1 INTRODUCTION

Initiation of sodium-glucose cotransporter 2 inhibitors (SGLT-2is) has been linked to an initial decline in estimated glomerular filtration rate (eGFR).^1-6 However, SGLT-2is have also been associated with reduced risk of acute renal failure (ARF) in clinical trials^{1-3, 7, 8} and have been shown to slow decline in eGFR in people with type 2 diabetes following an initial (and reversible) decline.^{4, 9-12} Several large clinical trials have shown SGLT-2is slow progression of chronic kidney disease (CKD).^{9, 10, 12-14}

Replicating findings observed in clinical trials in a real-world population is important, as clinical trial samples are seldom representative of the broader population with diabetes.^15-17 Indeed, most estimates of the effect of SGLT-2is on ARF are drawn from high-risk populations, and their generalizability to the broader population with type 2 diabetes is unclear. For example, the Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease (DAPA-CKD) trial included individuals with demonstrated baseline CKD, a median age of 62, and no participants over the age of 74, with no stratification of older people with respect to incidence of adverse renal events.¹⁰

Other observational studies have reported on whether SGLT-2is are associated with reduced risk of ARF.^{5, 7, 18-21} There is a lack of consensus and limitations among these studies as some report no association and others show a reduction in ARF with SGLT-2i initiation.^{5, 7, 18-21} Some previous studies that reported no significant effect of SGLT-2is on ARF have used any oral glucose lowering drug,¹⁹ glucagon-like peptide 1 (GLP1) agonist,²⁰ DPP-4i/GLP1 agonist/gliclazide,⁴ or no use as a comparator group.²² Other observational studies have reported 21%,⁵ 21%,¹⁸ and 53%^{5, 18} reductions in rates of ARF with SGLT-2i initiation versus dipeptidyl peptidase-4 inhibitor (DPP-4i) initiation.

The objective of this study was to investigate the association between post-hospital discharge initiation of SGLT-2i compared to DPP-4i and the incidence of subsequent hospital admission for ARF and CKD in people with type 2 diabetes.

2 METHODS

2.2 Study population and exposures

The study cohort was defined as people aged ≥30 years and discharged from a Victorian public or private hospital with an International Classification of Diseases, Tenth Revision, Australian Modification (ICD-10-AM) code indicative of type 2 diabetes (E11) between January 12, 2013 and June 30, 2018.

The index admission was defined as the first hospital admission during the study period among individuals with a diagnosis code for type 2 diabetes (see Table A1 for cause of index hospitalization). The index date was defined as the date when either an SGLT-2i or DPP-4i was initiated on or after the discharge date (Figure 1). Users who were dispensed the DPP-4i linagliptin were excluded as this is the preferred DPP-4i in reduced renal function. PBS data were available from 2006. This allowed the date of first supply to be ascertained because neither SGLT-2i nor DPP-4i were available in Australia prior to 2006. Anatomical Therapeutic Chemical codes were used to identify first SGLT-2i and DPP-4i dispensings (see Table A2). Only new users of SGLT-2i or DPP-4i were considered. This meant that people were included in the study only if they had no dispensing record of SGLT-2i and DPP-4i prior to the index date. People receiving both an SGLT-2i and a DPP-4i for the first time on the same day were excluded. DPP-4is were chosen as the comparator to reduce confounding by disease severity as both SGLT-2i and DPP-4i are second-line agents for type 2 diabetes in Australia.²⁵

The cohort was restricted to people using metformin within 1 year prior to the index date and excluded people with use of loop diuretics within 1 year prior to the index date, with hospitalization for ARF within 1 year prior to index date, or a prior diagnosis of CKD or dialysis since 2006 to index date. Our rationale for this was to minimize channeling bias as at the time of the study SGLT-2i were contraindicated in severe renal impairment. Figure 2 shows the flow chart for selection of patients.

3 RESULTS

4 DISCUSSION

We demonstrated that initiation of SGLT-2is versus DPP-4is at hospital discharge was associated with a 22% reduction in the rate of readmission for ARF and 17% reduction in rate of CKD admissions in people who initiated SGLT-2is versus DPP-4is. These findings from real-world data enhance what we know from randomized controlled trials (RCTs)^{1-3, 7, 8} and other observational studies^{5, 18} and suggest that SGLT2i do not cause ARF or have acute detriments on kidney function in people without severely reduced eGFR.

This was the first Australian study to demonstrate the real-world benefits of SGLT-2is versus DPP-4is for reducing ARF and CKD. There are numerous reasons that explain how our real-world data enhances what we know from RCTs. First, we were able to adjust for a range of clinically important covariates to minimize confounding by comorbidity and channeling bias by excluding people with prior medication use and comorbidities that predispose to ARF or CKD.³⁰ Many prior studies did not exclude this prior medication use and comorbidities. Second, the study analyzed data for a large state-wide cohort over a 6-year period (July 2012 to June 2018). All patients who were hospitalized were included (there was no opt-out option), which gave an accurate representation of the Victorian population.

Our study results are in alignment with previous RCTs and several other observational studies. An observational study in Canada including 39 094 people compared the 90 day risk of ARF in new initiators of SGLT-2is and DPP-4is, finding a 21% reduced risk of ARF for the SGLT-2i group compared to the DPP-4i group (risk ratio 0.79 (95% CI 0.64–0.98).¹³ Similarly, Cahn et al reported a 53% (95% CI 20–73) reduced risk of ARF in SGLT-2i versus DPP-4i users in their overall population.⁵ Some previous studies have reported no significant effect of SGLT-2is on ARF and have used any oral glucose lowering drug,¹⁹ GLP1 agonist,²⁰ DPP-4i/GLP1 agonist/gliclazide,⁴ or no use as a comparator group.²² Different comparators may explain some of the differences between our results and the findings from these studies. Previous RCTs have shown that SGLT-2is are associated with reduced rates of progression of CKD incidence compared to DPP-4is.^{9, 10, 12-14, 29}

To summarize major trials in this space, the Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial compared people with type 2 diabetes and CKD to receive canagliflozin or placebo. The incidence of end-stage kidney disease was lowered by 34% in the canagliflozin group compared to the placebo group (HR 0.66 (95% CI 0.54–0.86).³¹ In an RCT by Pasternak et al¹³ and by Pollock et al,⁹ the annual decline in eGFR slowed significantly after SGLT-2i therapy was initiated.^{9, 13} Similarly, DAPA-CKD¹⁰ showed among patients with CKD, the risk of a combined end point of at least 50% sustained decline in eGFR, end-stage kidney disease, or death from renal causes being 0.56 (95% CI, 0.45–0.68).¹⁰

Our study had several limitations. First, the cohort included only people discharged from hospital, which limits generalizability. People who are hospitalized are usually sicker and have more comorbidities than the general population of people with type 2 diabetes. If the outcomes (AKI or CKD) were identified in the community they would have been missed as we are using only hospitalization data. However, this should be consistent across both groups and not specific to one medication class. Second, we did not have access to data on type 2 diabetes duration. However, we used DCSI as a surrogate for type 2 diabetes severity, which usually increases with duration. Third, during the study period, SGLT-2is were contraindicated in people with impaired renal function (an eGFR <45 mL/min/1.73 m²). As the study had no access to eGFR, to address this we excluded people who had taken linagliptin, the preferred DPP-4i for use in renal impairment. It is also possible that there have been evolutions in SGLT-2i prescribing practices since 2018 and that clinicians may be more likely to prescribe SGLT-2i in patients at risk of renal failure now than in 2013–2018. Fourth, it is unclear if people took the medications as directed. Adherence to the use of SGLT-2 inhibitors and DPP-4 inhibitors was not measured; however, we are looking at protective effects, hence using an intention to treat analysis (not following up for adherence) is conservative. Fifth, the study was unable to ascertain whether people were dispensed SGLT-2is or DPP-4is outside of the PBS reimbursement system. However, non-PBS use is likely to have been rare due to higher costs to the patient. Finally, initiation of SGLT-2i or DPP-4is while in hospital for the index admission was not captured, and the date of first use could have been before the date of discharge. This could be a source of bias, in that people initiated while in hospital who have an acute kidney event while still in hospital, might have that medication withdrawn. Thus, the population of those who are discharged on the medication are enriched for people not at risk of an early acute kidney event.

The lack of specific clinical data, such as baseline renal function being not available, is a major limitation in analyzing the risk of kidney outcomes associated with medication usage. However, this is common for most studies using administrative data. Administrative data can still provide useful results without specific laboratory results. Perhaps future studies using electronic hospital records could address this.

There is a potential of under-reporting of comorbidities in our data, because hospital admission data captures only severe forms of the disease, or that these patients have different treatment approaches depending on their comorbidities. Using our two-pronged approach (both hospital coded diagnoses and medication dispensing) would be expected to be superior to using either one by itself.

One discrepancy is that heart failure prevalence is the same between groups; however, the proportions given heart failure drugs (such as aldosterone antagonist and digoxin) are different between groups. This could be due to the proportion that have heart failure with reduced ejection fraction compared to those with heart failure with preserved ejection fraction, where the treatment options are dramatically different. A limitation of the dataset is the specific type of heart failure is unavailable.

AUTHOR CONTRIBUTIONS

Kate E. D. Ziser, Stephen Wood, George S. Q. Tan, Jedidiah I. Morton, Jonathan E. Shaw, J. Simon Bell, and Jenni Ilomaki made substantial contributions to study conception and design, acquisition of data or analysis and interpretation of the data. J. Simon Bell and Jenni Ilomaki obtained grant funding. All authors drafted (Kate E. D. Ziser) or revised (Stephen Wood, George S. Q. Tan, Jedidiah I. Morton, Jonathan E. Shaw, J. Simon Bell, and Jenni Ilomaki) the article for important intellectual content. Kate E. D. Ziser, Stephen Wood, George S. Q. Tan, Jedidiah I. Morton, Jonathan E. Shaw, J. Simon Bell, and Jenni Ilomaki approved the final version to be published.

FUNDING INFORMATION

The authors gratefully acknowledge funding provided by the Dementia Australia Research Foundation – Yulgilbar Innovation Grant.

DISCLOSURE

J. Simon Bell has received grant funding or consulting funds from the National Health and Medical Research Council, Medical Research Future Fund, Victorian Government Department of Health and Human Services, Dementia Australia Research Foundation, Yulgilbar Foundation, Aged Care Quality and Safety Commission, Dementia Centre for Research Collaboration, Pharmaceutical Society of Australia, Society of Hospital Pharmacists of Australia, GlaxoSmithKline Supported Studies Programme, Amgen, and several aged care provider organizations unrelated to this work. All grants and consulting funds were paid to the employing institution. Jonathan E. Shaw has received honoraria for lectures and for advisory boards from: Astra Zeneca; Sanofi; Novo Nordisk; MSD; Eli Lilly; Pfizer; Roche; Mylan; Boehringer Ingelheim; Zuellig; Roche. Kate E. D. Ziser, George S. Q. Tan, Jedidiah I. Morton, and Stephen Wood have no relationships or activities to disclose. Jenni Ilomaki has received funding or consulting funds from the National Health and Medical Research Council, Medical Research Future Fund, Victorian Government Department of Health and Human Services, Dementia Australia Research Foundation, Yulgilbar Foundation, National Breast Cancer Foundation, Amgen, and AstraZeneca. All grants and consulting funds were paid to the employing institution.