Lancet: Blood analysis may be unnecessary for predicting CV disease
Simple measures that can be obtained in a doctor's office are just as effective at predicting the risk of developing cardiovascular disease (CVD) as the results of blood analyses, according to the National Health and Nutrition Examination Survey (NHANES) study published in the March 15 issue of The Lancet.
Thomas A. Gaziano, MD, division of cardiovascular medicine at Brigham & Women’s Hospital in Boston, reanalyzed data from an older study in which 14,407 U.S. adults between the age of 25 and 74 received comprehensive health evaluations between 1971 and 1975. Among the individuals, more than 6,000 were followed up over the next couple of decades to look for signs of CVD or cancer.
The investigators said that the NHANES I follow-up study population of 6,186 patients, included participants with complete information on these surveys who did not report a history of CVD (MI, heart failure, stroke, angina) or cancer, yielding an analysis dataset.
They compared how well either method could predict first-time fatal and non-fatal cardiovascular disease events in this cohort.
For the laboratory-based model, which required blood testing, Gaziano and colleagues used standard risk factors to assess risk of CVD: age, systolic blood pressure, smoking status, total cholesterol, reported diabetes status and current treatment for hypertension. For the non-laboratory-based model, they substituted body-mass index for cholesterol.
In the cohort of 6,186, there were 1,529 first-time CV events and 578 (38 percent) deaths due to CVD over 21 years, according to the researchers.
In women, the laboratory-based model was useful for predicting events, with a c statistic of 0.829, compared to the c statistic of the non-laboratory-based model, which was 0.831, the researchers found. In men, the investigators found that the results were similar (0.784 for the laboratory-based model and 0.783 for the non-laboratory-based model).
The results were similar between the laboratory-based and non-laboratory-based models in both men and women when restricted to fatal events only, according to the researchers.
Overall, the investigators said they were able to predict who would have a CV event just as accurately using BMI in combination with the other risk factors as they were using total cholesterol in combination with these same risk factors.
The researchers said that laboratory blood analysis may not be necessary to accurately predict the risk of CVD, a finding that could be helpful in the developing world where limited healthcare resources must be stretched over a large population.
Thomas A. Gaziano, MD, division of cardiovascular medicine at Brigham & Women’s Hospital in Boston, reanalyzed data from an older study in which 14,407 U.S. adults between the age of 25 and 74 received comprehensive health evaluations between 1971 and 1975. Among the individuals, more than 6,000 were followed up over the next couple of decades to look for signs of CVD or cancer.
The investigators said that the NHANES I follow-up study population of 6,186 patients, included participants with complete information on these surveys who did not report a history of CVD (MI, heart failure, stroke, angina) or cancer, yielding an analysis dataset.
They compared how well either method could predict first-time fatal and non-fatal cardiovascular disease events in this cohort.
For the laboratory-based model, which required blood testing, Gaziano and colleagues used standard risk factors to assess risk of CVD: age, systolic blood pressure, smoking status, total cholesterol, reported diabetes status and current treatment for hypertension. For the non-laboratory-based model, they substituted body-mass index for cholesterol.
In the cohort of 6,186, there were 1,529 first-time CV events and 578 (38 percent) deaths due to CVD over 21 years, according to the researchers.
In women, the laboratory-based model was useful for predicting events, with a c statistic of 0.829, compared to the c statistic of the non-laboratory-based model, which was 0.831, the researchers found. In men, the investigators found that the results were similar (0.784 for the laboratory-based model and 0.783 for the non-laboratory-based model).
The results were similar between the laboratory-based and non-laboratory-based models in both men and women when restricted to fatal events only, according to the researchers.
Overall, the investigators said they were able to predict who would have a CV event just as accurately using BMI in combination with the other risk factors as they were using total cholesterol in combination with these same risk factors.
The researchers said that laboratory blood analysis may not be necessary to accurately predict the risk of CVD, a finding that could be helpful in the developing world where limited healthcare resources must be stretched over a large population.