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SUMMARY:Most cardiovascular risk prediction equations need to be updated o
 r replaced - Professor Rod Jackson\, Professor of Epidemiology\, Universit
 y of Auckland
DTSTART:20170918T120000Z
DTEND:20170918T130000Z
UID:TALK82201@talks.cam.ac.uk
CONTACT:48007
DESCRIPTION:Background\nThe majority of cardiovascular disease (CVD) risk 
 prediction equations are derived from cohorts established last century tha
 t included participants at higher risk\, on less treatment and who were le
 ss socio-economically and ethnically diverse\, than patients the equations
  are now applied to. The validity of most of these equations is uncertain\
 , largely because the relevant cohorts required to evaluate them are rare.
  Approximately 90% of middle-aged New Zealanders have had quantitative CVD
  risk assessments using a Framingham Heart Study equation (FHSE)\, since r
 isk assessment was made a national primary healthcare priority in 2008. We
  piggybacked on this initiative to recruit a nationally representative pri
 mary care cohort to: i. assess the validity of the 2013 Pooled Studies equ
 ations (PCEs) that recently replaced FHSEs in the US and elsewhere\; and i
 i. develop new equations if justified.\n\nMethods\nThe PREDICT cohort stud
 y automatically recruits participants when general practitioners utilising
  PREDICT decision support software\, calculate patients’ 5-year CVD risk
  using a modified 1991 FHSE. Baseline CVD risk factors were prospectively 
 linked to ICD-coded CVD hospitalisations and deaths in national databases.
  To determine if new equations are justified\, firstly the calibration of 
 the 2013 US PCEs were assessed in the PREDICT cohort\, and secondly\, Cox 
 models including prognostic indices from the PCEs were updated by adding n
 ew variables available in PREDICT. Finally\, new equations including all v
 ariables were developed using Cox models and the performance of PCE and ne
 w equations compared.\n\nFindings\nApproximately 90% of eligible patients 
 were recruited and only 80 participants had incomplete risk factor data. T
 he 401\,752 participants aged 30-74 years\, recruited between 2002 and 201
 5\, experienced 15\,386 first major CVD events (9.8% were fatal and 55% me
 t the PCE definition of atherosclerotic CVD ) during 1\,685\,521 person-ye
 ars (mean 4•2 years) follow-up. The PCEs over-predicted 5-year CVD risk 
 by more than 50%\, which could not be explained by new treatment initiated
  after baseline. Additional variables representing Polynesian\, South Asia
 n and other Asian ethnicities and an area-based social deprivation variabl
 e identified substantial groups of patients with predicted CVD risk betwee
 n 30% lower and 60% higher than based on either the FHSE and PCE scores al
 one. New equations including additional predictors performed significantly
  better on all model assessment metrics.\n\nInterpretation\nWe demonstrate
  that a contemporary cohort representing typical patients that prediction 
 equations are applied to\, can be recruited using decision support integra
 ted with routine linked electronic patient records. We show that new US ri
 sk prediction equations substantially overestimate observed CVD risk and t
 his is not explained by new drug treatment. Recalibration would be insuffi
 cient to improve the performance of the PCEs and simple variables represen
 ting common ethnicities and socio-economic deprivation should be incorpora
 ted into current equations. New equations are provided that could be imple
 mented in the 15-20 high-income countries with relatively similar CVD even
 ts rates and healthcare systems to New Zealand.\n\n
LOCATION:Seminar Room\, Strangeways Research Laboratory
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