title: Subgroup economic analysis for glioblastoma in a health resource-limited setting.
abstract: BACKGROUND
  The aim of this research was to evaluate the economic outcomes of radiotherapy (RT), temozolomide (TMZ) and nitrosourea (NT) strategies for glioblastoma patients with different prognostic factors.
  
  
  RESULTS
  A Markov model was developed to track monthly patient transitions. Transition probabilities and utilities were derived primarily from published reports. Costs were estimated from the perspective of the Chinese healthcare system. The survival data with different prognostic factors were simulated using Weibull survival models. Costs over a 5-year period and quality-adjusted life years (QALYs) were estimated. Probabilistic sensitivity and one-way analyses were performed. The baseline analysis in the overall cohort showed that the TMZ strategy increased the cost and QALY relative to the RT strategy by $25,328.4 and 0.29, respectively; and the TMZ strategy increased the cost and QALY relative to the NT strategy by $23,906.5 and 0.25, respectively. Therefore, the incremental cost effectiveness ratio (ICER) per additional QALY of the TMZ strategy, relative to the RT strategy and the NT strategy, amounts to $87,940.6 and $94,968.3, respectively. Subgroups with more favorable prognostic factors achieved more health benefits with improved ICERs. Probabilistic sensitivity analyses confirmed that the TMZ strategy was not cost-effective. In general, the results were most sensitive to the cost of TMZ, which indicates that better outcomes could be achieved by decreasing the cost of TMZ.
  
  
  CONCLUSIONS
  In health resource-limited settings, TMZ is not a cost-effective option for glioblastoma patients. Selecting patients with more favorable prognostic factors increases the likelihood of cost-effectiveness.
authors.affiliation: Department of Pharmacy, School of Medicine, Shanghai Jiaotong University, Renji Hospital, Shanghai, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Wu
authors.forename: Yifeng
authors.initials: Y
authors.lastname: Miao
authors.forename: Yongrui
authors.initials: Y
authors.lastname: Bai
authors.forename: Min
authors.initials: M
authors.lastname: Ye
authors.forename: Yuejuan
authors.initials: Y
authors.lastname: Xu
authors.forename: Huafeng
authors.initials: H
authors.lastname: Chen
authors.forename: Jinfang
authors.initials: J
authors.lastname: Shen
authors.forename: Yongming
authors.initials: Y
authors.lastname: Qiu
mesh_terms: D018906:Antineoplastic Agents, Alkylating / Q000191:economics / Q000627:therapeutic use*; D002681:China; D015331:Cohort Studies; D003362:Cost-Benefit Analysis; D003606:Dacarbazine / Q000031:analogs & derivatives* / Q000191:economics / Q000627:therapeutic use; D005909:Glioblastoma / Q000188:drug therapy / Q000191:economics* / Q000532:radiotherapy; D006295:Health Resources; D006801:Humans; D008390:Markov Chains; D008875:Middle Aged; D018803:Models, Economic; D011379:Prognosis; D019057:Quality-Adjusted Life Years; D016019:Survival Analysis; D000077204:Temozolomide; D035501:Uncertainty
chemical_list: D018906:Antineoplastic Agents, Alkylating; D003606:Dacarbazine; D000077204:Temozolomide