Leonard Emuren1,2,3, Seth Welles1, Grace Macalino4,5, Alison A Evans1, Marcia Polansky1, Anuradha Ganesan4,5,6, Rhonda E Colombo4,5,7, Brian K Agan8,9. 1. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA. 2. Department of Pediatrics, Eastern Virginia Medical School, Norfolk, VA, USA. 3. Children's Hospital of the King's Daughters, 601 Children's Lane, Norfolk, VA, USA. 4. Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA. 5. The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA. 6. Division of Infectious Diseases, Walter Reed National Military Medical Center, Bethesda, MD, USA. 7. Division of Infectious Diseases, Madigan Army Medical Center, Joint Base Lewis-McChord, WA, USA. 8. Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA. bagan@idcrp.org. 9. The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA. bagan@idcrp.org.
Abstract
OBJECTIVES: 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. METHODS: 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). RESULTS: 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). CONCLUSION: 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.
OBJECTIVES: 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. METHODS: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). RESULTS: 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). CONCLUSION: 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.
Entities:
Keywords:
HIV; Health-related quality of life; Highly active antiretroviral therapy; Mental component summary scores; Physical component summary scores
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