Objective: To investigate the influence of heterogeneity in disease progression for detecting treatment effects in Alzheimer’s disease (AD) trials, using a simulation study.

Methods: Individuals with an abnormal amyloid PET scan, diagnosis of MCI or dementia, baseline MMSE ≥ 24, global CDR of 0.5, and ≥ 1 follow-up cognitive assessment were selected from the ADNI database (N=302, age 73±6.7; 44% female; 16.1±2.7 years of education; 69% APOE-e4 carrier). We simulated a clinical trial by randomly assigning individuals to a ‘placebo’ and ‘treatment’ group and subsequently computed group differences on the CDR-SB, ADAS-Cog-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-e4 status, CSF total tau levels) on the variability in effect-sizes.

Results: 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-e4 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).

Conclusions: 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.