Remote identification of MCI using self‐ and study partner‐report subjective cognitive decline in the Brain Health Registry

Abstract

AbstractBackgroundEfficient identification of older adults with Mild Cognitive Impairment (MCI), including MCI due to AD, is a pressing challenge. Remote methods to accurately identify older adults with MCI are a promising approach. Subjective cognitive decline (SCD), reported by individuals and their study partners, can be efficiently collected remotely.MethodsIn 1286 older adults in the Brain Health Registry (BHR, Table 1), using logistic regression, we determined the accuracy of online self‐report mood (Geriatric Depression Scale Short Form, GDS), family history of AD, Everyday Cognition Scale (ECog) as a measure of SCD, and Cogstate Brief Battery one card learning (OCL) accuray to distinguish (1) Cognitively‐unimpaired (CU) from MCI, and (2) CU from b‐amyloid (Ab)+ MCI. In a subset of 289 participants with enrolled study partners, we measured the contribution of study partner‐report SCD to predicting diagnostic category, and the correlation between self‐ and study partner‐report SCD. Models covaried for age, gender, and education level.ResultsSelf‐ and study partner‐report SCD scores were moderately correlated (r=0.44); associations between the two measures were significantly lower in participants with higher GDS scores, indicating more depressive symptoms (p=0.03). Models including self‐ and study partner‐report SCD and Cogstate OCL scores had the highest accuracy for distinguishing CU from all MCI, as well as CU from Ab+ MCI (AUC=0.90 for CU vs MCI; AUC=0.93 for CU vs Ab+ MCI). Models excluding study partner‐report SCD had moderate accuracy at diagnostic classification (AUC=0.81 for CU vs MCI; AUC=0.83 for CU vs Ab+ MCI). Models excluding all SCD measures, and instead relying on OCL accuracy scores, had lower accuracy (AUC=0.73 for CU vs MCI; AUC=0.76 for CU vs Ab+ MCI). Model outputs are summarized in Table 2.ConclusionsRemotely‐collected self‐ and study partner‐report SCD accurately distinguish CU from MCI, as well as CU from biomarker positive MCI. SCD measures perform well in identifying MCI, even in the absence of objective cognitive measures. Results support utilization of remote SCD measures to identify older adults for prodromal AD clinical trials, and who are suitable candidates to receive future anti‐amyloid therapeutics.