title: Assessing the clinical and economic impact of increasing treatment uptake in chronic hepatitis B infection using a Markov model.
abstract: Treatment uptake in chronic hepatitis B virus (HBV) infection is low in South Australia, and the cost-effectiveness of increasing treatment uptake rates in this population has not been assessed.
  
  
  OBJECTIVE
  Using a cohort Markov model, cost-effectiveness was assessed for three different treatment uptake scenarios: 2.9% (current level-scenario 1), 10% (scenario 2), and 15% (scenario 3). The initial HBV population included 2550 treatment eligible patients who transitioned between six different health states over a 10-year period. Treatment transition probabilities were based on tenofovir therapy, while those not assigned to treatment followed the natural history transition probabilities. We estimated the incremental cost per quality adjusted life year gained using the prevented number of deaths, hepatocellular carcinoma, and liver transplants.
  
  
  RESULTS
  Scenario 3 was associated with the lowest mean cost/person over 10 years (AU$60 133), compared with scenario 2 (AU$61 964) and scenario 1 (AU$64 597). Scenario 3 was also associated with the highest quality adjusted life year gained (8.196) compared with scenario 2 (7.985) and scenario 1 (7.684). Scenario 3 would result in 50% reduction in hepatocellular carcinoma and 30% reduction in HBV-related mortality compared with scenario 1, over a 10-year period. Higher treatment uptake was found to be cost-effective with at least 2 years of treatment at either 10% or 15% of the target population.
  
  
  CONCLUSIONS
  Maximizing the treatment uptake in the existing HBV population from 2.9% to 15% was cost-effective for periods of 2 years or more. This was due to a reduction in the number of expected clinical events.
authors.affiliation: Hepatology and Liver Transplantation Medicine Unit, Flinders Medical Centre, Bedford Park, South Australia, Australia.|School of Medicine, Flinders University, Bedford Park, South Australia, Australia.
authors.forename: Mohamed A
authors.initials: MA
authors.lastname: Chinnaratha
authors.affiliation: Flinders Health Economics Group, Flinders University, Bedford Park, South Australia, Australia.
authors.forename: Billingsley
authors.initials: B
authors.lastname: Kaambwa
authors.affiliation: School of Medicine, Flinders University, Bedford Park, South Australia, Australia.
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Woodman
authors.affiliation: Hepatology and Liver Transplantation Medicine Unit, Flinders Medical Centre, Bedford Park, South Australia, Australia.|School of Medicine, Flinders University, Bedford Park, South Australia, Australia.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Fraser
authors.affiliation: Hepatology and Liver Transplantation Medicine Unit, Flinders Medical Centre, Bedford Park, South Australia, Australia.|School of Medicine, Flinders University, Bedford Park, South Australia, Australia.
authors.forename: Alan J
authors.initials: AJ
authors.lastname: Wigg
mesh_terms: D000998:Antiviral Agents / Q000008:administration & dosage / Q000191:economics*; D001315:Australia / Q000453:epidemiology; D006528:Carcinoma, Hepatocellular / Q000517:prevention & control; D003362:Cost-Benefit Analysis; D019694:Hepatitis B, Chronic / Q000188:drug therapy* / Q000191:economics* / Q000453:epidemiology; D006801:Humans; D008113:Liver Neoplasms / Q000517:prevention & control; D016031:Liver Transplantation / Q000706:statistics & numerical data; D008390:Markov Chains; D011788:Quality of Life; D000068698:Tenofovir / Q000008:administration & dosage / Q000191:economics*; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D000998:Antiviral Agents; D000068698:Tenofovir
keywords: Markov model; chronic hepatitis B; treatment; uptake