Computer-assisted prediction of clinical progression in the earliest stages of AD

Hanneke F.M. Rhodius-Meester (Corresponding Author), Hilkka Liedes, Juha Koikkalainen, Steffen Wolfsgruber, Nina Coll-Padros, Johannes Kornhuber, Oliver Peters, Frank Jessen, Luca Kleineidam, José Luis Molinuevo, Lorena Rami, Charlotte E. Teunissen, Frederik Barkhof, Sietske A.M. Sikkes, Linda M.P. Wesselman, Rosalinde E.R. Slot, Sander C.J. Verfaillie, Philip Scheltens, Betty M. Tijms, Jyrki LötjönenWiesje M. van der Flier

    Research output: Contribution to journalArticleScientificpeer-review

    9 Citations (Scopus)


    Introduction: Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression. Methods: We included 674 patients with SCD (46% female, 64 ± 9 years, Mini–Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts. Results: After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8). Discussion: We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable.

    Original languageEnglish
    Pages (from-to)726-736
    Number of pages11
    JournalAlzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
    Publication statusPublished - Jan 2018
    MoE publication typeA1 Journal article-refereed


    • Alzheimer's disease
    • Clinical decision support system
    • Diagnostic test assessment
    • Prognosis
    • Subjective cognitive decline


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