Cost-effectiveness of Hepatitis C Virus Treatment Models for People Who Inject Drugs in Opioid Agonist Treatment Programs.


Journal

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
ISSN: 1537-6591
Titre abrégé: Clin Infect Dis
Pays: United States
ID NLM: 9203213

Informations de publication

Date de publication:
17 03 2020
Historique:
received: 07 12 2018
accepted: 08 05 2019
pubmed: 17 5 2019
medline: 7 1 2021
entrez: 17 5 2019
Statut: ppublish

Résumé

Many people who inject drugs in the United States have chronic hepatitis C virus (HCV). On-site treatment in opiate agonist treatment (OAT) programs addresses HCV treatment barriers, but few evidence-based models exist. We evaluated the cost-effectiveness of HCV treatment models for OAT patients using data from a randomized trial conducted in Bronx, New York. We used a decision analytic model to compare self-administered individual treatment (SIT), group treatment (GT), directly observed therapy (DOT), and no intervention for a simulated cohort with the same demographic characteristics of trial participants. We projected long-term outcomes using an established model of HCV disease progression and treatment (hepatitis C cost-effectiveness model: HEP-CE). Incremental cost-effectiveness ratios (ICERs) are reported in 2016 US$/quality-adjusted life years (QALY), discounted 3% annually, from the healthcare sector and societal perspectives. For those assigned to SIT, we projected 89% would ever achieve a sustained viral response (SVR), with 7.21 QALYs and a $245 500 lifetime cost, compared to 22% achieving SVR, with 5.49 QALYs and a $161 300 lifetime cost, with no intervention. GT was more efficient than SIT, resulting in 0.33 additional QALYs and a $14 100 lower lifetime cost per person, with an ICER of $34 300/QALY, compared to no intervention. DOT was slightly more effective and costly than GT, with an ICER > $100 000/QALY, compared to GT. In probabilistic sensitivity analyses, GT and DOT were preferred in 91% of simulations at a threshold of <$100 000/QALY; conclusions were similar from the societal perspective. All models were associated with high rates of achieving SVR, compared to standard care. GT and DOT treatment models should be considered as cost-effective alternatives to SIT.

Sections du résumé

BACKGROUND
Many people who inject drugs in the United States have chronic hepatitis C virus (HCV). On-site treatment in opiate agonist treatment (OAT) programs addresses HCV treatment barriers, but few evidence-based models exist.
METHODS
We evaluated the cost-effectiveness of HCV treatment models for OAT patients using data from a randomized trial conducted in Bronx, New York. We used a decision analytic model to compare self-administered individual treatment (SIT), group treatment (GT), directly observed therapy (DOT), and no intervention for a simulated cohort with the same demographic characteristics of trial participants. We projected long-term outcomes using an established model of HCV disease progression and treatment (hepatitis C cost-effectiveness model: HEP-CE). Incremental cost-effectiveness ratios (ICERs) are reported in 2016 US$/quality-adjusted life years (QALY), discounted 3% annually, from the healthcare sector and societal perspectives.
RESULTS
For those assigned to SIT, we projected 89% would ever achieve a sustained viral response (SVR), with 7.21 QALYs and a $245 500 lifetime cost, compared to 22% achieving SVR, with 5.49 QALYs and a $161 300 lifetime cost, with no intervention. GT was more efficient than SIT, resulting in 0.33 additional QALYs and a $14 100 lower lifetime cost per person, with an ICER of $34 300/QALY, compared to no intervention. DOT was slightly more effective and costly than GT, with an ICER > $100 000/QALY, compared to GT. In probabilistic sensitivity analyses, GT and DOT were preferred in 91% of simulations at a threshold of <$100 000/QALY; conclusions were similar from the societal perspective.
CONCLUSIONS
All models were associated with high rates of achieving SVR, compared to standard care. GT and DOT treatment models should be considered as cost-effective alternatives to SIT.

Identifiants

pubmed: 31095683
pii: 5490664
doi: 10.1093/cid/ciz384
pmc: PMC7318779
doi:

Substances chimiques

Analgesics, Opioid 0
Antiviral Agents 0
Pharmaceutical Preparations 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1397-1405

Subventions

Organisme : NIAID NIH HHS
ID : P30 AI042853
Pays : United States
Organisme : NIDA NIH HHS
ID : P30 DA040500
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA034086
Pays : United States

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

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Auteurs

Sarah Gutkind (S)

Department of Healthcare Policy & Research, Weill Cornell Medical College, New York.

Bruce R Schackman (BR)

Department of Healthcare Policy & Research, Weill Cornell Medical College, New York.

Jake R Morgan (JR)

Department of Medicine, Section of Infectious Diseases, Boston Medical Center, Massachusetts.

Jared A Leff (JA)

Department of Healthcare Policy & Research, Weill Cornell Medical College, New York.

Linda Agyemang (L)

Department of Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York.

Sean M Murphy (SM)

Department of Healthcare Policy & Research, Weill Cornell Medical College, New York.

Matthew J Akiyama (MJ)

Department of Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York.

Brianna L Norton (BL)

Department of Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York.

Alain H Litwin (AH)

Department of Medicine, University of South Carolina School of Medicine and Greenville Health System.
Clemson University School of Health Research, South Carolina.

Benjamin P Linas (BP)

Department of Medicine, Section of Infectious Diseases, Boston Medical Center, Massachusetts.
Department of Epidemiology, Boston University School of Public Health, Massachusetts.

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