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QRISK: a new CVD risk score development & validation Julia Hippisley-Cox Calgary 23 Oct 2007

QRISK: a new CVD risk score development & validation Julia Hippisley-Cox Calgary 23 Oct 2007. Acknowledgments coauthors . Carol Coupland statistician Yana Vinogradova statistician John Robson GP Margaret May statistician Peter Brindle GP. Acknowledgments. EMIS practices

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QRISK: a new CVD risk score development & validation Julia Hippisley-Cox Calgary 23 Oct 2007

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  1. QRISK: a new CVD risk score development & validationJulia Hippisley-CoxCalgary23 Oct 2007

  2. Acknowledgmentscoauthors • Carol Coupland statistician • Yana Vinogradova statistician • John Robson GP • Margaret May statistician • Peter Brindle GP

  3. Acknowledgments • EMIS practices • David Stables & Andy Whitam (EMIS) • Dept Health

  4. Goals of presentation • Background to CVD risk prediction • Overview of development of QRISK (new score) • Key results & validation • Web calculator

  5. What is Framingham? • Framingham small town near Boston • Half the size of Mansfield • Recruited a cohort of 5,000 people in 1950 • Followed them for > 50 years • It has been hugely important

  6. Framingham Highlights • 1959 – described the ‘silent MI’ • 1960 – smoking, high BP & high chol bad • 1967 – exercise good • 1976 – menopause bad (for the heart!) • 1978 – psychological factors can be bad • 1988 – high HDL good • 1991 – risk prediction equation used ALL AROUND THE WORLD

  7. Why a new CVD risk score? • Small cohort 50 years ago from one American town • Almost entirely white • Developed during peak incidence CVD in US • Overpredicts CVD risk by up to 50% • Doesn’t include BMI, family history, blood pressure Rx, deprivation • But crucially it under estimates risk in patients from deprived areas

  8. Policy context • NICE publication of lipid modification guidelines July 2007 • Statins recommended if CVD risk > 20% • Need to population screening tool to identify high risk patients • Dept Health considering ‘life check’ • Potential utility of routinely collected data • Interested in self assessment • Concern about health inequalities

  9. Inverse equity hypothesis • This shows that when new interventions are introduced • Inequalities initially worsen (uptake quickest in the healthy and wealthy) • Eventually there is a ‘catch up’ but only when the wealthy reach a ‘ceiling’ • Need to be proactive to avoid new policies exacerbating health inequalities

  10. AIM for QRISK • New CVD risk score • Calibrated to UK population • Better discrimination • Use routinely collected GP data • Include additional known risk factors (eg FH, deprivation, BMI, BPRx)

  11. QRISK – general approach • QRISK is a new approach designed • to tailor management to the individual patient • to identify patients at high risk of disease • to identify those most likely to benefit or be harmed by treatment • Present risks and benefits back to patients at the point of care in an accessible way

  12. QRESEARCH database • the largest GP database worldwide • 525 practices, 10 million patients ever • Good historical data > 12 years • Numerous validation studies

  13. QRISK study cohort • Derivation cohort (2/3rds practices) & validation cohort (1/3rd) • All patients registered 1995-2007 • Men and women aged 35-74 • UK sample free from CVD & diabetes • Ethnically & socially diverse • 66,000 Cardiovascular disease events • 8.3 million person years

  14. Cardiovascular disease outcomes • Computer recorded clinical diagnosis of • Coronary heart disease • TIA or Stroke • Outcome similar to that in JBS2 • Validation against ONS certified cause of death 94% ascertainment

  15. QRISK risk factors • Traditional risk factors • Age, Sex, Smoking status • Systolic blood pressure • TSC/HDL ratio • (LVH – recorded prevalence too low) • New risk factors • Deprivation (townsend score output area) • Family history premature CVD 1st degree relative < 60 years • Body mass index • BP treatment

  16. Validation • Comparison against Framingham • Independent one third of the database • Various statistics • Predicted vs observed CVD events • Clinical effect in terms of reclassification of patients into high/low risk

  17. Validation statistics(note: higher scores are better)

  18. Degree of over prediction

  19. % of the UK population 35-74 years at high risk >20%

  20. Clinically important issue is degree of reclassification • If we use QRISK rather than Framingham • Overall one in 10 reclassified • QRISK identifies different group of patients who are at higher risk • Incorrect classification affects patients from deprived areas (ie more high risk patients missed)

  21. Strengths of QRISK • Better calibrated for UK than Framingham • Less likely than Framingham to over predict risk • Better at identifying patients likely to clinically benefit from treatment • Includes deprivation which makes it fairer • Can be implemented into GP computer systems • Can be periodically updated and refined

  22. QRISK: Web calculator • Designed for patients to use • Also needs integration into clinical system • Link http://www.qrisk.org • Username qrisk • Password beta test

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