Confidential: for Review Only Use of Sodium-Glucose Co-Transporter 2 Inhibitors and Risk of Serious Renal Events: Scandinavian Cohort Study

BMJ

Confidential: For Review Only Use of sodium-glucose co-transporter 2 inhibitors and risk of serious renal events: Scandinavian cohort study

Journal: BMJ

Manuscript ID BMJ-2019-053706

Article Type: Research

BMJ Journal: BMJ

Date Submitted by the 21-Nov-2019 Author:

Complete List of Authors: Pasternak, Björn; Karolinska Institutet Department of Medicine Solna, Clinical Epidemiology Unit Wintzell, Viktor; Karolinska Institutet Department of Medicine Solna, Clinical Epidemiology Division Melbye, Mads; Dept of Epidemiology Research Eliasson, Björn; University of Gothenburg, Department of Medicine Svensson, Ann-Marie; University of Gothenburg Franzén, Stefan; Centre of Registers Västra Götaland Gudbjörnsdottir, Soffia; University of Gothenburg, Department of Medicine Hveem, Kristian; Norwegian University of Science and Technology, HUNT Research Centre, Department of Public Health and General Practice Jonasson, Christian; Norwegian University of Science and Technology, Faculty of Medicine and Health Science Svanström, Henrik; Statens Serum Institut, Department of Epidemiology Research Ueda, Peter; Karolinska Institutet, Clinical Epidemiology Division, Department of Medicine, Solna

Keywords: SGLT2 inhibitors, Chronic kidney disease, Renal failure, Type 2 diabetes

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1 2 3 4 Use of sodium-glucose co-transporter 2 inhibitors and risk of 5 6 7 serious renal events: Scandinavian cohort study 8 9 10 11 Björn Pasternak, MD, PhD; Viktor Wintzell, MSc; Mads Melbye, MD, DrMedSci; Björn 12 Confidential: For Review Only 13 14 Eliasson, MD, PhD; Ann-Marie Svensson, PhD; Stefan Franzén, PhD; Soffia 15 16 Gudbjörnsdottir, MD, PhD; Kristian Hveem, MD, PhD; Christian Jonasson, PhD; Henrik 17 18 19 Svanström, PhD; Peter Ueda, MD, PhD. 20 21 22 23 24 Clinical Epidemiology Division, Department of Medicine, Solna, Karolinska Institutet, 25 26 Stockholm, Sweden (BP, VW, HS, PU) 27 28 29 Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark 30 31 (HS, MM, BP) 32 33 Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark 34 35 36 (MM) 37 38 Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA 39 40 (MM) 41 42 43 Department of Molecular and Clinical Medicine, Institute of Medicine, University of 44 45 Gothenburg, Gothenburg, Sweden (BE, AMS, SG) 46 47 The Swedish National Diabetes Register, Västra Götalandsregionen, Gothenburg, 48 49 50 Sweden (AMS, SF, SG) 51 52 Health Metrics, Department of Public Health and Community Medicine, Sahlgrenska 53 54 Academy, University of Gothenburg, Gothenburg, Sweden (SF) 55 56 57 K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, 58 59 Faculty of Medicine and Health Science, NTNU—Norwegian University of Science and 60

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1 2 3 Technology, Trondheim, Norway (KH, CJ) 4 5 6 HUNT Research Center, Faculty of Medicine, NTNU—Norwegian University of Science 7 8 and Technology, Levanger, Norway (KH, CJ) 9 10 Division of Health Data and Digitalization, The Norwegian Institute of Public Health, 11 12 Confidential: For Review Only 13 Oslo, Norway (CJ) 14 15 16 17 Word count: 3025 18 19 20 Word count abstract: 328 21 22 Tables/figures: 2 Tables and 3 Figures. 23 24 Supplementary Material: additional methods, 13 supplementary tables and 3 25 26 27 supplementary figures. 28 29 30 31 Correspondence: Peter Ueda, MD, PhD. Clinical Epidemiology Division, Department of 32 33 34 Medicine, Solna, Eugeniahemmet, T2, Karolinska University Hospital, 17176, Stockholm, 35 36 Sweden. Email: [email protected] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Abstract 4 5 6 Objective 7 8 9 To assess the association between use of SGLT2 inhibitors and risk of serious renal 10 11 12 events inConfidential: data from routine clinical practice. For Review Only 13 14 15 Design 16 17 18 Cohort study using an active-comparator new-user design and nationwide register data. 19 20 21 Settings 22 23 24 Sweden, Denmark and Norway, 2013-2018. 25 26 27 Participants 28 29 Cohort of 29887 new users of SGLT2 inhibitors (dapagliflozin 66.1%; empagliflozin 30 31 32.6%; canagliflozin 1.3%) and 29887 new users of an active comparator, dipeptidyl 32 33 34 peptidase-4 (DPP4) inhibitors, matched 1:1 based on a propensity score with 57 35 36 variables. Mean (SD) follow-up time was 1.7 (1.0) years. 37 38 39 Exposures 40 41 42 SGLT2 inhibitors vs. DPP4 inhibitors, defined by filled prescriptions and analyzed 43 44 intention-to-treat. 45 46 47 48 Main outcome and measures 49 50 51 The main outcome was serious renal events, a composite including renal replacement 52 53 therapy, death from renal causes and hospitalization for renal events. Secondary 54 55 outcomes were the individual components of the main outcome. 56 57 58 Results 59 60

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1 2 3 Mean (SD) age of the study population was 61.3 (10.5) years, 19% had cardiovascular 4 5 6 disease and 3% had chronic kidney disease. Use of SGLT2 inhibitors, as compared with 7 8 DPP4 inhibitors, was associated with a reduced risk of serious renal events (2.6 events 9 10 per 1000 person-years vs. 6.2 events per 1000 person-years; HR 0.42, 95% CI 0.34-0.53; 11 12 Confidential: For Review Only 13 absolute difference -3.6 [-4.4 to -2.8] events per 1000 person-years). In secondary 14 15 outcome analyses, the HR for use of SGLT2 inhibitors vs. DPP4 inhibitors was 0.32 16 17 (0.22-0.47) for renal replacement therapy, 0.41 (0.32-0.52) for hospitalization for renal 18 19 20 events and 0.77 (0.26-2.23) for death from renal causes. In sensitivity analyses in each 21 22 of the Swedish and Danish parts of the cohort, the model was further adjusted for 23 24 glycated hemoglobin, estimated glomerular filtration rate (Sweden and Denmark), 25 26 27 blood pressure, body mass index and smoking (Sweden only); in these analyses the HR 28 29 moved from 0.41 (0.26-0.66) to 0.50 (0.31-0.81) in Sweden and from 0.42 (0.32-0.56) to 30 31 0.55 (0.41-0.74) in Denmark. 32 33 34 Conclusions 35 36 37 In this analysis using nationwide data from three countries, use of SGLT2 inhibitors, as 38 39 compared with DPP4 inhibitors, was associated with a significantly reduced risk of 40 41 42 serious renal events. 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Type 2 diabetes is the leading cause of kidney failure.1 While treatment with 4 5 6 angiotensin-converting enzyme inhibitors and angiotensin receptor blockers reduces 7 8 risk of adverse renal outcomes among patients with diabetes,2–4 the risk remains high 9 10 and there is a large need for new treatments that lower risk of kidney failure. Sodium- 11 12 Confidential: For Review Only 13 glucose co-transporter 2 (SGLT2) inhibitors are a class of glucose-lowering drugs which 14 15 also reduce blood pressure, body weight and albuminuria. Large clinical trials have 16 17 shown that these drugs have beneficial effects on renal outcomes. In the EMPAREG 18 19 20 OUTCOME trial, patients who received empagliflozin vs. placebo experienced lower 21 22 rates of the composite renal outcome, including progression to macroalbuminuria, 23 24 doubling of the serum creatinine level, initiation of renal-replacement therapy, or death 25 26 5 27 from renal disease (HR 0.61 [0.53-0.70]). Similarly, rates of composite renal outcomes 28 29 were reduced among patients receiving canagliflozin in the CANVAS Program (HR 0.58 30 31 (0.50–0.67))6 and the CREDENCE trial (HR 0.66 [0.53-0.81]),7 and among those 32 33 34 receiving dapagliflozin in the DECLARE TIMI-58 trial (HR 0.53 [0.43-0.66])8. 35 36 37 38 While the data from clinical trials provide evidence for the renoprotective effects of 39 40 41 SGLT2 inhibitors, uncertainty remains regarding the impact of these drugs on renal 42 43 outcomes in routine clinical practice. The four large clinical trials assessing renal 44 45 46 outcomes with SGLT2 inhibitors have included only patients at high cardiovascular 47 48 risk5,6,8 or with established nephropathy.7 Patients receiving SGLT2 inhibitors in clinical 49 50 practice tend to be more heterogenous9 and whether the findings of the clinical trials 51 52 53 are generalizable to broad, unselected groups of patients is unknown. 54 55 56 57 Using nationwide data from patients seen in routine clinical practice in Sweden, 58 59 60 Denmark and Norway, we performed a register-based cohort study to assess whether

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1 2 3 use of SGLT2 inhibitors, as compared with an active comparator (dipeptidyl peptidase-4 4 5 6 [DPP4] inhibitors), is associated with a reduced risk of serious renal events. 7 8 9 10 Methods 11 12 Confidential: For Review Only 13 Data sources 14 15 We used data from nationwide health and administrative registers in Sweden (April, 16 17 2013, through December, 2016), Denmark (April, 2013, through December, 2018) and 18 19 20 Norway (April, 2013, through December, 2016). Data sources included population 21 22 registers and Statistics Denmark/Statistics Sweden (vital status, demographics, 23 24 socioeconomic variables), patient registers (comorbidities, outcomes), prescription 25 26 27 registers (study drugs, co-medications), cause of death registers (outcomes; data from 28 29 this register in Denmark were available through 2017), the Swedish National Diabetes 30 31 Register (glycated hemoglobin level, blood pressure, albuminuria, estimated glomerular 32 33 34 filtration rate [eGFR], body mass index and smoking) and the Danish Register of 35 36 Laboratory Results for Research (glycated haemoglobin, albuminuria and eGFR); details 37 38 are provided in the Supplementary Material. 39 40 41 42 43 Active-comparator new-user design 44 45 46 We used an active-comparator new-user design10 in order to mitigate the risk of 47 48 49 confounding by indication, disease severity and unmeasured clinical characteristics. The 50 51 ideal active comparator would be a drug that is used in similar clinical situations as 52 53 SGLT2 inhibitors and has no expected associations with the investigated outcomes. We 54 55 56 used DPP4 inhibitors as the active comparator as clinical guidelines used during the 57 58 study period recommended both SGLT2 inhibitors and DPP4 inhibitors as second or 59 60 third-line glucose lowering therapies,11 and data from clinical trials in patients at high

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1 2 3 cardiovascular risk indicate that DPP4 inhibitors have no or limited effects on renal 4 5 12 6 outcomes. 7 8 9 10 Study population 11 12 Confidential: For Review Only 13 All patients in the three countries, aged 35-84 years, who filled their first prescription 14 15 for either a SGLT2 inhibitor or a DPP4 inhibitor during the study period (anatomic 16 17 therapeutic chemical [ATC] codes for study drugs shown in supplementary table 1) 18 19 20 were included. The date of filling the first prescription constituted cohort entry. 21 22 Exclusion criteria were previously filled prescriptions for any of the study drugs, no 23 24 specialist care contact or prescription drug in the past year, history of dialysis or renal 25 26 27 transplantation, end-stage illness, drug misuse, severe pancreatic disorders, and 28 29 hospitalization for any reason within 30 days before cohort entry (supplementary table 30 31 2). 32 33 34 35 36 Using logistic regression, we estimated the probability of starting a SGLT2 inhibitor vs. a 37 38 DPP4 inhibitor, conditional on the status of 57 covariates at cohort entry; the score 39 40 41 included variables on sociodemographic characteristics, co-morbidities, co-medications, 42 43 and health care utilization (supplementary table 3). Missing categories were used to 44 45 13 46 handle missing data on place of birth (<1%), civil status (<1%), and education (<3%); 47 48 none of the other variables had missing data. We estimated propensity scores in each 49 50 country separately. Due to variations in data availability, a few variables included in the 51 52 53 propensity score in Norway differed slightly as compared with those in Sweden and 54 55 Denmark (supplementary table 3). 56 57 58 59 60 We matched new users of SGLT2 inhibitors and DPP4 inhibitors (1:1 ratio) using the

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1 2 3 nearest neighbour algorithm (calliper width 0.2 of the SD of the logit propensity 4 5 14,15 6 score) with sex, age (5-year intervals) and a previous diagnosis of chronic kidney 7 8 disease (supplementary table 4) as additional matching criteria. Covariates were 9 10 considered as well balanced if the standardized difference was below 10%. We 11 12 Confidential: For Review Only 13 performed the analyses in a pooled dataset of the matched cohorts of the three 14 15 countries. 16 17 18 19 20 Outcomes 21 22 The primary outcome, serious renal events, was a composite outcome of renal 23 24 replacement therapy (dialysis or renal transplantation), death from renal causes and 25 26 27 hospitalization for renal events as captured in the patient registers and the cause of 28 29 death registers. Secondary outcomes were each component of the primary outcome. 30 31 Hospitalization for renal events was based on events consistent with serious renal 32 33 34 disease, including diabetic nephropathy, chronic kidney disease and acute kidney 35 36 injury; we considered this outcome as a renal analogue to the outcome hospitalization 37 38 for heart failure in cardiology such that it was regarded as an indicator of serious 39 40 41 worsening of renal status. International Classification of Diseases (version 10) codes 42 43 and procedure codes used to define the outcomes are shown in supplementary table 5. 44 45 46 47 48 Statistical analyses 49 50 Patients were followed from cohort entry until outcome event, death, emigration, 3 51 52 53 years of follow-up or end of the study period. Patients were censored at the time of the 54 55 first outcome event in the analyses of the primary outcome; in analyses of secondary 56 57 outcomes, patients were censored at the first occurrence of the outcome analyzed, 58 59 60 independent of other outcomes. We used an intention-to-treat exposure definition in

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1 2 3 which patients were defined as exposed to the study drug from cohort entry throughout 4 5 6 follow-up. Cox proportional-hazards regression with time since cohort entry as the time 7 8 scale was used to estimate HRs. The assumption of proportional hazards was examined 9 10 by a Wald test of the interaction between treatment status and time. HRs with 95% CI 11 12 Confidential: For Review Only 13 that did not overlap 1 were considered statistically significant. The absolute rate 14 15 difference was estimated assuming a Poisson distribution. 16 17 18 19 20 For the primary outcome, we conducted subgroup analyses by sex, age group, history of 21 22 major cardiovascular disease (supplementary table 6) and history of chronic kidney 23 24 disease. Effect modification by subgroup status was assessed using an interaction term 25 26 27 between treatment status and subgroup; in these analyses a p-value of <0.05 was 28 29 considered statistically significant. We also analyzed the primary outcome by country to 30 31 assess consistency across data sources. 32 33 34 35 36 In an additional analysis, we used an as-treated exposure definition which was based on 37 38 the estimated duration of the filled prescriptions (supplementary table 1), allowing for a 39 40 41 90-day grace period to account for prescription overlap, irregular drug use and events 42 43 that occurred shortly after treatment cessation. In these analyses, patients were 44 45 46 censored at treatment cessation and cross-over to the other study drug (i.e. initiation of 47 48 DPP4 inhibitors among users of SGLT2 inhibitors and vice versa). 49 50 51 52 53 In a prespecified sensitivity analysis, performed in each of the propensity score- 54 55 matched cohorts in Sweden and Denmark, we adjusted the Cox models for additional 56 57 variables. These variables included glycated hemoglobin level, blood pressure, 58 59 60 albuminuria, eGFR, body mass index, and smoking in Sweden and glycated hemoglobin

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1 2 3 level, albuminuria and eGFR in Denmark (supplementary table 7). Due to the proportion 4 5 6 of patients with missing data on these variables (supplementary table 7), multiple 7 8 imputation (fully conditional specification imputation) was used to handle missing 9 10 data16 and analyses were performed using 10 imputed datasets. 11 12 Confidential: For Review Only 13 14 15 Patient involvement 16 17 No patients were involved in setting the research question, nor in the design, conduct, 18 19 20 or interpretation of the study. The study is based on anonymized nationwide register 21 22 data and there is no planned dissemination of results directly to study participants. 23 24 25 26 27 Results 28 29 Study population 30 31 38273 new users of SGLT2 inhibitors and 107854 new users of DPP4 inhibitors fulfilled 32 33 34 study eligibility criteria (Figure 1). Supplementary table 8 shows baseline 35 36 characteristics of the cohort before matching. Following 1:1 matching, the cohort 37 38 included 29887 new users of SGLT2 inhibitors and 29887 new users of DPP4 inhibitors. 39 40 41 Covariates in the two groups were well balanced (Table 1). Mean (SD) age was 61.3 42 43 (10.5) years, 39.3% were female, 18.6% had a history of major cardiovascular disease, 44 45 46 and 3.3% had a history of chronic kidney disease. Total follow-up time in the primary 47 48 analysis was 42632 years (mean [SD], 1.4 [1.0] years) among SGLT2 inhibitor users and 49 50 58473 years (mean [SD], 2.0 [1.0] years) among DPP4 inhibitor users. Of the total 51 52 53 follow-up for SGLT2 inhibitors, the proportion of follow-up time by drug initiated at 54 55 cohort entry was 66.1% for dapagliflozin, 32.6% for empagliflozin and 1.3% for 56 57 canagliflozin. For DPP4 inhibitors, these proportions were 64.8% for sitagliptin, 20.0% 58 59 60 for vildagliptin, 10.2% for linagliptin, 2.8% for saxagliptin, and 2.2% for alogliptin.

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1 2 3 (supplementary table 9) 4 5 6 7 8 Primary and secondary outcomes 9 10 Figure 2 shows the cumulative incidence of the primary composite outcome, serious 11 12 Confidential: For Review Only 13 renal events. Use of SGLT2 inhibitors, as compared with DPP4 inhibitors, was associated 14 15 with a significantly lower risk of serious renal events (incidence rate 2.6 events per 16 17 1000 person-years vs. 6.2 events per 1000 person-years; HR 0.42 [95% CI 0.34-0.53]) 18 19 20 (Table 2). When the proportional hazards assumption was assessed, we observed a 21 22 significant interaction between year of follow-up and exposure to SGLT2 inhibitors 23 24 (p=0.009; Schoenfeld residuals are shown in supplementary figure 1). The association 25 26 27 of SGLT2 inhibitors with lower risk of serious renal events was largely driven by the 28 29 first 2 years of follow-up (HR for year 1 after cohort entry, 0.34 [0.25-0.47]; year 2, 0.43 30 31 [0.30-0.64]; year 3, 0.74 [0.46-1.17]). 32 33 34 35 36 In the analyses of the secondary outcomes, use of SGLT2 inhibitors, as compared with 37 38 DPP4 inhibitors was associated with a significantly lower risk of renal replacement 39 40 41 therapy (incidence rate 0.8 vs 2.5 per 1000 person-years; HR 0.32 [95% CI, 0.22-0.47]) 42 43 and hospitalization for renal events (incidence rate 2.0 vs 4.9 per 1000 person-years; 44 45 46 HR 0.41 [95% CI, 0.32-0.52]) but not death from renal causes (incidence rate 0.2 vs 0.2 47 48 per 1000 person-years; HR 0.77 [95% CI, 0.26-2.23]) (Table 2). 49 50 51 52 53 Subgroup and additional analyses 54 55 Subgroup analyses are shown in Figure 3. No significant interaction between use of 56 57 SGLT2 inhibitors and the primary outcome was observed in analyses by sex and age 58 59 60 group. HRs were lower for patients with a history of cardiovascular disease vs. those

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1 2 3 without (HR 0.30 [95% CI 0.21-0.44] vs 0.52 [95% CI 0.40-0.67]; p for interaction 4 5 6 0.022) and for those with a history of chronic kidney disease vs. those without (HR 0.18 7 8 [95% CI 0.10-0.31] vs. 0.52 [95% CI 0.41-0.65]; p for interaction <0.001). HRs were 9 10 consistent across countries (supplementary table 10). 11 12 Confidential: For Review Only 13 14 15 In the additional analyses using an as-treated exposure definition, the total follow-up 16 17 time was 21557 years (mean [SD], 0.7 [0.6] years) for users of SGLT2 inhibitors and 18 19 20 27314 years (mean [SD], 0.9 [0.8] years) for users of DPP4 inhibitors. In this analysis, 21 22 the HR for the association between use of SGLT2 inhibitors and the primary outcome 23 24 0.30 (95% CI 0.22-0.42). (supplementary figure 2 and supplementary table 11) The 25 26 27 assumption of proportional hazards was met (p=0.687) (supplementary figure 3). 28 29 30 31 Sensitivity analysis 32 33 34 The distribution of glycated hemoglobin, blood pressure, albuminuria, eGFR, body mass 35 36 index, and smoking in the Swedish part of the cohort is shown in supplementary table 37 38 12 and the distribution of glycated hemoglobin, albuminuria and eGFR in the Danish 39 40 41 part of the cohort is shown in supplementary table 13. Additional adjustment for these 42 43 variables resulted in slightly attenuated associations of SGLT2 inhibitors with the 44 45 46 primary outcome, as compared with the analyses without such adjustment (Sweden: HR 47 48 0.50 [95% CI 0.31-0.81] and 0.41 [95% CI 0.26-0.66], respectively; Denmark: HR 0.55 49 50 [95% CI 0.41-0.74] and 0.42 [95% CI 0.32-0.56], respectively) 51 52 53 54 55 Discussion 56 57 Main findings 58 59 60 In this cohort study using nationwide registers in three countries, use of SGLT2

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1 2 3 inhibitors was associated with a lower risk of the main composite outcome of serious 4 5 6 renal events (consisting of renal replacement therapy, renal death and hospitalization 7 8 for renal events) in analyses using DPP4 inhibitors as an active comparator. Use of 9 10 SGLT2 inhibitors was associated with a significantly lower risk of incident renal 11 12 Confidential: For Review Only 13 replacement therapy as well as hospitalization for renal events but not with death due 14 15 to renal causes. 16 17 18 19 20 21 Interpretation and comparison with previous studies 22 23 24 Large clinical trials have shown that SGLT2 inhibitors can reduce the risk of advanced 25 26 renal outcomes, including renal replacement therapy, and protect kidney function 27 28 5–8,17 29 among patients at high risk of cardiovascular disease or established nephropathy. 30 31 Our study adds to the knowledge about SGLT2 inhibitors and renal outcomes by using 32 33 nationwide registers from three countries to include a large number of patients seen in 34 35 36 routine clinical practice. Importantly, of the patients included in our study, 81% and 37 38 97% had no diagnosis of cardiovascular disease and chronic kidney disease, 39 40 respectively. While the absolute risk reduction associated with SGLT2 inhibitors was 41 42 43 larger in patients with cardiovascular disease or chronic kidney disease, the protective 44 45 association of SGLT2 inhibitors was also observed in patients without such history. The 46 47 48 findings from this observational study, which should be considered as complementary 49 50 to the data from clinical trials, thus provide further support for the use of SGLT2 51 52 inhibitors across a broad range of patients with type 2 diabetes. 53 54 55 56 57 58 59 60

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1 2 3 While the primary outcome definition used in our study did not directly correspond to 4 5 6 the composite renal outcomes used in clinical trials (which were largely driven by 7 8 albuminuria and changes in eGFR), the secondary outcome of renal replacement 9 10 therapy can be compared across studies. For this outcome, we observed a HR of 0.32 11 12 Confidential: For Review Only 13 (95% CI 0.22-0.47) for use of SGLT2 inhibitors vs. DPP4 inhibitors, which is broadly in 14 15 line with the HR vs. placebo for renal replacement therapy in the EMPAREG OUTCOME 16 17 trial of empagliflozin (HR 0.45 [0.21-0.97]),5 and for end-stage kidney disease in the 18 19 8 20 DECLARE-TIMI 58 trial of dapagliflozin (HR 0.31 [0.13-0.79]), while the HR for end- 21 22 stage kidney disease in the CREDENCE trial of canagliflozin was slightly higher (HR 0.68 23 24 [0.54-0.86]).7 Dapagliflozin (66.1% of the total follow-up time among users of SGLT2 25 26 27 inhibitors) and empagliflozin (32.6%) were the most common SGLT2 inhibitors in our 28 29 study population while use of canagliflozin was rare (1.3%). 30 31 32 33 34 35 We attempted to limit the risk of confounding by using a propensity score including a 36 37 wide range of patient characteristics. Moreover, we used a new-user design excluding 38 39 40 patients with history of any of the study drugs at cohort entry; this design removed the 41 42 possibility of immortal time bias, which has been highlighted in other observational 43 44 18 45 analyses of SGLT2 inhibitors. Another strength of the study was the use of data on 46 47 glycated hemoglobin level, albuminuria and eGFR (Sweden and Denmark) as well as 48 49 blood pressure, body mass index and smoking (Sweden) in the Swedish and Danish 50 51 52 parts of the cohort (78.5% of the overall cohort). When the outcome models were 53 54 further adjusted for these variables in sensitivity analyses, the point estimate for the 55 56 primary outcome moved from 0.41 to 0.50 in Sweden and from 0.42 to 0.55 in Denmark, 57 58 59 60

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1 2 3 indicating that the primary analyses may present slightly overestimated associations 4 5 6 due to confounding by these variables. 7 8 9 10 11 We used DPP4 inhibitors as the active comparator drug class in order to mitigate the 12 Confidential: For Review Only 13 risk of confounding by indication, disease severity and unmeasured clinical 14 15 16 characteristics. During the study period, both DPP4 inhibitors and SGLT2 inhibitors 17 18 were recommended as 2nd or 3rd line glucose-lowering medications and the two drug 19 20 classes were thus used in similar clinical situations and at a similar stage of disease.11 In 21 22 23 accordance with their neutral effect on cardiovascular outcomes and mortality, data 24 25 from clinical trials in patients at high cardiovascular risk indicate that DPP4 inhibitors 26 27 have no or limited effects on renal outcomes.12 The risk of composite renal outcomes 28 29 30 was similar among those receiving active treatment vs. placebo in the SAVOR TIMI 53 31 32 trial of saxagliptin19 and the CARMELINA trial of linagliptin,20 although some potential 33 34 benefit was indicated in exploratory analyses of albuminuria outcomes.20,21 In the 35 36 37 EXAMINE trial, the risk of dialysis and changes in eGFR were similar in those receiving 38 39 alogliptin vs. placebo.22 In the TECOS trial of sitagliptin, which comprised 64.8% of the 40 41 42 DPP inhibitor use in our study, the decline in eGFR was clinically similar in those 43 44 receiving active treatment vs. placebo.23 If DPP4 inhibitors have a protective effect on 45 46 renal outcomes, the associations observed in our study may represent an 47 48 49 underestimation of the effects of SGLT2 inhibitors. However, this would not change the 50 51 overall interpretation of our analyses and the study would still present a head-to-head 52 53 comparative effectiveness analysis of SGLT2 inhibitors and DPP-4 inhibitors. 54 55 56 57 58 Limitations 59 60 Our study has limitations. First, we analysed SGLT2 inhibitors as a drug class.

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1 2 3 Dapagliflozin and empagliflozin comprised most of the total follow-up time among users 4 5 6 of SGLT2 inhibitors while use of canagliflozin was rare. Head-to-head analyses of renal 7 8 outcomes with individual SGLT2 inhibitors is an important subject for further 9 10 examination. Second, the exposure definition was based on filled prescriptions; low 11 12 Confidential: For Review Only 13 adherence may bias the results towards the null. Third, although high sensitivity and 14 15 positive predictive values have been observed for procedure codes and diagnoses 16 17 recorded in Scandinavian health registers,24,25 validation studies of the specific codes 18 19 24,25 20 used for the outcome definition in our study have not been conducted. It is possible 21 22 that outcome misclassification have introduced bias in our analyses; however, such 23 24 misclassification is not likely to be different in patients receiving SGLT2 inhibitors vs. 25 26 27 DPP4 inhibitors. Finally, although we used an active-comparator new-user design and 28 29 estimated a propensity score to control for a large number of patient characteristics, 30 31 this was an observational study and the risk of unmeasured confounding cannot be 32 33 34 ruled out. 35 36 37 38 39 Conclusions 40 41 42 In conclusion, in this analysis of nationwide registers from three countries, use of SGLT2 43 44 45 inhibitors, as compared with DPP4 inhibitors, was associated with a reduced risk of 46 47 serious renal events. Complementing data from clinical trials, this study provides 48 49 further support for the use of SGLT2 inhibitors in a broad range of patients with type 2 50 51 52 diabetes. 53 54 55 56 57 58 59 60

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1 2 3 Summary box 4 5 6 What is already known on this topic 7 8 9  Clinical trials have shown that sodium-glucose co-transporter 2 (SGLT2) 10 11 12 inhibitorsConfidential: protect renal function For among Reviewpatients with type Only 2 diabetes and high 13 14 cardiovascular risk or established nephropathy. 15 16 17  The impact of SGLT2 inhibitors on serious renal events in broader unselected 18 19 groups of patients in routine clinical practice remains uncertain. 20 21 22 23 What this study adds 24 25 26  In this cohort study using nationwide register data from Sweden, Denmark and 27 28 Norway, use of SGLT2 inhibitors, as compared with use of dipeptidyl peptidase 4 29 30 (DPP4) inhibitors, was associated with a 58% lower risk of a composite outcome 31 32 33 of serious renal events, including renal replacement therapy, death from renal 34 35 causes and hospitalization for renal events. 36 37 38  Complementing the results of randomized trials, these data suggest that SGLT2 39 40 inhibitors may lower the risk of serious renal events in routine clinical practice. 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 ACKNOWLEDGEMENTS 4 5 6 Author Contributions 7 8 9 Drs Pasternak and Ueda had full access to all the data in the study and take 10 11 responsibility for the integrity of the data and the accuracy of the data analysis. 12 Confidential: For Review Only 13 14 Concept and design: Pasternak, Wintzell, Svanström, Ueda. 15 16 Acquisition, analysis, or interpretation of data: All authors. 17 18 19 Drafting of the manuscript: Pasternak, Ueda. 20 21 Critical revision of the manuscript for important intellectual content: All authors. 22 23 Statistical analysis: Wintzell 24 25 26 Obtained funding: Pasternak, Ueda. 27 28 Study supervision: Pasternak. 29 30 31 32 33 Funding/Support 34 35 Dr Pasternak was supported by an investigator grant from the Strategic Research Area 36 37 Epidemiology program at Karolinska Institutet. Dr Ueda was supported by grants from 38 39 40 the Swedish Heart-Lung Foundation and the Swedish Society for Medical Research. The 41 42 study was conducted with research grant support from the Swedish Cancer Society, the 43 44 45 Nordic Cancer Union, and the Novo Nordisk Foundation. 46 47 48 49 Role of the Funder/Sponsor 50 51 52 The funding sources had no role in the design and conduct of the study; collection, 53 54 management, analysis, and interpretation of the data; preparation, review, or approval 55 56 of the manuscript; and decision to submit the manuscript for publication. 57 58 59 60

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1 2 3 Conflict of Interest Disclosures 4 5 6 All authors have completed the Unified Competing Interest form at 7 8 9 www.icmje.org/coi_disclosure.pdf (available on request from the corresponding 10 11 author) and have the following declarations. Dr Jonasson reports personal fees from 12 Confidential: For Review Only 13 Pfizer and Bayer outside the submitted work. Dr Eliasson reports personal fees from 14 15 16 Amgen, AstraZeneca, Boerhringer Ingelheim, Eli Lilly, Merck Sharp & Dohme, 17 18 Mundipharma, Navamedic, Novo Nordisk, and RLS Global outside the submitted work, 19 20 and grants from Sanofi outside the submitted work. Dr Gudbjörnsdottir reports lecture 21 22 23 fees and research grants from AstraZeneca, Boerhringer Ingelheim, Eli Lilly, Merck 24 25 Sharp & Dohme, Novo Nordisk, and Sanofi outside of the submitted work. Dr Svanström 26 27 reports consulting fees from Celgene and employment at IQVIA outside the submitted 28 29 30 work. The other authors did not have any potential conflicts to report. 31 32 33 34 35 36 Ethical approval 37 38 The study was approved by the Regional Ethics Committee in Stockholm, Sweden, and 39 40 the Regional Committee for Medical and Health Research Ethics (REC Central), Norway. 41 42 43 In Denmark, ethics approval is not required for register-based research. 44 45 46 47 48 49 Data sharing 50 51 No additional data available. 52 53 54 The Corresponding Author has the right to grant on behalf of all authors and does grant 55 56 57 on behalf of all authors, an exclusive licence (or non exclusive for government 58 59 employees) on a worldwide basis to the BMJ Publishing Group Ltd to permit this article 60

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1 2 3 (if accepted) to be published in BMJ editions and any other BMJPGL products and 4 5 6 sublicences such use and exploit all subsidiary rights, as set out in our licence. 7 8 9 10 References 11 12 Confidential: For Review Only 13 14 15 1. Thomas MC, Cooper ME, Zimmet P. Changing epidemiology of type 2 diabetes 16 17 mellitus and associated chronic kidney disease. Nat Rev Nephrol. 2016;12(2):73- 18 19 20 81. 21 22 2. Lewis EJ, Hunsicker LG, Bain RP, Rohde RD. The Effect of Angiotensin-Converting- 23 24 Enzyme Inhibition on Diabetic Nephropathy. N Engl J Med. 1993;329(20):1456- 25 26 27 1462. 28 29 3. Lewis EJ, Hunsicker LG, Clarke WR, et al. Renoprotective Effect of the 30 31 Angiotensin-Receptor Antagonist Irbesartan in Patients with Nephropathy Due to 32 33 34 Type 2 Diabetes. N Engl J Med. 2001;345(12):851-860. 35 36 4. Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of Losartan on Renal and 37 38 Cardiovascular Outcomes in Patients with Type 2 Diabetes and Nephropathy. N 39 40 41 Engl J Med. 2001;345(12):861-869. 42 43 5. Wanner C, Inzucchi SE, Lachin JM, et al. Empagliflozin and Progression of Kidney 44 45 46 Disease in Type 2 Diabetes. N Engl J Med. 2016;375(4):323-334. 47 48 6. Perkovic V, de Zeeuw D, Mahaffey KW, et al. Canagliflozin and renal outcomes in 49 50 type 2 diabetes: results from the CANVAS Program randomised clinical trials. 51 52 53 Lancet Diabetes Endocrinol. 2018;6(9):691-704. 54 55 7. Perkovic V, Jardine MJ, Neal B, et al. Canagliflozin and renal outcomes in type 2 56 57 diabetes and nephropathy. N Engl J Med. 2019;380(24):2295-2306. 58 59 60 8. Mosenzon O, Wiviott SD, Cahn A, et al. Effects of dapagliflozin on development

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1 2 3 and progression of kidney disease in patients with type 2 diabetes: an analysis 4 5 6 from the DECLARE–TIMI 58 randomised trial. Lancet Diabetes Endocrinol. 7 8 2019;7(8):606-617. 9 10 9. Beekman-Hendriks WL, Thuresson M, Pignot M, et al. How Representative are the 11 12 Confidential: For Review Only 13 Patients Included in the CV outcome Trials with SGLT2 Inhibitors of a General 14 15 Type 2 Diabetes Population? A Large European Observational study. Diabetes, 16 17 Obes Metab. 2018;1(7):1-7. 18 19 20 10. Lund JL, Richardson DB, Stürmer T. The Active Comparator, New User Study 21 22 Design in Pharmacoepidemiology: Historical Foundations and Contemporary 23 24 Application. Curr Epidemiol Reports. 2015;2(4):221-228. 25 26 27 11. Inzucchi SE, Bergenstal RM, Buse JB, et al. Management of Hyperglycemia in Type 28 29 2 Diabetes, 2015: A Patient-Centered Approach: Update to a Position Statement of 30 31 the American Diabetes Association and the European Association for the Study of 32 33 34 Diabetes. Diabetes Care. 2015;38(1):140-149. 35 36 12. Muskiet MHA, Wheeler DC, Heerspink HJL. New pharmacological strategies for 37 38 protecting kidney function in type 2 diabetes. Lancet Diabetes Endocrinol. 39 40 41 2018;8587(18):1-16. 42 43 13. D’Agostino RB, Rubin DB. Estimating and Using Propensity Scores with Partially 44 45 46 Missing Data. J Am Stat Assoc. 2000;95(451):749-759. 47 48 14. Austin PC. Some Methods of Propensity-Score Matching had Superior 49 50 Performance to Others: Results of an Empirical Investigation and Monte Carlo 51 52 53 simulations. Biometrical J. 2009;51(1):171-184. 54 55 15. Rassen JA, Shelat AA, Myers J, Glynn RJ, Rothman KJ, Schneeweiss S. One-to-many 56 57 propensity score matching in cohort studies. Pharmacoepidemiol Drug Saf. 58 59 60 2012;21(SUPPL.2):69-80.

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1 2 3 16. Harel O, Zhou X-H. Multiple imputation: review of theory, implementation and 4 5 6 software. Stat Med. 2007;26(16):3057-3077. 7 8 17. Neuen BL, Young T, Heerspink HJL, et al. SGLT2 inhibitors for the prevention of 9 10 kidney failure in patients with type 2 diabetes: a systematic review and meta- 11 12 Confidential: For Review Only 13 analysis. Lancet Diabetes Endocrinol. 2019;2(19):1-10. 14 15 18. Suissa S. Lower Risk of Death With SGLT2 Inhibitors in Observational Studies: 16 17 Real or Bias? Diabetes Care. 2018;41(1):6-10. 18 19 20 19. Scirica BM, Bhatt DL, Braunwald E, et al. Saxagliptin and Cardiovascular Outcomes 21 22 in Patients with Type 2 Diabetes Mellitus. N Engl J Med. 2013;369(14):1317-1326. 23 24 20. Rosenstock J, Perkovic V, Johansen OE, et al. Effect of Linagliptin vs Placebo on 25 26 27 Major Cardiovascular Events in Adults With Type 2 Diabetes and High 28 29 Cardiovascular and Renal Risk. JAMA. 2019;321(1):69-79. 30 31 21. Mosenzon O, Leibowitz G, Bhatt DL, et al. Effect of Saxagliptin on Renal Outcomes 32 33 34 in the SAVOR-TIMI 53 Trial. Diabetes Care. 2017;40(1):69-76. 35 36 22. White WB, Cannon CP, Heller SR, et al. Alogliptin after Acute Coronary Syndrome 37 38 in Patients with Type 2 Diabetes. N Engl J Med. 2013;369(14):1327-1335. 39 40 41 23. Cornel JH, Bakris GL, Stevens SR, et al. Effect of Sitagliptin on Kidney Function and 42 43 Respective Cardiovascular Outcomes in Type 2 Diabetes: Outcomes From TECOS. 44 45 46 Diabetes Care. 2016;39(12):2304-2310. 47 48 24. Schmidt M, Schmidt SAJ, Sandegaard JL, Ehrenstein V, Pedersen L, Sørensen HT. 49 50 The Danish National Patient Registry: a review of content, data quality, and 51 52 53 research potential. Clin Epidemiol. 2015;7:449. 54 55 25. Ludvigsson JF, Andersson E, Ekbom A, et al. External review and validation of the 56 57 Swedish national inpatient register. BMC Public Health. 2011;11(1):450. 58 59 60

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1 2 3 Figure 1 Flow chart of patient inclusion in the study cohort, Sweden, Denmark and 4 5 6 Norway. 7 8 9 10 Figure 2 Cumulative incidence of serious renal events in users of SGLT2 inhibitors and 11 12 Confidential: For Review Only 13 DPP4 inhibitors. 14 15 16 17 Figure 3 Subgroup analyses of serious renal events among users of SGLT2 inhibitors as 18 19 20 compared with users of DPP4 inhibitors. 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Table 1 Baseline characteristics of propensity score-matched cohort of SGLT2 inhibitor 4 5 6 users and DPP4 inhibitor users, Sweden, Denmark and Norway. Numbers are shown in 7 8 n (%) unless otherwise indicated. 9 10 11 Standardized 12 Confidential: For Review Only mean 13 SGLT2 inhibitors DPP4 inhibitors difference 14 -- (N=29887) (N=29887) (%) 15 a 16 Country 17 Sweden 9241 (30.9) 9241 (30.9) - 18 Denmark 14232 (47.6) 14232 (47.6) - 19 Norway 6414 (21.5) 6414 (21.5) - 20 21 Male 18129 (60.7) 18129 (60.7) - 22 Age, mean (SD) 61.3 (10.5) 61.3 (10.5) 0.4 23 Age, years 24 - 25 35-39 744 (2.5) 744 (2.5) 26 40-44 1447 (4.8) 1447 (4.8) - 27 45-49 2534 (8.5) 2534 (8.5) - 28 - 29 50-54 3787 (12.7) 3787 (12.7) 30 55-59 4551 (15.2) 4551 (15.2) - 31 60-64 4921 (16.5) 4921 (16.5) - 32 65-69 5166 (17.3) 5166 (17.3) - 33 - 34 70-74 4006 (13.4) 4006 (13.4) 35 75-79 1948 (6.5) 1948 (6.5) - 36 80-84 783 (2.6) 783 (2.6) - 37 38 Place of Birth 39 Scandinavia 25000 (83.6) 25082 (83.9) 0.7 40 Rest of Europe 1977 (6.6) 1951 (6.5) 0.4 41 Outside Europe 2866 (9.6) 2812 (9.4) 0.6 42 43 Missing 44 (0.1) 42 (0.1) 0.2 44 Civil status 45 Married/living with partner 17533 (58.7) 17608 (58.9) 0.5 46 47 Single 12248 (41.0) 12178 (40.7) 0.5 48 Missing 106 (0.4) 101 (0.3) 0.3 49 Educationb 50 Primary-/Secondary school, vocational training 18455 (78.6) 18556 (79.1) 1.1 51 52 Short tertiary education 1384 (5.9) 1414 (6.0) 0.5 53 Medium or long tertiary education 2975 (12.7) 2887 (12.3) 1.1 54 Missing 659 (2.8) 616 (2.6) 1.1 55 56 Medical history 57 Acute coronary syndrome 2145 (7.2) 2039 (6.8) 1.4 58 Other ischemic heart disease 4978 (16.7) 4729 (15.8) 2.3 59 60 Heart failure/cardiomyopathy 1682 (5.6) 1560 (5.2) 1.8

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1 2 3 Valve disorders 727 (2.4) 666 (2.2) 1.4 4 5 Stroke 1166 (3.9) 1160 (3.9) 0.1 6 Other cerebrovascular disease 1268 (4.2) 1230 (4.1) 0.6 7 Atrial fibrillation 2066 (6.9) 1939 (6.5) 1.7 8 9 Other arrythmia 1258 (4.2) 1137 (3.8) 2.1 10 Coronary revascularization 11 in the previous year 438 (1.5) 436 (1.5) 0.1 12 Other cardiacConfidential: surgery/invasive procedure For Review Only 13 in the previous year 152 (0.5) 126 (0.4) 1.3 14 Arterial disease 1872 (6.3) 1871 (6.3) <0.1 15 Chronic kidney disease 987 (3.3) 987 (3.3) - 16 Other renal disease 1664 (5.6) 1559 (5.2) 1.6 17 18 Diabetic complications 8069 (27.0) 7828 (26.2) 1.8 19 COPD 1184 (4.0) 1127 (3.8) 1.0 20 Other lung disease 2080 (7.0) 2010 (6.7) 0.9 21 22 Venous thromboembolism 693 (2.3) 666 (2.2) 0.6 23 Cancer 1981 (6.6) 2002 (6.7) 0.3 24 Liver disease 621 (2.1) 622 (2.1) <0.1 25 26 Rheumatic disease 860 (2.9) 845 (2.8) 0.3 27 Psychiatric disorder 2594 (8.7) 2572 (8.6) 0.3 28 Fracture in the previous year 497 (1.7) 492 (1.6) 0.1 29 Hospitalizations in previous year 30 31 Cardiovascular causes 1290 (4.3) 1322 (4.4) 0.5 32 Type 2 diabetes-related causes 259 (0.9) 266 (0.9) 0.3 33 Non-cardiovascular/type 2 diabetes-related causes 3890 (13.0) 3771 (12.6) 1.2 34 35 Outpatient contacts in previous year 36 Cardiovascular causes 2844 (9.5) 2753 (9.2) 1.0 37 Type 2 diabetes-related causes 5908 (19.8) 5714 (19.1) 1.6 38 Non-cardiovascular/type 2 diabetes-related causes 16894 (56.5) 16713 (55.9) 1.2 39 40 Diabetes drugs in previous 6 months 41 None 2316 (7.7) 2201 (7.4) 1.5 42 Metformin 24339 (81.4) 24541 (82.1) 1.8 43 44 Sulphonylureas 5724 (19.2) 5741 (19.2) 0.1 45 GLP-1-receptor-agonists 2607 (8.7) 2549 (8.5) 0.7 46 Insulin 7852 (26.3) 7924 (26.5) 0.5 47 Other antidiabetics (glitazones, glinides, acarbose) 715 (2.4) 717 (2.4) <0.1 48 49 Time since first diabetes drug, years 50 <1 3969 (13.3) 4029 (13.5) 0.6 51 1-3 3812 (12.8) 3865 (12.9) 0.5 52 53 >3-5 3598 (12.0) 3591 (12.0) 0.1 54 >5-7 3862 (12.9) 3920 (13.1) 0.6 55 >7 14646 (49.0) 14482 (48.5) 1.1 56 57 Prescription drugs in previous year 58 ACEi/ARB 19589 (65.5) 19396 (64.9) 1.4 59 Calcium channel blockerb 8953 (30.0) 8759 (29.3) 1.4 60

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1 2 3 Loop diureticb 3206 (13.7) 3024 (12.9) 2.3 4 5 Other diureticb 4347 (18.5) 4205 (17.9) 1.6 6 Beta-blocker 9871 (33.0) 9648 (32.3) 1.6 7 Digoxin 639 (2.1) 639 (2.1) <0.1 8 9 Nitrate 1964 (6.6) 1900 (6.4) 0.9 10 Platelet inhibitor 10516 (35.2) 10406 (34.8) 0.8 11 Anticoagulant 2198 (7.4) 2057 (6.9) 1.8 12 Confidential: For Review Only Lipid lowering drug 20467 (68.5) 20380 (68.2) 0.6 13 14 Antidepressant 4539 (15.2) 4527 (15.1) 0.1 15 Antipsychotic 1164 (3.9) 1165 (3.9) <0.1 16 Anxiolytic hypnotic or sedative 4654 (15.6) 4572 (15.3) 0.8 17 18 Beta-2 agonist inhalant 2854 (9.5) 2772 (9.3) 0.9 19 Anticholinergic inhalant 903 (3.0) 879 (2.9) 0.5 20 Glucocorticoid inhalant 2822 (9.4) 2717 (9.1) 1.2 21 22 Oral glucocorticoid 2081 (7.0) 2069 (6.9) 0.2 23 NSAID 7478 (25.0) 7475 (25.0) <0.1 24 Opioid 5634 (18.9) 5560 (18.6) 0.6 25 No. of prescription drugs in last yearb 26 27 0-5 5481 (23.4) 5643 (24.0) 1.6 28 6-10 9681 (41.2) 9647 (41.1) 0.3 29 11-15 5382 (22.9) 5332 (22.7) 0.5 30 31 >15 2929 (12.5) 2851 (12.1) 1.0 32 33 Abbreviations: ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; COPD, 34 chronic obstructive pulmonary disease; DDP4, dipeptidyl peptidase 4; GLP1, glucagon-like peptide 1; 35 NSAID, non-steroidal anti-inflammatory drug; SD, standard deviation; SGLT2, sodium-glucose co- 36 transporter 2. a 37 Propensity score matching was performed separately by country. b 38 Not available in Norwegian dataset; numbers are shown for patients in Sweden and Denmark. 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Table 2 Association between use of SGLT2 inhibitors vs. DPP4 inhibitors for primary and secondary outcomes of serious renal events. 4 5 6 Absolute SGLT2 inhibitors DPP4 inhibitors difference, events 7 HR (95% CI) 8 Confidential:(n=29887) For(n=29887) Review Only(95% CI) per 1000 9 person-years 10 Events Events per 1000 Events Events per 1000 11 person-years person-years 12 Primary outcomea 111 2.6 360 6.2 0.42 (0.34 to 0.53) -3.6 (-4.4 to -2.8) 13 Secondary outcomes 14 Renal replacement therapy 33 0.8 146 2.5 0.32 (0.22 to 0.47) -1.7 (-2.2 to -1.2) 15 Death from renal causesb 5 0.2 11 0.2 0.77 (0.26 to 2.23) -0.1 (-0.2 to 0.1) 16 Hospitalization for renal events 85 2.0 285 4.9 0.41 (0.32 to 0.52) -2.9 (-3.6 to -2.2) 17 18 aSerious renal events, a composite of renal replacement therapy, death from renal causes and hospitalization for renal events. 19 bThe analysis of death from renal causes included 24639 new users of SGLT2 inhibitors and 27,857 new users of DPP4 inhibitors as data on cause of death was only 20 available until 2017 in Denmark and patients initiating a study drug after this year were not included. 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 27 43 https://mc.manuscriptcentral.com/bmj 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 BMJ FigurePage 28 of 541

1 54,110 new users of 122,624 new users of 2 SGLT2 inhibitors DPP4 inhibitors 3 4 5 6 7 15,837 were excludeda 14,770 were excludeda 8 9 13,163 due to previous use of 34 due to previous use of 10 DPP4Confidential: inhibitors For Review OnlySGLT2 inhibitors 11 149 due to no specialist care contact 905 due to no specialist care contact 12 and no use of prescription drugs in the and no use of prescription drugs in the 13 previous year previous year 14 135 due to dialysis or 1,424 due to dialysis or 15 renal transplantation renal transplantation 16 325 due to endstage illness 1,831 due to endstage illness 17 415 due to drug misuse 1,088 due to drug misuse 18 510 due to severe pancreatic disorder 1,010 due to severe pancreatic 19 1,842 due to hospitalization in the disorder 20 previous 30 days 9,850 due to hospitalization in the 21 previous 30 days 22 23 24 25 26 27 28 38,273 new users of 107,854 new users of 29 SGLT2 inhibitors eligible for DPP4 inhibitors eligible for 30 inclusion inclusion 31 32 33 34 35 Propensity score estimation 36 and 1:1 matching 37 38 39 40 41 42 59,774 patients included in 43 the matched cohort 44 45 29,887 new users of SGLT2 inhibitors 46 29,887 new users of DPP4 inhibitors 47 48 49 50 51 52 53 54 55 56 57 58 59 60 https://mc.manuscriptcentral.com/bmj

a One patient could be excluded due to more than one reason Page 29 of 54 BMJ Figure 2

1 Confidential: For Review Only 2 3 4 5 6 7 8 3 9 10 Hazard ratio 0.42 (95% CI 0.34 to 0.53) 11 12 13 14 15 2 DPP4 inhibitors 16 17 18 19 20 21 1 SGLT2 inhibitors 22 23 Cumulative incidence (%) 24 25 26 27 28 0 29 0 1 2 3 30 Years since start of treatment 31 Number at risk 32 SGLT2 inhibitors 29,887 17,734 9109 3198 33 https://mc.manuscriptcentral.com/bmj DPP4 inhibitors 29,887 22,689 15,720 9344 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 BMJ FigurePage 3 30 of 54 SGLT2 inhibitors DPP4 inhibitors Hazard ratio (95% CI) 1 2 Events Events 3 per 1000 per 1000 p value for 4 Patients (%) Events patient yrs Patients (%) Events patient yrs interaction 5 hr 6 Total population 29,887 (100) 111 2.6 29,887 (100) 360 6.2 0.42 (0.34 to 0.53) 7 Sex 0.704 8 Confidential: For Review Only 9 Men 18,129 (61) 69 2.7 18,129 (61) 232 6.6 0.41 (0.31 to 0.54)hr 10 11 Women 11,758 (39) 42 2.4 11,758 (39) 128 5.6 0.45 (0.32 to 0.64)hr 12 Age 0.985 13 14 35-64 years 17,984 (60) 45 1.7 17,984 (60) 148 4.2 0.42 (0.30 to 0.59)hr 15 16 65-84 years 11,903 (40) 66 4.0 11,903 (40) 212 9.4 0.43 (0.32 to 0.56)hr 17 18 Major cardiovascular disease 0.022 19 Yes 5,659 (19) 36 4.6 5,449 (18) 155 14.8 0.30 (0.21 to 0.44)hr 20 21 No 24,228 (81) 75 2.2 24,438 (82) 205 4.3 0.52 (0.40 to 0.67)hr 22 23 Chronic kidney disease <0.001 24 Yes 987 (3) 14 9.2 987 (3) 97 51.3 0.18 (0.10 to 0.31)hr 25 26 No 28,900 (97) 97 2.4 28,900 (97) 263 4.7 0.52 (0.41 to 0.65)hr 27 hr 28 29 0.5 1.0 30 31 32 33 34 35 36 37 38 39 40 41 42 43 https://mc.manuscriptcentral.com/bmj 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Page 31 of 54 BMJ

1 2 3 SUPPLEMENTARY MATERIAL 4 5 6 7 Use of sodium-glucose co-transporter 2 inhibitors and risk of serious renal events: 8 Scandinavian cohort study 9 10 Pasternak et al. 11 12 Confidential: For Review Only 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Data sources 4 5 6 7 Information about filled prescriptions was retrieved from the national prescription 8 9 registers in Sweden,1 Denmark2 and Norway3. The registers contain individual-level 10 11 information on all drug prescriptions filled at all pharmacies in the country since July 12 2005, inConfidential: Sweden, 1995 in Denmark, and For 2004 inReview Norway and include Only the anatomical 13 14 therapeutic chemical (ATC) code of the dispensed drug, data about the amount of drug 15 16 dispensed and the date when the prescription was filled. 17 18 The national patient registers contain individual-level data on outpatient and 19 20 emergency department visits and inpatient admissions to all hospitals.4–6 In our study, 21 22 we used physician-assigned procedure codes, and diagnoses according to the 23 24 International Classification of Diseases, tenth revision (ICD10), to obtain information 25 about history of disease at cohort entry for each patient and the outcome events during 26 27 the study period. The Cause of Death registers in each country also provided data on 28 29 outcome events. This register contain data on the date and cause of death.7–9 30 31 From the population registers we obtained information on age, sex, country of birth, 32 33 migration status, civil status (Norway) and vital status of study population10–12 Data on 34 35 patients’ educational level and civil status were obtained from Statistics Denmark and 36 Statistics Sweden.10 37 38 39 The National Diabetes Register includes data on risk factors in patients with type 1 or 40 41 type 2 diabetes in Sweden. Trained nurses and physicians collect the data during patient 42 visits to primary care and outpatient clinics nationwide. Currently, more than 90% of all 43 44 patients receiving drugs for diabetes in Sweden are included, with this number having 45 46 increased during the past years.13 For the Swedish part of the cohort, we used this 47 48 register to obtain data on glycated hemoglobin, blood pressure, albuminuria, estimated 49 glomerular filtration rate (eGFR), body-mass index and smoking. 50 51 52 The personal identification number assigned to all inhabitants in the three countries 53 54 enabled linkage of individual-level information across data sources. 55 56 57 58 59 60

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1 2 3 Supplementary Table 1 ATC codes and estimated days of exposure per unit of SGLT2 4 5 inhibitors and DPP4 inhibitors. 6 7 8 Category ATC definition Estimated days of supply per tablet 9 SGLT2 A10BK01, A10BK02, A10BK03, A10BD15, A10BK01 = 1.0; A10BK02 = 1.0; A10BK03 = 1.0; 10 Inhibitors A10BD16, A10BD19*, A10BD20, A10BD15 = 0.5; A10BD16 = 0.5; A10BD19 = 1.0; 11 A10BD21* A10BD20 = 0.5; A10BD21 = 1.0 12 DPP4 Confidential:A10BH01, A10BH02, A10BH03, For A10BH04, Review A10BH01 = 1.0 ; A10BH02Only = 0.5; A10BH03 = 1.0; 13 inhibitors A10BH05, A10BD07, A10BD08, A10BD09, A10BH04 = 1.0; A10BH05 = 1.0; A10BD07 = 0.5; 14 A10BD10, A10BD11, A10BD13, A10BD19*, A10BD08 = 0.5; A10BD09 = 1.0; A10BD10 = 0.5 15 A10BD21* A10BD11 = 0.5; A10BD13 = 0.5; A10BD19 = 1.0; 16 A10BD21 = 1.0 17 18 19 * Combinations of SGLT2 inhibitor and DPP4 inhibitors. These drugs were not included 20 as study drugs but were accounted for in the exclusion criteria of previous use of any of 21 the study drugs. 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 2 ICD10 and procedure codes for exclusion criteria. 4 5 6 7 Category Codes (ICD-10, procedure, or ATC) 8 Dialysis or renal transplantation at any time ICD-10: Z49, Z94.0, Z99.2 9 before index datea Procedure: KAS 10 11 Additional procedure codes:b 12 Confidential: ForSweden: Review DR012, DR013, Only DR014, DR015, DR016, 13 DR023, DR024, DR055, DR056, DR060, DR061 14 Denmark: (B)JFD, (B)JFZ 15 16 Endstage illness (severe malnutrition, cachexia, ICD-10: E40-E43, F00-F03, G30, R40.2b, R64 17 dementia, coma) at any time before index datea ATC: N06D 18 Drug misuse within last year ICD-10: F11-F16, F18, F19, R78.1-R78.5b T40b 19 ATC: N07BB, N07BC 20 Major pancreatic disease (chronic pancreatitis ICD-10: C25, K86.0, K86.1 21 [defined by pancreatic enzyme substitution Procedure: JLC, JLE 22 prescription within last year or diagnosis at any ATC: A09AA02 23 time before index date], pancreatic cancer, major 24 pancreatic surgery at any time before index datea) 25 No specialist care contact or prescription drug in n.a. 26 last year prior to the index date 27 Hospital admission within 30 days before index n.a. 28 date 29 30

31 Abbreviations: ICD, International Classification of Diseases; ATC, Anatomical Therapeutic Chemical 32 a 10-year lookback in Sweden and Denmark; 5-year look-back in Norway 33 b Not available in the Norwegian dataset. 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 4 5 Supplementary Table 3 Propensity score variables and definitions. 6 7 8 9 Sociodemographic 10 characteristics ICD/categories 11 Sex Women/men 12 Age Confidential:5-year categories For Review Only 13 Place of birth Scandinaviab; Rest of Europe; Outside Europe, Missing 14 Primary school; high school; vocational or short tertiary education; medium 15 Educationa or long tertiary education 16 Living with partner Yes/no 17 c 18 Medical history ICD-10 codes and procedure codes 19 Acute coronary syndrome ICD-10: I200, I21-22 20 Other ischemic heart disease ICD-10: I11 (not I110), I20 (not I200), I24, I25 21 Heart ICD-10: I50, I110, I130, I132, I42, I43, J81 22 failure/cardiomyopathy 23 Valve disorders ICD-10: I34-I37 24 Stroke ICD-10: I60-I64 25 Other cerebrovascular ICD-10: I65-I69, G45 (excl G454), G46 26 disease 27 Atrial fibrillation ICD-10: I48 28 Other arrhythmia ICD-10: I44-I47, I49 29 30 Arterial disease (including ICD-10: I65, I70, I72, I73, I74, I77, K550, K551, E115, E145, E135 31 amputation) Procedure: NFQ ,NGQ, NHQ 32 Other renal disease ICD-10: 33 N00-08, N10-N16, N17, N20-N23, N25-N29 34 Diabetes complications ICD-10: E110, E111, E113, E114, E116, E117, E118, E130, E131, E133, E134, 35 E136, E137, E138, E140, E141, E143, E144, E146, E147, E148, E160, E161, 36 E162, G990, G590, G632, H280a, H358, H360, M142, M146, M908, L984 37 Procedurea: CKC10, CKC12, CKC15, CKD65 38 39 COPD ICD-10: J44 40 Other lung disease ICD-10: I27, J84, R092, E662, Z99, J40-J43, J45-J47, J60-J69, J70,a J92, J96, 41 J982, J983 42 Procedure: GBB 43 44 Venous thromboembolism ICD-10: I26, I80 (except I80.0), I81, I820, I822-I829 45 Cancer (excl non-melanoma ICD-10: C00-C43, C45-C97 46 skin cancer) 47 Liver disease ICD-10: B18, I850, I859, I982, K70-K77 48 Rheumatic disease ICD-10: M05-M09, M30-34, M351, M353, M45 49 Psychiatric disorder ICD-10: F04-F10, F20-F99 50 Coronary revascularization in Procedure: FNA, FNB, FNC, FND, FNE, FNG, FNP02, FNP12, FNQ05, FNQ12, 51 previous yr FNR22 52

53 Other cardiac Procedure: F (except FNA, FNB, FNC, FND, FNE, FNG, FNP02, FNP12, FNQ05, 54 55 surgery/invasive cardiac FNQ12, FNR22, FPFE, FPGX), DF020 56 procedure in previous yr 57 Fracture in previous year ICD-10: S02 (except S025), S12, S22, S32, S42, S52, S62, S72, S82, S92, T02, 58 T08, T10, T12, M484, M485, M843 59 Prescription-drug use in ATC code 60 previous yr

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1 2 3 ACE-inhibitor or ARB C09A-D 4 Calcium channel blocker C08C, C08D 5 Loop diuretica C03C, C03EB 6 Other diuretica C03A, C03B, C03D, C03EA 7 8 Beta-blocker C07 9 Digoxin C01AA05 10 Nitrates C01DA 11 Platelet inhibitor B01AC 12 AnticoagulantConfidential: B01AA, B01AE07, For B01AF, Review B01AX05 Only 13 Lipid lowering drug C10 14 Antidepressant N06A 15 Antipsychotic N05A 16 Anxiolytic, hypnotic or N05B, N05C 17 sedative 18 19 Beta-2 agonist inhalant R03AC 20 Anticholinergic inhalant R03BB 21 Glucocorticoid inhalant R03BA, R03AK 22 Oral glucocorticoid H02AB 23 NSAID M01A 24 Opiate N02A 25 Diabetes drugs in the last 6 26 months 27 None Not any A10 28 29 Metformin A10BA02, A10BD02, A10BD03, A10BD05, A10BD07, A10BD08, A10BD10, 30 A10BD11, A10BD13, A10BD14, A10BD15, A10BD16, A10BD20 31 Sulphonylureas A10BB, A10BD01, A10BD02, A10BD04, A10BD06 32 GLP-1-receptor-agonists A10BJ01, A10BJ02, A10BJ03, A10BJ05, A10AE56 33 34 Insulin A10AB, A10AC, A10AD, A10AE 35 Other antidiabetics A10BF01, A10BG, A10BD03, A10BD04, A10BD05, A10BD06, A10BD09, 36 37 (glitazones, glinides, A10BD14, A10BX, 38 acarbose) 39 Time since first diabetes drug A10; 40 <1 year, 1-3 years, ≥3 to 5 years, ≥5 to 7 years, ≥7 years 41 Health care utilization in 42 previous year 43 No. of drugs used a 1-5, 6-10, 11-15, >15 44 Hospitalization due to I00-I99 (primary position) 45 cardiovascular causes 46 Hospitalization due to type 2 E11 (primary position) 47 diabetes 48 Hospitalization due to non- Not I00-I99, E11 (primary position) 49 cardiovascular or non-type 2 50 diabetes causes 51 52 Outpatient contact due to I00-I99 (primary position) 53 cardiovascular causes 54 Outpatient contact due to E11 (primary position) 55 type 2 diabetes 56 Outpatient contact due to Not I00-I99, E11 (primary position) 57 non-cardiovascular or non- 58 type 2 diabetes causes 59 60

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1 2 3 Abbreviations: ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; COPD, 4 chronic obstructive pulmonary disease; DDP4, dipeptidyl peptidase 4; GLP1, glucagon-like peptide 1; 5 NSAID, non-steroidal anti-inflammatory drug; SGLT2 sodium-glucose co-transporter 2. 6 7 a Not available in Norwegian dataset 8 b Defined as “Nordic countries” in Norwegian data 9 c 10-year look-back in Sweden and Denmark; 5-year look-back in Norway. 10 11 12 Confidential: For Review Only 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 4 ICD10 codes used to define history of chronic kidney disease. 4 5 6 ICD 10 Type of diagnosis / hospital 7 contact 8 E112, E132, E142, I120, I131, I132, N18, N19 Any/any 9 10 11 a10-year look-back in Sweden and Denmark; 5-year look-back in Norway 12 Confidential: For Review Only 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 5 ICD10 and procedure codes used for outcome definitions. 4 5 6 Outcome ICD 10 or procedure code Type of diagnosis/type of hospital 7 contact (data source) 8 9 Dialysis or renal All countries Any position / inpatient admission or 10 transplantation ICD10: Z49, Z940, Z992 outpatient visit (Patient registers) 11 12 Confidential:Sweden For Review Only 13 Procedure: KAS, DR012, DR013, DR014, 14 DR015, DR016, DR023, DR024, DR055, 15 DR056, DR060, DR061 16 17 Denmark 18 Procedure: KAS, BJFD, BJFZ 19 Norway 20 Procedure: KASa 21 22 Death from renal causesb ICD10: E112, E132, E142, I120, I131, Underlying cause of death (Cause of 23 I132, N00-N08, N10-N16, N17, N18, N19, Death registers) 24 N20-N23, N25-N29 25 26 Hospitalization for renal ICD10: E112, E132, E142, I120, I131, Primary diagnosis / inpatient 27 events I132, N17, N18, N19 admission (Patient registers) 28 29 30 31 32 a Extended procedure codes not available in the Norwegian dataset. 33 34 b As data on cause of death was available only through 2017 in Denmark, renal death, which accounted for 35 <5% of the events in the primary composite outcome, occurring in Denmark in 2018 was not included in 36 the primary outcome analyses. In secondary outcome analyses of renal death, end of the study period was 37 set to 31 December 2017 in Denmark. 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 6 ICD10 and procedure codes used to define history of major 4 5 cardiovascular disease. 6 7 8 ICD 10/procedure codea Type of diagnosis / 9 hospital contact 10 ICD10: I200, I21-22, I60-I64, I110, I130, I132, I42, I43, I50, J81, I65, I70, Any/any 11 I72, I73.9, K550, K551, E115, E135, E145 12 Confidential: For Review Only

13 14 Procedure: FNA, FNB, FNC, FND, FNE, FNG, FNP02, FNP12, FNQ05, 15 FNQ12, FNR22 16 17 18 19 a 10-year look-back in Sweden and Denmark; 5-year look-back in Norway 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 4 5 Supplementary Table 7 Variable definitions for the analyses using data from the 6 National Diabetes Register in Sweden and from healthcare databases in Denmark. 7 8 9 10 Variable Categorization % missing % missing 11 values values 12 Confidential: For Review Only(Sweden)a (Denmark)b 13 HbA1c (%) ≤ 6.9; 7.0-7.8; 7.9-8.7; 8.8-9.6; ≥9.7 41.1 31.9 14 Normalbuminuria; microalbuminuria; Albuminuria 38.7 51.3 15 macroalbuminuria 16 eGFR (ml/min) Linear, quadratic, cubic 26.2 31.0 17 Normotension: 18 SBP <140 mmHg AND DBP <90 mmHg 19 Stage 1 hypertension: Blood pressure 20.8 - 20 SBP ≥140 to <160 mmHg OR DBP: ≥90 to <100mmHg 21 Stage 2 hypertension: 22 SBP ≥160 mmHg OR DBP: ≥100 mmHg 23 Normal weight: <25 24 Body-mass index Overweight: ≥25 to <30 26.9 - 25 (kg/m2) Obese class I: ≥30 to <35 26 Obese class I/II: ≥35 27 Current smoking Yes/no 28.4 - 28 29 Abbreviations: SBP: systolic blood pressure; DBP: diastolic blood pressure; eGFR: estimated glomerular 30 filtration rate. 31 32 a Missing values in the propensity-score-matched cohort of SGLT2 inhibitor users and DPP4 inhibitor 33 users in Sweden. 34 b Missing values in the propensity-score-matched cohort of SGLT2 inhibitor users and DPP4 inhibitor 35 36 users in Denmark. 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 8 Baseline characteristics of users of SGLT2 inhibitors and DPP4 4 5 inhibitors in the three-country cohort before propensity score matching. Numbers are 6 shown in n (%) unless otherwise indicated. 7 8 9 Standardized 10 mean 11 SGLT2 inhibitors DPP4 inhibitors difference 12 Confidential: For Review Only (N=38273) (N=107854) (%) 13 14 Country 15 Sweden 10672 (27.9) 42718 (39.6) - 16 Denmark 20341 (53.1) 40077 (37.2) - 17 18 Norway 7260 (19.0) 25059 (23.2) - 19 Male 23386 (61.1) 65170 (60.4) 1.4 20 Age, mean (SD) 60.7 (10.3) 63.9 (11.1) - 21 Age 22 23 35-39 960 (2.5) 2040 (1.9) 4.2 24 40-44 1978 (5.2) 4129 (3.8) 6.5 25 45-49 3391 (8.9) 7291 (6.8) 7.8 26 27 50-54 5138 (13.4) 11034 (10.2) 9.9 28 55-59 6188 (16.2) 13645 (12.7) 10.0 29 60-64 6504 (17.0) 15848 (14.7) 6.3 30 65-69 6423 (16.8) 18756 (17.4) 1.6 31 32 70-74 4759 (12.4) 16728 (15.5) 8.9 33 75-79 2110 (5.5) 11428 (10.6) 18.8 34 80-84 822 (2.1) 6955 (6.4) 21.3 35 36 Place of Birth 37 Scandinavia 32436 (84.7) 89107 (82.6) 5.8 38 Rest of Europe 2413 (6.3) 7426 (6.9) 2.3 39 40 Outside Europe 3366 (8.8) 11156 (10.3) 5.3 41 Missing 58 (0.2) 165 (0.2) <0.1 42 Civil status 43 Married/living with partner 22789 (59.5) 62503 (58.0) 3.2 44 45 Single 15365 (40.1) 44823 (41.6) 2.9 46 Missing 119 (0.3) 528 (0.5) 2.8 47 Educationb 48 49 Primary-/Secondary school, vocational training 24384 (78.6) 65712 (79.4) 1.8 50 Short tertiary education 1775 (5.7) 5144 (6.2) 2.1 51 Medium or long tertiary education 4021 (13.0) 9388 (11.3) 5.0 52 Missing 833 (2.7) 2551 (3.1) 2.4 53 54 Medical history 55 Acute coronary syndrome 2818 (7.4) 7391 (6.9) 2.0 56 Other ischemic heart disease 6651 (17.4) 17136 (15.9) 4.0 57 58 Heart failure/cardiomyopathy 2183 (5.7) 6835 (6.3) 2.7 59 Valve disorders 892 (2.3) 3194 (3.0) 3.9 60 Stroke 1469 (3.8) 4687 (4.3) 2.6

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1 2 3 Other cerebrovascular disease 1617 (4.2) 5183 (4.8) 2.8 4 5 Atrial fibrillation 2597 (6.8) 8868 (8.2) 5.5 6 Other arrythmia 1616 (4.2) 4727 (4.4) 0.8 7 Coronary revascularization 8 in the previous year 565 (1.5) 1333 (1.2) 2.1 9 Other cardiac surgery/invasive procedure 10 in the previous year 183 (0.5) 654 (0.6) 1.7 11 Arterial disease 2699 (7.1) 6333 (5.9) 4.8 12 Confidential: For Review Only 13 Chronic kidney disease 1608 (4.2) 5786 (5.4) 5.5 14 Other renal disease 2170 (5.7) 7121 (6.6) 3.9 15 Diabetic complications 12283 (32.1) 24235 (22.5) 21.7 16 COPD 1533 (4.0) 4675 (4.3) 1.6 17 18 Other lung disease 2748 (7.2) 7272 (6.7) 1.7 19 Venous thromboembolism 906 (2.4) 2585 (2.4) 0.2 20 Cancer 2373 (6.2) 9059 (8.4) 8.5 21 22 Liver disease 785 (2.1) 2018 (1.9) 1.3 23 Rheumatic disease 1050 (2.7) 3474 (3.2) 2.8 24 Psychiatric disorder 3264 (8.5) 9359 (8.7) 0.5 25 26 Fracture in the previous year 616 (1.6) 1846 (1.7) 0.8 27 Hospitalizations in previous year 28 Cardiovascular causes 1651 (4.3) 5032 (4.7) 1.7 29 Type 2 diabetes-related causes 369 (1.0) 856 (0.8) 1.8 30 31 Non-cardiovascular/type 2 diabetes-related causes 5012 (13.1) 14591 (13.5) 1.3 32 Outpatient contacts in previous year 33 Cardiovascular causes 3646 (9.5) 10626 (9.9) 1.1 34 35 Type 2 diabetes-related causes 9205 (24.1) 16747 (15.5) 21.5 36 Non-cardiovascular/type 2 diabetes-related causes 22034 (57.6) 59220 (54.9) 5.4 37 Diabetes drugs in previous 6 months 38 None 2319 (6.1) 10520 (9.8) 13.7 39 40 Metformin 31496 (82.3) 87040 (80.7) 4.1 41 Sulphonylureas 6873 (18.0) 24467 (22.7) 11.8 42 GLP-1-receptor-agonists 9819 (25.7) 2663 (2.5) 70.7 43 44 Insulin 13025 (34.0) 15641 (14.5) 46.8 45 Other antidiabetics (glitazones, glinides, acarbose) 886 (2.3) 2656 (2.5) 1.0 46 Time since first diabetes drug 47 <1 4086 (10.7) 16717 (15.5) 14.3 48 49 1-3 4090 (10.7) 15428 (14.3) 11 50 >3-5 4077 (10.7) 15758 (14.6) 11.9 51 >5-7 4755 (12.4) 15219 (14.1) 5.0 52 53 >7 21265 (55.6) 44732 (41.5) 28.5 54 Prescription drugs in previous year 55 ACEi/ARB 25970 (67.9) 68539 (63.5) 9.1 56 57 Calcium channel blocker 11801 (30.8) 32855 (30.5) 0.8 58 Loop diuretic 4313 (13.9) 12721 (15.4) 4.1 59 Other diuretic 5944 (19.2) 15153 (18.3) 2.2 60

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1 2 3 Beta-blocker 12653 (33.1) 37898 (35.1) 4.4 4 5 Digoxin 808 (2.1) 2810 (2.6) 3.3 6 Nitrate 2530 (6.6) 7079 (6.6) 0.2 7 Platelet inhibitor 14152 (37.0) 37933 (35.2) 3.8 8 9 Anticoagulant 2762 (7.2) 9389 (8.7) 5.5 10 Lipid lowering drug 27261 (71.2) 71617 (66.4) 10.4 11 Antidepressant 6034 (15.8) 15348 (14.2) 4.3 12 Confidential: For Review Only Antipsychotic 1485 (3.9) 4138 (3.8) 0.2 13 14 Anxiolytic hypnotic or sedative 5620 (14.7) 18101 (16.8) 5.8 15 Beta-2 agonist inhalant 3667 (9.6) 9348 (8.7) 3.2 16 Anticholinergic inhalant 1106 (2.9) 3679 (3.4) 3.0 17 18 Glucocorticoid inhalant 3555 (9.3) 9700 (9.0) 1.0 19 Oral glucocorticoid 2504 (6.5) 8568 (7.9) 5.4 20 NSAID 9802 (25.6) 23939 (22.2) 8.0 21 22 Opioid 7360 (19.2) 18893 (17.5) 4.4 23 No. of prescription drugs in last yearb 24 0-5 6148 (19.8) 20857 (25.2) 12.9 25 6-10 12723 (41.0) 33434 (40.4) 1.3 26 27 11-15 7819 (25.2) 17972 (21.7) 8.3 28 >15 4323 (13.9) 10532 (12.7) 3.6 29 30 31 Abbreviations: ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; COPD, 32 chronic obstructive pulmonary disease; DDP4, dipeptidyl peptidase 4; GLP1, glucagon-like peptide 1; 33 NSAID, non-steroidal anti-inflammatory drug; SD, standard deviation; SGLT2, sodium-glucose co- 34 transporter 2. 35 36 a Propensity score matching was performed separately by country. 37 b Not available in Norwegian dataset; numbers are shown for patients in Sweden and Denmark. 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 9 Follow-up according to individual SGLT2 inhibitors and DPP4 4 5 inhibitors at cohort entry in the matched cohort. 6 7 8 Follow-up time, years 9 N (%)a Mean (SD) Total Overall % 10 11 Dapagliflozin 16004 (53.5) 1.8 (0.9) 28185 66.1 SGLT2 12 Confidential:Empagliflozin 13565 (45.4) For 1.0 Review (0.8) 13890 Only 32.6 13 inhibitors 14 Canagliflozin 322 (1.1) 1.7 (1.2) 561 1.3 15 Sitagliptin 20238 (67.7) 1.9 (1.0) 37897 64.8 16 Vildagliptin 5162 (17.3) 2.3 (0.9) 11719 20.0 17 DPP4 Saxagliptin 693 (2.3) 2.3 (0.8) 1621 2.8 18 inhibitors 19 Alogliptin 537 (1.8) 2.4 (0.9) 1267 2.2 20 Linagliptin 3261 (10.9) 1.8 (1.0) 5977 10.2 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 10 Analyses of the primary outcome by country. 4 5 6 SGLT2 inhibitors DPP4 inhibitors HR 7 (95% CI) 8 Patients Events Events Patients Events Events 9 per 1000 per 1000 10 person- person- 11 years years 12 DenmarkConfidential: 14232 63 2.9 For 14232 Review 219 Only6.8 0.42 (0.32 to 0.56) 13 Sweden 9241 23 2.0 9241 72 4.9 0.41 (0.26 to 0.66) 14 Norway 6414 25 2.7 6414 69 6.0 0.45 (0.29 to 0.71) 15

16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 11 Additional analyses using an as-treated exposure definition. 4 5 6 7 Absolute SGLT2 inhibitors DPP4 inhibitors difference, events 8 HR (95% CI) 9 (n=29887) (n=29887) (95% CI) per 1000 10 person-years Events per 1000 Events per 1000 11 Events Events 12 Confidential:person-years Forperson Review-years Only Primary 13 44 2.0 184 6.8 0.30 (0.22 to 0.42) -4.7 (-5.3 to -3.9) 14 outcomea 15 16 17 aSerious renal events, a composite of renal replacement therapy, death from renal causes and 18 hospitalization for renal events. 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Table 12 Distribution of variables from the National Diabetes Register 4 5 in the propensity-score-matched cohort of SGLT2 inhibitor users and DPP4 inhibitor 6 users in Sweden. Numbers are shown in n (%). 7 8 9 10 SGLT2 inhibitors DPP4 inhibitors 11 (N=9241) (N=9241) 12 Blood pressure,Confidential: mmHg For Review Only 13 SBP <150 and DBP <90 3985 (43.1) 4135 (44.7) 14 SBP: 140-159 or DBP: 90-99 2450 (26.5) 2508 (27.1) 15 16 SBP≥160 or DBP ≥100 792 (8.6) 765 (8.3) 17 Missing 2014 (21.8) 1833 (19.8) 18 Glycated hemoglobin (HbA1c), % (mmol/mol) 19 20 ≤6.9 (≤52) 449 (4.9) 572 (6.2) 21 7.0-7.8 (53-62) 1262 (13.7) 1560 (16.9) 22 7.9-8.7 (63-72) 1410 (15.3) 1480 (16.0) 23 8.8-9.6 (73-82) 1079 (11.7) 933 (10.1) 24 25 ≥9.7 (≥83) 1215 (13.1) 921 (10.0) 26 Missing 3826 (41.4) 3775 (40.9) 27 BMI, kg/m2 28 29 <25 417 (4.5) 582 (6.3) 30 25-29 1946 (21.1) 2316 (25.1) 31 30-34 2470 (26.7) 2318 (25.1) 32 33 ≥35 1888 (20.4) 1579 (17.1) 34 Missing 2520 (27.3) 2446 (26.5) 35 Albuminuria 36 Normalbuminuria 4107 (44.4) 4094 (44.3) 37 38 Microalbuminuria 1233 (13.3) 1171 (12.7) 39 Macroalbuminuria 311 (3.4) 411 (4.4) 40 Missing 3590 (38.8) 3565 (38.6) 41 2 42 eGFR, ml/min/1,73 m 43 ≥90 3312 (35.8) 2982 (32.3) 44 60-89 2870 (31.1) 2793 (30.2) 45 30-59 567 (6.1) 1044 (11.3) 46 47 < 30 9 (0.1) 60 (0.6) 48 Missing 2483 (26.9) 2362 (25.6) 49 Current smoking 50 51 No 5544 (60.0) 5673 (61.4) 52 Yes 974 (10.5) 1038 (11.2) 53 Missing 2723 (29.5) 2530 (27.4) 54 55 56 Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; eGFR, estimated glomerular 57 filtration rate. 58 59 60

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1 2 3 Supplementary Table 13 Distribution of glycated hemoglobin, albuminuria and 4 5 estimated glomerular filtration rate in the propensity-score-matched cohort of SGLT2 6 inhibitor users and DPP4 inhibitor users in Denmark. Numbers are shown in n (%). 7 8 9 SGLT2 inhibitors DPP4 inhibitors 10 (N=14232) (N=14232) 11 12 GlycatedConfidential: hemoglobin (HbA1c), % (mmol/mol) For Review Only 13 ≤6.9 (≤52) 1323 (9.3) 1333 (9.4) 14 7.0-7.8 (53-62) 3158 (22.2) 2921 (20.5) 15 16 7.9-8.7 (63-72) 2461 (17.3) 2069 (14.5) 17 8.8-9.6 (73-82) 1508 (10.6) 1172 (8.2) 18 ≥9.7 (≥83) 1892 (13.3) 1538 (10.8) 19 Missing 3890 (27.3) 5199 (36.5) 20 21 Albuminuria 22 Normalbuminuria 5306 (37.3) 4344 (30.5) 23 Microalbuminuria 1908 (13.4) 1571 (11.0) 24 25 Macroalbuminuria 356 (2.5) 369 (2.6) 26 Missing 6662 (46.8) 7948 (55.8) 27 eGFR, ml/min/1,73 m2 28 29 ≥90 5407 (38.0) 4555 (32.0) 30 60-89 4153 (29.2) 3183 (22.4) 31 30-59 882 (6.2) 1266 (8.9) 32 < 30 20 (0.1) 186 (1.3) 33 34 Missing 3770 (26.5) 5042 (35.4) 35 36 Abbreviations: eGFR, estimated glomerular filtration rate. 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Figure 1 Schoenfeld residuals for the primary outcome analysis. 4 5 6 7 8 9 10 11 12 Confidential: For Review Only 13 14 15 16 17 18 19

20 Schoenfeld residual 21 22 23 24 25 26 27 28 29

30 31 Days of follow-up 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Figure 2 Cumulative incidence of serious renal events in users of 4 5 SGLT2 inhibitors and DPP4 inhibitors using an as-treated exposure definition. 6 7 8 9 10 11 12 Confidential: For Review Only 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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1 2 3 Supplementary Figure 3 Schoenfeld residuals for the primary outcome analysis using 4 5 an as-treated exposure definition. 6 7 8 9 10 11 12 Confidential: For Review Only 13 14

15 16 17 18 19 20 21 Schoenfeld residual 22 23 24 25 26 27 28 29 30 31 32 Days of follow-up 33 34 35

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