Alzheimer disease identification using amyloid imaging and reserve variables

Abstract

Objective: Several factors may influence the relationship between Alzheimer disease (AD) lesions and the expression of dementia, including those related to brain and cognitive reserve. Other factors may confound the association between AD pathology and dementia. We tested whether factors thought to influence the association of AD pathology and dementia help to accurately identify dementia of the Alzheimer type (DAT) when considered together with amyloid imaging.

Methods: Participants with normal cognition (n = 180) and with DAT (n = 25), aged 50 years or older, took part in clinical, neurologic, and psychometric assessments. PET with the Pittsburgh compound B (PiB) tracer was used to measure brain amyloid, yielding a mean cortical binding potential (MCBP) reflecting PiB uptake. Logistic regression was used to generate receiver operating characteristic curves, and the areas under those curves (AUC), to compare the predictive accuracy of using MCBP alone vs MCBP together with other variables selected using a stepwise selection procedure to identify participants with DAT vs normal cognition.

Results: The AUC resulting from MCBP alone was 0.84 (95% confidence interval [CI] = 0.73–0.94; cross-validated AUC = 0.80, 95% CI = 0.68–0.92). The AUC for the predictive equation generated by a stepwise model including education, normalized whole brain volume, physical health rating, gender, and use of medications that may interfere with cognition was 0.94 (95% CI = 0.90–0.98; cross-validated AUC = 0.91, 95% CI = 0.85–0.96), an improvement (p = 0.025) over that yielded using MCBP alone.

Conclusion: Results suggest that factors reported to influence associations between AD pathology and dementia can improve the predictive accuracy of amyloid imaging for the identification of symptomatic AD.