Flandre Philippe
INSERM Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Sorbonne Université, Paris, France.
Pharm Stat. 2022 Nov;21(6):1281-1293. doi: 10.1002/pst.2245. Epub 2022 Jun 16.
Comparing survival functions with the log-rank test in the presence of dependent censoring can produce an invalid test result. We extend our previous work on the estimation of the survival function using prognostic variables to adjust for dependent censoring to the comparison of two survival distributions. In these estimators, the weights of a censored individual is redistributed among either a subset of patients in the risk set or all patients in the risk set but giving more weight to patients having smallest distances from the censored subject. The distance is based on two risk scores obtained from two working models, one for the failure time and one for the censoring time. Based on the estimators, we suggest a weighted log-rank test to compare two survival distributions. A simulation study compared performance of our method with the analysis of the observed data without using auxiliary variables and with a recent method based on multiple imputation (KMIB method). With appropriate parameters, the weighted log-rank approach provides sizes of the test comparable to the nominal value but higher powers than the two other methods. The method is illustrated with data from a breast cancer study.
在存在相依删失的情况下，使用对数秩检验比较生存函数可能会产生无效的检验结果。我们将之前利用预后变量估计生存函数以调整相依删失的工作扩展到两个生存分布的比较。在这些估计器中，删失个体的权重会重新分配到风险集中的一部分患者或风险集中的所有患者中，但会给与删失个体距离最小的患者更多权重。该距离基于从两个工作模型获得的两个风险评分，一个用于失效时间，一个用于删失时间。基于这些估计器，我们提出一种加权对数秩检验来比较两个生存分布。一项模拟研究将我们方法的性能与不使用辅助变量分析观测数据的方法以及最近基于多重填补的方法（KMIB方法）进行了比较。在适当的参数下，加权对数秩方法提供的检验规模与名义值相当，但功效高于其他两种方法。该方法通过一项乳腺癌研究的数据进行了说明。
