Post-discharge Clinical and Economic Outcomes Among Patients with ACS Managed with PCI and treated with Prasugrel versus Ticagrelor (H7T-MC-B023)

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

  (B01AC24) ticagrelor

  ticagrelor
• Medical condition to be studied:
  Acute coronary syndrome

Population studied

• Short description of the study population:
  Study conducted between 31 July 2008 and 01 Aug 2013 includes patients from ProMetis Lx® Database with no history of TIA or stroke will have evidence of a fill for prasugrel or ticagrelor within 30 days post-discharge from an index ACS-PCI hospitalization and any physician visit within 90 days after hospital discharge.
• 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:
  17406

Study design details

• Main study objective:
  The primary objective is to compare net adverse clinical events (NACE) up to 1 year post-discharge from an index ACS-PCI hospitalisation in patients treated with prasugrel versus ticagrelor. The main hypothesis is that, after adjustment for baseline differences, outcomes associated with prasugrel will be non-inferior to those with ticagrelor through 1 year for ACS-PCI patients in regards to NACE.
• Outcomes:
  Net adverse clinical events (NACE) up to one year post-discharge from an index hospitalisation. Resource utilisation (medical and pharmacy utilisation) and other clinical outcomes (NACE components including bleeding rehospitalisations), healthcare charges, and treatment patterns (including adherence and persistence) at 30 days, 6 months, and one year post-discharge from the index hospitalisation.
• Data analysis plan:
  Baseline and outcomes data will be analysed before and after propensity matching. Unmatched cohorts will be compared with an appropriate 2-tailed statistic for continuous or categorical variables. Treatment groups will be matched based on baseline demographic, clinical, procedural, and payer characteristics. A one-sided test will then be computed to see if the clinical event rate difference between treatment groups is significantly <1.2 (20% non-inferiority margin). Cox regression will be used to compare clinical outcomes, with patients censored at the end of the index treatment exposure time (that is, 7 days after discontinuation or switching of the index medication). Per patient per month economic measures and incidence rates will be assessed to account for the variable follow-up. Economic outcomes and treatment patterns will be analysed after matching using descriptive statistics and appropriate regression models (for example, generalized linear model and logistic regression).