title: Agreement among cardiovascular disease risk calculators.
abstract: BACKGROUND
  Use of cardiovascular disease risk calculators is often recommended by guidelines, but research on consistency in risk assessment among calculators is limited.
  
  
  RESULTS
  A search of PubMed and Google was performed. Five clinicians selected 25 calculators by independent review. Hypothetical patients were created with the use of 7 risk factors (age, sex, smoking, blood pressure, high-density lipoprotein, total cholesterol, and diabetes mellitus) dichotomized to high and low, generating 2(7) patients (128 total). These patients were assessed by each calculator by 2 clinicians. Risk estimates (and assigned risk categories) were compared among calculators. Selected calculators were from 8 countries, used 5- or 10-year predictions, and estimated either cardiovascular disease or coronary heart disease. With the use of 3 risk categories (low, medium, and high), the 25 calculators categorized each patient into a mean of 2.2 different categories, and 41% of unique patients were assigned across all 3 risk categories. Risk category agreement between pairs of calculators was 67%. This did not improve when analysis was limited to just the 10-year cardiovascular disease calculators. In nondiabetics, the highest calculated risk estimate from a calculator averaged 4.9 times higher (range, 1.9-13.3) than the lowest calculated risk estimate for the same patient. This did not change meaningfully for diabetics or when the analysis was limited to 10-year cardiovascular disease calculators.
  
  
  CONCLUSIONS
  The decision as to which calculator to use for risk estimation has an important impact on both risk categorization and absolute risk estimates. This has broad implications for guidelines recommending therapies based on specific calculators.
authors.affiliation: Evidence-Based Medicine, Department of Family Medicine, University of Alberta, Room 1706 College Plaza, 8215-112 St NW, Edmonton, Alberta T6G 2C8, Canada. michael.allan@ualberta.ca
authors.forename: G Michael
authors.initials: GM
authors.lastname: Allan
authors.forename: Faeze
authors.initials: F
authors.lastname: Nouri
authors.forename: Christina
authors.initials: C
authors.lastname: Korownyk
authors.forename: Michael R
authors.initials: MR
authors.lastname: Kolber
authors.forename: Ben
authors.initials: B
authors.lastname: Vandermeer
authors.forename: James
authors.initials: J
authors.lastname: McCormack
mesh_terms: D000367:Age Factors; D001794:Blood Pressure / Q000502:physiology; D002318:Cardiovascular Diseases / Q000175:diagnosis* / Q000453:epidemiology* / Q000378:metabolism; D002784:Cholesterol / Q000097:blood; D015331:Cohort Studies; D003920:Diabetes Mellitus / Q000175:diagnosis / Q000453:epidemiology / Q000378:metabolism; D006801:Humans; D012107:Research Design / Q000592:standards*; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology
chemical_list: D002784:Cholesterol
keywords: cardiovascular risk calculator; risk assessment