Abstract
IMPORTANCE: The Kansas City Cardiomyopathy Questionnaire (KCCQ) is a commonly used outcome in heart failure trials. While comparing means between treatment groups improves statistical power, mean treatment effects do not necessarily reflect the clinical benefit experienced by individual patients. OBJECTIVE: To evaluate the association between mean KCCQ treatment effects and the proportions of patients experiencing clinically important improvements across a range of clinical trials and heart failure etiologies. DESIGN, SETTING, AND PARTICIPANTS: A patient-level analysis of 11 randomized clinical trials, including 9977 patients, was performed to examine the association between mean treatment effects and the KCCQ Overall Summary Score (OSS) and the absolute differences in the proportions of patients experiencing clinically important (≥5 points) and moderate to large (≥10 points) improvements. There was no target date range, and included studies were those for which patient-level data were available. Validation was performed in 7 additional trials. The data were analyzed between July 1 and September 15, 2023. MAIN OUTCOMES AND MEASURES: Proportion of patients experiencing an improvement of 5 or more and 10 or more points in their KCCQ score (with each domain transformed to a range of 0 to 100 points, where higher scores represent better health status). RESULTS: Group mean KCCQ-OSS differences were strongly correlated with absolute differences in clinically important changes (Spearman correlations 0.76-0.92). For example, a mean KCCQ-OSS treatment effect of 2.5 points (half of a minimally important difference for an individual patient) was associated with an absolute difference of 6.0% (95% prediction interval [PI], 4.0%-8.1%) in the proportion of patients improving 5 or more points and 5.0% (95% PI, 3.1%-7.0%) in the proportion improving 10 or more points, corresponding to a number needed to treat of 17 (95% PI, 12-25) and 20 (95% PI, 14-33), respectively. CONCLUSIONS AND RELEVANCE: Inferences about clinical impacts based on population-level mean treatment effects may be misleading, since even small between-group differences may reflect clinically important treatment benefits for individual patients. Results of this study suggest that clinical trials should explicitly describe the distributions of KCCQ change at the patient level within treatment groups to support the clinical interpretation of their results.