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A Guide to Evidence Synthesis – Systematic Literature Reviews and Meta-Analyses

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Introduction

Evidence synthesis in systematic literature
reviews and meta-analyses involves the process of systematically gathering,
analyzing, and integrating evidence from multiple studies to address a specific
research question or objective.

Understanding all the steps in conducting a systematic literature review
before delving into the key components of its structure is paramount. This
comprehensive understanding serves as the foundation for conducting a rigorous
and methodologically sound review.

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Types of Reporting Standards for Evidence Synthesis

Several reporting standards have been developed to ensure transparent and comprehensive reporting of evidence syntheses, including systematic literature reviews and meta-analyses. Some prominent examples include:

  • PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses): PRISMA provides a checklist and flow diagram to guide the reporting of systematic reviews and meta-analyses. It covers items related to study identification, eligibility criteria, search strategy, study selection, data extraction, study quality assessment, synthesis methods, and interpretation of results.
  • MOOSE (Meta-analysis of Observational Studies in Epidemiology): MOOSE provides guidelines for reporting meta-analyses of observational studies. It includes items related to study design, search strategy, study selection, data extraction, quality assessment, data synthesis, sensitivity analysis, and interpretation of results.
  • Cochrane Handbook for Systematic Reviews of Interventions: Developed by the Cochrane Collaboration, the Cochrane Handbook provides detailed guidance on conducting systematic reviews and meta-analyses of healthcare interventions. It covers topics such as study design, search strategy, study selection, data extraction, risk of bias assessment, data synthesis, and interpretation of results.
  • ROSES (Reporting standards for Systematic Evidence Syntheses): ROSES is a comprehensive reporting guideline for evidence syntheses, including systematic reviews, meta-analyses, scoping reviews, and other types of syntheses. It covers items related to study identification, eligibility criteria, search strategy, study selection, data extraction, synthesis methods, and interpretation of results.
  • PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols): PRISMA-P provides guidelines for reporting protocols of systematic reviews and meta-analyses. It includes items related to the background, objectives, eligibility criteria, information sources, search strategy, study selection, data extraction, and analysis plan.

These reporting standards help ensure transparency, reproducibility, and methodological rigor in evidence synthesis research. Adhering to these guidelines when conducting and reporting systematic reviews and meta-analyses enhances the credibility and usefulness of the findings for researchers, policymakers, and other stakeholders.

The PRISMA Flow Diagram

The PRISMA Flow Diagram is a graphical representation used to illustrate the flow of studies through the systematic review process. It provides a visual summary of the study selection process, including the identification, screening, eligibility assessment, and inclusion of studies in the review.

The PRISMA Flow Diagram typically consists of a series of boxes and arrows that depict the number of studies identified, screened, assessed for eligibility, and included in the systematic review. The diagram follows a sequential flow, starting with the identification of studies through database searching, and ending with the inclusion of studies in the final analysis.

Key components of the PRISMA Flow Diagram include:

  • Identification: The diagram begins with the total number of records identified through database searching and other sources.
  • Screening: The number of records screened based on title and abstract, and the number of full-text articles assessed for eligibility are depicted in subsequent boxes.
  • Eligibility: The number of studies excluded at each stage of screening and eligibility assessment are indicated, along with reasons for exclusion (e.g., irrelevant study design, population, intervention).
  • Included Studies: The final box shows the number of studies included in the systematic review and meta-analysis, along with any additional studies identified through reference lists or other sources.

The PRISMA Flow Diagram provides readers with a clear and transparent overview of the study selection process, allowing them to assess the completeness and rigor of the review. It helps ensure transparency and reproducibility in reporting systematic reviews and meta-analyses, in accordance with the PRISMA guidelines. You can download a free and editable Microsoft Word document version of the flow chart here.

An example of PRISMA flow diagram for systematic literature review and meta-analyses used in evidence synthesis

Quantitative Evidence Synthesis in Meta-Analysis

Quantitative evidence synthesis in meta-analysis is a powerful statistical method used to combine data from multiple individual studies to produce a single summary estimate of the effect size for a particular outcome of interest.

Here is an overview of the process involved in quantitative evidence synthesis within a meta-analysis:

  • Effect Size Calculation: The effect size of interest (e.g., mean difference, risk ratio, odds ratio, correlation coefficient) is calculated for each study based on the available data. Effect sizes are standardized to ensure comparability across studies.
  • Pooling of Effect Sizes: Effect sizes from individual studies are combined using statistical techniques such as weighted averages or random-effects models to produce an overall summary estimate of the effect size. The weights assigned to each study reflect the precision of the effect estimate.
  • Heterogeneity Assessment: The degree of heterogeneity (variability) across studies is assessed using statistical tests and visual inspection of forest plots. High heterogeneity may indicate differences in study populations, interventions, or outcome measures that require further exploration.
  • Subgroup Analysis and Sensitivity Analysis: Subgroup analysis may be conducted to explore potential sources of heterogeneity and assess the robustness of results across different subgroups of studies. Sensitivity analysis examines the impact of excluding studies with high risk of bias or other methodological concerns on the overall findings.
  • Publication Bias Assessment: Publication bias, which arises when studies with positive results are more likely to be published, is assessed using statistical tests and visual inspection of funnel plots. Correction methods such as Egger’s regression or trim-and-fill are applied if publication bias is detected.
  • Interpretation and Reporting: The synthesized quantitative evidence is interpreted in the context of the research question and objectives of the meta-analysis. Findings are reported in a structured format, following established reporting guidelines such as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses).

Quantitative evidence synthesis in meta-analysis provides a rigorous and systematic approach to synthesizing evidence from multiple studies, allowing researchers to generate more precise estimates of the true effect size and draw evidence-based conclusions.

Qualitative Evidence Synthesis in Systematic Literature Review

Qualitative evidence synthesis in a systematic literature review involves systematically analyzing and synthesizing qualitative data from multiple studies to generate overarching themes, patterns, or theories related to a particular research question or phenomenon of interest.

Here is an overview of the process involved:

  • Data Analysis: Qualitative data analysis involves coding, categorizing, and thematically organizing the findings from individual studies. Common techniques include thematic analysis, grounded theory, content analysis, and narrative synthesis. Through iterative coding and interpretation, researchers identify common themes, patterns, or concepts across studies.
  • Synthesis: Synthesis involves integrating the findings from individual qualitative studies to develop overarching themes, theories, or conceptual frameworks. This may involve comparing and contrasting findings, identifying similarities and differences, and exploring relationships between different themes or concepts.
  • Validation: To enhance the trustworthiness and credibility of the synthesis, researchers may engage in member checking, peer debriefing, or expert consultation to validate the synthesized findings with stakeholders or other researchers familiar with the topic.
  • Interpretation and Reporting: The synthesized qualitative evidence is interpreted in the context of the research question and objectives of the review. Findings are reported in a structured format, often using narrative descriptions, thematic summaries, or illustrative quotes to convey key insights.

Summary

Evidence synthesis in systematic literature reviews and meta-analyses involves a rigorous and systematic process of gathering, analyzing, and integrating data from multiple studies to generate comprehensive insights into a particular research question or phenomenon. This process typically includes identifying relevant studies, screening for eligibility, extracting data, assessing study quality, synthesizing findings, and interpreting results. In meta-analyses, statistical techniques are used to combine data from individual studies to produce summary effect estimates. Overall, evidence synthesis aims to provide a transparent and robust summary of the existing evidence, facilitating informed decision-making and advancing knowledge in a specific field of study.

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Dr. Robertson Prime, Research Fellow
Dr. Robertson Prime, Research Fellow
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