title: Evaluating Expected Costs and Benefits of Granting Access to New Treatments on the Basis of Progression-Free Survival in Non-Small-Cell Lung Cancer.
abstract: OBJECTIVE
  Surrogate end points may be used as proxy for more robust clinical end points. One prominent example is the use of progression-free survival (PFS) as a surrogate for overall survival (OS) in trials for oncologic treatments. Decisions based on surrogate end points may expedite regulatory approval but may not accurately reflect drug efficacy. Payers and clinicians must balance the potential benefits of earlier treatment access based on surrogate end points against the risks of clinical uncertainty.
  
  
  OBJECTIVE
  To present a framework for evaluating the expected net benefit or cost of providing early access to new treatments on the basis of evidence of PFS benefits before OS results are available, using non-small-cell lung cancer (NSCLC) as an example.
  
  
  METHODS
  A probabilistic decision model was used to estimate expected incremental social value of the decision to grant access to a new treatment on the basis of PFS evidence. The model analyzed a hypothetical population of patients with NSCLC who could be treated during the period between PFS and OS evidence publication. Estimates for delay in publication of OS evidence following publication of PFS evidence, expected OS benefit given PFS benefit, incremental cost of new treatment, and other parameters were drawn from the literature on treatment of NSCLC.
  
  
  METHODS
  Incremental social value of early access for each additional patient per month (in 2014 US dollars).
  
  
  RESULTS
  For "medium-value" model parameters, early reimbursement of drugs with any PFS benefit yields an incremental social cost of more than $170,000 per newly treated patient per month. In contrast, granting early access on the basis of PFS benefit between 1 and 3.5 months produces more than $73,000 in incremental social value. Across the full range of model parameter values, granting access for drugs with PFS benefit between 3 and 3.5 months is robustly beneficial, generating incremental social value ranging from $38,000 to more than $1 million per newly treated patient per month, whereas access for all drugs with any PFS benefit is usually not beneficial.
  
  
  CONCLUSIONS
  The value of providing access to new treatments on the basis of surrogate end points, and PFS in particular, likely varies considerably. Payers and clinicians should carefully consider how to use PFS data in balancing potential benefits against costs in each particular disease.
authors.affiliation: Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles.
authors.forename: Darius N
authors.initials: DN
authors.lastname: Lakdawalla
authors.affiliation: Precision Health Economics, Los Angeles, California.
authors.forename: Jacquelyn W
authors.initials: JW
authors.lastname: Chou
authors.affiliation: Precision Health Economics, Los Angeles, California.
authors.forename: Mark T
authors.initials: MT
authors.lastname: Linthicum
authors.affiliation: Precision Health Economics, Los Angeles, California.
authors.forename: Joanna P
authors.initials: JP
authors.lastname: MacEwan
authors.affiliation: Novartis Pharmaceuticals, East Hanover, New Jersey.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles.
authors.forename: Dana P
authors.initials: DP
authors.lastname: Goldman
mesh_terms: D002289:Carcinoma, Non-Small-Cell Lung / Q000191:economics* / Q000401:mortality / Q000628:therapy*; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D018572:Disease-Free Survival; D004608:Eligibility Determination / Q000191:economics*; D017048:Health Care Costs; D006297:Health Services Accessibility / Q000191:economics*; D006801:Humans; D008175:Lung Neoplasms / Q000191:economics* / Q000401:mortality / Q000628:therapy*; D018803:Models, Economic; D018579:Patient Selection; D011050:Policy Making; D011336:Probability; D017064:Process Assessment, Health Care / Q000191:economics*; D016019:Survival Analysis; D013997:Time Factors; D016896:Treatment Outcome