Cargando…

Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database

Objective To develop, validate, and evaluate a new QRISK model to estimate lifetime risk of cardiovascular disease. Design Prospective cohort study with routinely collected data from general practice. Cox proportional hazards models in the derivation cohort to derive risk equations accounting for co...

Descripción completa

Detalles Bibliográficos
Autores principales: Hippisley-Cox, Julia, Coupland, Carol, Robson, John, Brindle, Peter
Formato: Texto
Lenguaje:English
Publicado: BMJ Publishing Group Ltd. 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999889/
https://www.ncbi.nlm.nih.gov/pubmed/21148212
http://dx.doi.org/10.1136/bmj.c6624
_version_ 1782193486893678592
author Hippisley-Cox, Julia
Coupland, Carol
Robson, John
Brindle, Peter
author_facet Hippisley-Cox, Julia
Coupland, Carol
Robson, John
Brindle, Peter
author_sort Hippisley-Cox, Julia
collection PubMed
description Objective To develop, validate, and evaluate a new QRISK model to estimate lifetime risk of cardiovascular disease. Design Prospective cohort study with routinely collected data from general practice. Cox proportional hazards models in the derivation cohort to derive risk equations accounting for competing risks. Measures of calibration and discrimination in the validation cohort. Setting 563 general practices in England and Wales contributing to the QResearch database. Subjects Patients aged 30–84 years who were free of cardiovascular disease and not taking statins between 1 January 1994 and 30 April 2010: 2 343 759 in the derivation dataset, and 1 267 159 in the validation dataset. Main outcomes measures Individualised estimate of lifetime risk of cardiovascular disease accounting for smoking status, ethnic group, systolic blood pressure, ratio of total cholesterol:high density lipoprotein cholesterol, body mass index, family history of coronary heart disease in first degree relative aged <60 years, Townsend deprivation score, treated hypertension, rheumatoid arthritis, chronic renal disease, type 2 diabetes, and atrial fibrillation. Age-sex centile values for lifetime cardiovascular risk compared with 10 year risk estimated using QRISK2 (2010). Results Across all the 1 267 159 patients in the validation dataset, the 50th, 75th, 90th, and 95th centile values for lifetime risk were 31%, 39%, 50%, and 57% respectively. Of the 10% of patients in the validation cohort classified at highest risk with either the lifetime risk model or the 10 year risk model, only 18 385(14.5%) were at high risk on both measures. Patients identified as high risk with the lifetime risk approach were more likely to be younger, male, from ethnic minority groups, and have a positive family history of premature coronary heart disease than those identified with the 10 year QRISK2 score. The lifetime risk calculator is available at www.qrisk.org/lifetime/. Conclusions Compared with using a 10 year QRISK2 score, a lifetime risk score will tend to identify patients for intervention at a younger age. Although lifestyle interventions at an earlier age could be advantageous, there would be small gains under the age of 65, and medical interventions carry risks as soon as they are initiated. Research is needed to examine closely the cost effectiveness and acceptability of such an approach.
format Text
id pubmed-2999889
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher BMJ Publishing Group Ltd.
record_format MEDLINE/PubMed
spelling pubmed-29998892010-12-16 Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database Hippisley-Cox, Julia Coupland, Carol Robson, John Brindle, Peter BMJ Research Objective To develop, validate, and evaluate a new QRISK model to estimate lifetime risk of cardiovascular disease. Design Prospective cohort study with routinely collected data from general practice. Cox proportional hazards models in the derivation cohort to derive risk equations accounting for competing risks. Measures of calibration and discrimination in the validation cohort. Setting 563 general practices in England and Wales contributing to the QResearch database. Subjects Patients aged 30–84 years who were free of cardiovascular disease and not taking statins between 1 January 1994 and 30 April 2010: 2 343 759 in the derivation dataset, and 1 267 159 in the validation dataset. Main outcomes measures Individualised estimate of lifetime risk of cardiovascular disease accounting for smoking status, ethnic group, systolic blood pressure, ratio of total cholesterol:high density lipoprotein cholesterol, body mass index, family history of coronary heart disease in first degree relative aged <60 years, Townsend deprivation score, treated hypertension, rheumatoid arthritis, chronic renal disease, type 2 diabetes, and atrial fibrillation. Age-sex centile values for lifetime cardiovascular risk compared with 10 year risk estimated using QRISK2 (2010). Results Across all the 1 267 159 patients in the validation dataset, the 50th, 75th, 90th, and 95th centile values for lifetime risk were 31%, 39%, 50%, and 57% respectively. Of the 10% of patients in the validation cohort classified at highest risk with either the lifetime risk model or the 10 year risk model, only 18 385(14.5%) were at high risk on both measures. Patients identified as high risk with the lifetime risk approach were more likely to be younger, male, from ethnic minority groups, and have a positive family history of premature coronary heart disease than those identified with the 10 year QRISK2 score. The lifetime risk calculator is available at www.qrisk.org/lifetime/. Conclusions Compared with using a 10 year QRISK2 score, a lifetime risk score will tend to identify patients for intervention at a younger age. Although lifestyle interventions at an earlier age could be advantageous, there would be small gains under the age of 65, and medical interventions carry risks as soon as they are initiated. Research is needed to examine closely the cost effectiveness and acceptability of such an approach. BMJ Publishing Group Ltd. 2010-12-09 /pmc/articles/PMC2999889/ /pubmed/21148212 http://dx.doi.org/10.1136/bmj.c6624 Text en © Hippisley-Cox et al 2010 This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.
spellingShingle Research
Hippisley-Cox, Julia
Coupland, Carol
Robson, John
Brindle, Peter
Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
title Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
title_full Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
title_fullStr Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
title_full_unstemmed Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
title_short Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database
title_sort derivation, validation, and evaluation of a new qrisk model to estimate lifetime risk of cardiovascular disease: cohort study using qresearch database
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2999889/
https://www.ncbi.nlm.nih.gov/pubmed/21148212
http://dx.doi.org/10.1136/bmj.c6624
work_keys_str_mv AT hippisleycoxjulia derivationvalidationandevaluationofanewqriskmodeltoestimatelifetimeriskofcardiovasculardiseasecohortstudyusingqresearchdatabase
AT couplandcarol derivationvalidationandevaluationofanewqriskmodeltoestimatelifetimeriskofcardiovasculardiseasecohortstudyusingqresearchdatabase
AT robsonjohn derivationvalidationandevaluationofanewqriskmodeltoestimatelifetimeriskofcardiovasculardiseasecohortstudyusingqresearchdatabase
AT brindlepeter derivationvalidationandevaluationofanewqriskmodeltoestimatelifetimeriskofcardiovasculardiseasecohortstudyusingqresearchdatabase