The Importance of Clinical Relevance and the Limitations of P -Values in Plastic Surgery Research : The CLARITY-SURG...

The proliferation of administrative databases, electronic health records, and large observational cohorts has profoundly expanded the scope of surgical research. At the same time, it has intensified a long-standing interpretive error: the routine conflation of statistical significance with clinical importance. In large data sets, small and often unstable numerical differences readily achieve conventional significance thresholds, driven by sample size, analytic flexibility, and selective reporting rather than by clinically meaningful or biologically coherent effects. Epidemiologic evidence demonstrates that null hypothesis significance testing (NHST) and dichotomous P -value thresholds are poorly suited for many observational, prognostic, and exploratory analyses common in surgical research, where effect size, precision, robustness, and plausibility are the true determinants of evidentiary value. This editorial synthesizes methodological insights from epidemiology, biostatistics, and surgical outcomes research to explain how selection processes, analytic latitude, publication bias, and large-sample artifacts systematically inflate the appearance of statistically "positive" findings. These concepts are translated into clinician-focused language, with illustrative examples drawn from surgery, where low-frequency but high-impact outcomes are particularly vulnerable to statistical fragility. To address these challenges, we introduce the CLARITY-SURG Statement (Clinical Linking of Association, Robustness, and Interpretability), a practical interpretive framework designed to help clinicians correctly evaluate observational study results. The framework provides a structured approach for assessing effect magnitude and precision, interrogating biological and surgical plausibility, examining analytic robustness, and determining the appropriate level of inference. By prioritizing clinical interpretability over threshold-based significance testing, the CLARITY-SURG Statement offers a reproducible, clinician-centered method for interpreting observational surgical research and for improving the quality, credibility, and clinical relevance of reported statistical findings.