Interpreting Population Mean Treatment Effects in the Kansas City Cardiomyopathy Questionnaire: A Patient-Level Meta-Analysis.

While comparing means between treatment groups improves statistical power, mean treatment effects do not necessarily reflect the clinical benefit experienced by individual patients.

虽然比较治疗组之间的平均值可以提高统计功效，但平均治疗效果并不一定反映个别患者所经历的临床益处。

Background

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.

评估平均KCCQ治疗效果与在一系列临床试验和心力衰竭病因中经历临床重要改善的患者比例之间的关联。

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.

设计、环境和参与者：对11项随机临床试验进行了患者级别的分析，包括9977名患者，以检查平均治疗效果与KCCQ总体总结评分（OSS）以及经历临床重要（≥5分）和中等到大（≥10分）改善的患者比例之间的绝对差异之间的关联。

There was no target date range, and included studies were those for which patient-level data were available.

没有设定具体的研究日期范围，纳入的研究是那些可以获得患者层面数据的研究。

Validation was performed in 7 additional trials.

在另外7项试验中进行了验证。

The data were analyzed between July 1 and September 15, 2023.

数据分析在2023年7月1日至9月15日之间进行。

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).

患者在KCCQ评分中体验到改善5分或更多以及10分或更多点的比例（每个领域转换为0到100分的范围，其中更高的分数代表更好的健康状况）。

Results

Group mean KCCQ-OSS differences were strongly correlated with absolute differences in clinically important changes (Spearman correlations 0.76-0.92).

组平均KCCQ-OSS差异与临床上重要变化的绝对差异之间存在强相关性（Spearman相关系数为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.

例如，平均KCCQ-OSS治疗效果为2.5分（个体患者最小重要差异的一半）与患者改善5分或更多点的比例绝对差异6.0%（95%预测区间[PI]，4.0%-8.1%）相关，以及与改善10分或更多点的比例绝对差异5.0%（95% PI，3.1%-7.0%）相关，分别对应于需要治疗的患者数为17（95% PI，12-25）和20（95% PI，14-33）。

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.

基于人群平均水平治疗效果的临床影响推断可能会产生误导，因为即使是小组间的小差异也可能反映了对个别患者具有临床重要性的治疗益处。

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.

本研究的结果表明，临床试验应明确描述治疗组内患者水平KCCQ变化的分布，以支持其结果的临床解释。