A clinical trial simulator tool for a randomized delayed start trial in Parkinson’s disease
Authors: Kosinski Luke , Cui Zihan , Ma Shu Chin , Romero Klaus , Aggarwal Varun 
Published: February 2025

Objectives: A major challenge in clinical trials for Parkinson’s Disease (PD) is to separate change in disease trajectory versus an immediate symptomatic drug effect. Randomized delayed start trials address this challenge by randomizing patients to an “early start” active arm and a “delayed start” control arm that starts on placebo and then switches to treatment after a predetermined amount of time. Since both groups are randomized and have the same expected amount of disease progression at baseline, the delayed start group should catch up to the early start group if the treatment only affects symptoms, and the two should remain differentiated if the treatment modifies disease progression. Several methods have been proposed to evaluate delayed start trials and assess whether a treatment has a disease modifying effect. We implement two methods in a freely available clinical trial simulator tool for a delayed start trial, one from Bhattaram et al. [1] and one from Liu-Seifert et al. [2]Methods: Both methods involve testing three hypotheses. The method from Bhattaram et al. proposes testing for 1) any difference in slopes between the two groups, 2) a statistically significant difference in endpoint measurement by the end of the study, and 3) a non-inferiority comparison of the slopes from the two groups [1]. Liu-Seifert et al. propose testing for 1) whether the groups are different at the end of the placebo-controlled phase, 2) like Bhattaram et al.’s hypothesis 2, a significant difference by the end of the study, and 3) retention at the end of the study of at least 50% of the difference between groups from hypothesis 1 [2]. Both methods were added as a randomized delayed start module to an existing R Shiny app for clinical trial simulation of PD based on a published model [3].Results: The R Shiny app simulates a randomized delayed start trial in PD. Users input various aspects of the trial: study and simulation parameters, patient characteristics, and choice of Bhattaram et al.’s or Liu-Seifert et al.’s method. The tool simulates and provides output to evaluate a delayed start trial: trajectories for the early and delayed start groups and a hypothetical placebo group that never switches, and a table for evaluating the trial using the chosen method.Conclusions: The randomized delayed start module adds functionality to an existing clinical trial simulator, helping inform randomized delayed start trial designs in PD. To request access to the tool, please send an email to QuantMedInfo@c-path.org.Citations: [1] Bhattaram VA, Siddiqui O, Kapcala LP, Gobburu JVS. Endpoints and Analyses to Discern Disease-Modifying Drug Effects in Early Parkinson’s Disease. AAPS J. 2009;11(3):456. doi:10.1208/s12248-009-9123-2[2] Liu-Seifert H, Andersen SW, Lipkovich I, Holdridge KC, Siemers E. A Novel Approach to Delayed-Start Analyses for Demonstrating Disease-Modifying Effects in Alzheimer’s Disease. Tractenberg RE, ed. PLOS ONE. 2015;10(3):e0119632. doi:10.1371/journal.pone.0119632[3] Conrado DJ, Timothy N, Kuenhi T, et al. Dopamine Transporter Neuroimaging as an Enrichment Biomarker in Early Parkinson’s Disease Clinical Trials: A Disease Progression Modeling Analysis. Clin Transl Sci. 2018;11(1):63-70. doi:10.1111/cts.12492