Comparative Cohort Study of Long-term Safety Outcomes of Risankizumab Compared to Biologic Treatments for Crohn’s Disease in a Real-world Setting in Sweden and Denmark

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Safety study (incl. comparative)
• Data collection methods:
  Secondary use of data

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Name of medicine:
  SKYRIZI
• Study drug International non-proprietary name (INN) or common name:
  RISANKIZUMAB
• Anatomical Therapeutic Chemical (ATC) code:
  (L04AC18) risankizumab

  risankizumab
• Medical condition to be studied:
  Crohn's disease

Population studied

• Age groups:
  Adult and elderly population (≥18 years)

Study design details

• Study design:
  This observational cohort population-based study will be carried out using data from Sweden and Denmark. A new-user, active comparator cohort design will be used to assess the association between exposure to risankizumab or other approved biologic treatment, with each safety outcome of interest.
• Main study objective:
  The objective is to estimate and compare, where possible, the incidence rates of malignancy excluding NMSC, NMSC, serious infections (including OI), serious hypersensitivity reactions and MACE, among individuals with moderate to severe CD aged ≥18 years who initiate risankizumab in the course of routine clinical care, as well as the incidence rates in individuals who initiate other approved biologic comparator treatments for the treatment of CD at the same line of therapy.
• Outcomes:
  The safety outcomes will be malignancy excluding NMSC, NMSC, serious infections (including OI), serious hypersensitivity reactions and MACE.
• Data analysis plan:
  Appropriate statistical analyses in an active-comparator design will be used. Cox proportional hazards regression model will be used to evaluate the association between the exposure and each one of the safety outcomes. Crude and adjusted hazard ratios, using Inverse Probability of the Treatment Weighting, will be estimated.