title: Estimating the Population Benefits and Costs of Rituximab Therapy in the United States from 1998 to 2013 Using Real-World Data.
abstract: BACKGROUND
  Rituximab was approved in 1997 and is regularly one of the largest drug expenditures for Medicare; however, its benefits and costs have not been estimated from a population perspective.
  
  
  OBJECTIVE
  To estimate both the clinical and the economic outcomes of rituximab for its approved hematological uses at the population level.
  
  
  METHODS
  Analyses using cancer registry incidence data from the Surveillance, Epidemiology, and End Results (SEER) program, and outcomes data from SEER data linked with Medicare administrative claims (SEER-Medicare data). These results were incorporated into an epidemiological simulation model of the population over time.
  
  
  METHODS
  We modeled all United States patients from 1998 to 2013 diagnosed with diffuse large B-cell lymphoma, follicular lymphoma, or chronic lymphocytic leukemia.
  
  
  METHODS
  Using this model, we estimated the life-years saved, as well as their economic benefit, in the United States population. We also estimated the incremental cost of adding rituximab to chemotherapy. All economic inputs were based on Medicare reimbursed amounts inflated to 2013 dollars.
  
  
  RESULTS
  There were 279,704 cumulative life-years saved which were valued at $25.44 billion. The incremental direct medical cost of rituximab was estimated to be $8.92 billion, resulting in an incremental economic gain of $16.52 billion.
  
  
  CONCLUSIONS
  These analyses, based on real-world evidence, show that the introduction of rituximab into clinical practice has produced a substantial number of incremental life-years. Importantly, the economic benefit of the life-years gained greatly exceeds the added costs of treatment.
authors.affiliation: *Outcomes Insights Inc., Westlake Village †Genentech Inc., South San Francisco, CA ‡Mayo Clinic Arizona, Scottsdale, AZ.
authors.forename: Mark D
authors.initials: MD
authors.lastname: Danese
authors.forename: Carolina M
authors.initials: CM
authors.lastname: Reyes
authors.forename: Michelle L
authors.initials: ML
authors.lastname: Gleeson
authors.forename: Marc
authors.initials: M
authors.lastname: Halperin
authors.forename: Sandra L
authors.initials: SL
authors.lastname: Skettino
authors.forename: Joseph
authors.initials: J
authors.lastname: Mikhael
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000970:Antineoplastic Agents / Q000191:economics* / Q000627:therapeutic use; D003362:Cost-Benefit Analysis; D016527:Drug Costs; D005260:Female; D006801:Humans; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000188:drug therapy* / Q000401:mortality; D016393:Lymphoma, B-Cell / Q000188:drug therapy* / Q000401:mortality; D008224:Lymphoma, Follicular / Q000188:drug therapy* / Q000401:mortality; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D008875:Middle Aged; D018803:Models, Economic; D009010:Monte Carlo Method; D000069283:Rituximab / Q000191:economics* / Q000627:therapeutic use; D018426:SEER Program / Q000706:statistics & numerical data; D016019:Survival Analysis; D013997:Time Factors; D014481:United States
chemical_list: D000970:Antineoplastic Agents; D000069283:Rituximab