Cardiovascular disease is a leading cause of death and morbidity in patients with end- stage renal disease (ESRD), accounting for nearly half of the 20% annualized mortality and 30% of hospitalizations. Despite the extraordinary progress in establishing the benefits of cardioprotective medications in primary and secondary prevention of cardiovascular events in non-ESRD patients, virtually no data are available that describe the effects of these medications in the ESRD population because persons with ESRD have been systematically excluded from the large body of clinical trials in cardioprotection. The National Kidney Foundation defaults to the clinical guidelines of the American Heart Association for the general population. Our approach to determining the effectiveness of cardioprotective medications in ESRD entails combining two national data sources: the United States Renal Data System (USRDS) and Medicaid drug data. Through this database, we will be able to link monthly cardioprotective medication use with important cardiac outcomes over multiple years. These outcomes are all- cause mortality, cardiac-related mortality, and cardiac-related morbidity. From this data, we will quantify the primary and secondary prevention effectiveness of three major classes of cardioprotective medications: beta-blockers, renin-angiotensin system antagonists, and HMG- CoA reductase inhibitors. Our primary prevention cohort is expected to include over 40,000 individuals without ischemic heart disease upon dialysis initiation. Our two secondary prevention cohorts will include over 20,000 individuals from the primary prevention cohort who had a cardiac event or those with ischemic heart disease at baseline. Because of limitations with using this type of data, we must adjust the statistical models for non-random treatment assignment. We will employ two different advanced statistical techniques, propensity scores and instrumental variables, to minimize the influence of selection bias on our results. Medication exposure will be quantified over time through use of the medication possession ratio, a marker of continuity of use. Our statistical models will control for important covariates known to influence the use of the medications as well as outcomes.

Public Health Relevance

Cardiovascular disease (CVD) is the most common cause of death and morbidity in the ESRD population accounting for approximately 50% of all deaths in ESRD individuals and nearly 30% of hospital admissions. The absolute risk of adverse cardiovascular outcomes in ESRD patients is the highest of any cardiovascular population. This project will evaluate the effectiveness of cardioprotective medications in reducing cardiac deaths and hospitalizations in ESRD patients.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Study Section
Kidney, Nutrition, Obesity and Diabetes (KNOD)
Program Officer
Eggers, Paul Wayne
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University of Kansas
Public Health & Prev Medicine
Schools of Medicine
Kansas City
United States
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Phadnis, Milind A; Wetmore, James B; Shireman, Theresa I et al. (2017) An ensemble survival model for estimating relative residual longevity following stroke: Application to mortality data in the chronic dialysis population. Stat Methods Med Res 26:2667-2680
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