Effect of Incretin Analogues and Dipeptidyl-peptidase-IV inhibitors on the risk of thyroid cancer

Study type

• Study topic:
  Disease /health condition

  Human medicinal product
• Study type:
  Non-interventional study
• Scope of the study:
  Drug utilisation
• Data collection methods:
  Secondary data collection

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (A10AE) Insulins and analogues for injection, long-acting

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

  (A10BJ) Glucagon-like peptide-1 (GLP-1) analogues

  (A10BK) Sodium-glucose co-transporter 2 (SGLT2) inhibitors
• Medical condition to be studied:
  Type 2 diabetes mellitus

Population studied

• Short description of the study population:
  The study population involved patients aged 66 years or older, prescribed with GLP-1RA, DPP-IV inhibitors or SGLT-2 inhibitors between January 1, 2008, and December 31, 2018 identified from the Medicare Fee-for-Service Database.
• Age groups:
  Adults (65 to < 75 years)

  Adults (75 to < 85 years)

  Adults (85 years and over)
• Special population of interest:
  Frail population
• Estimated number of subjects:
  100000

Study design details

• Main study objective:
  To estimate the comparative effect of GLP-1RA and DPP-IV inhibitors versus sodium-glucose cotransporter-2 (SGLT-2) inhibitors on the incidence of thyroid cancer.
• Outcomes:
  The primary outcome is thyroid cancer (TC).
• Data analysis plan:
  The main effect measure estimate will be standardized incidence rate differences (IRD) with the assumption that there is no unmeasured confounding. We will also estimate IRD within different times after antihyperglycemic drug initiation to allow for incidence rates to vary over time. Secondary effect measure will be hazard ratios. When estimating risks of cancer outcomes in older Medicare patients, censoring those who died prior to having the outcome of interest, as commonly done in survival analyses, could introduce bias in the risk estimation. To avoid this, we will employ Aalen Johansen (AJ) estimators to estimate risks.