A Gaussian Process Model for Estimating Within-Subject Variation in Indices of Protein-Energy Malnutrition Among ESRD Patients

• Activity Number: 279
• Type: Invited
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: WNAR
• Author(s): Daniel L. Gillen*+ and Tracy Holsclaw and Babak Shahbaba
• Companies: University of California, Irvine and University of California, Irvine and UC Irvine
• Keywords: Gaussian Process ; Longitudinal ; Summary Measure ; Hemodialysis ; Survival

Abstract

Serum albumin is a leading index of protein-energy malnutrition (PEM) that has been associated with mortality among hemodialysis patients. Studies have found that albumin levels at the start of dialysis and the slope of albumin over time are independent risk factors for mortality. It is also natural to hypothesize that high within-subject variability in albumin measured over time may also be indicative of increased mortality. That is, high instability around a patient's first-order trend is likely an indication of nutritional instability and hence may be a risk factor for morbidity and mortality. We develop a Gaussian process model for estimating a summary measure of within-subject variability in serum albumin measured over time. The proposed model includes a parameter to allow for subject-to-subject variability and places a Dirichlet process prior on this parameter in order to cluster subjects with similar longitudinal patterns. Simulation studies that assess the proposed model are presented and an illustrative example is provided where the induced summary measure of within-subject variability is associated with mortality using patients from the United States Renal Data System.