All Times EDT
Keywords: Estimands, Parkinson’s disease, simulation study, reference-based imputation
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. In this presentation, we consider relevant estimands for randomized trials of a potentially disease-modifying treatment versus placebo in early PD. A commonly used endpoint in this setting 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 initiation of symptomatic treatment. Different estimand strategies and corresponding appropriate estimators will be discussed. Hypothetical or treatment policy strategies, respectively, for different types of ICEs seem most appropriate in this context, with estimators based on MMRM or reference-based imputation methods. We will then compare the performance of different estimators in terms of bias, mean-squared error, and power in a simulation study. Many of the simulation parameters will be motivated by data analyses of a cohort study from the Parkinson’s Progression Markers Initiative (PPMI). This presentation is based on collaborative work by a cross-industry working group on estimands in early Parkinson’s disease.