title: The impact of drug vintage on patient survival: a patient-level analysis using Quebec's provincial health plan data.
abstract: OBJECTIVE
  There is some debate about the value received for the money spent on prescription drugs. Some argue that most drug spending is on "me-too" drugs--drugs that provide only marginal health gains. Others suggest that the opposite is true--new drugs offer good value for money and are well worth the cost. To provide evidence on this issue, we evaluated the impact of drug innovation on the longevity of Canadians.
  
  
  METHODS
  We analyzed patient-level claims data from Quebec's provincial health plan. We selected elderly patients with continuous health coverage dispensed at least one drug prescription in each year of the study period, 1997 to 2006. Drug vintage was defined as the active ingredient's earliest marketed date. We estimated the impact of drug vintage on patient survival using a time-varying Cox proportional hazards model that controlled for year indicator variables, patient age, sex, region of residence, low income status, medical services use, concomitant drug use, and comorbidities.
  
  
  RESULTS
  Of the 102,743 subjects in the study population, 14,154 (14%) died during the study period. Mean patient age was 68 years; 59% were women. Our survival models indicated that the use of newer medications was associated with a statistically significant mortality risk reduction (hazard ratio: 0.522; 95% confidence interval: 0.476 to 0.572, P < 0.0001), relative to older medications. Other covariates associated with an increased risk of mortality included age, sex (male), low guaranteed income supplement status, hospitalization, and number of comorbidities.
  
  
  CONCLUSIONS
  This analysis showed that recent drug innovation has had a significant beneficial impact on the longevity of elderly patients.
authors.affiliation: Graduate School of Business, Columbia University, New York, NY, USA.
authors.forename: Frank R
authors.initials: FR
authors.lastname: Lichtenberg
authors.forename: Paul
authors.initials: P
authors.lastname: Grootendorst
authors.forename: Marc
authors.initials: M
authors.lastname: Van Audenrode
authors.forename: Dominick
authors.initials: D
authors.lastname: Latremouille-Viau
authors.forename: Patrick
authors.initials: P
authors.lastname: Lefebvre
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease / Q000188:drug therapy* / Q000401:mortality; D015897:Comorbidity; D016208:Databases, Factual; D004345:Drug Industry / Q000706:statistics & numerical data / Q000639:trends*; D005260:Female; D006801:Humans; D008136:Longevity; D008297:Male; D009313:National Health Programs; D009936:Organizational Innovation; D055553:Prescription Drugs / Q000191:economics / Q000627:therapeutic use*; D016016:Proportional Hazards Models; D011792:Quebec; D012307:Risk Factors; D012737:Sex Factors; D016019:Survival Analysis; D015996:Survival Rate
chemical_list: D055553:Prescription Drugs