A BAYESIAN RE-ANALYSIS OF LECANEMAB (CLARITY AD) PHASE 3 TRIAL USING INFORMED T-TEST

Objective: Clinical trials for Alzheimer’s disease (AD) strive to enhance clinical symptomatology and modify the course of this intricate neurodegenerative disorder. Nonetheless, the conventional approach of null hypothesis significance testing (NHST) generally employed in these trials possesses limitations in evaluating the clinical significance and capturing detailed evidence for effectiveness on a gradual scale. In this study, we re-analyzed the phase 3 (Clarity-AD) trial of Lecanemab, a recently proposed humanized IgG1 monoclonal antibody that binds with high affinity to Aβ soluble protofibrils, using a Bayesian approach with informed t-test priors. Materials and Methods: We selected data from the trial and obtained effect size estimates for the primary endpoint, the Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB). Then, a set of Bayes Factor analyses was performed to compare the evidence for the null hypothesis (no effect of treatment) and the alternative hypothesis (effect present). Based on previous literature data and Lecanemab phase 3 trial, we used different minimal clinically important difference (MCID) values for the primary endpoint CDR-SB as priors. Results: Our results indicated anecdotal evidence in favor of the null hypothesis when using a standard prior. Robustness checks showed consistent results. Using informed priors, we found varying evidence for different MCID values, but overall, there was no evidence supporting the effectiveness of Lecanemab compared to the placebo. Discussion and Conclusion: Our study shows the value of Bayesian analysis in clinical trials while emphasizing the criticality of incorporating minimum clinically important difference (MCID) and effect size granularity when assessing treatment efficacy