Parallel designs with an end-of-treatment analysis are commonly used for randomised trials, but they remain challenging to conduct in rare diseases due to small sample size and heterogeneity. Model-based approaches can be more powerful to detect treatment effects. We investigated the performance of longitudinal modelling to evaluate disease-modifying treatments in rare diseases a simulation study, leveraging as showcase a model of the SARA score progression in Autosomal Recessive Cerebellar Ataxia. We compared the power of parallel, crossover and delayed start designs, investigating several trial settings: trial duration (2 or 5 years); disease progression rate (slower or faster); magnitude of residual error ( σ =2/ σ =0.5); number of patients (100 or 40); method of statistical analysis (longitudinal analysis with non-linear or linear models; standard statistical analysis). In our simulations, using non-linear mixed effect models resulted in higher power than a rich, sparse linear mixed effect model or standard statistical analysis. Parallel and delayed start designs performed better than crossover designs. Our analysis showed that since disease progression is slow and residual variability is high (for the standard clinician-reported outcome), longer durations are needed for power to be greater than 80%, up to 5 years for slower progression and 2 years for faster progression ataxias.

Dr. Synofzik has received consultancy honoraria from Ionis, UCB, Prevail, Orphazyme, Servier, Reata, Biogen, GenOrph, AviadoBio, Biohaven, Zevra, Solaxa, and Lilly, all unrelated to the present manuscript. Dr Emmanuelle Comets has received consultancy honoraria from Sanofi, unrelated to the present manuscript. Drs Hooker and Karlsson have received consultancy fees from and own stock in Pharmetheus, all unrelated to this manuscript. Dr. Mentre has received consultancy fees from Pharmetheus and Ipsen, all unrelated to this manuscript. All other authors declared no competing interests in this work.

This work was funded by the European Joint Programme on Rare Diseases (EJP RD) Joint Transnational Call 2019 for the EJP RD WP20 Innovation Statistics consortium EVIDENCE-RND focusing on Innovative Statistical Methodologies to Improve Rare Diseases Clinical Trials in Limited Populations under the EJP RD Grant Agreement (n 825575) (to M.K, R.S. and M.S.); as well as by the European Union, project European Rare Disease Research Alliance (ERDERA), GA n 101156595, funded under call HORIZON-HLTH-2023-DISEASE-07 (to M.S. R.S, and F.M.). Moreover, work in this project was supported by the Clinician Scientist programme PRECISE.net funded by the Else Kroner-Fresenius-Stiftung (to M.S., R.S. and A.T) and the Bundesministerium fur Bildung und Forschung (BMBF) through funding for the TreatHSP network (grant 01GM2209A to R.S.). This work was supported by members of the Evidence-RND consortium, which includes Xiaomei Chen, Nicole Maria Heussen, Ralf-Dieter Hilgers, Thomas Klockgether, Yevgen Ryeznik, Oleksandr Sverdlov. R.S. and M.S. are members of the European Reference Network for Rare Neurological Diseases, Project ID 739510.

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The study only used simulated data

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