Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Observational Study
. 2025;23(5):602-611.
doi: 10.2174/011570159X332930240925095423.

Fast Declining Prediction in Alzheimer's Disease from Early Clinical Assessment

Lourdes Alvarez-Sanchez  1   2 , Mar Pereto  1 , Lorena Garcia-Valles  1 , Angel Balaguer  3 , Carmen Pena-Bautista  1 , Laura Ferre-Gonzalez  1 , Miguel Baquero  1   2 , Consuelo Chafer Pericas  1
Affiliations
Observational Study

Fast Declining Prediction in Alzheimer's Disease from Early Clinical Assessment

Lourdes Alvarez-Sanchez et al. Curr Neuropharmacol. 2025.

Abstract

Introduction: The heterogenicity in Alzheimer's Disease (AD) progression hinders individual prognosis. The present work is an observational 2-year longitudinal study in patients with mild cognitive impairment due to AD (n = 52, with positive CSF biomarkers). The aim of this study is to predict which patients are at risk of fast progression. For this, 3 neuropsychological tests based on different domains (clinical dementia, cognition, delayed memory) and the sum of them were used.

Methods: The tests were performed at diagnosis time (T1) and two years after the diagnosis time (T2). Then, the corresponding progression models were developed using each individual test and their sum as a variable response.

Results: As a result, the model based on cognition status to predict fast decline (differences in the Z score (T2-T1) <1.5 were considered fast declining) provided satisfactory performance (AUC 0.74, 83.3% of sensibility and 70.2% of specificity); the models based on clinical dementia and delayed memory to predict fast declining showed low AUC and sensitivity. Nevertheless, the model based on the sum of the 3 tests showed the highest AUC (0.79), low sensitivity (63.6%), and high specificity.

Conclusion: The developed progression models could provide useful information to clinicians and AD patients regarding their fast/normal decline in general or specific domains.

Keywords: Alzheimer’s disease; biomarker.; early assessment; follow-up; neuropsychology; prognostic.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest, financial or otherwise.

References

    1. Hodson R. Alzheimer’s disease. Nature. 2018;559(7715):S1–S1. doi: 10.1038/d41586-018-05717-6. - DOI - PubMed
    1. 2015 Alzheimer’s disease facts and figures. Alzheimers Dement. 2015;11(3):332–384. doi: 10.1016/j.jalz.2015.02.003. - DOI - PubMed
    1. Mattson M.P. Pathways towards and away from Alzheimer’s disease. Nature. 2004;430(7000):631–639. doi: 10.1038/nature02621. - DOI - PMC - PubMed
    1. Hyman B.T., Phelps C.H., Beach T.G., Bigio E.H., Cairns N.J., Carrillo M.C., Dickson D.W., Duyckaerts C., Frosch M.P., Masliah E., Mirra S.S., Nelson P.T., Schneider J.A., Thal D.R., Thies B., Trojanowski J.Q., Vinters H.V., Montine T.J. National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease. Alzheimers Dement. 2012;8(1):1–13. doi: 10.1016/j.jalz.2011.10.007. - DOI - PMC - PubMed
    1. Long J.M., Holtzman D.M. Alzheimer disease: An update on pathobiology and treatment strategies. Cell. 2019;179(2):312–339. doi: 10.1016/j.cell.2019.09.001. - DOI - PMC - PubMed

Publication types

LinkOut - more resources