为了在患者报告结果（PROs）的时间退化（TTD）分析中应用估值框架，并确定适用于诸如死亡等事件干预（IEs）的适当统计方法。我们使用来自II期随机试验的数据。通过应用Kaplan-Meier（KM）估计器和Cox比例风险（PH）模型，使用EORTC QLQ-C30问卷估计TTD，将死亡作为IE。我们还探索了针对死亡作为竞争风险的Fine-Gray方法。定义了上述方法所针对的估值目标。对64名基线问卷可用患者的数据进行分析。在体能功能恶化方面观察到最显着的TTD估计差异：无论是忽略死亡（31起事件）还是将其视为恶化（58起事件）都得到了危险比为0.44 [95%CI 0.22-0.90]和0.62 [95%CI 0.36-1.07] 的估计（Cox-PH模型）。在考虑死亡作为竞争事件（Fine-Gray模型）时，亚危险比为0.51 [95%CI 0.26-1.01]。根据发生在恶化之前的死亡的比例和分布情况，应考虑Fine-Gray竞争风险模型，而不是KM估计器和Cox PH模型来反映患者对疾病和治疗负担的体验。版权所有©2023 Elsevier Inc.出版。

To apply the estimand framework in time to deterioration (TTD) analysis of patient-reported outcomes (PROs), and identify the appropriate statistical methods to deal with intercurrent event (IEs) such as death.Data from phase II randomized trial were used. We estimated TTD using EORTC QLQ-C30 questionnaire with death as the IE, by applying Kaplan-Meier (KM) estimator and Cox proportional hazards (PH) model. The Fine-Gray approach was explored, accounting for death as a competing risk. The estimands targeted by the aforementioned methods were defined.We analyzed data of 64 patients with available questionnaire at baseline. The most notable differences in TTD estimates were observed for deterioration in physical functioning: the hazard ratios were 0.44 [95%CI 0.22-0.90] and 0.62 [95%CI 0.36-1.07] by either ignoring death (31 events) or considering it as deterioration (58 events), respectively (Cox-PH model). When considering death as a competing event (Fine-Gray model), the sub-HR was 0.51 [95%CI 0.26-1.01].Depending on the proportion and distribution of deaths occurring before deterioration between arms, the Fine-Gray competing risks model should be considered rather than KM estimator and Cox PH model to reflect the patient's experience of the disease and treatment burden.Copyright © 2023. Published by Elsevier Inc.