Literature DB >> 17116649

Estimating lifetime risk of developing high serum total cholesterol: adjustment for baseline prevalence and single-occasion measurements.

Michael J Pencina1, Ralph B D'Agostino, Alexa S Beiser, Mark R Cobain, Ramachandran S Vasan.   

Abstract

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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Year:  2006        PMID: 17116649     DOI: 10.1093/aje/kwk025

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  3 in total

1.  Lifetime Risks for Hypertension by Contemporary Guidelines in African American and White Men and Women.

Authors:  Vincent Chen; Hongyan Ning; Norrina Allen; Kiarri Kershaw; Sadiya Khan; Donald M Lloyd-Jones; John T Wilkins
Journal:  JAMA Cardiol       Date:  2019-05-01       Impact factor: 14.676

2.  A comparison of ad hoc methods to account for non-cancer AIDS and deaths as competing risks when estimating the effect of HAART on incident cancer AIDS among HIV-infected men.

Authors:  Meredith S Shiels; Stephen R Cole; Joan S Chmiel; Joseph Margolick; Jeremy Martinson; Zuo-Feng Zhang; Lisa P Jacobson
Journal:  J Clin Epidemiol       Date:  2009-10-31       Impact factor: 6.437

Review 3.  Unbalanced baseline in school-based interventions to prevent obesity: adjustment can lead to bias - a systematic review.

Authors:  Rosely Sichieri; Diana Barbosa Cunha
Journal:  Obes Facts       Date:  2014-06-28       Impact factor: 3.942

  3 in total

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