Advances and Controversies in Cardiovascular Risk Prediction

Peter BrindleGeneral 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. 1967

• > 20 groups of regression equations between 1967 and 2008

• Modified Anderson et al 1991 used in UK

Framingham - Anderson

• Data collected 1968-75

• 5573 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

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

12,300 men and women, aged 45-64 and no evidence of cardiovascular disease at entry (1972-76)

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-Manual 0.69 p= 0.0005 Affluent 0.64p= 0.0017

for trendManual 0.52 Intermediate 0.56

Deprived 0.47

10-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

SCORESystematic Coronary Risk

Evaluation 2003

• 205,178 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?

SCORE ASSIGN

BP treatment No No

Family History No Yes

Deprivation No Yes

Ethnicity No No

Generalisability ? ?

Statistical validity Yes Yes

Face validity No 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?

SCORE ASSIGN QRISK1

BP treatment No No YesFamily History No Yes YesDeprivation No Yes YesEthnicity No No NoGeneralisability ? ? YesStatistical validity Yes Yes YesFace validity No 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

Model performance QRISK2 vs Modified Framingham

  QRISK2 Framingham

Females    

R squared 43.4% 38.9%

D statistic 1.793 1.632

Males    

R squared 38.4% 34.8%

D statistic 1.616 1.495

Age-standardised incidence of CVD by deprivation

0

2

4

6

8

10

12

females males

Q1 (affluent)Q2Q3Q4Q5 (deprived)

Adjusted Hazard Ratios for CVD

0

0.5

1

1.5

2

2.5

females (CVD) Males (CVD)

Haza

rd r

ati

o

WhiteIndianPakistaniBangladeshiOther AsianCaribbeanBlack AfricanChineseOther

QRISK2 – better than Framingham?

SCORE ASSIGN QRISK1 QRISK2

BP treatment No No Yes YesFamily History No Yes Yes YesDeprivation No Yes Yes YesEthnicity No No No YesReproducibility Yes Yes Yes YesGeneralisability ? ? Yes YesStatistical validity Yes Yes Yes YesFace validity No No Yes 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