Analytic Challenges in Clinical Trials of Early Alzheimer’s Disease

The present investigation assessed how the heavily right-skewed data seen in recently reported results in Alzheimer’s Disease (AD) clinical trials influenced treatment contrasts when data were analyzed via the typical mixed-effects model for repeated measures (MMRM) versus robust regression (RR) and the non-parametric Hodges-Lehman estimator (HL). Results in simulated data patterned after AD trials showed that imbalance across treatment arms in the number of patients in the extreme right tail (those with rapid disease progression) frequently occurred by chance alone. Each analysis method controlled Type I error at or below the nominal level. The RR analysis yielded smaller standard errors, and more power than MMRM and HL. In datasets with appreciable imbalance in the number of rapid progressing patients, MMRM results favored the treatment arm with fewer rapid progressors. Results from HL showed the same trend, but to a lesser degree. Robust regression yielded similar results regardless of the ratio of rapid progressors. Although more research is needed over a wider range of scenarios, it should not be assumed that MMRM is the optimal approach for trials in early Alzheimer’s Disease.