Cost-Effectiveness of Glucose-Lowering Therapies as Add-on to Standard Care for People With Type 2 Diabetes in Malaysia

OBJECTIVES

This study aims to evaluate the cost-effectiveness of various glucose-lowering therapies as add-on to standard care for people with type 2 diabetes (T2D) in Malaysia.

METHODS

A state-transition microsimulation model was developed to compare the clinical and economic outcomes of 4 treatments: standard care, dipeptidyl peptidase-4 inhibitors, sodium-glucose cotransporter-2 inhibitors (SGLT2is), and glucagon-like peptide-1 receptor agonists. Cost-effectiveness was assessed from a healthcare provider's perspective over a lifetime horizon with 3% discount rate in a hypothetical cohort of people with T2D. Data input were informed from literature and local data when available. Outcome measures include costs, quality-adjusted life-years, incremental cost-effectiveness ratios, and net monetary benefits. Univariate and probabilistic sensitivity analyses were performed to assess uncertainties.

RESULTS

Over a lifetime horizon, the costs to treat a person with T2D ranged from RM 12 494 to RM 41 250, whereas the QALYs gains ranged from 6.155 to 6.731, depending on the treatment. Based upon a willingness-to-pay threshold of RM 29 080 per QALY, we identified SGLT2i as the most cost-effective glucose-lowering treatment, as add-on to standard care over patient's lifetime, with the net monetary benefit of RM 176 173 and incremental cost-effectiveness ratios of RM 12 279 per QALY gained. The intervention also added 0.577 QALYs and 0.809 LYs compared with standard care. Cost-effectiveness acceptability curve showed that SGLT2i had the highest probability of being cost-effective in Malaysia across varying willingness-to-pay threshold. The results were robust to various sensitivity analyses.

CONCLUSIONS

SGLT2i was found to be the most cost-effective intervention to mitigate diabetes-related complications.

Impact of a training program on hospital pharmacists' patient-centered communication attitudes and behaviors

Background

Effective communication that integrates the value of patient-centered care is important in healthcare encounters. Communication skills training (CST) has been indicated as effective in improving patient-centered communication behaviors. However, there is a paucity of studies on the impact of CST among Malaysian hospital pharmacists.

Objective

This study aimed to evaluate the effects of a patient-centered CST program on patient-centered communication scores, communication self-efficacy, and attitudes toward concordance among pharmacists in public hospitals.

Methods

A communication skills training (CST) program was conducted among hospital pharmacists. This training intervention was developed based on patient-centered communication frameworks and techniques, namely the Four Habits Model and motivational interviewing. A pre-test/post-test quasi-experimental design was implemented for the evaluation. Pharmacists underwent pre-test/post-test audiotaped simulated consultations and completed questionnaires, including the Revised United States-Leeds Attitudes Toward Concordance scale (RUS-LATCon) and Communication Self-Efficacy scale. The Four Habits Coding Scheme (FHCS) was used to evaluate patient-centered communication scores from the audiotapes, and the Wilcoxon signed-rank test was used to analyze for differences in the pre- and post-intervention scores.

Results

A total of 38 pharmacists from four tertiary hospitals participated in this study and completed the pre-test. However, due to the impact of COVID-19, only 23 pharmacists completed the post-test data collection. Improvements were noted in the FHCS scores post-training, including items related to exploring patients' concerns, acceptability, and barriers to treatment. Based on the questionnaire, there was an improvement in recognizing patients' needs and potential medication uncertainty and an increase in the overall communication self-efficacy scores after the training.

Conclusions

CST may help improve the adoption of patient-centered communication in pharmacists' consultations with patients.

Impact of COVID-19 Lockdown on Glycemic, Weight, Blood Pressure Control and Medication Adherence in Patients with Type 2 Diabetes

Medication adherence profoundly affects blood glucose management in patients with type 2 diabetes. Measures to contain the COVID-19 pandemic have affected disease management and medication adherence, owing to limited access to healthcare facilities. This study aimed to examine the impact of the COVID-19 lockdown on adherence to glucose-lowering and lipid-lowering therapies (statins), and glycemic, weight, and systolic blood pressure control measures. A retrospective chart review was conducted one year pre- and post- March 18, 2020, for patients receiving glucose-lowering medications and lipid-lowering therapies (statins) in two major public hospitals in Malaysia. We compared the proportion of days covered by medication, HbA1c level, weight, and systolic blood pressure (SBP) values pre- and after the index date. A total of 1985 patients were included in this study. The adherence rate significantly increased for metformin, sulfonylureas dipeptidyl peptidase 4 inhibitors (DPP4i) and statin after the index date (metformin (PDC: 0.985 vs 0.978, p < 0.001), sulfonylureas (PDC: 0.988 vs 0.979, p < 0.01), DPP4i (PDC: 0.987 vs 0.98, p < 0.001), and statins (PDC: 0.983 vs 0.978, p < 0.05)). HbA1c levels were significantly reduced after the index follow-up (Mean difference: -0.43%, p < 0.001), while there was a 2.5 mmHg (p = 0.03) significant increase in SBP post-index follow-up. No significant changes in weight were observed during the post-index follow-up period. In this study, we observed better medication adherence and glycemic control among patients during the lockdown, but not for weight and systolic blood pressure control.

Association of Met420del Variant of Metformin Transporter Gene SLC22A1 with Metformin Treatment Response in Ethiopian Patients with Type 2 Diabetes

Objective

This study aimed to evaluate whether the M420del variants of SLC22A1 (rs72552763) is associated with metformin treatment response in Ethiopian patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

A prospective observational cohort study was conducted on 86 patients with T2DM who had been receiving metformin monotherapy for <1 year. Patients showing ≥0.5% reduction in HbA1c levels from baseline within 3 months and remained low for at least another 3 months were defined as responders while those patients with <0.5% reduction in HbA1c levels and/or those whom started a new class of glucose-lowering drug(s) because of unsatisfactory reduction were defined as non-responders. In addition, good glycemic control was observed when HbA1c ≤7.0%, and the above values were regarded as poor. Genotyping of rs72552763 SNP was performed using TaqMan® Drug Metabolism Enzyme Genotyping Assay and its association with metformin response and glycemic control were assessed by measuring the change in HbA1c and fasting blood glucose levels using Chi-square, logistic regression and Mann-Whitney U-test. Statistical significance was set at p <0.05.

Results

The minor allele frequency of the rs72552763 SNP of SLC22A1 was 9.3%. Metformin response was significantly higher in deletion_GAT (del_G) genotypes as compared to the wild-type GAT_GAT (G_G) genotypes. Furthermore, a significantly lower median treatment HbA1 level was found in del_G genotypes as compared to G_G genotypes. However, the association of rs72552763 with metformin response was not replicated at the allele level. In contrast, the minor del_allele was significantly associated with good glycemic control compared to the G_allele, though not replicated at del_G genotypes level.

Conclusion

This study demonstrated that metformin response was significantly higher in study participants with a heterozygous carrier of M420del variants of SLC22A1 as compared to the wild-type G_G genotypes after 3 months of treatment.

Comparison of a chronic kidney disease predictive model for type 2 diabetes mellitus in Malaysia using Cox regression versus machine learning approach

Background

Diabetes is one of the leading causes of chronic kidney disease (CKD) and end-stage renal disease. This study aims to develop and validate different risk predictive models for incident CKD and CKD progression in people with type 2 diabetes (T2D).

Methods

We reviewed a cohort of people with T2D seeking care from two tertiary hospitals in the metropolitan cities of the state of Selangor and Negeri Sembilan from January 2012 to May 2021. To identify the 3-year predictor of developing CKD (primary outcome) and CKD progression (secondary outcome), the dataset was randomly split into a training and test set. A Cox proportional hazards (CoxPH) model was developed to identify predictors of developing CKD. The resultant CoxPH model was compared with other machine learning models on their performance using C-statistic.

Results

The cohorts included 1992 participants, of which 295 had developed CKD and 442 reported worsening of kidney function. Equation for the 3-year risk of developing CKD included gender, haemoglobin A1c, triglyceride and serum creatinine levels, estimated glomerular filtration rate, history of cardiovascular disease and diabetes duration. For risk of CKD progression, the model included systolic blood pressure, retinopathy and proteinuria. The CoxPH model was better at prediction compared with other machine learning models examined for incident CKD (C-statistic: training 0.826; test 0.874) and CKD progression (C-statistic: training 0.611; test 0.655). The risk calculator can be found at https://rs59.shinyapps.io/071221/.

Conclusions

The Cox regression model was the best performing model to predict people with T2D who will develop a 3-year risk of incident CKD and CKD progression in a Malaysian cohort.

Pharmacogenetics of sulfonylurea-induced hypoglycemia in Type 2 diabetes patients: the SUCLINGEN study

Aim: This study investigated the incidence of sulfonylurea-induced hypoglycemia and its predictors in Type 2 diabetes (T2D) patients. Patients & methods: In this prospective, observational study, T2D patients on maximal sulfonylurea-metformin therapy >1 year were enrolled. Hypoglycemia was defined as having symptoms or a blood glucose level <3.9 mmol/l. Results: Of the 401 patients, 120 (29.9%) developed sulfonylurea-induced hypoglycemia during the 12-month follow-up. The ABCC8 rs757110, KCNJ11 rs5219, CDKAL1 rs7756992 and KCNQ1 rs2237892 gene polymorphisms were not associated with sulfonylurea-induced hypoglycemia (p > 0.05). Prior history of hypoglycemia admission (odds ratio = 16.44; 95% CI: 1.74-154.33, p = 0.014) independently predicted its risk. Conclusion: Sulfonylurea-treated T2D patients who experienced severe hypoglycemia are at increased risk of future hypoglycemia episodes.

Clinical and genetic predictors of secondary sulfonylurea failure in Type 2 diabetes patients: the SUCLINGEN study

Background: Due to several limitations in the study designs of sulfonylurea pharmacogenomics studies, we investigated the clinical and genetic predictors of secondary sulfonylurea failure in Type 2 diabetes patients. Materials & methods: Patients receiving the maximum sulfonylurea and metformin doses for >1 year were enrolled. Secondary sulfonylurea failure was defined as HbA1c >7.0% (>53 mmol/mol) after a 12-month follow-up. Results: By multivariate analysis, increased insulin resistance (HOMA2-IR), baseline HbA1c >7.0%, residing in eastern Peninsular Malaysia, and the CC genotype of rs757110 ABCC8 gene polymorphism were independent predictors of secondary sulfonylurea failure (p < 0.05) while sulfonylurea-induced hypoglycemia was protective against such failure (p < 0.05). Conclusion: Sulfonylurea does not benefit patients with an increased risk of secondary sulfonylurea failure.