Model-based characterization of the relationship between dapagliflozin systemic exposure and HbA1c response in patients with type 1 diabetes mellitus

Sodium-glucose co-transporter protein 2 (SGLT2) inhibitors for people with chronic kidney disease and diabetes

BACKGROUND

Diabetes is associated with high risks of premature chronic kidney disease (CKD), cardiovascular diseases, cardiovascular death and impaired quality of life. People with diabetes are more likely to develop kidney impairment, and approximately one in three adults with diabetes have CKD. People with CKD and diabetes experience a substantially higher risk of cardiovascular outcomes. Sodium-glucose co-transporter protein 2 (SGLT2) inhibitors have shown potential effects in preventing kidney and cardiovascular outcomes in people with CKD and diabetes. However, new trials are emerging rapidly, and evidence synthesis is essential to summarising cumulative evidence.

OBJECTIVES

This review aimed to assess the benefits and harms of SGLT2 inhibitors for people with CKD and diabetes.

SEARCH METHODS

We searched the Cochrane Kidney and Transplant Register of Studies up to 17 November 2023 using a search strategy designed by an Information Specialist. Studies in the Register are continually identified through regular searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Registry Platform (ICTRP) Search Portal and ClinicalTrials.gov.

SELECTION CRITERIA

Randomised controlled studies were eligible if they evaluated SGLT2 inhibitors versus placebo, standard care or other glucose-lowering agents in people with CKD and diabetes. CKD includes all stages (from 1 to 5), including dialysis patients.

DATA COLLECTION AND ANALYSIS

Two authors independently extracted data and assessed the study risk of bias. Treatment estimates were summarised using random effects meta-analysis and expressed as a risk ratio (RR) or mean difference (MD), with a corresponding 95% confidence interval (CI). Confidence in the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. The primary review outcomes were all-cause death, 3-point and 4-point major adverse cardiovascular events (MACE), fatal or nonfatal myocardial infarction (MI), fatal or nonfatal stroke, and kidney failure.

MAIN RESULTS

Fifty-three studies randomising 65,241 people with CKD and diabetes were included. SGLT2 inhibitors with or without other background treatments were compared to placebo, standard care, sulfonylurea, dipeptidyl peptidase-4 (DPP-4) inhibitors, or insulin. In the majority of domains, the risks of bias in the included studies were low or unclear. No studies evaluated the treatment in children or in people treated with dialysis. No studies compared SGLT2 inhibitors with glucagon-like peptide-1 receptor agonists or tirzepatide. Compared to placebo, SGLT2 inhibitors decreased the risk of all-cause death (20 studies, 44,397 participants: RR 0.85, 95% CI 0.78 to 0.94; I2 = 0%; high certainty) and cardiovascular death (16 studies, 43,792 participants: RR 0.83, 95% CI 0.74 to 0.93; I2 = 29%; high certainty). Compared to placebo, SGLT2 inhibitors probably make little or no difference to the risk of fatal or nonfatal MI (2 studies, 13,726 participants: RR 0.95, 95% CI 0.80 to 1.14; I2 = 24%; moderate certainty), and fatal or nonfatal stroke (2 studies, 13,726 participants: RR 1.07, 95% CI 0.88 to 1.30; I2 = 0%; moderate certainty). Compared to placebo, SGLT2 inhibitors probably decrease 3-point MACE (7 studies, 38,320 participants: RR 0.89, 95% CI 0.81 to 0.98; I2 = 46%; moderate certainty), and 4-point MACE (4 studies, 23,539 participants: RR 0.82, 95% CI 0.70 to 0.96; I2 = 77%; moderate certainty), and decrease hospital admission due to heart failure (6 studies, 28,339 participants: RR 0.70, 95% CI 0.62 to 0.79; I2 = 17%; high certainty). Compared to placebo, SGLT2 inhibitors may decrease creatinine clearance (1 study, 132 participants: MD -2.63 mL/min, 95% CI -5.19 to -0.07; low certainty) and probably decrease the doubling of serum creatinine (2 studies, 12,647 participants: RR 0.70, 95% CI 0.56 to 0.89; I2 = 53%; moderate certainty). SGLT2 inhibitors decrease the risk of kidney failure (6 studies, 11,232 participants: RR 0.70, 95% CI 0.62 to 0.79; I2 = 0%; high certainty), and kidney composite outcomes (generally reported as kidney failure, kidney death with or without ≥ 40% decrease in estimated glomerular filtration rate (eGFR)) (7 studies, 36,380 participants: RR 0.68, 95% CI 0.59 to 0.78; I2 = 25%; high certainty) compared to placebo. Compared to placebo, SGLT2 inhibitors incur less hypoglycaemia (16 studies, 28,322 participants: RR 0.93, 95% CI 0.89 to 0.98; I2 = 0%; high certainty), and hypoglycaemia requiring third-party assistance (14 studies, 26,478 participants: RR 0.75, 95% CI 0.65 to 0.88; I2 = 0%; high certainty), and probably decrease the withdrawal from treatment due to adverse events (15 studies, 16,622 participants: RR 0.94, 95% CI 0.82 to 1.08; I2 = 16%; moderate certainty). The effects of SGLT2 inhibitors on eGFR, amputation and fracture were uncertain. No studies evaluated the effects of treatment on fatigue, life participation, or lactic acidosis. The effects of SGLT2 inhibitors compared to standard care alone, sulfonylurea, DPP-4 inhibitors, or insulin were uncertain.

AUTHORS' CONCLUSIONS

SGLT2 inhibitors alone or added to standard care decrease all-cause death, cardiovascular death, and kidney failure and probably decrease major cardiovascular events while incurring less hypoglycaemia compared to placebo in people with CKD and diabetes.

Effectiveness of dapagliflozin as an insulin adjunct in type 1 diabetes: a semi-mechanistic exposure-response model

Introduction: Dapagliflozin-induced improvement of glycemic control in patients with inadequately controlled type 1 diabetes (T1D) is complicated by the delicate balance between blood glucose and exogenous insulin. In this work, we developed a semi-mechanistic population exposure-response model using pooled patient-level data to characterize the joint effect of dapagliflozin and insulin on average daily glucose concentrations and glycated hemoglobin (HbA1c) levels in patients with T1D. Methods: A non-linear mixed-effects model was developed in Monolix (Lixoft, France) and R software (R Project, www.r-project.org) using pooled patient-level data from phase 2 and phase 3 trials (NCT01498185, NCT02460978, NCT02268214). Results: Because of the apparent lack of association between bolus insulin dose and glucose concentrations measured by continuous glucose monitoring the model was able to capture the quantitative link between basal, but not bolus, insulin dose and plasma glucose. Even so, this association remained flat, with a 50% decrease in the basal insulin dose from pretreatment level, resulting in ∼5% increase in glucose exposure. Therefore, dapagliflozin efficacy was not significantly affected by the insulin dose adjustment, with 24-week HbA1c reduction on 10-mg dapagliflozin treatment changing from -0.5 [95% CI: -0.55, -0.45] to -0.42 [95%CI: -0.48, -0.36] after adjustment. At the same time, the analysis revealed ∼2-fold steeper slope of glucose-HbA1c relationship in dapagliflozin-treated patients vs. control group, suggesting the presence of additional dapagliflozin treatment-related benefits, not explained by the dapagliflozin-mediated ∼4% increase in plasma hemoglobin levels. Finally, the efficacy of 5 and 10-mg doses, represented by the mean HbA1c reduction at week 24 of dapagliflozin treatment, was shown to be notably greater than the 1- and 2.5-mg doses. Discussion: This research is an attempt to deconvolute and reconstruct dapagliflozin-HbA1c dose-response relationship in T1D by accounting for the drug's action on both daily insulin dose and plasma glucose on a subject-level. While the model is able to adequately capture the observed data, it also revealed that the variability in CGM is poorly approximated by the variability in insulin dose alone. Furthermore, the slope of CGM/HbA1c relationship may differ depending on the population and treatment scenarios. As such, a deeper dive into the physiological mechanisms is required to better quantify the intricate network of glycemic response under dapagliflozin treatment.

A mechanistic modeling platform of SGLT2 inhibition: Implications for type 1 diabetes

Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by abnormally high blood glucose concentrations due to dysfunction of the insulin-producing beta-cells in the pancreas. Dapagliflozin, an inhibitor of renal glucose reabsorption, has the potential to improve often suboptimal glycemic control in patients with T1DM through insulin-independent mechanisms and to partially mitigate the adverse effects associated with long-term insulin administration. In this work, we have adapted a systems pharmacology model of type 2 diabetes mellitus to describe the T1DM condition and characterize the effect of dapagliflozin on short- and long-term glycemic markers under various treatment scenarios. The developed platform serves as a quantitative tool for the in silico evaluation of the insulin-glucose-dapagliflozin crosstalk, optimization of the treatment regimens, and it can be further expanded to include additional therapies or other aspects of the disease.

Therapeutic effect and rebound evaluation of dapagliflozin on glycated hemoglobin (HbA1c) in type 1 diabetes mellitus patients

Dapagliflozin has been used to treat patients with type 1 diabetes mellitus; however, the actual drug efficacy of dapagliflozin on glycated hemoglobin (HbA1c) and whether there is a rebound from dapagliflozin efficacy on HbA1c remain unknown. The present study aimed to explore the actual therapeutic effect and rebound situation of dapagliflozin on HbA1c in type 1 diabetes mellitus patients. A total of 1,594 type 1 diabetes mellitus patients were enrolled for analysis using a non-linear mixed effect model from randomized controlled trials from published literature works including two 5 mg/day dapagliflozin dosage groups and three 10 mg/day dapagliflozin dosage groups. The change rate of HbA1c from a baseline value was chosen as a dapagliflozin pharmacodynamic evaluation index. After deducting control group effects, the therapeutic effect of 5 and 10 mg/day dapagliflozin on HbA1c in type 1 diabetes mellitus patients had no significant difference. In addition, the actual maximal efficacy (AE_max) of dapagliflozin on HbA1c was -6.24% at week 9. When it reached the AE_max, the dapagliflozin pharmacodynamic rebound on HbA1c occurred, and when the treatment was continued for 0.5 and 1 year, the actual efficacies were -4.70% (75% AE_max) and -3.27% (52% AE_max), respectively. This was the first time to clarify the actual therapeutic effect and rebound situation of dapagliflozin on HbA1c in type 1 diabetes mellitus patients, providing a reference value for clinical practices.

Effects of Sodium-Glucose Cotransporter-2 Inhibitors on Urine Albumin to Creatinine Ratio in Type 2 Diabetes Mellitus Patients and Medication Care

OBJECTIVES

The purpose of this study was to explore the effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors on urine albumin to creatinine ratio (UACR) in type 2 diabetes mellitus (T2DM) patients and to recommend appropriate medication care scheme.

METHODS

8371 T2DM patients from four dapagliflozin studies and two canagliflozin studies were collected for analyzing with nonlinear mixed effect model (NONMEM). The change rates of UACR from baseline were intended to be evaluation indicators.

RESULTS

In the present study, there was no significant difference in the effects on UACR using dapagliflozin or canagliflozin treatment in T2DM patients. The maximal effect (E _max) and the treatment duration of reaching half of E _max (ET₅₀) from SGLT-2 inhibitors on UACR in T2DM patients were -19.2% and 0.448 weeks, respectively. Further, the treatment duration to reach 25%, 50%, 75%, and 80% E _max was 0.150 weeks, 0.448 weeks, 1.344 weeks, and 1.792 weeks, respectively. Namely, for achieving the plateau period (80% of E _max) of SGLT-2 inhibitors on UACR in T2DM patients, 10 mg/day dapagliflozin (or 100 mg/day canagliflozin) should be taken for at least 1.792 weeks.

CONCLUSIONS

To our knowledge, the present study explored the effects of SGLT-2 inhibitors on UACR in T2DM patients, meanwhile, recommended appropriate medication care scheme for the first time.

Model-based characterization of the relationship between dapagliflozin systemic exposure and HbA1c response in patients with type 1 diabetes mellitus

AIMS

To quantitatively describe the relationship between dapagliflozin systemic exposure and HbA1c response among patients with type 1 diabetes mellitus (T1DM) and assess the potential impact of covariate effects.

MATERIALS AND METHODS

Individual longitudinal HbA1c data from two phase 3 studies in patients with T1DM (24-week treatment with once-daily dapagliflozin 5 or 10 mg or placebo, with adjustable insulin) were analyzed using a non-linear mixed effect modeling approach. Area under the concentration curve was used to measure dapagliflozin systemic exposure. Baseline HbA1c, estimated glomerular filtration rate, reduction in total insulin dose, baseline glucose concentrations, age, sex, race (Asian vs. non-Asian), and insulin administration method (multiple daily injections vs. insulin pump) were assessed as covariates.

RESULTS

A maximum effect (Emax ) model identified a positive exposure-response relationship. Model-predicted placebo-corrected HbA1c reductions after 24 weeks for dapagliflozin 5- and 10-mg doses were - 0.42% [95% confidence interval (CI) -0.47 to -0.36) and - 0.45% (95% CI -0.50 to -0.40), respectively; baseline HbA1c was ~8.4%. This was in good agreement with actual observations from both studies. Baseline HbA1c was a significant covariate: patients with higher baseline HbA1c were predicted to have greater HbA1c reductions.

CONCLUSIONS

The relationship between dapagliflozin systemic exposure and HbA1c response was successfully described in patients with T1DM. None of the tested covariates affected the efficacy of dapagliflozin to a clinically relevant extent. Therefore, no dose adjustment of dapagliflozin is required in patients with T1DM based on the tested covariates. ClinicalTrials.gov, NCT02268214; NCT02460978.