ObjectiveWe assessed the effects of sodium glucose cotransporter-2 inhibitors (SGLT2is) versus dipeptidyl peptidase-4 inhibitors (DPP4is) in a large real-world Asian cohort with type 2 diabetes (T2D) and performed a systematic review with integrating the present study findings to provide up-to-date evidence from the Asian perspective.MethodsNew users of SGLT2is or DPP4is were identified from the Taiwan’s National Health Insurance Research Database and followed until 2018. Primary outcomes were hospitalization for heart failure (HHF) and three-point major adverse cardiovascular event (3P-MACE; namely, myocardial infarction [MI], stroke, or cardiovascular death). Other outcomes included all-cause death, chronic kidney disease (CKD), amputation, and hospitalized hypoglycemia. Subdistribution hazard models were employed to assess treatment-associated clinical outcomes.ResultsA total of 21,329 SGLT2i and DPP4i propensity-score-matched pairs were analyzed. SGLT2is versus DPP4is showed lower risks of HHF (hazard ratio [95% CI]: 0.52 [0.45–0.59]), 3P-MACE (0.62 [0.55–0.70]), MI (0.63 [0.50–0.79]), stroke (0.60 [0.51–0.70]), all-cause death (0.57 [0.49–0.67]), CKD (0.46 [0.43–0.50]), amputation (0.64 [0.42–0.98]), and hospitalized hypoglycemia (0.54 [0.45–0.64]). Our results were consistent with findings from a systematic review.ConclusionAmong Asian patients with T2D, SGLT2is versus DPP4is showed benefits for several clinical outcomes. More research is warranted to explore the heterogeneous treatment effects of SGLT2is and DPP4is by race/ethnicity.

Background: EMPEROR-Reduced trial provides promising evidence on the efficacy of empagliflozin adding to the standard treatment in patients with heart failure and reduced ejection fraction (HFrEF). This study aimed to investigate the cost-effectiveness of add-on empagliflozin vs. standard therapy alone in HFrEF from the perspective of the Asia-Pacific healthcare systems.Methods: A Markov model was constructed to simulate HFrEF patients and to project the lifetime direct medical costs and quality-adjusted life years (QALY) of both therapies. Transitional probabilities were derived from the EMPEROR-Reduced trial. Country-specific costs and utilities were extracted from published resources. Incremental cost-effectiveness ratio (ICER) against willingness to pay (WTP) threshold was used to examine the cost-effectiveness. A series of sensitivity analyses was performed to ensure the robustness of the results.Results: The ICERs of add-on empagliflozin vs. standard therapy alone in HFrEF were US$20,508, US$24,046, US$8,846, US$53,791, US$21,543, and US$20,982 per QALY gained in Taiwan, Japan, South Korea, Singapore, Thailand, and Australia, respectively. Across these countries, the probabilities of being cost-effective for using add-on empagliflozin under the WTP threshold of 3-times country-specific gross domestic product per capita were 93.7% in Taiwan, 95.6% in Japan, 96.3% in South Korea, 94.2% Singapore, 51.9% in Thailand, and 95.9% in Australia. The probabilities were reduced when shortening the time horizon, assuming the same cardiovascular mortality for both treatments, and setting lower WTP thresholds.Conclusion: Adding empagliflozin to HFrEF treatment is expected to be a cost-effective option among the Asia-Pacific countries. The cost-effectiveness is influenced by the WTP thresholds of different countries.

Background : Current evidence about the cardiovascular safety of glucagon-like peptide-1 receptor agonist (GLP-1ra) possesses limited generalizability to real-world patients with type 2 diabetes (T2D) in usual practice. This study aimed to investigate the comparative cardiovascular safety of GLP-1ra in head-to-head comparisons with dipeptidyl peptidase-4 inhibitor (DPP-4i), sulfonylurea (SU), and insulin in a real-world population with T2D. Methods : Adults with newly-diagnosed T2D were identified from Taiwan’s National Health Insurance Research Database in 2003-2014. A prevalent new-user cohort design was adopted to include a broad representation of real-world T2D patients being treated with GLP-1ra. The between-group comparability of baseline patient characteristics was achieved by matching on (1) initiation time of study drugs, (2) prior exposure to glucose-lowering agents, and (3) diabetes severity and complications, comorbidities, and concomitant cardiovascular medications using propensity scores. The primary outcome was a composite of cardiovascular disease (CVD) events and assessed up to the end of 2015. Cox modeling was employed to assess the association between study drugs and outcomes. Results : A total of 3,195 GLP-1ra stable users was identified in 2011-2014. 1,893, 1,829, and 1,367 GLP-1ra stable users were 1:1 matched to DPP-4i, SU and insulin users, respectively. Compared to DPP-4i, SU and insulin, the use of GLP-1ra was associated with a lower risk of composite CVD events (hazard ratio [95% confidence interval]: 0.73 [0.57-0.96], 0.76 [0.57-1.00], and 0.81 [0.62-1.07], respectively). Subgroup analyses revealed that GLP-1ra versus DPP-4i yielded a greater cardiovascular benefit in those without established CVD versus those with established CVD. Conclusions : This head-to-head comparison study extends the supporting evidence for the cardiovascular safety of GLP-1ra to a broad spectrum of real-world T2D patients using GLP-1ra.

ImportanceIncreasing numbers of post hoc analyses have applied restricted mean survival time (RMST) analysis on the aggregated-level data from clinical trials to report treatment effects, but studies that use individual-level claims data are needed to determine the feasibility of RMST analysis for quantifying treatment effects among patients with type 2 diabetes in routine clinical settings.ObjectivesTo apply RMST analysis for assessing sodium-glucose cotransporter-2 inhibitor (SGLT2i)–associated cardiovascular (CV) events and estimating heterogenous treatment effects (HTEs) on CV and kidney outcomes in routine clinical settings.Design, Setting, and ParticipantsThis comparative effectiveness study of Taiwan’s National Health Insurance Research Database examined 21 144 propensity score (PS)-matched pairs of patients with type 2 diabetes with SGLT2i and dipeptidyl peptidase-4 inhibitor (DPP4i) treatment for assessing CV outcomes, and 19 951 PS-matched pairs of patients with type 2 diabetes with SGLT2i and DPP4i treatment for assessing kidney outcomes. Patients were followed until December 31, 2018. Statistical analysis was performed from August 2021 to April 2022.ExposuresNewly stable SGLT2i or DPP4i use in 2017.Main Outcomes and MeasuresStudy outcomes were CV events including hospitalization for heart failure (HHF), 3-point major adverse CV events (3P-MACE: nonfatal myocardial infarction [MI], nonfatal stroke, and CV death), 4-point MACE (4P-MACE: HHF and 3P-MACE), and all-cause death, and chronic kidney disease (CKD). RMST and Cox modeling analyses were applied to estimate treatment effects on study outcomes.ResultsAfter PS matching, the baseline patient characteristics were comparable between 21 144 patients with stable SGLT2i use (eg, mean [SD] age: 58.3 [10.7] years; 11 990 [56.7%] male) and 21 144 patients with stable DPP4i use (eg, mean [SD] age: 58.1 [11.6] years; 12 163 [57.5%] male) for assessing CV outcomes, and those were also comparable between 19 951 patients with stable SGLT2i use (eg, mean [SD] age: 58.1 [10.7] years; 11 231 [56.2%] male) and 19 951 patients with stable DPP4i use (eg, mean [SD] age: 57.9 [11.5] years; 11 340 [56.8%] male) for assessing kidney outcome. The 2-year difference in RMST between patients with SGLT2i use and patients with DPP4i use was 4.99 (95% CI, 3.56-6.42) days for HHF, 4.12 (95% CI, 2.72-5.52) days for 3P-MACE, 7.72 (95% CI, 5.83-9.61) days for 4P-MACE, 1.26 (95% CI, 0.47-2.04) days for MI, 2.70 (95% CI, 1.57-3.82) days for stroke, 0.69 (95% CI, 0.28-1.11) days for CV death, 6.05 (95% CI, 4.89-7.20) days for all-cause death, and 14.75 (95% CI, 12.99-16.52) days for CKD. Directions of hazard ratios from Cox modeling analyses were consistent with RMST estimates. No association was found between study treatment and the negative control outcome (dental visits for tooth care). Consistent results across sensitivity analyses using high-dimensional PS-matched and PS-weighting approaches supported the validity of primary analysis results. Largest difference in RMST of SGLT2i vs DPP4i use for HHF and CKD was found among patients with established heart failure (30.80 [95% CI, 5.08-56.51] days) and retinopathy (40.43 [95% CI, 31.74-49.13] days), respectively.Conclusions and RelevanceIn this comparative effectiveness study, RMST analysis was feasible for translating treatment effects into more clinical intuitive estimates and valuable for quantifying HTEs among diverse patients in routine clinical settings.

Background Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models. Methods Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences. Results Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (−0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models ( P = 0.049). Conclusions Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions. Highlights The findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs). There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.