Table 1.

Summary of characteristics and key CV results of published population‐based cohort studies on SGLT2‐Is. Unless specified otherwise, outcome results are expressed in terms of hazard ratios with relevant 95% confidence intervals in parentheses

Study	Population	Intervention	Comparator	Main CV outcome(s)	Key results	Main findings on subgroup/sensitivity analyses	Notes
UK cohort16	T2DM with 1‐yr registration period (electronic medical records from GPs); 20% with history of CVD	Dapagliflozin (4444 patients)	Not exposed to an SGLT2‐I (17 680)	ACM, incident CVD (MI and ischaemic heart disease, stroke or TIA, and heart failure or left ventricular dysfunction in low‐risk cohort)	ACM: adjIRR = 0.50 (0.33–0.75) Incident CVD: adjIRR = 0.89 (0.61–1.30)	In the low‐risk population, adjIRR = 0.44 (0.25–0.78) Sensitivity analyses (DPP4 Is used as a negative control, and high CV risk) consistent in magnitude and direction (except when excluding patients suggestive of T1DM)	Immortal time bias was accounted for Different covariates used as confounders, including BMI Median follow‐up 0.9 yr
Swedish cohort17	Patients with first‐time prescription of either DPP4 or SGLT2‐Is, or insulin recorded in national registers; 20% with microvascular disease (matched cohort)	DPP4‐Is or SGLT2‐Is (21 758 patients)	Insulin (10 979a)	ACM, fatal and non‐fatal CVM (MI, ischaemic stroke, unstable angina pectoris, heart failure or CVM)	ACM: 0.58 (0.52–0.65) Fatal and non‐fatal CVM: 0.84 (0.73–0.97).	In the subgroup of patients with established CV risk at baseline, dapagliflozin reduced CVM (HR = 0.47, 95% CI = 0.24–0.93), but no significance in the larger cohort without CV risk at baseline Data on dapagliflozin slightly more favourable for fatal/non‐fatal CVM	Potential for immortal time bias and time‐lag bias18, 19, 20, 21 Median follow‐up 1.5 yr (matched cohort)
US cohort15	T2DM (US commercial healthcare database); 52% with hypertension and 48% with hyperlipidemia	Canagliflozin (28 149 unique initiators)	Non‐gliflozin agents (DPP4‐I, GLP1‐RA, or a sulphonylurea)	HHF, MACE (admitted to hospital for acute MI, ischaemic stroke, or hemorrhagic stroke), ACM, stroke, unstable angina, MI	HHF (vs. DPP4‐Is): 0.70 (0.54–0.92) MACE (vs. DPP4‐Is): 0.89 (0.68–1.17) ACM (vs. DPP4‐Is): 0.66 (0.25–1.74)	Similar data in the three cohorts (vs. DPP4‐Is, GLP1‐RAs or sulphonylurea), with higher benefit for the third cohort Consistency in sensitivity analyses (adjusted for baseline HbA1c level, stratified by previous CV events), except for HHF (benefit emerged only in patients with previous HHF)	Propensity score matching and several sensitivity analyses to account for unmeasured confounders Median follow‐up 0.6 yr (matched cohort)
EASEL14	T2DM with established CV disease with ≥1 yr of observation before the index date (US Military Health System); 31% with chronic complications	New user of SGLT2‐Is (12629a)	New user of non‐SGLT2‐Is	ACM, HHF, MACE (ACM, non‐fatal MI, and non‐fatal stroke), MI, stroke, BKA	ACM: 0.57 (0.49–0.66) HHF: 0.57 (0.45–0.73) MACE: 0.67 (0.60–0.75) BKA: 1.99 (1.12–3.51)	Consistency of CV endpoints in sensitivity analyses (removing individually and collectively patients receiving insulin, sulphonylureas, and thiazolidinediones, having dementia) and subgroup analyses (sex, age, recent insulin/GLP‐1 RA use, history of HF, recent HHF, CVD type, renal disease) Some differences emerged only for BKA risk (higher in males, without previous use of GLP‐1 RA and no renal disease)	Propensity score matching with >850 variables Immortal time bias cannot be excluded Median follow‐up 1.6 yr (intention‐to‐threat cohort)
CVD‐REAL10	T2DM with >1 yr data history in the database before the index date (healthcare records from 6 countries); 13% with history of CVD	New user of SGLT2‐Is (as initial or add‐on therapy) [max 154 528 patientsa)	New user of any other oral or injectable glucose‐lowering medication	ACM, HHF, MACEb	ACM: 0.49 (0.41–0.57) HHF: 0.61 (0.51–0.73) MACEb: 0.54 (0.48–0.60)	Consistency in sensitivity analyses (within each country, United States vs. Europe, stepwise removal of specific antidiabetic classes, in‐ and outpatient hospital visit for HF), including published sub‐analysis in patients with/without previous CV disease22 Non‐significant reduced risk in UK cohort Modestly lower risk of MI and stroke in sub‐study23	Propensity score matching with several variables Potential immortal time bias18, 19, 20, 21 Median follow‐up 0.6 yr
CVD‐REAL Nordic11	T2DM with >1 yr data history in the database before the index date (healthcare records from Denmark, Norway, Sweden); 25% with history of CVD	New user of SGLT2‐Is (different definitions among countries) [22830a]	New user of any other oral or injectable glucose‐lowering medication	CVM, MACEc, HHF, ACM, atrial fibrillation	CVM: 0.53 (0.40–0.71) MACEc: 0.78 (0.69–0.87) HHF: 0.70 (0.61–0.81) ACM: 0.51 (0.45–0.58)	Data confirmed in the sub‐study comparing dapagliflozin with DPP4‐Is12 Some variability in subgroup analyses, but reduced risk of MACE only in patients with CV disease at baseline Neutral association for CVM and MACE in aged <65 Non‐significant reduced risk in Norwegian cohort	Propensity score matching with several variables Potential immortal time bias18, 19, 20, 21 Median follow‐up 0.9 yr
CVD‐REAL 213	T2DM with >1 yr data history in the database before the index date (healthcare records from 6 non‐EU countries); 27% with history of CVD	New user of SGLT2‐Is (as initial or add‐on therapy) [235 064 patientsa]	New user of any other oral or injectable glucose‐lowering medication	ACM, HHF, MACE (ACM or HHF, MI, and stroke), MI, stroke	ACM: 0.51 (0.37–0.70) HHF: 0.64 (0.50–0.82) MACE: 0.60 (0.47–0.76)	Neutral association for MI in all countries (except Korea) No differences according to the CV risk at baseline Consistency in sensitivity analyses, with ACM/HHF/MACE attenuated but statistically significant in first new user design No meaningful interactions in subgroup analyses	Propensity score matching with several variables Potential immortal time bias accounted for in sensitivity analyses (first new user design) Median follow‐up 1.1 yr
OBSERVE‐4D24	T2DM (healthcare records from 4 US administrative claims databases); approximately 30% with CVD	New user of canagliflozin (142 800 patients) or other SGLT2‐Is (110 897 patients)	New user of non SGLT2‐Is (two cohorts), other SGLT2‐Is (three cohorts)	HHF, BKA	HHF: 0.82 (0.75–0.89) [intention‐to‐treat, canagliflozin vs. select non‐SGLT2‐Is] BKA: 1.01 (0.81–1.25) [intention‐to‐treat, canagliflozin vs. select non‐SGLT2‐Is]	No differences when comparing canagliflozin with other SGLT2‐Is Incidence of HHF/BKA in patients with established CV disease was approximately 2‐fold higher compared to the overall cohorts (and new users of canagliflozin had lower baseline prevalence of renal impairment/urinary tract disease Consistency in sensitivity analyses (different prior exposure assumptions, time‐at‐risk windows, event types, propensity score adjustment strategies) and sub‐analysis in patients with established CV disease	Full access to source‐specific estimates through interactive web‐based application Propensity score matching with several variables Immortal time bias cannot be excluded Median follow‐up 1.5 yr (intention‐to‐treat cohort, highest value among databases)

ACM, all‐cause mortality; BKA, atraumatic below‐knee lower extremity amputation; CV, cardiovascular; CVD, cardiovascular disease; CVM, cardiovascular mortality; DPP4‐I, dipeptidyl peptidase‐4 inhibitor; GLP‐1RA, glucagon‐like peptide‐1 receptor agonist; GPs, general practitioners; HF, heart failure; HHF, hospitalization for heart failure; MACE, major adverse cardiovascular events; MI, myocardial infarction; TIA, transient ischemic attack; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus; IRR, incidence rate ratio.

^aIn propensity matched analyses.

^bComposite of HF and death.

^cCVM, main diagnosis of MI, main diagnosis of ischaemic or haemorrhagic stroke.