A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68)

Cost-effectiveness of weight-management pharmacotherapies in Canada: a societal perspective

OBJECTIVES

This study aimed to assess the cost-effectiveness of weight-management pharmacotherapies approved by Canada Health, i.e., orlistat, naltrexone 32 mg/bupropion 360 mg (NB-32), liraglutide 3.0 mg and semaglutide 2.4 mg as compared to the current standard of care (SoC).

METHODS

Analyses were conducted using a cohort with a mean starting age 50 years, body mass index (BMI) 37.5 kg/m2, and 27.6% having type 2 diabetes. Using treatment-specific changes in surrogate endpoints from the STEP trials (BMI, glycemic, blood pressure, lipids), besides a network meta-analysis, the occurrence of weight-related complications, costs, and quality-adjusted life-years (QALYs) were projected over lifetime.

RESULTS

From a societal perspective, at a willingness-to-pay (WTP) threshold of CAD 50 000 per QALY, semaglutide 2.4 mg was the most cost-effective treatment, at an incremental cost-utility ratio (ICUR) of CAD 31 243 and CAD 29 014 per QALY gained versus the next best alternative, i.e., orlistat, and SoC, respectively. Semaglutide 2.4 mg extendedly dominated other pharmacotherapies such as NB-32 or liraglutide 3.0 mg and remained cost-effective both under a public and private payer perspective. Results were robust to sensitivity analyses varying post-treatment catch-up rates, longer treatment durations and using real-world cohort characteristics. Semaglutide 2.4 mg was the preferred intervention, with a likelihood of 70% at a WTP threshold of CAD 50 000 per QALY gained. However, when the modeled benefits of weight-loss on cancer, mortality, cardiovascular disease (CVD) or osteoarthritis surgeries were removed simultaneously, orlistat emerged as the best value for money compared with SoC, with an ICUR of CAD 35 723 per QALY gained.

CONCLUSION

Semaglutide 2.4 mg was the most cost-effective treatment alternative compared with D&E or orlistat alone, and extendedly dominated other pharmacotherapies such as NB-32 or liraglutide 3.0 mg. Results were sensitive to the inclusion of the combined benefits of mortality, cancer, CVD, and knee osteoarthritis.

Cost-Effectiveness of Routine Monitoring of Long-Term Conditions in Primary Care: Informing Decision Modelling with a Systematic Review in Hypertension, Type 2 Diabetes and Chronic Kidney Disease

BACKGROUND

Long-term conditions (LTCs) are major public health problems with a considerable health-related and economic burden. Modelling is key in assessing costs and benefits of different disease management strategies, including routine monitoring, in the conditions of hypertension, type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) in primary care.

OBJECTIVE

This review aimed to identify published model-based cost-effectiveness studies of routine laboratory testing strategies in these LTCs to inform a model evaluating the cost effectiveness of testing strategies in the UK.

METHODS

We searched the Medline and Embase databases from inception to July 2023; the National Institute for Health and Care Institute (NICE) website was also searched. Studies were included if they were model-based economic evaluations, evaluated testing strategies, assessed regular testing, and considered adults aged >16 years. Studies identified were summarised by testing strategies, model type, structure, inputs, assessment of uncertainty, and conclusions drawn.

RESULTS

Five studies were included in the review, i.e. Markov (n = 3) and microsimulation (n = 2) models. Models were applied within T2DM (n = 2), hypertension (n = 1), T2DM/hypertension (n = 1) and CKD (n = 1). Comorbidity between all three LTCs was modelled to varying extents. All studies used a lifetime horizon, except for a 10-year horizon T2DM model, and all used quality-adjusted life-years as the effectiveness outcome, except a TD2M model that used glycaemic control. No studies explicitly provided a rationale for their selected modelling approach. UK models were available for diabetes and CKD, but these compared only a limited set of routine monitoring tests and frequencies.

CONCLUSIONS

There were few studies comparing routine testing strategies in the UK, indicating a need to develop a novel model in all three LTCs. Justification for the modelling technique of the identified studies was lacking. Markov and microsimulation models, with and without comorbidities, were used; however, the findings of this review can provide data sources and inform modelling approaches for evaluating the cost effectiveness of testing strategies in all three LTCs.

Referrals for proliferative diabetic retinopathy from two UK diabetic retinopathy screening services: a 10-year analysis of visual outcomes, requirement for vitrectomy, and mortality

BACKGROUND/OBJECTIVES

To determine long-term outcomes of patients referred with proliferative diabetic retinopathy (PDR) from diabetic eye screening programmes (DESP) to tertiary care centres in the United Kingdom (UK).

METHODS

Retrospective multicentre study of patients referred from two DESPs in the UK over a 36-month period (2007-9) and followed-up for 10 years. Critical outcomes included severe vision loss (SVL) and the need for vitrectomy. Other outcomes assessed included moderate vision loss (MVL), and patient survival time. Univariate and multiple variable Cox proportional hazards regressions were used to analyse survival outcomes.

RESULTS

212 eyes of 150 patients were referred with a diagnosis of PDR. 109 eyes of 72 patients were confirmed to have active PDR and included in the study. 61% of patients had low-risk PDR, while 39% exhibited high-risk features in at least one eye. Eight (7.3%) eyes developed SVL and 16 (14.7%) MVL during follow up. Vitrectomy was required in 24% (95% CI: 15 to 31%) of all PDR eyes and was most commonly performed for vitreous haemorrhage (65%). The 10-year survival in all PDR patients was 76% (95% CI: 63 to 85%) with the mean time to death for all deceased patients being 5.4 ± 3.6 years. On multivariable analysis, only age was found to have a significant association with the survival of patients with PDR.

CONCLUSIONS

During the 10 year follow up SVL was uncommon, but MVL occurred in almost one-fifth of the eyes. Approximately 1 in 4 eyes required vitrectomy, highlighting its significance in patient management.

Evaluating the Preferences and Willingness-to-Pay for Oral Antidiabetic Drugs Among Patients with Type 2 Diabetes Mellitus in China: A Discrete Choice Experiment

PURPOSE

To quantify the preferences for an oral antidiabetic drug (OAD) among patients with type 2 diabetes mellitus (T2DM) in China.

METHODS

A discrete choice experiment (DCE) with hypothetical OAD profiles was performed among patients with T2DM recruited from both online and offline sources. Each patient completed 12 DCE choice tasks. The attributes, elicited through mixed methods, include blood glucose level decrease, blood glucose level stability, frequency of medication, gastrointestinal side effects, dose adjustment and out-of-pocket expense. The conditional logit regression model was used to analyze the data. Patients' willingness-to-pay (WTP) was also calculated. Subgroup analyses based on patient characteristics were also conducted.

RESULTS

A total of 741 respondents were included in the analysis sample, covering 456 respondents online and 285 offline. The result showed that all attributes and levels were statistically significant, except one level "dose adjustment required for patients with hepatic or renal insufficiency" in the attribute of dose adjustment. WTP results showed that patients were willing to pay 12.06 and 23.20 yuan, respectively to reduce the frequency of medication from "once per day" and "three times per day" to "once every 2 weeks", respectively. Subgroup analyses showed that the frequency of medication (once versus two to three times per day) had the largest impact and influenced most coefficient estimates.

CONCLUSION

The results suggest that Chinese patients with T2DM prioritized better efficacy, less frequency of medication, lower gastrointestinal side effects, no dose adjustment required for patients with hepatic or renal insufficiency, and less out-of-pocket expense of OAD treatment.

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.

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.

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.

Tirzepatide 10 and 15 mg vs semaglutide 2.0 mg: A long-term cost-effectiveness analysis in patients with type 2 diabetes in the United States

BACKGROUND

Tirzepatide is a novel glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist approved for type 2 diabetes (T2D) treatment.

OBJECTIVE

To compare the long-term cost-effectiveness of tirzepatide 10 mg and 15 mg vs semaglutide 2.0 mg, an injectable glucagon-like peptide-1 receptor agonist, in patients with T2D from a US health care payer perspective.

METHODS

The PRIME T2D Model was used to project clinical and cost outcomes over a 50-year time horizon. Baseline cohort characteristics and treatment effects were sourced from a published adjusted indirect treatment comparison that used data from the SURPASS-2 and SUSTAIN FORTE trials. Patients were assumed to intensify to insulin therapy at a hemoglobin A1c of greater than 7.5%. Costs and health state utilities were derived from published sources. Future costs and clinical benefits were discounted at 3% annually.

RESULTS

Tirzepatide 10 mg and 15 mg were associated with improved quality-adjusted life-expectancy (10 mg: 0.085 quality-adjusted life-years [QALYs], 15 mg: 0.121 QALYs), higher direct costs (10 mg: USD 5,990, 15 mg: USD 6,617), and incremental cost-effectiveness ratios of USD 70,147 and 54,699 per QALY gained, respectively, vs semaglutide 2.0 mg. Both doses of tirzepatide remained cost-effective vs semaglutide 2.0 mg over a range of sensitivity analyses.

CONCLUSIONS

Long-term projections using the PRIME T2D model and based on treatment effects from an adjusted indirect treatment comparison indicate that tirzepatide 10 mg and 15 mg are likely to be cost-effective vs semaglutide 2.0 mg for the treatment of T2D in the United States.

Microsimulation Models on Mental Health: A Critical Review of the Literature

OBJECTIVES

To retrieve and synthesize the literature on existing mental health-specific microsimulation models or generic microsimulation models used to examine mental health, and to critically appraise them.

METHODS

All studies on microsimulation and mental health published in English in MEDLINE, Embase, PsycINFO, and EconLit between January 1, 2010, and September 30, 2022, were considered. Snowballing, Google searches, and searches on specific journal websites were also undertaken. Data extraction was done on all studies retrieved and the reporting quality of each model was assessed using the Quality Assessment Reporting for Microsimulation Models checklist, a checklist developed by the research team. A narrative synthesis approach was used to synthesize the evidence.

RESULTS

Among 227 potential hits, 19 studies were found to be relevant. Some studies covered existing economic-demographic models, which included a component on mental health and were used to answer mental-health-related research questions. Other studies were focused solely on mental health and included models that were developed to examine the impact of specific policies or interventions on specific mental disorders or both. Most models examined were of medium quality. The main limitations included the use of model inputs based on self-reported and/or cross-sectional data, small and/or nonrepresentative samples and simplifying assumptions, and lack of model validation.

CONCLUSIONS

This review found few high-quality microsimulation models on mental health. Microsimulation models developed specifically to examine mental health are important to guide healthcare delivery and service planning. Future research should focus on developing high-quality mental health-specific microsimulation models with wide applicability and multiple functionalities.

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.

Blood Monocyte Phenotype Is A Marker of Cardiovascular Risk in Type 2 Diabetes

BACKGROUND

Diabetes is a major risk factor for atherosclerotic cardiovascular diseases with a 2-fold higher risk of cardiovascular events in people with diabetes compared with those without. Circulating monocytes are inflammatory effector cells involved in both type 2 diabetes (T2D) and atherogenesis.

METHODS

We investigated the relationship between circulating monocytes and cardiovascular risk progression in people with T2D, using phenotypic, transcriptomic, and metabolomic analyses. cardiovascular risk progression was estimated with coronary artery calcium score in a cohort of 672 people with T2D.

RESULTS

Coronary artery calcium score was positively correlated with blood monocyte count and frequency of the classical monocyte subtype. Unsupervised k-means clustering based on monocyte subtype profiles revealed 3 main endotypes of people with T2D at varying risk of cardiovascular events. These observations were confirmed in a validation cohort of 279 T2D participants. The predictive association between monocyte count and major adverse cardiovascular events was validated through an independent prospective cohort of 757 patients with T2D. Integration of monocyte transcriptome analyses and plasma metabolomes showed a disruption of mitochondrial pathways (tricarboxylic acid cycle, oxidative phosphorylation pathway) that underlined a proatherogenic phenotype.

CONCLUSIONS

In this study, we provide evidence that frequency and monocyte phenotypic profile are closely linked to cardiovascular risk in patients with T2D. The assessment of monocyte frequency and count is a valuable predictive marker for risk of cardiovascular events in patients with T2D.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04353869.

External validation of the UK prospective diabetes study (UKPDS) risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran

Background

Cardiovascular diseases are the first leading cause of mortality in the world. Practical guidelines recommend an accurate estimation of the risk of these events for effective treatment and care. The UK Prospective Diabetes Study (UKPDS) has a risk engine for predicting CHD risk in patients with type 2 diabetes, but in some countries, it has been shown that the risk of CHD is poorly estimated. Hence, we assessed the external validity of the UKPDS risk engine in patients with type 2 diabetes identified in the national diabetes program in Iran.

Methods

The cohort included 853 patients with type 2diabetes identified between March 21, 2007, and March 20, 2018 in Lorestan province of Iran. Patients were followed for the incidence of CHD. The performance of the models was assessed in terms of discrimination and calibration. Discrimination was examined using the c-statistic and calibration was assessed with the Hosmer-Lemeshow χ2 statistic (HLχ2) test and a calibration plot was depicted to show the predicted risks versus observed ones.

Results

During 7464.5 person-years of follow-up 170 first Coronary heart disease occurred. The median follow-up was 8.6 years. The UKPDS risk engine showed moderate discrimination for CHD (c-statistic was 0.72 for 10-year risk) and the calibration of the UKPDS risk engine was poor (HLχ2 = 69.9, p < 0.001) and the UKPDS risk engine78% overestimated the risk of heart disease in patients with type 2 diabetes identified in the national diabetes program in Iran.

Conclusion

This study shows that the ability of the UKPDS Risk Engine to discriminate patients who developed CHD events from those who did not; was moderate and the ability of the risk prediction model to accurately predict the absolute risk of CHD (calibration) was poor and it overestimated the CHD risk. To improve the prediction of CHD in patients with type 2 diabetes, this model should be updated in the Iranian diabetic population.

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.

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.

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.

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.

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.

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).

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.

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.

Long-term cost-effectiveness analysis of tirzepatide versus semaglutide 1.0 mg for the management of type 2 diabetes in the United States

AIM

To evaluate the long-term cost-effectiveness of tirzepatide (5, 10 and 15 mg doses), a novel glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist, versus semaglutide 1.0 mg, an injectable glucagon-like peptide-1 receptor agonist, based on the results of the head-to-head SURPASS-2 trial, from a US healthcare payer perspective.

MATERIALS AND METHODS

The PRIME Type 2 Diabetes Model was used to make projections of clinical and cost outcomes over a 50-year time horizon. Baseline cohort characteristics, treatment effects and adverse event rates were derived from the 40-week SURPASS-2 trial. Intensification to insulin therapy occurred when HbA1c reached 7.5%, in line with American Diabetes Association recommendations. Direct costs in 2021 US dollars (US$) and health state utilities were derived from published sources. Future costs and clinical benefits were discounted at 3% annually.

RESULTS

All three doses of tirzepatide were associated with lower diabetes-related complication rates, improved life expectancy, improved quality-adjusted life expectancy and higher direct costs versus semaglutide. This resulted in incremental cost-effectiveness ratios of US$ 75 803, 58 908 and 48 785 per quality-adjusted life year gained for tirzepatide 5, 10 and 15 mg, respectively, versus semaglutide. Tirzepatide remained cost-effective versus semaglutide over a range of sensitivity analyses.

CONCLUSIONS

Long-term projections based on the SURPASS-2 trial results indicate that 5, 10 and 15 mg doses of tirzepatide are likely to be cost-effective versus semaglutide 1.0 mg for the treatment of type 2 diabetes in the United States.

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.

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.

Cost-Effectiveness Analysis of Flash Glucose Monitoring System for People with Type 2 Diabetes Receiving Intensive Insulin Treatment

AIMS

For people with type 2 diabetes (T2D) on intensive insulin therapy, the use of flash continuous glucose monitoring ("flash monitoring") is associated with improved average glucose control and/or reduced hypoglycemic exposure. This study assessed the cost-effectiveness of flash monitoring versus traditional blood glucose monitoring (BGM) in people with T2D using intensive insulin in the United Kingdom (UK).

METHODS

The IQVIA CORE Diabetes Model (IQVIA CDM; v9.0) was used to analyze the impact of flash monitoring versus BGM over a 40-year time horizon from the UK payer perspective. Model inputs included baseline characteristics, intervention effects, resource utilization, costs, and utilities, based on recently published literature and national databases. UK National Health Service reimbursed costs of flash monitoring and BGM were used. An intervention-related health utility was obtained from a time trade-off study. Alternative scenarios were explored to assess the impact of key assumptions on base case results.

RESULTS

In base-case analysis, flash monitoring compared with BGM resulted in an incremental cost of £5781 and an additional 0.47 quality-adjusted life years (QALYs). This provides an incremental cost-effectiveness ratio (ICER) of £12,309/QALY. HbA1c and the intervention-related health utility were the key drivers of differentiation. All scenario analyses, including different discount rates, time horizons, effects on HbA1c and on the intervention-related health utility, as well as glycemic emergencies, generated ICERs of less than £20,000 per QALY.

CONCLUSIONS

The consistent results across base case and a range of scenario analyses indicate that long-term flash glucose monitoring use is cost-effective compared with BGM in a UK population of T2D on intensive insulin therapy based on updated clinical effects and a cost-effectiveness threshold of £20,000-30,000 per QALY.

Precision prognostics for the development of complications in diabetes

Individuals with diabetes face higher risks for macro- and microvascular complications than their non-diabetic counterparts. The concept of precision medicine in diabetes aims to optimise treatment decisions for individual patients to reduce the risk of major diabetic complications, including cardiovascular outcomes, retinopathy, nephropathy, neuropathy and overall mortality. In this context, prognostic models can be used to estimate an individual's risk for relevant complications based on individual risk profiles. This review aims to place the concept of prediction modelling into the context of precision prognostics. As opposed to identification of diabetes subsets, the development of prediction models, including the selection of predictors based on their longitudinal association with the outcome of interest and their discriminatory ability, allows estimation of an individual's absolute risk of complications. As a consequence, such models provide information about potential patient subgroups and their treatment needs. This review provides insight into the methodological issues specifically related to the development and validation of prediction models for diabetes complications. We summarise existing prediction models for macro- and microvascular complications, commonly included predictors, and examples of available validation studies. The review also discusses the potential of non-classical risk markers and omics-based predictors. Finally, it gives insight into the requirements and challenges related to the clinical applications and implementation of developed predictions models to optimise medical decision making.

Derivation and External Validation of a Clinical Model to Predict Heart Failure Onset in Patients With Incident Diabetes

OBJECTIVE

Heart failure (HF) often develops in patients with diabetes and is recognized for its role in increased cardiovascular morbidity and mortality in this population. Most existing models predict risk in patients with prevalent rather than incident diabetes and fail to account for sex differences in HF risk factors. We derived sex-specific models in Ontario, Canada to predict HF at diabetes onset and externally validated these models in the U.K.

RESEARCH DESIGN AND METHODS

Retrospective cohort study using international population-based data. Our derivation cohort comprised all Ontario residents aged ≥18 years who were diagnosed with diabetes between 2009 and 2018. Our validation cohort comprised U.K. patients aged ≥35 years who were diagnosed with diabetes between 2007 and 2017. Primary outcome was incident HF. Sex-stratified multivariable Fine and Gray subdistribution hazard models were constructed, with death as a competing event.

RESULTS

A total of 348,027 Ontarians (45% women) and 54,483 U.K. residents (45% women) were included. At 1, 5, and 9 years, respectively, in the external validation cohort, the C-statistics were 0.81 (95% CI 0.79-0.84), 0.79 (0.77-0.80), and 0.78 (0.76-0.79) for the female-specific model; and 0.78 (0.75-0.80), 0.77 (0.76-0.79), and 0.77 (0.75-0.79) for the male-specific model. The models were well-calibrated. Age, rurality, hypertension duration, hemoglobin, HbA1c, and cardiovascular diseases were common predictors in both sexes. Additionally, mood disorder and alcoholism (heavy drinker) were female-specific predictors, while income and liver disease were male-specific predictors.

CONCLUSIONS

Our findings highlight the importance of developing sex-specific models and represent an important step toward personalized lifestyle and pharmacologic prevention of future HF development.

Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model

Management of diabetes requires a multifaceted approach of risk factor reduction; through management of risk factors such as glucose, blood pressure and cholesterol. Goals for these risk factors often vary and guidelines suggest that this is based on patient characteristics and need to be individualized. Evaluating risk is therefore critically important to determine goals and choose appropriate treatments. A risk engine is an analytic tool that collects a large amount of population data allowing the simulation of the progression of diabetes with set equations over a period of time. Recently, a number of data cohorts have become available, leading to the development of newer risk engines that are more dynamic and generalizable. An example is the Building, Relating, Assessing, and Validating Outcomes in (BRAVO) diabetes model which was built on the ACCORD trial database. It is capable of accurately predicting diabetes comorbidities in an international population based on calibration with international clinical trial data. It has potential uses in risk stratification of patients, evaluation of interventions and calculation of their long term cost effectiveness. Recently, it has been used to simulate long term outcomes based on short term data, using difference modelling scenarios.

Long-Term Cost-Effectiveness Analysis of Once-Weekly Semaglutide versus Dulaglutide in Patients with Type 2 Diabetes with Inadequate Glycemic Control in China

INTRODUCTION

The objective of the current study was to assess the long-term cost-effectiveness of once-weekly semaglutide 0.5 mg and 1.0 mg versus dulaglutide 1.5 mg for the treatment of patients with type 2 diabetes uncontrolled on metformin in the Chinese setting.

METHODS

The Swedish Institute of Health Economics Diabetes Cohort Model (IHE-DCM) was used to evaluate the long-term health and economic outcomes of once-weekly semaglutide and dulaglutide. Analysis was conducted from the perspective of the Chinese healthcare systems over a time horizon of 40 years. Data on baseline cohort characteristics and treatment effects were sourced from the SUSTAIN 7 clinical trial. Costs included treatment costs and costs of complications. Projected health and economic outcomes were discounted at a rate of 5% annually. The robustness of the results was evaluated through one-way sensitivity analyses and probabilistic sensitivity analyses.

RESULTS

Compared with dulaglutide 1.5 mg, once-weekly semaglutide 0.5 mg and 1.0 mg were associated with improvements in discounted life expectancy of 0.04 and 0.10 years, respectively, and improvements in discounted quality-adjusted life expectancy of 0.08 and 0.19 quality-adjusted life years (QALYs), respectively. Clinical benefits were achieved at reduced costs, with lifetime cost savings of 8355 Chinese Yuan (CNY) with once-weekly semaglutide 0.5 mg and 11,553 CNY with once-weekly semaglutide 1.0 mg. Sensitivity analyses verified the robustness of the research results.

CONCLUSIONS

Once-weekly semaglutide was suggested to be dominant (more effective and less costly) versus dulaglutide 1.5 mg in patients with type 2 diabetes uncontrolled on metformin treatment in China.

First-Line Therapy for Type 2 Diabetes With Sodium-Glucose Cotransporter-2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists : A Cost-Effectiveness Study

BACKGROUND

Guidelines recommend sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP1) receptor agonists as second-line therapy for patients with type 2 diabetes. Expanding their use as first-line therapy has been proposed but the clinical benefits may not outweigh their costs.

OBJECTIVE

To evaluate the lifetime cost-effectiveness of a strategy of first-line SGLT2 inhibitors or GLP1 receptor agonists.

DESIGN

Individual-level Monte Carlo-based Markov model.

DATA SOURCES

Randomized trials, Centers for Disease Control and Prevention databases, RED BOOK, and the National Health and Nutrition Examination Survey.

TARGET POPULATION

Drug-naive U.S. patients with type 2 diabetes.

TIME HORIZON

Lifetime.

PERSPECTIVE

Health care sector.

INTERVENTION

First-line SGLT2 inhibitors or GLP1 receptor agonists.

OUTCOME MEASURES

Life expectancy, lifetime costs, incremental cost-effectiveness ratios (ICERs).

RESULTS OF BASE-CASE ANALYSIS

First-line SGLT2 inhibitors and GLP1 receptor agonists had lower lifetime rates of congestive heart failure, ischemic heart disease, myocardial infarction, and stroke compared with metformin. First-line SGLT2 inhibitors cost $43 000 more and added 1.8 quality-adjusted months versus first-line metformin ($478 000 per quality-adjusted life-year [QALY]). First-line injectable GLP1 receptor agonists cost more and reduced QALYs compared with metformin.

RESULTS OF SENSITIVITY ANALYSIS

By removing injection disutility, first-line GLP1 receptor agonists were no longer dominated (ICER, $327 000 per QALY). Oral GLP1 receptor agonists were not cost-effective (ICER, $823 000 per QALY). To be cost-effective at under $150 000 per QALY, costs for SGLT2 inhibitors would need to be under $5 per day and under $6 per day for oral GLP1 receptor agonists.

LIMITATION

U.S. population and costs not generalizable internationally.

CONCLUSION

As first-line agents, SGLT2 inhibitors and GLP1 receptor agonists would improve type 2 diabetes outcomes, but their costs would need to fall by at least 70% to be cost-effective.

PRIMARY FUNDING SOURCE

American Diabetes Association.

Does the Structure Matter? An External Validation and Health Economic Results Comparison of Event Simulation Approaches in Severe Obesity

OBJECTIVES

As obesity-associated events impact long-term survival, health economic (HE) modelling is commonly applied, but modelling approaches are diverse. This research aimed to compare the events simulation and the HE outcomes produced by different obesity modelling approaches.

METHODS

An external validation, using the Swedish obesity subjects (SOS) study, of three main structural event modelling approaches was performed: (1) continuous body mass index (BMI) approach; (2) risk equation approach; and (3) categorical BMI-related approach. Outcomes evaluated were mortality, cardiovascular events, and type 2 diabetes (T2D) for both the surgery and the control arms. Concordance between modelling results and the SOS study were investigated by different state-of-the-art measurements, and categorized by the grade of deviation observed (grades 1-4 expressing mild, moderate, severe, and very severe deviations). Furthermore, the costs per quality-adjusted life-year (QALY) gained of surgery versus controls were compared.

RESULTS

Overall and by study arm, the risk equation approach presented the lowest average grade of deviation (overall grade 2.50; control arm 2.25; surgery arm 2.75), followed by the continuous BMI approach (overall 3.25; control 3.50; surgery 3.00) and by the categorial BMI approach (overall 3.63; control 3.50; surgery 3.75). Considering different confidence interval limits, the costs per QALY gained were fairly comparable between all structural approaches (ranging from £2,055 to £6,206 simulating a lifetime horizon).

CONCLUSION

None of the structural approaches provided perfect external event validation, although the risk equation approach showed the lowest overall deviations. The economic outcomes resulting from the three approaches were fairly comparable.

Cost-Effectiveness of iGlarLixi Versus Premix BIAsp 30 in People with Type 2 Diabetes Suboptimally Controlled by Basal Insulin in the US

INTRODUCTION

Many people with type 2 diabetes mellitus (T2DM) experience suboptimal glycemic control and require therapy advancement. This cost-effectiveness analysis was conducted to compare iGlarLixi (insulin glargine 100 U/mL plus lixisenatide) versus BIAsp 30 (biphasic insulin aspart 30) in people with T2DM suboptimally controlled with basal insulin.

METHODS

The IQVIA Core Diabetes Model was used to estimate lifetime costs and outcomes for people with T2DM from a US healthcare payer perspective. Initial clinical data were based on the phase 3 randomized, open-label, active-controlled SoliMix clinical study, which compared the efficacy and safety of once-daily iGlarLixi with twice-daily BIAsp 30. Lifetime costs (US$) and quality-adjusted life-years (QALYs) were predicted, and the incremental cost-effectiveness ratio (ICER) for iGlarLixi versus BIAsp 30 was estimated; the willingness-to-pay threshold was considered to be $50,000. A subgroup analysis considered people with T2DM aged ≥ 65 years.

RESULTS

Estimated QALYs gained were slightly higher with iGlarLixi compared with BIAsp 30 (9.3 vs. 9.2), with lower costs for iGlarLixi ($117,854 vs. $120,109); the ICER for iGlarLixi was therefore considered dominant over BIAsp 30 in the base case. Key drivers for cost savings were the higher dose and twice-daily administration for BIAsp 30 versus once-daily administration for iGlarLixi. The robustness of the base-case results was confirmed by sensitivity and scenario analyses. Results were similar in a subgroup of people with T2DM aged ≥ 65 years.

CONCLUSION

In people with T2DM with suboptimal glycemic control on basal insulin, iGlarLixi confers improved QALYs and reduced costs compared with BIAsp 30.

Development and validation of predictive risk models for sight threatening diabetic retinopathy in patients with type 2 diabetes to be applied as triage tools in resource limited settings

Background

Delayed diagnosis and treatment of sight threatening diabetic retinopathy (STDR) is a common cause of visual impairment in people with Type 2 diabetes. Therefore, systematic regular retinal screening is recommended, but global coverage of such services is challenging. We aimed to develop and validate predictive models for STDR to identify 'at-risk' population for retinal screening.

Methods

Models were developed using datasets obtained from general practices in inner London, United Kingdom (UK) on adults with type 2 Diabetes during the period 2007-2017. Three models were developed using Cox regression and model performance was assessed using C statistic, calibration slope and observed to expected ratio measures. Models were externally validated in cohorts from Wales, UK and India.

Findings

A total of 40,334 people were included in the model development phase of which 1427 (3·54%) people developed STDR. Age, gender, diabetes duration, antidiabetic medication history, glycated haemoglobin (HbA1c), and history of retinopathy were included as predictors in the Model 1, Model 2 excluded retinopathy status, and Model 3 further excluded HbA1c. All three models attained strong discrimination performance in the model development dataset with C statistics ranging from 0·778 to 0·832, and in the external validation datasets (C statistic 0·685 - 0·823) with calibration slopes closer to 1 following re-calibration of the baseline survival.

Interpretation

We have developed new risk prediction equations to identify those at risk of STDR in people with type 2 diabetes in any resource-setting so that they can be screened and treated early. Future testing, and piloting is required before implementation.

Funding

This study was funded by the GCRF UKRI (MR/P207881/1) and supported by the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology.

Long-term cost-effectiveness of quality of diabetes care; experiences from private and public diabetes centers in Iran

BACKGROUND

The quality of health care has a significant impact on both patients and the health system in terms of long-term costs and health consequences. This study focuses on determining the long-term cost-effectiveness in quality of diabetes care in two different settings (private/public) using longitudinal patient-level data in Iran.

METHODS

By extracting patients intermediate biomedical markers in under-treatment type 2 diabetes patients(T2DP) in a longitudinal retrospective study and by applying the localized UKPDS diabetes model, lifetime health outcomes including life expectancy, quality-adjusted Life expectancy (QALE) and direct medical costs of managing disease and related complications from a healthcare system perspective was predicted. Costs and utility decrements had derived on under-treatment T2DP from 7 private and 8 Public diabetes centers. We applied two steps sampling mehods to recruit the needed sample size (cluster and random sampling). To cope with first and second-order uncertainty, we used Monte-Carlo simulation and bootstrapping techniques. Both cost and utility variables were discounted by 3% in the base model.

RESULTS

In a 20-year time horizon, according to over 5 years of quality of care data, outcomes-driven in the private sector will be more effective and more costly (5.17 vs. 4.95 QALE and 15,385 vs. 8092). The incremental cost-effectiveness ratio (ICER) was $33,148.02 per QALE gained, which was higher than the national threshold.

CONCLUSION

Although quality of care in private diabetes centers resulted in a slight increase in the life expectancy in T2DM patients, it is associated with unfavorable costs, too. Private-sector in management of T2DM patients, compared with public (governmental) diabetic Centers, is unlikely to be cost-effective in Iran.

Digital Interventions Supporting Self-care in People With Type 2 Diabetes Across Greater Manchester (Greater Manchester Diabetes My Way): Protocol for a Mixed Methods Evaluation

BACKGROUND

Type 2 Diabetes (T2D) is common, with a prevalence of approximately 7% of the population in the United Kingdom. The quality of T2D care is inconsistent across the United Kingdom, and Greater Manchester (GM) does not currently achieve the National Institute for Health and Care Excellence treatment targets. Barriers to delivery of care include low attendance and poor engagement with local T2D interventions, which tend to consist of programs of education delivered in traditional, face-to-face clinical settings. Thus, a flexible approach to T2D management that is accessible to people from different backgrounds and communities is needed. Diabetes My Way (DMW) is a digital platform that offers a comprehensive self-management and educational program that should be accessible to a wide range of people through mobile apps and websites. Building on evidence generated by a Scotland-wide pilot study, DMW is being rolled out and tested across GM.

OBJECTIVE

The overarching objectives are to assess whether DMW improves outcomes for patients with T2D in the GM area, to explore the acceptability of the DMW intervention to stakeholders, and to assess the cost-effectiveness of the intervention.

METHODS

A mixed methods approach will be used. We will take a census approach to recruitment in that all eligible participants in GM will be invited to participate. The primary outcomes will be intervention-related changes compared with changes observed in a matched group of controls, and the secondary outcomes will be within-person intervention-related changes. The cost-effectiveness analysis will focus on obtaining reliable estimates of how each intervention affects risk factors such as HbA1c and costs across population groups. Qualitative data will be collected via semistructured interviews and focus groups and organized using template analysis.

RESULTS

As of May 10, 2021, a total of 316 participants have been recruited for the quantitative study and have successfully enrolled. A total of 278 participants attempted to register but did not have appropriate permissions set by the general practitioners to gain access to their data. In total, 10 participants have been recruited for the qualitative study (7 practitioners and 3 patients). An extension to recruitment has been granted for the quantitative element of the research, and analysis should be complete by December 2022. Recruitment and analysis for the qualitative study should be complete by December 2021.

CONCLUSIONS

The findings from this study can be used both to develop the DMW system and improve accessibility and usability in more deprived populations generally, thus improving equity in access to support for T2D self-management.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/26237.

Exploring Structural Uncertainty and Impact of Health State Utility Values on Lifetime Outcomes in Diabetes Economic Simulation Models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge

BACKGROUND

Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models.

METHODS

Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences.

RESULTS

Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models (P = 0.049).

CONCLUSIONS

Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.HighlightsThe findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs).There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

The transferability and validity of a population-level simulation model for the economic evaluation of interventions in diabetes: the MICADO model

AIMS

Valid health economic models are essential to inform the adoption and reimbursement of therapies for diabetes mellitus. Often existing health economic models are applied in other countries and settings than those where they were developed. This practice requires assessing the transferability of a model developed from one setting to another. We evaluate the transferability of the MICADO model, developed for the Dutch 2007 setting, in two different settings using a range of adjustment steps. MICADO predicts micro- and macrovascular events at the population level.

METHODS

MICADO simulation results were compared to observed events in an Italian 2000-2015 cohort (Casale Monferrato Survey [CMS]) and in a Dutch 2008-2019 (Hoorn Diabetes Care Center [DCS]) cohort after adjusting the demographic characteristics. Additional adjustments were performed to: (1) risk factors prevalence at baseline, (2) prevalence of complications, and (3) all-cause mortality risks by age and sex. Model validity was assessed by mean average percentage error (MAPE) of cumulative incidences over 10 years of follow-up, where lower values mean better accuracy.

RESULTS

For mortality, MAPE was lower for CMS compared to DCS (0.38 vs. 0.70 following demographic adjustment) and adjustment step 3 improved it to 0.20 in CMS, whereas step 2 showed best results in DCS (0.65). MAPE for heart failure and stroke in DCS were 0.11 and 0.22, respectively, while for CMS was 0.42 and 0.41.

CONCLUSIONS

The transferability of the MICADO model varied by event and per cohort. Additional adjustments improved prediction of events for MICADO. To ensure a valid model in a new setting it is imperative to assess the impact of adjustments in terms of model accuracy, even when this involves the same country, but a new time period.

Shortening of leucocyte telomere length is independently correlated with high body mass index and subcutaneous obesity (predominantly truncal), in Asian Indian women with abnormal fasting glycemia

INTRODUCTION

Leucocyte telomere length (LTL) is linked to accelerate aging and premature mortality. In this research, we aimed to explore the relations between biochemical and anthropometry markers and LTL in Asian Indian women with abnormal fasting glycemia (impaired fasting glucose).

RESEARCH DESIGN AND METHODS

In this study, 797 pre-diabetic women (obese, 492; non-obese, 305) were recruited. Demographic and clinical profiles, anthropometry, and fasting blood glucose were evaluated. LTL was quantified by a quantitative PCR. LTL was expressed as the relative telomere length or telomere repeat:single copy gene (T:S) ratio. The subjects were separated into quartiles according to the LTL.

RESULTS

The average LTL was significantly decreased with increasing age. The average LTL was significantly shorter in obese women with abnormal fasting glycemia (p<0.05). R-squared (R²) statistic for multivariable linear model after adjusted for age, family income, education and hypertension showed that LTL was inversely correlated with body mass index (BMI), waist and hip circumference, waist-hip and waist-to-height ratio, truncal skinfolds (subscapular, and subscapular/triceps ratio, central and total skinfolds), fat mass (kg) and % body fat. The relationship between obesity measures and LTL (using the LTL quartile 1 as reference) identified central skinfolds (R²=0.92, p<0.0001), Σ4SF (R²=0.90, p<0.0001), BMI (R²=0.93, p<0.0001) and % body fat (R²=0.91, p<0.0001) as independent predictors of LTL.

CONCLUSIONS

Besides age, obesity and subcutaneous adiposity (predominantly truncal) are major contributors to telomere shortening in Asian Indian women with abnormal fasting glycemia (impaired fasting glucose).

Cost-Effectiveness Analysis of Initiating Type 2 Diabetes Therapy with a Sodium-Glucose Cotransporter 2 Inhibitor Versus Conventional Therapy in Japan

INTRODUCTION

Many patients with type 2 diabetes mellitus (T2DM) suffer from complications that impose substantial burdens on prognosis and medical costs. Accumulating evidence has demonstrated the clinical benefit of sodium-glucose cotransporter 2 inhibitors (SGLT2i) on cardiovascular and renal complications. However, the health economic impact of SGLT2i remains unclear. The aim of this study was to evaluate the cost-effectiveness of initiating antidiabetic therapy with an SGLT2i using Japanese real-world data.

METHODS

We constructed a natural history model incorporating heart failure (HF), myocardial infarction, stroke, chronic kidney disease, and end-stage renal disease (ESRD) as complications. The target population comprised patients with T2DM who newly initiated their first oral glucose-lowering drugs. By using a population-based microsimulation, we estimated the 10-year medical costs in Japanese yen (JPY) and outcomes (hospitalization for/development of complications and quality-adjusted life years [QALY]) for patients who initiated antidiabetic therapy with an SGLT2i or conventional therapy. Sensitivity analyses included a probabilistic sensitivity analysis (PSA) with 1,000,000 iterations.

RESULTS

In the base-case analysis, the total medical cost per person was JPY 1,638,806 versus JPY 1,825,033 and the QALYs were 8.732 versus 8.513 for the SGLT2i strategy versus the conventional strategy, respectively. Thus, initiating treatment with an SGLT2i was dominant, more effective (QALY gain), and lower cost. When treating 10,000 patients, the SGLT2i strategy would reduce all-cause deaths by 410 (552 vs 962), HF events by 201 (897 vs 1098), and ESRD events by 16 (16 vs 32) versus the conventional strategy. The PSA revealed that the probability of dominance for initiating SGLT2i therapy was 90.5%, demonstrating the robustness of the results.

CONCLUSION

Our results suggest that initiating T2DM treatment with SGLT2i, aimed at managing cardiovascular and renal complications from the early stages of diabetes, can improve the clinical outcome and reduce cost burden of T2DM.

Cost-Effectiveness of Once-Weekly Semaglutide 1 mg versus Canagliflozin 300 mg in Patients with Type 2 Diabetes Mellitus in a Canadian Setting

OBJECTIVE

Our objective was to evaluate the long-term cost-effectiveness of once-weekly semaglutide 1 mg versus once-daily canagliflozin 300 mg in patients with type 2 diabetes mellitus (T2DM) uncontrolled with metformin from the healthcare payer and societal perspectives in Canada.

METHODS

Head-to-head data from the SUSTAIN 8 randomised trial (NCT03136484) were extrapolated over 40 years using economic simulation modelling. The cost-effectiveness of once-weekly semaglutide 1 mg versus canagliflozin 300 mg for treating T2DM was estimated using the Swedish Institute for Health Economics-Diabetes Cohort Model (IHE-DCM) and the Economic and Health Outcomes Model of T2DM (ECHO-T2DM). Unit costs and disutility weights capturing treatments and key macro- and microvascular complications were sourced from the literature to best match the Canadian setting. A probabilistic base-case simulation and sensitivity analyses were conducted.

RESULTS

Once-weekly semaglutide 1 mg was associated with reductions in macro- and microvascular complications, yielding incremental cost-effectiveness ratios (ICERs) of (Canadian dollars [CAD]) CAD16,392 and 18,098 per incremental quality-adjusted life-year (QALY) gained versus canagliflozin 300 mg for IHE-DCM and ECHO-T2DM, respectively, from a healthcare payer perspective. Accounting for productivity loss as well, ICERs were CAD14,127 and 13,188 per QALY gained for IHE-DCM and ECHO-T2DM, respectively, from a societal perspective. Sensitivity analyses confirmed that the base-case results were robust to changes in input parameters and assumptions used.

CONCLUSIONS

At a willingness-to-pay threshold of CAD50,000 per QALY gained, once-weekly semaglutide 1 mg was cost-effective over 40 years versus once-daily canagliflozin 300 mg for the treatment of T2DM in patients failing to maintain glycemic control with metformin alone.

Cost-Effectiveness of iGlarLixi Versus Premix BIAsp 30 in Patients with Type 2 Diabetes Suboptimally Controlled by Basal Insulin in the UK

INTRODUCTION

iGlarLixi is indicated as an adjunct to diet and exercise in addition to metformin (with or without sodium-glucose cotransporter-2 inhibitors) to improve glycemic control in adults with insufficiently controlled type 2 diabetes (T2D). A cost-effectiveness analysis was conducted to compare iGlarLixi with premix biphasic insulin aspart 30 (BIAsp 30) in people with T2D suboptimally controlled with basal insulin (BI).

METHODS

The IQVIA CORE Diabetes Model was used to estimate lifetime costs and outcomes for people with T2D from a UK health care perspective at a willingness-to-pay threshold of £20,000. Initial clinical data were based on the phase 3 randomized, open-label, active-controlled SoliMix clinical trial which compared the efficacy and safety of once-daily iGlarLixi with that of twice-daily BIAsp 30. Costs associated with management and complications and utilities values were derived from published sources. Lifetime costs (in £GBP) and quality-adjusted life-years (QALYs) were predicted; extensive scenario and sensitivity analyses were conducted.

RESULTS

Estimated QALYs gained were slightly higher with iGlarLixi (8.9 vs. 8.8) compared with premix BIAsp 30, at a higher cost (£23,204 vs. £21,961). The base case incremental cost-effectiveness ratio (ICER) per QALY was £13,598. Treatment acquisition was the main driver of cost differences (iGlarLixi, £11,750; premix BIAsp 30, £10,395). Costs associated with management and complications were generally similar between comparators.

CONCLUSION

iGlarLixi provides improved QALY outcomes at an acceptable cost compared with premix BIAsp 30, with an ICER below the threshold generally considered acceptable by UK authorities. In people with T2D, iGlarLixi is a simple, cost-effective option for advancing therapy of BI, with fewer daily injections than premix BIAsp 30.

Long-Term Cost Effectiveness of Oral Semaglutide Versus Empagliflozin and Sitagliptin for the Treatment of Type 2 Diabetes in the Swedish Setting

OBJECTIVE

The aim of this study was to assess the cost effectiveness of oral semaglutide versus other oral glucose-lowering drugs for the management of type 2 diabetes (T2D) in Sweden.

METHODS

The Swedish Institute for Health Economics Diabetes Cohort Model was used to assess the cost effectiveness of oral semaglutide 14 mg versus empagliflozin 25 mg and oral semaglutide 14 mg versus sitagliptin 100 mg, using data from the head-to-head PIONEER 2 and 3 trials, respectively, in which these treatments were added to metformin (± sulphonylurea). Base-case and scenario analyses were conducted. Robustness was evaluated with deterministic and probabilistic sensitivity analyses.

RESULTS

In the base-case analyses, greater initial lowering of glycated haemoglobin levels with oral semaglutide versus empagliflozin and oral semaglutide versus sitagliptin, respectively, resulted in reduced incidences of micro- and macrovascular complications and was associated with lower costs of complications and indirect costs. Treatment costs were higher for oral semaglutide, resulting in higher total lifetime costs than with empagliflozin (Swedish Krona [SEK] 1,245,570 vs. 1,210,172) and sitagliptin (SEK1,405,789 vs. 1,377,381). Oral semaglutide was shown to be cost effective, with an incremental cost-effectiveness ratio (ICER) of SEK239,001 per quality-adjusted life-year (QALY) compared with empagliflozin and SEK120,848 per QALY compared with sitagliptin, from a payer perspective. ICERs were lower at SEK191,721 per QALY compared with empagliflozin and SEK95,234 per QALY compared with sitagliptin from a societal perspective. Results were similar in scenario analyses that incorporated cardiovascular effects, and also in sensitivity analyses.

CONCLUSIONS

In a Swedish setting, oral semaglutide was cost effective compared with empagliflozin and sitagliptin for patients with T2D inadequately controlled on oral glucose-lowering drugs.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02863328 (PIONEER 2; registered 11 August 2016) and NCT02607865 (PIONEER 3; registered 18 November 2015).

Modeling Chronic Kidney Disease in Type 2 Diabetes Mellitus: A Systematic Literature Review of Models, Data Sources, and Derivation Cohorts

INTRODUCTION

As novel therapies for chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM) become available, their long-term benefits should be evaluated using CKD progression models. Existing models offer different modeling approaches that could be reused, but it may be challenging for modelers to assess commonalities and differences between the many available models. Additionally, the data and underlying population characteristics informing model parameters may not always be evident. Therefore, this study reviewed and summarized existing modeling approaches and data sources for CKD in T2DM, as a reference for future model development.

METHODS

This systematic literature review included computer simulation models of CKD in T2DM populations. Searches were implemented in PubMed (including MEDLINE), Embase, and the Cochrane Library, up to October 2021. Models were classified as cohort state-transition models (cSTM) or individual patient simulation (IPS) models. Information was extracted on modeled kidney disease states, risk equations for CKD, data sources, and baseline characteristics of derivation cohorts in primary data sources.

RESULTS

The review identified 49 models (21 IPS, 28 cSTM). A five-state structure was standard among state-transition models, comprising one kidney disease-free state, three kidney disease states [frequently including albuminuria and end-stage kidney disease (ESKD)], and one death state. Five models captured CKD regression and three included cardiovascular disease (CVD). Risk equations most commonly predicted albuminuria and ESKD incidence, while the most predicted CKD sequelae were mortality and CVD. Most data sources were well-established registries, cohort studies, and clinical trials often initiated decades ago in predominantly White populations in high-income countries. Some recent models were developed from country-specific data, particularly for Asian countries, or from clinical outcomes trials.

CONCLUSION

Modeling CKD in T2DM is an active research area, with a trend towards IPS models developed from non-Western data and single data sources, primarily recent outcomes trials of novel renoprotective treatments.

Cost-effectiveness of second-line empagliflozin versus liraglutide for type 2 diabetes in the United States

AIM

To estimate the cost-effectiveness of sequential use of the sodium-glucose co-transporter-2 inhibitor empagliflozin and glucagon-like peptide-1 receptor agonist liraglutide after metformin in patients with type 2 diabetes (T2D) from the US payer perspective.

MATERIALS AND METHODS

An economic simulation model with a lifetime horizon was developed to estimate T2D-related complications (including cardiovascular [CV] death, myocardial infarction, stroke, and renal outcomes) using EMPA-REG OUTCOME data or UK Prospective Diabetes Study risk equations, in patients with or without a history of cardiovascular disease (CVD), respectively. Evidence synthesis methods were used to provide effectiveness inputs for empagliflozin and liraglutide. Population characteristics, adverse event rates, treatment escalation, costs ($2019), and utilities (both discounted 3%/year) were taken from US sources.

RESULTS

Compared with second-line liraglutide in the overall T2D population, second-line empagliflozin was dominant as it was associated with lower total lifetime cost ($11 244/patient less) and resulted in a quality-adjusted life-year (QALY) gain (0.32/patient). Second-line empagliflozin was associated with reductions in CV death (by 5%) and lower cumulative complication rates in patients with CVD (by 2%), relative to second-line liraglutide. These findings were consistent among patients with co-morbid CVD, with gains in incremental QALYs (0.43/patient) and lower lifetime cost (by $10 175/patient) relative to second-line liraglutide. Scenario analyses consistently showed dominance for second-line empagliflozin.

CONCLUSION

For patients with T2D, use of second-line empagliflozin combined with metformin was a dominant strategy for US payers, associated with extended survival, improved QALYs, and lower costs compared with second-line liraglutide.

Potential Gains in Life Expectancy Associated With Achieving Treatment Goals in US Adults With Type 2 Diabetes

Importance

Improvements in control of factors associated with diabetes risk in the US have stalled and remain suboptimal. The benefit of continually improving goal achievement has not been evaluated to date.

Objective

To quantify potential gains in life expectancy (LE) among people with type 2 diabetes (T2D) associated with lowering glycated hemoglobin (HbA1c), systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), and body mass index (BMI) toward optimal levels.

Design, Setting, and Participants

In this decision analytical model, the Building, Relating, Assessing, and Validating Outcomes (BRAVO) diabetes microsimulation model was calibrated to a nationally representative sample of adults with T2D from the National Health and Nutrition Examination Survey (2015-2016) using their linked short-term mortality data from the National Death Index. The model was then used to conduct the simulation experiment on the study population over a lifetime. Data were analyzed from January to October 2021.

Exposure

The study population was grouped into quartiles on the basis of levels of HbA1c, SBP, LDL-C, and BMI. LE gains associated with achieving better control were estimated by moving people with T2D from the current quartile of each biomarker to the lower quartiles.

Main Outcomes and Measures

Life expectancy.

Results

Among 421 individuals, 194 (46%) were women, and the mean (SD) age was 65.6 (8.9) years. Compared with a BMI of 41.4 (mean of the fourth quartile), lower BMIs of 24.3 (first), 28.6 (second), and 33.0 (third) were associated with 3.9, 2.9, and 2.0 additional life-years, respectively, in people with T2D. Compared with an SBP of 160.4 mm Hg (fourth), lower SBP levels of 114.1 mm Hg (first), 128.2 mm Hg (second), and 139.1 mm Hg (third) were associated with 1.9, 1.5, and 1.1 years gained in LE in people with T2D, respectively. A lower LDL-C level of 59 mg/dL (first), 84.0 mg/dL (second), and 107.0 mg/dL (third) were associated with 0.9, 0.7, and 0.5 years gain in LE, compared with LDL-C of 146.2 mg/dL (fourth). Reducing HbA1c from 9.9% (fourth) to 7.7% (third) was associated with 3.4 years gain in LE. However, a further reduction to 6.8% (second) was associated with only a mean of 0.5 years gain in LE, and from 6.8% to 5.9% (first) was not associated with LE benefit. Overall, reducing HbA1c from the fourth quartile to the first is associated with an LE gain of 3.8 years.

Conclusions and Relevance

These findings can be used by clinicians to motivate patients in achieving the recommended treatment goals and to help prioritize interventions and programs to improve diabetes care in the US.

Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings

AIMS/HYPOTHESIS

We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes.

METHODS

Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation.

RESULTS

We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001).

CONCLUSIONS/INTERPRETATION

CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability.

The Cost-Effectiveness of Subcutaneous Semaglutide Versus Empagliflozin in Type 2 Diabetes Uncontrolled on Metformin Alone in Denmark

INTRODUCTION

International and Danish guidelines recommend the use of glucagon-like peptide 1 receptor agonists (GLP-1 RA) and sodium-glucose cotransporter 2 (SGLT-2) inhibitors already in second line in the management of type 2 diabetes (T2D). The objective of this study was to evaluate the long-term cost-effectiveness (CE) of subcutaneous (SC) semaglutide (GLP-1 RA) versus empagliflozin (SGLT-2 inhibitor) in individuals with T2D uncontrolled on metformin alone from a Danish payer's perspective.

METHODS

Cost-effectiveness analyses (CEA) were conducted from a Danish payer's perspective, using the IQVIA Core Diabetes model (CDM 9.5), with a time horizon of 50 years and an annual discount of 4% on costs and effects. Patients received either SC semaglutide or empagliflozin, in addition to metformin, until HbA1c threshold of 7.5% (58 mmol/mol) was reached, following which treatment intensification with insulin glargine in addition to empagliflozin or SC semaglutide plus metformin was considered. Baseline cohort characteristics and treatment effects were sourced from a published CEA. Utilities and cost of diabetes-related complications were also obtained from published sources. Treatment costs were derived from Danish official sources. Scenario analyses were also performed to test the accuracy of the base case results.

RESULTS

Individuals with T2D on SC semaglutide plus metformin gained 0.065 life-years (LYs) and 0.130 quality-adjusted LYs (QALYs), respectively, at an incremental cost of DKK 96,923 (€ 13,031) compared to empagliflozin plus metformin, resulting in an incremental cost-effectiveness ratio (ICER) of DKK 745,561(€ 100,239) per QALY gained. The probabilistic sensitivity analysis (PSA) results showed that the SC semaglutide plus metformin was cost-effective in 19% of simulations assuming a willingness-to-pay (WTP) threshold of DKK 357,100 (€ 48,011)/QALY gained. Duration of therapy with SC semaglutide seems the key driver of results.

CONCLUSION

The current analyses suggest that SC semaglutide plus metformin is not cost-effective compared to empagliflozin plus metformin from a Danish payer's perspective.