Ethnic disparities in cardiovascular and renal responses to canagliflozin between Asian and White patients with type 2 diabetes mellitus: A post hoc analysis of the CANVAS Program.

AIM: To assess the potential heterogeneity in cardiovascular (CV), renal and safety outcomes of canagliflozin between Whites and Asians, as well as these outcomes in each subgroup. MATERIALS AND METHODS: The CANVAS Program enrolled 10 142 patients with type 2 diabetes, comprising 78.34% Whites and 12.66% Asians. CV, renal and safety outcomes were comprehensively analysed using Cox regression models, while intermediate markers were assessed using time-varying mixed-effects models. Racial heterogeneity was evaluated by adding a treatment-race interacion term. RESULTS: Canagliflozin showed no significant racial disparities in the majority of the CV, renal and safety outcomes. The heterogeneity (p = .04) was observed on all-cause mortality, with reduced risk in Whites (hazard ratio 0.84; 95% confidence interval 0.71-0.99) and a statistically non-significant increased risk in Asians (hazard ratio 1.64; 95% confidence interval 0.94-2.90). There was a significant racial difference in acute kidney injury (p = .04) and a marginally significant racial heterogeneity for the composite of hospitalization for heart failure and CV death (p = .06) and serious renal-related adverse events (p = .07). CONCLUSION: Canagliflozin reduced CV and renal risks similarly in Whites and Asians; however, there was a significant racial discrepancy in all-cause mortality. This distinction may be attributed to the fact that Asian patients exhibited diminished CV protection effects and more renal adverse events with canagliflozin, potentially resulting from the smaller reductions in weight and uric acid. These findings highlight the importance of investigating the impact of race on treatment response to sodium-glucose cotransporter-2 inhibitors and provide more precise treatment strategies.

Metabolic-associated steatotic liver disease and risk of Alzheimer's disease: a real-world retrospective cohort study.

Objective: Alzheimer's Disease (AD) is increasingly recognized as being associated with metabolic disorders, including Metabolic Associated Steatotic Liver Disease (MASLD). This study aimed to assess the relative risk of AD in individuals with MASLD. Methods: In this retrospective cohort study, we analyzed data from individuals aged over 65 who underwent health check-ups between January 2018 and June 2023. MASLD was diagnosed based on ultrasound findings and cardiometabolic criteria. AD incidence was identified using ICD-10 codes and self-reports. Poisson regression models estimated the relative risk of AD in relation to MASLD, adjusting for age, BMI, sex, SBP, HbA1c, HDL-c, triglycerides, hs-CRP, GGT, and estimated GFR. Results: The study included 4,582 MASLD patients and 6,318 controls. MASLD patients showed a higher incidence of AD (127 cases) compared to controls (61 cases). The fully adjusted Poisson regression model indicated an increased AD risk in MASLD patients [RR: 2.80 (95% CI: 1.79-4.38)]. Conclusion: Our findings suggested MASLD as an independent risk factor for AD, underlining the role of metabolic dysfunctions in AD pathogenesis. The study emphasized the need for comprehensive metabolic health management in AD prevention strategies, particularly among high-risk groups.

Machine-learning models utilizing CYP3A4*1G show improved prediction of hypoglycemic medication in Type 2 diabetes.

The effectiveness and side effects of Type 2 diabetes (T2D) medication are related to individual genetic background. SNPs CYP3A4 and CYP2C19 were introduced to machine-learning models to improve the performance of T2D medication prediction. Two multilabel classification models, ML-KNN and WRank-SVM, trained with clinical data and CYP3A4/CYP2C19 SNPs were evaluated. Prediction performance was evaluated with Hamming loss, one-error, coverage, ranking loss and average precision. The average precision of ML-KNN and WRank-SVM using clinical data was 92.74% and 92.9%, respectively. Combined with CYP2C19*2*3, the average precision dropped to 88.84% and 89.93%, respectively. While combined with CYP3A4*1G, the average precision was enhanced to 97.96% and 97.82%, respectively. Results suggest that CYP3A4*1G can improve the performance of ML-KNN and WRank-SVM models in predicting T2D medication performance.

About 10% of adults around the world are living with Type 2 Diabetes (T2D). Due to the huge number of patients and the complexity of individual makeup, it is a challenge for doctors to prescribe appropriate hypoglycemic drugs. To aid prescribing, machine-learning models were developed to predict medication schemes based on patients' demographic information and laboratory test results. These models treat prediction as a multilabel classification problem, with each class of medication as a label. This work was designed to determine whether the introduction of genetic information would improve prediction performance. The machine-learning models were trained using datasets with and without genetic information and their performance was compared. The performance of the machine-learning models was improved by incorporating the SNP CYP3A4*1G into the datasets. Thus, this work demonstrates a novel strategy to improve the prediction of T2D hypoglycemic medication performance and provides new ideas for how to support the T2D health system with machine-learning techniques.

Cost-Effectiveness of Canagliflozin Versus Dapagliflozin Added to Metformin in Patients With Type 2 Diabetes in China.

PURPOSE: Agents that inhibit sodium glucose co-transporter 2 (SGLT2), including canagliflozin and dapagliflozin, become available for the treatment of Chinese patients with type 2 diabetes mellitus (T2DM). This study assessed the economic outcomes of canagliflozin 100 mg versus dapagliflozin 10 mg in patients with T2DM inadequately controlled with metformin in the Chinese context. MATERIALS AND METHODS: Economic outcomes were projected by using the validated Chinese Outcomes Model for T2DM (COMT). Efficacy and safety, medical expenditure, and utility data were derived from the literature, which were assigned to model variables for estimating the quality-adjusted life-years (QALYs) and costs as well as incremental cost-effectiveness ratios (ICERs). The analysis was conducted from the perspective of Chinese healthcare service providers. One-way and probabilistic sensitivity analyses were performed. Health outcomes and costs were discounted at 5%. RESULTS: Relative to dapagliflozin 10 mg, treatment with canagliflozin 100 mg was associated with additional 0.015 expected life years per patients treated and 0.013 QALYs gained, which was driven by the reduced risk of macrovascular and microvascular complications over lifetime horizon. The incremental cost of canagliflozin 100 mg versus dapagliflozin 10 mg was US $-129, which indicated the canagliflozin 100 mg strategy was a dominant option. The univariate sensitivity analyses indicated that the results were sensitive to several model inputs. CONCLUSION: These results suggested that canagliflozin was a cost-saving treatment option compared with dapagliflozin from the perspective of Chinese health care services providers for Chinese patients with T2DM who are inadequately controlled on metformin monotherapy.

Wuzhi capsule regulates chloroacetaldehyde pharmacokinetics behaviour and alleviates high-dose cyclophosphamide-induced nephrotoxicity and neurotoxicity in rats.

High-dose cyclophosphamide (HD-CTX) treatment often leads to severe nephrotoxicity and neurotoxicity, which are mainly caused by one of its metabolites, chloroacetaldehyde (CAA). However, there are no effective antidotes to prevent these side effects. The objective of this study was to evaluate the effect of Wuzhi Capsule (WZC) on the pharmacokinetics of CTX and its metabolites in rats, and the attenuation of CAA induced kidney and brain injuries, which was produced at equimolar with 2-dechloroethylcyclophosphamide. Rats were treated with single- or multiple-dose of WZC when giving HD-CTX, and the plasma concentration of CTX and its metabolites were quantitated by UHPLC-MS/MS Single-dose, not multiple-dose of WZC co-administration (300 mg/kg) significantly reduced Cmax and AUC0→24 h of DC-CTX by 33.10% and 35.51%, respectively. Biochemical assay suggested oxidative stress was involved in kidney and brain injuries by HD-CTX, which were attenuated by single-dose WZC (300 mg/kg) pre-treatment, with increased glutathione, glutathione peroxidase and superoxide dismutase contents/or activities in both tissues and plasma (P < 0.05). Meanwhile, WZC pre-treatment could also significantly decrease the plasma levels of creatinine, blood urea nitrogen and malondialdehyde (P < 0.05). Additionally, WZC treatment improved the morphology and pathology condition of the kidneys and brains in rats. In conclusion, single-dose WZC co-administration decreased CAA production and exerted protective effect on CTX-induced oxidative stress in kidney and brain, whereas repetitive WZC co-administration with CTX was probably not recommended.