Advances and Controversies in Cardiovascular Risk Prediction Peter Brindle General Practitioner R&D lead Bristol, N.Somerset and S.Glouc PCTs Promises, Pitfalls and Progress

Outline Promises –Why do CVD risk estimation? –Background – Framingham Pitfalls –How well to current methods perform? –Two studies Progress –Four new risk scores –Where to next?

PROMISES

Why do CVD risk estimation? To identify high risk individuals Prioritise treatment - for individuals - for policy Patient education

Background Guidelines recommend preventive treatment in high risk patients Population screening Lifelong treatment. Or not.

The Framingham Heart Study Data collection started in 1948 Bi-annual follow up First CVD risk equation: Truett et al > 20 groups of regression equations between 1967 and 2008 Modified Anderson et al 1991 used in UK

Framingham - Anderson Data collected men and women followed up for 12 years Six regression equations published in 1991

Risk factors used to calculate the Anderson Framingham risk score -age and sex -diastolic and systolic BP -total:HDL cholesterol ratio -diabetes (Y/N) -cigarette smoking (Y/N) -LVH (Y/N) Absolute CVD Risk over 10 years

Different versions and coloured charts New Zealand cardiovascular risk prediction charts

Sheffield Tables

Joint British Societies 1998

Joint British Societies(2) 2004

PITFALLS

Possible problems with Framingham Secular trends Decline in CHD since the 1970’s Geographical variation Accuracy depends on background risk of target population Uncertain generalisability

Getting it wrong People with little to gain may become patients, and the benefit to risk ratio of treatment becomes too small People with much to gain may not be offered preventive treatment Over-prediction means... Under-prediction means…

How well does Framingham perform? Single UK population One systematic review

 6643 men from 24 towns  aged years  no evidence of CVD at entry ( )  baseline risk factor assessment  10 year follow-up for fatal and non-fatal CHD Framingham in the British Regional Heart study

PREDICTED AND OBSERVED 10-YEAR CHD EVENT RATES IN MEN 10-year CHD risk (%) predicted HIGH RISK

PREDICTED AND OBSERVED 10-YEAR CHD EVENT RATES IN MEN 10-year CHD risk (%) predicted observed HIGH RISK

 12,300 men and women, aged and no evidence of cardiovascular disease at entry ( )  10-year follow up for cardiovascular disease mortality  Stratified by individual social class and area deprivation Framingham in the Renfrew/Paisley study

Social deprivation Social class (Pred/Obs) Deprivation (Pred/Obs) Non-Manual0.69 p= Affluent0.64 p= for trend Manual0.52Intermediate0.56 Deprived year predicted versus observed CVD death rates by area deprivation and social class The Framingham risk score does not reflect the increased risk of people from deprived backgrounds relative to affluent people

Predicted over observed ratios ordered by background risk of test population

Issues with Framingham BP treatment Family History Deprivation Ethnicity Generalisability Statistical validity Face validity Improvements are needed

PROGRESS

SCORE Systematic Coronary Risk Evaluation ,178 men and women from 12 European cohort studies Used by “European guidelines on cardiovascular disease prevention in clinical practice”

SCORE – better than Framingham? SCORE BP treatment No Family History No Deprivation No Ethnicity No Generalisability ? Statistical validity Yes Face validity No

ASSIGN - ASSessing cardiovascular risk, using SIGN guidelines Scottish Heart and Health Extended Cohort (SHHEC) 6540 men, 6757 women Classic risk factors plus –Deprivation –Family history Shifts treatment towards the socially deprived compared to Framingham

ASSIGN – better than Framingham? SCOREASSIGN BP treatment No Family History NoYes Deprivation NoYes Ethnicity No Generalisability ?? Statistical validity Yes Face validity No

QRISK1 and QRISK2 Electronic patient record Cohort analysis based on large validated GP database (QResearch) Contains individual patient level data 15 year study period 1993 to 2008 First diagnosis of CVD (including CVD death) QRISK1 –Deprivation –Family History –BMI –On BP treatment  NO Ethnicity

QRISK1 - better than Framingham? SCOREASSIGNQRISK1 BP treatment No Yes Family History NoYes Deprivation NoYes Ethnicity No Generalisability ??Yes Statistical validity Yes Face validity No Yes

QRISK2 Included ONS deaths linkage Included additional variables 2.3 million people (>16 million person yrs) Self-assigned ethnicity Derivation (1.5 million) and test cohorts

Self Assigned Ethnicity Initial analysis NHS 16+1 categories Categories used in derivation cohort –White1.5 million –Indian 7328 –Pakistani 4068 –Bangladeshi 2482 –Other Asian 3224 –Black Caribbean 7037 –Black African 6971 –Chinese 1987 –Other7086

Model performance QRISK2 vs Modified Framingham QRISK2Framingham Females R squared43.4%38.9% D statistic Males R squared38.4%34.8% D statistic

Model performance QRISK2 vs Modified Framingham QRISK2Framingham Females R squared43.4%38.9% D statistic ROC statistic Males R squared38.4%34.8% D statistic ROC statistic

Age-standardised incidence of CVD by deprivation

Age-standardised incidence of CVD by Ethnicity per 1000 pyrs %

Adjusted Hazard Ratios for CVD

Proportion women CVD risk >20% QRISK2 vs Framingham

Reclassification 40% of those at high risk on Framingham will be reclassified by QRISK2 Patients high on QRISK2 & low on Framingham have higher risks Patients at low risk on QRISK2 & high risk on Framingham have lower risks Reclassification affects women, ethnic groups, those from deprived areas Choice of score effects health inequalities

QRISK2 – better than Framingham? SCOREASSIGNQRISK1QRISK2 BP treatment No Yes Family History NoYes Deprivation NoYes Ethnicity No Yes Reproducibility Yes Generalisability ??Yes Statistical validity Yes Face validity No Yes

Where to next? Generalisability? Linkage –Census –Hospital data Improved ethnicity recording

Summary Promises –Why do CVD risk estimation? –Background – Framingham Pitfalls –How well to current methods perform? –Two studies Progress –Four new risk scores –Where to next? – linkage and statistics

CONCLUSION The idea of risk assessment is well established Existing methods flawed – but better than nothing Electronic patient record + improving data sources = exciting prospects

Acknowledgements British Regional Heart study team Renfrew/Paisley study team Shah Ebrahim Tom Fahey Andy Beswick Julia Hippisley-Cox John Robson Carol Coupland Yana Vinogradova Aziz Sheikh Rubin Minhas

CONCLUSION The idea of risk assessment is well established Existing methods flawed – but better than nothing Electronic patient record + improving data sources = exciting prospects

95% Confidence intervals

Changing hazard ratios with age for CVD

Patient characteristics