A Predictive Model of Health State Utilities for HIV Patients in the Modern Era of Highly Active Antiretroviral Therapy

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Existing estimates of human immunodeficiency virus (HIV)-related health state utilities are inadequate for comparing alternative treatments on the basis of regimen-specific attributes such as dosing requirements or tolerability. The objective of this study was to examine the marginal impact of dosing, adverse events (AEs), and other factors on patients' health state utilities.


Treatment naive and experienced HIV patients participating in five open-label trials of highly active antiretroviral therapy (HAART) completed the 36-Item Short Form Health Survey (SF-36) instrument at various time points. SF-36 responses were converted to utilities using a previously reported algorithm. Expected utilities were estimated as a function of patient demographics, regimen attributes, disease status, and AEs using a mixed-effects maximum likelihood model. Mean utilities for five HIV health states were derived from predicted patient utilities.


Negative predictors of utility included greater age (−0.001), prior acquired immune deficiency syndrome-defining events (−0.036), female gender (−0.038), and injection drug use (−0.056; P < 0.01 for all). Utility also depended on CD4+ cell count (P < 0.01), but not the presence of undetectable viral load. Regimen attributes were marginally associated with changes in utility. Depression was associated with the largest decrease in utility (−0.054, P < 0.001) among the AEs examined. Using the model to generate predicted utilities from the sample provided mean estimates ranging from 0.742 (SD 0.058) to 0.798 (0.052) for CD4+ counts between 0 and 99 and ≥500 cells/mm3, respectively.


HIV patients' health-related quality of life may be substantially affected by clinically relevant patient-, disease-, and treatment-related factors, such as injection drug use, disease status, food/drink restrictions, and AEs.

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