Rhodius-Meester, HFM;
Liedes, H;
Koikkalainen, J;
Wolfsgruber, S;
Coll-Padros, N;
Kornhuber, J;
Peters, O;
... van der Flier, WM; + view all
(2018)
Computer-assisted prediction of clinical progression in the earliest stages of AD.
Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
, 10
pp. 726-736.
10.1016/j.dadm.2018.09.001.
Preview |
Text
Hanneke_2.0-S2352872918300666-main.pdf - Published Version Download (1MB) | Preview |
Abstract
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.
Archive Staff Only
 |
View Item |
