An Observational Post-Authorisation Safety Study (PASS) of Patients with Chronic Opioid Use for Non-Cancer Pain and Cancer Pain who have Opioid-Induced Constipation (OIC) (Naldemedine PASS)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (A06AH05) naldemedine
• Medical condition to be studied:
  Constipation

Population studied

• 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:
  26568

Study design details

• Main study objective:
  Assess the incidence of major adverse cardiovascular (CV) outcomes (a composite of CV death, fatal and nonfatal myocardial infarction MI, and fatal and nonfatal stroke) and gastrointestinal (GI) perforation in patients initiating naldemedine vs. non-over-the-counter (non-OTC), non-PAMORA prescription treatment for OIC
• Outcomes:
  Characterise the safety profile of patients initiating naldemedine vs. non-OTC, non- PAMORA prescription treatments for OIC in subpopulations under-represented in the clinical development programmes ((with severe hepatic impairment, with a previous history of CV disease, >=75 years old, pregnant women, with severe renal impairment, taking concurrent methadone, treated >1 year. assess the incidence of less severe outcomes in patients initiating naldemedine vs. non-OTC, non-PAMORA prescribed medication for OIC: less severe CV outcomes (hypertension, angina, arrhythmia and syncope), abdominal pain, diarrhoea, vomiting, opioid withdrawal syndrome, anti-analgesic effect due to centrally-mediated opioid receptor antagonism.
• Data analysis plan:
  Poisson regression model will be used to estimate the Relative Risk (RR) and construct 95% CIs of cumulative incidence and exposure-adjusted incidence rate of MACE for each data source. Meta-analysis techniques will be used to summarise primary and secondary endpoints across databases.