Whether to Retest the Lipids of HIV-Infected Patients: How Much Does Fasting Bias Matter?

Xiting Yang (), Joseph B. Kadane (), Heidi M. Crane () and Mari M. Kitahata ()
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Xiting Yang: Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Joseph B. Kadane: Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Heidi M. Crane: Department of Medicine, University of Washington, Seattle, Washington 98104
Mari M. Kitahata: Department of Medicine, University of Washington, Seattle, Washington 98104

Decision Analysis, 2011, vol. 8, issue 2, 145-157

Abstract: This paper aids in the diagnosis and treatment of lipid abnormalities by enhancing understanding of lipid values among HIV-infected patients. An elicited loss function highlights the importance of true low-density lipoprotein (LDL) cholesterol. In clinical settings, total cholesterol, high-density lipoprotein cholesterol, and triglycerides are often measured. Interpreting the resulting values can be problematic because of uncertainty due to the unknown period of fasting before the patient's blood was drawn. This results in uncertainty in the LDL cholesterol values, which are often calculated from other lipid values rather than measured directly. To model true LDL cholesterol, a four-level Bayesian hierarchical model is analyzed using Markov chain Monte Carlo techniques and elicited prior distributions. In turn, this yields expected-loss-minimizing treatment decisions for individual patients.

Keywords: Bayesian; fasting; hierarchical; HIV; lipid measurement; treatment decision (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:8:y:2011:i:2:p:145-157

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