An epidemiologic model to project the impact of changes in glomerular filtration rate on quality of life and survival among persons with chronic kidney disease

Adrian R Levy,1,2 Robert M Perkins,3 Karissa M Johnston,2 Sean D Sullivan,4 Vipan C Sood,5 Wendy Agnese,5 Mark A Schnitzler61Department of Community Health and Epidemiology, Dalhousie University, Halifax, NS, Canada; 2Oxford Outcomes Ltd, Vancouver, BC, Canada; 3Center for Health Research and Division of Nephrology, Geisinger Health System, Danville, PA, USA; 4School of Pharmacy, University of Washington, Seattle, WA, USA; 5Mitsubishi Tanabe Pharma America, Jersey City, NJ, USA; 6Departments of Internal Medicine and Community Health, Saint Louis University, St Louis, MO, USAPurpose: Predicting the timing and number of end-stage renal disease (ESRD) cases from a population of individuals with pre-ESRD chronic kidney disease (CKD) has not previously been reported. The objective is to predict the timing and number of cases of ESRD occurring over the lifetime of a cohort of hypothetical CKD patients in the US based on a range of baseline estimated glomerular filtration rate (eGFR) values and varying rates of eGFR decline.Methods: A three-state Markov model – functioning kidney, ESRD, and death – with an annual cycle length is used to project changes in baseline eGFR on long-term health outcomes in a hypothetical cohort of CKD patients. Using published eGFR-specific risk equations and adjusting for predictive characteristics, the probability of ESRD (eGFR