title: An expanded portfolio of survival metrics for assessing anticancer agents.
abstract: OBJECTIVE
  With the introduction of more effective anticancer agents that prolong survival, there is a need for new methods to define the clinical value of treatments. The objective of this preliminary qualitative and quantitative analysis was to assess the utility of an expanded portfolio of survival metrics to differentiate the value of anticancer agents.
  
  
  METHODS
  A literature review was conducted of phase 3 trial data, reported in regulatory submissions within the last 10 years of agents for 6 metastatic cancers (breast cancer, colorectal cancer [CRC], melanoma, non-small cell lung cancer [NSCLC], prostate cancer [PC], and renal cell cancer [RCC]).
  
  
  METHODS
  A new, simplified cost-value analysis tool was applied using survival outcomes and total drug costs. Metrics included median overall survival (OS), mean OS, 1-year survival rate, and number needed to treat (NNT) to avoid 1 death at 1 year. Survival results were compiled and compared both within and across trials by tumor type. Total drug costs were calculated by multiplying each agent's cost per month (from October/November 2013, based on the database Price Rx/Medi-Span) by duration of therapy.
  
  
  RESULTS
  Relative clinical value for each agent was not consistent across survival outcomes. In 3 tumor types, both the highest improvement in median OS and the highest improvement in mean OS occurred with the same anticancer agent (ipilimumab with melanoma, pemetrexed with NSCLC, and sunitinib with RCC); the highest improvement in the 1-year survival rate and the lowest NNT occurred together with the same anticancer agent in 5 tumor types (bevacizumab with CRC, ipilimumab with melanoma, erlotinib with NSCLC, abiraterone with PC, and temsirolimus with RCC). In the cost-value analysis, agents were inconsistent and achieved a high relative value with some survival outcomes, but not others.
  
  
  CONCLUSIONS
  This analysis suggests that any 1 metric may not completely characterize the expected survival benefit of all patients. The cost-value analysis tool may be applied to trial data and may be useful in helping to make treatment decisions, regardless of the agent's effectiveness. A combined metric will be needed, as well as further research that includes more mature data, other tumor types, and emerging treatments.
authors.affiliation: QuintilesIMS, 485 Lexington Ave, 26th Fl, New York, NY 10017. E-mail: Jennifer.karweit@quintilesims.com.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Karweit
authors.forename: Srividya
authors.initials: S
authors.lastname: Kotapati
authors.forename: Samuel
authors.initials: S
authors.lastname: Wagner
authors.forename: James W
authors.initials: JW
authors.lastname: Shaw
authors.forename: Steffan W
authors.initials: SW
authors.lastname: Wolfe
authors.forename: Amy P
authors.initials: AP
authors.lastname: Abernethy
mesh_terms: D000970:Antineoplastic Agents / Q000009:adverse effects / Q000191:economics* / Q000627:therapeutic use; D017326:Clinical Trials, Phase III as Topic; D003362:Cost-Benefit Analysis / Q000191:economics*; D018572:Disease-Free Survival; D016527:Drug Costs; D005260:Female; D006801:Humans; D008297:Male; D009369:Neoplasms / Q000188:drug therapy* / Q000401:mortality* / Q000473:pathology; D018570:Risk Assessment; D016019:Survival Analysis; D014481:United States
chemical_list: D000970:Antineoplastic Agents