Cardiovascular Disease Population Risk Tool
This trial is active, not recruiting.
|Sponsor||Ottawa Hospital Research Institute|
|Collaborator||Canadian Institutes of Health Research (CIHR)|
|Start date||September 2000|
|End date||December 2014|
|Trial size||130000 participants|
|Trial identifier||NCT02267447, CIHR FRN - 133550|
The purpose of this study is to develop, evaluate, and apply a predictive algorithm for assessing CVD risk in the community setting: the Cardiovascular Disease Population Risk Tool (CVDPoRT).
Eligible respondents to the combined 2001, 2003 and 2005 Canadian Community Health Surveys, conducted by Statistics Canada.
Eligible respondents to the 2007 and 2009 Canadian Community Health Surveys.
major cardiovascular disease event
time frame: up to 12 years
Male or female participants at least 20 years old.
- Respondents to the Canadian Community Health Surveys
- Not eligible for Ontario's universal health insurance program
- Prior history of heart disease or stroke
- Younger than age 20
|Official title||Risk of Cardiovascular Disease in Canada and Burden of Health Behaviours: Development of Population-based Risk Algorithms|
|Description||This observational study will use the Ontario sample of the Canadian Community Health Survey (2001, 2003, 2005; 77,251 respondents) to assess risk factors - focusing on health behaviours (physical activity, diet, smoking, and alcohol use). Incident CVD outcomes will be assessed through linkage to administrative healthcare databases (619,886 person-years of follow-up until 31 December 2011). Socio-demographic factors (age, sex, immigrant status, education) and mediating factors such as presence of diabetes and hypertension will be included as predictors. Risk prediction models will be developed using competing risks survival analysis. The analysis plan adheres to published recommendations for the development of valid risk prediction models to limit the risk of over-fitting and improve the quality of predictions. Key considerations are fully pre-specifying the predictor variables; appropriate handling of missing data; use of flexible functions for continuous predictors; and avoiding data-driven variable selection procedures that increase the risk of type I error. The 2007 and 2009 surveys (approximately 50,000 respondents) will be used for validation. Calibration will be assessed overall and in predefined subgroups of importance to clinicians and policymakers.|
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