Sodium-glucose cotransporter-2 inhibitor initiation and the short-term risk of hospitalized acute kidney injury (SGLT2 inhibitors and short-term AKI)

Study type

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

  Drug utilisation

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (A10BK) Sodium-glucose co-transporter 2 (SGLT2) inhibitors

  Sodium-glucose co-transporter 2 (SGLT2) inhibitors

  (A10BB) Sulfonylureas

  Sulfonylureas
• Medical condition to be studied:
  Type 2 diabetes mellitus

  Acute kidney injury

Population studied

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

    • Adults (18 to < 65 years)

      • Adults (18 to < 46 years)
      • Adults (46 to < 65 years)
    • Elderly (≥ 65 years)

      • Adults (65 to < 75 years)
      • Adults (75 to < 85 years)
      • Adults (85 years and over)
• Special population of interest:
  Renal impaired

  Hepatic impaired
• Estimated number of subjects:
  300000

Study design details

• Main study objective:
  Objective 1 = To describe the temporal trends of SGLT2 inhibitor use in cohort of commercially insured beneficiaries with T2DM from the U.S. Objective 2 = To evaluate the association between SGLT2 inhibitor initiation and the short-term risk of hospitalized AKI in in cohort of commercially insured beneficiaries from the U.S.
• Outcomes:
  The primary outcome of interest is hospitalized AKI.
• Data analysis plan:
  For our outcomes study will will use an active comparator new-user study design. Cox proportional hazards models will be used to estimate hazard ratios (HRs) and their 95% confidence intervals (CIs) at each respective time point of interest (30-, 60- 90- and 180-days after new-use). In addition, Kaplan-Meier methods will be used to estimate risk differences (RDs) at each respective time point of interest (30-, 60- 90- and 180-days after new-use). The 95% CIs for RDs will be obtained using a non-parametric bootstrap based on 250 resamples. Across all analyses, inverse probability of treatment (IPT) weighting will be used for confounding control.