Effect size measures in laboratory medicine.

INTRODUCTION: Statistical significance indicates whether an observed finding is unlikely to have occurred by chance but does not quantify the magnitude or clinical importance of that finding. Effect size measures and related quantitative measures complement P values by improving the interpretation of laboratory findings. METHODS: This review examines the principal effect size measures and related quantitative measures used in contemporary laboratory medicine. It explains what each measure quantifies, when it is appropriate to use, and how it contributes to data interpretation. The application of these measures is illustrated using 40 published studies representing diverse diseases, laboratory disciplines, patient populations, and study designs. RESULTS: Across the reviewed studies, these measures consistently provided information beyond statistical significance by quantifying differences, associations, agreement, diagnostic performance, and other analytically important characteristics of laboratory tests. They supported a more comprehensive interpretation of biomarkers, analytical methods, diagnostic tests, and clinical interventions. DISCUSSION: Routine reporting and context-specific interpretation of appropriate effect size measures and related quantitative measures alongside P values should become standard practice in laboratory medicine to improve the interpretation, comparability, and clinical relevance of laboratory research.