This research focused journal club article introduces the Synthesis Without Meta-analysis (SWiM) guideline. This is a nine-item reporting checklist and was developed to increase the transparency of systematic reviews.

Research Article: Campbell, M., McKenzie, J. E., Sowden, A., Katikireddi, S. V., Brennan, S. E., Ellis, S., … & Thomson, H. (2020). Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guideline. BMJ, 368.

For decades, decision-makers in medicine and public health have relied on the “systematic review” as the gold standard for evidence. These comprehensive reports gather all available research on a topic to provide a clear, authoritative answer. But there’s a surprising problem lurking beneath the surface. When the gold-standard statistical method, meta-analysis, isn’t possible, the reporting on alternative methods often lacks transparency, potentially casting doubt on the findings.

A meta-analysis is designed to answer the question: “What is the average intervention effect?“

An estimated 32% of all health-related systematic reviews fall into this category, where reviews cannot perform a meta-analysis of intervention effects. This means a significant portion of our medical evidence base suffers from unclear reporting. To solve this, a dedicated group of researchers has developed a new guideline to bring much-needed clarity and restore confidence in these essential reviews.

In situations where studies are too diverse to be statistically combined in a meta-analysis, researchers use alternative methods. These are often grouped under the umbrella term “narrative synthesis,” which typically relies on a textual description of effects. The problem is that without a formal, reported structure, this ‘narrative’ can become a subjective summary rather than a reproducible scientific synthesis, making it impossible for peers to critically assess how conclusions were drawn. The core issue, therefore, is that the reporting on these methods is frequently poor, making it difficult for other scientists, doctors, or policymakers to validate the findings.

Serious shortcomings in reviews that use “narrative synthesis” have been identified, including a lack of description of the methods used; unclear links between the included data, the synthesis, and the conclusions; and inadequate reporting of the limitations of the synthesis. This means that for nearly one-third of systematic reviews, the foundational evidence used by doctors to choose a treatment might have conclusions that are difficult to verify. The evidence used by policymakers to write public health guidelines may rest on methods that are not transparently reported.

The SWiM (Synthesis Without Meta-analysis) signals a fundamental shift toward more precise, rigorous, and transparent language in scientific reporting over “narrative synthesis”. Avoidance of the term “narrative synthesis” in SWiM is a deliberate move to promote clarity in the methods used in reviews in which the synthesis does not rely on meta-analysis.

The Solution: A 9-Point Checklist for Transparency

The solution proposed by researchers is the “Synthesis Without Meta-analysis” (SWiM) guideline. It is a nine-item checklist designed to promote transparent reporting for the reviews that cannot use meta-analysis. It is designed not as a replacement, but as an extension to the well-known PRISMA statement, which guides the reporting of all systematic reviews.

A crucial point is that SWiM is a guideline for reporting what was done, not a manual for how to conduct the synthesis. This is a critical distinction: SWiM doesn’t tell researchers how to perform their analysis, but it mandates that they describe precisely what they did, ensuring their work can be scrutinised and validated.

The checklist prompts researchers to adhere to key standards of transparency, for example, it:

• Mandates a clear description of how studies were grouped for analysis.

• Requires explicit justification for the synthesis method used.

• Ensures data is presented in standardized tables and graphs for comparison.

• Forces an honest assessment of the synthesis’s limitations and their impact on conclusions.

The guideline aims to establish clarity. It seeks to build trust in reviews where quantitative data is synthesised. This is done without relying on traditional meta-analysis.