General CVD risk prediction tools appear to be useful for cancer survivors
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CVD risk prediction tools developed for a primary care population in New Zealand were similarly useful risk predictors for adult cancer survivors, researchers reported.
“The management of cardiovascular disease among people who have not had a cardiovascular disease event is based on their estimated absolute risk of disease, which is measured by cardiovascular disease risk prediction equations. Multiple such equations are available, but most have been developed in general primary care populations,” Essa Tawfiq, PhD, a research fellow with the School of Population Health at the University of Auckland, New Zealand, and colleagues wrote in The Lancet. “The validity of these equations in survivors of cancer is unclear. Evidence to date has been limited by small numbers of patients or by a focus on a specific cancer type or cardiovascular disease outcome.”
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In a validation study, Tawfiq and colleagues analyzed data from 14,263 adults aged 30 to 74 years who had a primary diagnosis of invasive cancer who participated in PREDICT, a study used to develop the New Zealand CVD risk prediction equations. The mean age of patients was 61 years for men and 60 years for women, with a median follow-up of 5.8 years for men and 5.7 years for women. Participants received a cancer diagnosis at least 2 years before the date of the first CVD risk assessment.
The risk prediction equations are sex-specific and include age, ethnicity, socioeconomic deprivation index, family CVD history, smoking status, history of atrial fibrillation and diabetes, systolic BP, ratio of total cholesterol to HDL, and preventive pharmacotherapy. Researchers assessed calibration by comparing the mean predicted 5-year CVD risk, estimated using the risk prediction equations, with the observed risk across deciles of risk, for men and women, and according to the three clinical 5-year CVD risk groups in New Zealand guidelines (< 5%, 5% to < 15% and 15%).
Researchers found that the observed CVD risk was underpredicted by a maximum of 2.5% in male and 3.2% in female decile groups.
When patients were grouped according to clinical risk groups, observed CVD risk was underpredicted by less than 2% in the lower-risk groups and overpredicted by 2.2% for men and 3.3% for women in the highest-risk group.
The C statistics were 0.67 (standard error, 0.01) for men and 0.73 (standard error, 0.01) for women, according to the researchers.
“We found that cardiovascular disease risk prediction equations developed in a New Zealand general primary care population were reasonable clinical tools for use in survivors of cancer in New Zealand for whom the assessment of cardiovascular disease risk was considered clinically appropriate by their primary care clinician,” the researchers wrote. “Prediction could be improved by adding cancer-specific variables and considering competing risks. The equations can predict cardiovascular disease risk with reasonable variations from observed risk in survivors of cancer at primary care practices.”
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