Using multiple anchor- and distribution-based estimates to evaluate clinically meaningful change on the functional assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) instrument
Using multiple anchor- and distribution-based estimates to evaluate clinically meaningful change on the functional assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) instrument
复制标题
DOI：
10.1111/j.1524-4733.2005.08202.x
复制
发表时间：
2005-03-01
期刊：
影响因子：
4.5
通讯作者：
Cella, D
中科院分区：
文献类型：
--
作者：
Yost, KJ;Sorensen, MV;Cella, D
目的：通过了解HRQL评分有意义的变化程度，可以加强对临床试验中健康相关生活质量（HRQL）数据的解释。我们的目标是结合基于分布和两种基于锚定的方法，以确定癌症治疗-生物反应调节剂功能评估（FACT-BRM）工具中27项试验结果指数（TOI）、7项社会幸福感（SWB）子量表和6项情绪幸福感（EWB）子量表的最小重要差异（MIDs）。方法：基于分布的mid以计量标准误差为基础。基于锚定的方法利用患者报告的整体变化评级（GRC）和医生报告的表现状态评级（PSR）的变化。使用相关性和加权kappa统计来评估两个锚点之间的关联和一致性。FACT-BRM变化在三个时间段进行评估：基线至第1个月、第2个月至第3个月、第5个月至第6个月。结果：GRC与PSR变化的相关性较差。锚点与HRQL变化评分的相关性在第1个月最大，在第6个月下降。综合所有方法的结果，确定的mid为TOI 5-8分，SWB子量表2分，EWB子量表2-3分。结论：我们结合患者报告的估计值、医生报告的估计值和基于分布的估计值，从FACT-BRM中得出HRQL结果的mid。这些结果将有助于在临床试验环境中解释治疗组效应，并可用于在设计未来研究时估计样本量或功率。
Objective: The interpretation of health-related quality of life (HRQL) data from clinical trials can be enhanced by understanding the degree of change in HRQL scores that is considered meaningful. Our objectives were to combine distribution-based and two anchor-based approaches to identify minimally important differences (MIDs) for the 27-item Trial Outcome Index (TOI), the seven-item Social Well-Being (SWB) subscale, and the six-item Emotional Well-being (EWB) subscale from the Functional Assessment of Cancer Therapy-Biological Response Modifiers (FACT-BRM) instrument.Methods: Distribution-based MIDs were based on the standard error of measurement. Anchor-based approaches utilized patient-reported global rating of change (GRC) and change in physician-reported performance status rating (PSR). Correlations and weighted kappa statistics were used to assess association and agreement between the two anchors. FACT-BRM changes were evaluated for three time periods: baseline to month 1, month 2 to month 3, and month 5 to month 6.Results: Association between GRC and change in PSR was poor. Correlation between the anchors and HRQL change scores was largest at month 1 and decreased through month 6. Combining results from all approaches, the MIDs identified were 5-8 points for the TOI, 2 points for the SWB subscale, and 2-3 points for the EWB subscale.Conclusions: We combined patient-reported estimates, physician-reported estimates, and distribution-based estimates to derive MIDs for HRQL outcomes from the FACT-BRM. These results will enable interpretation of treatment group effects in a clinical trial setting, and they can be used to estimate sample size or power when designing future studies.