Parkinson's disease (PD) is a chronic, degenerative neurological disorder. PD cannot be prevented, slowed or cured as of today but highly effective symptomatic treatments are available. We consider relevant estimands and treatment effect estimators for randomized trials of a novel treatment which aims to slow down disease progression versus placebo in early, untreated PD. A commonly used endpoint in PD trials is the MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), which is longitudinally assessed at scheduled visits. The most important intercurrent events (ICEs) which affect the interpretation of the MDS-UPDRS are study treatment discontinuations and initiations of symptomatic treatment. Different estimand strategies are discussed and hypothetical or treatment policy strategies, respectively, for different types of ICEs seem most appropriate in this context. Several estimators based on multiple imputation which target these estimands are proposed and compared in terms of bias, mean-squared error, and power in a simulation study. The investigated estimators include methods based on a missing-at-random (MAR) assumption, with and without the inclusion of time-varying ICE-indicators, as well as reference-based imputation methods. Simulation parameters are motivated by data analyses of a cohort study from the Parkinson's Progression Markers Initiative (PPMI).

翻译：Parkinson病(PD)是一种慢性、退化性神经疾病。PD无法预防、减慢或治愈,但目前已有高效的症状治疗。我们认为,用于随机试验一种新疗法的相关估计值和治疗效果估计值是随机试验一种新疗法的随机估计值和治疗效果估计值,这种试验的目的是在早期未经治疗的PD中减缓疾病进展与安慰。PD试验中常用的一个终点是MDS统一Parkinson疾病评比值(MDS-UPDRS),这是在预定的访问中经过纵向评估的。影响MDS-UPDDRS解释的最重要的流动事件(ICES)是研究MDS-UPDRS的治疗中止和开始症状治疗。在这里,讨论不同的估计值和治疗政策战略分别旨在减缓疾病在早期和未处理的PAD。基于多重估计值的估算值(MDS-MIS)的测评比(MDS-UPS-UPDRS)的参数和模拟研究中的权力的最重要的事件(ICES-CRestiming-assimending Adal-assimation Aration Adrient rodummissional)分析(根据缺失的测算算方法进行的一项测算的假设和测算的模型分析,不包含的测算算方法)。