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Lookup NU author(s): Professor Fiona MatthewsORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ. INTRODUCTION: Current efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool for dementia and multiple NCDs could be cost-effective and facilitate concurrent assessments as compared with a conventional single approach. The aim of this study is to develop and validate a new risk tool that estimates an individual's risk of developing dementia and other NCDs including diabetes mellitus, stroke and myocardial infarction. Once validated, it could be used by the public and general practitioners. METHODS AND ANALYSIS: Ten high-quality cohort studies from multiple countries were identified, which met eligibility criteria, including large representative samples, long-term follow-up, data on clinical diagnoses of dementia and NCDs, recognised modifiable risk factors for the four NCDs and mortality data. Pooled harmonised data from the cohorts will be used, with 65% randomly allocated for development of the predictive model and 35% for testing. Predictors include sociodemographic characteristics, general health risk factors and lifestyle/behavioural risk factors. A subdistribution hazard model will assess the risk factors' contribution to the outcome, adjusting for competing mortality risks. Point-based scoring algorithms will be built using predictor weights, internally validated and the discriminative ability and calibration of the model will be assessed for the outcomes. Sensitivity analyses will include recalculating risk scores using logistic regression. ETHICS AND DISSEMINATION: Ethics approval is provided by the University of New South Wales Human Research Ethics Committee (UNSW HREC; protocol numbers HC200515, HC3413). All data are deidentified and securely stored on servers at Neuroscience Research Australia. Study findings will be presented at conferences and published in peer-reviewed journals. The tool will be accessible as a public health resource. Knowledge translation and implementation work will explore strategies to apply the tool in clinical practice.
Author(s): Kootar S, Huque MH, Kiely KM, Anderson CS, Jorm L, Kivipelto M, Lautenschlager NT, Matthews F, Shaw JE, Whitmer RA, Peters R, Anstey KJ
Publication type: Article
Publication status: Published
Journal: BMJ Open
Year: 2023
Volume: 13
Issue: 9
Online publication date: 22/09/2023
Acceptance date: 05/09/2023
Date deposited: 09/10/2023
ISSN (print): 2044-6055
ISSN (electronic): 2044-6055
Publisher: BMJ Publishing Group
URL: https://doi.org/10.1136/bmjopen-2023-076860
DOI: 10.1136/bmjopen-2023-076860
PubMed id: 37739460
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