title: Application of Bayesian Approach to Cost-Effectiveness Analysis of Antiviral Treatments in Chronic Hepatitis B.
abstract: BACKGROUND
  Hepatitis B virus (HBV) infection is a major problem for public health; timely antiviral treatment can significantly prevent the progression of liver damage from HBV by slowing down or stopping the virus from reproducing. In the study we applied Bayesian approach to cost-effectiveness analysis, using Markov Chain Monte Carlo (MCMC) simulation methods for the relevant evidence input into the model to evaluate cost-effectiveness of entecavir (ETV) and lamivudine (LVD) therapy for chronic hepatitis B (CHB) in Jiangsu, China, thus providing information to the public health system in the CHB therapy.
  
  
  METHODS
  Eight-stage Markov model was developed, a hypothetical cohort of 35-year-old HBeAg-positive patients with CHB was entered into the model. Treatment regimens were LVD100mg daily and ETV 0.5 mg daily. The transition parameters were derived either from systematic reviews of the literature or from previous economic studies. The outcome measures were life-years, quality-adjusted lifeyears (QALYs), and expected costs associated with the treatments and disease progression. For the Bayesian models all the analysis was implemented by using WinBUGS version 1.4.
  
  
  RESULTS
  Expected cost, life expectancy, QALYs decreased with age. Cost-effectiveness increased with age. Expected cost of ETV was less than LVD, while life expectancy and QALYs were higher than that of LVD, ETV strategy was more cost-effective. Costs and benefits of the Monte Carlo simulation were very close to the results of exact form among the group, but standard deviation of each group indicated there was a big difference between individual patients.
  
  
  CONCLUSIONS
  Compared with lamivudine, entecavir is the more cost-effective option. CHB patients should accept antiviral treatment as soon as possible as the lower age the more cost-effective. Monte Carlo simulation obtained costs and effectiveness distribution, indicate our Markov model is of good robustness.
authors: Department of Medical Insurance, School of Public Health, Southeast University, Nanjing, Jiangsu, China.
authors: Hua
authors: H
authors: Zhang
authors: Zhongda Hospital Affiliated to Southeast University, Nanjing, Jiangsu, China.
authors: Mingdong
authors: M
authors: Huo
authors: Department of Medical Insurance, School of Public Health, Southeast University, Nanjing, Jiangsu, China.
authors: Jianqian
authors: J
authors: Chao
authors: Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, Jiangsu, China.|Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China.
authors: Pei
authors: P
authors: Liu
mesh_terms: D000328:Adult; D000998:Antiviral Agents / Q000008:administration & dosage* / Q000191:economics* / Q000627:therapeutic use; D001499:Bayes Theorem; D003362:Cost-Benefit Analysis / Q000379:methods*; D005260:Female; D006147:Guanine / Q000008:administration & dosage / Q000031:analogs & derivatives / Q000191:economics / Q000627:therapeutic use; D019694:Hepatitis B, Chronic / Q000188:drug therapy*; D006801:Humans; D019259:Lamivudine / Q000008:administration & dosage / Q000191:economics / Q000627:therapeutic use; D008297:Male; D009010:Monte Carlo Method; D019057:Quality-Adjusted Life Years; D016896:Treatment Outcome
chemical_list: D000998:Antiviral Agents; D019259:Lamivudine; C413685:entecavir; D006147:Guanine