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Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study
AIMS: The aim of this study was to derive and validate a risk prediction model with nationwide coverage to predict the individual and population-level risk of cardiovascular disease (CVD). METHODS AND RESULTS: All 2.98 million Danish residents aged 30–85 years free of CVD were included on 1 January...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241501/ https://www.ncbi.nlm.nih.gov/pubmed/35919262 http://dx.doi.org/10.1093/ehjopen/oeab015 |
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author | Christensen, Daniel Mølager Phelps, Matthew Gerds, Thomas Malmborg, Morten Schjerning, Anne-Marie Strange, Jarl Emanuel El-Chouli, Mohamad Larsen, Lars Bruun Fosbøl, Emil Køber, Lars Torp-Pedersen, Christian Mehta, Suneela Jackson, Rod Gislason, Gunnar |
author_facet | Christensen, Daniel Mølager Phelps, Matthew Gerds, Thomas Malmborg, Morten Schjerning, Anne-Marie Strange, Jarl Emanuel El-Chouli, Mohamad Larsen, Lars Bruun Fosbøl, Emil Køber, Lars Torp-Pedersen, Christian Mehta, Suneela Jackson, Rod Gislason, Gunnar |
author_sort | Christensen, Daniel Mølager |
collection | PubMed |
description | AIMS: The aim of this study was to derive and validate a risk prediction model with nationwide coverage to predict the individual and population-level risk of cardiovascular disease (CVD). METHODS AND RESULTS: All 2.98 million Danish residents aged 30–85 years free of CVD were included on 1 January 2014 and followed through 31 December 2018 using nationwide administrative healthcare registries. Model predictors and outcome were pre-specified. Predictors were age, sex, education, use of antithrombotic, blood pressure-lowering, glucose-lowering, or lipid-lowering drugs, and a smoking proxy of smoking-cessation drug use or chronic obstructive pulmonary disease. Outcome was 5-year risk of first CVD event, a combination of ischaemic heart disease, heart failure, peripheral artery disease, stroke, or cardiovascular death. Predictions were computed using cause-specific Cox regression models. The final model fitted in the full data was internally-externally validated in each Danish Region. The model was well-calibrated in all regions. Area under the receiver operating characteristic curve (AUC) and Brier scores ranged from 76.3% to 79.6% and 3.3 to 4.4. The model was superior to an age-sex benchmark model with differences in AUC and Brier scores ranging from 1.2% to 1.5% and −0.02 to −0.03. Average predicted risks in each Danish municipality ranged from 2.8% to 5.9%. Predicted risks for a 66-year old ranged from 2.6% to 25.3%. Personalized predicted risks across ages 30–85 were presented in an online calculator (https://hjerteforeningen.shinyapps.io/cvd-risk-manuscript/). CONCLUSION: A CVD risk prediction model based solely on nationwide administrative registry data provided accurate prediction of personal and population-level 5-year first CVD event risk in the Danish population. This may inform clinical and public health primary prevention efforts. |
format | Online Article Text |
id | pubmed-9241501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92415012022-08-01 Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study Christensen, Daniel Mølager Phelps, Matthew Gerds, Thomas Malmborg, Morten Schjerning, Anne-Marie Strange, Jarl Emanuel El-Chouli, Mohamad Larsen, Lars Bruun Fosbøl, Emil Køber, Lars Torp-Pedersen, Christian Mehta, Suneela Jackson, Rod Gislason, Gunnar Eur Heart J Open Original Article AIMS: The aim of this study was to derive and validate a risk prediction model with nationwide coverage to predict the individual and population-level risk of cardiovascular disease (CVD). METHODS AND RESULTS: All 2.98 million Danish residents aged 30–85 years free of CVD were included on 1 January 2014 and followed through 31 December 2018 using nationwide administrative healthcare registries. Model predictors and outcome were pre-specified. Predictors were age, sex, education, use of antithrombotic, blood pressure-lowering, glucose-lowering, or lipid-lowering drugs, and a smoking proxy of smoking-cessation drug use or chronic obstructive pulmonary disease. Outcome was 5-year risk of first CVD event, a combination of ischaemic heart disease, heart failure, peripheral artery disease, stroke, or cardiovascular death. Predictions were computed using cause-specific Cox regression models. The final model fitted in the full data was internally-externally validated in each Danish Region. The model was well-calibrated in all regions. Area under the receiver operating characteristic curve (AUC) and Brier scores ranged from 76.3% to 79.6% and 3.3 to 4.4. The model was superior to an age-sex benchmark model with differences in AUC and Brier scores ranging from 1.2% to 1.5% and −0.02 to −0.03. Average predicted risks in each Danish municipality ranged from 2.8% to 5.9%. Predicted risks for a 66-year old ranged from 2.6% to 25.3%. Personalized predicted risks across ages 30–85 were presented in an online calculator (https://hjerteforeningen.shinyapps.io/cvd-risk-manuscript/). CONCLUSION: A CVD risk prediction model based solely on nationwide administrative registry data provided accurate prediction of personal and population-level 5-year first CVD event risk in the Danish population. This may inform clinical and public health primary prevention efforts. Oxford University Press 2021-08-02 /pmc/articles/PMC9241501/ /pubmed/35919262 http://dx.doi.org/10.1093/ehjopen/oeab015 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Christensen, Daniel Mølager Phelps, Matthew Gerds, Thomas Malmborg, Morten Schjerning, Anne-Marie Strange, Jarl Emanuel El-Chouli, Mohamad Larsen, Lars Bruun Fosbøl, Emil Køber, Lars Torp-Pedersen, Christian Mehta, Suneela Jackson, Rod Gislason, Gunnar Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
title | Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
title_full | Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
title_fullStr | Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
title_full_unstemmed | Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
title_short | Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
title_sort | prediction of first cardiovascular disease event in 2.9 million individuals using danish administrative healthcare data: a nationwide, registry-based derivation and validation study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9241501/ https://www.ncbi.nlm.nih.gov/pubmed/35919262 http://dx.doi.org/10.1093/ehjopen/oeab015 |
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