Cardiovascular event risk dynamics over time in older patients on dialysis: a generalized multiple-index varying coefficient model approach.
Among patients on dialysis, cardiovascular disease and infection are leading causes of hospitalization and death. Although recent studies have found that the risk of cardiovascular events is higher after an infection-related hospitalization, studies have not fully elucidated how the risk of cardiovascular events changes over time for patients on dialysis. In this work, we characterize the dynamics of cardiovascular event risk trajectories for patients on dialysis while conditioning on survival status via multiple time indices: (1) time since the start of dialysis, (2) time since the pivotal initial infection-related hospitalization, and (3) the patient's age at the start of dialysis. This is achieved by using a new class of generalized multiple-index varying coefficient (GM-IVC) models. The proposed GM-IVC models utilize a multiplicative structure and one-dimensional varying coefficient functions along each time and age index to capture the cardiovascular risk dynamics before and after the initial infection-related hospitalization among the dynamic cohort of survivors. We develop a two-step estimation procedure for the GM-IVC models based on local maximum likelihood. We report new insights on the dynamics of cardiovascular events risk using the United States Renal Data System database, which collects data on nearly all patients with end-stage renal disease in the United States. Finally, simulation studies assess the performance of the proposed estimation procedures.
Department of Biostatistics, University of California, Los Angeles, California 90095, U.S.A.
Jason P
JP
Estes
Department of Medicine, University of California, Irvine, California 92868, U.S.A.|Institute for Clinical and Translational Science, University of California, Irvine, California 92687, U.S.A.
Danh V
DV
Nguyen
Division of Nephrology, Department of Medicine, University of California, Sacramento, California 95817, U.S.A.
Lorien S
LS
Dalrymple
Graduate Group in Epidemiology, University of California, Davis, California 95616, U.S.A.
Yi
Y
Mu
Department of Biostatistics, University of California, Los Angeles, California 90095, U.S.A.
Damla
D
Şentürk
D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D002318:Cardiovascular Diseases / Q000401:mortality*; D015984:Causality; D015331:Cohort Studies; D015897:Comorbidity; D003627:Data Interpretation, Statistical; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality* / Q000517:prevention & control*; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015995:Prevalence; D011379:Prognosis; D006435:Renal Dialysis / Q000706:statistics & numerical data*; D012307:Risk Factors; D016019:Survival Analysis; D015996:Survival Rate; D014481:United States / Q000453:epidemiology
Cardiovascular outcomes; End stage renal disease; Generalized linear models; Infection; Time‐varying effects; United States Renal Data System