Predicting the 30-year risk of cardiovascular disease: the framingham heart study.

BACKGROUND: Present cardiovascular disease (CVD) risk prediction algorithms were developed for a < or =10-year follow up period. Clustering of risk factors at younger ages and increasing life expectancy suggest the need for longer-term risk prediction tools. METHODS AND RESULTS: We prospectively followed 4506 participants (2333 women) of the Framingham Offspring cohort aged 20 to 59 years and free of CVD and cancer at baseline examination in 1971-1974 for the development of "hard" CVD events (coronary death, myocardial infarction, stroke). We used a modified Cox model that allows adjustment for competing risk of noncardiovascular death to construct a prediction algorithm for 30-year risk of hard CVD. Cross-validated survival C statistic and calibration chi2 were used to assess model performance. The 30-year hard CVD event rates adjusted for the competing risk of death were 7.6% for women and 18.3% for men. Standard risk factors (male sex, systolic blood pressure, antihypertensive treatment, total and high-density lipoprotein cholesterol, smoking, and diabetes mellitus), measured at baseline, were significantly related to the incidence of hard CVD and remained significant when updated regularly on follow-up. Body mass index was associated positively with 30-year risk of hard CVD only in models that did not update risk factors. Model performance was excellent as indicated by cross-validated discrimination C=0.803 and calibration chi2=4.25 (P=0.894). In contrast, 30-year risk predictions based on different applications of 10-year functions proved inadequate. CONCLUSIONS: Standard risk factors remain strong predictors of hard CVD over extended follow-up. Thirty-year risk prediction functions offer additional risk burden information that complements that of 10-year functions.

Duke Scholars

Author Michael J Pencina Biostatistics & Bioinformatics, Division of Biostatistics