{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T11:17:49Z","timestamp":1790162269776,"version":"4.1.0"},"reference-count":44,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2021,7,23]],"date-time":"2021-07-23T00:00:00Z","timestamp":1626998400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Euro J of Neurology"],"published-print":{"date-parts":[[2021,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Alzheimer's disease (AD) is characterized by a heterogeneous course. Predicting a fast rather than a slow decline over time is crucial to both provide a reliable prognosis and elaborate stricter enrolment criteria in clinical trials. Here we searched for independent predictors of cognitive decline rate to assess the risk of fast disease progression already at baseline.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Fifty\u2010three subjects with an \u201cin\u2010vivo biomarker confirmed\u201d diagnosis of AD were included. Neuropsychological assessment, plasma neurofilaments (NfL) concentrations and, in a subsample of 23 patients, brain magnetic resonance imaging were available. Patients were labelled FAST or SLOW depending on the Mini\u2010Mental State Examination (MMSE) points lost per year (FAST if more than 3 points). We adopted single logistic regression models to search for independent predictors of FAST progression.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>At baseline no differences were found between FAST and SLOW subgroups in demographics, MMSE scores, vascular burden and medial temporal lobe atrophy measurements. Higher plasma NfL concentrations and worse scores at semantic verbal fluency (SVF) and clock drawing test (CDT) were independent predictors of FAST decline, after controlling for age, education, sex and baseline disease severity stage. The regression model combining all the predictors correctly classified 80% of patients overall. The risk of FAST decline was 81.2% if all the three predictors were abnormal (i.e., SVF\u00a0\u226421.5, CDT\u00a0\u22645.5, NfL\u00a0\u226522.19).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>An easily applicable algorithm, including plasma NfL measurement and two neuropsychological tests worldwide adopted in clinical practice (SVF and CDT), may allow clinicians to reliably stratify AD patients in relation to the risk of fast cognitive decline.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ene.14999","type":"journal-article","created":{"date-parts":[[2021,6,27]],"date-time":"2021-06-27T19:04:15Z","timestamp":1624820655000},"page":"2980-2988","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Plasma neurofilament light chain levels and cognitive testing as predictors of fast progression in Alzheimer\u2019s 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