Clinically meaningful outcomes require more than statistical significance; they must also represent an actual benefit to patients. The minimum clinically important difference (MCID) is the smallest change in a patient-reported outcome measure (PROM) that is clinically significant to the patient. Despite the growing use of PROMs in clinical research, considerable variability exists in how MCID is defined, calculated, and interpreted across populations and clinical contexts. The objective of this review is to provide a comprehensive summary of the various methods for estimating and interpreting MCID, including distribution-based, anchor-based, and Delphi approaches, and to discuss their relationship with statistical significance in clinical practice. A literature search was conducted using Web of Science, MEDLINE, Embase, PubMed, and Google Scholar. MCID values may vary depending on the patient population, clinical context, and the PROM administered. Each calculation methodology has its strengths and limitations in evaluating clinically meaningful change from baseline to post-treatment. It is recommended to report both a statistically significant difference, defined as P < 0.05, or equivalently a 95% confidence interval (CI) that excludes the null value (i.e., does not include 0 for mean differences or 1 for odds ratios), and a clinically meaningful difference, defined as an effect size meeting or exceeding the established MCID for the outcome measure. Reporting the effect estimate alongside its 95% CI is encouraged as the primary approach, as this conveys both the magnitude and precision of the finding.
Saneii et al. (Sat,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: