Background: Days Alive and at Home (DAH) over a pre-defined follow-up period is a novel post-intervention composite outcome that combines data from at least three components: (i) initial length of hospital stay, (ii) length of total readmissions or other post-discharge care and (iii) mortality. Missing values bring unique challenges to the analysis of trials with the DAH outcome as the three components may have different rates of missingness caused by distinct missing data mechanisms. Current approaches define DAH as missing if any of the components are missing, and proceed with complete cases or Multiple Imputation (MI) of the composite. Methods: Through a simulation study motivated by the NOTACS trial, we compare several methods of handling missing data, including complete case analysis, MI of the composite, and MI of the components when the primary analysis is a Mann-Whitney-Wilcoxon test. Results: MI on the component level has good properties in terms of type I error control and power. We caution against the use of MI on the composite level with Predictive Mean Matching, which can lead to type I error inflation. Conclusions: Given the complex distributional characteristics of DAH, naive approaches such as defining missingness on the composite level and directly imputing the composite with Predictive Mean Matching, can lead to type I error inflation. Imputing on the component level is recommended, suggested future work included imputation approaches that are compatible with more complex definitions of DAH, as well as recommendations for sensitivity analyses to the Missing at Random assumption.

翻译：背景：在预设随访期内，“存活且居家天数”（DAH）是一种新型干预后复合结局指标，其整合了至少三个成分的数据：（i）初始住院时长，（ii）总再入院或其他出院后护理时长，以及（iii）死亡率。缺失值给DAH结局的试验分析带来独特挑战，因为三个成分可能因不同的缺失数据机制而呈现差异化的缺失率。当前方法将DAH定义为任一成分缺失则整体缺失，并采用完整病例分析或对复合结局进行多重插补（MI）。方法：基于NOTACS试验启发的模拟研究，我们比较了多种缺失数据处理方法，包括完整病例分析、对复合结局进行多重插补，以及在主分析采用曼-惠特尼-威尔科克森检验时对成分进行多重插补。结果：成分层面的多重插补在I类错误控制和统计功效方面具有良好特性。我们警示避免在复合层面使用预测均值匹配法进行多重插补，因其可能导致I类错误膨胀。结论：鉴于DAH的复杂分布特征，简单方法（如在复合层面定义缺失状态并直接采用预测均值匹配法对复合结局进行插补）可能引发I类错误膨胀。建议采用成分层面插补，未来工作可纳入与更复杂DAH定义兼容的插补方法，同时提出针对缺失随机假设的敏感性分析建议。