BACKGROUND: Use of cardiovascular disease risk calculators is often recommended by guidelines, but research on consistency in risk assessment among calculators is limited. METHOD AND 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.
BACKGROUND: Use of cardiovascular disease risk calculators is often recommended by guidelines, but research on consistency in risk assessment among calculators is limited. METHOD AND 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: G Michael Allan; Adrienne J Lindblad; Ann Comeau; John Coppola; Brianne Hudson; Marco Mannarino; Cindy McMinis; Raj Padwal; Christine Schelstraete; Kelly Zarnke; Scott Garrison; Candra Cotton; Christina Korownyk; James McCormack; Sharon Nickel; Michael R Kolber Journal: Can Fam Physician Date: 2015-10 Impact factor: 3.275
Authors: Benjamin S Wessler; Lana Lai Yh; Whitney Kramer; Michael Cangelosi; Gowri Raman; Jennifer S Lutz; David M Kent Journal: Circ Cardiovasc Qual Outcomes Date: 2015-07-07