Prospective Diabetes Study Outcomes Model Research Articles

Using QALYs as an Outcome for Assessing Global Prediction Accuracy in Diabetes Simulation Models.

(1) To demonstrate the use of quality-adjusted life-years (QALYs) as an outcome measure for comparing performance between simulation models and identifying the most accurate model for economic evaluation and health technology assessment. QALYs relate directly to decision making and combine mortality and diverse clinical events into a single measure using evidence-based weights that reflect population preferences. (2) To explore the usefulness of Q2, the proportional reduction in error, as a model performance metric and compare it with other metrics: mean squared error (MSE), mean absolute error, bias (mean residual), and R2. We simulated all EXSCEL trial participants (N = 14,729) using the UK Prospective Diabetes Study Outcomes Model software versions 1 (UKPDS-OM1) and 2 (UKPDS-OM2). The EXSCEL trial compared once-weekly exenatide with placebo (median 3.2-y follow-up). Default UKPDS-OM2 utilities were used to estimate undiscounted QALYs over the trial period based on the observed events and survival. These were compared with the QALYs predicted by UKPDS-OM1/2 for the same period. UKPDS-OM2 predicted patients' QALYs more accurately than UKPDS-OM1 did (MSE: 0.210 v. 0.253; Q2: 0.822 v. 0.786). UKPDS-OM2 underestimated QALYs by an average of 0.127 versus 0.150 for UKPDS-OM1. UKPDS-OM2 predictions were more accurate for mortality, myocardial infarction, and stroke, whereas UKPDS-OM1 better predicted blindness and heart disease. Q2 facilitated comparisons between subgroups and (unlike R2) was lower for biased predictors. Q2 for QALYs was useful for comparing global prediction accuracy (across all clinical events) of diabetes models. It could be used for model registries, choosing between simulation models for economic evaluation and evaluating the impact of recalibration. Similar methods could be used in other disease areas. Diabetes simulation models are currently validated by examining their ability to predict the incidence of individual events (e.g., myocardial infarction, stroke, amputation) or composite events (e.g., first major adverse cardiovascular event).We introduce Q2, the proportional reduction in error, as a measure that may be useful for evaluating and comparing the prediction accuracy of econometric or simulation models.We propose using the Q2 or mean squared error for QALYs as global measures of model prediction accuracy when comparing diabetes models' performance for health technology assessment; these can be used to select the most accurate simulation model for economic evaluation and to evaluate the impact of model recalibration in diabetes or other conditions.

Cost-utility analysis and drug pricing of once-weekly insulin icodec versus once-daily insulin degludec for type 2 diabetes patients treated with basal insulin in China.

Insulin icodec is a first once-weekly administration basal insulin analogue for type 2 diabetes. This study aimed to investigate the price range of icodec for type 2 diabetes in the Chinese market, taking insulin degludec as reference. Long-term health outcomes and costs for icodec and degludec were simulated using the United Kingdom Prospective Diabetes Study Outcomes Model (version 2.1) over 40 years from the Chinese healthcare provider's perspective. The efficacy and safety data were obtained from the ONWARDS 2 trial (Switching to once-weekly insulin icodec versus once-daily insulin degludec in individuals with basal insulin-treated type 2 diabetes (ONWARDS 2): a phase 3a, randomised, open label, multicentre, treat-to-target trial). Cost-utility analysis and a binary search were used to investigate the price range of icodec. Sensitivity analyses were performed to verify the robustness of the base-case analysis results. After a 40-year simulation, the quality-adjusted life years (QALY) of icodec and degludec were 10.32 and 10.28 years, respectively. At the initial assumption of the same annual costs of icodec and degludec of $455.40, icodec was the dominant therapy compared with degludec, with higher QALYs and lower total cost. After the binary search, we observed that the annual cost range of icodec was $625.17-$855.25. This cost range was finally adjusted to be $597.66-$736.34 using one-way sensitivity analysis and confirmed using probabilistic sensitivity analysis and scenario analysis. The scenario analysis revealed that the annual cost range of icodec could be $506.70-$736.34 if the price of degludec decreased by 20% in the future. Insulin icodec appears to be more cost effective than degludec if the annual cost of icodec ranges from $597.66 to $736.34 for patients with type 2 diabetes in China.

Estimating Risk Factor Time Paths Among People with Type 2 Diabetes and QALY Gains from Risk Factor Management.

Most type 2 diabetes simulation models utilise equations mapping out lifetime trajectories of risk factors [e.g. glycated haemoglobin (HbA1c)]. Existing equations, using historic data or assuming constant risk factors, frequently underestimate or overestimate complication rates. Updated risk factor time path equations are needed for simulation models to more accurately predict complication rates. (1) Update United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2) risk factor time path equations; (2) compare quality-adjusted life-years (QALYs) using original and updated equations; and (3) compare QALY gains for reference case simulations using different risk factor equations. Using pooled contemporary data from two randomised trials EXSCEL and TECOS (n = 28,608), we estimated: dynamic panel models of seven continuous risk factors (high-density lipoprotein cholesterol, low density lipoprotein cholesterol, HbA1c, haemoglobin, heart rate, blood pressure and body mass index); two-step models of estimated glomerular filtration rate; and survival analyses of peripheral arterial disease, atrial fibrillation and albuminuria. UKPDS-OM2-derived lifetime QALYs were extrapolated over 70 years using historical and the new risk factor equations. All new risk factor equation predictions were within 95% confidence intervals of observed values, displaying good agreement between observed and estimated values. Historical risk factor time path equations predicted trial participants would accrue 9.84 QALYs, increasing to 10.98 QALYs using contemporary equations. Incorporating updated risk factor time path equations into diabetes simulation models could give more accurate predictions of long-term health, costs, QALYs and cost-effectiveness estimates, as well as a more precise understanding of the impact of diabetes on patients' health, expenditure and quality of life. ClinicalTrials.gov NCT01144338 and NCT00790205.

Comparison of prediction models for cardiovascular and mortality risk in people with type 2 diabetes: An external validation in 23 685 adults included in the UK Biobank.

To validate cardiovascular risk prediction models for individuals with diabetes using the UK Biobank in order to assess their applicability. We externally validated 19 cardiovascular risk scores from seven risk prediction models (Chang et al., Framingham, University of Hong Kong-Singapore [HKU-SG], Li et al, RECODe [risk equations for complications of type 2 diabetes], SCORE [Systematic Coronary Risk Evaluation] and the UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2]), identified from systematic reviews, using UK Biobank data from 2006 to 2021 (n = 23 685; participant age 40-71 years, 63.5% male). We evaluated performance by assessing the discrimination and calibration of the models for the endpoints of mortality, cardiovascular mortality, congestive heart failure, myocardial infarction, stroke, and ischaemic heart disease. Over a total of 269 430 person-years of follow-up (median 11.89 years), the models showed low-to-moderate discrimination performance on external validation (concordance indices [c-indices] 0.50-0.71). Most models had low calibration with overprediction of the observed risk. RECODe outperformed other models across four comparable endpoints for discrimination: all-cause mortality (c-index 0.67, 95% confidence interval [CI] 0.65-0.69), congestive heart failure (c-index 0.71, 95% CI 0.69-0.72), myocardial infarction (c-index 0.67, 95% CI 0.65-0.68); and stroke (c-index 0.65, 95% CI 0.62-0.68), and for calibration (except for all-cause mortality). The UKPDS OM2 had comparable performance to RECODe for all-cause mortality (c-index 0.67, 95% CI 0.66-0.69) and cardiovascular mortality (c-index 0.71, 95% CI 0.70-0.73), but worse performance for other outcomes. The models performed better for younger participants and somewhat better for non-White ethnicities. Models developed from non-Western datasets showed worse performance in our UK-based validation set. The RECODe model led to better risk estimations in this predominantly White European population. Further validation is needed in non-Western populations to assess generalizability to other populations.

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

An integrated care program was set up in China to improve the collaboration between primary healthcare centers and hospitals on diabetes management. This study aims to evaluate the economic value of this program with real-world data and to examine whether it can be promoted in primary healthcare settings in China. This integrated diabetes care program was implemented in Yuhuan City, China, to coordinate primary care and specialty care, treatment and prevention services, as well as the responsibilities of doctors and nurses. Cost-effectiveness analysis was used to compare the short-term economic value of this program (intervention group) versus usual diabetes management (control group). The cost data were collected from a societal perspective, while the effectiveness indicators pointed to the improvement of control rates of fasting blood glucose (FBG), systolic blood pressure (SBP), and diastolic blood pressure (DBP) levels after the 1 year intervention. In addition, cost-utility analysis was applied to evaluate the long-term value of the two groups. Patients' long-term diabetes management costs and quality-adjusted life years (QALYs) were simulated by the United Kingdom Prospective Diabetes Study Outcomes Model 2. The results showed that for 1% FBG, SPB, and DBP control rate improvement, the costs for the intervention group were 290.53, 124.39, and 249.15 Chinese Yuan (CNY), respectively, while the corresponding costs for the control group were 655.19, 610.43, and 1460.25 CNY. Thus, the intervention group's cost-effectiveness ratios were lower than those of the control group. In addition, compared to the control group, the intervention group's incremental costs per QALY improvement were 102.67 thousand CNY, which means that the intervention was cost-effective according to the World Health Organization's standards. In conclusion, this study suggested that this integrated diabetes care program created short-term and long-term economic values through patient self-management support, primary care strengthening, and care coordination. As this program followed the principles of integrated care reform, it can be promoted in China. Also, its elements can provide valuable experience for other researchers to build customized integrated care models.

Estimation of HbA1c after weight loss using a beta-regression for an economic evaluation of a behavioural weight management programme from the GLoW trial: a methodological study

BackgroundIn economic evaluations, average intervention effects are usually applied to a population. However, this fails to reflect the change in the distribution of HbA1c due to heterogeneous responses to weight loss. We aimed to investigate whether allowing heterogeneous treatment effects using a beta regression better represented the distribution of HbA1c after a weight-loss intervention, and how this affected cost effectiveness. MethodsThe Glucose Lowering through Weight Management (GLoW) trial evaluated the effectiveness of a diabetes education and weight-loss intervention against a standard diabetes education programme. Adults diagnosed with type 2 diabetes within 3 years were recruited from Clinical Commissioning Groups across 159 sites in England from July 20, 2018, to July 22, 2018. Ethics approval (18/ES/0048) and participant informed consent were obtained. Considering the between-treatment-arm difference in HbA1c after 12 months, we compared a mean-effect estimated from a mixed-effects regression to a heterogeneous effect estimated from a beta regression performed on 12-month HbA1c conditional on baseline HbA1c, gender, diabetes duration and intervention group. We used the School of Public Health Research (SPHR) Diabetes Treatment model to apply these treatment effects and evaluate the lifetime NHS costs and quality-adjusted life-years (QALYs), discounted at 3·5%. The microsimulation model estimated diabetes-related health outcomes using the UK Prospective Diabetes Study Outcomes Model 2 risk equations and risk factor trajectory equations, alongside estimating diabetes remission, osteoarthritis, and cancer. We calculated the incremental net benefit (INB) of the intervention using a £20 000 per QALY valuation, by deterministic analysis. The GLoW trial is registered with the ISRCTN Registry, ISRCTN18399564. FindingsThe trial recruited 577 participants (mean age 60 years; 278 [53%] female, 247 [47%] male; 474 [91%] white ethnic background). Applying heterogeneous HbA1c changes better reproduced the skewness in post-intervention HbA1c than applying a mean-effect (Kolmogorov-Smirnov test p=0·02 compared with p=0·0000007). The beta-regression method suggested the intervention was more cost-effective, estimating an INB of £736 per person, compared with £584 when applying the mean-effect. InterpretationAlternative regression specification methods should be considered when evaluating the cost-effectiveness of interventions if the key intervention outcomes are not normally distributed. However, this alternative method requires further investigation to conclude its appropriateness in evaluating cost-effectiveness in different contexts. FundingNational Institute for Health and Care Research (NIHR) Programme Grants for Applied Research Programme (Reference Number RP-PG0216-20010).

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

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

Potential Value of Identifying Type 2 Diabetes Subgroups for Guiding Intensive Treatment: A Comparison of Novel Data-Driven Clustering With Risk-Driven Subgroups.

To estimate the impact on lifetime health and economic outcomes of different methods of stratifying individuals with type 2 diabetes, followed by guideline-based treatment intensification targeting BMI and LDL in addition to HbA1c. We divided 2,935 newly diagnosed individuals from the Hoorn Diabetes Care System (DCS) cohort into five Risk Assessment and Progression of Diabetes (RHAPSODY) data-driven clustering subgroups (based on age, BMI, HbA1c, C-peptide, and HDL) and four risk-driven subgroups by using fixed cutoffs for HbA1c and risk of cardiovascular disease based on guidelines. The UK Prospective Diabetes Study Outcomes Model 2 estimated discounted expected lifetime complication costs and quality-adjusted life-years (QALYs) for each subgroup and across all individuals. Gains from treatment intensification were compared with care as usual as observed in DCS. A sensitivity analysis was conducted based on Ahlqvist subgroups. Under care as usual, prognosis in the RHAPSODY data-driven subgroups ranged from 7.9 to 12.6 QALYs. Prognosis in the risk-driven subgroups ranged from 6.8 to 12.0 QALYs. Compared with homogenous type 2 diabetes, treatment for individuals in the high-risk subgroups could cost 22.0% and 25.3% more and still be cost effective for data-driven and risk-driven subgroups, respectively. Targeting BMI and LDL in addition to HbA1c might deliver up to 10-fold increases in QALYs gained. Risk-driven subgroups better discriminated prognosis. Both stratification methods supported stratified treatment intensification, with the risk-driven subgroups being somewhat better in identifying individuals with the most potential to benefit from intensive treatment. Irrespective of stratification approach, better cholesterol and weight control showed substantial potential for health gains.

EE137 Evaluating the Effects of the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model Risk Factor Progression Equations on Cost-Utility Outcomes in Type 2 Diabetes: Analyses Using the Prime Diabetes Model

The United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS OM) and the risk equations that drive it remain widely used in the economic modeling of type 2 diabetes mellitus. Two versions of the UKPDS OM have been developed and published to-date (OM1 and OM2). The UKPDS OM2 was based on substantially longer follow-up, was derived from more events, and captured more complications and covariates than UKPDS OM1. The objective was to evaluate differences in the performance of the OM1 and OM2 risk factor trajectory equations for glycated hemoglobin (HbA1c) and systolic blood pressure (SBP) in economic evaluations.

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

The main research purpose is to compare the long-term cost-effectiveness of semaglutide (SEMA) with that of dulaglutide (DULA) for patients with inadequately controlled type 2 diabetes throughout their lifetime. If necessary, the second aim is to investigate a further price cut for SEMA to provide sound advice for government drug price adjustments. Cost-utility analysis was performed by the United Kingdom Prospective Diabetes Study Outcomes Model 2 (UKPDS OM2) from the perspective of health care providers in China. Baseline characteristics and clinical efficacy of SEMA and DULA were sourced from the high-dose comparison in the SUSTAIN-7 trial. A binary search was used to identify the scope for further reduction in the price of SEMA. The impact of individual parameters was assessed with sensitivity analyses. Main analysis (SEMA vs. DULA) revealed a mean difference in quality-adjusted life years (QALYs) of 0.04 QALYs and costs of $1132.29. The incremental cost-utility ratio was $26 957.44/QALY, showing that SEMA was a better option compared with DULA. In sensitivity analyses, the discount rate made the greatest contribution to the incremental cost-utility ratio. In the binary search, there was still scope to reduce the SEMA cost further by approximately 6.83% to be cost-effective, taking DULA as a reference. After its addition to the National Medical Insurance System in China, SEMA is expected to be a cost-effective choice compared with DULA for patients with type 2 diabetes with inadequately controlled from the cost-utility analysis. However, there is still scope to reduce the annual cost of SEMA further.

894-P: The Potential Value of Clustering-Based Type 2 Diabetes Subgroups for Guiding Intensive Treatment: A Maximum Cost-Based Comparison with Threshold-Based Classifications

Aim: To quantify and compare the performance of setting priority for intensive treatment by novel clustering-based subgroups to threshold-based classifications using systematic coronary risk evaluation (SCORE) and HbA1c levels. Methods: We divided 2,935 patients from the Hoorn diabetes care system cohort into five clustering-based subgroups: severe insulin-deficient (SIDD) , severe insulin-resistant (SIRD) , mild obesity-related (MOD) mild (MD) , and mild with high HDL-cholesterol (MDH) diabetes, and four risk threshold-based subgroups. The United Kingdom Prospective Diabetes Study Outcomes Model was used to simulate lifetime health outcomes in the U.S. and U.K. settings. Gains from hypothetical treatment scenarios based on clinical guidelines were compared to “care-as-usual” and expressed in incremental quality-adjusted life-expectancy (QALE) and complication costs. Results: The SIRD and MOD subgroup had the lowest absolute and age-sex-standardized QALE, respectively (7.90; 9.07) . Threshold-based classifications better discriminated between patients with higher and lower absolute and standardized QALE than clustering-based subgroups. For MOD, hypothetical interventions costing up to $1973 (95%CI $1444-$2603) and £463 (95%CI £345-£603) per year would be cost-effective at $100,000 and £20,000 per QALY thresholds in the U.S. and U.K., respectively. The MOD, SIDD and SIRD subgroups had the best potential cost-effectiveness alongside the subgroup with high HbA1c and high SCORE. Conclusions: Intensified treatment could be cost-effective at higher-than-average costs for three out of five of the clustering-based subgroups and two out of four of the threshold-based classifications. Both classification methods support priority setting for intensive treatment, but the threshold-based method may better identify those who have the most potential to benefit from intensified treatment. Disclosure X.Li: None. A.Van giessen: None. J.Altunkaya: None. R.Slieker: None. J.Beulens: None. E.Pearson: Speaker's Bureau; Sanofi. P.J.M.Elders: None. T.Feenstra: Research Support; Dutch Healthcare Institute (ZIN) , European Union/IMI Rhapsody. J.Leal: None. Funding RHAPSODY (115881)

Cost-Utility of an Online Education Platform and Diabetes Personal Health Record: Analysis Over Ten Years.

My Diabetes My Way (MDMW) is Scotland's interactive website and mobile app for people with diabetes and their caregivers. It contains multimedia resources for diabetes education and offers access to electronic personal health records. This study aims to assess the cost-utility of MDMW compared with routine diabetes care in people with type 2 diabetes who do not use insulin. Analysis used the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model 2. Clinical parameters of MDMW users (n = 2576) were compared with a matched cohort of individuals receiving routine care alone (n = 11 628). Matching criteria: age, diabetes duration, sex, and socioeconomic status. Impact on life expectancy, quality-adjusted life years (QALYs), and costs of treatment and complications were simulated over ten years, including a 10% sensitivity analysis. MDMW cohort: 1670 (64.8%) men; average age 64.3 years; duration of diabetes 5.5 years. 906 (35.2%) women: average age 61.6 years; duration 4.7 years. The cumulative mean QALY (95% CI) gain: 0.054 (0.044-0.062) years. Mean difference in cost: -£118.72 (-£150.16 to -£54.16) over ten years. Increasing MDMW costs (10%): -£50.49 (-£82.24-£14.14). Decreasing MDMW costs (10%): -£186.95 (-£218.53 to -£122.51). MDMW is "dominant" over usual care (cost-saving and life improving) in supporting self-management in people with type 2 diabetes not treated with insulin. Wider use may result in significant cost savings through delay or reduction of long-term complications and improved QALYs in Scotland and other countries. MDMW may be among the most cost-effective interventions currently available to support diabetes.

Lifetime cost-effectiveness simulation of once-weekly exenatide in type 2 diabetes: A cost-utility analysis based on the EXSCEL trial

AimsThe Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial assessed once-weekly exenatide (EQW) vs. placebo, added to usual care in 14,752 patients with type 2 diabetes mellitus (Clinicaltrials.gov: NCT01144338). We assessed the lifetime cost-effectiveness of adding EQW vs. usual care alone from a healthcare perspective. MethodsMedical resource use and EQ-5D utilities were collected throughout the study. Within-trial results were extrapolated to a lifetime horizon using the UK Prospective Diabetes Study Outcomes Model version 2 (UKPDS-OM2), predicting predict cardiovascular and microvascular events. Cost-effectiveness was evaluated separately for US and UK settings, with outcomes measured in quality-adjusted life-years (QALYs). ResultsEQW plus usual care gained 0.162 QALYs at an additional cost of $41,545/patient, compared with usual care in a US setting. The incremental cost-effectiveness ratio (ICER) was $259,223/QALY. In a UK setting, the QALY gain was 0.151 at an additional cost of £6357: an ICER of £42,589/QALY. Sensitivity analyses ranged between $34,369–$269,571 and £3430–£46,560 per QALY gained. ConclusionsIn a lifetime extrapolation, adding EQW to usual care increased QALYs and costs compared with usual care alone. The base-case ICERs exceeded the commonly-cited cost-effectiveness thresholds of $100,000/QALY and £20,000/QALY. However, ICERs were considerably lower in some subgroups, and in sensitivity analyses.

Lifetime Cost-effectiveness of Oral Semaglutide Versus Dulaglutide and Liraglutide in Patients With Type 2 Diabetes Inadequately Controlled With Oral Antidiabetics

PurposeTo estimate the incremental cost-utility ratio of oral semaglutide (14 mg once daily) vs other glucagon-like peptide 1 receptor agonist treatments among adults with type 2 diabetes that was inadequately controlled with 1 to 2 oral antidiabetic drugs from a US payer perspective. MethodsA state-transition model with a competing risk approach was developed for diabetic complications and risk of cardiovascular events based on the UK Prospective Diabetes Study Outcomes Model 1 equations. Baseline population characteristics reflect the PIONEER 4 trial (Efficacy and Safety of Oral Semaglutide Versus Liraglutide and Versus Placebo in Subjects With Type 2 Diabetes Mellitus) of oral semaglutide. Model comparators included subcutaneous semaglutide, dulaglutide, and liraglutide. Treatment effects (change in glycosylated hemoglobin, weight, and systolic blood pressure) were estimated by network meta-analysis. Drug, management, and event costs (in 2019 US dollars), survival after nonfatal events, and utilities were obtained from the literature. Costs and quality-adjusted life-year (QALY) outcomes were discounted at 3% annually over a lifetime horizon. Probabilistic and 1-way sensitivity analyses were performed. FindingsTotal estimated costs and QALYs were $144,065 and 12.98 for oral semaglutide, $145,721 and 12.96 for dulaglutide, $145,833 and 12.99 for SC semaglutide, and $149,428 and 12.97 for liraglutide, respectively. Oral semaglutide was less costly and more effective than dulaglutide and liraglutide but less costly than subcutaneous semaglutide with similar effectiveness. Oral semaglutide was favored versus subcutaneous semaglutide in 52.10% of model replications at a willingness-to-pay of $150,000 per QALY. ImplicationsOral semaglutide is predicted to offer health benefits similar to subcutaneous semaglutide and ahead of dulaglutide and liraglutide. Oral semaglutide is a cost-effective glucagon-like peptide 1 receptor agonist treatment option.

Performance of the UK Prospective Diabetes Study Outcomes Model 2 in a Contemporary UK Type 2 Diabetes Trial Cohort

ObjectivesThe UK Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS-OM) developed using 30-year (1977-2007) data from the UKPDS is widely used for health outcomes’ projections and economic evaluations of therapies for patients with type 2 diabetes (T2D). Nevertheless, its reliability for contemporary UK T2D populations is unclear. We assessed the performance of version 2 of the model (UKPDS-OM2) using data from A Study of Cardiovascular Events in Diabetes (ASCEND), which followed participants with diabetes in the UK between 2005 and 2017. MethodsThe UKPDS-OM2 was used to predict the occurrence of myocardial infarction (MI), other ischemic heart disease, stroke, cardiovascular (CV) death, and other death among the 14 569 participants with T2D in ASCEND, all without previous CV disease at study entry. Calibration (comparison of predicted and observed year-on-year cumulative incidence over 10 years) and discrimination (c-statistics) of the model were assessed for each endpoint. The percentage error in event rates at year 7 (mean duration of follow up) was used to quantify model bias. ResultsThe UKPDS-OM2 substantially overpredicted MI, stroke, CV death, and other death over the 10-year follow-up period (by 149%, 42%, 269%, and 52%, respectively, at year 7). Discrimination of the model for MI and other ischemic heart disease (c-statistics 0.58 and 0.60, respectively) was poorer than that for other outcomes (c-statistics ranging from 0.66 to 0.72). ConclusionsThe UKPDS-OM2 substantially overpredicted risks of key CV outcomes and death in people with T2D in ASCEND. Appropriate adjustments or a new model may be required for assessments of long-term effects of treatments in contemporary T2D cohorts.

Estimating risk factor progression equations for the UKPDS Outcomes Model 2 (UKPDS 90).

To estimate 13equations that predict clinically plausible risk factor time paths to inform the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model version 2 (UKPDS-OM2). Data from 5102 UKPDS participants from the 20-year trial, and the 4031survivors with 10years further post-trial follow-up, were used to derive equations for the time paths of 13clinical risk factors: HbA1c , systolic blood pressure, LDL-cholesterol, HDL-cholesterol, BMI, micro- or macro-albuminuria, creatinine, heart rate, white blood cell count, haemoglobin, estimated glomerular filter rate, atrial fibrillation and peripheral vascular disease (PVD). The incidence of events and death predicted by the UKPDS-OM2 when informed by the new risk factor equations was compared with the observed cumulative rates up to 25years. The new equations were based on 24years of follow-up and up to 65,252 person-years of data. Women were associated with higher values of all continuous risk factors except for haemoglobin. Older age and higher BMI at diagnosis were associated with higher rates of PVD (HR 1.06 and 1.02), atrial fibrillation (HR 1.10 and 1.08) and micro- or macro-albuminuria (HR 1.01 and 1.18). Smoking was associated with higher rates of developing PVD (HR 2.38) and micro- and macro-albuminuria (HR 1.39). The UKPDS-OM2, informed by the new risk factor equations, predicted event rates for complications and death consistent with those observed. The new equations allow risk factor time paths beyond observed data, which should improve modelling of long-term health outcomes for people with type 2 diabetes when using the UKPDS-OM2 or other models.

Development and validation of the CHIME simulation model to assess lifetime health outcomes of prediabetes and type 2 diabetes in Chinese populations: A modeling study.

Existing predictive outcomes models for type 2 diabetes developed and validated in historical European populations may not be applicable for East Asian populations due to differences in the epidemiology and complications. Despite the continuum of risk across the spectrum of risk factor values, existing models are typically limited to diabetes alone and ignore the progression from prediabetes to diabetes. The objective of this study is to develop and externally validate a patient-level simulation model for prediabetes and type 2 diabetes in the East Asian population for predicting lifetime health outcomes. We developed a health outcomes model from a population-based cohort of individuals with prediabetes or type 2 diabetes: Hong Kong Clinical Management System (CMS, 97,628 participants) from 2006 to 2017. The Chinese Hong Kong Integrated Modeling and Evaluation (CHIME) simulation model comprises of 13 risk equations to predict mortality, micro- and macrovascular complications, and development of diabetes. Risk equations were derived using parametric proportional hazard models. External validation of the CHIME model was assessed in the China Health and Retirement Longitudinal Study (CHARLS, 4,567 participants) from 2011 to 2018 for mortality, ischemic heart disease, cerebrovascular disease, renal failure, cataract, and development of diabetes; and against 80 observed endpoints from 9 published trials using 100,000 simulated individuals per trial. The CHIME model was compared to United Kingdom Prospective Diabetes Study Outcomes Model 2 (UKPDS-OM2) and Risk Equations for Complications Of type 2 Diabetes (RECODe) by assessing model discrimination (C-statistics), calibration slope/intercept, root mean square percentage error (RMSPE), and R2. CHIME risk equations had C-statistics for discrimination from 0.636 to 0.813 internally and 0.702 to 0.770 externally for diabetes participants. Calibration slopes between deciles of expected and observed risk in CMS ranged from 0.680 to 1.333 for mortality, myocardial infarction, ischemic heart disease, retinopathy, neuropathy, ulcer of the skin, cataract, renal failure, and heart failure; 0.591 for peripheral vascular disease; 1.599 for cerebrovascular disease; and 2.247 for amputation; and in CHARLS outcomes from 0.709 to 1.035. CHIME had better discrimination and calibration than UKPDS-OM2 in CMS (C-statistics 0.548 to 0.772, slopes 0.130 to 3.846) and CHARLS (C-statistics 0.514 to 0.750, slopes -0.589 to 11.411); and small improvements in discrimination and better calibration than RECODe in CMS (C-statistics 0.615 to 0.793, slopes 0.138 to 1.514). Predictive error was smaller for CHIME in CMS (RSMPE 3.53% versus 10.82% for UKPDS-OM2 and 11.16% for RECODe) and CHARLS (RSMPE 4.49% versus 14.80% for UKPDS-OM2). Calibration performance of CHIME was generally better for trials with Asian participants (RMSPE 0.48% to 3.66%) than for non-Asian trials (RMPSE 0.81% to 8.50%). Main limitations include the limited number of outcomes recorded in the CHARLS cohort, and the generalizability of simulated cohorts derived from trial participants. Our study shows that the CHIME model is a new validated tool for predicting progression of diabetes and its outcomes, particularly among Chinese and East Asian populations that has been lacking thus far. The CHIME model can be used by health service planners and policy makers to develop population-level strategies, for example, setting HbA1c and lipid targets, to optimize health outcomes.

Cost-effectiveness of oral semaglutide added to current antihyperglycemic treatment for type 2 diabetes

BACKGROUND: Oral semaglutide is the first oral formulation of a glucagon-like peptide 1 (GLP-1) receptor agonist to be approved in the United States for glycemic control in people with type 2 diabetes mellitus (T2DM). While oral semaglutide is not indicated for reduction of cardiovascular event risk, its label does include evidence of no increase in cardiovascular risk in people who received oral semaglutide. OBJECTIVE: To estimate the incremental value of oral semaglutide added to existing antihyperglycemic treatment for people with T2DM with additional risk for cardiovascular disease. METHODS: We estimated the lifetime cost-effectiveness of oral semaglutide added to current antihyperglycemic treatment for T2DM using a microsimulation model based primarily on the UK Prospective Diabetes Study (UKPDS) Outcomes Model 2 (OM2) equations. Oral semaglutide added to current antihyperglycemic treatment was separately compared with (a) ongoing background antihyperglycemic treatment, (b) sitagliptin, (c) empagliflozin, and (d) liraglutide. Comparators sitagliptin, empagliflozin, and liraglutide were added to ongoing antihyperglycemic treatment. We applied hazard ratios derived from a network meta-analysis for cardiovascular and renal outcomes to the UKPDS OM2 estimated baseline rates. Health state utilities and costs were derived from the published literature. We estimated total costs, life-years (LYs), quality-adjusted life-years (QALYs), clinical events, and cost per major adverse cardiovascular event (MACE) avoided, over a lifetime time horizon using discount rates of 3% for costs and outcomes. RESULTS: The lifetime total cost for people treated with oral semaglutide was $311,300, with costs for the other comparators ranging from $262,800 (background treatment alone) to $287,800 (liraglutide). Oral semaglutide resulted in the fewest MACE, including the fewest cardiovascular deaths. Among the 5 modeled treatment strategies, oral semaglutide had the highest LYs gained (8.43 vs. 7.76 [background treatment alone] to 8.29 [empagliflozin and liraglutide]) and the highest QALYs gained (4.11 vs. 3.70 [background treatment alone] to 4.03 [empagliflozin]). Oral semaglutide would likely be considered cost-effective compared with liraglutide (incremental cost-effectiveness ratio [ICER] = $40,100), and moderately cost-effective versus background treatment alone ([ICER] = $117,500/QALY) and sitagliptin (ICER = $145,200/QALY). The ICER for oral semaglutide compared with empagliflozin was approximately $458,400 per QALY. CONCLUSIONS: As modeled, oral semaglutide as an add-on therapy to background antihyperglycemic treatment produced incremental benefits in MACE avoided, along with greater QALYs compared with background antihyperglycemic treatment alone. Oral semaglutide use resulted in better outcomes than background treatment alone or sitagliptin, and similar outcomes to liraglutide or empagliflozin with overlapping 95% confidence ranges for QALYs. Oral semaglutide was estimated to be cost-effective compared with liraglutide and to have incremental cost-effectiveness ratios between $100,000 and $150,000 per QALY versus sitagliptin and background therapy alone, but it did not meet these thresholds compared with empagliflozin. DISCLOSURES: Funding for this study was provided by the Institute for Clinical and Economic Review, an independent organization that evaluates the evidence on the value of health care interventions. ICER reports grants from Laura and John Arnold Foundation, California Health Care Foundation, Harvard Pilgrim Health Care, and Kaiser Foundation Health Plan. ICER's annual policy summit is supported by dues from AbbVie, Aetna, America's Health Insurance Plans, Anthem, Alnylam, AstraZeneca, Biogen, Blue Shield of CA, Cambia Health Services, CVS, Editas, Evolve Pharmacy, Express Scripts, Genentech/Roche, GlaxoSmithKline, Harvard Pilgrim, Health Care Service Corporation, Health Partners, Humana, Johnson & Johnson (Janssen), Kaiser Permanente, LEO Pharma, Mallinckrodt, Merck, Novartis, National Pharmaceutical Council, Premera, Prime Therapeutics, Regeneron, Sanofi, Spark Therapeutics, uniQure, and United Healthcare. Rind, Fazioli, Chapman, and Pearson are employed by ICER. Guzauskas and Hansen have nothing to disclose. Study results were presented at the New England Comparative Effectiveness Public Advisory Council (New England CEPAC), November 14, 2019, at Brown University, Providence, RI.

An Intuitive Risk Communication Tool to Enhance Patient–Provider Partnership in Diabetes Consultation

This technology report introduces an innovative risk communication tool developed to support providers in communicating diabetes-related risks more intuitively to people with type 2 diabetes mellitus (T2DM). The development process involved three main steps: (1) selecting the content and format of the risk message; (2) developing a digital interface; and (3) assessing the usability and usefulness of the tool with clinicians through validated questionnaires. The tool calculates personalized risk information based on a validated simulation model (United Kingdom Prospective Diabetes Study Outcomes Model 2) and delivers it using more intuitive risk formats, such as "effective heart age" to convey cardiovascular risks. Clinicians reported high scores for the usability and usefulness of the tool, making its adoption in routine care promising. Despite increased use of risk calculators in clinical care, this is the first time that such a tool has been developed in the diabetes area. Further studies are needed to confirm the benefits of using this tool on behavioral and health outcomes in T2DM populations.

Macrovascular Risk Equations Based on the CANVAS Program.

Widely used risk equations for cardiovascular outcomes for individuals with type 2 diabetes mellitus (T2DM) have been incapable of predicting cardioprotective effects observed in recent cardiovascular outcomes trials (CVOTs) involving individuals with T2DM at high risk for or with established cardiovascular disease (CVD). We developed cardiovascular and mortality risk equations using patient-level data from the CANVAS (CANagliflozin cardioVascular Assessment Study) Program to address this shortcoming. Data from 10,142 patients with T2DM at high risk for or with established CVD, randomized to canagliflozin + standard of care (SoC) or SoC alone and followed for a mean duration of 3.6 years in the CANVAS Program were used to derive parametric risk equations for myocardial infarction (MI), stroke, hospitalization for heart failure (HHF), and death. Accumulated knowledge from the widely used UKPDS-OM2 (United Kingdom Prospective Diabetes Study Outcomes Model 2) was leveraged, and any departures in parameterization were limited to those necessary to provide adequate goodness of fit. Candidate explanatory covariates were selected using only the placebo arm to minimize confounding effects. Internal validation was performed separately by study treatment arm. UKPDS-OM2 predicted CANVAS Program outcomes poorly. Recalibrating UKPDS-OM2 intercepts improved calibration in some cases. Refitting the coefficients but otherwise preserving the UKPDS-OM2 structure improved the fit substantially, which was sufficient for stroke and death. For MI, reselecting UKPDS-OM2 covariates and functional form proved sufficient. For HHF, selection from a broad set of candidate covariates and inclusion of a canagliflozin indicator was required. These risk equations address some of the limitations of widely used risk equations, such as the UKPDS-OM2, for modeling cardioprotective treatments for individuals with T2DM and high cardiovascular risk, including derivation from overly healthy patients treated with agents that lack cardioprotection and have been described as reflecting a different therapeutic era. Future work is needed to examine external validity.