Literature DB >> 25190680

Prognostic score for predicting risk of dementia over 10 years while accounting for competing risk of death.

Hélène Jacqmin-Gadda, Paul Blanche, Emilie Chary, Lucie Loubère, Hélène Amieva, Jean-François Dartigues.   

Abstract

Early detection of subjects at high risk of developing dementia is essential. By dealing with censoring and competing risk of death, we developed a score for predicting 10-year dementia risk by combining cognitive tests, and we assessed whether inclusion of cognitive change over the previous year increased its discrimination. Data came from the French prospective cohort study Personnes Agées QUID (PAQUID) and included 3,777 subjects aged 65 years or older (1988-1998). The combined prediction score was estimated by means of an illness-death model handling interval censoring and competing risk of death. Its predictive ability was measured using the receiver operating characteristic (ROC) curve, with 2 different definitions depending on the way subjects who died without a dementia diagnosis were considered. To account for right-censoring and interval censoring, we estimated the ROC curves by means of a weighting approach and a model-based imputation estimator. The combined score exhibited an area under the ROC curve (AUROC) of 0.81 for discriminating future demented subjects from subjects alive and nondemented 10 years later and an AUROC of 0.75 for discriminating future demented subjects from all other subjects (including deceased persons). Adjustment for cognitive change over the previous year did not improve prediction.
© The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  ROC curve; competing risks; death; dementia; interval censoring; prediction

Mesh:

Year:  2014        PMID: 25190680     DOI: 10.1093/aje/kwu202

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


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