Estimating preclinical amyloid positivity: A case study transporting ADNI to ARIC

Alzheimer's disease and related dementias researchers have benefited from deeply phenotyped clinical samples; however, there is a critical need for estimates that generalize to diverse, representative populations. Use of a statistical approach from causal inference, "transport," may allow generalization of findings from clinical samples to other target populations. Here we explore the feasibility and validity of extending results from a clinical sample, the Alzheimer's Disease Neuroimaging Initiative (ADNI), to a community-based target sample, the Atherosclerosis Risk in Communities Study Positron Emission Tomography Amyloid Imaging Study (ARIC-PET) using transport estimation and a standard approach, direct standardization, which itself can be considered a simple transport.

Eligible ARIC-PET (n = 343) and ADNI (n = 821) participants were White or Black, with normal cognition or mild cognitive impairment (MCI; 26.5% ARIC-PET, 56.4% ADNI). Estimates of amyloid positivity prevalence were derived from transporting from ADNI to ARIC-PET or standardizing ADNI to ARIC-ET using only sociodemographic characteristics and apolipoprotein E (APOE) ε4 status. Resulting estimates were compared to observed prevalences in ARIC-PET, overall and by age, sex, race, education, APOE ε4 status, and cognitive status.

Approximately half of transported prevalences were closer to observed ARIC-PET prevalences than the crude ADNI prevalences, including in all five subgroups in which crude prevalences differed substantially across cohorts. However, for many subgroups, transported prevalences were substantially further from observed ARIC-PET prevalences than crude ADNI prevalences. Standardization produced more variable estimates, which were not systematically closer to observed ARIC-PET prevalence than the crude ADNI prevalence estimates. Restriction to more homogenous samples did not improve performance of either method.

Although transport performed better than direct standardization in this example, available data appear insufficient to generalize findings from convenience samples to less selected samples with high confidence using either method. Recruitment of diverse, representative samples will likely be needed to derive population-level statistics given limitations of legacy samples.

Prior prevalence estimates of amyloid positivity are variable.Transport may improve generalization from samples to target populations.We standardized and transported estimates to a target with known prevalence.Neither worked reliably; transport performed better than standardization.Clinical convenience samples are inadequate to derive population-level statistics.