Effect of Sitagliptin on Kidney Function and Respective Cardiovascular Outcomes in Type 2 Diabetes: Outcomes From TECOS

Patients with type 2 diabetes mellitus are at high risk for macrovascular and microvascular complications (1), with type 2 diabetes being a key risk factor for the development of chronic kidney disease (CKD). CKD further increases the risk of adverse cardiovascular (CV) outcomes, especially in patients with known CV disease (2–5), and both microalbuminuria and macroalbuminuria are associated independently with an increased risk of CV events (6). Accordingly, the potential impact of type 2 diabetes therapies on CV and CKD outcomes is a major consideration in the long-term management strategy of the disease. Intensified glucose control and multiple CV risk factor therapies can reduce CV risk in general, and diabetic nephropathy in particular (7,8), but there is a paucity of data on the effectiveness of specific type 2 diabetes treatment regimens with regard to these two outcomes.

The Trial Evaluating Cardiovascular Outcomes With Sitagliptin (TECOS) (9) showed that adding sitagliptin, compared with placebo, to usual care in patients with type 2 diabetes and established CV disease did not have an impact on the risk of major CV outcomes, hospitalization for heart failure, or adverse events in general. The aim of the present post hoc analysis was to evaluate CV and CKD outcomes in TECOS participants with type 2 diabetes and CV disease when treated with sitagliptin, a dipeptidyl peptidase 4 inhibitor (DPP-4i), according to their baseline estimated glomerular filtration rate (eGFR) stage.

The rationale and design of TECOS (10), as well as its primary outcomes and safety measures (9), have been reported. Briefly, 14,735 participants from 38 countries were enrolled in the study between December 2008 and July 2012. Eligible participants were ≥50 years old with type 2 diabetes, established atherosclerotic CV disease, and HbA_1c values in the range 6.5–8.0% (48–64 mmol/mol) and were receiving stable-dose monotherapy or dual-combination therapy with metformin, pioglitazone, or sulfonylurea, or insulin with or without metformin. Patients with eGFR values <30 mL/min/1.73 m² were excluded from the study.

Participants were randomized in a double-blind manner to receive sitagliptin 100 mg/day or placebo, with a lower dose of 50 mg/day for those with eGFR values 30–50 mL/min/1.73 m². During the study, sitagliptin doses were adjusted, based on at least annual eGFR values, to 50 mg/day if eGFR values were 30–50 mL/min/1.73 m² and to 25 mg/day if eGFR values were <30 mL/min/1.73 m². If a sustained eGFR recovery occurred, sitagliptin doses could also be up-titrated.

Treatment for type 2 diabetes and its comorbidities was provided by usual care providers, based on local guidelines. Any other glucose-lowering agent could be added, except for a glucagon-like peptide 1 receptor agonist or an open-label DPP-4i, with rosiglitazone use discouraged.

The study was managed and all data were adjudicated and analyzed by academic partners (Duke Clinical Research Institute and the University of Oxford Diabetes Trials Unit). The database was held at and independently verified by the Duke Clinical Research Institute.

An independent clinical events committee, blinded to treatment allocation, adjudicated all events of death, myocardial infarction (MI), stroke, hospitalization for unstable angina, and hospitalization for heart failure (10). The clinical events committee, which was independent of both the sponsor and the TECOS Executive Committee, remained blinded to study treatment assignment. The primary CV composite outcome was a 4-point major adverse CV event (MACE), defined as time to CV death, nonfatal MI, nonfatal stroke, or hospitalization for unstable angina.

Kidney function during the trial was assessed by annual usual care measurements of eGFR, calculated using the Modification of Diet in Renal Disease Study Equation (11). For a subset of participants, usual care urinary albumin-to-creatinine ratio (UACR) measurements were also available.

Participants were categorized at baseline into eGFR stages 1, 2, 3a, and 3b (≥90, 60–89, 45–59, and 30–44 mL/min/1.73 m², respectively) (12) and into three UACR groups according to their baseline values (normoalbuminuria <30 mg/g, microalbuminuria 30–300 mg/g, and macroalbuminuria >300 mg/g). Baseline characteristics for the intention-to-treat (ITT) population were summarized as mean (± 1 SD) or median (25th, 75th percentile) for quantitative data and as percentages for categorical data.

Separate Kaplan-Meier plots for the primary 4-point MACE outcome were created for each eGFR stage, split by assigned study treatment or by HbA_1c level above or below the median. Possible associations between CV outcomes and the CKD stage or the UACR category were evaluated using Cox proportional hazards regression models, with region included as a stratification variable and adjustment covariates taken from models developed previously for the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) trial (13–15). Less than 4% of the adjustment variables had missing values apart from LDL cholesterol (24%), hemoglobin (34%), and UACR (65%). For modeling purposes, missing baseline data were imputed using SAS PROC MI (SAS Institute, Cary, NC). CV outcome rates are presented as the total number of events and as events/100 patient-years of follow-up. Adjusted hazard ratios and 95% CIs are presented for each of eGFR stages 2–3b, with stage 1 as the reference group. Models were repeated with the addition of the treatment-by-eGFR interaction.

Kidney-related outcomes included changes from baseline in eGFR and UACR, as specified in the TECOS protocol and statistical analysis plan (9). Repeated-measures ANOVA was used to test for between-treatment group eGFR and UACR differences over 4 years, with the overall difference summarized as the least squares mean difference and 95% CI. Overall least squares mean differences are presented for all patients and separately for each eGFR stage, with P values for the treatment group-by-eGFR stage interaction. Models were adjusted for region, baseline eGFR or UACR, and for study visit. The model for the association between treatment and eGFR changes over 4 years was also performed with adjustment for baseline HbA_1c level and change in HbA_1c level from baseline to each visit.

Data were analyzed with SAS version 9.4. P values <0.05 were considered to be statistically significant, with no adjustments made for multiple testing.

The ITT population comprised 14,671 participants with a median follow-up time of 3.0 years (range 2.3–3.8 years, maximum 5.7 years). Overall, 95.1% and 94.1% of participants, respectively, allocated to receive sitagliptin and placebo completed the study, with 26.1% and 27.5%, respectively, discontinuing study medication prematurely. Vital status was determined at study end for 97.5% of participants.

Baseline eGFR measurements were available for 14,525 of the 14,671 ITT participants, categorized as stage 1 (3,325, 22.9%), stage 2 (7,879, 54.2%), stage 3a (2,538, 17.5%), and stage 3b (783, 5.4%). The 146 participants not included in the study comprised 143 with missing baseline eGFR values and 3 with eGFR values <30 mL/min/1.73 m², which did not meet the TECOS eGFR exclusion criterion. Participant baseline characteristics by eGFR stage are presented in Supplementary Table 1. Participants with eGFR stage 3b were older, were more frequently were women, had a longer duration of diabetes, tended to have a higher UACR, and were more likely to have a history of heart failure and to be receiving treatment with insulin or diuretic agents but were less likely to be current smokers or receiving metformin treatment. For eGFR outcome analyses, a subset of 13,604 participants with at least one postbaseline eGFR measurement was used (93% of 14,671 participants).

Baseline UACR measurements were available for 5,148 of the 14,671 ITT participants, who were categorized as having normoalbuminuria (3,701, 71.9%), microalbuminuria (1,200, 23.3%), or macroalbuminuria (247, 4.8%). For UACR outcome analyses, a subset of 3,832 participants (26% of 14,671 participants) with baseline UACR and eGFR measurements and at least one postbaseline UACR measurement was used.

Table 1 shows CV outcomes by baseline eGFR stage. Rates for the primary 4-point MACE outcome increased with lower eGFR values (3.52, 3.55, 5.74, and 7.34 events/100 patient-years, respectively, for stages 1–3b). The corresponding adjusted hazard ratios, with stage 1 as the reference stage, were 0.93 (95% CI 0.82–1.06), 1.28 (1.10–1.49), and 1.39 (1.13–1.72), respectively. Rates increased similarly for the secondary 3-point MACE outcome (CV death, nonfatal MI, or nonfatal stroke) and all other secondary outcomes, except for hospitalization for unstable angina. There were no significant interactions (all P > 0.44) between continuous eGFR measurements and randomized treatment allocation (Supplementary Table 2).

Sitagliptin treatment did not have an impact on the primary 4-point MACE outcome irrespective of baseline eGFR stage, as shown by Kaplan-Meier curves (Supplementary Fig. 1). Lower event rates were seen in those participants who had within-study HbA_1c values below the median, compared with those with HbA_1c values greater than the median (Supplementary Fig. 2).

Table 2 shows the CV outcomes by baseline UACR category. CV outcomes worsened with increasing albuminuria, except for 4-point MACE, MI, stroke, and hospitalization for unstable angina. The modeled impact of continuous baseline eGFR and UACR values on the 4-point MACE primary outcome are shown in Supplementary Fig. 3. Rates increase substantially with eGFR values <60 mL/min/1.73 m² and with UACR values >30 mg/g.

The mean eGFR reduction over 4 years from baseline was greater in the sitagliptin group than in the placebo group (−4.0 ± 18.4 vs. −2.8 ± 18.3 mL/min/1.73 m²). The mean eGFR value was marginally lower in the sitagliptin group at the first postrandomization visit and remained consistently lower thereafter (Fig. 1A), with an overall estimated least squares mean difference of −1.34 mL/min/1.73 m² (95% CI −1.76 to −0.91, P < 0.001) (Table 3). The 4-year between-treatment group differences were similar for each eGFR stage, with no significant interactions of treatment effect by eGFR stage (Table 3 and Supplementary Fig. 4). The slight eGFR difference between treatment groups remained after adjusting for time from randomization when eGFR was measured, baseline eGFR, baseline HbA_1c level, change in HbA_1c level over time, and region (Supplementary Table 3), with an estimated overall mean difference of −1.43 mL/min/1.73 m² (95% CI −1.88 to −0.98, P < 0.0001).

In the subset of participants with UACR data, the median value was marginally and consistently lower in the sitagliptin group compared with the placebo group (Fig. 1B), with an estimated overall mean difference of −0.18 mg/g (95% CI −0.35 to −0.02, P = 0.031) (Table 3). The 4-year UACR between-treatment group differences were similar for each eGFR stage, with no significant interactions of treatment effect by eGFR stage (Table 3).

TECOS was a global clinical trial demonstrating that the addition of sitagliptin to usual care in patients with type 2 diabetes and established CV disease did not affect rates of major atherosclerotic CV events in a setting of glycemic equipoise. This study shows that, although CV events are more frequent in patients with lower levels of kidney function, there is no interaction with the addition of sitagliptin. Kidney function declined at the same rate in both the sitagliptin and placebo groups, but with a slightly lower and constant eGFR difference in those assigned to receive sitagliptin.

The primary 4-point MACE outcome rate was progressively higher in participants with lower eGFR levels, as was the 3-point MACE outcome rate in those with an increased UACR. These data confirm earlier observational studies in which both eGFR and albuminuria have been shown to be independently associated with increased mortality and morbidity (3). Interestingly, the rise in the rate of the primary 4-point MACE outcome starts with a UACR as low as 30 mg/g, emphasizing albuminuria as a strong predictor of risk, as shown previously by Matsushita et al. (16). As would be expected, TECOS participants with reduced baseline kidney function were less likely to be taking metformin and were more often receiving insulin therapy, but with no difference in the rates of sulfonylurea use. Despite the varying glucose-lowering strategies, sitagliptin therapy had no effect on the primary 4-point MACE outcome at any eGFR or UACR level and thus appears to be safe with respect to CV outcomes in patients with decreased kidney function.

Although the mean eGFR during the trial was marginally lower in the sitagliptin group compared with the placebo group, even when adjusted for glycemic control, the eGFR decline was the same. Mean UACR values were also marginally lower with sitagliptin than with placebo in the 26% of TECOS participants who had these data available. It is uncertain whether these small offsets in eGFR and UACR would have any long-term clinical implications. Similar observations of a decrease in UACR have been made in post hoc pooled analyses of phase 3 DPP-4i studies using linagliptin (17). Animal studies (18) in streptozotocin-induced diabetic rats found that DPP-4i treatment improved albuminuria, with similar improvements in creatinine clearance. Although microalbuminuria rates can be reduced by improving glucose control (19), the minimal effects of sitagliptin on eGFR and UACR appear to be unrelated to its glucose-lowering effects since they are not explained by baseline HbA_1c levels or HbA_1c level changes during the trial. Although the small eGFR offset occurs early and is s1 over time for all GFR categories, there is no evidence of progression, and the offset appears to be similar for other DPP-4i agents as well (20).

TECOS did not show a clinically relevant improvement of kidney outcomes in patients treated with sitagliptin. Microvascular complication rates are related to HbA_1c levels (21), and can be reduced with improved glycemic control (22,23), but in TECOS there was only a small difference in HbA_1c levels between treatment groups because the study aimed to achieve glycemic equipoise in order to minimize possible glycemic confounding effects on the outcomes of interest. The decline of kidney function in individuals with diabetes is often, but not always, preceded by glomerular hyperfiltration, possibly as early as the stage of impaired fasting glucose (24). Glomerular hyperfiltration is associated with high glucose levels and changes in tubuloglomerular feedback related to alterations in vasoactive mediators, such as nitric oxide and cyclooxygenase-2–derived prostanoids, resulting in glomerular hypertension. These changes contribute to the inflammatory nature of diabetes, which affects the vasculature and is directly associated with the genesis of microalbuminuria. Ultimately, in a subgroup of people, there is a decline in kidney function, with some individuals progressing to end-stage renal disease (25,26). Early studies (26,27) suggested that microalbuminuria was a predictor of faster declines in kidney function, but over the past decade the data clearly indicate it is a marker of increased CV disease risk in various pathophysiologic conditions, such as diabetes.

The strength of the current study was the large number of patients studied in a double-blind prospective manner. Limitations include the fact that follow-up may be relatively short for evaluating the risk of the development of diabetic nephropathy, especially in view of the biphasic change in GFR with initial hyperfiltration followed by a decrease in GFR. Furthermore, no differences were taken into account for eGFR stage 1 and CKD stage 1, in which microalbuminuria must be present and which may be a somewhat different class of patients.

Reduced eGFR and increased UACR were associated with a significantly increased risk of CV events, but we observed no clinically significant effect of sitagliptin treatment on CV outcomes or CKD progression in patients with different CKD categories at baseline.

Acknowledgments. The authors thank the investigators, staff, and participants in the TECOS trial without whose efforts and collaboration this work would not have been possible. The authors also thank the following academic partners and contract research organizations for their assistance: Parexel International, Jubilant Clinsys, Clinogent, Canadian VIGOUR Centre, Green Lane Coordinating Centre, and South Australian Health and Medical Research Institute.

Funding. Funded by Merck Sharp & Dohme, a subsidiary of Merck and Co., Inc.

Duality of Interest. J.H.C. has received personal fees from Merck and Co., Inc., Eli Lilly, and AstraZeneca. G.L.B. reports serving as consultant for Merck and Co., Inc., Bayer, Boehringer Ingelheim, AbbVie, Janssen, NxStage, AstraZeneca, and Sanofi. S.S.E. is an employee of Merck Sharp & Dohme., a subsidiary of Merck & Co., Inc., the manufacturer of sitagliptin. R.D.L. reports receiving research grants from Bristol-Myers Squibb and GlaxoSmithKline and serving as a consultant for Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Merck and Co., Inc., Pfizer, and Portola. D.K.M. has received personal fees from Boehringer Ingelheim, Janssen Research and Development LLC, Sanofi Group, Merck Sharp & Dohme, Daiichi Sankyo, Inc., Lilly USA, Novo Nordisk, GlaxoSmithKline, Takeda Pharmaceuticals North America, AstraZeneca, Lexicon, Regeneron, University of Oxford, Duke Clinical Research Institute, Partners Healthcare, and the Cleveland Clinic Foundation. H.W.R. conducts clinical trials, lectures, and serves on advisory boards for AstraZeneca, Boehringer Ingelheim, Janssen, Lilly, Merck and Co., Inc., Novo Nordisk, Sanofi, and Regeneron. I.S. has received grants, personal fees, and support from Merck and Co., Inc., AstraZeneca, Janssen, Boehringer Ingelheim, Novartis, Novo Nordisk, GlaxoSmithKline, and Servier. T.T. has received lecture fees and serves on advisory boards for Merck and Co., Inc., Boehringer Ingelheim, Novo Nordisk, Sanofi, Eli Lilly, Novartis, Servier, and AstraZeneca. J.W. reports serving as a consultant for AstraZeneca, Novo Nordisk, Eli Lilly, Novartis, Boehringer Ingelheim, and Sanofi. E.D.P. has received grants and personal fees from Janssen, grants from Eli Lilly, and personal fees from AstraZeneca, Bayer, and Sanofi. R.R.H. has received grants and personal fees from Merck and Co., Inc.; grants from Bayer and AstraZeneca; personal fees from Amgen, Bayer, Intarcia, Novartis, and Novo Nordisk; and other support from GlaxoSmithKline, Janssen, and Takeda. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. J.H.C. and W.A.B. drafted and edited the manuscript. G.L.B., M.A., L.-M.C., R.D.L., A.R., H.W.R., I.S., T.T., and J.W. edited the manuscript. S.R.S. performed the statistical analyses and edited the manuscript. S.S.E., D.K.M., and E.D.P. edited the manuscript and contributed to the study design and the data analysis and interpretation. R.R.H. drafted and edited the manuscript and contributed to the study design and data analysis and interpretation. R.R.H. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented in abstract form at the 75th Scientific Sessions of the American Diabetes Association, Boston, MA, 5–9 June 2015; the 51st EASD Annual Meeting, Stockholm, Sweden, 14–18 September 2015; and the Scientific Programme of the World Diabetes Congress 2015, Vancouver, British Columbia, Canada, 30 November–4 December 2015.