ArticleTherapeutic innovation & regulatory science2026
Improving the Analysis of KCCQ Endpoints in Heart Failure Clinical Trials.
Article in Therapeutic innovation & regulatory science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
backgroundThe Kansas City Cardiomyopathy Questionnaire (KCCQ) is frequently used in heart failure (HF) clinical trials to evaluate treatment effects on function and symptoms. However, due to the 0-100 boundedness in KCCQ scores, conventional mean change from baseline analysis can underestimate effects for lower-and overestimate effects for higher-baselines. This study demonstrates key issues with conventional statistical methods for analyzing treatment effects on KCCQ in randomized trials and evaluates alternative statistical methods that appropriately account for 0-100 boundedness of scores.
methodsWe conducted clinical trial simulations and re-analyzed a real HF randomized trial-the PRIORITIZE-HF phase II trial of sodium zirconium cyclosilicate. KCCQ change from baseline was analyzed with conventional ANCOVA models, and compared to methods that account for the 0-100 score boundedness: ANCOVA interaction models, Tobit regression, and Beta regression. Mean treatment effects and extent of bias are summarized by method.
resultsThere were clear baseline-dependencies in mean effects for KCCQ score change, both in simulated trials and in PRIORITIZE-HF. In the real trial, the conventional ANCOVA model mean effect on KCCQ-overall summary score was + 2.58 overall while for methods allowing effects to depend on baseline - ANCOVA interaction models and Beta regression - mean effects were over twice as large at baseline = 30 (+ 6.33 to + 6.75) and less than half at baseline = 70 (- 0.31 to + 0.89).
conclusionsConventional analyses of treatment effects on overall mean KCCQ score changes lead to misinterpretations in clinical trials, but this can be mitigated by using methods allowing for baseline-dependent effects.
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