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Development and validation of a cardiovascular disease risk-prediction model using population health surveys: the Cardiovascular Disease Population Risk Tool (CVDPoRT)

Canadian Medical Association journal (CMAJ), 2018-07, Vol.190 (29), p.E871-E882 [Peer Reviewed Journal]

Joule Inc. or its licensors ;2018 Joule Inc. or its licensors. ;COPYRIGHT 2018 Joule Inc. ;Copyright Joule Inc Jul 23, 2018 ;2018 Joule Inc. or its licensors 2018 ;ISSN: 0820-3946 ;EISSN: 1488-2329 ;DOI: 10.1503/cmaj.170914 ;PMID: 30037888

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Title:
Development and validation of a cardiovascular disease risk-prediction model using population health surveys: the Cardiovascular Disease Population Risk Tool (CVDPoRT)
Author: Manuel, Douglas G., MD ; Tuna, Meltem, PhD ; Bennett, Carol, MSc ; Hennessy, Deirdre, PhD ; Sanmartin, Claudia, PhD ; Rosella, Laura, PhD ; Tu, Jack V., MD ; Perez, Richard, MSc ; Fisher, Stacey, MSc ; Taljaard, Monica, PhD
Subjects: Algorithms ; Analysis ; Cardiovascular disease ; Cardiovascular diseases ; Chronic illnesses ; Clinical trials ; Consortia ; Development and progression ; Diabetes ; Diagnosis ; Disease prevention ; Epidemiology ; Health risk assessment ; Health surveys ; Hospitals ; Internal Medicine ; Outcome and process assessment (Health Care) ; Outcome and process assessment (Medical care) ; Polls & surveys ; Population ; Risk factors ; Sensitivity analysis ; Socioeconomic factors ; Statistical analysis ; Systematic review ; Vital statistics ; Womens health
Is Part Of: Canadian Medical Association journal (CMAJ), 2018-07, Vol.190 (29), p.E871-E882
Description: ABSTRACT BACKGROUND Routinely collected data from large population health surveys linked to chronic disease outcomes create an opportunity to develop more complex risk-prediction algorithms. We developed a predictive algorithm to estimate 5-year risk of incident cardiovascular disease in the community setting. METHODS We derived the Cardiovascular Disease Population Risk Tool (CVDPoRT) using prospectively collected data from Ontario respondents of the Canadian Community Health Surveys, representing 98% of the Ontario population (survey years 2001 to 2007; follow-up from 2001 to 2012) linked to hospital admission and vital statistics databases. Predictors included body mass index, hypertension, diabetes, and multiple behavioural, demographic and general health risk factors. The primary outcome was the first major cardiovascular event resulting in hospital admission or death. Death from a noncardiovascular cause was considered a competing risk. RESULTS We included 104 219 respondents aged 20 to 105 years. There were 3709 cardiovascular events and 818 478 person-years follow-up in the combined derivation and validation cohorts (5-year cumulative incidence function, men: 0.026, 95% confidence interval [CI] 0.025–0.028; women: 0.018, 95% 0.017–0.019). The final CVDPoRT algorithm contained 12 variables, was discriminating (men: C statistic 0.82, 95% CI 0.81–0.83; women: 0.86, 95% CI 0.85–0.87) and was well-calibrated in the overall population (5-year observed cumulative incidence function v. predicted risk, men: 0.28%; women: 0.38%) and in nearly all predefined policy-relevant subgroups (206 of 208 groups). INTERPRETATION The CVDPoRT algorithm can accurately discriminate cardiovascular disease risk for a wide range of health profiles without the aid of clinical measures. Such algorithms hold potential to support precision medicine for individual or population uses. Study registration: ClinicalTrials.gov, no. NCT02267447
Publisher: Canada: Joule Inc
Language: English
Identifier: ISSN: 0820-3946
EISSN: 1488-2329
DOI: 10.1503/cmaj.170914
PMID: 30037888
Source: ProQuest One Psychology
PubMed Central (Open access)
DOAJ Directory of Open Access Journals
GFMER Free Medical Journals
Alma/SFX Local Collection
ProQuest Central

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Development and validation of a cardiovascular disease risk-prediction model using population health surveys: the Cardiovascular Disease Population Risk Tool (CVDPoRT)

Joule Inc. or its licensors ;2018 Joule Inc. or its licensors. ;COPYRIGHT 2018 Joule Inc. ;Copyright Joule Inc Jul 23, 2018 ;2018 Joule Inc. or its licensors 2018 ;ISSN: 0820-3946 ;EISSN: 1488-2329 ;DOI: 10.1503/cmaj.170914 ;PMID: 30037888

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