title: Prognostic models for stable coronary artery disease based on electronic health record cohort of 102 023 patients.
abstract: OBJECTIVE
  The population with stable coronary artery disease (SCAD) is growing but validated models to guide their clinical management are lacking. We developed and validated prognostic models for all-cause mortality and non-fatal myocardial infarction (MI) or coronary death in SCAD.
  
  
  RESULTS
  Models were developed in a linked electronic health records cohort of 102 023 SCAD patients from the CALIBER programme, with mean follow-up of 4.4 (SD 2.8) years during which 20 817 deaths and 8856 coronary outcomes were observed. The Kaplan-Meier 5-year risk was 20.6% (95% CI, 20.3, 20.9) for mortality and 9.7% (95% CI, 9.4, 9.9) for non-fatal MI or coronary death. The predictors in the models were age, sex, CAD diagnosis, deprivation, smoking, hypertension, diabetes, lipids, heart failure, peripheral arterial disease, atrial fibrillation, stroke, chronic kidney disease, chronic pulmonary disease, liver disease, cancer, depression, anxiety, heart rate, creatinine, white cell count, and haemoglobin. The models had good calibration and discrimination in internal (external) validation with C-index 0.811 (0.735) for all-cause mortality and 0.778 (0.718) for non-fatal MI or coronary death. Using these models to identify patients at high risk (defined by guidelines as 3% annual mortality) and support a management decision associated with hazard ratio 0.8 could save an additional 13-16 life years or 15-18 coronary event-free years per 1000 patients screened, compared with models with just age, sex, and deprivation.
  
  
  CONCLUSIONS
  These validated prognostic models could be used in clinical practice to support risk stratification as recommended in clinical guidelines.
authors.affiliation: Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 7BH, UK.
authors.forename: Eleni
authors.initials: E
authors.lastname: Rapsomaniki
authors.forename: Anoop
authors.initials: A
authors.lastname: Shah
authors.forename: Pablo
authors.initials: P
authors.lastname: Perel
authors.forename: Spiros
authors.initials: S
authors.lastname: Denaxas
authors.forename: Julie
authors.initials: J
authors.lastname: George
authors.forename: Owen
authors.initials: O
authors.lastname: Nicholas
authors.forename: Ruzan
authors.initials: R
authors.lastname: Udumyan
authors.forename: Gene Solomon
authors.initials: GS
authors.lastname: Feder
authors.forename: Aroon D
authors.initials: AD
authors.lastname: Hingorani
authors.forename: Adam
authors.initials: A
authors.lastname: Timmis
authors.forename: Liam
authors.initials: L
authors.lastname: Smeeth
authors.forename: Harry
authors.initials: H
authors.lastname: Hemingway
mesh_terms: D000368:Aged; D003324:Coronary Artery Disease / Q000401:mortality*; D016757:Death, Sudden, Cardiac / Q000453:epidemiology; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D009203:Myocardial Infarction / Q000401:mortality; D011379:Prognosis; D018570:Risk Assessment
keywords: CALIBER; Electronic health records; Myocardial infarction; Prognosis; Stable angina; Stable coronary artery disease