title: Cost-Effectiveness of Peg-Interferon, Interferon and Oral Nucleoside Analogues in the Treatment of Chronic Hepatitis B and D Infections in China.
abstract: OBJECTIVE
  The cost-effectiveness of highly effective, but costly, peg-interferon (peg-IFN) treatment for chronic hepatitis B (CHB) infections in China is unknown. Endemic hepatitis D virus (HDV) may also modify the effectiveness of any HBV treatment option. The objective of this study is to determine the best antiviral treatment from a societal perspective in the Chinese population, which contains a mix of HBV and HDV infections.
  
  
  METHODS
  A Markov model is developed to simulate the clinical course of CHB and chronic hepatitis D (CHD) individuals. For a hypothetical Chinese cohort of 10,000 individuals aged 30-60 years, cost-utility analysis is performed for therapies with: lamivudine, adefovir, telbivudine, entecavir, IFN and Peg-IFN. Costs and quality-adjusted life-years (QALYs) are discounted at 3 % annually. A one-way sensitivity analysis is also conducted.
  
  
  RESULTS
  Lamivudine, adefovir, telbivudine, and entecavir are all cost-effective treatments compared to palliative care at an incremental cost-effectiveness ratio (ICER) of -$418, -$197, -$443 and -$317 per QALY, respectively (2015 US dollars). Peg-IFN yields a maximum 156,000 QALYs with an ICER of $1149 per QALY while IFN results in the highest cumulative mortality of 48 % along with the lowest QALY gained. Probabilistic sensitivity analyses confirm that only Peg-IFN and ETV are the only two cost-effective options at the current willingness-to-pay (WTP) of $12,000 in China. However, entecavir has a higher probability of being cost-effective than Peg-IFN at current WTP for all age groups.
  
  
  CONCLUSIONS
  Peg-IFN generates maximum QALYs compared to lamivudine, adefovir, telbivudine and interferon, and presents itself as a cost-effective option at current WTP. Alternatively entecavir can be used in China, generating 10 % lower QALYs than Peg-IFN but costing less than palliative care.
authors.affiliation: School of Mathematics and Statistics, University of New South Wales, Sydney, NSW, 2052, Australia. ashish.goyal@student.unsw.edu.au.
authors.forename: Ashish
authors.initials: A
authors.lastname: Goyal
authors.affiliation: School of Mathematics and Statistics, University of New South Wales, Sydney, NSW, 2052, Australia.
authors.forename: John M
authors.initials: JM
authors.lastname: Murray
mesh_terms: D000225:Adenine / Q000031:analogs & derivatives; D000328:Adult; D000367:Age Factors; D000368:Aged; D000998:Antiviral Agents / Q000191:economics / Q000627:therapeutic use*; D002681:China; D015331:Cohort Studies; D017281:Cost of Illness; D003362:Cost-Benefit Analysis; D016527:Drug Costs; D005260:Female; D019694:Hepatitis B, Chronic / Q000188:drug therapy* / Q000191:economics; D019701:Hepatitis D, Chronic / Q000188:drug therapy* / Q000191:economics; D006801:Humans; D007372:Interferons / Q000191:economics / Q000627:therapeutic use*; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D009705:Nucleosides / Q000627:therapeutic use*; D063065:Organophosphonates; D010166:Palliative Care / Q000191:economics; D019057:Quality-Adjusted Life Years
chemical_list: D000998:Antiviral Agents; D009705:Nucleosides; D063065:Organophosphonates; C053001:adefovir; D007372:Interferons; D000225:Adenine