How many sites are enough? a novel, site-based power analysis method for real-world registry studies of anti-amyloid monoclonal antibodies.

Background: Real-world registries ALZ-NET (US) and AD-DMT (Japan) support safety surveillance of anti-amyloid antibodies. Conventional power calculations-dividing required patients by mean per-site caseload-can underestimate the number of centers needed because of patient counts variability.

Objectives: To develop and evaluate a simulation-based method for site-level sample size planning that incorporates inter-site variability.

Design: We developed a simulation using a zero-truncated negative binomial model to reflect caseload heterogeneity. We estimated the required sites (k) to achieve a target precision (95 % confidence interval [CI] width) for ARIA incidence under random and volume-weighted sampling, based on data from published trials. The required number of sites was determined as the point where the CI width met a prespecified precision target (< 0.1).

Setting: Simulated ALZ-NET and AD-DMT registry settings using prevalence and ARIA frequencies from published lecanemab and donanemab trials.

Measurements: Precision (95 % CI width) for estimating ARIA incidence in APOE-ε4 homozygotes; comparison of required site counts as estimated by the three methods.

Results: Under random sampling, our method's site requirement (∼320 sites) was consistent with the ICC-adjusted method, whereas the conventional method underestimated the need (∼220 sites). Critically, our framework showed that strategic volume-weighted sampling could reduce the requirement to as few as 110 sites, surpassing the efficiency of the static analytical methods.

Conclusions: Conventional methods risk underestimating site requirements by ignoring caseload heterogeneity. Our simulation framework provides more realistic estimates and, crucially, quantifies the substantial efficiency gains from strategic recruitment, serving as a flexible tool to optimize registry design.