Evaluation of the performance of alternative models in analyzing longitudinal data for Alzheimer clinical trials compared to MMRM

Secondary prevention clinical trials (stage 2) for Alzheimer disease (AD) typically employs a cognitive composite score, consisting of multiple cognitive test scores, as the primary endpoint because of its sensitivity to subtle cognitive change. The underlying assumptions of using a composite score are that: (i) the treatment if effective will lead to similar treatment effects in each of its component (e.g., ∼25% reduction in the placebo progression); and (ii) the estimated treatment is an average of the treatment effects across the components regardless the satisfaction of assumption (i). The composite is typically analyzed using mixed models for repeated measurements (MMRM). Under the same assumptions, we proposed to analyze the composite using the multivariate MMRM (mMMRM) and the proportional mMMRM (PmMMRM). On the other hand, CDR SB is often used as the primary endpoint in early‐stage AD trials (stage 3), however, 20% to 30% of the placebo patients demonstrated no progression during an 18‐month follow‐up. These non‐progression participants would dilute the treatment effect comparison under the MMRM analysis. Because CDR SB is an ordinal rank measure, we propose to analyze it using the Cox proportional hazards model for recurrent events, where a recurrent event is defined as any ordinal increment over the previous visit. The goal of this study is to evaluate the performance (i.e., power) of these alternative models relative to MMRM.