a meta analysis vs literature review

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Systematic reviews vs meta-analysis: what’s the difference?

Posted on 24th July 2023 by Verónica Tanco Tellechea

You may hear the terms ‘systematic review’ and ‘meta-analysis being used interchangeably’. Although they are related, they are distinctly different. Learn more in this blog for beginners.

What is a systematic review?

According to Cochrane (1), a systematic review attempts to identify, appraise and synthesize all the empirical evidence to answer a specific research question. Thus, a systematic review is where you might find the most relevant, adequate, and current information regarding a specific topic. In the levels of evidence pyramid , systematic reviews are only surpassed by meta-analyses. 

To conduct a systematic review, you will need, among other things: 

• A specific research question, usually in the form of a PICO question.
• Pre-specified eligibility criteria, to decide which articles will be included or discarded from the review. 
• To follow a systematic method that will minimize bias.

You can find protocols that will guide you from both Cochrane and the Equator Network , among other places, and if you are a beginner to the topic then have a read of an overview about systematic reviews.

What is a meta-analysis?

A meta-analysis is a quantitative, epidemiological study design used to systematically assess the results of previous research (2) . Usually, they are based on randomized controlled trials, though not always. This means that a meta-analysis is a mathematical tool that allows researchers to mathematically combine outcomes from multiple studies.

When can a meta-analysis be implemented?

There is always the possibility of conducting a meta-analysis, yet, for it to throw the best possible results it should be performed when the studies included in the systematic review are of good quality, similar designs, and have similar outcome measures.

Why are meta-analyses important?

Outcomes from a meta-analysis may provide more precise information regarding the estimate of the effect of what is being studied because it merges outcomes from multiple studies. In a meta-analysis, data from various trials are combined and generate an average result (1), which is portrayed in a forest plot diagram. Moreover, meta-analysis also include a funnel plot diagram to visually detect publication bias.

Conclusions

A systematic review is an article that synthesizes available evidence on a certain topic utilizing a specific research question, pre-specified eligibility criteria for including articles, and a systematic method for its production. Whereas a meta-analysis is a quantitative, epidemiological study design used to assess the results of articles included in a systematic-review. 

Remember: All meta-analyses involve a systematic review, but not all systematic reviews involve a meta-analysis.

If you would like some further reading on this topic, we suggest the following:

The systematic review – a S4BE blog article

Meta-analysis: what, why, and how – a S4BE blog article

The difference between a systematic review and a meta-analysis – a blog article via Covidence

Systematic review vs meta-analysis: what’s the difference? A 5-minute video from Research Masterminds:

• About Cochrane reviews [Internet]. Cochranelibrary.com. [cited 2023 Apr 30]. Available from: https://www.cochranelibrary.com/about/about-cochrane-reviews
• Haidich AB. Meta-analysis in medical research. Hippokratia. 2010;14(Suppl 1):29–37.

Verónica Tanco Tellechea

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Systematic Review VS Meta-Analysis

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How you organize your research is incredibly important; whether you’re preparing a report, research review, thesis or an article to be published. What methodology you choose can make or break your work getting out into the world, so let’s take a look at two main types: systematic review and meta-analysis.

Let’s start with what they have in common – essentially, they are both based on high-quality filtered evidence related to a specific research topic. They’re both highly regarded as generally resulting in reliable findings, though there are differences, which we’ll discuss below. Additionally, they both support conclusions based on expert reviews, case-controlled studies, data analysis, etc., versus mere opinions and musings.

What is a Systematic Review?

A systematic review is a form of research done collecting, appraising and synthesizing evidence to answer a particular question, in a very transparent and systematic way. Data (or evidence) used in systematic reviews have their origin in scholarly literature – published or unpublished. So, findings are typically very reliable. In addition, they are normally collated and appraised by an independent panel of experts in the field. Unlike traditional reviews, systematic reviews are very comprehensive and don’t rely on a single author’s point of view, thus avoiding bias.

Systematic reviews are especially important in the medical field, where health practitioners need to be constantly up-to-date with new, high-quality information to lead their daily decisions. Since systematic reviews, by definition, collect information from previous research, the pitfalls of new primary studies is avoided. They often, in fact, identify lack of evidence or knowledge limitations, and consequently recommend further study, if needed.

Why are systematic reviews important?

• They combine and synthesize various studies and their findings.
• Systematic reviews appraise the validity of the results and findings of the collected studies in an impartial way.
• They define clear objectives and reproducible methodologies.

What is a Meta-analysis?

This form of research relies on combining statistical results from two or more existing studies. When multiple studies are addressing the same problem or question, it’s to be expected that there will be some potential for error. Most studies account for this within their results. A meta-analysis can help iron out any inconsistencies in data, as long as the studies are similar.

For instance, if your research is about the influence of the Mediterranean diet on diabetic people, between the ages of 30 and 45, but you only find a study about the Mediterranean diet in healthy people and another about the Mediterranean diet in diabetic teenagers. In this case, undertaking a meta-analysis would probably be a poor choice. You can either pursue the idea of comparing such different material, at the risk of findings that don’t really answer the review question. Or, you can decide to explore a different research method (perhaps more qualitative).

Why is meta-analysis important?

• They help improve precision about evidence since many studies are too small to provide convincing data.
• Meta-analyses can settle divergences between conflicting studies. By formally assessing the conflicting study results, it is possible to eventually reach new hypotheses and explore the reasons for controversy.
• They can also answer questions with a broader influence than individual studies. For example, the effect of a disease on several populations across the world, by comparing other modest research studies completed in specific countries or continents.

Undertaking research approaches, like systematic reviews and/or meta-analysis, involve great responsibility. They provide reliable information that has a real impact on society. Elsevier offers a number of services that aim to help researchers achieve excellence in written text, suggesting the necessary amendments to fit them into a targeted format. A perfectly written text, whether translated or edited from a manuscript, is the key to being respected within the scientific community, leading to more and more important positions like, let’s say…being part of an expert panel leading a systematic review or a widely acknowledged meta-analysis.

Check why it’s important to manage research data .

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Understanding the Differences Between a Systematic Review vs Meta Analysis

Automate every stage of your literature review to produce evidence-based research faster and more accurately.

The advent of evidence-based medicine has increased the demand for systematic methods to analyze and synthesize clinical evidence. When it comes to the search for the best available clinical evidence, randomized control trials, systematic reviews, and meta-analysis are considered the “gold standard” [1].

Since both systematic reviews and meta-analyses are secondary research approaches (research of research), sometimes the terms are used interchangeably, but there are vast differences between them.

A systematic review is a review that collects, critically appraises, and synthesizes all the available evidence to answer a specifically formulated research question.

A meta-analysis, on the other hand, is a statistical method that is used to pool results from various independent studies, to generate an overall estimate of the studied phenomenon.

Systematic reviews can sometimes use meta-analysis to synthesize their results, but they are two very distinct techniques. In this article, we will look at the definition of a systematic review , and understand how it is different from a meta-analysis.

What Is A Systematic Review?

In section 1.2.2 of the Cochrane Handbook, titled What is a systematic review?, the following definition can be found, “A systematic review attempts to collate all empirical evidence that fits the pre-specified eligibility criteria in order to answer a specific research question. It uses explicit, systematic methods that are selected with a view to minimizing bias, thus providing more reliable findings from which conclusions can be drawn and decisions made (Antman 1992, Oxman 1993). The key characteristics of a systematic review are: a clearly stated set of objectives with pre-defined eligibility criteria for the studies; an explicit, reproducible methodology; a systematic search that attempts to identify all the studies that would meet the eligibility criteria; an assessment of the validity of the findings of the included studies, for example through the assessment of the risk of bias; and a systematic presentation, and synthesis, of the characteristics and findings of the included studies”[2].

The evidence collected in a systematic review can be analyzed and synthesized, quantitatively, or qualitatively. The quantitative analysis of empirical evidence can use a meta-analysis as the statistical approach. To know more about how to write a systematic review , you can read our article; previously linked.

What Is Meta-Analysis?

Meta-analysis is a statistical method used to combine the results of individual studies. It uses a quantitative, formal, and epidemiological study design to systematically assess the results of previous studies to derive conclusions about a specific research parameter [3]. It is therefore an approach for systematically combining pertinent qualitative and quantitative study data from several included studies to establish a single conclusion that has significant statistical power.

Typically, the primary studies included in a meta-analysis are randomized controlled trials (RCTs). In a meta-analysis, the main objective is to provide more precise estimates of the effects of a treatment or of a risk factor for a disease, than any of the individual studies included in the pooled analysis. The data is also analyzed for heterogeneity (variation within outcomes), and generalizability (similarities between outcomes) within the individual studies, which facilitates more effective clinical decision making. Examining the heterogeneity of effect estimates within the primary studies is perhaps the most important task in a meta-analysis.

Meta-analyses of observational studies such as cohort studies are frequently performed, but no widely accepted guidance is available at the moment. While these meta-analyses are frequently published in literature, they are considered suboptimal to those involving RCTs.  The main reason is that the observational studies may entail an increased risk of biases and high levels of heterogeneity. Researchers who have to conduct meta-analyses on observational studies ought to carefully consider whether all included studies are able to answer the same clinical question.

Although meta-analysis is a subset of systematic reviews, a systematic review may or may not include a meta-analysis. An advantage of meta-analysis is that it has the ability to be completely objective in evaluating the research parameter. However, not all research areas have enough evidence to allow a meta-analysis. The inclusion of meta-analysis in a systematic review depends on the research question, the intervention to be studied, and the desired outcomes.

• Sur RL, Dahm P. History of evidence-based medicine. Indian journal of urology: IJU: journal of the Urological Society of India. 2011;27(4):487–9.
• Clarke M, Chalmers I. Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents? Jama. 1998;280(3):280–2.
• Haidich AB. Meta-analysis in medical research. Hippokratia. 2010;14(Suppl 1):29-37.

3 Reasons to Connect

Literature Review, Systematic Review and Meta-analysis

Literature reviews can be a good way to narrow down theoretical interests; refine a research question; understand contemporary debates; and orientate a particular research project. It is very common for PhD theses to contain some element of reviewing the literature around a particular topic. It’s typical to have an entire chapter devoted to reporting the result of this task, identifying gaps in the literature and framing the collection of additional data.

Systematic review is a type of literature review that uses systematic methods to collect secondary data, critically appraise research studies, and synthesise findings. Systematic reviews are designed to provide a comprehensive, exhaustive summary of current theories and/or evidence and published research (Siddaway, Wood & Hedges, 2019) and may be qualitative or qualitative. Relevant studies and literature are identified through a research question, summarised and synthesized into a discrete set of findings or a description of the state-of-the-art. This might result in a ‘literature review’ chapter in a doctoral thesis, but can also be the basis of an entire research project.

Meta-analysis is a specialised type of systematic review which is quantitative and rigorous, often comparing data and results across multiple similar studies. This is a common approach in medical research where several papers might report the results of trials of a particular treatment, for instance. The meta-analysis then statistical techniques to synthesize these into one summary. This can have a high statistical power but care must be taken not to introduce bias in the selection and filtering of evidence.

Whichever type of review is employed, the process is similarly linear. The first step is to frame a question which can guide the review. This is used to identify relevant literature, often through searching subject-specific scientific databases. From these results the most relevant will be identified. Filtering is important here as there will be time constraints that prevent the researcher considering every possible piece of evidence or theoretical viewpoint. Once a concrete evidence base has been identified, the researcher extracts relevant data before reporting the synthesized results in an extended piece of writing.

Literature Review: GO-GN Insights

Sarah Lambert used a systematic review of literature with both qualitative and quantitative phases to investigate the question “How can open education programs be reconceptualised as acts of social justice to improve the access, participation and success of those who are traditionally excluded from higher education knowledge and skills?”

“My PhD research used systematic review, qualitative synthesis, case study and discourse analysis techniques, each was underpinned and made coherent by a consistent critical inquiry methodology and an overarching research question. “Systematic reviews are becoming increasingly popular as a way to collect evidence of what works across multiple contexts and can be said to address some of the weaknesses of case study designs which provide detail about a particular context – but which is often not replicable in other socio-cultural contexts (such as other countries or states.) Publication of systematic reviews that are done according to well defined methods are quite likely to be published in high-ranking journals – my PhD supervisors were keen on this from the outset and I was encouraged along this path. “Previously I had explored social realist authors and a social realist approach to systematic reviews (Pawson on realist reviews) but they did not sufficiently embrace social relations, issues of power, inclusion/exclusion. My supervisors had pushed me to explain what kind of realist review I intended to undertake, and I found out there was a branch of critical realism which was briefly of interest. By getting deeply into theory and trying out ways of combining theory I also feel that I have developed a deeper understanding of conceptual working and the different ways theories can be used at all stagesof research and even how to come up with novel conceptual frameworks.”

Useful references for Systematic Review & Meta-Analysis: Finfgeld-Connett (2014); Lambert (2020); Siddaway, Wood & Hedges (2019)

Research Toolkit for Librarians Copyright © by Kathy Essmiller; Jamie Holmes; and Marla Lobley is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Systematic Reviews and Meta Analysis

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Systematic review Q & A

What is a systematic review.

A systematic review is guided filtering and synthesis of all available evidence addressing a specific, focused research question, generally about a specific intervention or exposure. The use of standardized, systematic methods and pre-selected eligibility criteria reduce the risk of bias in identifying, selecting and analyzing relevant studies. A well-designed systematic review includes clear objectives, pre-selected criteria for identifying eligible studies, an explicit methodology, a thorough and reproducible search of the literature, an assessment of the validity or risk of bias of each included study, and a systematic synthesis, analysis and presentation of the findings of the included studies. A systematic review may include a meta-analysis.

For details about carrying out systematic reviews, see the Guides and Standards section of this guide.

Is my research topic appropriate for systematic review methods?

A systematic review is best deployed to test a specific hypothesis about a healthcare or public health intervention or exposure. By focusing on a single intervention or a few specific interventions for a particular condition, the investigator can ensure a manageable results set. Moreover, examining a single or small set of related interventions, exposures, or outcomes, will simplify the assessment of studies and the synthesis of the findings.

Systematic reviews are poor tools for hypothesis generation: for instance, to determine what interventions have been used to increase the awareness and acceptability of a vaccine or to investigate the ways that predictive analytics have been used in health care management. In the first case, we don't know what interventions to search for and so have to screen all the articles about awareness and acceptability. In the second, there is no agreed on set of methods that make up predictive analytics, and health care management is far too broad. The search will necessarily be incomplete, vague and very large all at the same time. In most cases, reviews without clearly and exactly specified populations, interventions, exposures, and outcomes will produce results sets that quickly outstrip the resources of a small team and offer no consistent way to assess and synthesize findings from the studies that are identified.

If not a systematic review, then what?

You might consider performing a scoping review . This framework allows iterative searching over a reduced number of data sources and no requirement to assess individual studies for risk of bias. The framework includes built-in mechanisms to adjust the analysis as the work progresses and more is learned about the topic. A scoping review won't help you limit the number of records you'll need to screen (broad questions lead to large results sets) but may give you means of dealing with a large set of results.

This tool can help you decide what kind of review is right for your question.

Can my student complete a systematic review during her summer project?

Probably not. Systematic reviews are a lot of work. Including creating the protocol, building and running a quality search, collecting all the papers, evaluating the studies that meet the inclusion criteria and extracting and analyzing the summary data, a well done review can require dozens to hundreds of hours of work that can span several months. Moreover, a systematic review requires subject expertise, statistical support and a librarian to help design and run the search. Be aware that librarians sometimes have queues for their search time. It may take several weeks to complete and run a search. Moreover, all guidelines for carrying out systematic reviews recommend that at least two subject experts screen the studies identified in the search. The first round of screening can consume 1 hour per screener for every 100-200 records. A systematic review is a labor-intensive team effort.

How can I know if my topic has been been reviewed already?

Before starting out on a systematic review, check to see if someone has done it already. In PubMed you can use the systematic review subset to limit to a broad group of papers that is enriched for systematic reviews. You can invoke the subset by selecting if from the Article Types filters to the left of your PubMed results, or you can append AND systematic[sb] to your search. For example:

"neoadjuvant chemotherapy" AND systematic[sb]

The systematic review subset is very noisy, however. To quickly focus on systematic reviews (knowing that you may be missing some), simply search for the word systematic in the title:

"neoadjuvant chemotherapy" AND systematic[ti]

Any PRISMA-compliant systematic review will be captured by this method since including the words "systematic review" in the title is a requirement of the PRISMA checklist. Cochrane systematic reviews do not include 'systematic' in the title, however. It's worth checking the Cochrane Database of Systematic Reviews independently.

You can also search for protocols that will indicate that another group has set out on a similar project. Many investigators will register their protocols in PROSPERO , a registry of review protocols. Other published protocols as well as Cochrane Review protocols appear in the Cochrane Methodology Register, a part of the Cochrane Library .

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Reproduced from Grant, M. J. and Booth, A. (2009), A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26: 91–108. doi:10.1111/j.1471-1842.2009.00848.x

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Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare

S. gopalakrishnan.

Department of Community Medicine, SRM Medical College, Hospital and Research Centre, Kattankulathur, Tamil Nadu, India

P. Ganeshkumar

Healthcare decisions for individual patients and for public health policies should be informed by the best available research evidence. The practice of evidence-based medicine is the integration of individual clinical expertise with the best available external clinical evidence from systematic research and patient's values and expectations. Primary care physicians need evidence for both clinical practice and for public health decision making. The evidence comes from good reviews which is a state-of-the-art synthesis of current evidence on a given research question. Given the explosion of medical literature, and the fact that time is always scarce, review articles play a vital role in decision making in evidence-based medical practice. Given that most clinicians and public health professionals do not have the time to track down all the original articles, critically read them, and obtain the evidence they need for their questions, systematic reviews and clinical practice guidelines may be their best source of evidence. Systematic reviews aim to identify, evaluate, and summarize the findings of all relevant individual studies over a health-related issue, thereby making the available evidence more accessible to decision makers. The objective of this article is to introduce the primary care physicians about the concept of systematic reviews and meta-analysis, outlining why they are important, describing their methods and terminologies used, and thereby helping them with the skills to recognize and understand a reliable review which will be helpful for their day-to-day clinical practice and research activities.

Introduction

Evidence-based healthcare is the integration of best research evidence with clinical expertise and patient values. Green denotes, “Using evidence from reliable research, to inform healthcare decisions, has the potential to ensure best practice and reduce variations in healthcare delivery.” However, incorporating research into practice is time consuming, and so we need methods of facilitating easy access to evidence for busy clinicians.[ 1 ] Ganeshkumar et al . mentioned that nearly half of the private practitioners in India were consulting more than 4 h per day in a locality,[ 2 ] which explains the difficulty of them in spending time in searching evidence during consultation. Ideally, clinical decision making ought to be based on the latest evidence available. However, to keep abreast with the continuously increasing number of publications in health research, a primary healthcare professional would need to read an insurmountable number of articles every day, covered in more than 13 million references and over 4800 biomedical and health journals in Medline alone. With the view to address this challenge, the systematic review method was developed. Systematic reviews aim to inform and facilitate this process through research synthesis of multiple studies, enabling increased and efficient access to evidence.[ 1 , 3 , 4 ]

Systematic reviews and meta-analyses have become increasingly important in healthcare settings. Clinicians read them to keep up-to-date with their field and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research and some healthcare journals are moving in this direction.[ 5 ]

This article is intended to provide an easy guide to understand the concept of systematic reviews and meta-analysis, which has been prepared with the aim of capacity building for general practitioners and other primary healthcare professionals in research methodology and day-to-day clinical practice.

The purpose of this article is to introduce readers to:

• The two approaches of evaluating all the available evidence on an issue i.e., systematic reviews and meta-analysis,
• Discuss the steps in doing a systematic review,
• Introduce the terms used in systematic reviews and meta-analysis,
• Interpret results of a meta-analysis, and
• The advantages and disadvantages of systematic review and meta-analysis.

Application

What is the effect of antiviral treatment in dengue fever? Most often a primary care physician needs to know convincing answers to questions like this in a primary care setting.

To find out the solutions or answers to a clinical question like this, one has to refer textbooks, ask a colleague, or search electronic database for reports of clinical trials. Doctors need reliable information on such problems and on the effectiveness of large number of therapeutic interventions, but the information sources are too many, i.e., nearly 20,000 journals publishing 2 million articles per year with unclear or confusing results. Because no study, regardless of its type, should be interpreted in isolation, a systematic review is generally the best form of evidence.[ 6 ] So, the preferred method is a good summary of research reports, i.e., systematic reviews and meta-analysis, which will give evidence-based answers to clinical situations.

There are two fundamental categories of research: Primary research and secondary research. Primary research is collecting data directly from patients or population, while secondary research is the analysis of data already collected through primary research. A review is an article that summarizes a number of primary studies and may draw conclusions on the topic of interest which can be traditional (unsystematic) or systematic.

Terminologies

Systematic review.

A systematic review is a summary of the medical literature that uses explicit and reproducible methods to systematically search, critically appraise, and synthesize on a specific issue. It synthesizes the results of multiple primary studies related to each other by using strategies that reduce biases and random errors.[ 7 ] To this end, systematic reviews may or may not include a statistical synthesis called meta-analysis, depending on whether the studies are similar enough so that combining their results is meaningful.[ 8 ] Systematic reviews are often called overviews.

The evidence-based practitioner, David Sackett, defines the following terminologies.[ 3 ]

• Review: The general term for all attempts to synthesize the results and conclusions of two or more publications on a given topic.
• Overview: When a review strives to comprehensively identify and track down all the literature on a given topic (also called “systematic literature review”).
• Meta-analysis: A specific statistical strategy for assembling the results of several studies into a single estimate.

Systematic reviews adhere to a strict scientific design based on explicit, pre-specified, and reproducible methods. Because of this, when carried out well, they provide reliable estimates about the effects of interventions so that conclusions are defensible. Systematic reviews can also demonstrate where knowledge is lacking. This can then be used to guide future research. Systematic reviews are usually carried out in the areas of clinical tests (diagnostic, screening, and prognostic), public health interventions, adverse (harm) effects, economic (cost) evaluations, and how and why interventions work.[ 9 ]

Cochrane reviews

Cochrane reviews are systematic reviews undertaken by members of the Cochrane Collaboration which is an international not-for-profit organization that aims to help people to make well-informed decisions about healthcare by preparing, maintaining, and promoting the accessibility of systematic reviews of the effects of healthcare interventions.

Cochrane Primary Health Care Field is a systematic review of primary healthcare research on prevention, treatment, rehabilitation, and diagnostic test accuracy. The overall aim and mission of the Primary Health Care Field is to promote the quality, quantity, dissemination, accessibility, applicability, and impact of Cochrane systematic reviews relevant to people who work in primary care and to ensure proper representation in the interests of primary care clinicians and consumers in Cochrane reviews and review groups, and in other entities. This field would serve to coordinate and promote the mission of the Cochrane Collaboration within the primary healthcare disciplines, as well as ensuring that primary care perspectives are adequately represented within the Collaboration.[ 10 ]

Meta-analysis

A meta-analysis is the combination of data from several independent primary studies that address the same question to produce a single estimate like the effect of treatment or risk factor. It is the statistical analysis of a large collection of analysis and results from individual studies for the purpose of integrating the findings.[ 11 ] The term meta-analysis has been used to denote the full range of quantitative methods for research reviews.[ 12 ] Meta-analyses are studies of studies.[ 13 ] Meta-analysis provides a logical framework to a research review where similar measures from comparable studies are listed systematically and the available effect measures are combined wherever possible.[ 14 ]

The fundamental rationale of meta-analysis is that it reduces the quantity of data by summarizing data from multiple resources and helps to plan research as well as to frame guidelines. It also helps to make efficient use of existing data, ensuring generalizability, helping to check consistency of relationships, explaining data inconsistency, and quantifies the data. It helps to improve the precision in estimating the risk by using explicit methods.

Therefore, “systematic review” will refer to the entire process of collecting, reviewing, and presenting all available evidence, while the term “meta-analysis” will refer to the statistical technique involved in extracting and combining data to produce a summary result.[ 15 ]

Steps in doing systematic reviews/meta-analysis

Following are the six fundamental essential steps while doing systematic review and meta-analysis.[ 16 ]

Define the question

This is the most important part of systematic reviews/meta-analysis. The research question for the systematic reviews may be related to a major public health problem or a controversial clinical situation which requires acceptable intervention as a possible solution to the present healthcare need of the community. This step is most important since the remaining steps will be based on this.

Reviewing the literature

This can be done by going through scientific resources such as electronic database, controlled clinical trials registers, other biomedical databases, non-English literatures, “gray literatures” (thesis, internal reports, non–peer-reviewed journals, pharmaceutical industry files), references listed in primary sources, raw data from published trials and other unpublished sources known to experts in the field. Among the available electronic scientific database, the popular ones are PUBMED, MEDLINE, and EMBASE.

Sift the studies to select relevant ones

To select the relevant studies from the searches, we need to sift through the studies thus identified. The first sift is pre-screening, i.e., to decide which studies to retrieve in full, and the second sift is selection which is to look again at these studies and decide which are to be included in the review. The next step is selecting the eligible studies based on similar study designs, year of publication, language, choice among multiple articles, sample size or follow-up issues, similarity of exposure, and or treatment and completeness of information.

It is necessary to ensure that the sifting includes all relevant studies like the unpublished studies (desk drawer problem), studies which came with negative conclusions or were published in non-English journals, and studies with small sample size.

Assess the quality of studies

The steps undertaken in evaluating the study quality are early definition of study quality and criteria, setting up a good scoring system, developing a standard form for assessment, calculating quality for each study, and finally using this for sensitivity analysis.

For example, the quality of a randomized controlled trial can be assessed by finding out the answers to the following questions:

• Was the assignment to the treatment groups really random?
• Was the treatment allocation concealed?
• Were the groups similar at baseline in terms of prognostic factors?
• Were the eligibility criteria specified?
• Were the assessors, the care provider, and the patient blinded?
• Were the point estimates and measure of variability presented for the primary outcome measure?
• Did the analyses include intention-to-treat analysis?

Calculate the outcome measures of each study and combine them

We need a standard measure of outcome which can be applied to each study on the basis of its effect size. Based on their type of outcome, following are the measures of outcome: Studies with binary outcomes (cured/not cured) have odds ratio, risk ratio; studies with continuous outcomes (blood pressure) have means, difference in means, standardized difference in means (effect sizes); and survival or time-to-event data have hazard ratios.

Combining studies

Homogeneity of different studies can be estimated at a glance from a forest plot (explained below). For example, if the lower confidence interval of every trial is below the upper of all the others, i.e., the lines all overlap to some extent, then the trials are homogeneous. If some lines do not overlap at all, these trials may be said to be heterogeneous.

The definitive test for assessing the heterogeneity of studies is a variant of Chi-square test (Mantel–Haenszel test). The final step is calculating the common estimate and its confidence interval with the original data or with the summary statistics from all the studies. The best estimate of treatment effect can be derived from the weighted summary statistics of all studies which will be based on weighting to sample size, standard errors, and other summary statistics. Log scale is used to combine the data to estimate the weighting.

Interpret results: Graph

The results of a meta-analysis are usually presented as a graph called forest plot because the typical forest plots appear as forest of lines. It provides a simple visual presentation of individual studies that went into the meta-analysis at a glance. It shows the variation between the studies and an estimate of the overall result of all the studies together.

Forest plot

Meta-analysis graphs can principally be divided into six columns [ Figure 1 ]. Individual study results are displayed in rows. The first column (“study”) lists the individual study IDs included in the meta-analysis; usually the first author and year are displayed. The second column relates to the intervention groups and the third column to the control groups. The fourth column visually displays the study results. The line in the middle is called “the line of no effect.” The weight (in %) in the fifth column indicates the weighting or influence of the study on the overall results of the meta-analysis of all included studies. The higher the percentage weight, the bigger the box, the more influence the study has on the overall results. The sixth column gives the numerical results for each study (e.g., odds ratio or relative risk and 95% confidence interval), which are identical to the graphical display in the fourth column. The diamond in the last row of the graph illustrates the overall result of the meta-analysis.[ 4 ]

Interpretation of meta-analysis[ 4 ]

Thus, the horizontal lines represent individual studies. Length of line is the confidence interval (usually 95%), squares on the line represent effect size (risk ratio) for the study, with area of the square being the study size (proportional to weight given) and position as point estimate (relative risk) of the study.[ 7 ]

For example, the forest plot of the effectiveness of dexamethasone compared with placebo in preventing the recurrence of acute severe migraine headache in adults is shown in Figure 2 .[ 17 ]

Forest plot of the effectiveness of dexamethasone compared with placebo in preventing the recurrence of acute severe migraine headache in adults[ 17 ]

The overall effect is shown as diamond where the position toward the center represents pooled point estimate, the width represents estimated 95% confidence interval for all studies, and the black plain line vertically in the middle of plot is the “line of no effect” (e.g., relative risk = 1).

Therefore, when examining the results of a systematic reviews/meta-analysis, the following questions should be kept in mind:

• Heterogeneity among studies may make any pooled estimate meaningless.
• The quality of a meta-analysis cannot be any better than the quality of the studies it is summarizing.
• An incomplete search of the literature can bias the findings of a meta-analysis.
• Make sure that the meta-analysis quantifies the size of the effect in units that you can understand.

Subgroup analysis and sensitivity analysis

Subgroup analysis looks at the results of different subgroups of trials, e.g., by considering trials on adults and children separately. This should be planned at the protocol stage itself which is based on good scientific reasoning and is to be kept to a minimum.

Sensitivity analysis is used to determine how results of a systematic review/meta-analysis change by fiddling with data, for example, what is the implication if the exclusion criteria or excluded unpublished studies or weightings are assigned differently. Thus, after the analysis, if changing makes little or no difference to the overall results, the reviewer's conclusions are robust. If the key findings disappear, then the conclusions need to be expressed more cautiously.

Advantages of Systematic Reviews

Systematic reviews have specific advantages because of using explicit methods which limit bias, draw reliable and accurate conclusions, easily deliver required information to healthcare providers, researchers, and policymakers, help to reduce the time delay in the research discoveries to implementation, improve the generalizability and consistency of results, generation of new hypotheses about subgroups of the study population, and overall they increase precision of the results.[ 18 ]

Limitations in Systematic Reviews/Meta-analysis

As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers’ ability to assess the strengths and weaknesses of those reviews.[ 5 ]

Even though systematic review and meta-analysis are considered the best evidence for getting a definitive answer to a research question, there are certain inherent flaws associated with it, such as the location and selection of studies, heterogeneity, loss of information on important outcomes, inappropriate subgroup analyses, conflict with new experimental data, and duplication of publication.

Publication Bias

Publication bias results in it being easier to find studies with a “positive” result.[ 19 ] This occurs particularly due to inappropriate sifting of the studies where there is always a tendency towards the studies with positive (significant) outcomes. This effect occurs more commonly in systematic reviews/meta-analysis which need to be eliminated.

The quality of reporting of systematic reviews is still not optimal. In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias even though there is overwhelming evidence both for its existence and its impact on the results of systematic reviews. Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or interpreted it appropriately.[ 20 ]

To overcome certain limitations mentioned above, the Cochrane reviews are currently reported in a format where at the end of every review, findings are summarized in the author's point of view and also give an overall picture of the outcome by means of plain language summary. This is found to be much helpful to understand the existing evidence about the topic more easily by the reader.

A systematic review is an overview of primary studies which contains an explicit statement of objectives, materials, and methods, and has been conducted according to explicit and reproducible methodology. A meta-analysis is a mathematical synthesis of the results of two or more primary studies that addressed the same hypothesis in the same way. Although meta-analysis can increase the precision of a result, it is important to ensure that the methods used for the reviews were valid and reliable.

High-quality systematic reviews and meta-analyses take great care to find all relevant studies, critically assess each study, synthesize the findings from individual studies in an unbiased manner, and present balanced important summary of findings with due consideration of any flaws in the evidence. Systematic review and meta-analysis is a way of summarizing research evidence, which is generally the best form of evidence, and hence positioned at the top of the hierarchy of evidence.

Systematic reviews can be very useful decision-making tools for primary care/family physicians. They objectively summarize large amounts of information, identifying gaps in medical research, and identifying beneficial or harmful interventions which will be useful for clinicians, researchers, and even for public and policymakers.

Source of Support: Nil

Conflict of Interest: None declared.

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The difference between a systematic review and a meta-analysis

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Covidence explains the difference between systematic review & meta-analysis.

Systematic review and meta-analysis are two terms that you might see used interchangeably. Each term refers to research about research, but there are important differences!

A systematic review is a piece of work that asks a research question and then answers it by summarising the evidence that meets a set of pre-specified criteria. Some systematic reviews present their results using meta-analysis, a statistical method that combines the results of several trials to generate an average result. Meta-analysis adds value because it can produce a more precise estimate of the effect of a treatment than considering each study individually 🎯.

Let’s take a look at a few related questions that you might have about systematic reviews and meta-analysis.

🙋🏽‍♂️ What are the stages of a systematic review?

A systematic review starts with a research question and a protocol or research plan. A review team searches for studies to answer the question using a highly sensitive search strategy. The retrieved studies are then screened for eligibility using the inclusion and exclusion criteria (this is done by at least two people working independently). Next, the reviewers extract the relevant data and assess the quality of the included studies. Finally, the review team synthesises the extracted study data (perhaps using meta-analysis) and presents the results. The process is shown in figure 1.

Covidence helps researchers complete systematic review quickly and easily! It supports reviewers with study selection, data extraction and quality assessment. Data exported from Covidence can be saved in Excel for reliable transfer to your choice of data analysis software or, if you’re writing a Cochrane Review, to RevMan 5.

🙋🏻‍♀️ What does 'systematic' actually mean?

In this context, systematic means that the methods used to search for and analyse the data are

transparent, reproducible and defined before searching begins. This is what differentiates a systematic review from a descriptive review that might be based on, for example, a subset of the literature that the author is familiar with at the time of writing. Systematic reviews strive to be as thorough and rigorous as possible to minimise the bias that would result from cherry-picking studies in a non-systematic way. Systematic reviews sit at the top of the evidence hierarchy because it is widely agreed that studies with rigorous methods are those best able to minimise the risk of bias on the results of the study. This is what makes systematic reviews the most reliable form of evidence (see figure 2). 

🙋🏾‍♂️ Why don't all systematic reviews use meta-analysis?

Meta-analysis can improve the precision of an effect estimate. But it can also be misleading if it is performed with data that are not sufficiently similar, or with data whose methodological quality is poor (for example, because the study participants were not properly randomized). So it’s not always appropriate to use meta-analysis and many systematic reviews do not include them. Reviews that do not contain meta-analysis can still synthesise study data to produce something that has greater value than the sum of its parts.

🙋🏾‍♀️ What does meta-analysis do?

Meta-analysis produces a more precise estimate of treatment effect. There are several types of effect size and the most suitable type is chosen by the review team based on the type of outcomes and interventions under investigation. Typical effect sizes in systematic reviews are the odds ratio, the risk ratio, the weighted mean difference and the standardized mean difference. The results of a meta-analysis are displayed using a forest plot like the one in figure 3.

Some meta-analyses also include subgroup analysis or meta-regression. These techniques are used to explore a factor (for example, the age of the study participant) that might influence the relationship between the treatment and the intervention. Plans to analyse the data using these techniques should be described and justified before looking at the data, ideally at the research plan or protocol stage, to avoid introducing bias. Like meta-analysis, subgroup analysis and meta-regression are advisable only in certain circumstances.

Systematic reviewer pro-tip

  Think carefully before you plan subgroup analysis or meta-regression and always ask a methodologist for advice

🙋🏼‍♀️ What are the other ways to synthesise evidence?

Systematic reviews combine study data in a number of ways to reach an overall understanding of the evidence. Meta-analysis is a type of statistical synthesis. Narrative synthesis combines the findings of multiple studies using words. All systematic reviews, including those that use meta-analysis, are likely to contain an element of narrative synthesis by summarising in words the evidence included in the review. But narrative synthesis doesn’t just describe the included studies: it also seeks to explain the gathered evidence, for example by looking at similarities and differences between the study findings and by exploring possible reasons for those similarities and differences in a systematic way. Narrative synthesis should not be confused with narrative review, which is a term sometimes used for a non-systematic review of the literature (for example in a textbook chapter) where there is no systematic attempt to address issues of bias.

There are many types of systematic review . What they all have in common is the use of transparent and reproducible methods that are defined before the search begins. There is no ‘best’ way to synthesise systematic review evidence, and the most suitable approach will depend on factors such as the nature of the review question, the type of intervention and the outcomes of interest.

Covidence is a web-based tool that saves you time at the screening, selection, data extraction and quality assessment stages of your review. It provides easy collaboration across teams and a clear overview of task status, helping you to efficiently complete your review. Sign up for a free trial today! 😀

1 Effectiveness of psychosocial interventions for reducing parental substance misuse – McGovern, R – 2021 | Cochrane Library https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD012823.pub2/full .  Accessed 25 March 2021

Laura Mellor. Portsmouth, UK

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Systematic reviews.

• Getting Started with Systematic Reviews

What is a Systematic Review and Meta-Analysis

Differences between systematic and literature reviews.

• Finding and Evaluating Existing Systematic Reviews
• Steps in a Systematic Review
• Step 1: Developing a Question
• Step 2: Selecting Databases
• Step 3: Grey Literature
• Step 4: Registering a Systematic Review Protocol
• Step 5: Translate Search Strategies
• Step 6: Citation Management Tools
• Step 7: Article Screening
• Other Resources
• Interlibrary Loan (ILL)

A systematic review collects and analyzes all evidence that answers a specific research question. In a systematic review, a question needs to be clearly defined and have inclusion and exclusion criteria. In general, specific and systematic methods selected are intended to minimize bias. This is followed by an extensive search of the literature and a critical analysis of the search results. The reason why a systematic review is conducted is to provide a current evidence-based answer to a specific question that in turn helps to inform decision making. Check out the Centers for Disease Control and Prevention and Cochrane Reviews links to learn more about Systematic Reviews.

A systematic review can be combined with a meta-analysis. A meta-analysis is the use of statistical methods to summarize the results of a systematic review. Not every systematic review contains a meta-analysis. A meta-analysis may not be appropriate if the designs of the studies are too different, if there are concerns about the quality of studies, if the outcomes measured are not sufficiently similar for the result across the studies to be meaningful.

Centers for Disease Control and Prevention. (n.d.).  Systematic Reviews . Retrieved from  https://www.cdc.gov/library/researchguides/sytemsaticreviews.html

Cochrane Library. (n.d.).  About Cochrane Reviews . Retrieved from  https://www.cochranelibrary.com/about/about-cochrane-reviews

Source: Kysh, Lynn (2013): Difference between a systematic review and a literature review. [figshare]. Available at:  https://figshare.com/articles/Difference_between_a_systematic_review_and_a_literature_review/766364

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Basics of Systematic Reviews

• About Systematic Review

Types of Reviews

Literature review.

Collects key sources on a topic and discusses those sources in conversation with each other

• Standard for research articles in most disciplines
• Tells the reader what is known, or not known, about a particular issue, topic, or subject
• Demonstrates knowledge and understanding of a topic
• Establishes context or background for a case or argument
• Helps develop the author’s ideas and perspective

Rapid Review

Thorough methodology but with process limitations in place to expeditethe completion of a review.

• For questions that require timely answers
• 3-4 months vs. 12-24 months
• Limitations - scope, comprehensiveness bias, and quality of appraisal
• Discusses potential effects that the limited methods may have had on results

Scoping Review

Determine the scope or coverage of a body of literature on a given topic and give clear indication of the volume of literature and studies available as well as an overview of its focus.

• Identify types of available evidence in a given field
• Clarify key concepts/definitions in the literature
• Examine how research is conducted on a certain topic or field
• Identify key factors related to a concept
• Key difference is focus
• Identify and analyze knowledge gaps

Systematic Review

Attempts to identify, appraise, and summarize all empirical evidence that fits pre-specified eligibility criteria to answer a specific research question.

• clearly defined question with inclusion/exclusion criteria
• rigorous and systematic search of the literature
• thorough screening of results
• data extraction and management
• analysis and interpretation of results
• risk of bias assessment of included studies

Meta-Analysis

Used to systematically synthesize or merge the findings of single, independent studies, using statistical methods to calculate an overall or ‘absolute’ effect.

• Combines results from multiple empirical studies
• Requires systematic review first
• Use well recognized, systematic methods to account for differences in sample size, variability (heterogeneity) in study approach and findings (treatment effects)
• Test how sensitive their results are to their own systematic review protocol

For additional types of reviews please see these articles:

• Sutton, A., Clowes, M., Preston, L. and Booth, A. (2019), Meeting the review family: exploring review types and associated information retrieval requirements. Health Info Libr J, 36: 202-222. https://doi.org/10.1111/hir.12276
• Grant, M.J. and Booth, A. (2009), A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26: 91-108. https://doi.org/10.1111/j.1471-1842.2009.00848.x
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Mortality burden of pre-treatment weight loss in patients with non-small-cell lung cancer: A systematic literature review and meta-analysis.

Cachexia, with weight loss (WL) as a major component, is highly prevalent in patients with cancer and indicates a poor prognosis. The primary objective of this study was to conduct a meta-analysis to estimate the risk of mortality associated with cachexia (using established WL criteria prior to treatment initiation) in patients with non-small-cell lung cancer (NSCLC) in studies identified through a systematic literature review. The review was conducted according to PRISMA guidelines. Embase® and PubMed were searched to identify articles on survival outcomes in adult patients with NSCLC (any stage) and cachexia published in English between 1 January 2016 and 10 October 2021. Two independent reviewers screened titles, abstracts and full texts of identified records against predefined inclusion/exclusion criteria. Following a feasibility assessment, a meta-analysis evaluating the impact of cachexia, defined per the international consensus criteria (ICC), or of pre-treatment WL ≥ 5% without a specified time interval, on overall survival in patients with NSCLC was conducted using a random-effects model that included the identified studies as the base case. The impact of heterogeneity was evaluated through sensitivity and subgroup analyses. The standard measures of statistical heterogeneity were calculated. Of the 40 NSCLC publications identified in the review, 20 studies that used the ICC for cachexia or reported WL ≥ 5% and that performed multivariate analyses with hazard ratios (HRs) or Kaplan-Meier curves were included in the feasibility assessment. Of these, 16 studies (80%; n = 6225 patients; published 2016-2021) met the criteria for inclusion in the meta-analysis: 11 studies (69%) used the ICC and 5 studies (31%) used WL ≥ 5%. Combined criteria (ICC plus WL ≥ 5%) were associated with an 82% higher mortality risk versus no cachexia or WL < 5% (pooled HR [95% confidence interval, CI]: 1.82 [1.47, 2.25]). Although statistical heterogeneity was high (I2 = 88%), individual study HRs were directionally aligned with the pooled estimate, and there was considerable overlap in CIs across included studies. A subgroup analysis of studies using the ICC (HR [95% CI]: 2.26 [1.80, 2.83]) or WL ≥ 5% (HR [95% CI]: 1.28 [1.12, 1.46]) showed consistent findings. Assessments of methodological, clinical and statistical heterogeneity indicated that the meta-analysis was robust. Overall, this analysis found that ICC-defined cachexia or WL ≥ 5% was associated with inferior survival in patients with NSCLC. Routine assessment of both weight and weight changes in the oncology clinic may help identify patients with NSCLC at risk for worse survival, better inform clinical decision-making and assess eligibility for cachexia clinical trials.

Duke Scholars

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• 4207 Sports science and exercise
• 4201 Allied health and rehabilitation science
• 3202 Clinical sciences
• 1106 Human Movement and Sports Sciences
• 1103 Clinical Sciences
• 0606 Physiology

• Open access
• Published: 18 May 2024

Medical radiation exposure in inflammatory bowel disease: an updated meta-analysis

• Chao Lu 1 ,
• Xin Yao 1 ,
• Mosang Yu 1 &
• Xinjue He 1  

BMC Gastroenterology volume  24 , Article number:  173 ( 2024 ) Cite this article

187 Accesses

Metrics details

There have been previous studies and earlier systematic review on the relationship between inflammatory bowel disease (IBD) and radiation exposure. With the diversification of current test methods, this study intended to conduct a meta-analysis to evaluate the IBD radiation exposure in recent years.

Three databases (PUBMED, EMBASE, and MEDICINE) for relevant literature up to May 1, 2023 were searched. The statistical data meeting requirements were collated and extracted.

20 papers were enrolled. The overall high radiation exposure rate was 15% (95% CI = [12%, 19%]) for CD and 5% (95% CI = [3%, 7%]) for UC. The pooled result found that high radiation exposure rate was 3.44 times higher in CD than in UC (OR = 3.44, 95% CI = [2.35, 5.02]). Moreover, the average radiation exposure level in CD was 12.77 mSv higher than that in UC (WMD = 12.77, 95% CI = [9.93, 15.62] mSv). Furthermore, radiation exposure level of CD after 2012 was higher than those before 2012 (26.42 ± 39.61vs. 23.76 ± 38.46 mSv, P  = 0.016), while UC did not show similar result (11.99 ± 27.66 vs. 10.01 ± 30.76 mSv, P  = 0.1). Through subgroup analysis, it was found that disease duration (WMD = 2.75, 95% CI = [0.10, 5.40] mSv), complications (OR = 5.09, 95% CI = [1.50, 17.29]), and surgical history (OR = 5.46, 95% CI = [1.51, 19.69]) significantly increased the proportion of high radiation exposure.

This study found that radiation exposure level of IBD patients was high, which revealed the radiation risk in the process of diagnosis and treatment of IBD patients. In the future, longer follow-up and prospective studies are needed to reveal the relationship between high radiation exposure and solid tumorigenesis.

Peer Review reports

Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), refers to a group of lifelong idiopathic disorders characterized by gastrointestinal inflammation and extra-intestinal manifestations [ 1 ]. The incidence and prevalence of IBD is increasing worldwide especially in Asia, while it is still highest among developed countries in Europe and America [ 2 ]. Due to the unclear pathogenesis and the complexity of treatment, IBD has a significant disease and economic burden [ 3 ]. The diagnosis of IBD is a difficult and complicated process. In addition to gastrointestinal endoscopy, repeated imaging tests are also required, especially for the diagnosis of CD, which needs to assess the extent and severity of the disease, and the presence of complications [ 4 ]. Therefore, the assessment of radiation exposure is very important.

IBD itself increases the risk of intestinal tumors [ 5 , 6 ], and the use of drugs such as azathioprine, other immunosuppressive agents and biological agents will increase the risk of malignant tumors such as lymphoma [ 7 ]. In addition, exposure to ionizing radiation may potentially increase the risk of malignancy [ 8 ]. Radiation exposure as low as 50 millisieverts (mSv) has been associated with the development of certain solid tumors such as colon, bladder cancer [ 9 ]. Globally, up to 2% of malignancies can be attributed to diagnostic medical radiation (DMR) [ 10 ]. Although some clinicians believe that DMR exposure is indeed a potential risk, the actual exposure of IBD patients in clinical practice still lacks sufficient multicenter large sample data to support, that leads to many concerns for patients, such as whether they are exposed to excessive DMR. Previous meta-analysis study have shown that IBD patients do have higher DMR [ 11 ]. With the continuous development of medical technology, such as the application of MRI and intestinal ultrasound, it is not clear whether DMR has changed from before.

Therefore, it is important to conduct this study to update our current knowledge by meta-analysis to analyze relevant studies found to date, especially recent studies, to determine the pooled prevalence of increased exposure in IBD patients and risk factors associated with exposure to potentially harmful ionizing levels.

Data selection

We searched three databases (PUBMED, EMBASE, and MEDICINE) for relevant literature up to May 1, 2023. Literature search limited to human studies and English version, including prospective and retrospective studies. The following search terms were used to retrieve potential articles: ((Inflammatory Bowel Disease) OR (IBD) OR (Crohn’s disease) OR (CD) OR (ulcerative colitis) OR (UC)) AND ((radiation exposure) OR (radiation injuries) OR (medical radiation)).

The search was independently performed by 2 authors according to title and abstract, and full text was retrieved if it met the requirement. In addition, disagreement would be evaluated by a third author independently.

Inclusion criteria and quality assessment

The diagnosis of IBD was based on symptoms, imaging, and histopathology [ 12 ]. High diagnostic medical radiation exposure was defined as ≥ 50 mSv. In addition, sufficient data for calculation were needed for inclusion in the study. STROBE checklist was used to assess Quality assessment and risk of bias for the studies included [ 13 ]. Moreover, the work was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [ 14 ].

Data extraction

Relevant data from every included study according to the unified standard were extracted by two independent authors and then they proceeded to cross-check the results. The extracted data contained author, country or region, published year, number of subjects, radiation exposure dose, number of high diagnostic medical radiation exposure and factors affecting radiation exposure. Agreement between the investigators was greater than 95%, and differences between the datasets were resolved by discussion.

Statistical analysis

Continuous variables were expressed as mean and standard deviation, and dichotomous variables were described by odds ratio (OR) and 95% confidence interval (CI). Heterogeneity of the data was quantified with the I 2 statistic and assessed by Cochran’s Q statistic. In this study, when heterogeneity was less than 50%, the pooled estimates were obtained using the fixed-model (Mantel and Haenszel) method. On the contrary, the random-model (M-H heterology) method was chosen if heterogeneity was more than 50% [ 15 ]. This study compared the following: difference in radiation exposure between CD and UC; difference in high diagnostic medical radiation exposure between CD and UC; difference in radiation exposure of CD and UC patients before and after 2012 (According to the articles, it can be basically determined that articles after 2012 did not overlap the count of CT before), and the difference in radiation exposure under different influencing factors including disease duration, gender, complications, surgical history and medication. In addition, sensitivity analysis was used to evaluate whether the results were reliable. Begg’s test was conducted to estimate publication bias with a value of P  > 0.05 suggesting no publication bias. All data analysis methods involved in this study were implemented through STATA 15 (StataCorp., College Station, Tex, USA).

Basic characteristics

A total of 3894 relevant articles were screened, of which 20 papers were enrolled finally according to inclusion criteria. The flowchart has been schematically outlined in Fig.  1 which described the process of the study selection. 20 articles all referred to CD, and 15 of them referred to radiation exposure of UC. The included population of 17 articles came from Europe and the United States. Of the 20 articles reporting on CD, 17 mentioned average radiation exposure values, 16 mentioned numbers of high diagnostic medical radiation exposure, and 13 articles were published after 2012. Of the 15 articles reporting on UC, 13 mentioned average radiation exposure values, 12 mentioned numbers of high diagnostic medical radiation exposure, and 9 articles were published after 2012. UC did not perform subgroup analysis on influencing factors due to lack of literature support. About CD, 3 referred to disease duration, 3 referred to gender, 3 referred to complications, 4 referred to surgical history, and 3 referred to medication.

Flowchart of articles selected

Radiation exposure in CD and UC patients

The total number and number of individuals with high radiation exposure of CD was 32,963 and 5181 respectively, and the average radiation exposure level was 26.31 mSv (Table  1 ). At the same time, The total number and number of individuals with high radiation exposure of UC was 34,854 and 2147 respectively, and the average radiation exposure level was 11.97 mSv (Table  2 ). Combining rates by meta-analysis found that the overall high radiation exposure rate was 15% (95% CI = [12%, 19%]) for CD (Fig.  2 A) and 5% (95% CI = [3%, 7%]) for UC (Fig.  2 B). The pooled result of meta-analysis found that high radiation exposure rate was 3.44 times higher in CD than in UC (OR = 3.44, 95% CI = [2.35, 5.02]) (Fig.  3 A). Moreover, the pooled results of meta-analysis showed that the average radiation exposure level in CD was 12.77 mSv higher than that in UC (WMD = 12.77, 95% CI = [9.93, 15.62] mSv) (Fig.  3 B).

Forest plot showed event rate defined as proportion of patients exposed to high diagnostic medical radiation exposure ≥ 50 mSv in CD and UC patients

Forest plot showed the difference between radiation exposure level and high radiation exposure odds ratios between CD and UC

Furthermore, we compared whether there was a difference in radiation exposure level before and after 2012 in order to judge whether the increase in imaging methods in recent years has affected radiation exposure. 11 articles on CD were published after 2012, while 6 articles were published before 2012 (Table  1 ). The pooled radiation exposure level was 26.42 ± 39.61 mSv after 2012 and 23.76 ± 38.46 mSv before 2012, and there was a statistical difference between two groups ( P  = 0.016). In addition, high radiation exposure rate was 16.10% after 2012 and 12.25% before 2012, and it also had statistical difference ( P  < 0.01). However, UC did not show similar results. 8 articles were published after 2012, while 5 articles were published before 2012 (Table  2 ). The pooled radiation exposure level was 11.99 ± 27.66 mSv after 2012 and 10.01 ± 30.76 mSv before 2012, and high radiation exposure rate was 6.64% after 2012 and 4.30% before 2012. Neither parameter had statistical difference ( P  = 0.1 and P  = 0.62, respectively).

Finally, the study analyzed factors affecting radiation exposure. Due to lack of data, we only analyzed the influencing factors of CD. Disease duration, gender, complications, surgical history, and medication were the factors for our analysis. Through subgroup analysis, it was found that disease duration (WMD = 2.75, 95% CI = [0.10, 5.40] mSv), complications (OR = 5.09, 95% CI = [1.50, 17.29]), and surgical history (OR = 5.46, 95% CI = [1.51, 19.69]) significantly increased the proportion of high radiation exposure, while gender (OR = 1.16, 95% CI = [0.76, 1.77]) and medication (OR = 1.75, 95% CI = [0.99, 3.11]) had no effect. (Fig.  4 )

Forest plot showed odds ratio of risk factors of high radiation exposure grouped according to exposure

Funnel plot analyses of studies assessing radiation exposure revealed no significant publication bias ( P  > 0.05). Sensitivity analysis showed that although some results were fluctuant, the overall results were stable and reliable.

This updated meta-analysis showed that radiation exposure of IBD patients was significantly increased, and the proportion of patients with high radiation exposure was also significantly increased. In addition, radiation exposure level of CD patients was significantly higher than that of UC patients, and the high radiation exposure of CD was related to disease duration, complications and surgical history.

Radiation exposure in IBD patients was significantly higher, which was depended on the course of diagnosis and treatment of the disease. Especially for CD patients, because the entire digestive tract may be involved, doctors need to conduct a comprehensive evaluation, especially the evaluation of the small intestine, which requires the use of small intestine CT and abdominal CT. It reported that incidence and mortality of solid cancer were positively associated with higher radiation dose and younger age of exposure [ 16 ]. And it has been reported that ionising radiation levels as low as 50 mSv have been contributed to the development of solid tumors [ 9 ]. Based on the results of this study and the characteristics of IBD patients with young age of onset and high radiation exposure [ 17 ], we believed that IBD patients may be exposed to an environment with a higher tumor incidence. So what can be done to reduce the risk of solid tumors in patients with IBD? First, we could propose the creation of an IBD patient radiation diary to record total radiation exposure and increase physician awareness of patient exposure to ionizing radiation [ 18 ]. Second, in tertiary care institutions, the frequency of magnetic resonance enterography (MRE) examinations can be increased to replace CT enterography (CTE). MRE is used to obtain cross-sectional imaging of small bowel without exposure to DMR, which can show the inflammation and fibrotic bowel wall in detail [ 19 ]. In a prospective study, Fiorino et al. found that MRE and CTE were similar accuracy in localizing CD, bowel wall enhancement, enteroenteric fistula, and MRE was superior to CTE for assessing strictures and bowel wall thickening [ 20 ]. Therefore, European Crohn’s and Colitis Organisation advocate increased routine usage of MRI for the assessment of small bowel CD [ 21 ]. According to the results of this study, why do the articles published in recent years showed that radiation exposure dose of IBD was higher than before. The authors believed that there were many reasons for this. First, the popularity of MRE is still only available in large general hospitals. Therefore, CTE remains the primary usage of IBD examination. Second, with the tense medical environment, doctors are more careful to deal with complications that may occur at any time during the diagnosis and treatment of patients and pay more attention to the efficacy of patients, so the frequency of examinations may be increased. Finally, Although the article was published in recent years, the patients included in the article may go back several years.

The results of this study showed that disease duration, complications and surgical history were associated with high radiation exposure, which was clearly closely related to the diagnosis and follow-up of the disease. The earlier the onset, the earlier the initial exposure. In addition, complications and surgical history have also added additional imaging tests to assess the severity of the disease. CT imaging offers advantages of rapid acquisition of images, high sensitivity, widespread availability, and specificity for the detection of intestinal and extra-intestinal disease [ 22 ]. Combined with the improved visualization of the small bowel mucosa by CTE, the assessment of small bowel disease activity is more accurate [ 23 ]. However, previous studies have shown that the role of CT in assessing intestinal disease activity may be limited [ 24 ]. In turn, radiation-induced cancer occurs in 1/1000 patients who undergo at least10 mSv CT scan [ 25 ]. Therefore, the appropriate imaging examination methods and frequency in the process of IBD diagnosis and treatment still require doctors to pay close attention.

On the basis of previous studies, this study has carried out a more detailed and systematic study and obtained more convincing results, but there were still some shortcomings needed to be pointed out. First, this study included data from multiple centers, which can lead to patient heterogeneity. Although sensitivity analysis showed the overall results were stable and reliable, the existence of heterogeneity still made this study only select random effect model for data analysis. The inconsistency of equipment models in different centers, the inconsistency of doctors’ cognition of diseases, and the compliance of patients would all affect the total radiation exposure. Moreover, this study has conducted extensive screening of papers. But based on the data provided by the published papers, the data of some included papers was not complete. We also asked the authors about the data through email, but unfortunately there was no reply. Additionally, the estimated radiation dose may be greater or less than the actual exposure. It is also possible that tests performed at other centers may not have been captured, leading to underestimate the total radiation dose. Second, we lacked studies with large sample data. Some studies included limited patients, which affected the reliability of the results. In particular, in the subgroup analysis of high exposure risk factors, the number of articles and patients included was limited, so the reliability of the results was limited. Finally, we lacked longer-term follow-up and prospective studies to analyze the risk of solid tumor development in high radiation exposure patients. The emergence of such results will have important guiding significance for the selection of imaging examinations in the process of IBD diagnosis and treatment.

In conclusion, this study found that radiation exposure level of IBD patients was high, and exposure level of CD patients was higher than UC, which revealed the radiation risk in the process of diagnosis and treatment of IBD patients. In the future, longer follow-up and prospective studies are needed to reveal the relationship between high radiation exposure and solid tumorigenesis.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

• Inflammatory bowel disease
• Crohn’s disease
• Ulcerative colitis

Diagnostic medical radiation

Millisieverts

Confidence interval

Magnetic resonance enterography

CT enterography

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• Amanuel Tesfay Gebremedhin 4 , 5 &
• Paul Ward 3  

Conflict and Health volume  18 , Article number:  40 ( 2024 ) Cite this article

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Despite the fact that Sub-Saharan Africa bears a disproportionate burden of armed conflicts and HIV infection, there has been inadequate synthesis of the impact of armed conflict on HIV treatment outcomes. We summarized the available evidence on the impact of armed conflicts on HIV treatment outcomes in Sub-Saharan Africa from 2002 to 2022.

We searched four databases; MEDLINE, PubMed, CINHAL, and Scopus. We also explored grey literature sources and reviewed the bibliographies of all articles to identify any additional relevant studies. We included quantitative studies published in English from January 1, 2002 to December 30, 2022 that reported on HIV treatment outcomes for patients receiving antiretroviral therapy (ART) in conflict and post-conflict areas, IDP centers, or refugee camps, and reported on their treatment outcomes from sub-Saharan Africa. Studies published in languages other than English, reporting on non-ART patients and reporting on current or former military populations were excluded. We used EndNote X9 and Covidence to remove duplicates, extracted data using JBI-MAStARI, assessed risk of bias using AHRQ criteria, reported results using PRISMA checklist, and determined Statistical heterogeneity using Cochran Q test and Higgins I 2 , R- and RevMan-5 software were used for meta-analysis.

The review included 16 studies with participant numbers ranging from 102 to 2572. Lost To Follow-Up (LTFU) percentages varied between 5.4% and 43.5%, virologic non-suppression rates ranged from 25 to 33%, adherence rates were over 88%, and mortality rates were between 4.2% and 13%. A pooled meta-analysis of virologic non-suppression rates from active conflict settings revealed a non-suppression rate of 30% (0.30 (0.26–0.33), I2 = 0.00%, p  = 0.000). In contrast, a pooled meta-analysis of predictors of loss to follow-up (LTFU) from post-conflict settings identified a higher odds ratio for females compared to males (1.51 (1.05, 2.17), I2 = 0%, p  = 0.03).

The review highlights a lack of research on the relationship between armed conflicts and HIV care outcomes in SSA. The available documents lack quality of designs and data sources, and the depth and diversity of subjects covered.

Introduction

Armed conflicts have a negative impact on the health of populations, particularly on HIV patients who require strict adherence to treatment [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Providing regular HIV care and ensuring a continuous supply of drugs in conflict zones is difficult [ 2 ], leading to increased HIV incidence, prevalence, and related morbidity and mortality[ 8 9 ]. Less than 20% of people in conflict situations receive ART [ 10 ], and HIV services are scarce or nonexistent in conflict-affected countries; such as the Central African Republic (CAR), South Sudan, and parts of Yemen [ 10 ]. With 1.8 billion people living in conflict-affected areas [ 11 ], and 89.3 million people displaced from their homes by the end of 2021[ 12 ], researchers need to investigate how war affects HIV treatment.

However, there is a lack of systematic reviews investigating the connection between HIV and conflict, including the impact of armed conflict on HIV treatment outcomes. There were few systematic reviews[ 9 13 , 14 , 15 , 16 , 17 ] that have paid close attention to HIV prevalence and incidence as a result of armed conflict. None of the systematic reviews assessed the impact of armed conflict on HIV treatment outcomes. Given the importance of HIV treatment in reducing HIV incidence and prevalence, the double burden of HIV and conflict in Sub-Saharan Africa, and the already fragile healthcare system in the region, there is a need for systematic synthesis and exploration of this area of research. This review aims to synthesize the impact of armed conflict on HIV treatment outcomes among HIV patients affected by armed conflicts in SSA, including retention, attrition, LTFU, clinical failure, immunological failure, treatment failure, virological failure, and mortality.

Study registration

The review was registered in the International Prospective Register for Systematic Reviews (PROSPERO), with the registration number CRD42022361924 and the protocol is published online in BMJ Open [ 18 ].

Population and context

The review included individuals in sub-Saharan Africa who received antiretroviral therapy between 2002 and 2022 and were living in conflict-affected, post-conflict, or displacement areas. We selected 2002, as many sub-Saharan African countries introduced HIV care and treatment programs in 2002[ 19 ]. The review was limited to sub-Saharan Africa due to the region’s disproportionately high affected by both HIV infection [ 20 ] and armed conflicts[ 16 21 , 22 , 23 , 24 ] (Fig.  1 ), weak healthcare systems, and lack of clear directives and funding for addressing HIV care in conflict-affected settings.

(Source: UCDP Version 2021)

Number of conflict-affected and conflict incidents in sub-Saharan Africa between 2002 and 2021.

Search strategy and data sources

The search was conducted using three themes: conflict, HIV care, and SSA, and was conducted in four databases. Although the initial plan was to search five databases, access to Web of Sciences was not possible. After seeking advice from our librarian, we chose to exclude Web of Sciences from our search since it had comparable literature content to SCOPUS. Consequently, we searched the remaining four databases, which included MEDLINE, PubMed, CINHAL, and SCOPUS. We also explored grey literature sources and reviewed the bibliographies of all articles to identify any additional relevant studies.

Study selection and eligibility criteria

The study only included quantitative studies conducted in English from January 1, 2002 and December 31, 2022 that focused on HIV patients receiving ART from conflict areas, IDP centers, or refugee camps, and reported on their treatment outcomes. Studies that included both conflict-affected and non-conflict-affected populations were only included if they provided data specifically for the conflict-affected group. Studies published in languages other than English, those that did not mention conflict or provide disaggregated data for conflict-affected populations, studies that involved current or former military populations, studies from countries outside of SSA, studies reporting on African refugees settled outside of SSA, studies published before 2002, and studies reporting on HIV patients not receiving ART were excluded.

Quality assessment

The search results were filtered through a multi-step process that included independent review by two reviewers, evaluation of methodological validity using standardized JBI appraisal instruments [ 25 ], and assessment of risk of bias using AHRQ criteria [ 26 ]. Disagreements among reviewers were resolved through discussion and consensus but included and extracted data from all relevant documents irrespective of their quality score.

Data extraction

We used EndNote X9 and Covidence to remove duplicates. Data were extracted using the standardized data extraction tool from JBI-MAStARI [ 27 ]. The data extracted included specific details about the authors, publication year, country of study, populations, sample size, summary of HIV treatment outcome.

Types of interventions and comparators

The review considered impact of armed conflict on HIV treatment outcomes.

Types of outcome measures

The study focused on HIV care treatment outcomes, including adherence, LTFU, clinical failure, immunological failure, virological failure, and mortality.

Operational definitions

There is no universally accepted definition of armed conflict, as it is an umbrella word for a wide range of ideas and activities, such as conflict, war, violence, terrorism, or catastrophic loss of civilian life, a civil unrest, massive displacement, and violations of human rights and international humanitarian law. While we put the definition of conflict as follows, we would like to remain open to additional definitions by authors.

• Armed conflict

Is a situation in which states or other organized parties fight against each other by way of military force. Armed conflicts shall be of international and non-international armed conflicts [ 28 ].

Conflict affected areas

Are areas experiencing an armed conflict, and post-conflict regions. The area may be a region, a country, an area within a country, or an area that crosses one or more country boundaries. The impact of conflict may extend beyond the region of conflict to include surrounding areas and those hosting displaced persons. As a result, our definition remains open to the definition of authors.

Conflict -affected populations

Individuals, groups, and communities affected by and remaining in conflict-affected areas, as well as those forcibly displaced from them as refugees and IDPs. Conflict may have an impact on those who host IDPs and refugees. As a result, our definition remains open to author definition.

Internally displaced persons (IDPs)

Those who have been forced or compelled to leave their homes, often due to armed conflict, and who stay within their country’s borders.

Post-conflict

Refers to the period immediately following a conflict, when open combat is over. Nevertheless, despite its linguistic simplicity, the phrase is more challenging to define practically in terms of time, response, transformation, and sustainability. Therefore, our definition remains open to author definition.

People who are outside their country of birth due to conflict, war, widespread violence, or feared persecution and who as a result need international protection within the African continent [ 29 ].

Data management, analysis and synthesis

The results were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement [ 30 ] and meta regression was done to assess the relationship between armed conflict and HIV treatment outcomes. The Cochran Q test and Higgins I 2 [ 31 ] were used to determine statistical heterogeneity, and the random effect model was used when moderate statistical heterogeneity was detected. A meta-analysis to assess the predictors of LTFU was also conducted. The study used various statistical tools and software for analysis; R- software, STATA, and RevMan-5.

Outcome of the search

The comprehensive search identified 2487 records; 2332 identified through database searches, and 155 through manual searching of references and websites identified. All the identified 2487 references were exported into EndNote X9, and then into Covidence; 171 in the endnote, and 181 articles in the Covidence duplications were removed. After eliminating duplicates and conducting a comprehensive screening using Covidence was done, and 16 studies were considered eligible for data extraction, with 10 of them providing data for meta-analysis (Fig.  2 ).

PRISMA flowchart diagram of study selection impact of armed conflict on HIV care outcomes in SSA, 2002–2022

Description of included studies

The research covered in the review spanned from 2007[ 32 ] to 2022[ 33 ] and had varying follow-up periods, ranging from 4 days [ 34 ] to 60 months [ 35 ]. The majority of the studies were conducted in Western and Eastern Africa, with a significant number of studies coming from the Democratic Republic of the Congo[ 32 33 35 , 36 , 37 ], Kenya [ 38 , 39 , 40 ], and Uganda[ 34 41 42 ]. Most of the studies were designed as cohort studies, either retrospective[ 32 35 38 , 39 , 40 , 41 43 , 44 , 45 ] or prospective[ 33 36 37 42 46 ]. The majority of the studies focused on adult populations[ 33 , 34 , 35 , 36 , 37 39 40 42 , 43 , 44 ], with one study [ 38 ] specifically examining children. The studies included patients who were non-IDPs[ 32 33 35 , 36 , 37 , 38 40 41 ], non-IDPs & IDPs[ 34 39 42 44 45 ], refugees[ 44 47 ], or a mix of these groups [ 43 ]. Ten studies were carried out in conflict settings[ 32 , 33 , 34 36 37 42 44 , 45 , 46 , 47 ], while five took place in post-conflict zones[ 35 38 , 39 , 40 , 41 ], and one in both [ 43 ] (Table  1 and Supplementary Table 1 ).

Quality assessment—Data aource/Validity/Reliability

Methodological validity of the included studies was evaluated using JBI appraisal instruments. The quality of evidence was rated as high quality ( n  = 7, 90.91%, n  = 5, 81.82%, n  = 1, 100%, n  = 1, 90%, n  = 1, 75%, n  = 1, 72.73%) and presented moderate quality. The outcomes of the BJI assessment are shown in supplementary (supplementary Table 2 ).

Conflict and HIV treatment outcomes

The studies reported various outcomes, with four[ 33 36 37 46 ] focusing on the relationship between conflict and HIV treatment outcome as the primary outcome, five reporting adherence rates[ 32 34 38 42 44 ], two reporting treatment interruption[ 39 40 ], nine reporting LTFU[ 32 35 36 38 41 43 45 , 46 , 47 ], four reporting immunologic gain[ 32 40 42 43 ], four looking at the rate of viral non-suppression[ 37 40 45 47 ], and seven reporting mortality[ 32 33 35 42 43 46 47 ] (Supplementary Table 3 ).

The review found that adherence rates among HIV patients in Sub-Saharan Africa ranged from 88.2%[ 44 ] to 99.6%[ 34 ]. The studies reported predictors of non-adherence, and non-adherence was associated with being on first-line therapy(OR = 22.22, 95% CI 1.53, 333.33; p  = 0.02)[ 34 ], and feeling condemned by clinic workers (OR = 22.22, 95%CI 1.53, 333.33; p  = 0.02)[ 34 ].

Pooled meta-analysis

The pooled adherence rate among HIV patients in conflict-affected SSA regions was 0.06 (0.02–0.12), I2 = 87.12%, p  = 0.00, with a significant clinical heterogeneity (Fig.  3 ).

Pooled meta-analysis of non-adherence rate from active conflict settings among HIV patients who were on ART in SSA from 2002 to 2022

Treatment interruption (TI)

Two studies[ 39 40 ] conducted in Kenya reported instances of treatment interruption, with the risk of interruption increasing by 71% during post-election violence (95%CI 34, 118, p  = 0.001). Male patients (OR = 1.37, 95%CI 1.07, 1.76; p  = 0.01), and who traveled more than three hours to the clinic (OR = 1.86, 95%CI 1.28, 2.71; p  = 0.001) were found to be at a higher risk of treatment interruption [ 39 ]. Treatment interruptions were associated with detectable viral load, with viral loads exceeding 5,000 copies/mL and 10,00060 copies/mL[ 40 ].

Lost to follow-up

In active conflict settings, the rate of loss to follow-up (LTFU) ranged from 5.4% (95% CI = 3.2–7.5)[ 32 ] to 28.8% (95% CI: 24.9–33.1) [ 36 ], while post-conflict areas had a paradoxical level of LTFU ranging from 2.6%[ 38 ] to 43.5%[ 41 ]. The included studies indicated that factors like educational level [ 36 ], place of residence [ 36 ], prior experience with antiretroviral therapy (ART) upon enrollment [ 36 ], and the World Health Organization (WHO) clinical stage of disease [ 41 ] were linked to loss to follow-up (LTFU) among adult patients. Additionally, the study showed that receiving ART reduced the likelihood of complete loss to follow-up among children with HIV in post-crisis Kenya [ 38 ].

Pooled LTFU rates of 0.16 (0.08–0.28), I2 = 98.55%, p  = 0.00 were found in studies from active conflict settings[ 32 36 46 47 ], (Fig.  4 ), and 0.16(0.01–0.42), I2 = 99.52%, p  = 0.00 post-conflict settings[ 35 38 41 ] (Fig.  5 ).

Pooled meta-analysis of LTFU rate from active conflict settings among HIV patients who were on ART in SSA from 2002 to 2022

Pooled meta-analysis of LTFU rate from post conflict settings among HIV patients who were on ART in SSA from 2002 to 2022

Similarly, a review of studies conducted in post-conflict settings analyzed factors that may predict loss to follow-up (LTFU) in HIV care. The study found that only gender was statistically significant, with a 1.51 (1.05, 2.17), I 2  = 0%, P  = 0.03 odds ratio for LTFU in females compared to males (Fig.  6 ).

Meta-analysis of predictors of LTFU in post conflict-settings among HIV patients who were on ART in SSA from 2002 to 2022

Immunologic gain

CD4 gain was reported by four studies[ 32 40 42 43 ], as a secondary outcome, with changes ranging from 129 mm3[ 43 ] to a median of 163 cells/mm 3 [ 32 ] in six months.

Viral non-suppressions

Four studies examined the prevalence of viral non-suppression[ 37 40 45 47 ], with different thresholds ranging from > 50[ 45 47 ] to > 1000 copies/mL[ 45 47 ]. Three studies[ 37 45 47 ] investigated predictors of viral non-suppression, with two finding no significant variables and one [ 37 ] reporting that being in stage III or IV of the disease (AOR = 1.86, 95% CI 1.01–3.43), and having a high baseline HIV viremia of over 1000 copies/mL(AOR = 3.41, 95% CI 1.64–7.08) were associated with increased risk [ 37 ].

A pooled-analysis of two studies[ 45 47 ] from active conflict settings found a pooled non-suppression rate of 30% (0.30(0.26–0.33), I2 = 0.00%, p  = 0.000) using a cut-off point of > 1000 copies/mL and a follow-up period of 6–12 months (Fig.  7 ).

Pooled meta-analysis of virologic non-suppression rate from active conflict settings among HIV patients who were on ART in SSA from 2002 to 2022

Seven studies provided information on mortality rates, with five conducted in active conflict settings[ 32 33 42 46 47 ], and one each in post-conflict [ 35 ] and both conflict and post-conflict [ 43 ] settings. Mortality rates ranged from 3.6% (17/468)[ 33 ] to 13.0% (182/1400)[ 47 ]. Three studies[ 33 46 42 ] examined predictors of mortality namely, socio-demographic variables such as age and sex, as well as clinical variables such as baseline ART status, viral load, CD4 count, WHO clinical stage, and adherence level were reported having associated with lower risk of mortality.

A pooled-analysis of five studies from active conflict settings showed a pooled mortality rate of 0.07 (0.04–0.11), I2 = 95.84%, p  = 0.00), indicating high clinical heterogeneity (Fig.  8 ).

Pooled meta-analysis of mortality rate from active conflict settings among HIV patients who were on ART in SSA from 2002 to 2022

This systematic review included 16 articles published from 2002 to 2022. To the best of our knowledge, this systematic review is one of the first comprehensive reviews to assess quantitative studies in seeking to address the substantial gaps in current knowledge regarding the impact of armed conflict on HIV care outcomes in SSA.

Despite the anticipated challenges in accessing ART medication and care schedules in conflict settings[ 16 32 48 ], such as ARV medications running out, lack of or poor access to health services, a shortage of medical professionals, and an increased burden of other medical priorities, along with the expected negative impact on HIV care outcomes[ 16 32 49 ]; the systematic review found lower rates of non-adherence, loss to follow-up, virologic non-suppression, and mortality compared to those reported from politically stable and well-resourced regions in Sub-Saharan Africa[ 43 50 , 51 , 52 , 53 , 54 ].

Furthermore, the pattern of unfavourable clinical outcomes among those HIV patients in ART reported in the included studies is driven more strongly by patient level covariates than by the evolution of the surrounding long-term conflict, socioeconomic factors[ 35 39 ], socioeconomic and clinical factors[ 33 37 42 46 ], and clinical variables[ 34 36 40 ], and these findings correspond to those of previous research in low-income countries, which also found that unfavourable clinical outcomes were associated with patient age, baseline VL, and the status of treatment before enrollment [ 53 ]. This suggests that the cause of poor clinical outcomes was likely not to have been related to armed conflict and associated factors.

The inconsistency of the studies with the perceived outcomes reflects the complex interrelationship between conflict and HIV care. Many factors could have contributed to the disparity in perceived HIV care outcomes and conflict. These include, patient commitment and creativity in obtaining treatment[ 32 34 38 39 42 ], as well as education about the benefits of treatment, contribute to positive clinical outcomes. Furthermore, the results of the included studies might have been influenced by information bias, as the impact of conflict-related factors on HIV care was not taken into account. conflict could lead to a range of indirect factors that negatively affect the HIV care outcomes; such as, lack of access to safe drinking water, food insecurity, social unrest, displacement, insecurity, and destruction of livelihoods, psychosocial trauma, and the inability of health systems and other social services[ 16 39 48 55 ].

Additionally, the studies themselves had limitations, including retrospective design which rely heavily on patient charts which may have missing data and possible information bias, simplistic study (cause and effect) approach, bias in representativeness as majority of the studies were reported from NGOs funded and managed IDP sites, and a focus on adult populations rather than vulnerable groups like children. These non-governmental organizations (NGOs) are concentrated in small, stable areas. They had a small number of patients in them. The studies were also limited by their small geographic scope. The majority of HIV-infected people, however, live in remote villages.

Therefore, the systematic review highlights the limited research on the relationship between armed conflict and HIV care outcomes in Sub-Saharan Africa. Despite high double burden of armed conflicts and HIV infection in Sub-Saharan Africa, the extensive systematic search revealed that there is limited research on the relationship between armed conflict and HIV care outcomes in Sub-Saharan Africa, with only 16 eligible studies found (Fig.  9 ). This could be due to the belief that providing ART and conducting research during conflict is too difficult [ 48 ]. Furthermore, the existing studies focus on a limited geographic scope and adopt a simplistic cause-and-effect approach, failing to capture the complex and contentious relationship between conflict and HIV care outcomes in SSA. Additionally, the available studies failed to consider the conflict related factors, and indirect factors, post conflict settings. Additionally, pediatrics and mothers were also neglected in the available studies. The available studies fall short of addressing the realities of HIV care in conflict settings, and more research is needed to understand the impacts of armed conflicts on HIV care outcomes, especially in sub-Saharan Africa. Therefore, more research is needed to understand the reciprocal relationship between conflict and HIV care outcomes in Sub-Saharan Africa. Details of the recommended research areas are tabled in Table  2 .

Mapping conflict events, and locations where studies on the impact of armed conflicts on HIV care outcomes were published, SSA between 2002 and 2021. (source: UCDP Version 21)

This systematic review filled a gap in study on HIV treatment outcomes in conflict zones in Sub-Saharan Africa. However, the review highlights a lack of research on the relationship between armed conflicts and HIV care outcomes in Sub-Saharan Africa. The available documents lack quality of designs and data sources, and depth and diversity of subjects covered; calling further primary studies on a prioritized future research agenda. Furthermore, there were possible limitations to the review, including there might be exclusion of studies not labeled as conflict-related, selection bias due to language limitations (the database search was limited to English), and potential confounding variables of which we are unaware might be present.

Data availability

All data relevant to the study are included in the article or uploaded as supplementary information. All data relevant to the study are included in the article.

Abbreviations

Anti-Retroviral Therapy

Human Immuno-Deficiency Virus

Internally Displaced People

Lost To Follow-Up

Ministry of Health

Non-Governmental Organizations

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)

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Hafte Kahsay Kebede

College of Health Sciences, Mekelle University, Mekelle, 231, Ethiopia

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H.K.K performed the search, and employed screening and data extraction with H.A.G independently. All authors have full access to all the data in the study and have final responsibility for the decision to submit for publication. Study concept and design: P.R.W, H.A.G, H.K.K. Acquisition, analysis, or interpretation of data: P.R.W, H.A.G, H.K.K. Drafting of the manuscript: H.K.K. Critical revision of the manuscript for important intellectual content: P.R.W, H.A.G, H.K.K Meta- analysis, and mapping: A.T.G, H.K.K.Study supervision: P.R.W, H.A.G.

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Kebede, H.K., Gesesew, H.A., Gebremedhin, A.T. et al. The impact of armed conflicts on HIV treatment outcomes in Sub-Saharan Africa: a systematic review and meta-analysis. Confl Health 18 , 40 (2024). https://doi.org/10.1186/s13031-024-00591-8

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Received : 02 October 2023

Accepted : 28 March 2024

Published : 17 May 2024

DOI : https://doi.org/10.1186/s13031-024-00591-8

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