UKPDS outcomes model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82

Temporal associations of diabetes-related complications with health-related quality of life decrements in Chinese patients with type 2 diabetes: A prospective study among 19 322 adults-Joint Asia Diabetes Evaluation (JADE) register (2007-2018)

BACKGROUND

Patients with type 2 diabetes (T2D) are at high risk of developing multiple complications, affecting their health-related quality of life (HRQoL). Existing studies only considered impact of complication on HRQoL in the year of occurrence but not its residual impacts in subsequent years. We investigated temporal impacts of diabetes-related complications on HRQoL in a 12-year prospective cohort of ambulatory Chinese patients with T2D enrolled in the clinic-based Joint Asia Diabetes Evaluation (JADE) Register.

METHODS

HRQoL utility measures were derived from EuroQol five-dimensional three-level questionnaire (EQ-5D-3L) questionnaires completed by 19 322 patients with T2D in Hong Kong (2007-2018). Temporal EQ-5D utility decrements associated with subtypes of cardiovascular-renal events were estimated using generalized linear regression model after stepwise selection of covariates with p < .01 as cutoff.

RESULTS

In this cohort (mean ± SD age:61.2 ± 11.5 years, 55.3% men, median [interquartile range] duration of diabetes:10.1 [3.0-15.0] years, glycated hemoglobin [HbA1C] 7.5 ± 1.5%), EQ-5D utility was 0.860 ± 0.163. The largest HRQoL decrements were observed in year of occurrence of hemorrhagic stroke (-0.230), followed by ischemic stroke (-0.165), peripheral vascular disease (-0.117), lower extremity amputation (-0.093), chronic kidney disease (CKD) G5 without renal replacement therapy (RRT) (-0.079), congestive heart failure (CHF) (-0.061), and CKD G3-G4 without RRT (-0.042). Residual impacts on HRQoL persisted for 2 years after occurrence of CHF or ischemic stroke and 1 year after hemorrhagic stroke or CKD G3-G4 without RRT.

CONCLUSION

This is the first comprehensive report on temporal associations of HRQoL decrements with subtypes of diabetes-related complications in ambulatory Asian patients with T2D. These data will improve the accuracy of cost-effectiveness analysis of diabetes interventions at an individual level in an Asian setting.

Cost-utility analysis and drug pricing for tirzepatide for type 2 diabetes in the Chinese market compared with semaglutide

AIM

To investigate the most matchable price of tirzepatide (TIRZ) compared with semaglutide (SEMA) in the treatment of type 2 diabetes in China.

METHODS

The patient cohort and clinical efficacy data were derived from the SURPASS-2 trial. Cost-utility analysis and a binary search were performed to identify the most matchable price of TIRZ from a Chinese healthcare provider's perspective.

RESULTS

After lifetime simulation, the quality-adjusted life years of TIRZ 5, 10, 15 mg and SEMA 1 mg were 11.17, 11.21, 11.27 and 11.12 years, respectively. Despite an initial assumption that the annual cost of TIRZ equals that of SEMA, our analysis revealed that TIRZ is probably more cost-effective than SEMA. A thorough evaluation of pricing showed that the cost ranges for TIRZ at doses of 5, 10 and 15 mg were $1628.61-$1846.23, $1738.40-$2140.95 and $1800.30-$2430.81, respectively. After adjustment in the univariate sensitivity analysis, the cost ranges for TIRZ 5, 10 and 15 mg were $1542.68-$1757.57, $1573.00-$1967.16 and $1576.54-$2133.96, respectively. These cost intervals were validated through robust probabilistic sensitivity analysis and scenario analysis, except for the cost range for TIRZ 5 mg.

CONCLUSIONS

This study shows that, using SEMA as a reference, the annual costs for TIRZ 10 and 15 mg are $1573.00-$1967.16 and $1576.54-$2133.96, respectively, for patients with type 2 diabetes in China.

A short-term economic evaluation of early insulin therapy compared to oral anti-diabetic drugs in order to reduce the major adverse events in type 2 diabetes patients in Iran

OBJECTIVE

While there are some recommendations about early insulin therapy in newly diagnosed Type 2 Diabetes Mellitus (T2DM) patients, there is not sufficient evidence on this strategy's cost-effectiveness. This study compared early insulin therapy versus oral anti-diabetic drugs (OADs) for managing T2DMusing a cost-effectiveness analysis approach in Iran.

METHODS

In this economic evaluation, a decision analytic model was designed. The target population was newly diagnosed type 2 diabetic patients, and the study was carried out from the perspective of Iran's healthcare system with a one-year time horizon. Basal insulin, Dipeptidyl peptidase-4 (DPP-4) inhibitors, and Thiazolidinediones (TZDs) were compared in this evaluation. The main outcome for assessing the effectiveness of each intervention was the reduction in the occurrence of diabetes complications. Strategies were compared using the incremental cost-effectiveness ratio (ICER), and deterministic and probabilistic sensitivity analyses were carried out.

RESULTS

The DPP-4 inhibitors strategy was the dominant strategy with the highest effectiveness and the lowest cost. Early insulin therapy was dominated (ICER: $-53,703.18), meaning that it was not cost-effective. The sensitivity analyses consistently affirmed the robustness of the base case findings. The probabilistic sensitivity analysis indicated probabilities of 77%, 22%, and 1% for DPP-4 inhibitors, TZDs strategies, and early insulin therapy, respectively, in terms of being cost-effective.

CONCLUSION

In terms of cost-effectiveness, early insulin therapy was not cost-effective compared to OADs for managing newly diagnosed T2DM patients. Future studies in this regard, utilizing more comprehensive evidence, can yield more accurate results.

Advances in Addressing Patient Heterogeneity in Economic Evaluation: A Review of the Methods Literature

Cost-effectiveness analyses commonly use population or sample averages, which can mask key differences across subgroups and may lead to suboptimal resource allocation. Despite there being several new methods developed over the last decade, there is no recent summary of what methods are available to researchers. This review sought to identify advances in methods for addressing patient heterogeneity in economic evaluations and to provide an overview of these methods. A literature search was conducted using the Econlit, Embase and MEDLINE databases to identify studies published after 2011 (date of a previous review on this topic). Eligible studies needed to have an explicit methodological focus, related to how patient heterogeneity can be accounted for within a full economic evaluation. Sixteen studies were included in the review. Methodologies were varied and included regression techniques, model design and value of information analysis. Recent publications have applied methodologies more commonly used in other fields, such as machine learning and causal forests. Commonly noted challenges associated with considering patient heterogeneity included data availability (e.g., sample size), statistical issues (e.g., risk of false positives) and practical factors (e.g., computation time). A range of methods are available to address patient heterogeneity in economic evaluation, with relevant methods differing according to research question, scope of the economic evaluation and data availability. Researchers need to be aware of the challenges associated with addressing patient heterogeneity (e.g., data availability) to ensure findings are meaningful and robust. Future research is needed to assess whether and how methods are being applied in practice.

The long-term cost-effectiveness of once-weekly semaglutide versus sitagliptin for the treatment of type 2 diabetes in China

BACKGROUND

To estimate the long-term cost-effectiveness of once-weekly semaglutide versus sitagliptin as an add-on therapy for type 2 diabetes patients inadequately controlled on metformin in China, to better inform healthcare decision making.

METHODS

The Cardiff diabetes model which is a Monte Carlo micro-simulation model was used to project short-term effects of once-weekly semaglutide versus sitagliptin into long-term outcomes. Short-term data of patient profiles and treatment effects were derived from the 30-week SUSTAIN China trial, in which 868 type 2 diabetes patients with a mean age of 53.1 years inadequately controlled on metformin were randomized to receive once-weekly semaglutide 0.5 mg, once-weekly semaglutide 1 mg, or sitagliptin 100 mg. Costs and quality-adjusted life years (QALYs) were estimated from a healthcare system perspective at a discount rate of 5%. Univariate sensitivity analysis, scenario analysis, and probabilistic sensitivity analysis were conducted to test the uncertainty.

RESULTS

Over patients' lifetime projections, patients in both once-weekly semaglutide 0.5 mg and 1 mg arms predicted less incidences of most vascular complications, mortality, and hypoglycemia, and lower total costs compared with those in sitagliptin arm. For an individual patient, compared with sitagliptin, once-weekly semaglutide 0.5 mg conferred a small QALY improvement of 0.08 and a lower cost of $5173, while once-weekly semaglutide 1 mg generated an incremental QALY benefit of 0.12 and a lower cost of $7142, as an add-on to metformin. Therefore, both doses of once-weekly semaglutide were considered dominant versus sitagliptin with more QALY benefits at lower costs.

CONCLUSION

Once-weekly semaglutide may represent a cost-effective add-on therapy alternative to sitagliptin for type 2 diabetes patients inadequately controlled on metformin in China.

The Determination of Diabetes Utilities, Costs, and Effects Model: A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation

OBJECTIVES

To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes.

METHODS

The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error.

RESULTS

The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios.

CONCLUSIONS

The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.

Risk Prediction Scores for Type 2 Diabetes Microvascular and Cardiovascular Complications Derived and Validated With Real-world Data From 2 Provinces: The DIabeteS COmplications (DISCO) Risk Scores

OBJECTIVES

Existing tools to predict the risk of complications among people with type 2 diabetes poorly discriminate high- from low-risk patients. Our aim in this study was to develop risk prediction scores for major type 2 diabetes complications using real-world clinical care data, and to externally validate these risk scores in a different jurisdiction.

METHODS

Using health-care administrative data and electronic medical records data, risk scores were derived using data from 25,088 people with type 2 diabetes from the Canadian province of Ontario, followed between 2002 and 2017. Scores were developed for major clinically important microvascular events (treatment for retinopathy, foot ulcer, incident end-stage renal disease), cardiovascular disease events (acute myocardial infarction, heart failure, stroke, amputation), and mortality (cardiovascular, noncardiovascular, all-cause). They were then externally validated using the independent data of 11,416 people with type 2 diabetes from the province of Manitoba.

RESULTS

The 10 derived risk scores had moderate to excellent discrimination in the independent validation cohort, ranging from 0.705 to 0.977. Their calibration to predict 5-year risk was excellent across most levels of predicted risk, albeit with some displaying underestimation at the highest levels of predicted risk.

CONCLUSIONS

The DIabeteS COmplications (DISCO) risk scores for major type 2 diabetes complications were derived and externally validated using contemporary real-world clinical data. As a result, they may be more accurate than other risk prediction scores derived using randomized trial data. The use of more accurate risk scores in clinical practice will help improve personalization of clinical care for patients with type 2 diabetes.

Machine Learning Models for Prediction of Diabetic Microvascular Complications

IMPORTANCE AND AIMS

Diabetic microvascular complications significantly impact morbidity and mortality. This review focuses on machine learning/artificial intelligence (ML/AI) in predicting diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN).

METHODS

A comprehensive PubMed search from 1990 to 2023 identified studies on ML/AI models for diabetic microvascular complications. The review analyzed study design, cohorts, predictors, ML techniques, prediction horizon, and performance metrics.

RESULTS

Among the 74 identified studies, 256 featured internally validated ML models and 124 had externally validated models, with about half being retrospective. Since 2010, there has been a rise in the use of ML for predicting microvascular complications, mainly driven by DKD research across 27 countries. A more modest increase in ML research on DR and DN was observed, with publications from fewer countries. For all microvascular complications, predictive models achieved a mean (standard deviation) c-statistic of 0.79 (0.09) on internal validation and 0.72 (0.12) on external validation. Diabetic kidney disease models had the highest discrimination, with c-statistics of 0.81 (0.09) on internal validation and 0.74 (0.13) on external validation, respectively. Few studies externally validated prediction of DN. The prediction horizon, outcome definitions, number and type of predictors, and ML technique significantly influenced model performance.

CONCLUSIONS AND RELEVANCE

There is growing global interest in using ML for predicting diabetic microvascular complications. Research on DKD is the most advanced in terms of publication volume and overall prediction performance. Both DR and DN require more research. External validation and adherence to recommended guidelines are crucial.

A literature review of quality assessment and applicability to HTA of risk prediction models of coronary heart disease in patients with diabetes

This literature review had two objectives: to identify models for predicting the risk of coronary heart diseases in patients with diabetes (DM); and to assess model quality in terms of risk of bias (RoB) and applicability for the purpose of health technology assessment (HTA). We undertook a targeted review of journal articles published in English, Dutch, Chinese, or Spanish in 5 databases from 1st January 2016 to 18th December 2022, and searched three systematic reviews for the models published after 2012. We used PROBAST (Prediction model Risk Of Bias Assessment Tool) to assess RoB, and used findings from Betts et al. 2019, which summarized recommendations and criticisms of HTA agencies on cardiovascular risk prediction models, to assess model applicability for the purpose of HTA. As a result, 71 % and 67 % models reporting C-index showed good discrimination abilities (C-index >= 0.7). Of the 26 model studies and 30 models identified, only one model study showed low RoB in all domains, and no model was fully applicable for HTA. Since the major cause of high RoB is inappropriate use of analysis method, we advise clinicians to carefully examine the model performance declared by model developers, and to trust a model if all PROBAST domains except analysis show low RoB and at least one validation study conducted in the same setting (e.g. country) is available. Moreover, since general model applicability is not informative for HTA, novel adapted tools may need to be developed.

The Health Economics of Automated Insulin Delivery Systems and the Potential Use of Time in Range in Diabetes Modeling: A Narrative Review

Intensive therapy with exogenous insulin is the treatment of choice for individuals living with type 1 diabetes (T1D) and some with type 2 diabetes, alongside regular glucose monitoring. The development of systems allowing (semi-)automated insulin delivery (AID), by connecting glucose sensors with insulin pumps and algorithms, has revolutionized insulin therapy. Indeed, AID systems have demonstrated a proven impact on overall glucose control, as indicated by effects on glycated hemoglobin (HbA1c), risk of severe hypoglycemia, and quality of life measures. An alternative endpoint for glucose control that has arisen from the use of sensor-based continuous glucose monitoring is the time in range (TIR) measure, which offers an indication of overall glucose control, while adding information on the quality of control with regard to blood glucose level stability. A review of literature on the health-economic value of AID systems was conducted, with a focus placed on the growing place of TIR as an endpoint in studies involving AID systems. Results showed that the majority of economic evaluations of AID systems focused on individuals with T1D and found AID systems to be cost-effective. Most studies incorporated HbA1c, rather than TIR, as a clinical endpoint to determine treatment effects on glucose control and subsequent quality-adjusted life year (QALY) gains. Likely reasons for the choice of HbA1c as the chosen endpoint is the use of this metric in most validated and established economic models, as well as the limited publicly available evidence on appropriate methodologies for TIR data incorporation within conventional economic evaluations. Future studies could include the novel TIR metric in health-economic evaluations as an additional measure of treatment effects and subsequent QALY gains, to facilitate a holistic representation of the impact of AID systems on glycemic control. This would provide decision makers with robust evidence to inform future recommendations for health care interventions.

COMPAR-EU Recommendations on Self-Management Interventions in Type 2 Diabetes Mellitus

Self-management interventions (SMIs) offer a promising approach to actively engage patients in the management of their chronic diseases. Within the scope of the COMPAR-EU project, our goal is to provide evidence-based recommendations for the utilisation and implementation of SMIs in the care of adult individuals with type 2 diabetes mellitus (T2DM). A multidisciplinary panel of experts, utilising a core outcome set (COS), identified critical outcomes and established effect thresholds for each outcome. The panel formulated recommendations using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach, a transparent and rigorous framework for developing and presenting the best available evidence for the formulation of recommendations. All recommendations are based on systematic reviews (SR) of the effects and of values and preferences, a contextual analysis, and a cost-effectiveness analysis. The COMPAR-EU panel is in favour of using SMIs rather than usual care (UC) alone (conditional, very low certainty of the evidence). Furthermore, the panel specifically is in favour of using ten selected SMIs, rather than UC alone (conditional, low certainty of the evidence), mostly encompassing education, self-monitoring, and behavioural techniques. The panel acknowledges that, for most SMIs, moderate resource requirements exist, and cost-effectiveness analyses do not distinctly favour either the SMI or UC. Additionally, it recognises that SMIs are likely to enhance equity, deeming them acceptable and feasible for implementation.

Cost-Effectiveness Analysis of a Prescription Digital Therapeutic in Type 2 Diabetes

INTRODUCTION

BT-001 (AspyreRx™) prescription digital therapy, a form of personalized cognitive behavioral therapy, has demonstrated clinically meaningful and durable hemoglobin A1c reductions in patients with type 2 diabetes (T2D). The current study examined the cost-effectiveness of BT-001 plus standard of care (SoC) versus SoC alone in T2D over a lifetime horizon from a healthcare payer perspective.

METHODS

We modeled the T2D pathway using an individual patient-level simulation; clinical data were sourced from the intention-to-treat subset of the BT-001 randomized clinical trial (RCT). SoC across both arms included the composition of oral and injectable treatments for T2D. Events were simulated using the United Kingdom Prospective Diabetes Study Outcomes Model 2 risk equation. A 3-month model cycle length was used in the first year, then annual model cycles were used in line with the original risk engine specifications. Patient characteristics informed event equations and Monte Carlo random sampling was used to assess the occurrence of events within each model cycle. Incidence of hypoglycemic events, drug discontinuation, costs, and health utilities and disutility values were sourced from the literature.

RESULTS

From a payer perspective, BT-001 plus SoC versus SoC alone was dominant with a gain in quality-adjusted life years (QALYs) of 0.101 and cost savings of $7343 per patient over the lifetime horizon (i.e., more effective and less costly). BT-001 plus SoC was cost-effective at a willingness-to-pay of $100,000 per QALY (incremental net monetary benefit was $17,443). Savings with BT-001 were primarily driven by a reduction in drug acquisition costs. The reduction in hemoglobin A1c with BT-001 was associated with fewer T2D complications.

CONCLUSIONS

BT-001 plus SoC was estimated to dominate SoC alone over the lifetime horizon from a payer perspective, suggesting that using BT-001 can empower patients to better manage their diabetes with the potential for lifelong advantages.

Comparison of medical resources and costs among patients with coronary heart disease and impaired glucose tolerance in the Acarbose Cardiovascular Evaluation trial

BACKGROUND

The Acarbose Cardiovascular Evaluation (ACE) trial (ISRCTN91899513) evaluated the alpha-glucosidase inhibitor acarbose, compared with placebo, in 6522 patients with coronary heart disease and impaired glucose tolerance in China and showed a reduced incidence of diabetes. We assessed the within-trial medical resource use and costs, and quality-adjusted life years (QALYs).

METHODS

Resource use data were collected prospectively within the ACE trial. Hospitalizations, medications, and outpatient visits were valued using Chinese unit costs. Medication use was measured in drug days, with cardiovascular and diabetes drugs summed across the trial by participant. Health-related quality of life was captured using the EuroQol-5 Dimension-3 Level questionnaire. Regression analyses were used to compare resource use, costs, and QALYs, accounting for regional variation. Costs and QALYs were discounted at 3% yearly.

RESULTS

Hospitalizations were 6% higher in the acarbose arm during the trial (rate ratio 1.06, p = .009), but there were no significant differences in total inpatient days (rate ratio 1.04, p = .30). Total costs per participant, including study drug, were significantly higher for acarbose (¥ [Yuan] 56 480, £6213), compared with placebo (¥48 079, £5289; mean ratio 1.18, p < 0.001). QALYs reported by participants in the acarbose arm (3.96 QALYs) were marginally higher than in the placebo arm (3.95 QALYs), but the difference was not statistically significant (0.01 QALYs; p = .58).

CONCLUSIONS

Acarbose, compared with placebo, participants cost more due to study drug costs and reported no statistically significant difference in QALYs. These higher within-trial costs could potentially be offset in future by savings from the acarbose-related lower incidence of diabetes.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D).

METHODS

We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.

RESULTS

Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort.

CONCLUSIONS

Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

BACKGROUND

Diabetes mellitus is a chronic and complex disease, increasing in prevalence and consequent health expenditure. Cost-effectiveness models with long time horizons are commonly used to perform economic evaluations of diabetes' treatments. As such, prediction accuracy and structural uncertainty are important features in cost-effectiveness models of chronic conditions.

OBJECTIVES

The aim of this systematic review is to identify and review published cost-effectiveness models of diabetes treatments developed between 2011 and 2022 regarding their methodological characteristics. Further, it also appraises the quality of the methods used, and discusses opportunities for further methodological research.

METHODS

A systematic literature review was conducted in MEDLINE and Embase to identify peer-reviewed papers reporting cost-effectiveness models of diabetes treatments, with time horizons of more than 5 years, published in English between 1 January 2011 and 31 of December 2022. Screening, full-text inclusion, data extraction, quality assessment and data synthesis using narrative synthesis were performed. The Philips checklist was used for quality assessment of the included studies. The study was registered in PROSPERO (CRD42021248999).

RESULTS

The literature search identified 30 studies presenting 29 unique cost-effectiveness models of type 1 and/or type 2 diabetes treatments. The review identified 26 type 2 diabetes mellitus (T2DM) models, 3 type 1 DM (T1DM) models and one model for both types of diabetes. Fifteen models were patient-level models, whereas 14 were at cohort level. Parameter uncertainty was assessed thoroughly in most of the models, whereas structural uncertainty was seldom addressed. All the models where validation was conducted performed well. The methodological quality of the models with respect to structure was high, whereas with respect to data modelling it was moderate.

CONCLUSIONS

Models developed in the past 12 years for health economic evaluations of diabetes treatments are of high-quality and make use of advanced methods. However, further developments are needed to improve the statistical modelling component of cost-effectiveness models and to provide better assessment of structural uncertainty.

A health economic analysis of an integrated diabetes care program in China: based on real-world evidence

Introduction

An integrated care program was set up in China to improve the collaboration between primary healthcare centers and hospitals on diabetes management. This study aims to evaluate the economic value of this program with real-world data and to examine whether it can be promoted in primary healthcare settings in China.

Methods

This integrated diabetes care program was implemented in Yuhuan City, China, to coordinate primary care and specialty care, treatment and prevention services, as well as the responsibilities of doctors and nurses. Cost-effectiveness analysis was used to compare the short-term economic value of this program (intervention group) versus usual diabetes management (control group). The cost data were collected from a societal perspective, while the effectiveness indicators pointed to the improvement of control rates of fasting blood glucose (FBG), systolic blood pressure (SBP), and diastolic blood pressure (DBP) levels after the 1 year intervention. In addition, cost-utility analysis was applied to evaluate the long-term value of the two groups. Patients' long-term diabetes management costs and quality-adjusted life years (QALYs) were simulated by the United Kingdom Prospective Diabetes Study Outcomes Model 2.

Results

The results showed that for 1% FBG, SPB, and DBP control rate improvement, the costs for the intervention group were 290.53, 124.39, and 249.15 Chinese Yuan (CNY), respectively, while the corresponding costs for the control group were 655.19, 610.43, and 1460.25 CNY. Thus, the intervention group's cost-effectiveness ratios were lower than those of the control group. In addition, compared to the control group, the intervention group's incremental costs per QALY improvement were 102.67 thousand CNY, which means that the intervention was cost-effective according to the World Health Organization's standards.

Discussion

In conclusion, this study suggested that this integrated diabetes care program created short-term and long-term economic values through patient self-management support, primary care strengthening, and care coordination. As this program followed the principles of integrated care reform, it can be promoted in China. Also, its elements can provide valuable experience for other researchers to build customized integrated care models.

Effectiveness, safety and costs of the FreeStyle Libre glucose monitoring system for children and adolescents with type 1 diabetes in Spain: a prospective, uncontrolled, pre-post study

OBJECTIVES

This study aimed to evaluate the effectiveness, safety and costs of FreeStyle Libre (FSL) glucose monitoring system for children and adolescents with type 1 diabetes mellitus (T1DM) in Spain.

DESIGN

Prospective, multicentre pre-post study.

SETTING

Thirteen Spanish public hospitals recruited patients from January 2019 to March 2020, with a 12-month follow-up.

PARTICIPANTS

156 patients were included.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary: glycated haemoglobin (HbA1c) change. Secondary: severe hypoglycaemic events (self-reported and clinical records), quality of life, diabetes treatment knowledge, treatment satisfaction, adverse events, adherence, sensor usage time and scans. Healthcare resource utilisation was assessed for cost analysis from the National Health System perspective, incorporating direct healthcare costs. Data analysis used mixed regression models with repeated measures. The intervention's total cost was estimated by multiplying health resource usage with unit costs.

RESULTS

In the whole sample, HbA1c increased significantly (0.32%; 95% CI 0.10% to 0.55%). In the subgroup with baseline HbA1c≥7.5% (n=88), there was a significant reduction at 3 months (-0.46%; 95% CI -0.69% to -0.23%), 6 months (-0.49%; 95% CI -0.73% to -0.25%) and 12 months (-0.43%; 95% CI -0.68% to -0.19%). Well-controlled patients had a significant 12-month worsening (0.32%; 95% CI 0.18% to 0.47%). Self-reported severe hypoglycaemia significantly decreased compared with the previous year for the whole sample (-0.37; 95% CI -0.62 to -0.11). Quality of life and diabetes treatment knowledge showed no significant differences, but satisfaction increased. Adolescents had lower sensor usage time and scans than children. Reduction in HbA1c was significantly associated with device adherence. No serious adverse effects were observed. Data suggest that use of FSL could reduce healthcare resource use (strips and lancets) and costs related to productivity loss.

CONCLUSIONS

The use of FSL in young patients with T1DM was associated with a significant reduction in severe hypoglycaemia, and improved HbA1c levels were seen in patients with poor baseline control. Findings suggest cost savings and productivity gains for caregivers. Causal evidence is limited due to the study design. Further research is needed to confirm results and assess risks, especially for patients with lower baseline HbA1c.

De Novo Cost-Effectiveness Model Framework for Nonalcoholic Steatohepatitis-Modeling Approach and Validation

BACKGROUND

Nonalcoholic steatohepatitis (NASH) is a chronic liver disease associated with hepatic morbidity and mortality and extra-hepatic comorbidities. Published NASH cost-effectiveness models (CEMs) are heterogeneous and consistently omit comorbid conditions that frequently co-exist alongside NASH. We aimed to develop a de novo CEM framework that incorporates extra-hepatic disease states and outcomes alongside hepatic components to enable future estimation of the cost-effectiveness of NASH interventions.

METHODS

Patient-level simulation and cohort-level Markov models were implemented in the same framework. Model inputs included fibrosis progression; late-stage liver disease outcomes; comorbidity outcomes for cardiovascular disease, type 2 diabetes, and obesity; mortality; health-related quality of life; and direct medical costs. The prototype analysis assessed the cost-effectiveness of obeticholic acid versus standard of care from a US payer perspective over a lifetime horizon with costs and effects discounted at 3% per annum. However, the CEM was designed for easy adaptation to other countries, time horizons, and other considerations. Efficacy and adverse event parameters were obtained from the 18-month interim analysis of the REGENERATE trial. Outputs include total and incremental costs, total life years, and quality-adjusted life years.

RESULTS

In this model, total costs, total life years, and quality-adjusted life years were all higher with obeticholic acid compared with standard of care. Cross-validation of this model with the 2016 and 2020 Institute for Clinical and Economic Review models revealed marked differences, mainly driven by mortality inputs, transition probability estimates, and incorporation of the effect of treatment and comorbidities.

CONCLUSION

This is the first CEM in NASH to incorporate the clinical consequences of several comorbidities. The flexible yet standardized framework permits estimation of the cost-effectiveness of NASH interventions in a variety of settings. The model currently includes several assumptions and will be further developed as more relevant data become available.

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.

A Systematic Review of Cost-Effectiveness Studies of Newer Non-Insulin Antidiabetic Drugs: Trends in Decision-Analytical Models for Modelling of Type 2 Diabetes Mellitus

BACKGROUND

We performed a systematic overview of the cost-effectiveness analyses (CEAs) comparing Non-insulin antidiabetic drugs (NIADs) with other NIADs for the treatment of type 2 diabetes mellitus (T2DM), using decision-analytical modelling (DAM), focusing on both the economic results and the underlying methodological choices.

METHODS

Eligible studies were CEAs using DAM to compare NIADs within the glucagon-like peptide-1 (GLP1) receptor agonists, sodium-glucose cotransporter-2 (SGLT2) inhibitors, or dipeptidyl peptidase-4 (DPP4) inhibitor classes with other NIADs within those classes for the treatment of T2DM. The PubMed, Embase and Econlit databases were searched from 1 January 2018 to 15 November 2022. Two reviewers screened the studies for relevance by titles and abstracts and then for eligibility via full-text screening, extracted the data from the full texts and appendices, and then stored the data in a spreadsheet.

RESULTS

The search yielded 890 records and 50 studies were eligible for inclusion. The studies were mainly based on a European setting (60%). Industry sponsorship was found in 82% of studies. The CORE diabetes model was used in 48% of the studies. GLP1 and SGLT2 products were the main comparators in 31 and 16 studies, respectively, while one study had DPP4 and two had no easily discernible main comparator. Direct comparison between SGLT2 and GLP1 occurred in 19 studies. At a class level, SGLT2 dominated GLP1 in six studies and was cost effective against GLP1 once as part of a treatment pathway. GLP1 was cost effective in nine studies and not cost effective against SGLT2 in three studies. At a product level, oral and injectable semaglutide, and empagliflozin, were cost effective against other within-class products. Injectable and oral semaglutide were more frequently found cost effective in these comparisons, with some conflicting results. Most of the modelled cohorts and treatment effects were sourced from randomised controlled trials. The following model assumptions varied depending on the class of the main comparator: choice of and reasoning behind risk equations, the time until the treatment switch, and how often the comparators were discontinued. Diabetes-related complications were emphasised on par with quality-adjusted life-years as model outputs. The main quality issues were regarding the description of alternatives, the perspective of analysis, the measurement of costs and consequences, and patient subgroups.

CONCLUSION

The included CEAs using DAMs have limitations that hinder their ability to inform decision makers on the cost-effective choice: lack of updated reasoning behind the choice of key model assumptions, over-reliance on risk equations based on older treatment practices, and sponsorship bias. The question of which NIAD is cost effective for the treatment of which T2DM patient is a pressing one and the answer remains unclear.

Cost-Effectiveness of SGLT2 Inhibitors in a Real-World Population: A MICADO Model-Based Analysis Using Routine Data from a GP Registry

OBJECTIVE

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been shown to reduce the risk of cardiovascular complications, which largely drive diabetes' health and economic burdens. Trial results indicated that SGLT2i are cost effective. However, these findings may not be generalizable to the real-world target population. This study aims to evaluate the cost effectiveness of SGLT2i in a routine care type 2 diabetes population that meets Dutch reimbursement criteria using the MICADO model.

METHODS

Individuals from the Hoorn Diabetes Care System cohort (N = 15,392) were filtered to satisfy trial inclusion criteria (including EMPA-REG, CANVAS, and DECLARE-TIMI58) or satisfy the current Dutch reimbursement criteria for SGLT2i. We validated a health economic model (MICADO) by comparing simulated and observed outcomes regarding the relative risks of events in the intervention and comparator arm from three trials, and used the validated model to evaluate the long-term health outcomes using the filtered cohorts' baseline characteristics and treatment effects from trials and a review of observational studies. The incremental cost-effectiveness ratio (ICER) of SGLT2i, compared with care-as-usual, was assessed from a third-party payer perspective, measured in euros (2021 price level), using a discount rate of 4% for costs and 1.5% for effects.

RESULTS

From Dutch individuals with diabetes in routine care, 15.8% qualify for the current Dutch reimbursement criteria for SGLT2i. Their characteristics were significantly different (lower HbA1c, higher age, and generally more preexisting complications) than trial populations. After validating the MICADO model, we found that lifetime ICERs of SGLT2i, when compared with usual care, were favorable (< €20,000/QALY) for all filtered cohorts, resulting in an ICER of €5440/QALY using trial-based treatment effect estimates in reimbursed population. Several pragmatic scenarios were tested, the ICERs remained favorable.

CONCLUSIONS

Although the Dutch reimbursement indications led to a target group that deviates from trial populations, SGLT2i are likely to be cost effective when compared with usual care.

Cost-utility of real-time continuous glucose monitoring versus self-monitoring of blood glucose in people with insulin-treated Type 2 diabetes in Canada

Aim: Clinical trials and real-world data for Type 2 diabetes have shown that real-time continuous glucose monitoring (rt-CGM) lowers glycated hemoglobin (A1c) and reduces hypoglycemia relative to self-monitoring of blood glucose (SMBG). This analysis examined the long-term health and economic outcomes associated with using rt-CGM versus SMBG in people with insulin-treated Type 2 diabetes in Canada. Materials & methods: Clinical data were sourced from a real-world study, in which rt-CGM reduced A1C by 0.56% versus continued SMBG. The analysis was performed using the IQVIA Core Diabetes Model, from a Canadian payer perspective over a lifetime horizon for a cohort aged 65 years with an A1C of 8.3% at baseline. Future costs and clinical outcomes were discounted at 1.5% annually. Results: Projected total mean lifetime costs were CAD 207,466 for rt-CGM versus CAD 189,863 for SMBG (difference: CAD 17,602) and projected mean quality-adjusted life expectancy was 9.97 quality-adjusted life years (QALYs) for rt-CGM versus 9.02 QALYs for SMBG (difference: 0.95 QALYs), resulting in an incremental cost-utility ratio (ICUR) of CAD 18,523 per QALY gained for rt-CGM versus SMBG. Findings were sensitive to changes in the A1C treatment effect, annual cost and quality of life benefit associated with using rt-CGM, SMBG frequency, and baseline age, but ICURs remained below CAD 50,000 per QALY in all analyses. Conclusion: For people in Canada with insulin-treated Type 2 diabetes and poor glycemic control, use of rt-CGM is likely to be cost-effective relative to SMBG.

Development and validation of the prediction model for mortality in patients with diabetic kidney disease in intensive care unit: a study based on medical information Mart for intensive care

We aimed to explore factors associated with mortality of diabetic kidney disease (DKD), and to establish a prediction model for predicting the mortality of DKD. This was a cohort study. In total, 1,357 DKD patients were identified from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, with 505 DKD patients being identified from the MIMIC-III as the testing set. The outcome of the study was 1-year mortality. COX proportional hazard models were applied to screen the predictive factors. The prediction model was conducted based on the predictive factors. A receiver operating characteristic (ROC) curve with the area under the curve (AUC) was calculated to evaluate the performance of the prediction model. The median follow-up time was 365.00 (54.50,365.00) days, and 586 patients (43.18%) died within 1 year. The predictive factors for 1-year mortality in DKD included age, weight, sepsis, heart rate, temperature, Charlson Comorbidity Index (CCI), Simplified Acute Physiology Score (SAPS) II, and Sequential Organ Failure Assessment (SOFA), lymphocytes, red cell distribution width (RDW), serum albumin, and metformin. The AUC of the prediction model for predicting 1-year mortality in the training set was 0.771 [95% confidence interval (CI): 0.746-0.795] and the AUC of the prediction model in the testing set was 0.795 (95% CI: 0.756-0.834). This study establishes a prediction model for predicting mortality of DKD, providing a basis for clinical intervention and decision-making in time.

Prognostic models for heart failure in patients with type 2 diabetes: a systematic review and meta-analysis

OBJECTIVE

To provide a systematic review, critical appraisal, assessment of performance and generalisability of all the reported prognostic models for heart failure (HF) in patients with type 2 diabetes (T2D).

METHODS

We performed a literature search in Medline, Embase, Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and Scopus (from inception to July 2022) and grey literature to identify any study developing and/or validating models predicting HF applicable to patients with T2D. We extracted data on study characteristics, modelling methods and measures of performance, and we performed a random-effects meta-analysis to pool discrimination in models with multiple validation studies. We also performed a descriptive synthesis of calibration and we assessed the risk of bias and certainty of evidence (high, moderate, low).

RESULTS

Fifty-five studies reporting on 58 models were identified: (1) models developed in patients with T2D for HF prediction (n=43), (2) models predicting HF developed in non-diabetic cohorts and externally validated in patients with T2D (n=3), and (3) models originally predicting a different outcome and externally validated for HF (n=12). RECODe (C-statistic=0.75 95% CI (0.72, 0.78), 95% prediction interval (PI) (0.68, 0.81); high certainty), TRS-HFDM (C-statistic=0.75 95% CI (0.69, 0.81), 95% PI (0.58, 0.87); low certainty) and WATCH-DM (C-statistic=0.70 95% CI (0.67, 0.73), 95% PI (0.63, 0.76); moderate certainty) showed the best performance. QDiabetes-HF demonstrated also good discrimination but was externally validated only once and not meta-analysed.

CONCLUSIONS

Among the prognostic models identified, four models showed promising performance and, thus, could be implemented in current clinical practice.

Effectiveness and cost-effectiveness of six GLP-1RAs for treatment of Chinese type 2 diabetes mellitus patients that inadequately controlled on metformin: a micro-simulation model

Objective

To systematically estimate and compare the effectiveness and cost-effectiveness of the glucagon-like peptide-1 receptor agonists (GLP-1RAs) approved in China and to quantify the relationship between the burden of diabetic comorbidities and glycosylated hemoglobin (HbA1c) or body mass index (BMI).

Methods

To estimate the costs (US dollars, USD) and quality-adjusted life years (QALY) for six GLP-1RAs (exenatide, loxenatide, lixisenatide, dulaglutide, semaglutide, and liraglutide) combined with metformin in the treatment of patients with type 2 diabetes mellitus (T2DM) which is inadequately controlled on metformin from the Chinese healthcare system perspective, a discrete event microsimulation cost-effectiveness model based on the Chinese Hong Kong Integrated Modeling and Evaluation (CHIME) simulation model was developed. A cohort of 30,000 Chinese patients was established, and one-way sensitivity analysis and probabilistic sensitivity analysis (PSA) with 50,000 iterations were conducted considering parameter uncertainty. Scenario analysis was conducted considering the impacts of research time limits. A network meta-analysis was conducted to compare the effects of six GLP-1RAs on HbA1c, BMI, systolic blood pressure, and diastolic blood pressure. The incremental net monetary benefit (INMB) between therapies was used to evaluate the cost-effectiveness. China's per capita GDP in 2021 was used as the willingness-to-pay threshold. A generalized linear model was used to quantify the relationship between the burden of diabetic comorbidities and HbA1c or BMI.

Results

During a lifetime, the cost for a patient ranged from USD 42,092 with loxenatide to USD 47,026 with liraglutide, while the QALY gained ranged from 12.50 with dulaglutide to 12.65 with loxenatide. Compared to exenatide, the INMB of each drug from highest to lowest were: loxenatide (USD 1,124), dulaglutide (USD -1,418), lixisenatide (USD -1,713), semaglutide (USD -4,298), and liraglutide (USD -4,672). Loxenatide was better than the other GLP-1RAs in the base-case analysis. Sensitivity and scenario analysis results were consistent with the base-case analysis. Overall, the price of GLP-1RAs most affected the results. Medications with effective control of HbA1c or BMI were associated with a significantly smaller disease burden (p < 0.05).

Conclusion

Loxenatide combined with metformin was identified as the most economical choice, while the long-term health benefits of patients taking the six GLP-1RAs are approximate.

A New Type 2 Diabetes Microsimulation Model to Estimate Long-Term Health Outcomes, Costs, and Cost-Effectiveness

OBJECTIVES

This study aimed to develop a microsimulation model to estimate the health effects, costs, and cost-effectiveness of public health and clinical interventions for preventing/managing type 2 diabetes.

METHODS

We combined newly developed equations for complications, mortality, risk factor progression, patient utility, and cost-all based on US studies-in a microsimulation model. We performed internal and external validation of the model. To demonstrate the model's utility, we predicted remaining life-years, quality-adjusted life-years (QALYs), and lifetime medical cost for a representative cohort of 10 000 US adults with type 2 diabetes. We then estimated the cost-effectiveness of reducing hemoglobin A1c from 9% to 7% among adults with type 2 diabetes, using low-cost, generic, oral medications.

RESULTS

The model performed well in internal validation; the average absolute difference between simulated and observed incidence for 17 complications was < 8%. In external validation, the model was better at predicting outcomes in clinical trials than in observational studies. The cohort of US adults with type 2 diabetes was projected to have an average of 19.95 remaining life-years (from mean age 61), incur $187 729 in discounted medical costs, and accrue 8.79 discounted QALYs. The intervention to reduce hemoglobin A1c increased medical costs by $1256 and QALYs by 0.39, yielding an incremental cost-effectiveness ratio of $9103 per QALY.

CONCLUSIONS

Using equations exclusively derived from US studies, this new microsimulation model achieves good prediction accuracy in US populations. The model can be used to estimate the long-term health impact, costs, and cost-effectiveness of interventions for type 2 diabetes in the United States.

Health and economic impact of improved glucose, blood pressure and lipid control among German adults with type 2 diabetes: a modelling study

AIMS/HYPOTHESIS

The aim of this study was to estimate the long-term health and economic consequences of improved risk factor control in German adults with type 2 diabetes.

METHODS

We used the UK Prospective Diabetes Study Outcomes Model 2 to project the patient-level health outcomes and healthcare costs of people with type 2 diabetes in Germany over 5, 10 and 30 years. We parameterised the model using the best available data on population characteristics, healthcare costs and health-related quality of life from German studies. The modelled scenarios were: (1) a permanent reduction of HbA1c by 5.5 mmol/mol (0.5%), of systolic BP (SBP) by 10 mmHg, or of LDL-cholesterol by 0.26 mmol/l in all patients, and (2) achievement of guideline care recommendations for HbA1c (≤53 mmol/mol [7%]), SBP (≤140 mmHg) or LDL-cholesterol (≤2.6 mmol/l) in patients who do not meet the recommendations. We calculated nationwide estimates using age- and sex-specific quality-adjusted life year (QALY) and cost estimates, type 2 diabetes prevalence and population size.

RESULTS

Over 10 years, a permanent reduction of HbA1c by 5.5 mmol/mol (0.5%), SBP by 10 mmHg or LDL-cholesterol by 0.26 mmol/l led to per-person savings in healthcare expenditures of €121, €238 and €34, and 0.01, 0.02 and 0.015 QALYs gained, respectively. Achieving guideline care recommendations for HbA1c, SBP or LDL-cholesterol could reduce healthcare expenditure by €451, €507 and €327 and gained 0.03, 0.05 and 0.06 additional QALYs in individuals who did not meet the recommendations. Nationally, achieving guideline care recommendations for HbA1c, SBP and LDL-cholesterol could reduce healthcare costs by over €1.9 billion.

CONCLUSIONS/INTERPRETATION

Sustained improvements in HbA1c, SBP and LDL-cholesterol control among diabetes patients in Germany can lead to substantial health benefits and reduce healthcare expenditures.

Endocan is Related to Increased Cardiovascular Risk in Type 2 Diabetes Mellitus Patients

Aim: Type 2 diabetes mellitus (T2D) patients have an increased risk for cardiovascular disease (CVD). Different algorithms are used for the CVD risk quantification and United Kingdom Prospective Diabetes Study (UKPDS) score was among the most validated. Endocan is a novel endothelial dysfunction marker. The aim was to explore the potential relationship between serum endocan level and UKPDS risk engine score [which enables calculation of the 10-year risk of nonfatal and fatal coronary heart disease (eCHD) and stroke] in T2D patients. Materials and Methods: The study included a cohort of 104 patients with T2D (of them 52.8% men), with median age 66 years and body mass index (BMI) = 30.7 kg/m2. Patients were divided into: low (<15%), moderate (≥15% and <30%), and high-risk UKPDS category (≥30%). Results: In multivariable regression analysis (when adjusted for sex, BMI and/or hip circumference), endocan was the independent predictor for moderate and high estimated risks (nonfatal eCHD, fatal eCHD, and nonfatal stroke risk). In the Model for high nonfatal eCHD [areas under curve (AUC) = 0.895] and high fatal eCHD (AUC = 0.860) endocan indicated good clinical accuracy, and an excellent accuracy in discriminating patients with high risk for nonfatal stroke risk (AUC = 0.945). Conclusion: Endocan was the independent predictor for moderate and high estimated risks (i.e., nonfatal and fatal CHD and nonfatal stroke risk scores) in T2D patients. When included in models with sex and obesity indices endocan demonstrated good clinical accuracy in discriminating T2D patients with high risk for nonfatal and fatal eCHD and nonfatal stroke risk from those patients with low risk.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Evaluating the long-term cost-effectiveness of fixed-ratio combination insulin degludec/liraglutide (IDegLira) versus other treatment regimens in the chinese type 2 diabetes patients

BACKGROUND AND AIMS

To assess the cost-effectiveness of utilizing IDegLira in comparison to other treatment regimens ( liraglutide and degludec) in managing type 2 diabetes, taking into account the Chinese healthcare system's perspective.

METHODS

The clinical data were obtained from the randomized controlled trials (RCTs) of the DUAL I and DUAL II evidence studies that took place in China. To estimate the lifetime quality-adjusted life-years (QALYs) and direct medical costs of patients receiving different treatment strategies from a long-term perspective, the IQVIA CORE Diabetes Model version 9.0 (IQVIA, Basel, Switzerland) was utilized. The costs were evaluated from the perspective of the China National Health System. Future costs and clinical benefits were discounted annually at 5%, and sensitivity analyses were conducted.

RESULTS

IDegLira was projected to reduce the incidence of diabetes-related complications and improve quality-adjusted life expectancy (QALE) versus liraglutide and degludec. A survival benefit was observed with IDegLira over Liraglutide (0.073 years). Lifetime costs were lower by Chinese yuan (CNY) 27,945 on IDegLira than on Liraglutide therapy. A similar survival benefit was observed with IDegLira over degludec (0.068 years). Lifetime costs were lower by CNY 1196 on IDegLira than on degludec therapy. Therefore, IDegLira was found to be cost-effective versus liraglutide and degludec with incremental cost-effectiveness ratios of Dominant per QALY gained, respectively, under the threshold of three times the gross domestic product (GDP) per capita in China.

CONCLUSION

IDegLira is a cost-effective hypoglycemic treatment option that delivers positive clinical outcomes while also reducing costs for Chinese patients living with type 2 diabetes.

Cost-effectiveness analysis of once-daily oral semaglutide versus placebo and subcutaneous glucagon-like peptide-1 receptor agonists added to insulin in patients with type 2 diabetes in China

Introduction: Oral semaglutide is a glucagon-like peptide-1 receptor agonist (GLP-1 RA) that improves glycated hemoglobin levels and body weight in patients with type 2 diabetes (T2DM). We aim to evaluate the cost-effectiveness of once-daily oral semaglutide in comparison to placebo and injectable GLP-1 RAs in Chinese patients with T2DM inadequately controlled on basal insulin. Methods: The United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS OM2.1) was used to estimate the cost-effectiveness by calculating the incremental cost-effectiveness ratio (ICER). Baseline characteristics of the simulation cohort were obtained from the PIONEER 8 trial. Utility and safety inputs were derived from a network meta-analysis of 12 trials. Direct medical costs were retrieved from published literature and discounted at an annual rate of 5%. We used a willingness-to-pay (WTP) threshold of $36,528.3 per quality-adjusted life-year (QALY) gained. Scenario analysis, and one-way and probabilistic sensitivity analysis were performed. Results: The effectiveness of oral semaglutide was 10.39 QALYs with a total cost of $30,223.10, while placebo provided 10.13 QALYs at a lower total cost of $20,039.19. Oral semaglutide was not cost-effective at an ICER of $39,853.22 and $88,776.61 per QALY compared to placebo and exenatide at the WTP. However, at an annual price of $1,871.9, it was cost-effective compared with dulaglutide, liraglutide, and lixisenatide. The model was most sensitive to the discount rate and annual cost of oral semaglutide. The price of oral semaglutide needed to be reduced to $1,711.03 per year to be cost-effective compared to placebo and other injectable GLP-1 RAs except for exenatide and semaglutide injection. Conclusion: We found that once-daily oral semaglutide, at a comparable price of semaglutide injection, proves to be a cost-effective add-on therapy to insulin for Chinese patients with T2DM, especially when compared to subcutaneous GLP-1 RAs other than injectable semaglutide and exenatide. However, to achieve cost-effectiveness in comparison to placebo, further cost reduction of oral semaglutide is necessary. The estimated annual cost of $1,711.03 for oral semaglutide demonstrates a more cost-effective option than placebo, highlighting its potential value in the management of T2DM.

Prediction of complications in health economic models of type 2 diabetes: a review of methods used

AIM

Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions.

METHODS

PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated.

RESULTS

The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the 'sunflower method' (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly.

CONCLUSIONS

The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

Expected Health Benefits of SGLT-2 Inhibitors and GLP-1 Receptor Agonists in Older Adults

Background. Older and sicker adults with type 2 diabetes (T2D) were underrepresented in randomized trials of glucagon-like peptide 1 receptor-agonist (GLP1RA) and sodium-glucose cotransporter 2 inhibitors (SGLT2I), and thus, health benefits are uncertain in this population. Objective. To assess the impact of age, health status, and life expectancy in older adults with T2D on health benefits of GLP1RA and SGLT2I. Design. We used the United Kingdom Prospective Diabetes Study (UKPDS) model to simulate lifetime health outcomes. We calibrated the UKPDS model to improve mortality prediction in older adults using a common geriatric prognostic index. Participants. National Health and Nutrition Examination Survey 2013-2018 participants 65 y and older with T2D, eligible for GLP1RA or SGLT2I according to American Diabetes Association guidelines. Interventions. GLP1RA or SGLT2I use versus no additional medication. Main Measures. Lifetime complications and weighted life-years (LYs) and quality-adjusted life-years (QALYs) across overall treatment arms and life expectancies. Key Results. The overall older adult population was predicted to experience significant health benefits from GLP1RA (+0.29 LY [95% confidence interval: 0.27, 0.31], +0.15 QALYs [0.14, 0.16]) and SGLT2I (+0.26 LY [0.24, 0.28], +0.13 QALYs [0.12, 0.14]) as compared with no added medication. However, expected benefits declined in subgroups with shorter life expectancies. Participants with <4 y of life expectancy had minimal gains of <0.05 LY and <0.03 QALYs from added medication. Accounting for injection-related disutility, GLP1RA use reduced QALYs (-0.03 QALYs [-0.04, -0.02]). Conclusions. While GLP1RA and SGLT2I have substantial health benefits for many older adults with type 2 diabetes, benefits are not clinically significant in patients with <4 y of life expectancy. Life expectancy and patient preferences are important considerations when prescribing newer diabetes medications.

Highlights

On average, older adults benefit significantly from SGLT2I and GLP1RA use. However, the benefits of these drugs are not clinically significant among older patients with life expectancy less than 4 y.There is potential harm in injectable GLP1RA use in the oldest categories of adults with type 2 diabetes.Heterogeneity in life expectancy and patient preferences for injectable versus oral medications are important to consider when prescribing newer diabetes medications.

DNA methylation markers for kidney function and progression of diabetic kidney disease

Epigenetic markers are potential biomarkers for diabetes and related complications. Using a prospective cohort from the Hong Kong Diabetes Register, we perform two independent epigenome-wide association studies to identify methylation markers associated with baseline estimated glomerular filtration rate (eGFR) and subsequent decline in kidney function (eGFR slope), respectively, in 1,271 type 2 diabetes subjects. Here we show 40 (30 previously unidentified) and eight (all previously unidentified) CpG sites individually reach epigenome-wide significance for baseline eGFR and eGFR slope, respectively. We also develop a multisite analysis method, which selects 64 and 37 CpG sites for baseline eGFR and eGFR slope, respectively. These models are validated in an independent cohort of Native Americans with type 2 diabetes. Our identified CpG sites are near genes enriched for functional roles in kidney diseases, and some show association with renal damage. This study highlights the potential of methylation markers in risk stratification of kidney disease among type 2 diabetes individuals.

Cost-Effectiveness of Semaglutide vs. Empagliflozin, Canagliflozin, and Sitagliptin for Treatment of Patients with Type 2 Diabetes in Denmark: A Decision-Analytic Modelling Study

OBJECTIVE

The aim was to evaluate the cost-effectiveness of oral and subcutaneous semaglutide versus other oral glucose-lowering drugs (i.e., empagliflozin, canagliflozin, and sitagliptin) for the management of type 2 diabetes (T2D) in Denmark using clinically relevant treatment intensification rules.

METHODS

A Markov-type cohort model for evaluating the cost-effectiveness of treatment pathways for T2D was used to produce cost-effectiveness estimates based on four head-to-head trials. Evidence from PIONEER 2 and 3 trials was used to evaluate the cost-effectiveness of oral semaglutide vs. empagliflozin and sitagliptin. Evidence from SUSTAIN 2 and 8 trials was used to evaluate the cost-effectiveness of subcutaneous semaglutide vs. sitagliptin and canagliflozin. Base case analyses used trial product estimands of treatment efficacy to avoid the confounding effects of rescue medication use during trials. Deterministic scenario analyses and probabilistic sensitivity analyses were conducted to assess robustness of cost-effectiveness estimates.

RESULTS

Semaglutide-based treatment regimens were consistently associated with higher lifetime diabetes treatment costs, lower costs of complications, and higher lifetime accumulated QALYs. The PIONEER 2 analysis estimated the cost-effectiveness of oral semaglutide vs. empagliflozin was DKK 150,618/QALY (€20,189). The PIONEER 3 analysis estimated the cost-effectiveness of oral semaglutide vs. sitagliptin was DKK 95,093/QALY (€12,746). The SUSTAIN 2 analysis estimated the cost-effectiveness of subcutaneous semaglutide vs. sitagliptin was DKK 79,982/QALY (€10,721). The SUSTAIN 8 analysis estimated the cost-effectiveness of subcutaneous semaglutide vs. canagliflozin was DKK 167,664/QALY (€22,474).

CONCLUSIONS

Daily oral and weekly subcutaneous semaglutide are likely to both increase cost and health benefits, but are likely to do so under commonly considered cost-effectiveness thresholds.

TRIAL REGISTRATIONS

Clinicaltrials.gov: NCT02863328 (PIONEER 2; registered August 11, 2016); NCT02607865 (PIONEER 3; registered November 18, 2015); NCT01930188 (SUSTAIN 2; registered August 28, 2013); NCT03136484 (SUSTAIN 8; registered May 2, 2017).

The cost-effectiveness of using a prognosis-tailored strategy model to triage couples with idiopathic infertility for assisted reproduction technology

OBJECTIVES

To evaluate whether a prognosis-tailored triage of ART for couples with idiopathic infertility by using the Hunault prognostic model can decrease the cost of treatment without compromising the chance of live birth.

STUDY DESIGN

This is a retrospective study conducted in an Australian fertility clinic. Couples seeking infertility consultation who were subsequently found to have idiopathic infertility after evaluation were included. We compared the costs per conception leading to live birth of the prognosis-tailored strategy with the immediate ART strategy, which generally reflects the current practice in Australian fertility clinics, over a 24-month period. In the prognosis-tailored strategy, for each couple, the prognosis for natural conception was assessed using the well-established Hunault model. Total cost of treatments were calculated as the sum of typical out-of-pocket and Australian Medicare cost (Australian national insurance scheme).

RESULTS

We studied 261 couples. In the prognosis-tailored strategy, the total cost was $2,766,781 and the live birth rate was 63.9%. In contrast, the immediate ART strategy yielded a live birth rate of 64.4% with a total cost of $3,176,845. Implementing the prognosis-tailored strategy using the Hunault model saved $410,064 in total and $1,571 per couple. The incremental cost-effectiveness ratio (ICER) was $341,720 per live birth.

CONCLUSION

In couples with idiopathic infertility, assessment of prognosis for natural conception using the Hunault model and delaying ART for 12 months in couples with favourable prognoses can considerably reduce costs without significantly compromising live birth rates.

A Cost-effectiveness Analysis of iGlarLixi Versus IDegAsp and Appropriate Price Exploration of iGlarLixi for Type 2 Diabetes Mellitus Patients in China

BACKGROUND AND OBJECTIVE

The efficacy and safety of iGlarLixi, a fixed-ratio combination (FRC) of basal insulin glargine plus lixisenatide, have been demonstrated in type 2 diabetes mellitus (T2DM) patients. However, no relevant economic analysis of iGlarLixi has been done in China. Thus, the primary objective of this study is to evaluate the cost effectiveness of iGlarLixi versus IDegAsp in Chinese T2DM patients, and then back-calculate the appropriate drug price of iGlarLixi to support its pricing after listing in China.

METHODS

The United Kingdom Prospective Diabetes Study Outcome Model 2 (UKPDS OM2) was applied to estimate lifetime health and economic outcomes from the Chinese health-care system perspective. As no head-to-head comparison data are currently available, the baseline cohort characteristics and the initial clinical data for iGlarLixi were derived from the randomized LixiLan-L-China trial. The relative treatment effects for IDegAsp were based on an indirect treatment comparison. Due to the unavailability of iGlarLixi pricing data, the annual medication cost of iGlarLixi was assumed to be equal to that of IDegAsp at the beginning of the study. Afterwards, a break-even analysis using comparator drug price and the willingness-to-pay (WTP) threshold was performed to back-calculate the appropriate drug price of iGlarLixi. One-way sensitivity analysis, scenario analysis and probabilistic sensitivity analysis (PSA) were conducted to assess the robustness of the model.

RESULTS

Based on the initial assumption of equal annual medication cost of iGlarLixi and IDegAsp, iGlarLixi was cost effective compared to IDegAsp with an incremental cost-effectiveness ratio (ICER) far below the WTP threshold in Chinese T2DM patients. From the back calculation for the price of iGlarLixi, the annual medication cost of iGlarLixi was $656.96 and $1075.96 to obtain an ICER of iGlarLixi versus IDegAsp close to 1 × GDP and 3 × GDP, respectively. When the discount rate was changed from the base value to 8% (the most sensitive parameter to the model results in one-way sensitivity analysis), the ICER was nearly equal to 1 × GDP and 3 × GDP with the annual medication cost of iGlarLixi decreasing to $590.41 and $865.03, respectively. Thus, iGlarLixi was dominant over IDegAsp with an annual medication cost of $590.41 to $865.03. The findings were robust to one-way sensitivity analysis, PSA and scenario analysis.

CONCLUSION

This long-term cost-effectiveness analysis in Chinese T2DM patients indicates that iGlarLixi, assuming equal price to IDegAsp, is cost-effective versus IDegAsp with an ICER far below the WTP threshold. With 1 × GDP and 3 × GDP threshold set we back-calculate the appropriate annual medication cost of iGlarLixi to be $590.41 to $865.03, respectively.

Model-based predictions on health benefits and budget impact of implementing empagliflozin in people with type 2 diabetes and established cardiovascular disease

AIM

To perform a model-based analysis of the short- and long-term health benefits and costs of further increased implementation of empagliflozin for people with type 2 diabetes and established cardiovascular disease (eCVD) in Sweden.

MATERIALS AND METHODS

The validated Institute for Health Economics Diabetes Cohort Model (IHE-DCM) was used to estimate health benefits and a 3-year budget impact, and lifetime costs per quality-adjusted life years (QALY) gained of increased implementation of adding empagliflozin to standard of care (SoC) for people with type 2 diabetes and eCVD in a Swedish setting. Scenarios with 100%/75%/50% implementation were explored. Analyses were based on 30 model cohorts with type 2 diabetes and eCVD (n = 131 412 at baseline) from national health data registers. Sensitivity analyses explored the robustness of results.

RESULTS

Over 3 years, SoC with empagliflozin (100% implementation) versus SoC before empagliflozin resulted in 7700 total life years gained and reductions in cumulative incidence of cardiovascular deaths by 30% and heart failures by 28%. Annual costs increased by 15% from higher treatment costs and increased survival. Half of these benefits and costs are not yet reached with current implementation below 50%. SoC with empagliflozin yielded 0.37 QALYs per person, with an incremental cost-effectiveness ratio of 16 000 EUR per QALY versus SoC before empagliflozin.

CONCLUSIONS

Model simulations using real-world data and trial treatment effects indicated that a broader implementation of empagliflozin, in line with current guidelines for treatment of people with type 2 diabetes and eCVD, would lead to further benefits even from a short-term perspective.

Once-Weekly Subcutaneous Semaglutide 2.4 mg Injection is Cost-Effective for Weight Management in the United Kingdom

OBJECTIVES

The objective of the current preliminary study was to present the cost-effectiveness analyses submitted to the National Institute for Health and Care Excellence (NICE) (TA10765) that deemed semaglutide 2.4 mg subcutaneous (s.c.) injection a cost-effective option for weight management in the United Kingdom (UK) alongside diet and exercise (D&E).

METHODS

The study was conducted from the National Health Service (NHS) and Personal Social Services perspective and based on the NICE reference case. The clinical safety and efficacy of semaglutide 2.4 mg s.c. injection were obtained from the Semaglutide Treatment Effect in People with Obesity (STEP) 1 trial. The previously published and validated Core Obesity Model was used to project lifetime occurrence of obesity complications, their costs and quality of life consequences over 40 years. The base case cohort had a mean starting age of 48 years and BMI of 38.7 kg/m². The confidential NHS price for semaglutide 2.4 mg s.c. injection was provided by Novo Nordisk. The incremental cost-effectiveness ratios (ICERs) were expressed as cost/quality-adjusted life-year (QALY). Uncertainty was assessed through sensitivity analyses, including a scenario analysis using clinical data from the STEP 2 trial and a previously published and validated Core Diabetes Model to investigate a cohort with type 2 diabetes at baseline.

RESULTS

Semaglutide 2.4 mg s.c. injection showed higher total costs and health benefits compared with D&E, with an ICER of £14,827/QALY gained. The probabilistic sensitivity analysis showed that semaglutide 2.4 mg s.c. injection was cost-effective in 90% of cases at a willingness-to-pay threshold of £20,000/QALY. The ICER from the scenario analysis for the diabetic population was £16,613/QALY gained, using the Core Diabetes Model.

CONCLUSION

Semaglutide 2.4 mg s.c. injection is a cost-effective therapy compared to D&E alone for patients with obesity and weight-related comorbidities in the UK. Sensitivity and scenario analyses confirm the robustness of the analyses.

The challenges and pitfalls of incorporating evidence from cardiovascular outcomes trials in health economic modelling of type 2 diabetes

The clinical evidence base for evaluating modern type 2 diabetes interventions has expanded greatly in recent years, with numerous efficacious treatment options available (including dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors). The cardiovascular safety of these interventions has been assessed individually versus placebo in numerous cardiovascular outcomes trials (CVOTs), statistically powered to detect differences in a composite endpoint of major adverse cardiovascular events. There have been growing calls to incorporate these data in the long-term modelling of type 2 diabetes interventions because current diabetes models were developed prior to the conduct of the CVOTs and therefore rely on risk equations developed in the absence of these data. However, there are numerous challenges and pitfalls to avoid when using data from CVOTs. The primary concerns are around the heterogeneity of the trials, which have different study durations, inclusion criteria, rescue medication protocols and endpoint definitions; this results in significant uncertainty when comparing two or more interventions evaluated in separate CVOTs, as robust adjustment for these differences is difficult. Analyses using CVOT data inappropriately can dilute clear evidence from head-to-head clinical trials, and blur healthcare decision making. Calibration of existing models may represent an approach to incorporating CVOT data into diabetes modelling, but this can only offer a valid comparison of one intervention versus placebo based on a single CVOT. Ideally, model development should utilize patient-level data from CVOTs to prepare novel risk equations that can better model modern therapies for type 2 diabetes.

Impact of a social prescribing intervention in North East England on adults with type 2 diabetes: the SPRING_NE multimethod study

Background

Link worker social prescribing enables health-care professionals to address patients’ non-medical needs by linking patients into various services. Evidence for its effectiveness and how it is experienced by link workers and clients is lacking.

Objectives

To evaluate the impact and costs of a link worker social prescribing intervention on health and health-care costs and utilisation and to observe link worker delivery and patient engagement.

Data sources

Quality Outcomes Framework and Secondary Services Use data.

Design

Multimethods comprising (1) quasi-experimental evaluation of effects of social prescribing on health and health-care use, (2) cost-effectiveness analysis, (3) ethnographic methods to explore intervention delivery and receipt, and (4) a supplementary interview study examining intervention impact during the first UK COVID-19 lockdown (April–July 2020).

Study population and setting

Community-dwelling adults aged 40–74 years with type 2 diabetes and link workers in a socioeconomically deprived locality of North East England, UK.

Intervention

Link worker social prescribing to improve health and well-being-related outcomes among people with long-term conditions.

Participants

(1) Health outcomes study, approximately n = 8400 patients; EuroQol-5 Dimensions, five-level version (EQ-5D-5L), study, n = 694 (baseline) and n = 474 (follow-up); (2) ethnography, n = 20 link workers and n = 19 clients; and COVID-19 interviews, n = 14 staff and n = 44 clients.

Main outcome measures

The main outcome measures were glycated haemoglobin level (HbA1c; primary outcome), body mass index, blood pressure, cholesterol level, smoking status, health-care costs and utilisation, and EQ-5D-5L score.

Results

Intention-to-treat analysis of approximately 8400 patients in 13 intervention and 11 control general practices demonstrated a statistically significant, although not clinically significant, difference in HbA1c level (–1.11 mmol/mol) and a non-statistically significant 1.5-percentage-point reduction in the probability of having high blood pressure, but no statistically significant effects on other outcomes. Health-care cost estimates ranged from £18.22 (individuals with one extra comorbidity) to –£50.35 (individuals with no extra comorbidity). A statistically non-significant shift from unplanned (non-elective and accident and emergency admissions) to planned care (elective and outpatient care) was observed. Subgroup analysis showed more benefit for individuals living in more deprived areas, for the ethnically white and those with fewer comorbidities. The mean cost of the intervention itself was £1345 per participant; the incremental mean health gain was 0.004 quality-adjusted life-years (95% confidence interval –0.022 to 0.029 quality-adjusted life-years); and the incremental cost-effectiveness ratio was £327,250 per quality-adjusted life-year gained. Ethnographic data showed that successfully embedded, holistic social prescribing providing supported linking to navigate social determinants of health was challenging to deliver, but could offer opportunities for improving health and well-being. However, the intervention was heterogeneous and was shaped in unanticipated ways by the delivery context. Pressures to generate referrals and meet targets detracted from face-to-face contact and capacity to address setbacks among those with complex health and social problems.

Limitations

The limitations of the study include (1) a reduced sample size because of non-participation of seven general practices; (2) incompleteness and unreliability of some of the Quality and Outcomes Framework data; (3) unavailability of accurate data on intervention intensity and patient comorbidity; (4) reliance on an exploratory analysis with significant sensitivity analysis; and (5) limited perspectives from voluntary, community and social enterprise.

Conclusions

This social prescribing model resulted in a small improvement in glycaemic control. Outcome effects varied across different groups and the experience of social prescribing differed depending on client circumstances.

Future work

To examine how the NHS Primary Care Network social prescribing is being operationalised; its impact on health outcomes, service use and costs; and its tailoring to different contexts.

Trial registration

This trial is registered as ISRCTN13880272.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme, Community Groups and Health Promotion (grant no. 16/122/33) and will be published in full in Public Health Research; Vol. 11, No. 2. See the NIHR Journals Library website for further project information.

CELESTIA: Cost-Effectiveness Analysis of Empagliflozin Versus Sitagliptin in Patients with Type 2 Diabetes in Greece

Purpose

Globally, the prevalence of diabetes is on the rise, with the number of affected individuals predicted to cross 700 million by 2045. In Greece, in 2015, almost 700,000 people received prescribed medication for type 2 diabetes. The CELESTIA study aims to assess the cost-effectiveness of empagliflozin compared to branded sitagliptin in type 2 diabetes patients both with and without established cardiovascular disease in Greece from a third payer perspective.

Methods

The IQVIA Core Diabetes Model was used and analyses were conducted from the Greek healthcare payer perspective. Patients received either empagliflozin or sitagliptin until HbA1c threshold of 8.5% (69 mmol/mol) was exceeded. Subsequently, patients were assumed to intensify to insulin therapy. Baseline cohort characteristics and treatment effects were derived from clinical trial data. Literature data were used for input (utilities, treatment costs and costs of diabetes-related complications costs). A lifetime time horizon (50 years) was applied, and costs and benefits were discounted at an annual rate of 3.5%.

Results

Over a lifetime horizon, for empagliflozin, the estimated ICER was of €6,587 and €966 per quality-adjusted life years gained versus sitagliptin, in patients without established cardiovascular disease and in patients with established cardiovascular disease, respectively. Probabilistic sensitivity analysis confirmed the robustness of the analysis.

Conclusion

The analysis demonstrated that for type 2 diabetes patients, empagliflozin is a cost-effective treatment option versus branded sitagliptin in Greece.

Cost-utility analysis of semaglutide for type 2 diabetes after its addition to the National Medical Insurance System in China

INTRODUCTION

The main research purpose is to compare the long-term cost-effectiveness of semaglutide (SEMA) with that of dulaglutide (DULA) for patients with inadequately controlled type 2 diabetes throughout their lifetime. If necessary, the second aim is to investigate a further price cut for SEMA to provide sound advice for government drug price adjustments.

METHODS

Cost-utility analysis was performed by the United Kingdom Prospective Diabetes Study Outcomes Model 2 (UKPDS OM2) from the perspective of health care providers in China. Baseline characteristics and clinical efficacy of SEMA and DULA were sourced from the high-dose comparison in the SUSTAIN-7 trial. A binary search was used to identify the scope for further reduction in the price of SEMA. The impact of individual parameters was assessed with sensitivity analyses.

RESULTS

Main analysis (SEMA vs. DULA) revealed a mean difference in quality-adjusted life years (QALYs) of 0.04 QALYs and costs of $1132.29. The incremental cost-utility ratio was $26 957.44/QALY, showing that SEMA was a better option compared with DULA. In sensitivity analyses, the discount rate made the greatest contribution to the incremental cost-utility ratio. In the binary search, there was still scope to reduce the SEMA cost further by approximately 6.83% to be cost-effective, taking DULA as a reference.

CONCLUSION

After its addition to the National Medical Insurance System in China, SEMA is expected to be a cost-effective choice compared with DULA for patients with type 2 diabetes with inadequately controlled from the cost-utility analysis. However, there is still scope to reduce the annual cost of SEMA further.

Developing a prediction model for all-cause mortality risk among patients with type 2 diabetes mellitus in Shanghai, China

BACKGROUND

All-cause mortality risk prediction models for patients with type 2 diabetes mellitus (T2DM) in mainland China have not been established. This study aimed to fill this gap.

METHODS

Based on the Shanghai Link Healthcare Database, patients diagnosed with T2DM and aged 40-99 years were identified between January 1, 2013 and December 31, 2016 and followed until December 31, 2021. All the patients were randomly allocated into training and validation sets at a 2:1 ratio. Cox proportional hazards models were used to develop the all-cause mortality risk prediction model. The model performance was evaluated by discrimination (Harrell C-index) and calibration (calibration plots).

RESULTS

A total of 399 784 patients with T2DM were eventually enrolled, with 68 318 deaths over a median follow-up of 6.93 years. The final prediction model included age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, glycosylated hemoglobin, and high-density lipoprotein cholesterol. The model showed good discrimination and calibration in the validation sets: the mean C-index value was 0.8113 (range 0.8110-0.8115) and the predicted risks closely matched the observed risks in the calibration plots.

CONCLUSIONS

This study constructed the first 5-year all-cause mortality risk prediction model for patients with T2DM in south China, with good predictive performance.

Calibration of the IQVIA Core Diabetes Model to the stroke outcomes from the SUSTAIN 6 cardiovascular outcomes trial of once-weekly semaglutide

AIMS

In the SUSTAIN 6 cardiovascular outcomes trial, once-weekly semaglutide was associated with a statistically significant reduction in major adverse cardiovascular events compared with placebo. To date, no studies have assessed how accurately existing diabetes models predict the outcomes observed in SUSTAIN 6. The aims of this analysis were to investigate the performance of the IQVIA Core Diabetes Model when used to predict the SUSTAIN 6 trial outcomes, to calibrate the model such that projected outcomes reflected observed outcomes, and to examine the impact of calibration on the cost-effectiveness of once-weekly semaglutide from a UK healthcare payer perspective.

METHODS

The IQVIA Core Diabetes Model was calibrated to ensure that the projected non-fatal stroke event rates reflected the non-fatal stroke event rates observed in SUSTAIN 6 over a two-year time horizon. Cost-effectiveness analyses of once-weekly semaglutide versus placebo plus standard of care were conducted over a lifetime horizon using the uncalibrated and calibrated models to assess the impact on cost-effectiveness outcomes.

RESULTS

To replicate the non-fatal stroke event rate in SUSTAIN 6, calibration of the model through the application of relative risks for stroke of 1.07 and 1.65 with once-weekly semaglutide and placebo, respectively, was required. In the long-term cost-effectiveness analysis, the uncalibrated model projected an incremental cost-effectiveness ratio for once-weekly semaglutide versus placebo plus standard of care of GBP 22,262 per quality-adjusted life year (QALY) gained, which fell to GBP 17,594 per QALY gained when the calibrated model was used.

CONCLUSIONS

The requirement for calibration to replicate the outcomes observed in SUSTAIN 6 suggests that the reductions in risk of cardiovascular complications observed with once-weekly semaglutide cannot be solely explained by differences in conventional risk factors. Accurate estimation of the risk of diabetes-related complications using methods such as calibration is important to ensure accurate cost-effectiveness analyses are conducted.

Long-Term Cost-Effectiveness of Subcutaneous Once-Weekly Semaglutide Versus Polyethylene Glycol Loxenatide for Treatment of Type 2 Diabetes Mellitus in China

OBJECTIVE

This study aimed to evaluate the long-term cost-effectiveness of once-weekly subcutaneous semaglutide versus polyethylene glycol loxenatide (PEG-loxenatide) in patients with type 2 diabetes uncontrolled on metformin, from a Chinese healthcare systems perspective.

METHODS

The study applied the Swedish Institute of Health Economics Diabetes Cohort Model to evaluate the long-term clinical and economic outcomes of once-weekly treatment of semaglutide at 0.5 mg and 1.0 mg, respectively, versus PEG-loxenatide 0.2 mg, over a 40-year time horizon. Baseline cohort characteristics were collected from the SUSTAIN China trial. A network meta-analysis was conducted to obtain comparative treatment effects of once-weekly semaglutide and PEG-loxenatide based on two phase 3a clinical trials. Drug costs were sourced from the national bidding price of China. Outcomes were discounted at 5.0% per annum. One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the uncertainty of the base-case results.

RESULTS

When compared with PEG-loxenatide 0.2 mg, the projections of outcomes over the 40-year time horizon in patients with type 2 diabetes uncontrolled on metformin showed that treatment with once-weekly semaglutide 0.5 mg and 1.0 mg were associated with improved discounted life expectancy by 0.08 and 0.12 years, and improved discounted quality-adjusted life expectancy by 0.16 and 0.22 quality-adjusted life-years, respectively. Once-weekly semaglutide 0.5 mg and 1.0 mg were achieved at lifetime cost savings of 19,309 China Yuan (CNY) and 10,179 CNY, respectively. Sensitivity analyses verified the robustness of the results.

CONCLUSION

From the perspective of Chinese healthcare systems, treatment with once-weekly subcutaneous semaglutide represents a dominant option versus PEG-loxenatide for patients with type 2 diabetes uncontrolled on metformin.

Serum Pentosidine is Associated with Cardiac Dysfunction and Atherosclerosis in T2DM

AIM

The purpose of this paper is to investigate the relationship between serum pentosidine levels and cardiac function and vascular disease in diabetic patients, and to provide a new reference indicator for the early detection of diabetic cardiovascular complications.

MATERIALS AND METHODS

This was a cross-sectional study. One hundred and twenty-two patients with type 2 diabetes were grouped by LVEF quartiles to compare the differences between their clinical data and serum pentosidine levels. Also, the correlation between serum pentosidine and clinical indicators was assessed. The effect of serum pentosidine on cardiac function and vascular stiffness was analyzed by multiple stepwise regression.

RESULTS

Serum pentosidine levels were higher in patients with LVEF ≤57%. Serum pentosidine levels were positively correlated with waist-to-hip ratio, hemoglobin, AIP, baPWV, LVESD, and ARD, and negatively correlated with LVEF. Low serum pentosidine was associated with increased LVESD; high pentosidine was significantly associated with increased ARD, high AIP and high baPWV.

CONCLUSION

The results suggest that serum pentosidine, a member of AGEs, may reflect cardiac remodeling and dysfunction as well as atherosclerosis.

Causal evidence in health decision making: methodological approaches of causal inference and health decision science

Objectives

Public health decision making is a complex process based on thorough and comprehensive health technology assessments involving the comparison of different strategies, values and tradeoffs under uncertainty. This process must be based on best available evidence and plausible assumptions. Causal inference and health decision science are two methodological approaches providing information to help guide decision making in health care. Both approaches are quantitative methods that use statistical and modeling techniques and simplifying assumptions to mimic the complexity of the real world. We intend to review and lay out both disciplines with their aims, strengths and limitations based on a combination of textbook knowledge and expert experience.

Methods

To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends.

Results

Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference. Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased.

Conclusions

Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.

Renal function decline and heart failure hospitalisation in patients with type 2 diabetes: Dynamic predictions from the prospective SURDIAGENE cohort

AIMS

For type 2 diabetes persons, we assessed the association between renal function decline and heart failure hospitalisation (HFH) and validated dynamic HFH predictions (DynHFH) based on repeated estimated Glomerular Filtration Rate (eGFR) values.

METHODS

We studied 1413 patients from the SURDIAGENE cohort. From a joint model for longitudinal CKD-EPI measures and HFH risk, we calculated the probability of being HFH-free in the next five years.

RESULTS

The mean eGFR decline was estimated at 1.48 ml/min/1.73 m² per year (95 % CI from 1.23 to 1.74). We observed that eGFR decline was significantly associated with the HFH risk (_adjHR = 1.15 for an increase in yearly decline of 1 ml/min/1.73 m², 95 % CI from 1.03 to 1.26) independently of 7 baseline variables (from clinical, biological and ECG domains). Discrimination was good along the prediction times: AUC at 0.87 (95 %CI from 0.84 to 0.91) at patient inclusion and 0.77 (95 %CI from 0.67 to 0.87) at seven years' follow-up.

CONCLUSIONS

Renal function decline was significantly associated with the HFH risk. In the era of computer-assisted medical decisions, the DynHFH, a tool that dynamically predicts HFH in type 2 diabetes persons (https://shiny.idbc.fr/DynHFH), might be helpful for precision medicine and the implementation of stratified medical decision-making.

Development and Validation of a Lifetime Risk Model for Kidney Failure and Treatment Benefit in Type 2 Diabetes: 10-Year and Lifetime Risk Prediction Models

BACKGROUND AND OBJECTIVES

Individuals with type 2 diabetes are at a higher risk of developing kidney failure. The objective of this study was to develop and validate a decision support tool for estimating 10-year and lifetime risks of kidney failure in individuals with type 2 diabetes as well as estimating individual treatment effects of preventive medication.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

The prediction algorithm was developed in 707,077 individuals with prevalent and incident type 2 diabetes from the Swedish National Diabetes Register for 2002-2019. Two Cox proportional regression functions for kidney failure (first occurrence of kidney transplantation, long-term dialysis, or persistent eGFR <15 ml/min per 1.73 m2) and all-cause mortality as respective end points were developed using routinely available predictors. These functions were combined into life tables to calculate the predicted survival without kidney failure while using all-cause mortality as the competing outcome. The model was externally validated in 256,265 individuals with incident type 2 diabetes from the Scottish Care Information Diabetes database between 2004 and 2019.

RESULTS

During a median follow-up of 6.8 years (interquartile range, 3.2-10.6), 8004 (1%) individuals with type 2 diabetes in the Swedish National Diabetes Register cohort developed kidney failure, and 202,078 (29%) died. The model performed well, with c statistics for kidney failure of 0.89 (95% confidence interval, 0.88 to 0.90) for internal validation and 0.74 (95% confidence interval, 0.73 to 0.76) for external validation. Calibration plots showed good agreement in observed versus predicted 10-year risk of kidney failure for both internal and external validation.

CONCLUSIONS

This study derived and externally validated a prediction tool for estimating 10-year and lifetime risks of kidney failure as well as life years free of kidney failure gained with preventive treatment in individuals with type 2 diabetes using easily available clinical predictors.

PODCAST

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