A Comparison of Cross-Sectional and Longitudinal Methods of Defining Objective Subtle Cognitive Decline in Preclinical Alzheimer’s Disease Based on Cogstate One Card Learning Accuracy Performance

Article type: Research Article

Authors: Pudumjee, Shehroo B.^a | Lundt, Emily S.^b | Albertson, Sabrina M.^b | Machulda, Mary M.^a | Kremers, Walter K.^b | Jack Jr., Clifford R.^c | Knopman, David S.^d | Petersen, Ronald C.^e | Mielke, Michelle M.^{d; e} | Stricker, Nikki H.^{a; *}

Affiliations: [a] Division of Neurocognitive Disorders, Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA | [b] Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA | [c] Department of Radiology, Mayo Clinic, Rochester, MN, USA | [d] Department of Neurology, Mayo Clinic, Rochester, MN, USA | [e] Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

Correspondence: [*] Correspondence to: Nikki H. Stricker, PhD, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. Tel.: +1 507 284 2649; Fax: +1 507 284 4158; E-mail: [email protected].; ©2021 Mayo Foundation for Medical Education and Research

Abstract: Background:Longitudinal, but not cross-sectional, cognitive testing is one option proposed to define transitional cognitive decline for individuals on the Alzheimer’s disease continuum. Objective:Compare diagnostic accuracy of cross-sectional subtle objective cognitive impairment (sOBJ) and longitudinal objective decline (ΔOBJ) over 30 months for identifying 1) cognitively unimpaired participants with preclinical Alzheimer’s disease defined by elevated brain amyloid and tau (A+T+) and 2) incident mild cognitive impairment (MCI) based on Cogstate One Card Learning (OCL) accuracy performance. Methods:Mayo Clinic Study of Aging cognitively unimpaired participants aged 50 + with amyloid and tau PET scans (n = 311) comprised the biomarker-defined sample. A case-control sample of participants aged 65 + remaining cognitively unimpaired for at least 30 months included 64 who subsequently developed MCI (incident MCI cases) and 184 controls, risk-set matched by age, sex, education, and visit number. sOBJ was assessed by OCL z-scores. ΔOBJ was assessed using within subjects’ standard deviation and annualized change from linear regression or linear mixed effects (LME) models. Concordance measures Area Under the ROC Curve (AUC) or C-statistic and odds ratios (OR) from conditional logistic regression models were derived. sOBJ and ΔOBJ were modeled jointly to compare methods. Results:sOBJ and ΔOBJ-LME methods differentiated A+T+ from A-T- (AUC = 0.64, 0.69) and controls from incident MCI (C-statistic = 0.59, 0.69) better than chance; other ΔOBJ methods did not. ΔOBJ-LME improved prediction of future MCI over baseline sOBJ (p = 0.003) but not over 30-month sOBJ (p = 0.09). Conclusion:Longitudinal decline did not offer substantial benefit over cross-sectional assessment in detecting preclinical Alzheimer’s disease or incident MCI.

Keywords: Amyloid, biomarker, cognigram, memory, neuropsychology, reliable change index, sensitivity and specificity, tau, transitional cognitive decline, validity

DOI: 10.3233/JAD-210251

Journal: Journal of Alzheimer's Disease, vol. 83, no. 2, pp. 861-877, 2021