{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T20:21:56Z","timestamp":1790713316401,"version":"4.1.0"},"reference-count":63,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T00:00:00Z","timestamp":1742428800000},"content-version":"vor","delay-in-days":19,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["alz-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Alzheimer's &amp;amp; Dementia"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>BACKGROUND<\/jats:title>\n                    <jats:p>Integrating non\u2010invasive measures to estimate abnormal amyloid beta accumulation (A\u03b2+) is key to developing a screening tool for preclinical Alzheimer's disease (AD). The predictive capability of standard neuropsychological tests in estimating A\u03b2+ has not been quantified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We constructed machine learning models using six cognitive measurements alongside demographic and genetic risk factors to predict A\u03b2 status. Data were drawn from three cohorts: Anti\u2010Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4), Alzheimer's Disease Neuroimaging Initiative (ADNI), and Australian Imaging, Biomarker &amp; Lifestyle (AIBL) study. Internal validation was conducted within A4 with external validations in ADNI and AIBL to assess model generalizability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>The highest area under the curve (AUC) for predicting A\u03b2+ was observed with demographic, genetic, and cognitive variables in A4 (median AUC\u00a0=\u00a00.745), but this was not significantly different from models without cognitive variables. External validation showed no improvement in ADNI and a slight decrease in AIBL.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>Standard neuropsychological tests do not significantly enhance A\u03b2+ prediction in cognitively unimpaired adults beyond demographic and genetic information.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Standard neuropsychological tests do not significantly improve the prediction of amyloid beta positivity (A\u03b2+) in cognitively unimpaired older adults beyond demographic and genetic information alone.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Across three well\u2010characterized cohorts, machine learning models incorporating cognitive measures failed to significantly improve A\u03b2+ prediction, indicating the limited relationship between cognitive performance on these tests and the risk of pre\u2010clinical Alzheimer's disease (AD).<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>These findings challenge assumptions about cognitive symptoms preceding A\u03b2+ screening and emphasize the need for developing more sensitive cognitive tests for early AD detection.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  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