Economic Evaluations of Guideline-Directed Medical Therapies for Heart Failure With Reduced Ejection Fraction: A Systematic Review.

OBJECTIVES: Decision-analytic models (DAMs) with varying structures and assumptions have been applied in economic evaluations (EEs) to assist decision making for heart failure with reduced ejection fraction (HFrEF) therapeutics. This systematic review aimed to summarize and critically appraise the EEs of guideline-directed medical therapies (GDMTs) for HFrEF. METHODS: A systematic search of English articles and gray literature, published from January 2010, was performed on databases including MEDLINE, Embase, Scopus, NHSEED, health technology assessment, Cochrane Library, etc. The included studies were EEs with DAMs that compared the costs and outcomes of angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, angiotensin-receptor neprilysin inhibitors, beta-blockers, mineralocorticoid-receptor agonists, and sodium-glucose cotransporter-2 inhibitors. The study quality was evaluated using the Bias in Economic Evaluation (ECOBIAS) 2015 checklist and Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklists. RESULTS: A total of 59 EEs were included. Markov model, with a lifetime horizon and a monthly cycle length, was most commonly used in evaluating GDMTs for HFrEF. Most EEs conducted in the high-income countries demonstrated that novel GDMTs for HFrEF were cost-effective compared with the standard of care, with the standardized median incremental cost-effectiveness ratio (ICER) of $21 361/quality-adjusted life-year. The key factors influencing ICERs and study conclusions included model structures, input parameters, clinical heterogeneity, and country-specific willingness-to-pay threshold. CONCLUSIONS: Novel GDMTs were cost-effective compared with the standard of care. Given the heterogeneity of the DAMs and ICERs, alongside variations in willingness-to-pay thresholds across countries, there is a need to conduct country-specific EEs, particularly in low- and middle-income countries, using model structures that are coherent with the local decision context.

Comparative effectiveness of cardiovascular, renal and safety outcomes of second-line antidiabetic drugs use in people with type 2 diabetes: A systematic review and network meta-analysis of randomised controlled trials.

AIMS: To compare the cardiovascular, renal and safety outcomes of second-line glucose-lowering agents used in the management of people with type 2 diabetes. METHODS: MEDLINE, EMBASE and CENTRAL were searched from inception to 13 July 2021 for randomised controlled trials comparing second-line glucose lowering therapies with placebo, standard care or one another. Primary outcomes included cardiovascular and renal outcomes. Secondary outcomes were non-cardiovascular adverse events. Risk ratios (RRs) and corresponding confidence intervals (CI) or credible intervals (CrI) were reported within pairwise and network meta-analysis. The quality of evidence was evaluated using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) criteria. Number needed to treat (NNT) and number needed (NNH) to harm were calculated at 5 years using incidence rates and RRs. PROSPERO (CRD42020168322). RESULTS: We included 38 trials from seven classes of glucose-lowering therapies. Both sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP1RA) showed moderate to high certainty in reducing risk of 3-point major adverse cardiovascular events, 3P-MACE (network estimates: SGLT2i [RR 0.90; 95% CrI 0.84-0.96; NNT, 59], GLP1RA [RR 0.88; 95% CrI 0.83-0.93; NNT, 50]), cardiovascular death, all-cause mortality, renal composite outcome and macroalbuminuria. SGLT2i also showed high certainty in reducing risk of hospitalization for heart failure (hHF), ESRD, acute kidney injury, doubling in serum creatinine and decline in eGFR. GLP1RA were associated with lower risk of stroke (high certainty) while glitazone use was associated with an increased risk of hHF (very low certainty). The risk of developing ESRD was lower with the use of sulphonylureas (low certainty). For adverse events, sulphonylureas and insulin were associated with increased hypoglycaemic events (very low to low certainty), while GLP1RA increased the risk of gastrointestinal side effects leading to treatment discontinuation (low certainty). DPP-4i increased risk of acute pancreatitis (low certainty). SGLT2i were associated with increased risk of genital infection, volume depletion (high certainty), amputation and ketoacidosis (moderate certainty). Risk of fracture was increased with the use of glitazones (moderate certainty). CONCLUSIONS: SGLT2i and GLP1RA were associated with lower risk for different cardiorenal end points, when used as an adjunct to metformin in people with type 2 diabetes. Additionally, SGLT2i demonstrated benefits in reducing risk for surrogate end points in kidney disease progression. Safety outcomes differ among the available pharmacotherapies.

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.

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 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.

Digital health interventions for gestational diabetes mellitus: A systematic review and meta-analysis of randomised controlled trials.

Good blood glucose control is important to reduce the risk of adverse effects on mothers and their offspring in women with gestational diabetes (GDM). This review examined the impact of using digital health interventions on reported glycaemic control among pregnant women with GDM and its impact on maternal and foetal outcomes. Seven databases were searched from database inception to October 31st, 2021 for randomised controlled trials that examined digital health interventions to provide services remotely for women with GDM. Two authors independently screened and assessed the studies for eligibility for inclusion. Risk of bias was independently assessed using the Cochrane Collaboration's tool. Studies were pooled using random effects model and presented as risk ratio or mean difference with 95% confidence intervals. Quality of evidence was assessed using GRADE framework. Twenty-eight randomised controlled trials that examined digital health interventions in 3,228 pregnant women with GDM were included. Moderate certainty of evidence showed that digital health interventions improved glycaemic control among pregnant women, with lower fasting plasma glucose (mean difference -0.33 mmol/L; 95% CI: -0.59 to -0.07), 2-hour post-prandial glucose (-0.49 mmol/L; -0.83 to -0.15) and HbA1c (-0.36%; -0.65 to -0.07). Among those randomised to digital health interventions, there was a lower need for caesarean delivery (Relative risk: 0.81; 0.69 to 0.95; high certainty) and foetal macrosomia (0.67; 0.48 to 0.95; high certainty). Other maternal and foetal outcomes were not significantly different between both groups. Moderate to high certainty evidence support the use of digital health interventions, as these appear to improve glycaemic control and reduce the need for caesarean delivery. However, more robust evidence is needed before it can be offered as a choice to supplement or replace clinic follow up. Systematic review registration: PROSPERO: CRD42016043009.

Patient Preference and Satisfaction with the Use of Telemedicine for Glycemic Control in Patients with Type 2 Diabetes: A Review.

BACKGROUND: Telemedicine has the potential to improve patient care and management for various chronic diseases such as type 2 diabetes. To ensure the success of any telemedicine program, there is a need to understand the patients' satisfaction and their preferences. This review aims to collate and provide evidence related to practices that may influence the performance of telemedicine for patients with type 2 diabetes. METHODS: We searched three electronic databases for studies examining patients' satisfaction and preferences for using telemedicine in type 2 diabetes. An evaluation matrix was developed to collect the data from the included articles. A total of 20 articles were identified and data on the key outcomes identified were narratively synthesized. RESULTS: Patients were generally satisfied with the use of telemedicine for management of type 2 diabetes. Users reported that telemedicine was beneficial as it provided constant monitoring, improved access to healthcare providers, and reduced waiting time. When adopting a telemedicine platform, most patients expressed preference for mobile health (mHealth) as the telemedicine modality, especially if it has been endorsed by their physician. To improve usability and sustainability, patients suggested that modules related to diabetes education be enhanced, together with sufficient technical and physician support when adopting telemedicine. Patients also expressed the importance of having a sufficiently flexible platform that could be adapted to their needs. CONCLUSION: Personalized telemedicine strategies coupled with appropriate physician endorsement greatly influences a patient's decision to undertake telemedicine. Future work should focus on improving telemedicine infrastructure and increasing physician's involvement, especially during the implementation phase.