Why can publication bias make the conclusions of a meta-analysis less reliable?

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In the context of epidemiology and medicine, publication bias refers to the tendency of investigators or editors to publish findings based on factors such as the strength or implication of the results, rather than the scientific merit of the study.1

This bias makes the conclusions of a meta-analysis less reliable primarily because it leads to the selective reporting of data. For instance, studies that demonstrate negative results are frequently not published, which creates an incomplete and skewed evidence base. When a meta-analysis synthesizes only the available published literature, it may overestimate the efficacy of a medical intervention because the "missing" negative studies are excluded from the calculation.1

To maintain scientific integrity, researchers must strive for transparency and objectivity. Relying on a biased subset of data undermines the ethical principle of providing accurate, evidence-based guidance for public health and clinical decision-making. Researchers often use tools like funnel plots to detect this asymmetry, but a comprehensive search for unpublished results remains a critical step in mitigating this risk.1