title: Modeling mortality risk in hemodialysis patients using laboratory values as time-dependent covariates.
abstract: Proportional hazards analyses assume that the magnitude of mortality risk for a predictor variable remains proportional over time. In a time-dependent model, the explanatory variable violates this assumption, and repeat observations are required to accommodate the change in risk that occurs over time. Using a retrospective cohort design, we tested the following laboratory values for a time-by-covariate interaction: hematocrit (HCT), serum albumin (ALB), and serum creatinine (CR). A random sample of 4,083 hemodialysis patients whose specimens were analyzed in a central laboratory over a 3-year period served as the study group. Using the baseline observation, we discovered significant probability values for the interaction terms TIME*CR (P = 0.013) and TIME*ALB (P < 0.01). The beta coefficient for TIME*HCT was not significant, indicating that the proportional hazard assumption was not violated by this covariate. Based on these results, we fitted a multivariate regression model containing two time-dependent covariates (CR and ALB) using a data structure that incorporated repeat observations of these laboratory values. Patients with high ALB levels experienced the lowest mortality risk. Similarly, serum CR levels were higher in long-term survivors. This analysis verifies the clinical importance of monitoring ALB and CR levels over time and the hazard of using a single laboratory observation to make long-term projections. Additionally, the predictive values of the time-dependent covariates ALB and CR affirm the significance of nutritional approaches directed toward maintaining visceral and somatic protein content throughout renal replacement therapy.
authors.affiliation: College of Nursing and the Department of Preventive Medicine and Environmental Health, The University of Iowa, Iowa City 52242, USA.
authors.forename: K
authors.initials: K
authors.lastname: Culp
authors.forename: M
authors.initials: M
authors.lastname: Flanigan
authors.forename: E G
authors.initials: EG
authors.lastname: Lowrie
authors.forename: N
authors.initials: N
authors.lastname: Lew
authors.forename: B
authors.initials: B
authors.lastname: Zimmerman
mesh_terms: D000328:Adult; D015331:Cohort Studies; D003404:Creatinine / Q000097:blood; D003922:Diabetes Mellitus, Type 1 / Q000453:epidemiology; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology; D005260:Female; D006400:Hematocrit; D006801:Humans; D007676:Kidney Failure, Chronic / Q000097:blood / Q000175:diagnosis / Q000401:mortality* / Q000628:therapy*; D008297:Male; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D006435:Renal Dialysis / Q000401:mortality*; D012189:Retrospective Studies; D012307:Risk Factors; D012709:Serum Albumin / Q000032:analysis; D013997:Time Factors
chemical_list: D012709:Serum Albumin; D003404:Creatinine