Comparison Of Clinical Outcomes, Resource Utilisation, And Costs In Patients Hospitalized For ACS Managed With PCI And Receiving Prasugrel Or Ticagrelor (H7T-US-B019)

Study type

• Study topic:
  Human medicinal product

  Disease /health condition
• Study type:
  Non-interventional study
• Scope of the study:
  Effectiveness study (incl. comparative)
• Data collection methods:
  Secondary use of data

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (B01AC22) prasugrel

  prasugrel
• Medical condition to be studied:
  Acute coronary syndrome

Population studied

• Short description of the study population:
  ACS patients managed with PCI and treated with prasugrel vs. ticagrelor through 30 days, including the index hospitalization.
• Age groups:
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)
• Special population of interest:
  Other
• Special population of interest, other:
  Patients with acute coronary syndrome
• Estimated number of subjects:
  18414

Study design details

• Main study objective:
  To compare 30-day net adverse clinical events (NACE) rates in ACS patients managed with PCI and treated with prasugrel vs. ticagrelor through 30 days, including the index hospitalisation.
• Outcomes:
  Net adverse clinical events (NACE), defined as the composite of all-cause death, any CV event, severe bleeding during index hospitalisation or rehospitalisation for bleeding, Components of the composite primary outcome measure (bleeding, mortality, TIA, stroke, or rehospitalisation for MI, UA, CHF, revascularisation, or stent thrombosis), dyspnea, bradyarrhythmia, economic outcomes (resource utilisation, costs), and treatment patterns(concomitant medications, PCI procedure, CABG surgery) at 30 and 90 days post discharge from the index hospitalisation
• Data analysis plan:
  Propensity score matching based on baseline demographic, clinical, procedural and payer characteristics will be used to adjust for potential confounding. All baseline variables will be described before and after matching. Primary and secondary categorical outcomes will be assessed as dependent variables using McNemar’s test. A one-sided p-value will be computed to test if the upper confidence limit of the event rate comparison between prasugrel and ticagrelor is <1.2 (20% non-inferiority margin based on relative risk). Cohort differences in matched continuous outcome variables will be analyzed as dependent variables using a generalized linear model (GLM) with gamma, Poisson and/or negative binomial distribution. Generalized Estimating Equations will be used to account for correlation between matched pairs. Sensitivity analyses will be employed as appropriate to assess the robustness of results to the potential for unmeasured confounding and other statistical assumptions.