Key result
Novel lifetime risk model improves long-term prediction of developing high total cholesterol.
The lifetime risk statistic is a powerful tool in epidemiology. It has been successfully applied to estimate and highlight the risks of numerous diseases, including breast cancer, Alzheimer's disease, stroke, and coronary heart disease and some of its risk factors. Application of this method to health-related conditions that may have an onset early in young adulthood or to measurements that can fluctuate over time introduces problems of under- or overestimation of risk. To correctly quantify the long-term risk of developing high serum total cholesterol (> or =240 mg/dl or use of lipid-lowering medication), the authors propose a key modification of the lifetime risk statistic: adjustment for baseline prevalence. It accounts for the fact that many people already have the condition at a young age (an age often chosen as baseline). The authors derive point estimators and confidence intervals and supply a SAS macro (SAS Institute, Inc., Cary, North Carolina). For assessment of the risk inflation due to single-occasion measurement, the authors suggest two diagnostic tools, one requiring the condition to be present on two consecutive occasions and the other taking into account intrasubject variability. As an illustration, the authors calculate risk estimates for US Caucasians based on hypercholesterolemia incidence (1971-early 2001) from the Framingham Heart Study and prevalence data from the 1999-2000 National Health and Nutrition Examination Survey.
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Pencina et al. (2006) studied High serum total cholesterol. Modified lifetime risk statistic adjusting for baseline prevalence was evaluated on Long-term risk of developing high serum total cholesterol (≥240 mg/dl or use of lipid-lowering medication). A modified lifetime risk statistic adjusting for baseline prevalence was developed to correctly quantify the long-term risk of developing high serum total cholesterol (≥240 mg/dl or medication use).
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