title: Comparative economics of a 12-gene assay for predicting risk of recurrence in stage II colon cancer.
abstract: BACKGROUND
  Prior economic analysis that compared the 12-gene assay to published patterns of care predicted the assay would improve outcomes while lowering medical costs for stage II, T3, mismatch-repair-proficient (MMR-P) colon cancer patients. This study assessed the validity of those findings with real-world adjuvant chemotherapy (aCT) recommendations from the US third-party payer perspective.
  
  
  METHODS
  Costs and quality-adjusted life-years (QALYs) were estimated for stage II, T3, MMR-P colon cancer patients using guideline-compliant, state-transition probability estimation methods in a Markov model. A study of 141 patients from 17 sites in the Mayo Clinic Cancer Research Consortium provided aCT recommendations before and after knowledge of the 12-gene assay results. Progression and adverse events data with aCT regimens were based on published literature. Drug and administration costs for aCT were obtained from 2014 Medicare Fee Schedule. Sensitivity analyses evaluated the drivers and robustness of the primary outcomes.
  
  
  RESULTS
  After receiving the 12-gene assay results, physician recommendations in favor of aCT decreased 22 %; fluoropyrimidine monotherapy and FOLFOX recommendations each declined 11 %. Average per-patient drugs, administration, and adverse events costs decreased $US2,339, $US733, and $US3,211, respectively. Average total direct medical costs decreased $US991. Average patient well-being improved by 0.114 QALYs. Savings are expected to persist even if the cost of oxaliplatin drops by >75 % due to generic substitution.
  
  
  CONCLUSIONS
  This study provides evidence that real-world changes in aCT recommendations due to the 12-gene assay are likely to reduce direct medical costs and improve well-being for stage II, T3, MMR-P colon cancer patients.
authors.affiliation: Mayo Clinic, 1216 2nd St SW, Rochester, MN, 55902, USA.
authors.forename: Steven R
authors.initials: SR
authors.lastname: Alberts
authors.forename: Tiffany M
authors.initials: TM
authors.lastname: Yu
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Behrens
authors.forename: Lindsay A
authors.initials: LA
authors.lastname: Renfro
authors.forename: Geetika
authors.initials: G
authors.lastname: Srivastava
authors.forename: Gamini S
authors.initials: GS
authors.lastname: Soori
authors.forename: Shaker R
authors.initials: SR
authors.lastname: Dakhil
authors.forename: Rex B
authors.initials: RB
authors.lastname: Mowat
authors.forename: John P
authors.initials: JP
authors.lastname: Kuebler
authors.forename: George P
authors.initials: GP
authors.lastname: Kim
authors.forename: Miroslaw A
authors.initials: MA
authors.lastname: Mazurczak
authors.forename: John
authors.initials: J
authors.lastname: Hornberger
mesh_terms: D000328:Adult; D017024:Chemotherapy, Adjuvant / Q000191:economics; D003110:Colonic Neoplasms / Q000188:drug therapy / Q000191:economics* / Q000235:genetics*; D003362:Cost-Benefit Analysis; D016527:Drug Costs; D005260:Female; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing / Q000191:economics*; D017048:Health Care Costs; D006801:Humans; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000188:drug therapy / Q000191:economics* / Q000235:genetics*; D019057:Quality-Adjusted Life Years