Biometrics Unit, Montpellier Cancer Institute (ICM), University of Montpellier, 208, avenue des Apothicaires, 34298, Montpellier, France.
French National Platform Quality of Life and Cancer, Montpellier, France.
BMC Med Res Methodol. 2020 Sep 3;20(1):223. doi: 10.1186/s12874-020-01104-w.
Health-related quality of life (HRQoL) has become a major endpoint to assess the clinical benefit of new therapeutic strategies in oncology clinical trials. Typically, HRQoL outcomes are analyzed using linear mixed models (LMMs). However, longitudinal analysis of HRQoL in the presence of missing data remains complex and unstandardized. Our objective was to compare the modeling alternatives that account for informative dropout.
We investigated three alternative methods-the selection model (SM), pattern-mixture model (PMM), and shared-parameters model (SPM)-in relation to the LMM. We first compared them on the basis of methodological arguments highlighting their advantages and drawbacks. Then, we applied them to data from a randomized clinical trial that included 267 patients with advanced esophageal cancer for the analysis of four HRQoL dimensions evaluated using the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire.
We highlighted differences in terms of outputs, interpretation, and underlying modeling assumptions; this methodological comparison could guide the choice of method according to the context. In the application, none of the four models detected a significant difference between the two treatment arms. The estimated effect of time on HRQoL varied according to the method: for all analyzed dimensions, the PMM estimated an effect that contrasted with those estimated by the SM and SPM; the LMM estimated effects were confirmed by the SM (on two of four HRQoL dimensions) and SPM (on three of four HRQoL dimensions).
The PMM, SM, or SPM should be used to confirm or invalidate the results of LMM analysis when informative dropout is suspected. Of these three alternative methods, the SPM appears to be the most interesting from both theoretical and practical viewpoints.
This study is registered with ClinicalTrials.gov , number NCT00861094 .
健康相关生活质量（HRQoL）已成为评估肿瘤学临床试验中新治疗策略临床获益的主要终点。通常，使用线性混合模型（LMM）分析 HRQoL 结果。然而，在存在缺失数据的情况下，HRQoL 的纵向分析仍然复杂且未标准化。我们的目的是比较考虑信息性缺失的建模替代方案。
我们研究了三种替代方法 - 选择模型（SM）、模式混合模型（PMM）和共享参数模型（SPM） - 与 LMM 相关。我们首先根据突出其优缺点的方法论点对它们进行比较。然后，我们将它们应用于一项随机临床试验的数据中，该试验纳入了 267 名晚期食管癌患者，使用欧洲癌症研究与治疗组织（EORTC）QLQ-C30 问卷评估了四个 HRQoL 维度。
我们突出了输出、解释和潜在建模假设方面的差异；这种方法比较可以根据上下文指导方法的选择。在应用中，四种模型均未检测到两种治疗方法之间的显著差异。HRQoL 随时间的变化估计值因方法而异：对于所有分析的维度，PMM 估计的效果与 SM 和 SPM 估计的效果相反；LMM 的估计效果得到了 SM（四个 HRQoL 维度中的两个）和 SPM（四个 HRQoL 维度中的三个）的证实。
当怀疑存在信息性缺失时，应使用 PMM、SM 或 SPM 来确认或否定 LMM 分析的结果。在这三种替代方法中，SPM 似乎从理论和实践角度来看都是最有趣的。
这项研究在 ClinicalTrials.gov 注册，编号为 NCT00861094。
