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Prediction of mortality from coronary heart disease among diverse populations: is there a common predictive function?
Pubmed ID: 12181209
Pubmed Central ID: PMC1767330
Journal: Heart (British Cardiac Society)
Publication Date: Sept. 1, 2002
MeSH Terms: Humans, Male, Adult, Female, Aged, Risk Factors, United States, Cohort Studies, Middle Aged, Coronary Disease, ROC Curve, Risk Assessment, Proportional Hazards Models, Multivariate Analysis, Prospective Studies, Cause of Death, Survival Rate, Asia, Europe, West Indies
Grants: HL 61769
Cite As: Diverse Populations Collaborative Group. Prediction of mortality from coronary heart disease among diverse populations: is there a common predictive function? Heart 2002 Sep;88(3):222-8.
Studies:
- Framingham Heart Study (FHS) Offspring (OS) and OMNI 1 Cohorts
- Framingham Heart Study-Cohort (FHS-Cohort)
- Honolulu Heart Program (HHP)
- Hypertension Detection and Follow-Up Program (HDFP)
- Lipid Research Clinics (LRC) Prevalence Study (PS)
- Multiple Risk Factor Intervention Trial for the Prevention of Coronary Heart Disease (MRFIT)
- Puerto Rico Heart Health Program (PRHHP)
Abstract
OBJECTIVES: To examine the generalisability of multivariate risk functions from diverse populations in three contexts: ordering risk, magnitude of relative risks, and estimation of absolute risk. DESIGN: Meta-analysis of prospective cohort studies. PATIENTS: Participants from various epidemiological studies. MAIN OUTCOME MEASURE: Death from coronary heart disease (CHD). RESULTS: The analysis included 105 420 men and 56 535 women 35-74 years of age and free of CHD at baseline from 16 observational studies with a total of 27 analytical groups. The area under the receiver operating characteristic curve (AUC) was used to judge the ability of the multivariate risk function to order risk correctly. AUCs ranged from 0.60 to 0.80. The AUCs differed significantly between the studies (p < 0.01) but were very similar for different risk functions applied to the same population, indicating similar ability to rank risk for different models. The magnitudes of the relative risks associated with major risk factors (age, systolic blood pressure, serum total cholesterol, smoking, and diabetes) varied significantly across studies (p < 0.05 for homogeneity). The prediction of absolute risk was not very accurate in most of the cases when a model derived from one study was applied to a different study. CONCLUSIONS: When considered qualitatively, the major risk factors are associated with CHD mortality in a diverse set of populations. However, when considered quantitatively, there was significant heterogeneity in all three aspects: ordering risk, magnitude of relative risks, and estimation of absolute risk.