Recent research has suggested that BP variability may be an important risk factor for CVD (over and above mean), in particular variability in visit-to-visit BP measurements. However, although the additional prognostic value of BP variability has been demonstrated through survival analysis of long-term cohort and trial data, the utility of this factor in a risk prediction model has not been assessed. This study aims to develop two risk scores to predict future risk of CVD in individuals, one including traditional risk factors alone and a second additionally including BP variability as a risk factor. Both risk scores will be developed using data from adults without prior history of CVD, with linkage to mortality and hospital episodes data (to more accurately ascertain events) and deprivation data.
The risk scores will be developed in a derivation subsample using parametric survival models and fractional polynomials to model the relationship between traditional CVD risk factors and CVD outcomes. The accuracy of the two risk scores will be compared to each other in terms of discrimination, calibration and net reclassification index in a validation subsample.
Cardiovascular events; - Myocardial infarction - Coronary and ischaemic heart disease - Angina- Cerebrovascular and haemorrhagic stroke events- Cause-specific mortality
Richard Stevens - Chief Investigator - University of Oxford
Richard McManus - Collaborator - University of Oxford
Sarah Lay-Flurrie - Collaborator - University of Oxford