependency between project tasks, while a Gantt chart helps you visualize progress on a project as it’s happening. 

5. Make a balance sheet

Now that you have an actionable plan in hand, it’s time to reevaluate the finances of the project. To do this, bring in financial data to prepare a project kickoff balance sheet. Are you still projecting the same revenue? 

6. Check your data

It’s crunch time. Before you decide whether it makes sense to move forward with the project, take another look at all the data at your fingertips. Objectively, how likely is it that this project will be successful? 

7. Decide what’s next

With all of these evaluations in place, you’ll be able to confidently, objectively, and strategically determine whether the project is feasible. If it’s not, you can build a more thoughtful, strategic plan to run through a feasibility study. If all signs point to “yes,” it’s time to give your project the green light. 

Business moves fast, and for many businesses, it can be tempting to skip evaluation stages in order to get projects done more quickly. Too often, however, this leads to misalignment, derailed projects, duplicative work—or even worse, wasted time and budget. No matter your industry, a feasibility study can help you surface risks and uncertainties and increase your odds of business success. 

About Lucidchart

Lucidchart, a cloud-based intelligent diagramming application, is a core component of Lucid Software's Visual Collaboration Suite. This intuitive, cloud-based solution empowers teams to collaborate in real-time to build flowcharts, mockups, UML diagrams, customer journey maps, and more. Lucidchart propels teams forward to build the future faster. Lucid is proud to serve top businesses around the world, including customers such as Google, GE, and NBC Universal, and 99% of the Fortune 500. Lucid partners with industry leaders, including Google, Atlassian, and Microsoft. Since its founding, Lucid has received numerous awards for its products, business, and workplace culture. For more information, visit lucidchart.com.

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How to use a feasibility study in project management

It can be exciting to run a large, complex project that has a huge potential impact on your organization. On the one hand, you’re driving real change. On the other, failure is intimidating. 

What is a feasibility study? 

A feasibility study—sometimes called a feasibility analysis or feasibility report—is a way to evaluate whether or not a project plan could be successful. A feasibility study evaluates the practicality of your project plan in order to judge whether or not you’re able to move forward with the project. 

It does so by answering two questions: 

Does our team have the required tools or resources to complete this project? 

Will there be a high enough return on investment to make the project worth pursuing? 

Feasibility studies are important for projects that represent significant investments for your business. Projects that also have a large potential impact on your presence in the market may also require a feasibility study. 

As the project manager , you may not be directly responsible for driving the feasibility study, but it’s important to know what these studies are. By understanding the different elements that go into a feasibility study, you can better support the team driving the feasibility study and ensure the best outcome for your project.

When should you conduct a feasibility study

A feasibility study should be conducted after the project has been pitched but before any work has actually started. The study is part of the project planning process. In fact, it’s often done in conjunction with a SWOT analysis or project risk assessment , depending on the specific project. 

Feasibility studies help: 

Confirm market opportunities before committing to a project

Narrow your business alternatives

Create documentation about the benefits and detriments of your proposed initiative

Provide more information before making a go/no go decision

You likely don’t need a feasibility study if:

You already know the project is feasible

You’ve run a similar project in the past

Your competitors are succeeding with a similar initiative in market

The project is small, straightforward, and has minimal long-term business impact

Your team ran a similar feasibility study within the past three years

One thing to keep in mind is that a feasibility study is not a project pitch. During a project pitch, you’re evaluating whether or not the project is a good idea for your company, and whether the goals of the project are in line with your overall strategic plan. Typically, once you’ve established that the project is a good idea, you’d then run a feasibility study to confirm the project is possible with the tools and resources you have at your disposal. 

Feasibility study vs. project charter

A project charter is a relatively informal document to pitch your project to stakeholders. Think of the charter like an elevator pitch of your project objectives, scope, and responsibilities. Typically, your project sponsor or executive stakeholders reviews the charter before ratifying the project. 

A feasibility study should be implemented after the project charter has been ratified. This isn’t a document to pitch whether or not the project is in line with your team’s goals—rather, it’s a way to ensure the project is something you and your team can accomplish. 

Feasibility study vs. business case

A business case is a more formalized version of the project charter. While you’d typically create a project charter for small or straightforward initiatives, you should create a business case if you are pitching a large, complex initiative that will make a major impact on the business. This longer, more formal document will also include financial information, and typically involves more senior stakeholders. 

After your business case is approved by relevant stakeholders, you’d then run a feasibility study to make sure the work is doable. If you find it isn’t, you might return to your executive stakeholders and request more resources, tools, or time in order to ensure your business case is feasible.

Feasibility study vs. business plan

A business plan is a formal document of your organization’s goals. You typically write a business plan when founding your company, or when your business is going through a significant shift. Your business plan informs a lot of other business decisions, including your three to five year strategic plan . 

As you implement your business and strategic plan, you’ll invest in individual projects. A feasibility study is a way to evaluate the practicality of any given individual project or initiative. 

4 elements of a feasibility analysis

There are four main elements that go into a feasibility study: technical feasibility, financial feasibility, market feasibility (or market fit), and operational feasibility. You may also see these referred to as the four types of feasibility studies, though most feasibility studies actually include a review of all four elements. 

Technical feasibility

A technical feasibility study reviews the technical resources available for your project. This study determines if you have the right equipment, enough equipment, and the right technical knowledge to complete your project objectives . For example, if your project plan proposes creating 50,000 products per month, but you can only produce 30,000 products per month in your factories, this project isn’t technically feasible. 

Financial feasibility

Financial feasibility describes whether or not your project is fiscally viable. A financial feasibility report includes a cost/benefit analysis of the project. It also forecasts an expected return on investment (ROI), as well as outlines any financial risks. The goal at the end of the financial feasibility study is to understand the economic benefits the project will drive. 

Market feasibility

The market feasibility study is an evaluation of how your team expects the project’s deliverables to perform in the market. This part of the report includes a market analysis, market competition breakdown, and sales projections. 

Operational feasibility

An operational feasibility study evaluates whether or not your organization is able to complete this project. This includes staffing requirements, organizational structure, and any applicable legal requirements. At the end of the operational feasibility study, your team will have a sense of whether or not you have the resources, skills, and competencies to complete this work. 

Feasibility study checklist

Most feasibility studies are structured in a similar way. These documents serve as an assessment of the practicality of a proposed business idea. Creating a clear feasibility study helps project stakeholders during the decision making process. 

A feasibility study contains: 

An executive summary describing the project’s overall viability

A description of the product or service being developed during this project

Any technical considerations , including technology, equipment, or staffing

The market survey , including a study of the current market and the marketing strategy 

The operational feasibility study , evaluating whether or not your team’s current organizational structure can support this initiative

The project timeline

Financial projections based on your financial feasibility report

6 steps to conduct a feasibility study

You likely won’t be conducting the feasibility study yourself, but you will probably be called on to provide insight and information. To conduct a feasibility study, hire a trained consultant or, if you have an in-house project management office (PMO) , ask if they take on this type of work. In general, here are the steps they’ll take to complete this work: 

1. Run a preliminary analysis

Creating a feasibility study is a time-intensive process. Before diving into the feasibility study, it’s important to evaluate the project for any obvious and insurmountable roadblocks. For example, if the project requires significantly more budget than your organization has available, you likely won’t be able to complete it. Similarly, if the project deliverables need to be live and in market by a certain date, but they won’t be available for several months after the fact, the project likely isn’t feasible either. These types of large-scale obstacles make a feasibility study unnecessary, because it’s clear the project is not viable. 

2. Evaluate financial feasibility

Think of the financial feasibility study as the projected income statement for the project. This part of the feasibility study clarifies the expected project income and outlines what your organization needs to invest—in terms of time and money—in order to hit the project objectives. 

During the financial feasibility study, take into account whether or not the project will impact your business's cash flow. Depending on the complexity of the initiative, your internal PMO or external consultant may want to work with your financial team to run a cost-benefit analysis of the project. 

3. Run a market assessment

The market assessment, or market feasibility study, is a chance to identify the demand in the market. This study offers a sense of expected revenue for the project, and any potential market risks you could run into. 

The market assessment, more than any other part of the feasibility study, is a chance to evaluate whether or not there’s an opportunity in the market. During this study, it’s critical to evaluate your competitor’s positions and analyze demographics to get a sense of how the project will do. 

4. Consider technical and operational feasibility

Even if the financials are looking good and the market is ready, this initiative may not be something your organization can support. To evaluate operational feasibility, consider any staffing or equipment requirements this project needs. What organizational resources—including time, money, and skills—are necessary in order for this project to succeed? 

Depending on the project, it may also be necessary to consider the legal impact of the initiative. For example, if the project involves developing a new patent for your product, you will need to involve your legal team and incorporate that requirement into the project plan. 

5. Review project points of vulnerability

At this stage, your internal PMO team or external consultant have looked at all four elements of your feasibility study—financials, market analysis, technical feasibility, and operational feasibility. Before running their recommendations by you and your stakeholders, they will review and analyze the data for any inconsistencies. This includes ensuring the income statement is in line with your market analysis. Similarly, now that they’ve run a technical feasibility study, are any liabilities too big of a red flag? (If so, create a contingency plan !) 

Depending on the complexity of your project, there won’t always be a clear answer. A feasibility analysis doesn’t provide a black and white decision for a complex problem. Rather, it helps you come to the table with the right questions—and answers—so you can make the best decision for your project and for your team. 

6. Propose a decision

The final step of the feasibility study is an executive summary touching on the main points and proposing a solution. 

Depending on the complexity and scope of the project, your internal PMO or external consultant may share the feasibility study with stakeholders or present it to the group in order to field any questions live. Either way, with the study in hand, your team now has the information you need to make an informed decision. 

Achieve project success with Asana

Done with your feasibility study? You’re ready to run a project! Set your project up for success by tracking your progress in a work management tool , like Asana. From the small stuff to the big picture, Asana organizes work so teams know what to do, why it matters, and how to get it done. 

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• Correspondence
• Open access
• Published: 16 July 2010

What is a pilot or feasibility study? A review of current practice and editorial policy

• Mubashir Arain 1 ,
• Michael J Campbell 1 ,
• Cindy L Cooper 1 &
• Gillian A Lancaster 2  

BMC Medical Research Methodology volume  10 , Article number:  67 ( 2010 ) Cite this article

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In 2004, a review of pilot studies published in seven major medical journals during 2000-01 recommended that the statistical analysis of such studies should be either mainly descriptive or focus on sample size estimation, while results from hypothesis testing must be interpreted with caution. We revisited these journals to see whether the subsequent recommendations have changed the practice of reporting pilot studies. We also conducted a survey to identify the methodological components in registered research studies which are described as 'pilot' or 'feasibility' studies. We extended this survey to grant-awarding bodies and editors of medical journals to discover their policies regarding the function and reporting of pilot studies.

Papers from 2007-08 in seven medical journals were screened to retrieve published pilot studies. Reports of registered and completed studies on the UK Clinical Research Network (UKCRN) Portfolio database were retrieved and scrutinized. Guidance on the conduct and reporting of pilot studies was retrieved from the websites of three grant giving bodies and seven journal editors were canvassed.

54 pilot or feasibility studies published in 2007-8 were found, of which 26 (48%) were pilot studies of interventions and the remainder feasibility studies. The majority incorporated hypothesis-testing (81%), a control arm (69%) and a randomization procedure (62%). Most (81%) pointed towards the need for further research. Only 8 out of 90 pilot studies identified by the earlier review led to subsequent main studies. Twelve studies which were interventional pilot/feasibility studies and which included testing of some component of the research process were identified through the UKCRN Portfolio database. There was no clear distinction in use of the terms 'pilot' and 'feasibility'. Five journal editors replied to our entreaty. In general they were loathe to publish studies described as 'pilot'.

Pilot studies are still poorly reported, with inappropriate emphasis on hypothesis-testing. Authors should be aware of the different requirements of pilot studies, feasibility studies and main studies and report them appropriately. Authors should be explicit as to the purpose of a pilot study. The definitions of feasibility and pilot studies vary and we make proposals here to clarify terminology.

Peer Review reports

A brief definition is that a pilot study is a 'small study for helping to design a further confirmatory study'[ 1 ]. A very useful discussion of exactly what is a pilot study has been given by Thabane et al. [ 2 ] Such kinds of study may have various purposes such as testing study procedures, validity of tools, estimation of the recruitment rate, and estimation of parameters such as the variance of the outcome variable to calculate sample size etc. In pharmacological trials they may be referred to as 'proof of concept' or Phase I or Phase II studies. It has become apparent to us when reviewing research proposals that small studies with all the trappings of a major study, such as randomization and hypothesis testing may be labeled a 'pilot' because they do not have the power to test clinically meaningful hypotheses. The authors of such studies perhaps hope that reviewers will regard a 'pilot' more favourably than a small clinical trial. This lead us to ask when it is legitimate to label a study as a 'pilot' or 'feasibility' study, and what features should be included in these types of studies.

Lancaster et al [ 3 ] conducted a review of seven major medical journals in 2000-1 to produce evidence regarding the components of pilot studies for randomized controlled trials. Their search included both 'pilot' and 'feasibility' studies as keywords. They reported certain recommendations: having clear objectives in a pilot study, inappropriateness of mixing pilot data with main research study, using mainly descriptive statistics obtained and caution regarding the use of hypothesis testing for conclusions. Arnold et al [ 1 ] recently reviewed pilot studies particularly related to critical care medicine by searching the literature from 1997 to 2007. They provided narrative descriptions of some pilot papers particularly those describing critical care medicine procedures. They pointed out that few pilot trials later evolved into subsequent published major trials. They made useful distinctions between: pilot work which is any background research to inform a future study, a pilot study which has specific hypotheses, objectives and methodology and a pilot trial which is a stand-alone pilot study and includes a randomization procedure. They excluded feasibility studies from their consideration.

Thabane et al [ 2 ] gave a checklist of what they think should be included in a pilot study. They included 'feasibility' or 'vanguard' studies but did not distinguish them from pilot studies. They provided a good discussion on how to interpret a pilot study. They stress that not only the outcome or surrogate outcome for the subsequent main study should be described but also that a pilot study should have feasibility outcomes which should be clearly defined and described. Their article was opinion based and not supported by a review of current practice.

The objective of this paper is to provide writers and reviewers of research proposals with evidence from a variety of sources for which components they should expect, and which are unnecessary or unhelpful, in a study which is labeled as a pilot or feasibility study. To do this we repeated Lancaster et al's [ 3 ] review for current papers see if there has been any change in how pilot studies were reported since their study. As many pilot studies are never published we also identified pilot studies which were registered with the UK Clinical Research Network (UKCRN) Portfolio Database. This aims to be a "complete picture of the clinical research which is currently taking place across the UK". All studies included have to have been peer reviewed through a formal independent process. We examined the websites of some grant giving bodies to find their definition of a pilot study and their funding policy toward them. Finally we contacted editors of leading medical journals to discover their policy of accepting studies described as 'pilot' or 'feasibility'.

Literature survey

MEDLINE, Web of Science and university library data bases were searched for the years 2007-8 using the same key words "Pilot" or "Feasibility" as used by Lancaster et al. [ 3 ]. We reviewed the same four general medicine journals: the British Medical Journal (BMJ), Lancet, the New England Journal of Medicine (NEJM) and the Journal of American Medical Association (JAMA) and the same three specialist journals: British Journal of Surgery (BJS), British Journal of Cancer (BJC), British Journal of Obstetrics and Gynecology (BJOG). We excluded review papers. The full text of the relevant papers was obtained. GL reviewed 20 papers and classified them into groups as described in her original paper [ 3 ]. Subsequently MA, in discussion with MC, designed a data extraction form to classify the papers. We changed one category from GL's original paper. We separated the category 'Phase I/II trials' from the 'Piloting new treatment, technique, combination of treatments' category. We then classified the remaining paper into the categories described in Table 1 . The total number of research papers by journal was obtained by searching journal article with abstracts (excluding reviews) using Pubmed. We searched citations to see whether the pilot studies identified by Lancaster et al [ 3 ] eventually led to main trials.

Portfolio database review

The (UKCRN) Portfolio Database was searched for the terms 'feasibility' or 'pilot' in the title or research summary. Duplicate cases and studies classified as 'observational' were omitted. From the remaining studies those classified as 'closed' were selected to exclude studies which may not have started or progressed. Data were extracted directly from the research summary of the database or where that was insufficient the principle investigator was contacted for related publications or study protocols.

Editor and funding agency survey

We wrote to the seven medical journal editors of the same journals used by Lancaster et al. [ 3 ], (BMJ, Lancet, NEJM, JAMA. BJS, BJC and BJOG) and looked at the policies of three funding agencies (British Medical Research Council, Research for Patient Benefit and NETSCC (National Institute for Health Research Trials and Studies Coordinating Centre). We wished to explore whether there was any specified policy of the journal for publishing pilot trials and how the editors defined a pilot study. We also wished to see if there was funding for pilot studies.

Initially 77 papers were found in the target journals for 2007-8 but 23 were review papers or commentaries or indirectly referred to the word "pilot" or "feasibility" and were not actually pilot studies leaving a total of 54 papers. Table 1 shows the results by journal and by type of study and also shows the numbers reported by Lancaster et al. [ 3 ] for 2000-01 in the same medical journals. There was a decrease in the proportion of pilot studies published over the period of time, however the difference was not statistically significant (2.0% vs 1.6%; X 2 = 1.6, P = 0.2). It is noticeable that the Phase I or Phase II studies are largely confined to the cancer journals.

Lancaster et al [ 3 ] found that 50% of pilot studies reported the intention of further work yet we identified only 8 (8.8%) which were followed up by a major study. Of these 2 (25%) were published in the same journal as the pilot.

Twenty-six of the studies found in 2007-8 were described as pilot or feasibility studies for randomized clinical trials (RCTs) including Phase II studies. Table 2 gives the numbers of studies which describe specific components of RCTs. Sample size calculations were performed and reported in 9 (36%) of the studies. Hypothesis testing and performing inferential statistics to report significant results was observed in 21 (81%) of pilot studies. The processes of blinding was observed in only 5 (20%) although the randomization procedure was applied or tested in 16 (62%) studies. Similarly a control group was assigned in most of the studies (n = 18; 69%). As many as 21 (81%) of pilot studies suggested the need for further investigation of the tested drug or procedure and did not report conclusive results on the basis of their pilot data. The median number of participants was 76, inter-quartile range (42, 216).

Of the 54 studies in 2007-8, a total of 20 were described as 'pilot' and 34 were described as 'feasibility' studies. Table 3 contrasts those which were identified by the keyword 'pilot' with those identified by 'feasibility'. Those using 'pilot' were more likely to have a pre-study sample size estimate, to use randomization and to use a control group. In the 'pilot' group 16(80%) suggested further study, in contrast to 15 (44%) in the 'feasibility' group.

A total of 34 studies were identified using the term 'feasibility' or 'pilot' in the title or research summary which were prospective interventional studies and were closed, i.e. not currently running and available for analysis. Only 12 studies were interventional pilot/feasibility studies which included testing of some component of the research process. Of these 5 were referred to as 'feasibility', 6 as 'pilot' and 1 as both 'feasibility' and 'pilot' (Table 4 ).

The methodological components tested within these studies were: estimation of sample size; number of subjects eligible; resources (e.g. cost), time scale; population-related (e.g. exclusion criteria), randomisation process/acceptability; data collection systems/forms; outcome measures; follow-up (response rates, adherence); overall design; whole trial feasibility. In addition to one or more of these, some studies also looked at clinical outcomes including: feasibility/acceptability of intervention; dose, efficacy and safety of intervention.

The results are shown in Table 4 . Pilot studies alone included estimation of sample size for a future bigger study and tested a greater number of components in each study. The majority of the pilots and the feasibility studies ran the whole study 'in miniature' as it would be in the full study, with or without randomization.

As an example of a pilot study consider 'CHOICES: A pilot patient preference randomised controlled trial of admission to a Women's Crisis House compared with psychiatric hospital admissions' http://www.iop.kcl.ac.uk/projects/default.aspx?id=10290 . This study looked at multiple components of a potential bigger study. It aimed to determine the proportion of women unwilling to be randomised, the feasibility of a patient preference RCT design, the outcome and cost measures to determine which outcome measures to use, the recruitment and drop out rates; and to estimate the levels of outcome variability to calculate sample sizes for the main study. It also intended to develop a user focused and designed instrument which is the outcome from the study. The sample size was 70.

The editors of five (out of seven) medical journals responded to our request for information regarding publishing policy for pilot studies. Four of the journals did not have a specified policy about publishing pilot studies and mostly reported that pilot trials cannot be published if the standard is lower than a full clinical trial requirement. The Lancet has started creating space for preliminary phase I trials and set a different standard for preliminary studies. Most of the other journals do not encourage the publication of pilot studies because they consider them less rigorous than main studies. Nevertheless some editors accepted pilot studies for publication by compromising only on the requirement for a pre-study sample size calculation. All other methodological issued were considered as important as for the full trials, such as trial registration, randomization, hypothesis testing, statistical analysis and reporting according to the CONSORT guidelines.

All three funding bodies made a point to note that pilot and feasibility studies would be considered for funding. Thabane et al [ 2 ] provided a list of websites which define pilot or feasibility studies. We considered the NETSCC definition to be most helpful and to most closely mirror what investigators are doing and it is given below.

NETSCC definition of pilot and feasibility studies http://www.netscc.ac.uk/glossary/

Feasibility Studies

Feasibility Studies are pieces of research done before a main study. They are used to estimate important parameters that are needed to design the main study. For instance:

standard deviation of the outcome measure, which is needed in some cases to estimate sample size,

willingness of participants to be randomised,

willingness of clinicians to recruit participants,

number of eligible patients,

characteristics of the proposed outcome measure and in some cases feasibility studies might involve designing a suitable outcome measure,

follow-up rates, response rates to questionnaires, adherence/compliance rates, ICCs in cluster trials, etc.

Feasibility studies for randomised controlled trials may not themselves be randomised. Crucially, feasibility studies do not evaluate the outcome of interest; that is left to the main study.

If a feasibility study is a small randomised controlled trial, it need not have a primary outcome and the usual sort of power calculation is not normally undertaken. Instead the sample size should be adequate to estimate the critical parameters (e.g. recruitment rate) to the necessary degree of precision.

Pilot studies

A Pilot Study is a version of the main study that is run in miniature to test whether the components of the main study can all work together. It is focused on the processes of the main study, for example to ensure recruitment, randomisation, treatment, and follow-up assessments all run smoothly. It will therefore resemble the main study in many respects. In some cases this will be the first phase of the substantive study and data from the pilot phase may contribute to the final analysis; this can be referred to as an internal pilot. Alternatively at the end of the pilot study the data may be analysed and set aside, a so-called external pilot.

In our repeat of Lancaster et al's study [ 3 ] we found that the reporting of pilot studies was still poor. It is generally accepted that small, underpowered clinical trials are unethical [ 4 ]. Thus it is not an excuse to label such a study as a pilot and hope to make it ethical. We have shown that pilot studies have different objectives to RCTs and these should be clearly described. Participants in such studies should be informed that they are in a pilot study and that there may not be a further larger study.

It is helpful to make a more formal distinction between a 'pilot' and a 'feasibility' study. We found that studies labeled 'feasibility' were conducted with more flexible methodology compared to those labeled 'pilot'. For example the term 'feasibility' has been used for large scale studies such as a screening programme applied at a population level to determine the initial feasibility of the programme. On the other hand 'pilot' studies were reported with more rigorous methodological components like sample size estimation, randomization and control group selection than studies labeled 'feasibility'. We found the NETSCC definition to be the most helpful since it distinguishes between these types of study.

In addition it was observed that most of the pilot studies report their results as inconclusive, with the intention of conducting a further, larger study. In contrast, several of the feasibility studies did not admit such an intention. On the basis of their intention one would have expected about 45 of the studies identified by Lancaster et al in 2000/1 to have been followed by a bigger study whereas we only found 8. This would reflect the opinion of most of the journal editors and experts who responded to our survey, who felt that pilot studies rarely act as a precursor for a bigger study. The main reason given was that if the pilot shows significant results then researchers may not find it necessary to conduct the main trial. In addition if the results are unfavorable or the authors find an unfeasible procedure, the main study is less likely to be considered useful. Our limited review of funding bodies was encouraging. Certainly when reviewing grant applications, we have found it helpful to have the results of a pilot study included in the bid. We think that authors of pilots studies should be explicit as to their purpose, e.g. to test a new procedure in preparation for a clinical trial. We also think that authors of proposals for pilot studies should be more explicit as to the criteria which lead to further studies being abandoned, and that this should be an important part of the proposal.

In the Portfolio Database review, only pilot studies cited an intention to estimate sample size calculations for future studies and the majority of pilot studies were full studies run with smaller sample sizes to test out a number of methodological components and clinical outcomes simultaneously. In comparison the feasibility studies tended to focus on fewer methodological components within individual studies. For example, the 6 pilot studies reported the intention to evaluate a total of 17 methodological components whereas in the 5 feasibility studies a total of only 6 methodological components were specifically identified as being under investigation (Table 4 ). However, both pilot and feasibility studies included trials run as complete studies, including randomization, but with sample sizes smaller than would be intended in the full study and the distinction between the two terms was not clear-cut.

Another reason for conducting a pilot study is to provide information to enable a sample size calculation in a subsequent main study. However since pilot studies tend to be small, the results should be interpreted with caution [ 5 ]. Only a small proportion of published pilot studies reported pre-study sample size calculations. Most journal editors reported that a sample size calculation is not a mandatory criterion for publishing pilot studies and suggested that it should not be done.

Some authors suggest that analysis of pilot studies should mainly be descriptive,[ 3 , 6 ] as hypothesis testing requires a powered sample size which is usually not available in pilot studies. In addition, inferential statistics and testing hypothesis for effectiveness require a control arm which may not be present in all pilot studies. However most of the pilot interventional studies in this review contained a control group and the authors performed and reported hypothesis testing for one or more variables. Some tested the effectiveness of an intervention and others just performed statistical testing to discover any important associations in the study variables. Observed practice is not necessarily good practice and we concur with Thabane et al [ 2 ] that any testing of an intervention needs to be reported cautiously.

The views of the journal editors, albeit from a small sample, were not particularly encouraging and reflected the experience of Lancaster et al [ 3 ]. Pilot studies, by their nature, will not produce 'significant' (i.e P < 0.05) results. We believe that publishing the results of well conducted pilot or feasibility studies is important for research, irrespective of outcome.. There is an increasing awareness that publishing only 'significant' results can lead to considerably error [ 7 ]. The journals we considered were all established, paper journals and perhaps the newer electronic journals will be more willing to consider the publication of the results from these types of studies.

We may expect that trials will increasingly be used to evaluate 'complex interventions'[ 8 , 9 ]. The MRC guidelines [ 8 ] explicitly suggest that preliminary studies, including pilots, be used prior to any major trial which seeks to evaluate a package of interventions (such as an educational course), rather than a single intervention (such as a drug). Thus it is likely that reviewers will be increasingly asked to pronounce on these and will require guidance as to how to review them.

Conclusions

We conclude that pilot studies are still poorly reported, with inappropriate emphasis on hypothesis-testing. We believe authors should be aware of the different requirements of pilot studies and feasibility studies and report them appropriately. We found that in practice the definitions of feasibility and pilot studies are not distinct and vary between health research funding bodies and we suggest use of the NETSCC definition to clarify terminology.

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MA reviewed the papers of 2000/1 and those of 2007/8 under the supervision of MC and helped to draft the manuscript. MC conceived of the study, and participated in its design and coordination and drafted the manuscript. CC conducted the portfolio database study and commented on the manuscript. GA conducted the original study, reviewed 20 papers and commented on the manuscript. All authors read and approved the final manuscript.

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Arain, M., Campbell, M.J., Cooper, C.L. et al. What is a pilot or feasibility study? A review of current practice and editorial policy. BMC Med Res Methodol 10 , 67 (2010). https://doi.org/10.1186/1471-2288-10-67

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From Idea to Innovation: What Is a Feasibility Study In Research

Learn the process behind feasibility study in research, how it helps research projects, and the factors that make up a successful project.

Have you ever thought of doing something but wondered whether it’s doable or not? Obviously, there will be several constraints when we wish to do something unique. To understand all these constraints and to check whether the idea that we have in our mind is beneficial or not, we do this preparatory work called a feasibility study.

A feasibility study is like a reality check for your idea, helping you determine if it’s really worth pursuing. In this article, we will discuss what is a feasibility study in research , various aspects of the feasibility study, how it is engaged, how it has to be checked, and how it helps us create a perfect model for our idea.

What is a Feasibility Study in Research? 

A feasibility study is an in-depth assessment conducted to determine the practicality and viability of a proposed project or idea. It involves evaluating various factors such as technical, economic, legal, operational, and scheduling aspects to ascertain whether the project can be successfully implemented.

The purpose of a feasibility study is to provide objective and unbiased information to decision-makers, enabling them to make informed choices regarding the project’s future. It helps identify potential risks, challenges, and opportunities associated with the undertaking, allowing stakeholders to gauge its potential outcomes.

By conducting a feasibility study, decision-makers can determine if the project aligns with organizational goals, identify potential hurdles, and develop contingency plans. This systematic assessment ensures that resources are allocated efficiently and that projects with a high chance of success are pursued.  

What is the Purpose of the Feasibility Study?

A feasibility study serves as a vital tool for assessing the practicality and viability of a proposed project or initiative before committing significant resources to its implementation. It is a comprehensive evaluation that considers various factors such as technical, economic, legal, operational, and scheduling aspects, providing stakeholders with crucial insights to make informed decisions.

First and foremost, a feasibility study helps identify the project’s objectives and determine whether they align with the organization’s overall goals. It allows stakeholders to assess the project’s potential benefits and weigh them against the associated risks. By conducting a feasibility study, decision-makers can gain a clearer understanding of the project’s potential impact on the organization’s resources, capabilities, and market position.

Examination of technical feasibility

One key aspect of a feasibility study is the examination of technical feasibility. This involves evaluating whether the proposed project can be implemented using available technology, infrastructure, and expertise. It helps identify potential technical constraints or challenges that may arise during project execution and allows for appropriate contingency planning.

Furthermore, a feasibility study evaluates the economic viability of a project. It involves conducting a detailed cost-benefit analysis to determine the financial implications associated with the project. This analysis helps stakeholders understand the potential return on investment, project profitability, and the timeline for cost recovery.

Related Article: What is Geospatial Analysis? The Plan Before the Actual Plan

Types of Feasibility Studies

There are several types of feasibility studies, each with its own specific focus and objectives. Some of the most common types of feasibility studies include:

• Technical feasibility study: This type of study assesses whether the proposed project can be implemented using available technology, infrastructure, and expertise. It identifies potential technical constraints or challenges that may arise during project execution and allows for appropriate contingency planning.
• Economic feasibility study: This type of study involves conducting a detailed cost-benefit analysis to determine the financial implications associated with the project. It helps stakeholders understand the potential return on investment, project profitability, and the timeline for cost recovery.
• Legal feasibility study: This type of study examines the legal and regulatory requirements associated with the project. By identifying any legal hurdles or compliance issues early on, organizations can ensure that the project aligns with legal frameworks and minimizes the risk of legal complications down the line.
• Operational feasibility study: This type of study assesses whether the project can be smoothly integrated into existing systems and processes. It examines factors such as staffing requirements, training needs, and potential impacts on day-to-day operations.
• Scheduling feasibility study: This type of study helps establish a realistic timeline for project completion. It considers the availability of resources, dependencies, and potential bottlenecks, allowing stakeholders to develop a well-structured project plan and set achievable milestones.
• Market feasibility study: This type of study evaluates the potential demand for the proposed project in the marketplace. It examines factors such as customer preferences, competition, and market trends to determine whether the project is likely to be successful.
• Environmental feasibility study: This type of study assesses the potential environmental impacts of the proposed project. It examines factors such as air and water quality, habitat destruction, and waste management to ensure that the project is sustainable and environmentally responsible.

Overall, the type of feasibility study conducted will depend on the specific objectives of the proposed project and the information needed to make informed decisions about its implementation.

How to Conduct a Feasibility Study?

A feasibility study is an important step in evaluating the viability of a proposed project or business venture. The study is typically conducted before any significant investment is made to determine whether the project is feasible, both financially and operationally. Here are the general steps to conduct a feasibility study:

Step 1 – Define the scope of the study

Clearly define the objectives of the feasibility study and the specific questions that need to be answered. Identify the stakeholders who will be involved in the study and their roles and responsibilities.

Step 2 – Conduct market research

Research the market and competition to determine the potential demand for the product or service, as well as the size and characteristics of the target market. Analyze the existing competition and identify any gaps in the market that the proposed project could fill.

Step 3 – Evaluate the operational feasibility

Assess the operational feasibility of the proposed project, including the availability of resources, skills, and expertise needed to execute the project.

Step 4 – Identify potential risks

Identify potential risks and challenges that could impact the success of the proposed project. Develop contingency plans to mitigate these risks.

Step 5 – Make recommendations

Based on the results of the feasibility study, make recommendations about whether or not to move forward with the proposed project and, if so, what steps should be taken to ensure its success.

It’s important to note that the specific steps and level of detail required for a feasibility study may vary depending on the nature and complexity of the project. A feasibility study is a critical step in the decision-making process and should be conducted thoroughly and objectively to ensure that all aspects of the proposed project have been evaluated.

How to Write a Feasibility Study?

Writing a feasibility study involves conducting a systematic analysis to determine the viability and potential success of a proposed project or initiative. Here are the steps to help you write a feasibility study: 

• Executive Summary: Provide a brief overview of the project, its objectives, and the purpose of the feasibility study.
• Introduction : Describe the background and context of the project, including its goals, scope, and any relevant background information.
• Project Description: Provide a detailed description of the project, outlining its objectives, deliverables, and expected outcomes. Include information on the target audience or beneficiaries.
• Market Analysis: Assess the market conditions and demand for the proposed project. Identify the target market, competitors, and potential customers. Analyze market trends, growth prospects, and any potential challenges or risks.
• Technical Feasibility: Evaluate the technical aspects of the project, such as the required infrastructure, technology, resources, and expertise. Determine if the necessary resources and capabilities are available or can be acquired within the project’s constraints.
• Financial Feasibility: Conduct a thorough financial analysis of the project. Estimate the initial investment costs, operational expenses, and projected revenues. Evaluate the project’s profitability, return on investment (ROI), payback period, and other financial indicators. Consider potential funding sources and financing options.
• Organizational Feasibility: Assess the project’s compatibility with the existing organizational structure and capabilities. Evaluate the availability of skilled personnel, management support, and any potential impact on the organization’s operations. Consider any legal, regulatory, or compliance requirements.
• Risk Analysis: Identify and evaluate potential risks and uncertainties associated with the project. Analyze both internal and external factors that may impact the project’s success. Develop risk mitigation strategies and contingency plans.
• Implementation Plan: Outline a detailed plan for implementing the project. Define the necessary steps, timelines, and responsibilities. Consider resource allocation, project management methodologies, and any potential challenges during the implementation phase.
• Summarize your findings: Write a clear and concise summary of your findings and conclusions. This should include an assessment of the project’s overall feasibility, a description of any risks or challenges, and a recommendation on whether or not to proceed with the project.

Examples of Feasibility Studies

It typically examines various aspects such as technical, economic, legal, operational, and scheduling factors. Here are some examples of feasibility studies conducted for different purposes: 

• New Business Venture: A study to determine the feasibility of opening a new restaurant, including analysis of market demand, location suitability, competition, and financial projections.
• Real Estate Development: An evaluation of the feasibility of constructing a shopping mall, considering factors such as land availability, market demand, construction costs, potential tenants, and expected return on investment.
• Renewable Energy Project: Assessing the feasibility of establishing a solar power plant, including examination of solar resources, land requirements, grid connectivity, financial analysis, and environmental impact.
• Information Technology System: A study to determine the feasibility of implementing a new software system within an organization, analyzing factors like system requirements, compatibility, cost-benefit analysis, and potential impact on existing operations.

These are some examples of feasibility studies and it is very important to note that though the process looks the same for every domain of work, the concept will be different for each one of them so it is important to analyze the domain before getting to work on it.

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Feasibility Studies: What They Are, How They Are Done, and What We Can Learn From Them

Anne M. Kolenic

Nursing clinical research is a growing field, and as more nurses become engaged in conducting clinical research, feasibility studies may be their first encounter. Understanding what they are, how to conduct them, and the importance of properly reporting their outcomes is vital to the continued advancement of nursing science.

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Many interventions, practices, and processes exist in the nursing field that are grounded in evidence; however, problems that do not appear to be linked to any strong evidence are encountered in daily practice. Nurses are left questioning, “Why do we do it this way?” or “Is there a better way to provide this intervention?” Sometimes these questions may be answered by performing a literature search and realizing that a novel approach exists to implement into their practice; however, if the literature search does not yield any results for an evidence-based practice change, then conducting research could be the next step. Conducting a large, well-designed study can be overwhelming and expensive and may require funding; it also may not be the appropriate first step in the research process (Morris & Rosenbloom, 2017). A feasibility study may be the appropriate first step to help identify whether a larger research study is warranted.

A feasibility study is often a critical step to be taken prior to conducting a larger study. The primary aim of a feasibility study is to assess the feasibility of conducting future conclusive randomized, controlled trials (RCTs) (Eldridge et al., 2016a). Feasibility studies do not have a primary focus on effectiveness or efficacy (Eldridge et al., 2016a); they can be viewed as a dry run to identify problems that may hinder or prevent success of a subsequent larger trial (Conn, Algase, Rawl, Zerwic, & Wyman, 2010). Feasibility studies can demonstrate that a research design is achievable and that recruitment for an anticipated larger study is possible (Morris & Rosenbloom, 2017). They also can supply data that often are required to receive funding and support for a larger RCT to demonstrate that the study approach is feasible and to make a case that the proposed study will answer the question that is being posed (Morris & Rosenbloom, 2017). They also permit testing of sampling strategies, intervention content, delivery methods, data collection, and analysis (Conn et al., 2010). The article “Nurse-Delivered Symptom Assessment for Individuals With Advanced Lung Cancer” (Flannery et al., 2018) provides an example of how a nurse took a clinical question and moved it into the research arena by conducting a feasibility study to assess an intervention strategy.

A feasibility study’s focus is not on efficacy or effectiveness, but the publication of the findings is beneficial and important to the development of science and must follow high standards, just as definitive trials do (Conn et al., 2010; Eldridge et al., 2016a). The Consolidated Standards of Reporting Trials (CONSORT) statement, last updated in 2010, is a guideline designed to improve the transparency and quality of the reporting of RCTs (Eldridge et al., 2016a). Eldridge et al. (2016a) presented an extension to that statement for randomized pilot and feasibility trials conducted in advance of a future definitive RCT. The development was motivated by the increasing number of studies that were described as pilot or feasibility studies and by research that identified weaknesses in the way they were being conducted and in their reporting (Eldridge et al., 2016b). Eldridge et al. (2016b) recognized that, although much of the information to be reported in these trials was similar to RCTs, key differences also were seen, and the CONSORT standards and checklists needed to be adapted to assist in improving the reporting of pilot and feasibility studies (Eldridge et al., 2016a). When conducting and reporting a feasibility study, of importance is that the guidelines, flowchart, and checklists provided in the 2016 extension of the CONSORT 2010 statement are used by the researcher to promote transparency and to improve the quality and standardization of the reporting (Eldridge et al., 2016a).

Many terms are used interchangeably to describe preliminary studies that are done before a larger study, but consensus is growing in the field of research that distinctions among them should be recognized and more consistently used (Morris & Rosenbloom, 2017). The rationale for needing increased consistency in usage is because the way terms are defined determines the necessary components of the study (Eldridge et al., 2016b; Morris & Rosenbloom, 2017). For example, the terms feasibility studies, pilot studies, pilot RCTs, pilot trials, and pilot work are used by many authors to reference a study done in advance of a future definitive RCT and whose primary aim is to assess feasibility (Eldridge et al., 2016b; Morris & Rosenbloom, 2017). This can be confusing when reading and searching the literature. Eldridge et al. (2016b) proposed the following definitions, which may be helpful when reading articles or when a researcher is deciding on which type of study to perform:

•  Feasibility study: Research conducted to determine whether something can or should be done and, if so, how

•  Randomized pilot study: A small-scale feasibility study, conducted with randomization of participants, that evaluates the practicability of carrying out all or part of an intervention and other processes to be undertaken in a future larger study; may or may not include alternative approaches

•  Nonrandomized pilot study: A small-scale feasibility study, conducted without randomization of participants, that evaluates the practicability of carrying out all or part of an intervention—and, possibly, other processes—to be undertaken in a future larger study

•  Feasibility study that is not a pilot study: A feasibility study that does not incorporate the intervention or other processes to be undertaken in a future trial but may address the development of interventions or processes

Regardless of the type of feasibility study that will be done, they all start the same way, with a question or a problem that a clinician has come up with, followed by a literature search. After that, the researcher must identify gaps in knowledge and in the literature, followed by revision and refinement of the original question into a specific research question. Next, the reasons for conducting the preliminary research need to be considered and then the form it should take determined. The focus of feasibility studies can be on any aspect of research, including the following (Morris & Rosenbloom, 2007):

•  Processes: Informed consent procedures, recruitment approaches, nonadherence

•  Resources: Budget allocation, equipment, data collection time, time requirements

•  Management: Data management, ease of data entry, overall study feasibility, and reporting procedures

•  Science: Treatment safety, dose levels and responses, and variance of treatment effect

After the focus and form are decided, the researcher must design the study, collaborate with stakeholders, carry out the study, and analyze the results. Finally, the researcher must relate the findings to plans for a future study and disseminate the findings.

The publication of feasibility studies provides important information to the scientific community. The results of feasibility studies focus on the value of outcomes for subsequent studies rather than on specific findings (Morris & Rosenbloom, 2017). These studies can provide detailed information that often is omitted from reports of large-scale trials because of space considerations, such as changes to the protocol or other modifications that were done because of findings during the pilot (Conn et al., 2010). Often, a larger trial does not happen after the pilot study is completed for one reason or another, so publication of the pilot results may be the only publicly available record that the intervention was tested (Conn et al., 2010). Flannery et al. (2018) reported that although delivering the intervention with fidelity was possible, the feasibility findings did not warrant intervention replication. This is an important finding to report because it will prevent additional researchers from wasting their time and resources testing that same intervention and process. So, even though these findings did not support the plan to conduct a future larger study, they still provide vital information concerning this vulnerable population. This article provides detailed information on how the feasibility study was designed and conducted, allowing future researchers to change the approach and test different interventions and delivery to this population to promote their well-being.

Feasibility studies are extremely important to advance the science of nursing because they allow for the planning of subsequent larger trials. Nurses often think of ideas and solutions to everyday clinical problems and issues but are challenged to move that idea into a full-scale study. Taking that idea or solution and conducting a feasibility study may be a first step into the area of research for many nurses.

About the Author(s)

Anne M. Kolenic, DNP, APRN, AOCNS®, is an ambulatory clinical nurse specialist at the University Hospitals Seidman Cancer Center in Cleveland, OH. No financial relationships to disclose. Kolenic can be reached at [email protected] , with copy to [email protected] .

Conn, V.S., Algase, D.L., Rawl, S.M., Zerwic, J.J., & Wyman, J.F. (2010). Publishing pilot intervention work. Western Journal of Nursing Research, 32, 994–1010. https://doi.org/10.1177/0193945910367229

Eldridge, S.M., Chan, C.L., Campbell, M.J., Bond, C.M., Hopewell, S., Thabane, L., & Lancaster, G.A. (2016a). CONSORT 2010 statement: Extension to randomised pilot and feasibility trials. Pilot and Feasibility Studies, 2, 64.

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• Methodology
• Open access
• Published: 03 February 2021

Determining sample size for progression criteria for pragmatic pilot RCTs: the hypothesis test strikes back!

• M. Lewis   ORCID: orcid.org/0000-0001-5290-7833 1 , 2 ,
• K. Bromley 1 , 2 ,
• C. J. Sutton 3 ,
• G. McCray 1 , 2 ,
• H. L. Myers 2 &
• G. A. Lancaster 1 , 2  

Pilot and Feasibility Studies volume  7 , Article number:  40 ( 2021 ) Cite this article

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The current CONSORT guidelines for reporting pilot trials do not recommend hypothesis testing of clinical outcomes on the basis that a pilot trial is under-powered to detect such differences and this is the aim of the main trial. It states that primary evaluation should focus on descriptive analysis of feasibility/process outcomes (e.g. recruitment, adherence, treatment fidelity). Whilst the argument for not testing clinical outcomes is justifiable, the same does not necessarily apply to feasibility/process outcomes, where differences may be large and detectable with small samples. Moreover, there remains much ambiguity around sample size for pilot trials.

Many pilot trials adopt a ‘traffic light’ system for evaluating progression to the main trial determined by a set of criteria set up a priori. We construct a hypothesis testing approach for binary feasibility outcomes focused around this system that tests against being in the RED zone (unacceptable outcome) based on an expectation of being in the GREEN zone (acceptable outcome) and choose the sample size to give high power to reject being in the RED zone if the GREEN zone holds true. Pilot point estimates falling in the RED zone will be statistically non-significant and in the GREEN zone will be significant; the AMBER zone designates potentially acceptable outcome and statistical tests may be significant or non-significant.

For example, in relation to treatment fidelity, if we assume the upper boundary of the RED zone is 50% and the lower boundary of the GREEN zone is 75% (designating unacceptable and acceptable treatment fidelity, respectively), the sample size required for analysis given 90% power and one-sided 5% alpha would be around n = 34 (intervention group alone). Observed treatment fidelity in the range of 0–17 participants (0–50%) will fall into the RED zone and be statistically non-significant, 18–25 (51–74%) fall into AMBER and may or may not be significant and 26–34 (75–100%) fall into GREEN and will be significant indicating acceptable fidelity.

In general, several key process outcomes are assessed for progression to a main trial; a composite approach would require appraising the rules of progression across all these outcomes. This methodology provides a formal framework for hypothesis testing and sample size indication around process outcome evaluation for pilot RCTs.

Peer Review reports

The importance and need for pilot and feasibility studies is clear: “A well-conducted pilot study, giving a clear list of aims and objectives … will encourage methodological rigour … and will lead to higher quality RCTs” [ 1 ]. The CONSORT extension to external pilot and feasibility trials was published in 2016 [ 2 ] with the following key methodological recommendations: (i) investigate areas of uncertainty about the future definitive RCT; (ii) ensure primary aims/objectives are about feasibility, which should guide the methodology used; (iii) include assessments to address the feasibility objectives which should be the main focus of data collection and analysis; and (iv) build decision processes into the pilot design whether or how to proceed to the main study. Given that many trials incur process problems during implementation—particularly with regard to recruitment [ 3 , 4 , 5 ]—the need for pilot and feasibility studies is evident.

One aspect of pilot and feasibility studies that remains unclear is the required sample size. There is no consensus but recommendations vary from 10 to 12 per group through to 60–75 per group depending on the main objective of the study. Sample size may be based on precision of a feasibility parameter [ 6 , 7 ]; precision of a clinical parameter which may inform main trial sample size—particularly the standard deviation (SD) [ 8 , 9 , 10 , 11 ] but also event rate [ 12 ] and effect size [ 13 , 14 ]; or, to a lesser degree, for clinical scale evaluation [ 9 , 15 ]. Billingham et al. [ 16 ] reported that the median sample size of pilot and feasibility studies is around 30–36 per group but there is wide variation. Herbert et al. [ 17 ] reported that targets within internal as opposed to external pilots are often slightly larger and somewhat different, being based on percentages of the total sample size and timeline rather than any fixed sample requirement.

The need for a clear directive on sample size of studies is of upmost relevance. The CONSORT extension [ 2 ] reports that “Pilot size should be based on feasibility objectives and some rationale given” and states that a “confidence interval approach may be used to calculate and justify the sample size based on key feasibility objective(s)”. Specifically, item 7a (How sample size was determined: Rationale for numbers in the pilot trial) qualifies: “Many pilot trials have key objectives related to estimating rates of acceptance, recruitment, retention, or uptake … for these sorts of objectives, numbers required in the study should ideally be set to ensure a desired degree of precision around the estimated rate”. Item 7b (When applicable, explanation of any interim analyses and stopping guidelines) is generally an uncommon scenario for pilot and feasibility studies and is not given consideration here.

A key aspect of pilot and feasibility studies is to inform progression to the main trial, which has important implications for all key stakeholders (funders, researchers, clinicians and patients). The CONSORT extension [ 2 ] states that “decision processes about how to proceed needs to be built into the pilot design (which might involve formal progression criteria to decide whether to proceed, proceed with amendments, or not to proceed)” and authors should present “if applicable, the pre-specified criteria used to judge whether or how to proceed with a future definitive RCT; … implications for progression from pilot to future definitive RCT, including any proposed amendments”. Avery et al. [ 18 ] published recommendations for internal pilots emphasising a traffic light (stop-amend-go/red-amber-green) approach to progression with focus on process assessment (recruitment, protocol adherence, follow-up) and transparent reporting around the choice of trial design and the decision-making processes for stopping, amending or proceeding to a main trial. The review of Herbert et al. [ 17 ] reported that the use of progression criteria (including recruitment rate) and traffic light stop-amend-go as opposed to simple stop-go is increasing for internal pilot studies.

A common misuse of pilot and feasibility studies has been the application of hypothesis testing for clinical outcomes in small under-powered studies. Arain et al. [ 19 ] claimed that pilot studies were often poorly reported with inappropriate emphasis on hypothesis testing. They reviewed 54 pilot and feasibility studies published in 2007–2008, of which 81% incorporated hypothesis testing of clinical outcomes. Similarly, Leon et al. [ 20 ] stated that a pilot is not a hypothesis testing study: safety, efficacy and effectiveness should not be evaluated. Despite this, hypothesis testing has been commonly performed for clinical effectiveness/efficacy without reasonable justification. Horne et al. [ 21 ] reviewed 31 pilot trials published in physical therapy journals between 2012 and 2015 and found that only 4/31 (13%) carried out a valid sample size calculation on effectiveness/efficacy outcomes but 26/31 (84%) used hypothesis testing. Wilson et al. [ 22 ] acknowledged a number of statistical challenges in assessing potential efficacy of complex interventions in pilot and feasibility studies. The CONSORT extension [ 2 ] re-affirmed many researchers’ views that formal hypothesis testing for effectiveness/efficacy is not recommended in pilot/feasibility studies since they are under-powered to do so. Sim’s commentary [ 23 ] further contests such testing of clinical outcomes stating that treatment effects calculated from pilot or feasibility studies should not be the basis of a sample size calculation for a main trial.

However, when the focus of analysis is on confidence interval estimation for process outcomes, this does not give a definitive basis for acceptance/rejection of progression criteria linked to formal powering. The issue in this regard is that precision focuses on alpha ( α , type I error) without clear consideration of beta (β, type II error) and may therefore not reasonably capture true differences if a study is under-powered. Further, it could be argued that hypothesis testing of feasibility outcomes (as well as addressing both alpha and beta) is justified on the grounds that moderate-to-large differences (‘process-effects’) may be expected rather than small differences that would require large sample numbers. Moore et al. [ 24 ] previously stated that some pilot studies require hypothesis testing to guide decisions about whether larger subsequent studies can be undertaken, giving the following example of how this could be done for feasibility outcomes: asking the question “Is taste of dietary supplement acceptable to at least 95% of the target population?”, they showed that sample sizes of 30, 50 and 70 provide 48%, 78% and 84% power to reject an acceptance rate of 85% or lower if the true acceptance rate is 95% using a 1-sided α = 0.05 binomial test. Schoenfeld [ 25 ] advocates that, even for clinical outcomes, there may be a place for testing at the level of clinical ‘indication’ rather than ‘clinical evidence’. He suggested that preliminary hypothesis testing for efficacy could be conducted with high alpha (up to 0.25), not to provide definitive evidence but as an indication as to whether a larger study should be conducted. Lee et al. [ 14 ] also reported how type 1 error levels other than the traditional 5% could be considered to provide preliminary evidence for efficacy, although they did stop short of recommending doing this by concluding that a confidence interval approach is preferable.

Current recommendations for sample sizes of pilot/feasibility studies vary, have a single rather than a multi-criterion basis, and do not necessarily link directly to formal progression criteria. The purpose of this article is to introduce a simple methodology that allows sample size derivation and formal testing of proposed progression cut-offs, whilst offering suggestions for multi-criterion assessment, thereby giving clear guidance and sign-posting for researchers embarking on a pilot/feasibility study to assess uncertainty in feasibility parameters prior to a main trial. The suggestions within the article do not directly apply to internal pilot studies built into the design of a main trial, but given the similarities to external randomised pilot and feasibility studies, many of the principles outlined here for external pilots might also extend to some degree to internal pilots of randomised and non-randomised studies.

The proposed approach focuses on estimation and hypothesis testing of progression criteria for feasibility outcomes that are potentially modifiable (e.g. recruitment, treatment fidelity/ adherence, level of follow up). Thus, it aligns with the main aims and objectives of pilot and feasibility studies and with the progression stop-amend-go recommendations of Eldridge et al. [ 2 ] and Avery et al. [ 18 ].

Hypothesis concept

Let R UL denote the upper RED zone cut-off and G LL denote the lower GREEN zone cut-off. The concept is to set up hypothesis testing around progression criteria that tests against being in the RED zone (designating unacceptable feasibility—‘ STOP ’) based on an alternative of being in the GREEN zone (designating acceptable feasibility—‘ GO ’). This is analogous to the zero difference (null) and clinically important difference (alternative) in a main superiority trial. Specifically, we are testing against R UL when G LL is hypothesised to be true:

Null hypothesis: True feasibility outcome ( ε ) not greater than the upper “RED” stop limit ( R UL )

Alternative hypothesis: True feasibility outcome ( ε ) is greater than R UL

The test is a 1-tailed test with suggested alpha ( α ) of 0.05 and beta (β) of 0.05, 0.1 or 0.2, dependent on the required strength of evidence of the test. An example of a feasibility outcome might be percentage recruitment uptake.

Progression rules

Let E denote the observed point estimate (ranging from 0 to 1 for proportions, or for percentages 0–100%). Simple 3-tiered progression criteria would follow as:

E ≤ R UL [ P value non-significant ( P ≥ α )] -> RED (unacceptable—STOP)

R UL < E < G LL -> AMBER (potentially acceptable—AMEND)

E ≥ G LL [ P value significant ( P < α )] -> GREEN (acceptable—GO)

Sample size

Table 1 displays a quick look-up grid for sample size across a range of anticipated proportions for R UL and G LL for one-sample one-sided 5% alpha with typical 80% and 90% (as well as 95%) power for the normal approximation method with continuity correction (see Appendix for corresponding mathematical expression; derived from Fleiss et al. [ 26 ]). Table 2 is the same look-up grid relating to the Binomial exact approach with sample sizes derived using G*Power version 3.1.9.7 [ 27 ]. Clearly, as the difference between proportions R UL and G LL increases the sample size requirement is reduced.

Multi-criteria assessment

We recommend that progression for all key feasibility criteria should be considered separately, and hence overall progression would be determined by the worst-performing criterion, e.g. RED if at least one signal is RED, AMBER if none of the signals fall into RED but at least one falls into AMBER and GREEN if all signals fall into the GREEN zone. Hence, the GREEN signal to ‘GO’ across the set of individual criteria will give indication that progression to a main trial can take place without any necessary changes. A signal to ‘STOP’ and not proceed to a main trial is recommended if any of the observed estimates are ‘unacceptably’ low (i.e. fall within the RED zone). Otherwise, where neither ‘GO’ nor ‘STOP’ are signalled, the design of the trial will need amending by indication of subpar performance on one or more of the criteria.

Sample size requirements across multi-criteria will vary according to the designated parameters linked to the progression criteria, which may be set at different stages of the study on different numbers of patients (e.g. those screened, eligible, recruited and randomised, allocated to the intervention arm, total followed up). The overall size needed will be dictated by the requirement to power each of the multi-criteria statistical tests. Since these tests will yield separate conclusions in regard to the decision to ‘STOP’, ‘AMEND’ or ‘GO’ across all individual feasibility criteria there is no need to consider a multiple testing correction with respect to alpha. However, researchers may wish to increase power (and hence, sample size) to ensure adequate power to detect ‘GO’ signals across the collective set of feasibility criteria. For example, powering at 90% across three criteria (assumed independent) will ensure a collective power of 73% (i.e. 0.9 3 ), which may be considered reasonable, but 80% power across five criteria will reduce the power of the combined test to 33%. The final three columns of Table 1 cover the sample sizes required for 95% power, which may address collective multi-criteria assessment when considering keeping a high overall statistical power.

Further expansion of AMBER zone

Within the same sample size framework, the AMBER zone may be further split to indicate whether ‘minor’ or ‘major’ amendments are required according to the significance of the p value. Consider a 2-way split in the AMBER zone denoted by cut-off A C , which indicates the threshold for statistical significance, where an observed estimate below the cut-point will result in a non-significant result and an estimate at or above the cut-point a significant result. Let AMBER R denote the region of Amber zone adjacent to the RED zone between R UL and A C , and AMBER G denote the region of AMBER zone between A C and G LL adjacent to the GREEN zone. This would draw on two possible levels of amendment (‘major’ AMEND and ‘minor’ AMEND) and the re-configured approach would follow as:

R UL < E < G LL and P ≥ α { R UL < E < A c } -> AMBER R (major AMEND)

R UL < E < G LL and P < α { A c ≤ E < G LL } -> AMBER G (minor AMEND)

In Tables 1 and 2 in relation to designated sample sizes for different R UL and G LL and specified α and β, we show the corresponding cut-points for statistical significance ( p < 0.05) both in absolute terms of sample number ( n ) [ A C ] and as a percentage of the total sample sizes [ A C % ].

A motivating example (aligned to the normal approximation approach) is presented in Table 3 , which illustrates a pilot trial with three progression criteria. Table 4 presents the sample size calculations for the example scenario following the 3-tiered approach, and Table 5 gives the sample size calculations for the example scenario using the extended 4-tiered approach. Cut-points for the feasibility outcomes relating to the shown sample sizes are also presented to show RED, AMBER and GREEN zones for each of the three progression criteria.

Overall sample size requirement should be dictated by the multi-criteria approach. This is illustrated in Table 4 where we have three progression criteria each with a different denominator population. For recruitment uptake, the denominator denotes the total number of children screened and the numerator the number of children randomised; for follow-up, the denominator is the number of children randomised with the numerator being number of those randomised who are successfully followed up; and lastly for treatment fidelity, the denominator is the number allocated to the intervention arm with the numerator being the number of children who were administered the treatment correctly by the dietician. In the example in order to meet the individual ≥ 90% power requirement for all three criteria we would need: (i) for recruitment, the number to be screened to be 78; (ii) for treatment fidelity, the number in the intervention arm to be 34; and (iii) for follow up, the number randomised to be 44. In order to determine the overall sample size for the whole study, we base our decision on the criterion that requires the largest numbers, which is the treatment fidelity criterion which requires 68 to be randomised. We cannot base our decision on the 78 required to be screened for recruitment because this would give only an expected number of 28 randomised (i.e. 35% of 78). If we expect 35% recruitment uptake, then we need to inflate the total 68 (randomised) to be 195 (1/0.35 × 68) children to be screened (rounded to 200). This would give 99.9%, 90% and 98.8% power for criteria (i), (ii) and (iii), respectively (assuming 68 of the 200 screened are randomised), giving a very reasonable collective 88.8% power of rejecting the null hypotheses over the three criteria if the alternative hypotheses (for acceptable feasibility outcomes) are true in each case.

Inherent in our approach are the probabilities around sample size, power and hypothesised feasibility parameters. For example, taking the cut-offs from treatment fidelity as a feasibility outcome from Table 4 (ii), we set a lower GREEN zone limit of G LL = 0.75 (“acceptable” (hypothesised alternative value)) and an upper RED zone limit of R UL = 0.5 (“not acceptable” (hypothesised null value)) for rejecting the null for this criterion based on 90% power and a 1-sided 5% significance level (alpha). Figure 1 presents the normal probability density functions for ε , for the null and alternative hypotheses. In the illustration this would imply through normal sampling theory that if G LL holds true (i.e. true recruitment uptake ( ε ) = G LL ) there would be the following:

A probability of 0.1 (type II error probability β) of the estimate falling within RED/AMBER R zones (i.e. blue shaded area under the curve to the left of A C where the test result will be non-significant ( p ≥ 0.05))

Probability of 0.4 of it falling in the AMBER G zone (i.e. area under the curve to the right of A C but below G LL )

Probability of 0.5 of the estimate falling in the GREEN zone (i.e. G LL and above).

Illustration of power using the 1-tailed hypothesis testing against the traffic light signalling approach to pilot progression. E , observed point estimate; R UL , upper limit of RED zone; G LL , lower limit of GREEN zone; Ac , cut-off for statistical significance (at the 1-sided 5% level); α , type I error; β , type II error

If R UL (the null) holds true (i.e. true feasibility outcome ( ε ) = R UL ), there would be the following:

A probability of 0.05 (one-tailed type I error probability α ) of the statistic/estimate falling in the AMBER G /GREEN zones (i.e. pink shaded area under the curve to the right of A C where the test result will be significant ( p < 0.05) as shown within Fig. 1 )

Probability of 0.45 of it falling in the AMBER R zone (i.e. to the left of A C but above R UL )

Probability of 0.5 of the estimate falling in the RED zone (i.e. R UL and below)

Figure 1 also illustrates how changing the sample size affects the sampling distribution and power of the analysis around the set null value (at R UL ) when the hypothesised alternative ( G LL ) is true. The figure emphasises the need for a large enough sample to safeguard against under-powering of the pilot analysis (as shown in the last plot which has a wider bell-shape than the first two plots and where the size of the beta probability is increased).

Figure 2 plots the probabilities of making each type of traffic light decision as functions of the true parameter value (focused on the recruitment uptake example from Table 5 (i)). Additional file 1 presents the R code for reproducing these probabilities and enables readers to insert different parameter values.

Probability of traffic light given true underlying probability of an event using the example from Table 5 (i). Two plots are presented: a relating to normal approximation approach and b relating to binomial exact approach. Based on n = 200, R UL = 40 and G LL = 70

The methodology introduced in this article provides an innovative formal framework and approach to sample size derivation, aligning sample size requirement to progression criteria with the intention of providing greater transparency to the progression process and full engagement with the standard aims and objectives of pilot/feasibility studies. Through the use of both alpha and beta parameters (rather than alpha alone), the method ensures rigour and capacity to address the progression criteria by ensuring there is adequate power to detect an acceptable threshold for moving forward to the main trial. As several key process outcomes are assessed in parallel and in combination, the method embraces a composite multi-criterion approach that appraises signals for progression across all the targeted feasibility measures. The methodology extends beyond the requirement for ‘sample size justification but not necessarily sample size calculation’ [ 28 ].

The focus of the strategy reported here is on process outcomes, which align with the recommended key objectives of primary feasibility evaluation for pilot and feasibility studies [ 2 , 24 ] and necessary targets to address key issues of uncertainty [ 29 ]. The concept of justifying progression is key. Charlesworth et al. [ 30 ] developed a checklist for intended use in decision-making on whether pilot data could be carried forward to a main trial. Our approach builds on this philosophy by introducing a formalised hypothesis test approach to address the key objectives and pilot sample size. Though the suggested sample size derivation focuses around the key process objectives, it may also be the case that other objectives are also important, e.g. assessment of precision of clinical outcome parameters. In this case, researchers may also wish to ensure that the size of the study suitably covers the needs of those evaluations, e.g. to estimate the SD of the intended clinical outcome, then the overall sample size may be boosted to cover this additional objective [ 10 ]. This tallies with the review by Blatch-Jones et al. [ 31 ] who reported that testing recruitment, determining the sample size and numbers available, and the intervention feasibility were the most commonly used targets of pilot evaluations.

Hypothesis testing in pilot studies, particularly in the context of effectiveness/efficacy of clinical outcomes, has been widely criticised due to the improper purpose and lack of statistical power of such evaluations [ 2 , 20 , 21 , 23 ]. Hence, pilot evaluations of clinical outcomes are not expected to include hypothesis testing. Since the main focus is on feasibility the scope of the testing reported here is different and importantly relates back to the recommended objectives of the study whilst also aligning with nominated progression criteria [ 2 ]. Hence, there is clear justification for this approach. Further, for the simple 3-tiered approach hypothesis testing is somewhat hypothetical: there is no need to physically carry out a test since the zonal positioning of the observed sample statistic estimate for the feasibility outcome will determine the decision in regard to progression; thus adding to the simplicity of the approach.

The link between the sample size and need to adequately power the study to detect a meaningful feasibility outcome gives this approach the extra rigour over the confidence interval approach. It is this sample size-power linkage that is key to the determination of the respective probabilities of falling into the different zones and is a fundamental underpinning to the methodological approach. In the same way as for a key clinical outcome in a main trial where the emphasis is not just on alpha but also on beta thereby addressing the capacity to detect a clinically significant difference, similarly, our approach is to ensure there is sufficient capacity to detect a meaningful signal for progression to a main trial if it truly exists. A statistically significant finding in this context will at least provide evidence to reject RED (signifying a decision to STOP) and in the 4-tiered case it would fall above AMBER R (decision to major-AMEND); hence, the estimate will fall into AMBER G or GREEN (signifying a decision to minor-AMEND or GO, respectively). The importance of adequately powering the pilot trial to address a feasibility criterion can be simply illustrated. For example, if we take R UL as 50% and G LL as 75% but with two different sample sizes of n = 25 and n = 50; the former would have 77.5% power of rejecting RED on the basis of a 1-sided 5% alpha level whereas the larger sample size would have 97.8% power of rejecting RED. So, if G LL holds true, there would be 20% higher probability of rejecting the null and being in the AMBER G /GREEN zone for the larger sample giving an increased chance of progressing to the main trial. It will be necessary to carry out the hypothesis test for the extended 4-tier approach if the observed statistic ( E ) falls in the AMBER zone to determine statistical significance or not, which will inform whether the result falls into the ‘minor’ or ‘major’ AMBER sub-zones.

We provide recommended sample sizes within a look-up grid relating to perceived likely progression cut-points to aid quick access and retrievable sample sizes for researchers. For a likely set difference in proportions between hypothesised null and alternative parameters of 0.15 to 0.25 when α = 0.05 and β = 0.1 the corresponding total sample size requirements for the approach of normal approximation with continuity correction take the range of 33 to 100 (median 56) [similarly these are 33–98 (median 54) for the binomial exact method]. Note, for treatment fidelity/adherence/compliance particularly, the marginal difference could be higher, e.g. ≥ 25%, since in most situations we would anticipate and hope to attain a high value for the outcome whilst being prepared to make necessary changes within a wide interval of below par values (and providing the value is not unacceptably low). As this relates to an arm-specific objective (relating to evaluation of the intervention only), then a usual 1:1 pilot will require twice the size; hence, the arm-specific sample size powered for detecting a ≥ 25% difference from the null would be about 34 (or lower)—as depicted from our illustration (Table 4 (ii), equating to n ≤ 68 overall for a 1:1 pilot; intervention and control arms). Hence, we expect that typical pilot sizes of around 30–40 randomised per arm [ 16 ] would likely fit with the proposed methodology within this manuscript (the number needed for screening being extrapolated upward of this figure) but if a smaller marginal difference (e.g. ≤ 15%) is to be tested then these sample sizes may fall short. We stress that the overall required sample size needs to be carefully considered and determined in line with the hypothesis testing approach across all criteria ensuring sufficiently high power. In our paper, we have made recommendations regarding various sample sizes based on both the normal approximation (with continuity correction) and binomial exact approaches; these are conservative compared to the Normal approximation (without continuity correction).

Importantly, the methodology outlines the necessary multi-criterion approach to the evaluation of pilot and feasibility studies. If all progression criteria are performing as well as anticipated (highlighting ‘GO’ according to all criteria), then the recommendation of the pilot/feasibility study is that all criteria meet their desired levels with no need for adjustment and the main trial can proceed without amendment. However, if the worst signal (across all measured criteria) is an AMBER signal, then adjustment will be required against those criteria that fall within that signal. Consequently, there is the possibility that the criteria may need subsequent re-assessment to re-evaluate processes in line with updated performance for the criteria in question. If one or more of the feasibility statistics fall within the RED zone then this signals ‘STOP’ and concludes that a main trial is not feasible based on those criteria. This approach to collectively appraising progression based on the results of all feasibility outcomes assessed against their criteria will be conservative as the power of the collective will be lower than the individual power of the separate tests; hence, it is recommended that the power of the individual tests is set high enough (for example, 90–95%) to ensure the collective power is high enough (e.g. at least 70 or 80%) to detect true ‘GO’ signals across all the feasibility criteria.

In this article, we also expand the possibilities for progression criterion and hypothesis testing where the AMBER zone is sub-divided arbitrarily based on the significance of the p value. This may work well when the AMBER zone has a wide range and is intended to provide a useful and workable indication of the level of amendment (‘minor’ (non-substantive) or ‘major’ (substantive)) required to progress to the main trial. Examples of substantial amendments include study re-design with possible re-appraisal and change of statistical parameters, inclusion of several additional sites, adding further data recruitment methods, significant reconfiguration of exclusions, major change to the method of delivery of trial intervention to ensure enhanced treatment fidelity/adherence, enhanced measures to systematically ensure greater patient compliance with allocated treatment, additional mode(s) of collecting and retrieving data (e.g. use of electronic data collection methods in addition to postal questionnaires). Minor amendments include small changes to the protocol and methodology, e.g. addition of one or two sites for attaining a slightly higher recruitment rate, use of occasional reminders in regard to treatment protocol and adding a further reminder process for boosting follow up. For the most likely parametrisation of α = 0.05/β = 0.1, the AMBER zone division will be roughly at the midpoint. However, researchers can choose this point (the major/minor cut-point) based on decisive arguments around how major and minor amendments would align to the outcome in question. This should be factored within the process of sample size determination for the pilot. In this regard, a smaller sample size will move A C upwards (due to increased standard error/reduced precision) and hence increase the size of the AMBER R zone in relation to AMBER G (whereas a larger sample size will shift A C downwards and do the opposite, increasing the ratio of AMBER G :AMBER R ). From Table 1 , for smaller sample sizes (related to 80% power) the AMBER R zone makes up 56–69% of the total amber zone across presented scenarios, whereas this falls to 47–61% for samples (related to 90% power) and 41–56% for larger samples (related to 95% power) for the same scenarios. Beyond our proposed 4-tier approach, other ways of providing an indication of level of amendment could include evaluation and review of the point and interval estimates or by evaluating posterior probabilities via a Bayesian approach [ 14 , 32 ].

The methodology illustrated here focuses on feasibility outcomes presented as percentages/proportions, which is likely to be the most common form for progression criteria under consideration. However, the steps that have been introduced can be readily adapted to any feasibility outcomes taking a numerical format, e.g. rate of recruitment per month per centre, count of centres taking part in the study. Also, we point out that in the examples presented in the paper (recruitment, treatment fidelity and percent follow-up), high proportions are acceptable and low ones not. This would not be true for, say, adverse events where a reverse scale is required.

Biased sample estimates are a concern as they may result in a wrong decision being made. This systematic error is over-and-above the possibility of an erroneous decision being made on the basis of sampling error; the latter may be reduced through an increased pilot sample size. Any positive bias will inflate/overestimate the feasibility sample estimate in favour of progressing whereas a negative bias will deflate/underestimate it towards the null and stopping. Both are problematic for opposite reasons; for example, the former may inform researchers that the main trial can ‘GO’ ahead when in fact it will struggle to meet key feasibility targets, whereas the latter may caution against progression when in reality the feasibility targets of a main trial would be met. For example, in regard to the choice of centres (and hence practitioners and participants), a common concern is that the selection of feasibility trial centres might not be a fair and representative sample of the ‘population’ of centres to be used for the main trial. It may be that the host centre (likely used in pilot studies) recruits far better than others (positive bias), thus exaggerating the signal to progress and subsequent recruitment to the main trial. Beets et al. [ 33 ] ‘define “risk of generalizability biases” as the degree to which features of the intervention and sample in the pilot study are NOT scalable or generalizable to the next stage of testing in a larger, efficacy/effectiveness trial … whether aspects like who delivers an intervention, to whom it is delivered, or the intensity and duration of the intervention during the pilot study are sustained in the larger, efficacy/effectiveness trial.’ As in other types of studies, safeguards regarding bias should be addressed through appropriate pilot study design and conduct.

Issues relating to progression criteria for internal pilots may be different to those for external pilots and non-randomised feasibility studies. The consequence of a ‘stop’ within an internal pilot may be more serious for stakeholders (researchers, funders, patients) as it would bring an end to the planned continuation into the main trial phase, whereas there would be less at stake for a negative external pilot. By contrast, the consequence of a ‘GO’ signal may work the other way with a clear and immediate gain for the internal pilot whereas for an external pilot, the researchers would still need to apply and get the necessary funding and approvals to undertake an intended main trial. The chances of falling into the different traffic light zones are likely to be quite different between the two designs. Possibly external pilot and feasibility studies are more likely to have estimates falling in and around the RED zone than for internal pilots, reflecting the greater uncertainty in the processes for the former and greater confidence in the mechanisms for trial delivery for the latter. However, to counter this, there are often large challenges with recruitment within internal pilot studies where the target population is usually spread over more diverse sites than may be expected for an external pilot. Despite this possible imbalance, the interpretation of zonal indications remains consistent for external and internal pilot studies. As such, our focus with regard to the recommendations in this article are aligned to requirements for external pilots, though application of this methodology to a degree may similarly hold for internal pilots (and further, to non-randomised studies that can include progression criteria—including longitudinal observational cohorts with the omission of the treatment fidelity criterion).

Conclusions

We propose a novel framework that provides a paradigm shift towards formally testing feasibility progression criteria in pilot and feasibility studies. The outlined approach ensures rigorous and transparent reporting in line with CONSORT recommendations for evaluation of STOP-AMEND-GO criteria and presents clear progression sign-posting which should help decision-making and inform stakeholders. Targeted progression criteria are focused on recommended pilot and feasibility objectives, particularly recruitment uptake, treatment fidelity and participant retention, and these criteria guide the methodology for sample size derivation and statistical testing. This methodology is intended to provide a more definitive and rounded structure to pilot and feasibility design and evaluation than currently exists. Sample size recommendations will be dependent on the nature and cut-points for multiple key pre-defined progression criteria and should ensure a sufficient sample size for other feasibility outcomes such as review of the precision of clinical parameters to better inform main trial size.

Availability of data and materials

Not applicable.

Abbreviations

Significance level (Type I error probability)

AMBER sub-zone split adjacent to the GREEN zone (within 4-tiered approach)

AMBER sub-zone split adjacent to the RED zone (within 4-tiered approach)

AMBER-statistical significance threshold (within the AMBER zone) where an observed estimate below the cut-point will result in a non-significant result (p ≥ 0.05) and figures at or above the cut-point will be significant (p < 0.05)

A C expressed as a percentage of the sample size

Type II error probability

Estimate of feasibility outcome

True feasibility parameter

Lower Limit of GREEN zone

Sample size (n s = number of patients screened; n r = number of patients randomised; n i = number of patients randomised to the intervention arm only)

(1 – Type II error probability)

Upper Limit of RED zone

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Acknowledgements

We thank Professor Julius Sim, Dr Ivonne Solis-Trapala, Dr Elaine Nicholls and Marko Raseta for their feedback on the initial study abstract.

KB was supported by a UK 2017 NIHR Research Methods Fellowship Award (ref RM-FI-2017-08-006).

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ML and CJS conceived the original methodological framework for the paper. ML prepared draft manuscripts. KB and GMcC provided examples and illustrations. All authors contributed to the writing and provided feedback on drafts and steer and suggestions for article updating. All authors read and approved the final manuscript.

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Supplementary Information

Additional file 1..

R codes used for Fig. 2 .

Mathematical formulae for derivation of sample size

The required sample size may be derived using normal approximation to binary response data—using a continuity correction, via Fleiss et al. [ 26 ] if the convention of np > 5 and n ( 1 − p ) > 5 holds true:

where R UL = upper limit of RED zone; G LL = lower limit of GREEN zone; z 1− α = one-sided statistical significance level (type I error probability); z 1−β = beta (type II error probability)

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Lewis, M., Bromley, K., Sutton, C.J. et al. Determining sample size for progression criteria for pragmatic pilot RCTs: the hypothesis test strikes back!. Pilot Feasibility Stud 7 , 40 (2021). https://doi.org/10.1186/s40814-021-00770-x

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A feasibility study testing four hypotheses with phase II outcomes in advanced colorectal cancer (MRC FOCUS3): a model for randomised controlled trials in the era of personalised medicine?

• T S Maughan 1 ,
• A M Meade 2 ,
• R A Adams 3 ,
• S D Richman 4 ,
• R Butler 5 ,
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• R H Wilson 6 ,
• B Jasani 7 ,
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• M T Seymour 8 ,
• L L Nichols 2 ,
• S L Kenny 2 ,
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• C M Sampson 9 ,
• E Hodgkinson 10 ,
• J A Bridgewater 11 ,
• D L Furniss 10 ,
• M J Pope 2   na1 ,
• J K Pope 2   na1 ,
• M Parmar 2 ,
• P Quirke 4 &
• R Kaplan 2  

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This article has been updated

Background:

Molecular characteristics of cancer vary between individuals. In future, most trials will require assessment of biomarkers to allocate patients into enriched populations in which targeted therapies are more likely to be effective. The MRC FOCUS3 trial is a feasibility study to assess key elements in the planning of such studies.

Patients and Methods:

Patients with advanced colorectal cancer were registered from 24 centres between February 2010 and April 2011. With their consent, patients’ tumour samples were analysed for KRAS/BRAF oncogene mutation status and topoisomerase 1 (topo-1) immunohistochemistry. Patients were then classified into one of four molecular strata; within each strata patients were randomised to one of two hypothesis-driven experimental therapies or a common control arm (FOLFIRI chemotherapy). A 4-stage suite of patient information sheets (PISs) was developed to avoid patient overload.

A total of 332 patients were registered, 244 randomised. Among randomised patients, biomarker results were provided within 10 working days (w.d.) in 71%, 15 w.d. in 91% and 20 w.d. in 99%. DNA mutation analysis was 100% concordant between two laboratories. Over 90% of participants reported excellent understanding of all aspects of the trial. In this randomised phase II setting, omission of irinotecan in the low topo-1 group was associated with increased response rate and addition of cetuximab in the KRAS, BRAF wild-type cohort was associated with longer progression-free survival.

Conclusions:

Patient samples can be collected and analysed within workable time frames and with reproducible mutation results. Complex multi-arm designs are acceptable to patients with good PIS. Randomisation within each cohort provides outcome data that can inform clinical practice.

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Fluoropyrimidine type, patient age, tumour sidedness and mutation status as determinants of benefit in patients with metastatic colorectal cancer treated with EGFR monoclonal antibodies: individual patient data pooled analysis of randomised trials from the ARCAD database

Critical evaluation of molecular tumour board outcomes following 2 years of clinical practice in a Comprehensive Cancer Centre

Cancer is the product of a somatic evolutionary process, in which successive advantageous genetic and epigenetic alterations drive the progression of the disease ( Greaves and Maley, 2012 ). Although current knowledge indicates many similar changes in different cancers, the number of possible combinations of changes even within a given anatomical/histological type such as colorectal cancer (CRC) is very large ( The Cancer Genome Network Atlas, 2012 ). This raises a major challenge in the search for effective therapies that target the properties of any given cancer, especially for advanced disease where clonal evolution and the selective pressure of prior therapies drive increasing diversity and resistance to subsequent therapy ( Sequist et al, 2011 ; Gerlinger et al, 2012 ). This emerging understanding of the heterogeneity of cancer is a major challenge to clinical trialists and demands new methodologies for testing novel therapies.

Fundamental to this challenge is the identification of biomarkers that help enrich the evaluated population for benefit from a specific therapy. In CRC, the use of epidermal growth factor receptor (EGFR)-targeted therapy has led to the discovery of the importance of KRAS and recently NRAS mutations ( Douillard et al, 2013 ) in prediction of lack of response to that therapy and association of BRAF mutation with a particularly poor prognosis in advanced CRC (ACRC; Lievre et al, 2006 ; Karapetis et al, 2008 ; Maughan et al, 2011 ). Further biomarker candidates under evaluation as potentially predicting lack of benefit from anti-EGFR therapy are PI3K mutations and loss of PTEN expression ( De Roock et al, 2010 ; Seymour et al, 2013 ).

This paper reports the results of the MRC FOCUS3 trial (ISRCTN83171665), a randomised feasibility trial for the selection of therapy for patients with ACRC based on their KRAS and BRAF mutation status as well as their topoisomerase 1 (topo-1) expression status.

Materials and Methods

Trial design.

Patients were registered on the day they provided written consent for the release of a tumour sample. Upon determination of their biomarker status, patients were allocated to one of four molecular subgroups for randomisation: (1) low topo-1 expression levels and both KRAS and BRAF wild type, (2) low topo-1 and either KRAS- or BRAF -activating mutations, (3) high topo-1 and both KRAS and BRAF wild type and (4) high topo-1 and either KRAS or BRAF mutations. These randomisation subgroups correspond to the prior hypotheses that: (1) in patients with low topo-1 tumours, FU alone is similarly effective and therefore preferable to irinotecan/FU combination ( Braun et al, 2008 ); (2) in patients with KRAS/BRAF wild-type tumours, anti-EGFR therapy improves outcomes ( Van Cutsem et al, 2009 ); (3) in patients with high topo-1 tumours, addition of oxaliplatin to irinotecan/FU improves outcomes ( Braun et al, 2008 ) and (4) in patients with KRAS/BRAF-mutated tumours, anti-VEGF therapy might improve outcomes. There was no specific rationale for a biologically targeted therapy in patients with KRAS mutations; however, there were data suggesting benefit of bevacizumab ( Ince et al, 2005 ).

Patients were randomised centrally by the MRC CTU via telephone using minimisation and allocated in a 1 : 1 : 1 ratio to the control arm (A) common to each of the four subgroups or one of two experimental regimens ( Figures 1 and 2 ). If either molecular test failed, patients could still be randomised in a 1 : 1 ratio based on the results available ( Figure 1 ). Treatment allocation was not masked. Randomisation was stratified by standard clinical prognostic factors.

Trial design.

Diagram in patient information sheet 1 – given to patients to explain the tests carried out on their tumour sample.

Eligibility criteria were age ⩾ 18 years, colorectal adenocarcinoma, inoperable metastatic or locoregional RECIST measurable disease, no previous chemotherapy for metastases, WHO performance status 0–2 and good organ function ( Maughan and Meade, 2010 ). Written informed consent for both molecular testing and randomisation was required.

Outcome measures and sample size

The primary outcome measures for FOCUS3 were process outcomes, namely, in this national multi-site setting, how frequently the target could be met of ⩽ 10 w.d. between the date of registration and: (1) the provision of results to the investigator and (2) randomisation.

The target sample size was 240 patients; if >226 tumour blocks were processed within 10 w.d., we could reliably state that ⩾ 90% samples could be analysed within that time frame. If <206 blocks were processed within 10 w.d., we could reliably exclude a turnaround rate of 90% (i.e., the upper 95% confidence limit would exclude 90%).

Secondary outcome measures included toxicity, response rates (RRs) and progression-free survival (PFS) of the different regimens within each molecular subgroup; reproducibility of biomarker results and attitudes of patients to the study design, the consent process and refusal rates for trial entry.

Informed consent and patients attitudes to the trial design

A staged set of patient information sheets (PISs) was developed with input from patients, carers and nursing staff: PIS 1 explained the need for further analyses of tumour tissue using a very simple diagram and no technical details (see Figure 2 ), PIS2, given to patients before results of their molecular tests were known, covered the general issues of a three arm RCT and treatment side-effects. PIS3, in four specific versions a–d, describing the three arm randomisation for each of the four molecular sub-types (1–4) was given to patients before randomisation. PIS4, versions a–e, contained full details of the five treatment regimens (A–E).

Patient understanding of the information was captured on a questionnaire delivered immediately following their reading of the stage 2 PIS.

Attitudes of participants to trial entry, understanding and experience, particularly to the proposed 2 weeks time for tumour testing before treatment allocation, were evaluated by one-to-one semi-structured interviews using interpretative phenomenological analysis in a subgroup of randomised patients ( Smith and Osborn, 2003 ).

Sample collection and analysis process

The clinical research nurse (CRN) at the recruiting hospital requested the patients’ diagnostic FFPE block. Histopathology agreements were in place between MRC and all diagnostic hospitals outlining the trial rationale and stressing the importance of sending blocks promptly to the central laboratories. The MRC CTU team actively tracked samples throughout the biomarker analysis process. Upon reconfirmation of eligibility, and with their consent, patients were randomised.

Biomarker analysis

Analysis of DNA extracted from macro-dissected FFPE sections of KRAS codons 12, 13 and 61 and BRAF codon 600 was each performed by Pyrosequencing (details in Supplementary Appendix ).

Topo-1 protein expression was identified using a topo-1 antibody (NCL-TOPO1; Leica, Wetzlar, Germany; details in Supplementary Appendix ). Each case was scored on the basis of the percentage of positive tumour cells (<10% scored low, >10% high).

Quality assurance of biomarker analysis

Fifty samples were blinded and exchanged between the two laboratories before the trial and analysed for KRAS and BRAF mutation status. Throughout the trial both laboratories took part in external quality assessment (UK NEQAS) for KRAS . Topo-1 IHC was compared between laboratories.

Interventions and assessments

The five treatment regimens were all based on the 2-weekly FOLFIRI regimen – folinic acid and irinotecan followed by bolus and infusional 5-fluouracil (5-FU; Douillard et al, 2000 ): (A) Control: FOLFIRI, (B) omits irinotecan: LV5FU2, (C) adds oxaliplatin: FOLFOXIRI (FOLFIRI and oxaliplatin), (D) FOLFIRI plus cetuximab and (E) FOLFIRI plus bevacizumab. Doses in (C) were dependent on patient age and WHO performance status. The chemotherapy regimens FOLFIRI and LV5FU2 are internationally recognised acronyms. The actual regimens used in FOCUS3 were established in the UK ( Cheeseman et al, 2002 ; Leonard et al, 2002 ). They have been used in large numbers of patients, have been shown to be both efficacious and safe ( Seymour et al, 2007 ) and will be referred to as FOLFIRI and LV5FU2 in this paper. The FOLFIRI regimen consisted of an IV infusion of 180 mg m −2 IV infusion over 30 min followed by 350 mg IV infusion d,l-folinic acid or 175 mg l-folinic acid over 2 h. A 400 mg m −2 IV bolus injection of 5-FU was then administered over 5 min followed by 2400 mg m −2 5-flurouracil IV infusion over 46 h. For the LV5FU2 regimen, irinotecan was omitted and the 5-fluourouracil IV infusion dose was increased to 2800 mg m −2 . There were three different FOLFOXIRI regimens, which were prescribed based on the patient’s age and WHO PS status. The regimen for patients aged 70 years or less and with PS=0–1 contained 180 mg m −2 irinotecan and 85 mg m −2 oxaliplatin, 400 mg m −2 5-fluorouracil bolus and 2400 mg m −2 5-fluorouracil infusion. The individual components were reduced to 80% of full dose for patients ⩾ 70 years or PS=2 and to 60% for patients ⩾ 70 years and PS=2. In arm D, cetuximab was administered before chemotherapy as an IV dose of 500 mg m −2 , whereas in arm E bevacizumab was administered first as a 5 mg kg −1 IV infusion. All of the regimens are described in detail in the FOCUS 3 protocol ( Maughan and Meade, 2010 ).

If molecular results were not confirmed by 2 weeks, patients could have one cycle of LV5FU2 before randomisation. Treatment continued for at least 24 weeks or until disease progression on treatment.

Patient symptoms were scored using National Cancer Institute Common Toxicity Criteria for Adverse Events version 3.0. SAEs and deaths, together with an assessment of causality, were continuously reported; and were reassessed by an experienced oncologist on behalf of the MRC.

CT scans were performed within 5 weeks before the start of treatment and then 12 weekly on treatment and evaluated using RECIST (v1.1) criteria. Responses were not confirmed by repeat scans and external radiological review was not undertaken.

Statistical methods

Analyses were conducted according to a predefined statistical analysis plan, which was approved by the FOCUS3 TMG before database lock (first analysed in August 2011, data updated for final analysis in May 2012).

For each of the co-primary process outcomes, an exact binomial 95% confidence interval was calculated around the result. Exploratory analyses of the efficacy end points were planned in relation to the four hypotheses stated above (Trial Design), which in each case involved factorial analysis of two relevant molecular subgroups, as illustrated in Figure 1 . Time-to-event curves for analysis of PFS were estimated using the Kaplan–Meier method. All statistical analyses were carried out using Stata version 12 (StataCorp, College Station, TX, USA).

Between February 2010 and April 2011, 332 patients from 24 centres in the UK were registered for the FOCUS3 trial.

Topo-1 status was determined in 306 patients (92%) and was highly expressed (2–3) in 244 (73%). KRAS and BRAF status were determined in 319 patients (96%), of whom 117 (37%) had a KRAS mutation alone, 25 (8%) BRAF mutation alone, 1 (<1%) both mutations, 169 (53%) were double wild type and 7 (2%) had a BRAF mutation but inconclusive KRAS status. No association was seen between topo-1 expression and KRAS / BRAF mutation status ( Table 1 ).

Of patients registered, 288 were eligible for randomisation, and ultimately 244 (85%) were randomised. The reasons why patients were not randomised are described in Figure 3 (Consort Diagram). The main baseline characteristics and treatment allocation of all randomised patients are shown in Table 2 (and in Supplementary Tables 1 and 2 ) and Figure 3 . The distribution of KRAS/BRAF and Topo-1 status both at registration and randomisation is shown in Table 1 .

CONSORT diagram.

Primary process outcomes

The two co-primary process outcome measures were not met. Of those patients randomised 180 (74%) had their biomarker results within 10 w.d. of registration (95% CI=68%, 79%). However, the results for 225 patients (92%) were available to investigators within 15 w.d. of randomisation (95% CI=88%, 95%). The interval between registration and randomisation was less than or equal to 10 w.d. in only 70 (29%) patients (95% CI=23%, 35%), which suggests delays due to clinical issues (such as visit scheduling after results were available) had a greater impact on timelines than delays in biomarker analysis ( Supplementary Table 3 ).

Reproducibility of biomarker results

100% concordance was achieved in the DNA mutation analysis results obtained between the two reference laboratories. Initial crossing over of topo-1 samples between the laboratories produced consistent results, although there were a higher proportion of ‘high’ expressing tumours than was observed in FOCUS. The Cardiff centre was not able to fully adopt the previously validated Leeds laboratory topo-1 protocol, and early in the trial it was realised that the protocols adopted at the two centres were not giving uniformly consistent results required for trial purposes. All subsequent sample testing for KRAS , BRAF and topo-1 was therefore performed at Leeds.

Patient understanding

In all, 90–95% of participants self-reported that they either fully or mostly understood all of the aspects of the trial, see Figure 4 . The areas that were least well understood were the need to wait 2 weeks before start of treatment, how treatment was allocated and what happens during treatment.

Patient understanding of the consent process. Q1: Understanding of PIS2. Q2: Understanding why tumour was tested. Q3: Understanding of different treatments. Q4: Understanding of why you had to wait 2 weeks. Q5: Understanding of how treatment was allocated. Q6: Understanding of what happens during treatment. Q7: Understanding of request to give blood, complete questionnaire, take part in an interview.

Qualitative research

In-depth, interviews with 14 randomised patients were analysed using interpretative phenomenological analysis and will be published in full elsewhere. The dominant issue for the majority of participants was that they were discussing the trial immediately following diagnosis of ACRC. This was a greater concern than trial entry itself. Two of the fourteen interviewees experienced delays with results from tumour testing, causing significant distress. The majority of patients expressed no concern with tumour testing times but highlighted distress caused by prior delays during diagnosis and treatment.

Relationships with family were key to ongoing practical and emotional support and particularly relevant to the decision to enrol on the trial and the processing of information. The multiple roles of the CRN emerged in relation to recruitment and the ongoing care of participants in the trial. Reasons for enrolling in FOCUS3 related to altruism, perception of the trial as offering personalised treatment and better care, finding a cure for cancer and being the only option available.

Treatment and follow-up

Of the 244 randomised patients, 4 did not commence treatment—2 from arm A and 2 from arm E. Of the remaining 240, two patients (0.8%) received a single initial cycle of LV5FU2 alone before commencing their allocated regimens. Full-dose FOLFOXIRI was initiated in the 86% of patients with high topo-1 who were <70 and PFS 0–1; the remainder commenced at lower doses as per protocol. The median number of cycles of treatment delivered was 12 (IQR=7–13).

Efficacy outcomes

Efficacy outcomes were assessed in May 2012 when the median duration of follow-up was 15.2 months (IQR=12.6–18.8 months).

In patients with low topo-1 (B vs A, n =30), 12-week RR was 60% with LV5FU2 alone and 47% with FOLFIRI, supporting the original hypothesis that irinotecan does not add benefit in this group. There was no evidence of a difference in PFS.

There was no improvement in RR (40% vs 45%) or in PFS (HR=1.08 (0.67–1.76)) with the addition of oxaliplatin ( n =127) to FOLFIRI (C vs A). The complex randomisation algorithm resulted in a gender imbalance with more males in this group, which has uncertain relevance.

In patients with KRAS and BRAF wild type (D vs A, n =92), the addition of cetuximab to FOLFIRI was associated with an increased RR (44% vs 66%) and PFS (HR=0.44 (0.23–0.82)), consistent with the results of the phase III Crystal trial ( Van Cutsem et al, 2009 , 2011 ).

For the addition of bevacizumab to FOLFIRI in patients with KRAS or BRAF mutations (E vs A, n =72), there was an observed increased RR (47% vs 33%). No PFS benefits were observed.

Kaplan–Meier survival curves are presented in Figure 5 and 12-week RR data are summarised in Table 3 .

Treatment comparisons – progression-free survival.

Toxicity observed was as expected for the LV5FU2, FOLFIRI, FOLFIRI+cetuximab and FOLFIRI+bevacizumab regimens. The anticipated increased toxicity of the FOLFOXIRI regimen was minimal, with only 27% grade 3+ neutropenia. This may be due to the reduced dosing schedule in the elderly/less fit patients ( n =9 of 127) previously described ( Supplementary Table 4 ).

The primary objective of FOCUS3 was to assess the feasibility of undertaking a complex biomarker-driven trial in a national multicentre setting. Although the study did not meet either of its ambitious pre-specified co-primary process outcome measures, the trial has shown that complex prospective biomarker-driven RCTs are possible on a substantial scale across the United Kingdom. Extra resources are required in the reference pathology laboratories to undertake the biomarker analyses, but within investigator sites and the trials office there is no requirement for special dedicated staff.

Potentially eligible patients were necessarily approached for consent at precisely the time when they had recently learned of the life-threatening status of their disease; our qualitative research showed this was the dominating concern in their minds. That we achieved our target patient number from 24 centres in 1 year demonstrated that the strategy for explaining the trial was successful and that, even under difficult circumstances, complex trials can be attractive to patients. Our four-step consent procedure was developed in consultation with patients and carers and was praised by the research ethics committee. The responses to the questionnaire administered after patients had read their stage 2 PIS showed high levels of understanding of the trial. The subsequent steps in the consent process, with specific patient consent forms for each molecular cohort and for each treatment, avoided information overload and provided only that information that was specifically relevant to the particular patient.

The logistics of retrieval of the FFPE blocks from the diagnostic hospitals was a major concern. Prior written agreement, a modest (£15) fee for retrieval and detailed sample tracking by CTU personnel minimised delay. The critical lessons were the need for excellent communication between all parties in the chain: from CRN to pathologist to the central laboratories to the coordinating trials unit.

A delay in reporting analysis results back to the MRC CTU was observed in 22 cases and was distressing to some patients. The delays were due to insufficient tumour in the block ( n =4), unexpected technical difficulties ( n =6), initial testing inconclusive or failed ( n =12). This was mitigated by allowing patients ( n =2) to start cycle one of chemotherapy using the infusional 5-FU and folinic acid backbone, which was common to all treatment protocols and then adding in the relevant additional agents for cycle 2 once the biomarker results were available.

Overall, the most important laboratory issue was reproducibility of IHC results. Although 100% concordance was achieved in the calling of KRAS and BRAF mutations between the two laboratories, it proved very difficult to perform and report the topo-1 IHC staining intensity in a sufficiently comparable way. Owing to technical- and manpower-based organisational limitations, it was not possible to completely replicate the manual staining methodology adopted initially by the Leeds laboratory in the Cardiff laboratory where an automated staining platform was used. Even what were deemed inconsequential differences between staining protocols contributed to this lack of consistency. For future studies, contributing diagnostic centres will use the same antibodies, protocol and automated staining platform. Detailed guidance on scoring, blinded replication in contributing centres with face to face comparison of discrepantly scored sections have been implemented for IHC tests in FOCUS4. On trial quality assurance by double reading of slides will ensure comparability of evaluation.

This trial was structured so that we could address four distinct hypotheses, any or all of which might be the subject of a subsequent phase III trial. Our first hypothesis, arising from the observation in the earlier FOCUS trial that patients with low topo-1 expression appear to gain no benefit from the addition of irinotecan to LV5FU2 ( Seymour et al, 2007 ; Braun et al, 2008 ), was supported and remains an intriguing one. Only 30 patients were randomised to this comparison because of the lower than expected rate of low topo-1 expression, but the high RR (60%) in the LV5FU2 only treated patients suggests further work in this area might be rewarding.

The second hypothesis proposed that patients with high topo-1 expression, who alone in FOCUS gained benefit from either irinotecan or oxaliplatin in comparison to 5-FU ( Braun et al, 2008 ), may derive additional benefit from the triple chemotherapy regimen. With the protocol-specified dose reductions, the regimen was well tolerated. However, in contrast to the international literature ( Falcone et al, 2007 , 2013 ), although patients had a minimally higher RR, there was no hint of a PFS benefit.

The third hypothesis, tested in 92 patients with KRAS and BRAF wild-type tumours, was that the addition of cetuximab would increase efficacy. This recapitulated the Crystal study ( Van Cutsem et al, 2009 , 2011 ) and benefits in PFS and RR were observed.

Finally, our fourth hypothesis for patients with KRAS or BRAF mutations (72 patients) was based on the limited data that bevacizumab retains efficacy in these patients ( Ince et al, 2005 ). No benefits on either RR or PFS were observed.

The FOCUS4 trial programme ( Kaplan et al, 2013 ) has recently opened to recruitment building on many of the lessons learned in FOCUS3. Patient and clinician enthusiasm for biomarker-stratified trials and the rapid accrual observed in FOCUS3 have encouraged us to be optimistic in our predicted recruitment targets: 2400 registered patients with over 1500 randomised into multiple biomarker-directed comparisons in 4 years for FOCUS4. Staged PISs have been designed with information given at the time of registration limited to that which is necessary for consent for release of tumour blocks, plus a minimal outline of the protocol so as to avoid information overload. Detailed quality assurance work has been undertaken between the two biomarker reference laboratories, especially for the IHC tests (PTEN and mismatch repair proteins). In FOCUS4, the allocation by biomarker to specific comparisons occurs for patients with stable or responding disease after 4 months of first-line chemotherapy. Knowing that in FOCUS3 we completed biomarker analysis in 99% of patients within 20 w.d. of consent, the FOCUS4 logistics (registration of patients up to 12 weeks into their first-line chemotherapy) should facilitate accrual. Detailed engagement with pathologists in referring hospitals and a relatively small (£15) payment per case enabled rapid release of blocks for central analysis in FOCUS3 and the same pattern has been used in FOCUS4. Perhaps most important is the strength of the team working established through FOCUS3, including patient representatives, clinicians, biomarker experts (including histopathologists, immunohistochemists, geneticists and technicians), statisticians, research nurses, pharmacists, trial managers and data managers. To this, we have added research network managers to ensure improved patient transfers between district general hospitals and experimental cancer medicine centres, who are required in FOCUS4 for some patients randomised to the novel agent combinations being studied.

The FOCUS3 trial was a feasibility study designed to address the challenges of patient acceptability, technical logistics, and to test a novel design for examining the predictive role of biomarkers for first-line therapy of ACRC. We have shown that such studies are feasible and very well received by participants. The central trial design concepts have been taken forward into a major UK trial programme FOCUS4-molecular selection of therapy in CRC: a molecularly stratified RCT programme, which opened to accrual in January 2014 ( Kaplan et al, 2013 ).

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Acknowledgements

We are indebted to the 332 patients and their families who participated in FOCUS3.

The design of the Medical Research Council (MRC) FOCUS3 trial was conceived and developed by the National Cancer Research Institute (NCRI) advanced colorectal cancer group. The trial was funded by the MRC. Additional support was provided by Merck KGaA (free cetuximab), Pfizer and Roche (educational research grants for the MRC colorectal research portfolio). The topo-1 antibody was provided free from Leica. Laboratory work in Leeds was also supported by funding from Yorkshire Cancer Research and the Leeds Experimental Cancer Medicines Centre. All tumour samples from patients who consented for future CRC research are stored at the Wales Cancer Bank.

The MRC was the overall sponsor of the study. FOCUS3 was approved by the Medicines and Healthcare Regulatory Agency (MHRA) on 12 June 2009 and Research Ethics Committee for Wales on 26 May 2009. The trial was coordinated by the MRC Clinical Trials Unit (CTU) following the principles of GCP, conducted with a Trial Management Group (TMG), monitored by a Data Monitoring Committee (DMC) and overseen by an independent Trial Steering Committee. Data collection at UK sites was supported by staff funding from the National Cancer Research Networks. All statistical analyses were performed at the MRC CTU. The trial is registered as an International Standard Randomised Controlled trial, number ISRCTN83171665.

Trial Management Group : TS Maughan (chair), R Adams, RH Wilson, MT Seymour, B Jasani, R Butler, S Richman, P Quirke, AM Nelson, GT Williams, G Taylor, H Grabsch, I Frayling, J Sampson, E Hodgkinson, P Rogers, M Pope and MRC CTU staff.

MRC Clinical Trials Unit: AM Meade, R Kaplan, D Fisher, SL Kenny, JK Mitchell, LL Nichols, L Harper, K Letchemanan, M Parmar.

Data Monitoring Committee: AM Meade, R Kaplan, D Fisher, TS Maughan, MT Seymour.

Trial Steering Committee: C Parker (current chair), R Rudd, J Whelan.

Sponsor: Medical Research Council.

Clinical Investigators (Institution—(number of patients contributed)): Bridgewater J, King J, Aggarwal A, Harinarayanan S, Melcher L, Karp Stephen (North Middlesex Hospital (32)), Furniss D, Wadsley J, Walkington L, Simmons T, Hornbuckle J, Pledge S, Clenton S (Weston Park Hospital (30)), Roy R, Dhadda A (Castle Hill Hospital (26)), Adams R, Maughan T, Jones R, Brewster A, Iqbal N, Arif, Crosby T (Velindre Hospital (23)), Falk S, Garadi K, Hopkins K (Bristol Haematology and Oncology Centre (18)), Seymour M, Swinson D, Anthoney A, (St James’ University Hospital, Leeds (18)), Leonard P, Mohamed M, (Whittington Hospital (14)), Benstead K, Farrugia D, Shepherd S (Cheltenham General Hospital (11)), Blesing C, Hyde K, Grant W (Great Western Hospital (10)), Lowdell C, Cleator S, Riddle P, Kenny L, Ahmad R (Charing Cross Hospital (9)), Hill M, Bhattacharjee P, Sevitt T, Summers J, Shah R (Maidstone Hospital (9)), Whillis D, Nicholls A, Ireland H, Macgregor C (Raigmore Hospital (8)), Sizer B, Basu D (Essex County Hospital (7)), Dent J, Hofmann U (Huddersfield Royal Infirmary (6)), Roy R, Butt M, Iqbal M (Diana, Princess of Wales Hospital (6)), Dent J (Calderdale Royal Hospital (6)), Hickish T, Osborne R (Poole Hospital (3)), Hickish T, Astras G, Purandare L (Royal Bournemouth Hospital (2)), Tahir S, Srinivasan G (Broomfield Hospital (2)), Gollins S, Kodavatiganti R (Wrexham Maelor Hospital (2)), Bale C, Mullard A, Fuller C, Williams R, Stuart N (Ysbyty Gwynedd (1)), Gollins S, Neupane R (Glan Clwyd Hospital (1)), Bessell E, Potter V (Nottingham University Hospital (0)), Tsang D (Southend University Hospital (0)).

In addition to the above-named individuals, we acknowledge the contributions of a large number of clinicians, research nurses, data managers and other clinical and support staff at the participating centres.

Author information

M J Pope and J K Pope: Malcolm and Janet Pope are Consumer Representatives; they also represent Velindre Hospital, Patient Liaison Group, Cardiff CF14 2TL, UK

Authors and Affiliations

CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford OX3 7DQ, UK

T S Maughan

MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, WC2B 6NH, UK

A M Meade, D Fisher, L L Nichols, S L Kenny, M J Pope, J K Pope, M Parmar & R Kaplan

Cardiff University and Velindre Cancer Centre, Cardiff, UK

Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK

S D Richman, G R Taylor & P Quirke

University Hospital of Wales, Cardiff, CF14 4XW, UK

Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast, BT9 7AE, UK

Institute of Cancer and Genetics, Cardiff University, Cardiff, CF14 4XN, UK

B Jasani, G T Williams & J R Sampson

St James’s Institute of Oncology, University of Leeds, Leeds, LS9 7TF, UK

M T Seymour

Wales Cancer Trials Unit, Cardiff University, Cardiff, CF14 4YS, UK

A Nelson & C M Sampson

Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, S5 7AU, UK

E Hodgkinson & D L Furniss

UCL Cancer Institute, London, WC1E 6BT, UK

J A Bridgewater

Department of Oncology, Castle Hill Hospital, East Riding of Yorkshire, HU16 5JQ, UK

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Correspondence to A M Meade .

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Maughan, T., Meade, A., Adams, R. et al. A feasibility study testing four hypotheses with phase II outcomes in advanced colorectal cancer (MRC FOCUS3): a model for randomised controlled trials in the era of personalised medicine?. Br J Cancer 110 , 2178–2186 (2014). https://doi.org/10.1038/bjc.2014.182

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Accepted : 13 March 2014

Published : 17 April 2014

Issue Date : 29 April 2014

DOI : https://doi.org/10.1038/bjc.2014.182

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A feasibility study testing four hypotheses with phase II outcomes in advanced colorectal cancer (MRC FOCUS3): a model for randomised controlled trials in the era of personalised medicine?

Affiliations.

• 1 CRUK/MRC Oxford Institute for Radiation Oncology, University of Oxford, Oxford OX3 7DQ, UK.
• 2 MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London WC2B 6NH, UK.
• 3 Cardiff University and Velindre Cancer Centre, Cardiff, UK.
• 4 Leeds Institute of Cancer and Pathology, University of Leeds, Leeds LS9 7TF, UK.
• 5 University Hospital of Wales, Cardiff CF14 4XW, UK.
• 6 Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast BT9 7AE, UK.
• 7 Institute of Cancer and Genetics, Cardiff University, Cardiff CF14 4XN, UK.
• 8 St James's Institute of Oncology, University of Leeds, Leeds LS9 7TF, UK.
• 9 Wales Cancer Trials Unit, Cardiff University, Cardiff CF14 4YS, UK.
• 10 Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield S5 7AU, UK.
• 11 UCL Cancer Institute, London WC1E 6BT, UK.
• 12 Department of Oncology, Castle Hill Hospital, East Riding of Yorkshire HU16 5JQ, UK.
• PMID: 24743706
• PMCID: PMC4007241
• DOI: 10.1038/bjc.2014.182

Background: Molecular characteristics of cancer vary between individuals. In future, most trials will require assessment of biomarkers to allocate patients into enriched populations in which targeted therapies are more likely to be effective. The MRC FOCUS3 trial is a feasibility study to assess key elements in the planning of such studies.

Patients and methods: Patients with advanced colorectal cancer were registered from 24 centres between February 2010 and April 2011. With their consent, patients' tumour samples were analysed for KRAS/BRAF oncogene mutation status and topoisomerase 1 (topo-1) immunohistochemistry. Patients were then classified into one of four molecular strata; within each strata patients were randomised to one of two hypothesis-driven experimental therapies or a common control arm (FOLFIRI chemotherapy). A 4-stage suite of patient information sheets (PISs) was developed to avoid patient overload.

Results: A total of 332 patients were registered, 244 randomised. Among randomised patients, biomarker results were provided within 10 working days (w.d.) in 71%, 15 w.d. in 91% and 20 w.d. in 99%. DNA mutation analysis was 100% concordant between two laboratories. Over 90% of participants reported excellent understanding of all aspects of the trial. In this randomised phase II setting, omission of irinotecan in the low topo-1 group was associated with increased response rate and addition of cetuximab in the KRAS, BRAF wild-type cohort was associated with longer progression-free survival.

Conclusions: Patient samples can be collected and analysed within workable time frames and with reproducible mutation results. Complex multi-arm designs are acceptable to patients with good PIS. Randomisation within each cohort provides outcome data that can inform clinical practice.

Publication types

• Clinical Trial, Phase II
• Randomized Controlled Trial
• Research Support, Non-U.S. Gov't
• Aged, 80 and over
• Biomarkers, Tumor / analysis
• Colorectal Neoplasms / drug therapy*
• Colorectal Neoplasms / genetics*
• Colorectal Neoplasms / mortality
• DNA Mutational Analysis
• Disease-Free Survival
• Feasibility Studies
• Middle Aged
• Precision Medicine*
• Proto-Oncogene Proteins / genetics*
• Proto-Oncogene Proteins B-raf / genetics*
• Proto-Oncogene Proteins p21(ras)
• Treatment Outcome
• ras Proteins / genetics*
• Biomarkers, Tumor
• KRAS protein, human
• Proto-Oncogene Proteins
• BRAF protein, human
• Proto-Oncogene Proteins B-raf
• ras Proteins

Associated data

• ISRCTN/ISRCTN83171665

Grants and funding

• MCCC-FCO-11-C/MCCC_/Marie Curie/United Kingdom
• G0701770/MRC_/Medical Research Council/United Kingdom
• MC_UU_12023/3/MRC_/Medical Research Council/United Kingdom
• MC_U122861325/MRC_/Medical Research Council/United Kingdom
• 18815/CRUK_/Cancer Research UK/United Kingdom
• 15954/CRUK_/Cancer Research UK/United Kingdom

• Open access
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Delayed recognition of acute disease among older adults hinders timely management and increases the risk of hospital admission. Point-of-Care testing, including Focused Lung Ultrasound (FLUS) and in-home analysis of biological material, may support clinical decision-making in suspected acute respiratory disease. The aim of this study was to pilot test the study design for a planned randomised trial, investigate whether in-home extended use of point-of-care testing is feasible, and explore its’ potential clinical impact.

A non-randomised pilot and feasibility study was conducted during September–November 2021 in Kolding Municipality, Denmark. A FLUS-trained physician accompanied an acute community nurse on home-visits to citizens aged 65 + y with signs of acute respiratory disease. The acute community nurses did a clinical assessment (vital signs, capillary C-reactive protein and haemoglobin) and gave a presumptive diagnosis. Subsequently, the physician performed FLUS, venipuncture with bedside analysis (electrolytes, creatinine, white blood cell differential count), nasopharyngeal swab (PCR for upper respiratory pathogens), and urine samples (flow-cytometry). Primary outcomes were feasibility of study design and extended point-of-care testing; secondary outcome was the potential clinical impact of extended point-of-care testing.

One hundred consecutive individuals were included. Average age was 81.6 (SD ± 8.4). Feasibility of study design was acceptable, FLUS 100%, blood-analyses 81%, PCR for upper respiratory pathogens 79%, and urine flow-cytometry 4%. In addition to the acute community nurse’s presumptive diagnosis, extended point-of-care testing identified 34 individuals with a condition in need of further evaluation by a physician.

Overall, in-home assessments with extended point-of-care testing are feasible and may aid to identify and handle acute diseases in older adults.

Peer Review reports

The population of older adults is increasing, and healthcare sectors worldwide face capacity challenges [ 1 ]. In Denmark, acute community healthcare services (ACHCS) were established in 2018 to carry out initial in-home clinical assessments of vulnerable citizens suspected of emerging acute diseases. The purpose was to support early decision-making and triage to reduce the number of avoidable admissions and the pressure on the secondary healthcare sector [ 2 ]. However, diagnosing older adults is challenging as they may present with vague symptoms, e.g., coughing is a less prominent symptom in pneumonia [ 3 ], or atypical symptoms e.g., functional decline, delirium, and falls [ 4 , 5 ]. Delayed recognition of disease prevents timely management and increases the risk of hospital admission [ 6 ].

Point-of-care testing (POCT) is carried out bedside or near the patient, i.e., in-home [ 7 ], and increases timely diagnosis and decision-making in emergency departments and in primary care [ 8 ]. C-Reactive Protein (CRP), haemoglobin, international normalised ratio (INR), urine test strips, and blood glucose testing are widely implemented in primary care [ 9 ]. In recent years, new POCTs have been developed, such as white blood cell (WBC) differential count, hand-held point-of-care ultrasound, and urine flow-cytometry, but the tests are still not widely implemented in primary care nor validated among older adults [ 10 , 11 , 12 ]. The Danish ACHCSs use POCT for CRP and haemoglobin on capillary blood, but given the challenges of diagnosing older adults, a comprehensive approach is needed with additional clinical assessment, biochemical results, and imaging modalities [ 6 ]. By introducing extended POCT (ExtPOCT) during in-home assessment, we hypothesize that ExtPOCT improves diagnostic work-up and supports the primary care physicians’ clinical decision-making.

Prior to a planned randomised controlled trial (RCT), the primary objective was to investigate whether ExtPOCT during in-home assessments among older adults was feasible, and, secondly, to pilot-test the study design including the intervention consisting of ExtPOCT, defined by Focused Lung Ultrasound (FLUS) and in-home analysis of biological material (blood, nasopharyngeal swab, urine).

The secondary objective was to explore whether ExtPOCT had potential clinical impact by identifying conditions in need of clinical decision-making not identified by usual in-home assessments.

Trial design

This study was conducted as a prospective observational non-randomised pilot and feasibility study, adhering to the guidelines outlined by the CONSORT 2010 statement: extension to randomised pilot and feasibility studies [ 13 , 14 ].

Study setting

The study was conducted in 2021 from September 1 st to December 1 st , in Kolding Municipality, Denmark, covering an area of 604.5 km 2 with 93,161 inhabitants (65 + year olds: 18,453) [ 15 ]. The pilot study was conducted in collaboration with the ACHCS in Kolding Municipality.

The ACHCS is operated by acute community nurses (ACNs) trained in in-home assessment including vital signs and POCT for C-Reactive Protein (CRP) and haemoglobin on capillary blood ( usual care) [ 2 ]. All clinical information is communicated to the primary care physician (PCP) to support clinical decision-making. In-home assessment is performed after referral from PCPs or home care service personnel when an acute condition in vulnerable citizens is suspected and can be carried out at the place of residence, i.e., in own home, care home, or skilled nursing facility. Approximately five patients are referred each day to the ACHCS for an in-home assessment. Hospital physicians refer patients for in-home treatment with intravenous antibiotics carried out by ACNs.

Study participants

Participants eligible for this study were adults aged 65 years or older, referred to the ACHCS in Kolding Municipality for an acute in-home assessment, irrespective of their status as home care recipients or their place of residence, including own home, a care home, or a skilled nursing facility.

The participants had at least one of the following inclusion criteria: Cough, dyspnoea, fever (≥ 38 °C), chest pain, fall, or functional decline, defined as either subjective (not able to perform normal daily activities) or objective functional decline (increased need of home care service). Fall and functional decline are usually not perceived as symptoms of worsened or acute respiratory disease, but are known as atypical disease presentations [ 4 , 5 ]. Participants with known moderate to severe cognitive impairment were excluded from the study, due to Danish legislation and recommendations from the Regional Committees on Health Research Ethics for Southern Denmark.

A convenience sample of 100–150 participants was chosen to investigate feasibility and potential clinical impact. The pilot-study should not exceed 3 months, as inclusion rate was part of the feasibility assessment.

Intervention

The intervention was an add-on to the ACNs’ usual in-home assessment and included hand-held FLUS, biochemical analysis on venous blood samples, and microbiological analysis of nasopharyngeal swabs and urine samples (Fig.  1 ).

Overview of examination program and data collection. ^ POCT on capillary blood samples for C-reactive protein and Hemoglobin (using Quick-read PRO). *POCT on venous blood samples for creatinine and electrolytes (using i-STAT ®), and for Leucocytes with differential count (using Hemocue® WBF DIFF System). **POCT on nasopharyngeal swabs for 22 different viral and bacterial pathogens (using BioMérieux BioFire ® FilmArray ®  Respiratory Panel 2.1). ***POCT on urine samples for flow-cytometry (using Sysmex UF-5000 ®). Abbreviations: ACN: Acute Community Nurse, POCT: Point-of-care Testing, PCP: Primary Care Physician, PCR: Polymerase chain reaction

FLUS examination was performed using a hand-held ultrasound scanner in the form of a Lumify® C5-2 Curved Array Transducer (Philips Medical Systems, Bothell, WA) (5–2 MHz, scan depth up to 30 cm) connected by USB-C to a FuturePAD® FPZ10-A tablet (CONCEPT International GmbH, Munich Germany). The standard Philips Lumify App version 4.0.1 software and its dedicated lung-preset was installed on the tablet and used for the examination. FLUS followed a standardised 14 scanning zone protocol using predefined questions regarding pneumothorax, pleural effusion, interstitial syndrome, and other obvious pathology [ 16 , 17 ].

Blood-samples were collected by venipuncture and analysed immediately during in-home assessment. Blood samples for creatinine and electrolytes (collected in lithium/heparin vacutainers) were analysed using CHEM8+ cassettes on i-STAT® (Abbott, Inc., NJ, U.S.A.). WBC differential count (collected in EDTA-vacutainers) was analysed using HemoCue® WBF DIFF System (HemoCue AB, Ängelholm, Sweden) with dedicated micro-cuvettes.

Nasopharyngeal swabs and urine samples were collected during in-home assessment, and carried to Hospital Lillebaelt, Kolding, within 2 h. Nasopharyngeal swabs were analysed on the BioMérieux BioFire ® FilmArray ®  Respiratory Panel 2.1 (RP2.1) (BioFire Diagnostics, Salt Lake City, UT, USA). The BioFire ®  FilmArray ® RP2.1 targets 22 respiratory pathogens [ 18 ]. Urine samples were analysed on urine flow-cytometer Sysmex UF-5000 ® (Sysmex Corporation, Kobe, Japan).

Feasibility was evaluated based on several criteria, including the average inclusion rate, acceptability of the intervention, and the utilization of ExtPOCT. The average inclusion rate was considered feasible if at least two participants a day, 4 days a week, were enrolled in the study. The acceptability of the intervention was determined by assessing the number participants who declined participation and by assessing the acceptance of the results from ExtPOCT by PCPs. Additionally, the feasibility of ExtPOCT and collection of other biological material during in-home assessment was defined and calculated as the percentage of completed examinations. The intervention procedure (ExtPOCT) was considered feasible if used in > 80% of participants.

To assess the potential clinical impact of ExtPOCT, we predefined specific conditions in participants that necessitated clinical decision-making by the PCP based on usual care results, and subsequently compared these with the findings from ExtPOCT. Conditions requiring clinical decision-making were defined as instances necessitating treatment initiations or adjustments (e.g., antibiotics, diuretics, or inhalation therapy), hospital admission, or increased need for home care. The identification of participants with conditions requiring further clinical decision-making, which were not detected by usual in-home assessment conducted by ACNs, was considered indicative of potential clinical impact of ExtPOCT.

The registration of conditions requiring clinical decision-making was derived by using predefined cut-offs and international standardised agreements [ 16 , 17 , 19 , 20 , 21 , 22 ]. Conditions identified by ExtPOCT were: Pneumothorax, pleural effusion, interstitial syndrome, pneumonia, elevated leucocytes (> 11*10 9 /L), elevated creatinine (> 150 µmol/L), abnormal electrolytes (K + : < 3 mmol/L or > 5 mmol/L, Na + : < 125 mmol/L or > 145 mmol/L), positive PCR for upper respiratory tract pathogens, positive urine flow-cytometry (> 10 5 BACT/ml).

Data collection

An overview of the data collection and examination program is illustrated in Fig.  1 .

The primary investigator, a physician certified and trained in thoracic ultrasound corresponding to European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) thoracic ultrasound competency level 1, accompanied the ACNs during in-home assessment [ 23 ]. The usual in-home assessment was made by the ACNs, after which the ACNs noted a presumptive diagnosis and whether a clinical decision by a physician was required. Subsequently the primary investigator performed ExtPOCT.

All results from the usual care and ExtPOCT were communicated by the ACN to the participants PCP both by telephone and by written electronic communication.

The primary investigator collected descriptive data from all study participants during the in-home assessment (Fig.  1 ), including symptoms, symptom duration, height, smoking status, and alcohol consumption. Functional level was assessed using the Barthel Index 20, while frailty among participants was evaluated using the Clinical Frailty Scale, both of which were assessed using validated Danish-translated assessment scales [ 24 , 25 ]. Additional data on the amount of home care received by participants was extracted from the municipal Electronic Social Care Record. Polypharmacy, defined as the use of 5 or more medications per day, was assessed using the Shared Medication Record (In Danish: FMK – Fælles Medicin Kort), a nationwide digital database at the Danish Health Data Authority, storing data on all Danish citizens’ current medication plans, electronic prescriptions, and medicine purchases [ 26 ].

The hospital Electronic Patient Journal (EPJ) was accessed after 30 days to register admissions, reasons for admission, length of admission, and deaths, as these variables are primary and secondary outcomes for the planned RCT. Adverse events and harms were also registered and served as safety assessment of the intervention.

Statistical methods

We used descriptive statistics to present demographic and baseline characteristics. Categorical data was reported as number and percentage. Continuous data was reported as means (SD), medians [IQR], and range. The primary outcome was assessed by calculating inclusion-rate, number of declining participants, and number of contacts to the PCPs. The feasibility of ExtPOCT was calculated as the percentage of completed examinations. The secondary outcome was reported as the number of participants in need of clinical decision-making not identified by the ACNs usual in-home assessment. All statistical analyses were carried out using STATA version 16 software (StataCorp LLC, Texas, USA).

Inclusion-flow

Totally, 139 older adults were assessed for eligibility during the study period, of which 35 could not be included due to cognitive impairment, two declined, and two required urgent hospitalisation, thereby including 100 participants in the study. For details, see Fig.  2 . Inclusion rate was 2.08 participants per day, 4 days a week, for 3 months. All participants were followed for 30 days.

Study population

Mean age of included participants was 81.6 years (SD ± 8.4) and 54% were female. Most assessments were carried out in the participants own home (86%), of whom 71% received home care. The prevalence of polypharmacy (> 5 medications daily) was high (95%). Median Clinical Frailty Scale level was 5 (range 1–9). Less than four participants had chest pain. For details, see Table  1 .

Usual in-home assessment

The ACNs carried out in-home assessment in all participants. Median values of vital signs are shown in Table  2 . Median value of CRP and haemoglobin was 24 mg/L (IQR 5.3–57) and 7.4 mmol/L (IQR 6.6–8.1), respectively. ACNs presumptive diagnoses based on results from the usual in-home assessment suggested that 48 participants had conditions requiring clinical decision-making by a physician. The suggested diagnoses and conditions were pneumonia ( n  = 20), acute exacerbation of chronic obstructive pulmonary disease ( n  = 15), infection but unclear focus ( n  = 6), urinary tract infection ( n  = 5), and other ( n  < 3). For details, see Table  2 .

Intervention – ExtPOCT

FLUS was performed in all participants (100%), venous blood-samples in 81%, nasopharyngeal swabs in 79%, and urine samples in 4%. Reasons for missing venous blood samples were practical difficulties in obtaining a blood sample. Reasons for missing nasopharyngeal swabs were acute admissions, and urine samples were missing due to permanent catheters (27%) or participants unable to provide a urine sample (73%) during the in-home assessment.

ExtPOCT identified additional 34 participants with acute conditions requiring clinical decision-making by a physician. This is illustrated in Fig.  3 . FLUS alone identified additional conditions in 21 participants needing further clinical decision-making by a physician: Pneumothorax, interstitial syndrome, moderate to large pleural effusions, and pneumonia. A significantly elevated creatinine (> 150 µmol/L) supporting a diagnosis of dehydration was identified in nine participants, which was not identified in the usual in-home assessment. Elevated WBC differential counts were identified in 16 participants, not suspected to have a bacterial infection in the usual in-home assessment. PCR for respiratory pathogens identified less than three viral infections. Only few urine samples were collected, and the potential clinical impact is therefore uncertain.

Potential clinical impact of extended point-of-care testing. Extended point-of-care testings’ potential for clinical impact by identifying additional participants with conditions in need of clinical decision-making compared to usual in-home assessments. A ACNs identified 48 out of 100 participants in need of clinical decision-making by a primary care physician. Extended POCT identified additional 34 participants with a condition in need of clinical decision-making, not identified by the usual in-home assessment. Each specific POCT is illustrated in B , C , D , except for PCR for upper respiratory tract infection and urine flow-cytometry, as results did not change clinical decision-making: B Focused Lung ultrasound identified 21 participants with a condition in need of clinical decision-making not identified by the ACNs in-home assessment. (Feasibility 100%). C POCT for leucocytes with differential count identified 16 participants with a condition in need of clinical decision-making not identified by the ACNs in-home assessment. (Feasibility 89%). D POCT for creatinine identified 9 participants with a condition in need of clinical decision-making not identified by the ACNs in-home assessment. (Feasibility 89%). Abbreviations: ACN: Acute Community Nurse, ExtPOCT: Extended point-of-care testing, FLUS: Focused Lung Ultrasound, POCT: Point-of-care Testing, PCR: Polymerase chain reaction

Healthcare contacts

In 62 of the in-home assessments, the PCP was contacted on the day of the visit directly by phone, and in 77% of the cases, the contact led to initiation of treatment, mainly oral antibiotics (37%), diuretics (6%), or hospital admission (21%). In total 42 participants (55 admissions) were admitted to hospital from the day of inclusion to 30 days follow-up. Median duration of hospital admission was 5 days (IQR 2–8).

Adverse events

No adverse events were reported to or observed by the research team. In total, 11 deaths occurred, and most deaths took place in hospital ( n  = 7).

Key results and interpretation

The overall study design and use of ExtPOCT during in-home assessment of older adults were feasible. Our results suggest that FLUS and POCT on venous blood might supplement the usual in-home assessment of older adults suspected of acute respiratory disease by identifying additional conditions - potentially facilitating diagnostic work-up and early treatment.

The study design of the planned RCT has been modified based on the insights gained from the pilot study. As a result, the inclusion criteria were revised, which involved omitting chest as an eligibility symptom. This adjustment was informed by the observation that very few participants presented with chest pain. It is also important to note that in Denmark, chest pain as a standalone symptom typically warrants acute admission regardless of other factors. Therefore, including chest pain as a criterion in our study was deemed potentially confounding, and it was decided to exclude chest pain as a specific inclusion criterion for our study. We also omitted nasopharyngeal swab for PCR for upper respiratory pathogens and urine flow-cytometry from the intervention as explained in the following sections.

FLUS had the highest feasibility and did provide additional information to the clinical decision making. These findings are in line with other studies, showing that FLUS identifies missed conditions in need of treatment [ 16 , 27 , 28 ]. In general, only few studies on the use of FLUS have been conducted in primary care [ 29 ]. A recent study conducted in primary care investigated lung ultrasound performed by PCPs in patients suspected of community-acquired pneumonia found a higher prevalence of pneumonia compared to our findings (53% vs 25%) [ 30 ]. However, they used more specific inclusion criteria for community-acquired pneumonia, and patients were younger (median age of 47 vs 81.6 years). Only one participant in our study had classic dynamic bronchoaerograms, whereas most participants with pneumonia had unspecific findings with a thickened, fragmented visceral pleura, smaller sub-pleural consolidations, and focal B-lines [ 19 ]. Another notable finding from FLUS was pleural effusions: The identified moderate to large pleural effusions were among individuals without classic respiratory symptoms, but functional decline. In conclusion, FLUS is highly feasible, could have clinical impact, and will remain part of the intervention in the planned RCT.

Elevated creatinine level led to initiation of treatment or hospital admission in cases not identified by usual in-home assessment. Elevated leucocytes > 11*10 9 /L were interpreted as sign of bacterial infection, although cut-off points on different biomarkers of inflammation in older multimorbid adults have not reached international consensus and/or are still not validated [ 10 , 11 , 31 ]. In addition, systematic reviews and prospective studies have shown that older adults differ in biochemical presentation compared to younger adults [ 32 , 33 , 34 ]. This highlights the need for further research in diagnosing infections in older adults. Due to high feasibility and potential clinical impact, we chose to keep both creatinine, electrolytes, and WBC differential count in the planned RCT.

Nasopharyngeal swabs were feasible to collect, but PCR for upper respiratory pathogens did not add to the clinical decision-making. During the study period, rates of viral respiratory tract infections were very low probably as a consequence of general restrictions and recommendations to reduce and contain the COVID-19 pandemic in Denmark [ 35 ]. Because of the possible low number of positive samples, the uncertain clinical impact, and the high cost, POCT PCR was omitted from the RCT.

Urine samples were difficult to collect as many participants had catheters or were unable to provide a urine sample during the in-home assessment. Hence, the added clinical value of urine analysis is unknown and urine flow-cytometry is therefore excluded from the RCT.

The high rate of hospital admissions during the 30 days follow-up highlights the need for early detection of suspected disease in older adults. ExtPOCT might have added to the high rate by detecting pathologies in need of hospital admissions e.g., large pleural effusions. Additionally, ExtPOCT may yield false positive findings, or unclear results leading to unnecessary contacts to the secondary healthcare sector. However, it also has potential for early, relevant treatment decisions to prevent clinical deterioration and subsequent functional decline. Our planned RCT aims to investigate the effect of ExtPOCT on specific healthcare outcomes such as hospital admissions, in-hospital length of stay, and mortality, thereby addressing the effect of ExtPOCT on hospital admissions.

POCT for CRP, haemoglobin, blood glucose, and urine test strips, are widely implemented in primary care, but there is limited evidence of using other POCT in primary care especially among older adults and during in-home assessments [ 10 , 11 , 36 ]. A recent study from Germany highlighted that many PCPs rated only a limited number of POCT as useful [ 37 ], but without explaining why. Barriers towards POCT among PCPs, e.g., low economic benefit, over-reliance, increased risk of over-treatment, over-diagnostics, and unnecessary hospital admissions, can hinder implementations. We therefore plan to explore how citizens, ACNs, and PCPs experience ExtPOCT during in-home assessment, in a user-perspective evaluation after completion of the planned RCT.

Generalisability

The study sample was older adults with high rates of polypharmacy, frailty, and home-care dependency – a group of older adults who are at increased risk of hospital admission, and similar to the study population we aim to include for our planned RCT [ 1 , 38 ].

The ACHCS setup is common in Scandinavia, though organised differently between countries and municipalities [ 39 ]. Results from the present pilot-study and the planned RCT might not be applicable in other countries than Denmark, but the concept is applicable: By increasing competencies, e.g., introducing in-home POCT, to healthcare professionals caring for frail older adults, timely clinical decisions may be facilitated.

Limitations

Our study is classified as a pilot and feasibility study, as it aims to assess both the feasibility of the intervention and its potential clinical impact. Although our study lacked randomisation, we aimed to pilot-test the intervention and explore our hypothesis that ExtPOCT had potential to enhance the diagnostic work-up. Acceptability of the intervention was utilized as an outcome measure to assess feasibility. While acceptability traditionally focuses on participants’ and stakeholders’ attitudes towards an intervention, data collection process, or randomization, we followed the approach advocated by Eldridge et al. to explore acceptability as a means of informing the feasibility of a larger RCT [ 14 ]. Therefore, we utilized acceptability as a measure of feasibility to evaluate whether the intervention could be effectively implemented in a future RCT.

We had to exclude participants with cognitive impairment, and therefore we do not know whether ExtPOCT is feasible or have potential clinical impact in the diagnostic work-up among older adults with cognitive impairment.

We are well aware that it is not possible for us to determine the causal effect of ExtPOCT on clinical impact, and we do not have a final diagnosis on all participants. However, it was important to explore the potential clinical impact prior to the RCT: If the usual in-home assessments carried out by ACNs can identify most conditions in need of clinical decision-making, ExtPOCT is redundant.

The primary investigator performed ExtPOCT. Prior to the planned RCT, ACNs will complete an extensive training programme for collecting venous blood samples, handling POCT, and performing FLUS, and subsequently carry out ExtPOCT during the RCT.

Conclusions

The overall study design for the planned RCT is feasible, and in-home blood analyses and FLUS have a potential clinical impact by identifying acute conditions earlier in the diagnostic process, which suggests a potential for improving clinical decision-making during in-home assessment among older adults.

Availability of data and materials

The dataset generated and analysed during the current study is available from the corresponding author on reasonable request.

Abbreviations

Acute community healthcare service

Acute community nurse

Clinical Frailty Scale

C-reactive protein

Extended Point-of-care testing, including a focused lung ultrasound scan (FLUS), biochemical analysis on venous blood samples, and microbiological analysis of nasopharyngeal swabs and urine samples

Focused lung ultrasound scan

General Data Protection Regulation

International Normalised Ratio

Open Patient data Explorative Network

Polymerase chain reaction

Point-of-care

• Point-of-care testing

Randomised controlled trial

White blood cells

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Acknowledgements

We would like to acknowledge Open Patient Explorative Network (OPEN) for support on data-management. We would also like to thank the Acute Community Healthcare Service in Kolding Municipality (Acute Team Kolding) and all Acute Community Nurses for their cooperation in the study. Peter Barkholdt and Anne-Mette Rottwitt contributed with their assistance to the implementation of the study and dedicated engagement in the Advisory Board. We would also like to thank all the primary care physicians in Kolding Municipality for their collaboration. The Emergency Department and Department of Biochemistry and Immunology, Lillebaelt Hospital, Kolding, and Department  of Clinical  Microbiology , Lillebaelt  Hospital ,  Vejle , supported the study with their expertise in handling and analysing POCT samples.

Open access funding provided by University of Southern Denmark. This work was supported by Odense University Hospital, Innovationspuljen [A4848], Hartmann Foundation [A36257], Grosserer L. F. Foghts Foundation, and the University of Southern Denmark [20/15107]. None of the funding bodies had any role in the conceptualization of design, data collection, analysis, interpretation, peer-review, decision to publish, or preparation of the manuscript.

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Siri Aas Smedemark & Karen Andersen-Ranberg

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Siri Aas Smedemark, Christian B. Laursen & Karen Andersen-Ranberg

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Dorte Ejg Jarbøl

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SAS, CBL, DEJ, FSR and KAR designed the study. SAS conducted the study, collected data, analysed data, prepared manuscript, figures, and tables. CBL, DEJ, FSR, and KAR provided constructive feedback on the draft and manuscript. SAS, CBL, FSR, DEJ, and KAR interpreted findings and read and approved the final manuscript.

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The ethical principles for medical research as stated by the Declaration of Helsinki, were applied throughout the study [ 40 ]. The study is reported in line with CONSORT 2010 statements for pilot and feasibility trials [ 13 ]. The study was approved by the Regional Committees on Health Research Ethics for Southern Denmark (S-20210046). Methods have followed guidelines and regulation given by the Regional Committees on Health Research Ethics for Southern Denmark. Consent forms and process have been ethically reviewed by the Regional Committees on Health Research Ethics for Southern Denmark. All participants provided written informed consent. Written informed consent was obtained from all participants by the principal investigator.

The pilot-study was registered at the Research & Innovation Organisation (RIO), University of Southern Denmark, record of data processing activities, (Project identification number: 11.404). Data was processed and stored in accordance with EU General Data Protection Regulation (GDPR) and the Danish Data Protection Act.

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CBL has in the past 36 months received speaker’s honoraria for lectures at educational events / symposia / courses organised by AstraZeneca, royalties as author of book chapters or as editor of books / web publications by Munksgaard.

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Smedemark, S.A., Laursen, C.B., Jarbøl, D.E. et al. Improving diagnostics using extended point-of-care testing during in-home assessments of older adults with signs of emerging acute disease: a prospective observational non-randomised pilot and feasibility study. BMC Geriatr 24 , 373 (2024). https://doi.org/10.1186/s12877-024-04914-5

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They Shoot Owls in California, Don’t They?

An audacious federal plan to protect the spotted owl would eradicate hundreds of thousands of barred owls in the coming years.

Northern spotted owl populations have declined by up to 80 percent over the last two decades. As few as 3,000 remain on federal lands, compared with 12,000 in the 1990s. Credit... Gerry Ellis/Minden Pictures

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By Franz Lidz

• April 29, 2024

In the ancient forests of the Pacific Northwest, the northern spotted owl, a rare and fragile subspecies of spotted owl, is being muscled out of its limited habitat by the barred owl, its larger and more ornery northeastern cousin. The opportunistic barred owl has been moving in on spotted owl turf for more than half a century, competing with the locals for food and space, outnumbering, out-reproducing and inevitably chasing them out of their nesting spots. Barred owls have also emerged as a threat to the California spotted owl, a closely related subspecies in the Sierra Nevada and the mountains of coastal and Southern California.

Crammed into marginal territories and bedeviled by wildfires, northern spotted owl populations have declined by up to 80 percent over the last two decades. As few as 3,000 remain on federal lands, compared with 11,000 in 1993. In the wilds of British Columbia, the northern spotted owl has vanished; only one, a female, remains. If the trend continues, the northern spotted owl could become the first owl subspecies in the United States to go extinct.

In a last-ditch effort to rescue the northern spotted owl from oblivion and protect the California spotted owl population, the U.S. Fish and Wildlife Service has proposed culling a staggering number of barred owls across a swath of 11 to 14 million acres in Washington, Oregon and Northern California, where barred owls — which the agency regards as invasive — are encroaching. The lethal management plan calls for eradicating up to half a million barred owls over the next 30 years, or 30 percent of the population over that time frame. The owls would be dispatched using the cheapest and most efficient methods, from large-bore shotguns with night scopes to capture and euthanasia.

Karla Bloem, the executive director of the International Owl Center in Minnesota, is conflicted over the prospect of killing one species to protect another. “The concept of shooting birds is awful — nobody wants that,” she said. “But none of the alternatives have worked, and at this late date no other option is viable. Extinction is a forever thing.”

Bob Sallinger, the executive director of Bird Conservation Oregon, agreed but emphasized that the culling must complement the restoration and preservation of the few remaining old-growth forests. “The science clearly shows that you must both protect and increase habitat and remove some level of barred owls if the northern spotted owl is to have a chance of survival,” he said.

The agency’s plan, outlined last fall in a draft report assessing its environmental impact that is due for final review this summer, has pitted conservationists, who say it will benefit both species, against animal supporters, who consider the proposed scale, scope and timeline unsustainable.

Last month, a coalition of 75 wildlife protection and animal welfare organizations sent a letter to Secretary of the Interior Deb Haaland urging her to scrap what they called a “colossally reckless action” that would necessitate a perpetual killing program to keep the number of barred owls in check. Wayne Pacelle, the president of Animal Wellness Action and an author of the statement, said it was dangerous for the government to start managing competition and social interaction among North American species, including ones that have expanded their range as a partial effect of “human perturbations” of the environment. “I cannot see how this succeeds politically, because of its price tag and its sweeping ambitions,” he said in an email.

Mr. Pacelle questions whether barred owls, which are indigenous to North America, truly meet the criteria for an invasive species. “This ‘invasive’ language rings familiar to me in our current political debates,” he said. “Demonize the migrants, and the harsh policy options become much easier from a moral perspective.”

The signatories argued that the current predicament warranted nonlethal control, and that the agency’s approach would lead to the wrong owls being shot and to the death of thousands of eagles, hawks and other creatures from lead poisoning. “Implementing a decades-long plan to unleash untold numbers of ‘hunters’ in sensitive forest ecosystems is a case of single-species myopia regarding wildlife control,” the letter said.

Rocky Gutierrez, a wildlife ecologist who has conducted research on spotted owls since 1980, described the letter as disingenuous. “It is apparent to me that the authors either did not understand the plan or they didn’t read it carefully,” he said. “Secretary Haaland is likely not to be swayed by their arguments because they are often incorrect or based on nonscience.”

Dr. Gutierrez noted that the government draft explicitly forbade lead and other toxic ammunition, and that the agency planned to enlist not hunters but highly trained specialists who would be required to take a course and pass a test.

“Because the training and rigorous protocol minimize the chance for misidentification, there has yet to be a case of mistaken identity,” Dr. Gutierrez said, referring to the results of a five-year field experiment published in 2021. “Several major peer-reviewed studies have demonstrated the efficacy of this removal method.”

Ms. Bloem, of the International Owl Center, added: “Spotted owl research is some of the most rigorous science on earth because so much has been riding on it. This management plan is no exception.”

A spotted decline

The Fish and Wildlife Service has been trying to save the spotted owl for decades. The effort became a cause célèbre in the 1980s as environmentalists saw it as a way to force the U.S. government to drastically reduce logging in northwestern federal forests. The birds depend on old growth woodland to survive, preferring towering trees such as Douglas firs that typically take 150 to 200 years to mature.

Over the passionate objections of the timber industry, spotted owls were listed as threatened under the Endangered Species Act in 1990. As loggers mounted protests, dead owls were nailed to road signs and “owl fricassee” appeared facetiously on restaurant menus. Four years later, the Northwest Forest Plan established a new management framework for the 24 million acres of federal forest land in Washington, Oregon and California within the range of the northern spotted owl. Despite sharp logging cutbacks, the bird’s population decline continued, especially in areas where barred owls were densest.

Barred owls started making their way west in the early 1900s as European settlers transformed the Midwest landscape from prairie to patches of woodland. Aided perhaps by a warming trend in the boreal forests of eastern Canada and northern Minnesota, where barred owls are abundant, the birds spread across the Great Plains and, by 1943, were spied in British Columbia, the domain of the northern spotted owl.

“When spotted owls were listed in 1990, it was known that barred owls could be a potential threat,” said David Wiens, a wildlife biologist with the U.S. Geological Survey. “But we knew very little about barred owls then, and had no idea what their population trajectory would be in the Pacific Northwest.”

At first sight, it’s easy to mistake a spotted for a barred: Both have tuftless rounded heads, teddy bear eyes and bodies mottled brown and white. They can interbreed to produce chicks called sparred owls. But they differ in their habitat requirements. Up to four pairs of barred owls can occupy the three-to-12 square miles that one spotted couple needs, and barred owls aggressively defend their terrain. “The closer spotted owls live to barred owls, the less likely the spotted owls are to have offspring,” Dr. Wiens said. Barred owls also produce four times as many young.

Spotted owls are extremely picky eaters: In California, they eat only flying squirrels and wood rats. “Barred owls devour anything and everything,” Ms. Bloem said, “which is hard on Western screech owls, rare reptiles and amphibians, and has cascading effects on the ecosystem.”

‘No one wants them’

Some animal activists have suggested that rather than shoot the barred owls, the Fish and Wildlife Service should try to stop them from reproducing. But Eric Forsman, a retired Forest Service biologist whose research informed the Northwest Forest Plan, countered that every other option had already been on the table. “Half-baked methods like sterilization and egg removal would be impossible at the scale needed to reduce numbers,” he said.

Another nonstarter is relocation, which would risk introducing new parasites and diseases from the West into the barred owls’ historical range. “If people complain about the cost and feasibility of 15,000 birds removed per year, the price tag for translocation would probably send them into cardiac arrest,” Dr. Gutierrez said. “And besides being too time-consuming, where would you relocate the owls to? No one wants them.” You could “let nature take its course,” he added, but that course would be extinction for the spotted owl.

Three years ago, researchers published the results of a pilot program that involved discreetly culling 2,485 barred owls in five study sites along the West Coast. The birds were lured with recordings of their calls, which cause spotted owls in the wild to retreat and remain silent to avoid detection.

Dr. Wiens, who helped run the experiment, said that over five years of culling barred owls halted declines in the spotted owl population; in areas without removal, spotted owl populations fell by about 12 percent annually.

Ms. Bloem offered a “successful precedent” for the government’s owl scheme. In the 1970s, an effort by the Fish and Wildlife Service to trap brown-headed cowbirds in Michigan saved the Kirtland’s warbler from extinction, though the warbler’s population did not increase for almost 20 years after trapping began.

“If efforts are focused on the leading edge of the barred owl invasion in California and in the few remaining pockets in Washington and Oregon, continued annually or every few years, there is a reasonable chance for this to work,” Ms. Bloem said. She added that the best hope was for the California spotted owl, which has not been so thoroughly infiltrated yet.

Dr. Forsman is less sanguine. He feared that attempts to control barred owls were likely to fail, because the bird’s range expansion was too extensive. To him, the proposed policy is a call for action based on the “untestable” hypothesis that humans were responsible for the expansion.

If we were not responsible, would we still be making the same call for action? he wondered. “Or even if we were, is there some point at which we simply admit that we have screwed things up so badly that there is no going back to the good old days?” he said. “I am torn apart by this dilemma, and I find it difficult to get mad at anyone on either side of the argument.”

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