Estimating Dementia Risk Using Multifactorial Prediction Models.

Autor:	Kivimäki M; Department of Mental Health of Older People, UCL Brain Sciences, University College London, London, United Kingdom.; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland., Livingston G; Department of Mental Health of Older People, UCL Brain Sciences, University College London, London, United Kingdom., Singh-Manoux A; Department of Mental Health of Older People, UCL Brain Sciences, University College London, London, United Kingdom.; Université Paris Cité, Inserm U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Paris, France., Mars N; Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland.; Broad Institute of MIT and Harvard, Cambridge, Massachusetts., Lindbohm JV; Department of Mental Health of Older People, UCL Brain Sciences, University College London, London, United Kingdom.; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.; Broad Institute of MIT and Harvard, Cambridge, Massachusetts., Pentti J; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland., Nyberg ST; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland., Pirinen M; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.; Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland.; Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland., Anderson EL; Department of Mental Health of Older People, UCL Brain Sciences, University College London, London, United Kingdom.; MRC Integrative Epidemiology Unit and Population Health Sciences, University of Bristol Medical School, Bristol, United Kingdom., Hingorani AD; Institute of Cardiovascular Sciences, University College London, London, United Kingdom., Sipilä PN; Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Jazyk:	angličtina
Zdroj:	JAMA network open [JAMA Netw Open] 2023 Jun 01; Vol. 6 (6), pp. e2318132. Date of Electronic Publication: 2023 Jun 01.
DOI:	10.1001/jamanetworkopen.2023.18132
Abstrakt:	Importance: The clinical value of current multifactorial algorithms for individualized assessment of dementia risk remains unclear. Objective: To evaluate the clinical value associated with 4 widely used dementia risk scores in estimating 10-year dementia risk. Design, Setting, and Participants: This prospective population-based UK Biobank cohort study assessed 4 dementia risk scores at baseline (2006-2010) and ascertained incident dementia during the following 10 years. Replication with a 20-year follow-up was based on the British Whitehall II study. For both analyses, participants who had no dementia at baseline, had complete data on at least 1 dementia risk score, and were linked to electronic health records from hospitalizations or mortality were included. Data analysis was conducted from July 5, 2022, to April 20, 2023. Exposures: Four existing dementia risk scores: the Cardiovascular Risk Factors, Aging and Dementia (CAIDE)-Clinical score, the CAIDE-APOE-supplemented score, the Brief Dementia Screening Indicator (BDSI), and the Australian National University Alzheimer Disease Risk Index (ANU-ADRI). Main Outcomes and Measures: Dementia was ascertained from linked electronic health records. To evaluate how well each score predicted the 10-year risk of dementia, concordance (C) statistics, detection rate, false-positive rate, and the ratio of true to false positives were calculated for each risk score and for a model including age alone. Results: Of 465 929 UK Biobank participants without dementia at baseline (mean [SD] age, 56.5 [8.1] years; range, 38-73 years; 252 778 [54.3%] female participants), 3421 were diagnosed with dementia at follow-up (7.5 per 10 000 person-years). If the threshold for a positive test result was calibrated to achieve a 5% false-positive rate, all 4 risk scores detected 9% to 16% of incident dementia and therefore missed 84% to 91% (failure rate). The corresponding failure rate was 84% for a model that included age only. For a positive test result calibrated to detect at least half of future incident dementia, the ratio of true to false positives ranged between 1 to 66 (for CAIDE-APOE-supplemented) and 1 to 116 (for ANU-ADRI). For age alone, the ratio was 1 to 43. The C statistic was 0.66 (95% CI, 0.65-0.67) for the CAIDE clinical version, 0.73 (95% CI, 0.72-0.73) for the CAIDE-APOE-supplemented, 0.68 (95% CI, 0.67-0.69) for BDSI, 0.59 (95% CI, 0.58-0.60) for ANU-ADRI, and 0.79 (95% CI, 0.79-0.80) for age alone. Similar C statistics were seen for 20-year dementia risk in the Whitehall II study cohort, which included 4865 participants (mean [SD] age, 54.9 [5.9] years; 1342 [27.6%] female participants). In a subgroup analysis of same-aged participants aged 65 (±1) years, discriminatory capacity of risk scores was low (C statistics between 0.52 and 0.60). Conclusions and Relevance: In these cohort studies, individualized assessments of dementia risk using existing risk prediction scores had high error rates. These findings suggest that the scores were of limited value in targeting people for dementia prevention. Further research is needed to develop more accurate algorithms for estimation of dementia risk.
Databáze:	MEDLINE
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