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B0616
Title: Multilevel joint modeling of hospitalization and survival in patients on dialysis Authors:  Esra Kurum - University of California, Riverside (United States) [presenting]
Danh Nguyen - University of California, Irvine (United States)
Damla Senturk - University of California Los Angeles (United States)
Abstract: More than 720,000 patients with end-stage renal disease in the U.S. require life-sustaining dialysis treatment that is predominantly administered at local dialysis facilities. In this population of typically older patients with a high morbidity burden, hospitalization is frequent at a rate of about twice per patient-year. Aside from frequent hospitalizations, which are a major source of death risk, overall mortality in dialysis patients is higher than in other comparable populations, including Medicare patients with cancer. Thus, understanding patient- and facility-level risk factors that jointly contribute to longitudinal hospitalizations and mortality is of interest. Towards this objective, we propose a novel methodology to jointly model hospitalization, a binary longitudinal outcome, and survival, based on multilevel data from the United States Renal Data System, with repeated observations over time nested in patients and patients nested in dialysis facilities. Motivated by the data structure, the proposed joint modeling approach includes multilevel random effects and multilevel covariates, at both the patient and facility levels. An approximate Expectation-Maximization (EM) algorithm is developed for estimation where fully exponential Laplace approximations are utilized to address computational challenges and standard error formulas for the estimated parameters are derived.