Objective: Develop a Bayesian progression model (BPM) for MSA that leverages individual-level data derived from long-term follow up and offers a clinically interpretable, slope-based primary outcome within a Bayesian framework that enables the use of posterior probabilities for decision-making and allows for placebo enrichment with natural history data.

Background: Trials assessing disease modifying drug effect are typically long and often evaluate the treatment effect at a fixed timepoint using a categorical time mixed model for repeated measures, missing the opportunity to estimate treatment effect from individual progression trajectories. Given the rarity of the disease and lack of information from prior trials, efficient use of all available data is crucial to detect clinically meaningful effects on slowing clinical progression in MSA trials with feasible sample size and duration.

Method: Published MSA progression data were used to build a BPM that reflected up to 2 years of clinical progression (based on UMSARS assessments). This model was then used as the primary analysis of a phase 2 trial which incorporated a variable double-blind treatment period (48-72 weeks) [1]. Observations from the phase 2 trial were then used to extend the BPM framework to account for other disease aspects and evaluate the appropriateness of the model framework for future use.

Results: Although non-significant in the ITT phase 2 population, prespecified and post-hoc analyses of patients with MSA-C or less impairment at baseline showed separation of the active-treated group from placebo in relation to slowing in clinical progression with sufficient probability (>97.5%) of being a true effect as evaluated with posterior distributions. Following enrichment of the phase 2 placebo group using individualized natural history MSA data from European and Chinese cohorts, the results confirmed the appropriateness of the model and highlighted the absence of a strong placebo effect in this trial context.

Conclusion: Bayesian modelling provides an appropriate framework for assessing disease progression, as exemplified here in MSA, a rapidly progressing rare neurodegenerative disease that currently has no effective treatment. Moving forward, the BPM will be further extended to account for informative censoring through a joint analysis of clinical disease progression and a time-to-event disease milestone.

References: Singer et al. Safety and Efficacy of the Anti-alpha Synuclein Monoclonal Antibody Lu AF82422 for the Treatment of Patients with MSA: Results from the Phase 2 AMULET Trial [abstract]. Mov Disord. 2024; 39 (suppl 1).

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MDS Abstracts - https://www.mdsabstracts.org/abstract/assessing-disease-progression-in-msa-development-of-a-bayesian-progression-model/