Literature DB >> 34172513

Development and validation of a predictive algorithm for risk of dementia in the community setting.

Stacey Fisher1,2,3, Douglas G Manuel4,2,3,5,6, Amy T Hsu4,2,3,6, Carol Bennett4,2, Meltem Tuna4,2, Anan Bader Eddeen4,2, Yulric Sequeira4,3, Mahsa Jessri4,2,5, Monica Taljaard4,3, Geoffrey M Anderson7,8, Peter Tanuseputro4,2,6,9.   

Abstract

BACKGROUND: Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed.
METHODS: The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health Survey (survey years 2001 to 2012). Five-year incidence of physician-diagnosed dementia was ascertained by individual linkage to administrative healthcare databases and using a validated case ascertainment definition with follow-up to March 2017. Sex-specific proportional hazards regression models considering competing risk of death were developed using self-reported risk factors including information on socio-demographic characteristics, general and chronic health conditions, health behaviours and physical function.
RESULTS: Among 75 460 respondents included in the combined derivation and validation cohorts, there were 8448 cases of incident dementia in 348 677 person-years of follow-up (5-year cumulative incidence, men: 0.044, 95% CI: 0.042 to 0.047; women: 0.057, 95% CI: 0.055 to 0.060). The final full models each include 90 df (65 main effects and 25 interactions) and 28 predictors (8 continuous). The DemPoRT algorithm is discriminating (C-statistic in validation data: men 0.83 (95% CI: 0.81 to 0.85); women 0.83 (95% CI: 0.81 to 0.85)) and well-calibrated in a wide range of subgroups including behavioural risk exposure categories, socio-demographic groups and by diabetes and hypertension status.
CONCLUSIONS: This algorithm will support the development and evaluation of population-level dementia prevention strategies, support decision-making for population health and can be used by individuals or their clinicians for individual risk assessment. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  dementia; disease modeling; epidemiology; public health

Year:  2021        PMID: 34172513     DOI: 10.1136/jech-2020-214797

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN: 0143-005X            Impact factor:   3.710


  2 in total

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Authors:  Xianglong Xu; Zongyuan Ge; Eric P F Chow; Zhen Yu; David Lee; Jinrong Wu; Jason J Ong; Christopher K Fairley; Lei Zhang
Journal:  J Clin Med       Date:  2022-03-25       Impact factor: 4.241

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  2 in total

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