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Risk prediction models for dementia: role of age and cardiometabolic risk factors

BACKGROUND: Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score is the only currently available midlife risk score for dementia. We compared CAIDE to Framingham cardiovascular Risk Score (FRS) and FINDRISC diabetes score as predictors of dementia and assessed the role of...

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Autores principales: Fayosse, Aurore, Nguyen, Dinh-Phong, Dugravot, Aline, Dumurgier, Julien, Tabak, Adam G., Kivimäki, Mika, Sabia, Séverine, Singh-Manoux, Archana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236124/
https://www.ncbi.nlm.nih.gov/pubmed/32423410
http://dx.doi.org/10.1186/s12916-020-01578-x
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author Fayosse, Aurore
Nguyen, Dinh-Phong
Dugravot, Aline
Dumurgier, Julien
Tabak, Adam G.
Kivimäki, Mika
Sabia, Séverine
Singh-Manoux, Archana
author_facet Fayosse, Aurore
Nguyen, Dinh-Phong
Dugravot, Aline
Dumurgier, Julien
Tabak, Adam G.
Kivimäki, Mika
Sabia, Séverine
Singh-Manoux, Archana
author_sort Fayosse, Aurore
collection PubMed
description BACKGROUND: Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score is the only currently available midlife risk score for dementia. We compared CAIDE to Framingham cardiovascular Risk Score (FRS) and FINDRISC diabetes score as predictors of dementia and assessed the role of age in their associations with dementia. We then examined whether these risk scores were associated with dementia in those free of cardiometabolic disease over the follow-up. METHODS: A total of 7553 participants, 39–63 years in 1991–1993, were followed for cardiometabolic disease (diabetes, coronary heart disease, stroke) and dementia (N = 318) for a mean 23.5 years. Cox regression was used to model associations of age at baseline, CAIDE, FRS, and FINDRISC risk scores with incident dementia. Predictive performance was assessed using Royston’s R(2), Harrell’s C-index, Akaike’s information criterion (AIC), the Greenwood-Nam-D’Agostino (GND) test, and calibration-in-the-large. Age effect was also assessed by stratifying analyses by age group. Finally, in multistate models, we examined whether cardiometabolic risk scores were associated with incidence of dementia in persons who remained free of cardiometabolic disease over the follow-up. RESULTS: Among the risk scores, the predictive performance of CAIDE (C-statistic = 0.714; 95% CI 0.690–0.739) and FRS (C-statistic = 0.719; 95% CI 0.693–0.745) scores was better than FINDRISC (C-statistic = 0.630; 95% CI 0.602–0.659); p < 0.001), AIC difference > 3; R(2) 32.5%, 32.0%, and 12.5%, respectively. When the effect of age in these risk scores was removed by drawing data on risk scores at age 55, 60, and 65 years, the association with dementia in all age groups remained for FRS and FINDRISC, but not for CAIDE. Only FRS at age 55 was associated with dementia in persons who remained free of cardiometabolic diseases prior to dementia diagnosis while no such association was observed at older ages for any risk score. CONCLUSIONS: Our analyses of CAIDE, FRS, and FINDRISC show the FRS in midlife to predict dementia as well as the CAIDE risk score, its predictive value being also evident among individuals who did not develop cardiometabolic events. The importance of age in the predictive performance of all three risk scores highlights the need for the development of multivariable risk scores in midlife for primary prevention of dementia.
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spelling pubmed-72361242020-05-27 Risk prediction models for dementia: role of age and cardiometabolic risk factors Fayosse, Aurore Nguyen, Dinh-Phong Dugravot, Aline Dumurgier, Julien Tabak, Adam G. Kivimäki, Mika Sabia, Séverine Singh-Manoux, Archana BMC Med Research Article BACKGROUND: Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score is the only currently available midlife risk score for dementia. We compared CAIDE to Framingham cardiovascular Risk Score (FRS) and FINDRISC diabetes score as predictors of dementia and assessed the role of age in their associations with dementia. We then examined whether these risk scores were associated with dementia in those free of cardiometabolic disease over the follow-up. METHODS: A total of 7553 participants, 39–63 years in 1991–1993, were followed for cardiometabolic disease (diabetes, coronary heart disease, stroke) and dementia (N = 318) for a mean 23.5 years. Cox regression was used to model associations of age at baseline, CAIDE, FRS, and FINDRISC risk scores with incident dementia. Predictive performance was assessed using Royston’s R(2), Harrell’s C-index, Akaike’s information criterion (AIC), the Greenwood-Nam-D’Agostino (GND) test, and calibration-in-the-large. Age effect was also assessed by stratifying analyses by age group. Finally, in multistate models, we examined whether cardiometabolic risk scores were associated with incidence of dementia in persons who remained free of cardiometabolic disease over the follow-up. RESULTS: Among the risk scores, the predictive performance of CAIDE (C-statistic = 0.714; 95% CI 0.690–0.739) and FRS (C-statistic = 0.719; 95% CI 0.693–0.745) scores was better than FINDRISC (C-statistic = 0.630; 95% CI 0.602–0.659); p < 0.001), AIC difference > 3; R(2) 32.5%, 32.0%, and 12.5%, respectively. When the effect of age in these risk scores was removed by drawing data on risk scores at age 55, 60, and 65 years, the association with dementia in all age groups remained for FRS and FINDRISC, but not for CAIDE. Only FRS at age 55 was associated with dementia in persons who remained free of cardiometabolic diseases prior to dementia diagnosis while no such association was observed at older ages for any risk score. CONCLUSIONS: Our analyses of CAIDE, FRS, and FINDRISC show the FRS in midlife to predict dementia as well as the CAIDE risk score, its predictive value being also evident among individuals who did not develop cardiometabolic events. The importance of age in the predictive performance of all three risk scores highlights the need for the development of multivariable risk scores in midlife for primary prevention of dementia. BioMed Central 2020-05-19 /pmc/articles/PMC7236124/ /pubmed/32423410 http://dx.doi.org/10.1186/s12916-020-01578-x Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made. 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/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Fayosse, Aurore
Nguyen, Dinh-Phong
Dugravot, Aline
Dumurgier, Julien
Tabak, Adam G.
Kivimäki, Mika
Sabia, Séverine
Singh-Manoux, Archana
Risk prediction models for dementia: role of age and cardiometabolic risk factors
title Risk prediction models for dementia: role of age and cardiometabolic risk factors
title_full Risk prediction models for dementia: role of age and cardiometabolic risk factors
title_fullStr Risk prediction models for dementia: role of age and cardiometabolic risk factors
title_full_unstemmed Risk prediction models for dementia: role of age and cardiometabolic risk factors
title_short Risk prediction models for dementia: role of age and cardiometabolic risk factors
title_sort risk prediction models for dementia: role of age and cardiometabolic risk factors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236124/
https://www.ncbi.nlm.nih.gov/pubmed/32423410
http://dx.doi.org/10.1186/s12916-020-01578-x
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