In this paper, we develop a semiparametric sensitivity analysis approach designed to address unmeasured confounding in observational studies with time-to-event outcomes. We target estimation of the marginal distributions of potential outcomes under competing exposures using influence function-based techniques. We derived the non-parametric influence function for uncensored data and mapped the uncensored data influence function to the observed data influence function. Our methodology is motivated by and applied to an observational study evaluating the effectiveness of radical prostatectomy (RP) versus external beam radiotherapy with androgen deprivation (EBRT+AD) for the treatment of prostate cancer. We also present a simulation study to evaluate the statistical properties of our methodology.

翻译：摘要：本文提出一种半参数敏感性分析方法，旨在解决观察性研究中未测量混杂对时间至事件结局的影响。我们基于影响函数技术，针对竞争暴露条件下潜在结局的边缘分布进行估计。推导出未删失数据的非参数影响函数，并将未删失数据影响函数映射至观测数据影响函数。该方法受一项评估根治性前列腺切除术（RP）与雄激素剥夺联合体外放射治疗（EBRT+AD）对前列腺癌疗效的观察性研究启发，并应用于该研究。我们同时通过模拟研究评估该方法的统计性质。