Md Hamidul Huque
A single risk assessment for the most common diseases of ageing, developed and validated on 10 cohort studies
Huque, Md Hamidul; Kootar, Scherazad; Kiely, Kim M.; Anderson, Craig S.; van Boxtel, Martin; Brodaty, Henry; Sachdev, Perminder S.; Carlson, Michelle; Fitzpatrick, Annette L.; Whitmer, Rachel A.; Kivipelto, Miia; Jorm, Louisa; Köhler, Sebastian; Lautenschlager, Nicola T.; Lopez, Oscar L.; Shaw, Jonathan E.; Matthews, Fiona E.; Peters, Ruth; Anstey, Kaarin J.
Authors
Scherazad Kootar
Kim M. Kiely
Craig S. Anderson
Martin van Boxtel
Henry Brodaty
Perminder S. Sachdev
Michelle Carlson
Annette L. Fitzpatrick
Rachel A. Whitmer
Miia Kivipelto
Louisa Jorm
Sebastian Köhler
Nicola T. Lautenschlager
Oscar L. Lopez
Jonathan E. Shaw
Professor Fiona Matthews F.Matthews@hull.ac.uk
Pro-Vice-Chancellor Research and Enterprise
Ruth Peters
Kaarin J. Anstey
Abstract
BACKGROUND: We aimed to develop risk tools for dementia, stroke, myocardial infarction (MI), and diabetes, for adults aged ≥ 65years using shared risk factors. METHODS: Data were obtained from 10 population-based cohorts (N = 41,755) with median follow-up time (years) for dementia, stroke, MI, and diabetes of 6.2, 7.0, 6.8, and 7.4, respectively. Disease-free participants at baseline were included, and 22 risk factors (sociodemographic, medical, lifestyle, laboratory biomarkers) were evaluated. Two risk tools (DemNCD and DemNCD-LR based on Fine and Gray sub-distribution and logistic regression [LR], respectively) were developed and validated. Predictive accuracies of these risk tools were assessed using Harrel's C-statistics and area under the curve (AUC) and 95% confidence interval (CI). Model calibration was conducted using Hosmer-Lemeshow goodness of fit test along calibration plots. RESULTS: Both the DemNCD and DemNCD-LR resulted in similar predictive accuracy for each outcome. The overall AUC (95% CI) for dementia, stroke, MI, and diabetes risk tool were 0·68 (0·65, 0·70), 0·58 (0·54, 0·61), 0·65 (0·61, 0·68), and 0·68 (0·64, 0·72), respectively, for males. For females, these figures were 0·65 (0·63, 0·67), 0·55 (0·52, 0·57), 0·65 (0·62, 0·68), and 0·61 (0·57, 0·65). CONCLUSIONS: The DemNCD is the first tool to predict both dementia and multiple cardio-metabolic diseases using comprehensive risk factors and provided similar predictive accuracy to existing risk tools. It has similar predictive accuracy as tools designed for single outcomes in this age-group. DemNCD has the potential to be used in community and clinical settings as it includes self-reported and routinely available clinical measures.
Citation
Huque, M. H., Kootar, S., Kiely, K. M., Anderson, C. S., van Boxtel, M., Brodaty, H., Sachdev, P. S., Carlson, M., Fitzpatrick, A. L., Whitmer, R. A., Kivipelto, M., Jorm, L., Köhler, S., Lautenschlager, N. T., Lopez, O. L., Shaw, J. E., Matthews, F. E., Peters, R., & Anstey, K. J. (2024). A single risk assessment for the most common diseases of ageing, developed and validated on 10 cohort studies. BMC medicine, 22(1), Article 501. https://doi.org/10.1186/s12916-024-03711-6
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 17, 2024 |
Online Publication Date | Oct 31, 2024 |
Publication Date | Oct 31, 2024 |
Deposit Date | Nov 1, 2024 |
Publicly Available Date | Nov 4, 2024 |
Journal | BMC medicine |
Electronic ISSN | 1741-7015 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 22 |
Issue | 1 |
Article Number | 501 |
DOI | https://doi.org/10.1186/s12916-024-03711-6 |
Keywords | Risk factors; Risk tool; Primary prevention; Dementia; Stroke; Diabetes; Heart attack; Risk prediction |
Public URL | https://hull-repository.worktribe.com/output/4908091 |
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Copyright Statement
© The Author(s) 2024.
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
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