Linwei Wang1, Emanuel Krebs1, Jeong E Min1, W Christopher Mathews2, Ank Nijhawan3, Charurut Somboonwit4, Judith A Aberg5, Richard D Moore6, Kelly A Gebo6, Bohdan Nosyk7. 1. British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada. 2. Department of Medicine, University of California San Diego, San Diego, CA, USA. 3. Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA. 4. Department of Internal Medicine, University of South Florida Morsani College of Medicine, Tampa, FL, USA. 5. Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. 6. Johns Hopkins University School of Medicine, Baltimore, MD, USA. 7. British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada; Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada. Electronic address: bnosyk@cfenet.ubc.ca.
Abstract
BACKGROUND: Accurately estimating HIV disease progression and retention on antiretroviral therapy (ART) can help inform interventions to control HIV microepidemics and mathematical models used to inform health-resource allocation decisions. Our objective was to estimate the monthly probabilities of on-ART CD4 T-cell count progression, mortality, ART dropout, and ART reinitiation using a continuous-time multistate Markov model. We also aimed to validate health-state transition probability estimates to ensure they accurately reproduced the regional HIV microepidemics across the USA. METHODS: In our modelling study, we considered a cohort of patients from the HIV Research Network, a consortium of 17 adult and paediatric HIV-care providers located in the northeastern (n=8), southern (n=5), and western (n=4) regions of the USA. Individuals aged 15 years or older who were in HIV care (defined as one CD4 test and one HIV-care visit in a calendar year period) with at least one ART prescription between Jan 1, 2010, and Dec 31, 2015, were included in the analysis. We used continuous-time multistate Markov models to estimate transitions between CD4 strata and between on-ART and off-ART states. We examined and adjusted for differences in probability of transition by region, race or ethnicity, sex, HIV risk group, and other baseline clinical indicators. FINDINGS: The median age of the 32 242 individuals included in the analysis was 44 years (interquartile range 35-51). Over a median follow-up of 4·9 years (2·6-6·0), 8614 (26·7%) of 32 242 people interrupted ART and 1325 (4·1%) of 32 242 people died. Women, men who have sex with men, and individuals with no previous ART experience had greater increases in CD4 cell counts, whereas black people and people who inject drugs had increased probabilities of ART dropout and faster disease progression. Regardless of CD4 strata, individuals had increased hazard for ART dropout if they were from the south (adjusted hazard ratio [aHR] range from 1·91, 95% CI 1·71-2·13, to 2·45, 2·29-2·62) or the west (aHR range from 1·29, 1·10-1·51, to 1·66, 1·51-1·82) of the USA, compared with individuals from the northeast USA. INTERPRETATION: Our results show heterogeneities in disease progression during ART and probability of ART retention across race and ethnicity, HIV risk groups, and regions. These differences should be viewed as targets for intervention and should be incorporated in mathematical models of regional HIV microepidemics in the USA. FUNDING: US National Institutes of Health, Agency for Healthcare Research and Quality, and Health Resources and Services Administration.
BACKGROUND: Accurately estimating HIV disease progression and retention on antiretroviral therapy (ART) can help inform interventions to control HIV microepidemics and mathematical models used to inform health-resource allocation decisions. Our objective was to estimate the monthly probabilities of on-ART CD4 T-cell count progression, mortality, ART dropout, and ART reinitiation using a continuous-time multistate Markov model. We also aimed to validate health-state transition probability estimates to ensure they accurately reproduced the regional HIV microepidemics across the USA. METHODS: In our modelling study, we considered a cohort of patients from the HIV Research Network, a consortium of 17 adult and paediatric HIV-care providers located in the northeastern (n=8), southern (n=5), and western (n=4) regions of the USA. Individuals aged 15 years or older who were in HIV care (defined as one CD4 test and one HIV-care visit in a calendar year period) with at least one ART prescription between Jan 1, 2010, and Dec 31, 2015, were included in the analysis. We used continuous-time multistate Markov models to estimate transitions between CD4 strata and between on-ART and off-ART states. We examined and adjusted for differences in probability of transition by region, race or ethnicity, sex, HIV risk group, and other baseline clinical indicators. FINDINGS: The median age of the 32 242 individuals included in the analysis was 44 years (interquartile range 35-51). Over a median follow-up of 4·9 years (2·6-6·0), 8614 (26·7%) of 32 242 people interrupted ART and 1325 (4·1%) of 32 242 peopledied. Women, men who have sex with men, and individuals with no previous ART experience had greater increases in CD4 cell counts, whereas black people and people who inject drugs had increased probabilities of ART dropout and faster disease progression. Regardless of CD4 strata, individuals had increased hazard for ART dropout if they were from the south (adjusted hazard ratio [aHR] range from 1·91, 95% CI 1·71-2·13, to 2·45, 2·29-2·62) or the west (aHR range from 1·29, 1·10-1·51, to 1·66, 1·51-1·82) of the USA, compared with individuals from the northeast USA. INTERPRETATION: Our results show heterogeneities in disease progression during ART and probability of ART retention across race and ethnicity, HIV risk groups, and regions. These differences should be viewed as targets for intervention and should be incorporated in mathematical models of regional HIV microepidemics in the USA. FUNDING: US National Institutes of Health, Agency for Healthcare Research and Quality, and Health Resources and Services Administration.
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