title: A comparison of methods for determining HIV viral set point.
abstract: During a course of human immunodeficiency virus (HIV-1) infection, the viral load usually increases sharply to a peak following infection and then drops rapidly to a steady state, where it remains until progression to AIDS. This steady state is often referred to as the viral set point. It is believed that the HIV viral set point results from an equilibrium between the HIV virus and immune response and is an important indicator of AIDS disease progression. In this paper, we analyze a real data set of viral loads measured before antiretroviral therapy is initiated, and propose two-phase regression models to utilize all available data to estimate the viral set point. The advantages of the proposed methods are illustrated by comparing them with two empirical methods, and the reason behind the improvement is also studied. Our results illustrate that for our data set, the viral load data are highly correlated and it is cost effective to estimate the viral set point based on one or two measurements obtained between 5 and 12 months after HIV infection. The utility and limitations of this recommendation will be discussed.
authors.affiliation: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0205, U.S.A. ymei@isye.gatech.edu
authors.forename: Y
authors.initials: Y
authors.lastname: Mei
authors.forename: L
authors.initials: L
authors.lastname: Wang
authors.forename: S E
authors.initials: SE
authors.lastname: Holte
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000821:virology; D015331:Cohort Studies; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D018450:Disease Progression; D015658:HIV Infections / Q000821:virology*; D015497:HIV-1 / Q000254:growth & development; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D012044:Regression Analysis; D012107:Research Design; D018401:Sample Size; D019562:Viral Load