{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Wang L"],"funding":["Agency for Healthcare Research and Quality","NIDA NIH HHS","Foundation for the National Institutes of Health","Health Resources and Services Administration","National Institutes of Health","National Institute on Drug Abuse","Simon Fraser University"],"pagination":["e531-e539"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6693664"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["6(8)"],"pubmed_abstract":["<h4>Background</h4>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.<h4>Methods</h4>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), southe"],"journal":["The lancet. HIV"],"pubmed_title":["Combined estimation of disease progression and retention on antiretroviral therapy among treated individuals with HIV in the USA: a modelling study."],"pmcid":["PMC6693664"],"funding_grant_id":["R01 DA041747","HHSA290201100007C","R01DA041747-02S1","HHSH250201600009C"],"pubmed_authors":["Gebo KA","Korthuis PT","Mathews WC","Mayer K","Diaz-Reyes R","Agwu A","Krebs E","Gaur A","Keruly J","Voss C","Wang L","Hellinger F","Beil R","Urbina A","Valenti W","Rutstein R","Moore RD","Aberg JA","Boswell S","Akbar M","Nijhawan A","Somboonwit C","Baranoski A","Felsen U","Min JE","Collins C","Fleishman J","Mills R","Edelstein H","Nosyk B","HIV Research Network","Allen S"],"additional_accession":[]},"is_claimable":false,"name":"Combined estimation of disease progression and retention on antiretroviral therapy among treated individuals with HIV in the USA: a modelling study.","description":"<h4>Background</h4>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.<h4>Methods</h4>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), southe","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Aug","modification":"2025-04-29T10:31:16.136Z","creation":"2020-10-04T07:16:39Z"},"accession":"S-EPMC6693664","cross_references":{"pubmed":["31303557"],"doi":["10.1016/S2352-3018(19)30148-1","10.1016/s2352-3018(19)30148-1"]}}