To investigate the influence of heterogeneity in disease progression for detecting treatment effects in Alzheimer disease (AD) trials, using a simulation study.
Individuals with an abnormal amyloid PET scan, diagnosis of mild cognitive impairment or dementia, baseline Mini-Mental State Examination (MMSE) score ≥24, global Clinical Dementia Rating (CDR) score of 0.5, and ≥1 follow-up cognitive assessment were selected from the Alzheimer’s Disease Neuroimaging Initiative database (n = 302, age 73 ± 6.7; 44% female; 16.1 ± 2.7 years of education; 69% APOE 4 carrier). We simulated a clinical trial by randomly assigning individuals to a “placebo” and “treatment” group and subsequently computed group differences on the CDR–sum of boxes (CDR-SB), Alzheimer’s Disease Assessment Scale–cognitive subscale–13 and MMSE after 18 months follow-up. We repeated this simulation 10,000 times to determine the 95% range of effect sizes. We further studied the influence of known AD risk factors (age, sex, education, APOE 4 status, CSF total tau levels) on the variability in effect sizes.
Individual trajectories on all cognitive outcomes were highly variable, and the 95% ranges of possible effect sizes at 18 months were broad (e.g., ranging from 0.35 improvement to 0.35 decline on the CDR-SB). Results of recent anti-amyloid trials mostly fell within these 95% ranges of effect sizes. APOE 4 carriers and individuals with abnormal baseline tau levels showed faster decline at group level, but also greater within-group variability, as illustrated by broader 95% effect size ranges (e.g., ±0.70 points for the CDR-SB).
Individuals with early AD show heterogeneity in disease progression, which increases when stratifying on risk factors associated with progression. We provide guidance for a priori effect sizes on cognitive outcomes for detecting true change, which is crucial for future AD trials.