Meta-analysis.

A statistical synthesis of results from multiple studies.

A meta-analysis statistically combines results across multiple studies addressing a similar question to produce a pooled estimate, which is usually more precise than any single study and can reveal whether the individual studies agree with each other. It also lets researchers examine heterogeneity, meaning how much the results scatter, and to look for publication bias, the tendency for studies finding nothing to go unpublished and therefore to be missing from the pool. In peptide research meta-analyses cluster where the trial evidence is dense, chiefly the metabolic drug classes, and are largely absent for compounds that have never been tested in humans at scale. That absence is itself informative: a compound with no trials cannot have a meta-analysis, so pointing to the lack of one is not a criticism, but claiming strong evidence in that situation is. The misunderstanding worth correcting is treating meta-analysis as automatically the highest form of evidence. Pooling weak or poorly matched studies produces a precise-looking number built on weak foundations, and combining trials that used different compounds, populations, or outcome measures can average away the very differences that matter. The quality of a synthesis is capped by the quality of what went into it.