Observational study on the risk of myocardial infarction and stroke associated with proton pump inhibitor use (RiDe-PPI (MI & STROKE))

Study type

• Study topic:
  Human medicinal product

  Disease /health condition
• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness
• 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:
  (A02BC) Proton pump inhibitors

  Proton pump inhibitors
• Medical condition to be studied:
  Acute myocardial infarction

  Ischaemic stroke

Population studied

• Short description of the study population:
  All patients aged 18 years or older who have been insured by the statutory health insurance provider Allgemeine Ortskrankenkasse (AOK) Bayern, for at least 2 years since January 2008.; Eligibility/exclusion criteria are: age of at least 18 years; no prevalent cardiovascular disease; no prior use of any PPIs. Additionally we demand no prior use of the; comparator medication in target trial.
• 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)
• Estimated number of subjects:
  6100000

Study design details

• Main study objective:
  We investigate whether long-term intake of proton pump inhibitors is associated with the risk of myocardial infarction and stroke.
• Outcomes:
  The risk of myocardial infarction and stroke associated with the long-term intake of proton pump inhibitors.
• Data analysis plan:
  || Estimation of the observational analog of the intention-to-treat effect: We will fit pooled logistic regression models to estimate hazard ratios and survival curves using time-varying stabilized inverse-probability weights. || Estimation of the observational analog of the per-protocol effect: We will apply different prespecified dose-response models, and derive another dose-response model from the data estimating a weighted cumulative exposure model. For each of these models we fit marginal structural Cox models using stabilized inverse probability of treatment weights.

Documents

Study publications

Nolde, M., Ahn, N., Dreischulte, T., Rückert-Eheberg, I.‑M., Güntner, F., Günte…