The Michigan Model for Coronary Heart Disease in Type 2 Diabetes: Development and Validation

Dapagliflozin and sacubitril on myocardial microperfusion in patients with post-acute myocardial infarction heart failure and type 2 diabetes

BACKGROUND

Coronary heart disease and type 2 diabetes mellitus (T2DM) frequently coexist, creating a complex and challenging clinical scenario, particularly when complicated with acute myocardial infarction (AMI).

AIM

To examine the effects of dapagliflozin combined with sakubactrovalsartan sodium tablets on myocardial microperfusion.

METHODS

In total, 98 patients were categorized into control (n = 47) and observation (n = 51) groups. The control group received noxital, while the observation group was treated with dapagliflozin combined with noxital for 6 months. Changes in myocardial microperfusion, blood glucose level, cardiac function, N-terminal prohormone of brain natriuretic peptide (NT-proBNP) level, growth differentiation factor-15 (GDF-15) level, and other related factors were compared between the two groups. Additionally, the incidence of major adverse cardiovascular events (MACE) and adverse reactions were calculated.

RESULTS

After treatment, in the observation and control groups, the corrected thrombolysis in myocardial infarction frame counts were 37.12 ± 5.02 and 48.23 ± 4.66, respectively. The NT-proBNP levels were 1502.65 ± 255.87 and 2015.23 ± 286.31 pg/mL, the N-terminal pro-atrial natriuretic peptide (NT-proANP) levels were 1415.69 ± 213.05 and 1875.52 ± 241.02 ng/mL, the GDF-15 levels were 0.87 ± 0.43 and 1.21 ± 0.56 g/L, and the high-sensitivity C-reactive protein (hs-CRP) levels were 6.54 ± 1.56 and 8.77 ± 1.94 mg/L, respectively, with statistically significant differences (P < 0.05). The cumulative incidence of MACEs in the observation group was significantly lower than that in the control group (P < 0.05). The incidence of adverse reactions was 13.73% (7/51) in the observation group and 10.64% (5/47) in the control group, with no statistically significant difference (P > 0.05).

CONCLUSION

Dapagliflozin combined with nocinto can improve myocardial microperfusion and left ventricular remodeling and reduce MACE incidence in patients with post-AMI heart failure and T2DM. The underlying mechanism may be related to the reduction in the expression levels of NT-proANP, GDF-15, and hs-CRP.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A systematic review of whole disease models for informing healthcare resource allocation decisions

BACKGROUND

Whole disease models (WDM) are large-scale, system-level models which can evaluate multiple decision questions across an entire care pathway. Whilst this type of model can offer several advantages as a platform for undertaking economic analyses, the availability and quality of existing WDMs is unknown.

OBJECTIVES

This systematic review aimed to identify existing WDMs to explore which disease areas they cover, to critically assess the quality of these models and provide recommendations for future research.

METHODS

An electronic search was performed on multiple databases (MEDLINE, EMBASE, the NHS Economic Evaluation Database and the Health Technology Assessment database) on 23rd July 2023. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) appraisal checklist for economic evaluations. Model characteristics were descriptively summarised.

RESULTS

Forty-four WDMs were identified, of which thirty-two were developed after 2010. The main disease areas covered by existing WDMs are heart disease, cancer, acquired immune deficiency syndrome and metabolic disease. The quality of included WDMs is generally low. Common limitations included failure to consider the harms and costs of adverse events (AEs) of interventions, lack of probabilistic sensitivity analysis (PSA) and poor reporting.

CONCLUSIONS

There has been an increase in the number of WDMs since 2010. However, their quality is generally low which means they may require significant modification before they could be re-used, such as modelling AEs of interventions and incorporation of PSA. Sufficient details of the WDMs need to be reported to allow future reuse/adaptation.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Cost-effectiveness of carotid artery stenting vs endarterectomy: A simulation

OBJECTIVE

Clinical trials conducted before the introduction of modern medical management to prevent stroke demonstrated that carotid endarterectomy (CEA) and carotid artery stenting (CAS) prevent stroke following transient ischemic attack (TIA). We compared the cost-effectiveness of CEA, CAS, and modern medical management in two secular settings of medical management in individuals with incident TIA and type 2 diabetes.

METHODS

Using simulation modeling, our base-case analyses were performed from the healthcare sector perspective over a 20-year time horizon with an annual 3% discount rate applied to both costs and quality-adjusted life years (QALYs). Outcomes depended on age, sex, biomarkers associated with cardiovascular risk, and treatment effects based on a validated model of type 2 diabetes. Our simulation population was drawn from the National Health and Nutrition Examination Survey (NHANES) 2014 cohort. Costs for modern medical management were based on average wholesale prices, and revascularization costs were derived from published literature. One-way and probabilistic sensitivity analyses were conducted.

RESULTS

Compared to all other strategies, historical medical management plus CEA was either cost-saving or cost-effective at a threshold of $100,000 per QALY gained. Modern medical management was cost-effective compared to historical medical management without revascularization at a $100,000 acceptability threshold. However, both revascularization approaches (plus medical management) were cost-saving compared to modern medical management alone.

CONCLUSION

Among individuals requiring carotid revascularization, carotid endarterectomy is the cost-effective strategy to treat individuals with type 2 diabetes following a TIA. For individuals for whom revascularization is contraindicated, modern medical therapy is cost-effective.

Invited Commentary: Mechanistic and Biologically Based Models in Epidemiology-A Powerful Underutilized Tool

Mechanistic and biologically based mathematical models of chronic and behavioral disease processes aim to capture the main mechanistic or biological features of the disease development and to connect these with epidemiologic outcomes. These approaches have a long history in epidemiologic research and are complementary to traditional epidemiologic or statistical approaches to investigate the role of risk factor exposures on disease risk. Simonetto et al. (Am J Epidemiol. 2022;191(10):1766-1775) present a mechanistic, process-oriented model to investigate the role of smoking, hypertension, and dyslipidemia in the development of atherosclerotic lesions and their progression to myocardial infarction. Their approach builds on and brings to cardiovascular disease the ideas and perspectives of earlier mechanistic and biologically based models for the epidemiology of cancer and other chronic diseases, providing important insights into the mechanisms and epidemiology of smoking related myocardial infarction. We argue that although mechanistic modeling approaches have demonstrated their value and place in epidemiology, they are highly underutilized. We call for efforts to grow mechanistic and biologically based modeling research, expertise, and awareness in epidemiology, including the development of training and collaboration opportunities to attract more students and researchers from science, technology, engineering, and medical field into the epidemiology field.

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

OBJECTIVES

To estimate 13 equations that predict clinically plausible risk factor time paths to inform the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model version 2 (UKPDS-OM2).

METHODS

Data from 5102 UKPDS participants from the 20-year trial, and the 4031 survivors with 10 years further post-trial follow-up, were used to derive equations for the time paths of 13 clinical risk factors: HbA_1c , 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 25 years.

RESULTS

The new equations were based on 24 years 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.

CONCLUSIONS

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.

Health State Utility Values for Type 2 Diabetes and Related Complications in East and Southeast Asia: A Systematic Review and Meta-Analysis

OBJECTIVES

East and Southeast Asia has the greatest burden of diabetes in the world. We sought to derive a reference set of utility values for type 2 diabetes without complication and disutility (utility decrement) values for important diabetes-related complications to better inform economic evaluation.

METHODS

A systematic review to identify utility values for diabetes and related complications reported in East and Southeast Asia. We searched MEDLINE (OVID) from inception to May 26, 2020 for utility values elicited using direct and indirect methods. Identified studies were assessed for quality based on the National Institute of Health and Care Excellence guidelines. Utility and disutility estimates were pooled by meta-analyses with subgroup analyses to evaluate differences by nationality and valuation instrument. (PROSPERO: CRD42020191075).

RESULTS

We identified 17 studies for the systematic review from a total of 13 035 studies in the initial search, of which 13 studies met the quality criteria for inclusion in the meta-analyses. The pooled utility value for diabetes without complication was 0.88 (95% CI 0.83-0.93), with the pooled utility decrement for associated complications ranged from 0.00 (for excess BMI) to 0.18 (for amputation). The utility values were consistently more conservative than previous estimates derived in Western populations. Utility decrements were comparable for SF-6D and EQ-5D valuation instruments and for Chinese and other Asian groups.

CONCLUSIONS

A reference set of pooled disutility and utility values for type 2 diabetes and its complications in East and Southeast Asian populations yielded more conservative estimates than Western populations.

Targeting of the diabetes prevention program leads to substantial benefits when capacity is constrained

OBJECTIVE

Approximately 84 million people in the USA have pre-diabetes, but only a fraction of them receive proven effective therapies to prevent type 2 diabetes. We estimated the value of prioritizing individuals at highest risk of progression to diabetes for treatment, compared to non-targeted treatment of individuals meeting inclusion criteria for the Diabetes Prevention Program (DPP).

METHODS

Using microsimulation to project outcomes in the DPP trial population, we compared two interventions to usual care: (1) lifestyle modification and (2) metformin administration. For each intervention, we compared targeted and non-targeted strategies, assuming either limited or unlimited program capacity. We modeled the individualized risk of developing diabetes and projected diabetic outcomes to yield lifetime costs and quality-adjusted life expectancy, from which we estimated net monetary benefits (NMB) for both lifestyle and metformin versus usual care.

RESULTS

Compared to usual care, lifestyle modification conferred positive benefits and reduced lifetime costs for all eligible individuals. Metformin's NMB was negative for the lowest population risk quintile. By avoiding use when costs outweighed benefits, targeted administration of metformin conferred a benefit of $500 per person. If only 20% of the population could receive treatment, when prioritizing individuals based on diabetes risk, rather than treating a 20% random sample, the difference in NMB ranged from $14,000 to $20,000 per person.

CONCLUSIONS

Targeting active diabetes prevention to patients at highest risk could improve health outcomes and reduce costs compared to providing the same intervention to a similar number of patients with pre-diabetes without targeted selection.

Cost-Effectiveness of a Diabetes Self-Management Education and Support Intervention Led by Community Health Workers and Peer Leaders: Projections From the Racial and Ethnic Approaches to Community Health Detroit Trial

OBJECTIVE

To simulate the long-term cost-effectiveness of a peer leader (PL)-led diabetes self-management support (DSMS) program following a structured community health worker (CHW)-led diabetes self-management education (DSME) program in reducing risks of complications in people with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

The trial randomized 222 Latino adults with T2D to 1) enhanced usual care (EUC); 2) a CHW-led, 6-month DSME program and 6 months of CHW-delivered monthly telephone outreach (CHW only); or 3) a CHW-led, 6-month DSME program and 12 months of PL-delivered weekly group sessions with telephone outreach to those unable to attend (CHW + PL). Empirical data from the trial and the validated Michigan Model for Diabetes were used to estimate cost and health outcomes over a 20-year time horizon from a health care sector perspective, discounting both costs and benefits at 3% annually. The primary outcome measure was the incremental cost-effectiveness ratio (ICER).

RESULTS

Over 20 years, the CHW + PL intervention had an ICER of $28,800 and $5,900 per quality-adjusted life-year (QALY) gained compared with the EUC and CHW-only interventions, respectively. The CHW-only intervention had an ICER of $430,600 per QALY gained compared with the EUC intervention. In sensitivity analyses, the results comparing the CHW + PL with EUC and CHW-only interventions were robust to changes in intervention effects and costs.

CONCLUSIONS

The CHW + PL-led DSME/DSMS intervention improved health and provided good value compared with the EUC intervention. The 6-month CHW-led DSME intervention without further postintervention CHW support was not cost effective in Latino adults with T2D.

Cost-effectiveness of Telephone-Delivered Education and Behavioral Skills Intervention for African American Adults with Diabetes

Purpose

Evaluate cost-effectiveness of a telephone-delivered education and behavioral skills intervention in reducing glycemic control (HbA1c) and decreasing risk of complications.

Methods

Data from a randomized controlled trial, conducted from August 1, 2008 - June 30, 2010 and using a 2x2 factorial design delivered to 255 African American adults not meeting glycemic targets for diabetes were used. Though the primary aim found no significant differences in HbA1c between groups, there was an overall drop in HbA1c across arms and differential cost. Primary clinical outcome was HbA1c measured at 12-months. Costs were estimated based on self-reported utilization of primary care, emergency, and other health care. Costs due to lost wages were calculated based on self-reported days of work missed due to illness. The Michigan Model for Diabetes was used to estimate 10-year probability of developing congestive heart failure, cardiovascular disease, end stage renal disease, stroke, myocardial infarction, all cause death, and CVD death. Total cost per patient and clinical outcomes were used to estimate an incremental cost effectiveness ratio (ICER) using non-parametric bootstrapping.

Results

ICERs indicated combined education and skills intervention was $3,630 less expensive than usual care to achieve a 0.6% decrease in HbA1c and was between $34,000 and $95,000 less expensive than usual care to reduce risk of complications. The knowledge only intervention was $661 less expensive than usual care and the behavioral skills only intervention did not indicate cost effectiveness.

Conclusion

The combined intervention ICER for HbA1c is comparable to other education programs and the ICER to reduce the probability of complications falls below previously recommended long-term cut-off of $100,000, suggesting cost-effectiveness in an African American population.

Cost-effectiveness of Community-Based Depression Interventions for Rural and Urban Adults With Type 2 Diabetes: Projections From Program ACTIVE (Adults Coming Together to Increase Vital Exercise) II

OBJECTIVE

We estimated the cost-effectiveness of the Program ACTIVE (Adults Coming Together to Increase Vital Exercise) II community-based exercise (EXER), cognitive behavioral therapy (CBT), and EXER+CBT interventions in adults with type 2 diabetes and depression relative to usual care (UC) and each other.

RESEARCH DESIGN AND METHODS

Data were integrated into the Michigan Model for Diabetes to estimate cost and health outcomes over a 10-year simulation time horizon from the health care sector and societal perspectives, discounting costs and benefits at 3% annually. Primary outcome was cost per quality-adjusted life-year (QALY) gained.

RESULTS

From the health care sector perspective, the EXER intervention strategy saved $313 (USD) per patient and produced 0.38 more QALY (cost saving), the CBT intervention strategy cost $596 more and gained 0.29 more QALY ($2,058/QALY), and the EXER+CBT intervention strategy cost $403 more and gained 0.69 more QALY ($585/QALY) compared with UC. Both EXER and EXER+CBT interventions dominated the CBT intervention. Compared with EXER, the EXER+CBT intervention strategy cost $716 more and gained 0.31 more QALY ($2,323/QALY). From the societal perspective, compared with UC, the EXER intervention strategy saved $126 (cost saving), the CBT intervention strategy cost $2,838/QALY, and the EXER+CBT intervention strategy cost $1,167/QALY. Both EXER and EXER+CBT interventions still dominated the CBT intervention. In comparison with EXER, the EXER+CBT intervention strategy cost $3,021/QALY. Results were robust in sensitivity analyses.

CONCLUSIONS

All three Program ACTIVE II interventions represented a good value for money compared with UC. The EXER+CBT intervention was highly cost-effective or cost saving compared with the CBT or EXER interventions.

Economic Simulation Modeling in Type 2 Diabetes

PURPOSE OF REVIEW

This paper provides an overview of type 2 diabetes economic simulation modeling and reviews current topics of discussion and major challenges in the field.

RECENT FINDINGS

Important challenges in the field include increasing the generalizability of models and improving transparency in model reporting. To identify and address these issues, modeling groups have organized through the Mount Hood Diabetes Challenge meetings and developed tools (i.e., checklist, impact inventory) to standardize modeling methods and reporting of results. Accordingly, many newer diabetes models have begun utilizing these tools, allowing for improved comparability between diabetes models. In the last two decades, type 2 diabetes simulation models have improved considerably, due to the collaborative work performed through the Mount Hood Diabetes Challenge meetings. To continue to improve diabetes models, future work must focus on clarifying diabetes progression in racial/ethnic minorities and incorporating equity considerations into health economic analysis.

TECH-VER: A Verification Checklist to Reduce Errors in Models and Improve Their Credibility

BACKGROUND

In health economic literature, checklists or best practice recommendations on model validation/credibility always declare verification of the programmed model as a fundamental step, such as 'is the model implemented correctly and does the implementation accurately represent the conceptual model?' However, to date, little operational guidance for the model verification process has been given. In this study, we aimed to create an operational checklist for model users or reviewers to verify the technical implementation of health economic decision analytical models and document their verification efforts.

METHODS

Literature on model validation, verification, programming errors and credibility was reviewed systematically from scientific databases. An initial beta version of the checklist was developed based on the checklists/tests identified from the literature and from authors' previous modeling/appraisal experience. Next, the first draft checklist was presented to a number of health economists on several occasions and was tested on different models (built in different software, developed by different stakeholders, including drug manufacturers, consultancies or academia), each time leading to an update of the checklist and culminating in the final version of the TECHnical VERification (TECH-VER) checklist, introduced in this paper.

RESULTS

The TECH-VER necessitates a model reviewer (preferably independent), an executable and transparent model, its input sources, and detailed documentation (e.g. technical report/scientific paper) in which the conceptual model, its implementation, programmed model inputs, and results are reported. The TECH-VER checklist consists of five domains: (1) input calculations; (2) event-state (patient flow) calculations; (3) result calculations; (4) uncertainty analysis calculations; and (5) other overall checks (e.g. validity or interface). The first four domains reflect the verification of the components of a typical health economic model. For these domains, as a prerequisite of verification tests, the reviewer should identify the relevant calculations in the electronic model and assess the provided justifications for the methods used in the identified calculations. For this purpose, we recommend completeness/consistency checks. Afterwards, the verification tests can be conducted for the calculations in each of these stages by checking the correctness of the implementation of these calculations. For this purpose, the following type of tests are recommended in consecutive order: (i) black-box tests, i.e. checking if model calculations are in line with a priori expectations; (ii) white-box testing, i.e. going through the program code details line by line, or cell by cell (recommended for some crucial calculations and if there are some unexpected results from the black-box tests); and (iii) model replication/parallel programming (recommended only in certain situations, and if the issues related to the identified unexpected results from black-box tests could not be resolved through white-box testing). To reduce the time burden of model verification, we suggest a hierarchical order in tests i-iii, where going to the next step is necessary when the previous step fails.

CONCLUSIONS

The TECH-VER checklist is a comprehensive checklist for the technical verification of decision analytical models, aiming to help identify model implementation errors and their root causes while improving the transparency and efficiency of the verification efforts. In addition to external reviews, we consider that the TECH-VER can be used as an internal training and quality control tool for new health economists, while developing their initial models. It is the authors' aim that the TECH-VER checklist transforms itself to an open-source living document, with possible future versions, or 'bolt-on' extensions for specific applications with additional 'fit-for-purpose' tests, as well as 'tips and tricks' and some demonstrative error examples. For this reason, the TECH-VER checklist and the list of black-box tests created in this paper and a few model verification examples is uploaded to an open access, online platform (github and the website of the institute), where other users will also be able to upload their original verification efforts and tests.

Development and Validation of PREDICT-DM: A New Microsimulation Model to Project and Evaluate Complications and Treatments of Type 2 Diabetes Mellitus

Background: Type 2 diabetes mellitus (T2DM) affects ∼30 million people in the United States and ∼400 million people worldwide, numbers likely to increase due to the rising prevalence of obesity. We sought to design, develop, and validate PREDICT-DM (PRojection and Evaluation of Disease Interventions, Complications, and Treatments-Diabetes Mellitus), a state-transition microsimulation model of T2DM, incorporating recent data. Methods: PREDICT-DM is populated with natural history, risk factor, and outcome data from large-scale cohort studies and randomized clinical trials. The model projects diabetes-relevant outcomes, including cardiovascular and renal disease outcomes, and 5/10-year survival. We assessed the model validity against 62 endpoints from ACCORD (Action to Control Cardiovascular Risk in Diabetes), VADT (Veterans Affairs Diabetes Trial), and Look AHEAD trials via several comparative statistical methods, including mean absolute percentage error (MAPE), Bland-Altman graphs, and Kaplan-Meier curves. Results: For the comparison between simulated and observed outcomes of the intervention/control arms of the trial, the MAPE was 19%/25% (ACCORD), 29%/20% (VADT), and 42%/10% (Look AHEAD). The Bland-Altman's 95% limit of agreement was 0.02 (ACCORD), 0.03 (VADT), and 0.01 (Look AHEAD), and the mean difference (95% confidence interval) for the comparison between PREDICT-DM and trial endpoints was 0.0025 (-0.0018 to 0.0070) for ACCORD, -0.0067 (-0.0137 to 0.0002) for VADT, and -0.0033 (-0.0067 to 0.00002) for Look AHEAD, indicating an adequate model fit to the data. The model-driven Kaplan-Meier curves were similarly close to those previously published. Conclusions: PREDICT-DM can reasonably predict clinical outcomes from ACCORD and other clinical trials of U.S. patients with T2DM. This model may be leveraged to inform clinical strategy questions related to the management and care of T2DM in the United States.

Are the favorable cardiovascular outcomes of empagliflozin treatment explained by its effects on multiple cardiometabolic risk factors? A simulation of the results of the EMPA-REG OUTCOME trial

AIMS

It is unclear whether the favorable impact of empagliflozin on cardiovascular outcomes (CVOs) is due to its effect on multiple cardiometabolic risk factors (CRFs).

METHODS

We used the Michigan Model for Diabetes, a validated computer simulation model, and published data from the EMPA-REG OUTCOME trial to estimate three-year CVOs in the placebo and pooled empagliflozin treatment groups to assess whether the observed benefits might be attributable to differences in CRFs.

RESULTS

When we programmed the model to match the baseline characteristics of the trial population and the reported trajectories of five CRFs (weight, HbA1c, systolic blood pressure, low- and high-density lipoprotein cholesterol), the simulated hazard ratio (HR) for the primary composite CVO did not differ from the reported result. The simulated HRs for fatal/nonfatal myocardial infarction and coronary revascularization procedure fell within the reported 95% confidence intervals (CIs), but those for fatal/nonfatal stroke, hospitalization for heart failure, cardiovascular death, and all-cause mortality fell outside the reported 95% CIs. The effects of empagliflozin on CRFs accounted for approximately half of the observed benefit for the primary composite CVO, but explained smaller proportions of risk reductions for hospitalization for heart failure, cardiovascular death, and all-cause mortality.

CONCLUSIONS

The effects of empagliflozin on multiple CRFs account for some but not all of reduced risks of CVOs in the EMPA-REG OUTCOME trial. More comparable control of established CRFs in type 2 diabetes CVO trials of antidiabetic agents with pleiotrophic effects would facilitate the interpretation of the observed outcomes.