Systematic review vs Meta-analysis

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 Data (or evidence) used in systematic reviews have their origin in scholarly literature – published or unpublished.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.

Systematic Review and Meta-Analysis are two methods commonly used in evidence-based research to summarize and evaluate existing literature. While they share some similarities, there are distinct differences between the two approaches.

A systematic review is a comprehensive and rigorous synthesis of all available evidence on a particular research question or topic. It involves a systematic search and selection process to identify relevant studies, followed by critical appraisal and synthesis of the findings. The goal of a systematic review is to provide an unbiased summary of the existing evidence and to identify any gaps or inconsistencies in the literature. It typically includes a detailed description of the search strategy, study selection criteria, and methods used to assess the quality of included studies.

On the other hand, a meta-analysis is a statistical technique used to combine the results of multiple studies that have addressed a similar research question. It involves pooling the data from individual studies and analyzing them collectively to generate a summary effect size or estimate of the treatment effect. Meta-analysis provides a quantitative assessment of the available evidence, allowing researchers to derive more precise estimates of the treatment effect and assess its statistical significance. It can also explore sources of heterogeneity across studies and investigate potential publication bias.

In summary, the key differences between a systematic review and a meta-analysis are as follows:

• Scope: A systematic review aims to provide a comprehensive summary of the existing evidence, including both qualitative and quantitative synthesis. A meta-analysis, on the other hand, focuses specifically on quantitative synthesis by pooling data from multiple studies to generate a summary effect size.
• Data Analysis: While a systematic review primarily focuses on qualitative synthesis, examining the similarities and differences across studies, a meta-analysis involves statistical analysis of the pooled data to derive quantitative estimates of the treatment effect.
• Statistical Techniques: Systematic reviews use qualitative techniques such as narrative synthesis, thematic analysis, or qualitative comparative analysis to summarize the findings. Meta-analysis employs statistical techniques, such as calculating effect sizes, conducting subgroup analyses, or assessing publication bias.
• Reporting: Systematic reviews typically provide a narrative summary of the evidence, often accompanied by tables and figures to present the characteristics and results of the included studies. Meta-analyses, in addition to the narrative summary, provide quantitative estimates, forest plots, and statistical analyses to summarize the pooled data.
• Purpose: Both systematic reviews and meta-analyses aim to provide a comprehensive and rigorous analysis of existing evidence. However, their specific purposes can differ. A systematic review may be conducted to explore a broad research question, summarize the available evidence, identify research gaps, or inform clinical guidelines. A meta-analysis, on the other hand, is primarily focused on synthesizing quantitative data to estimate the overall treatment effect or evaluate the consistency of findings across studies.
• Study Selection: Systematic reviews and meta-analyses follow a systematic and transparent process for study selection. However, the inclusion criteria can differ. In a systematic review, studies may be included based on various factors such as study design, population characteristics, intervention types, or outcome measures. In contrast, a meta-analysis typically requires studies to provide sufficient quantitative data (e.g., means and standard deviations) to enable statistical pooling of results.
• Statistical Power: Meta-analysis can enhance statistical power by combining data from multiple studies, thereby increasing the precision of the estimates. This is particularly beneficial when individual studies have small sample sizes or produce inconclusive or contradictory results. Systematic reviews, while not providing pooled effect estimates, can still contribute by offering a comprehensive synthesis of the evidence, including both positive and negative findings.
• Generalizability: Both systematic reviews and meta-analyses aim to provide an overview of the available evidence. However, it's important to consider the generalizability of the findings. Factors such as variations in study populations, interventions, outcome measures, and study quality can influence the generalizability of the results. Systematic reviews often discuss the heterogeneity across studies, which can impact the applicability of the findings to different populations or contexts.
• Publication Bias: Meta-analyses can assess and address publication bias, which refers to the tendency for studies with significant or positive results to be more likely to be published, while studies with non-significant or negative results may be less likely to be published. Systematic reviews can also explore publication bias qualitatively by considering unpublished studies or gray literature, but meta-analyses provide more quantitative tools, such as funnel plots or statistical tests, to detect and adjust for publication bias.
• Study Heterogeneity: Systematic reviews and meta-analyses deal with study heterogeneity in different ways. Systematic reviews often explore heterogeneity qualitatively by examining variations in study design, population characteristics, interventions, and outcomes. They may provide subgroup analyses or narrative explanations for observed heterogeneity. Meta-analyses, on the other hand, employ statistical techniques to quantitatively assess heterogeneity. This can include conducting sensitivity analyses, subgroup analyses, or meta-regression to explore potential sources of variation across studies.
• Level of Evidence: Systematic reviews and meta-analyses are both considered high-level evidence in evidence-based practice. They provide a comprehensive synthesis of existing literature and are often used to inform clinical decision-making, policy development, or future research directions. However, it's important to note that the quality of the included studies in a systematic review or meta-analysis can affect the overall strength and reliability of the evidence.
• Time and Resource Requirements: Conducting a systematic review and a meta-analysis can be time-consuming and resource-intensive processes. Systematic reviews involve comprehensive literature searches, study selection, data extraction, quality assessment, and synthesis of findings. Meta-analyses require additional steps such as data pooling, statistical analysis, and interpretation of results. Both approaches require a rigorous and systematic approach to ensure the validity and reliability of the findings.
• Limitations: It's important to acknowledge the limitations of both systematic reviews and meta-analyses. Systematic reviews may face limitations such as publication bias, heterogeneity across studies, potential biases in study selection or quality assessment, or limited availability of high-quality studies. Meta-analyses may encounter similar limitations but also face additional challenges related to data availability, statistical assumptions, and the potential influence of outliers on pooled estimates.
• Updating the Evidence: Both systematic reviews and meta-analyses should be considered as dynamic processes, as new evidence can emerge over time. It is recommended to periodically update systematic reviews and meta-analyses to incorporate new studies and reassess the validity and relevance of the findings.

In summary, systematic reviews and meta-analyses are robust approaches for synthesizing and analyzing existing evidence. A systematic review provides a comprehensive synthesis and critical appraisal of the evidence, while a meta-analysis focuses on quantitative synthesis to estimate treatment effects. The choice of approach depends on the research question, available data, and specific objectives of the study. They have distinct methodologies and purposes but often complement each other in evidence-based research. Conducting a systematic review provides a comprehensive overview of the evidence, while a meta-analysis adds quantitative synthesis to estimate treatment effects. Researchers should carefully consider the research question, available data, and specific objectives to determine which approach or combination of approaches is most appropriate for their study.