Dipeptidyl Peptidase-4 Inhibitors and Inflammatory Bowel Disease Risk: Impact of Study Design Differences on Comparative Safety Results

Study type

• Study type:
  Non-interventional study

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (A10BB) Sulfonylureas

  Sulfonylureas

  (A10BG) Thiazolidinediones

  Thiazolidinediones

  (A10BH) Dipeptidyl peptidase 4 (DPP-4) inhibitors

  Dipeptidyl peptidase 4 (DPP-4) inhibitors

  (A10BK) Sodium-glucose co-transporter 2 (SGLT2) inhibitors

  Sodium-glucose co-transporter 2 (SGLT2) inhibitors

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:
  100000

Study design details

• Main study objective:
  To evaluate the association between the initiation of DPP4i versus the initiation of clinically relevant second-line glucose lowering therapies (TZD and SU) and the short-term risk of IBD, based on an active comparator, new user study design.
• Outcomes:
  We use the same outcome algorithm in the study by Abrahami et al 1 (Appendix 4), defined using Read codes. In this algorithm, IBD events qualify as a study outcome only if they were accompanied by at least one supporting event in the 6 months preceding or following the IBD code (Appendix 5). Secondary outcomes include Crohn’s disease (CD) and ulcerative colitis (UC), respectively.
• Data analysis plan:
  We will assess this balance by looking at the crude distribution of CPRD data based covariates across treatment cohorts. We will then use propensity scores to remove remaining imbalances in measured potential confounders between study cohorts. Our primary aim is to identify active comparator drug initiators that will allow us to estimate what would have happened to the actual DPP4i initiators if they had, contrary to the fact, not initiated DPP4i. To achieve this goal, we will estimate the average treatment effect in the treated (ATT) by reweighting the comparator drug initiators by the propensity score odds (PS/(1-PS)), i.e. standardized mortality/morbidity ratio (SMR) weights 18. We will estimate and compare the cumulative incidence of both primary and secondary outcomes for each study cohort using weighted Kaplan-Meier methods. Crude and adjusted hazard ratios (HRs) for both primary and secondary outcomes will be estimated using weighted Cox proportional hazards models.