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20-02-2020 | Uitgave 7/2020

Quality of Life Research 7/2020

Predictors of health-related quality of life among military HIV-infected individuals

Quality of Life Research > Uitgave 7/2020
Leonard Emuren, Seth Welles, Grace Macalino, Alison A. Evans, Marcia Polansky, Anuradha Ganesan, Rhonda E. Colombo, Brian K. Agan, the Infectious Disease Clinical Research Program HIV Working Group
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s11136-020-02441-5) contains supplementary material, which is available to authorized users.


The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions or policies of Uniformed Services University of the Health Sciences (USUHS), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. (HJF), the Department of Defense (DoD), the Departments of the Army, Navy, or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government. The investigators have adhered to the policies for protection of human subjects as prescribed in 45CFR46.

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To determine long-term predictors of health-related quality of life (HRQOL) and evaluate the treatment effect of highly active antiretroviral therapy (HAART) on HRQOL in the US Military HIV Natural History Study (NHS) cohort.


Participants were a nested cohort of the NHS who responded to the Rand Short Form 36 questionnaire administered from 2006 to 2010. Physical component summary scores (PCS) and mental component summary scores (MCS) were computed using standard algorithms. HAART-status was categorized as non-protease inhibitor-based (NPI-HAART), protease inhibitor-based (PI-HAART), HAART-naïve, or off-HAART. Mixed linear random effects models were used to estimate changes in PCS and MCS over time for treatment and covariates (including CD4 count, HIV viral load, medical and mental comorbidities).


Eight hundred and twelve participants met the inclusion criteria. There was no difference in PCS or MCS between those on PI-HAART compared to NPI-HAART. Significant predictors of PCS were CD4 count < 200 cells/mm3 (β = − 2.90), CD4 count 200–499 cells/mm3 (β = − 0.80), and mental comorbidity (β = − 3.23). Others were medical comorbidity, AIDS-defining illness, being on NPI-HAART, HAART-naïve, age, and rank. Those with medical comorbidities experienced yearly improvement in PCS. Predictors of MCS were CD4 count < 200 cells/mm3 (β = − 2.53), mental comorbidity (β = − 4.58), and being African American (β = 2.59).


HRQOL was significantly affected by low CD4 count, medical and mental comorbidities. Addressing these modifiable factors would be expected to improve the physical and mental HRQOL of the cohort. Our study did not find any treatment benefit of NPI-HAART over PI-HAART on HRQOL in the long term.

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