Comparative cost-effectiveness of metformin-based dual therapies associated with risk of cardiovascular diseases among Chinese patients with type 2 diabetes: Evidence from a population-based national cohort in Taiwan

Antidiabetic potency of glimepiride and naringin: an in silico and in vitro investigation

Glimepiride (GLM) is one of the potential antidiabetic drugs used in clinics for a long time. It is currently used in combination with metformin along with other drugs, but has shown various complications in patients from long-term use. Thus, the hypothesis is to use a lower dose of GLM with a non-toxic class of flavonoid, naringin (NARN), for better therapy with minimal side-effects. Initially, we assessed the binding efficacy of GLM and NARN against nine putative target enzymes using AutoDock 4.2 software. We also analysed the drug chemistry, drug-ability, and cytotoxicity, as well as performed molecular dynamic (MD) simulation at 100 ns with individual and combination states using GROMACS-2022 software. Both candidates showed higher binding efficacy, especially against the AKT-serine/threonine kinase-1 (AKT1) target enzyme (-11.85 kcal/mol), and demonstrated higher stability and compatibility with AKT1 from MD-simulation (based on RMSD, Rg, RMSF, and H-bond plots) in combination than individual form. The in vitro cytotoxicity with human embryonic kidney (HEK-293) cells suggested 100 µg/mL (observed 80% of the cell viability) as a non-toxic dose for further study. Alpha-amylase, alpha-glucosidase, and DPP-IV inhibition assays revealed that both GLM and NARN inhibited up to 60% at 100 µg/mL in a concentration-dependent manner. At the end, selecting a lower dose of GLM and a higher dose of NARN (2:8 v/v ratio) showed up to 87% inhibition at 100 µg/mL. Both in silico and in vitro studies suggest that the investigated formulation could be a potential and non-toxic dose for diabetics.

Sponsorship bias in published pharmacoeconomic evaluations of national reimbursement negotiation drugs in China: a systematic review

BACKGROUND

China's National Reimbursement Drug List (NRDL) has become the primary route for drug reimbursement in China. More recently, the authority has made pharmacoeconomic evaluation an integral part of the application for NRDL inclusion. The underlying financial conflict of interests (FCOI) of pharmacoeconomic evaluations, however, has the potential to influence evidence generated and thus subsequent decision-making yet remains poorly understood.

METHODS

We searched for studies published between January 2012 and January 2022 on the 174 drugs added to the 2017-2020 NRDLs after successful negotiation. We categorised the study's FCOI status into no funding, industry funding, non-profit funding and multiple fundings based on authors' disclosure and assessed the reporting quality of included studies using the Consolidated Health Economic Evaluation Reporting Standards 2022 checklist. We compiled descriptive statistics of funding types and study outcomes using t-tests and χ2 tests and conducted multivariate regression analysis.

RESULTS

We identified 378 records and our final sample included 92 pharmacoeconomic evaluations, among which 69.6% were conducted with at least one funding source. More than half (57.6%) of the evaluations reached favourable conclusions towards the intervention drug and 12.6% reached a dominant result of the intervention drug over the comparison from model simulation. The reporting quality of included studies ranged from 19 to 25 (on a scale of 28), with an average of 22.3. The statistical tests indicated that industry-funded studies were significantly more likely to conclude that the intervention therapy was economical (p<0.01) and had a significantly higher proportion of resulting target drug economically dominated the comparison drug (p<0.05).

CONCLUSION

The study revealed that FCOI bias is common in published pharmacoeconomic evaluations conducted in Chinese settings and could significantly influence the study's economical results and conclusions through various mechanisms. Multifaceted efforts are needed to improve transparency, comparability and reporting standardisation.

Three-step matching algorithm to enhance between-group comparability and minimize confounding in comparative effectiveness studies

We developed a three-step matching algorithm to enhance the between-group comparability for comparative drug effect studies involving prevalent new-users of the newer study drug versus older comparator drug(s). The three-step matching scheme is to match on: (1) index date of initiating the newer study drug to align the cohort entry time between study groups, (2) medication possession ratio measures that consider prior exposure to all older comparator drugs, and (3) propensity scores estimated from potential confounders. Our approach is illustrated with a comparative cardiovascular safety study of glucagon-like peptide-1 receptor agonist (GLP-1ra) versus sulfonylurea (SU) in type 2 diabetes patients using Taiwan’s National Health Insurance Research Database 2003–2015. 66% of 3195 GLP-1ra users had previously exposed to SU. The between-group comparability was well-achieved after implementing the matching algorithm (i.e., standardized mean difference < 0.2 for all baseline patient characteristics). Compared to SU, the use of GLP-1ra yielded a significantly reduced risk of the primary composite cardiovascular events (hazard ratio [95% confidence interval]: 0.71 [0.54–0.95], p = 0.022). Our matching scheme can enhance the between-group comparability in prevalent new-user cohort designs to minimize time-related bias, improve confounder adjustment, and ensure the reliability and validity of study findings.

Big Data and Real-World Data based Cost-Effectiveness Studies and Decision-making Models: A Systematic Review and Analysis

Background: Big data and real-world data (RWD) have been increasingly used to measure the effectiveness and costs in cost-effectiveness analysis (CEA). However, the characteristics and methodologies of CEA based on big data and RWD remain unknown. The objectives of this study were to review the characteristics and methodologies of the CEA studies based on big data and RWD and to compare the characteristics and methodologies between the CEA studies with or without decision-analytic models. Methods: The literature search was conducted in Medline (Pubmed), Embase, Web of Science, and Cochrane Library (as of June 2020). Full CEA studies with an incremental analysis that used big data and RWD for both effectiveness and costs written in English were included. There were no restrictions regarding publication date. Results: 70 studies on CEA using RWD (37 with decision-analytic models and 33 without) were included. The majority of the studies were published between 2011 and 2020, and the number of CEA based on RWD has been increasing over the years. Few CEA studies used big data. Pharmacological interventions were the most frequently studied intervention, and they were more frequently evaluated by the studies without decision-analytic models, while those with the model focused on treatment regimen. Compared to CEA studies using decision-analytic models, both effectiveness and costs of those using the model were more likely to be obtained from literature review. All the studies using decision-analytic models included sensitivity analyses, while four studies no using the model neither used sensitivity analysis nor controlled for confounders. Conclusion: The review shows that RWD has been increasingly applied in conducting the cost-effectiveness analysis. However, few CEA studies are based on big data. In future CEA studies using big data and RWD, it is encouraged to control confounders and to discount in long-term research when decision-analytic models are not used.

Comparative cardiovascular safety of GLP-1 receptor agonists versus other glucose-lowering agents in real-world patients with type 2 diabetes: a nationwide population-based cohort study

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 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 3195 GLP-1ra stable users was identified in 2011-2014. 1893, 1829, and 1367 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 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.

Review of the cardiovascular safety of dipeptidyl peptidase-4 inhibitors and the clinical relevance of the CAROLINA trial

BACKGROUND

Cardiovascular (CV) disease (CVD) is a well-recognized complication of type 2 diabetes mellitus (T2DM) and there is a clinical need for glucose-lowering therapies that do not further increase CV risk in this population. Although sulfonylureas (SUs) may be used as second-line therapy for patients requiring additional therapy after first-line metformin to improve glycemic control, their long-term effects on CV outcomes remain uncertain, and a wide range of alternative agents exist including dipeptidyl peptidase-4 (DPP-4) inhibitors.

METHODS

Literature searches in PubMed (2013-2018) were conducted with terms for DPP-4 inhibitors combined with CV terms, with preference given to cardiovascular outcomes trials (CVOTs). Reference lists from retrieved articles and diabetes guidelines were also considered.

RESULTS

This narrative review discusses current evidence for the CV safety of these agents, describes the long-term CV effects of DPP-4 inhibitors, including effects on CV events, mortality, the risk for heart failure hospitalization, and highlights the need for further research into the CV effects of SU therapy. Although SUs remain a treatment option for T2DM, the long-term effects of these agents on CV outcomes are unclear, and further long-term studies are required. For DPP-4 inhibitors, uncertainties have been raised about their long-term effect on hospitalization for heart failure in light of the results of SAVOR-TIMI 53, although the findings of other DPP-4 inhibitor CVOTs in T2DM and data analyses have suggested these agents do not increase the occurrence of adverse CV outcomes.

CONCLUSIONS

Based on recent CVOTs and guideline updates, the choice of add-on to metformin therapy for patients with T2DM and established CV disease should be a sodium-glucose co-transporter-2 inhibitor or a glucagon-like peptide-1 agonist with proven CV benefit. Additional treatment options for those individuals who require therapy intensification, as well as in patients with T2DM and without established CVD include DPP-4 inhibitors and SUs. Since few head-to-head trials have compared the effects of different oral glucose-lowering agents on CV outcomes in T2DM, with most CVOTs using placebo as a comparator, the CAROLINA trial will provide important information on the comparative CV safety of a commonly prescribed SU and a DPP-4 inhibitor.

Short-term air pollution exposure is associated with hospital length of stay and hospitalization costs among inpatients with type 2 diabetes: a hospital-based study

Air pollution is a risk factor for type 2 diabetes (T2D), exerting heavy economic burden on both individuals and societies. However, there is no apparent report regarding the influence of air pollutants such as particulate matter (PM_2.5 and PM₁₀), sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), and ozone (O₃) on financial burden to individuals and societies suffering from T2D. This study aimed to determine whether short-term (no more than 16 d) air pollution exposure was associated with T2D-related length of stay (LOS) and hospitalization expenses incurred by patients. This investigation examined 2840 T2D patients hospitalized from December 17, 2013 to May 31, 2016 in China. Multiple linear regression analysis was applied to determine the association between short-term (no more than 16 d) ambient air pollution, LOS, and hospitalization expenses, controlling for age, gender, ethnicity, marital status, and weather conditions. Sulfur dioxide (SO₂) and carbon monoxide (CO) were significantly positively while nitrogen dioxide (NO₂) was negatively associated with presence of T2D, LOS, and expenses. A 10-μg/m³ rise in 16-d (lag 0-15) average concentrations of SO₂ and CO prior to hospitalization was correlated with a significant elevation in LOS and elevation in expenses in T2D patients. However, a 10-μg/m³ rise in 16-d average NO₂ was associated with marked negative alterations in LOS and hospital costs in T2D patients. Taken together, data demonstrate that exposure to air pollutants impacts differently on LOS and hospitalization costs for T2D patients. This is the first apparent report regarding the correlation between air pollution exposure and clinical costs of T2D in China. It is of interest that air pollutants affected T2D patients differently as evidenced by LOS and clinical expenses where SO₂ and CO exhibited a positive adverse relationship in contrast to NO₂.

Incidence of diabetes-related complications in Chinese patients with type 1 diabetes: a population-based longitudinal cohort study in Taiwan

OBJECTIVE

To estimate the incidence densities and cumulative incidence of diabetes-related complications in patients with type 1 diabetes for a maximum of 15-year follow-up. The estimations were further stratified by gender and age at diagnosis (ie, early onset: 0-12 years, late onset:≥13 years).

DESIGN

A population-based retrospective longitudinal cohort study.

SETTING

Taiwan's National Health Insurance medical claims.

PARTICIPANTS

4007 patients newly diagnosed with type 1 diabetes were identified during 1999-2012.

OUTCOME MEASURES

Acute complications included diabetic ketoacidosis (DKA) and hypoglycaemia. Chronic complications were cardiovascular diseases (CVD), retinopathy, neuropathy and nephropathy.

RESULTS

The incidence density of retinopathy was greatest (97.74 per 1000 person-years), followed by those of nephropathy (31.36), neuropathy (23.93) and CVD (4.39). Among acute complications, the incidence density of DKA was greatest (121.11 per 1000 person-years). The cumulative incidences of acute complications after 12 years following diagnosis were estimated to be 52.1%, 36.1% and 4.1% for DKA, outpatient hypoglycaemia and hospitalised hypoglycaemia, respectively. For chronic complications, the cumulative incidence of retinopathy after 12 years following diagnosis was greatest (65.2%), followed by those of nephropathy (30.2%), neuropathy (23.7%) and CVD (4.1%). Females with late-onset diabetes were greatly affected by advanced retinopathy (ie, sight-threatening diabetic retinopathy) and hospitalised hypoglycaemia, whereas those with early-onset diabetes were more vulnerable to DKA. Chronic complications were more commonly seen in late-onset diabetes, whereas early-onset diabetes were most affected by acute complications.

CONCLUSIONS

Ethnic Chinese patients with type 1 diabetes were greatly affected by DKA and retinopathy. The incidence of diabetes-related complications differed by age at diagnosis and sex.