title: Strategies for treating latent multiple-drug resistant tuberculosis: a decision analysis.
abstract: BACKGROUND
  The optimal treatment for latent multiple-drug resistant tuberculosis infection remains unclear. In anticipation of future clinical trials, we modeled the expected performance of six potential regimens for treatment of latent multiple-drug resistant tuberculosis.
  
  
  METHODS
  A computerized Markov model to analyze the total cost of treatment for six different regimens: Pyrazinamide/ethambutol, moxifloxacin monotherapy, moxifloxacin/pyrazinamide, moxifloxacin/ethambutol, moxifloxacin/ethionamide, and moxifloxacin/PA-824. Efficacy estimates were extrapolated from mouse models and examined over a wide range of assumptions.
  
  
  RESULTS
  In the base-case, moxifloxacin monotherapy was the lowest cost strategy, but moxifloxacin/ethambutol was cost-effective at an incremental cost-effectiveness ratio of $21,252 per quality-adjusted life-year. Both pyrazinamide-containing regimens were dominated due to their toxicity. A hypothetical regimen of low toxicity and even modest efficacy was cost-effective compared to "no treatment."
  
  
  CONCLUSIONS
  In our model, moxifloxacin/ethambutol was the preferred treatment strategy under a wide range of assumptions; pyrazinamide-containing regimens fared poorly because of high rates of toxicity. Although more data are needed on efficacy of treatments for latent MDR-TB infection, data on toxicity and treatment discontinuation, which are easier to obtain, could have a substantial impact on public health practice.
authors.affiliation: Department of Medicine, Duke University Medical Center, Durham, North Carolina, United States of America. david.p.holland@duke.edu
authors.forename: David P
authors.initials: DP
authors.lastname: Holland
authors.forename: Gillian D
authors.initials: GD
authors.lastname: Sanders
authors.forename: Carol D
authors.initials: CD
authors.lastname: Hamilton
authors.forename: Jason E
authors.initials: JE
authors.lastname: Stout
mesh_terms: D000818:Animals; D000995:Antitubercular Agents / Q000627:therapeutic use*; D001372:Aza Compounds / Q000627:therapeutic use; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D004358:Drug Therapy / Q000191:economics / Q000379:methods; D004359:Drug Therapy, Combination; D004977:Ethambutol / Q000627:therapeutic use; D024841:Fluoroquinolones; D006801:Humans; D007538:Isoniazid / Q000627:therapeutic use; D008390:Markov Chains; D051379:Mice; D008962:Models, Theoretical; D000077266:Moxifloxacin; D017063:Outcome Assessment, Health Care; D019057:Quality-Adjusted Life Years; D011804:Quinolines / Q000627:therapeutic use; D012293:Rifampin / Q000627:therapeutic use; D018088:Tuberculosis, Multidrug-Resistant / Q000188:drug therapy*
chemical_list: D000995:Antitubercular Agents; D001372:Aza Compounds; D024841:Fluoroquinolones; D011804:Quinolines; D004977:Ethambutol; D000077266:Moxifloxacin; D007538:Isoniazid; D012293:Rifampin