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

Kuo, Shihchen; Ye, Wen; Duong, Justin J.; Herman, William H.

doi:10.1016/j.diabres.2018.04.040

Cited by 12 publications

(9 citation statements)

References 20 publications

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“…First, some drug classes, notably SGLT2 inhibitors and GLP-1 receptor agonists, have reported treatment effects that cannot be explained only by improvements in known biomarker risk factors, and hence models including these risk factors in their risk predictions cannot be expected to fully capture the reported outcomes, at least until the mechanisms of action are better understood. [20][21][22] The Ninth Mount Hood Diabetes Challenge has confirmed this finding. Second, widely used risk equations such as the UKPDS 68 and the UKPDS 82 reflect cohorts initially recruited in an earlier "therapeutic era," since when improved clinical care and many other factors have contributed to secular declines in morbidity and mortality in type 2 diabetes and in cardiovascular disease generally.…”

Section: Discussionmentioning

confidence: 77%

“…18 These cardioprotective effects reported cannot be fully explained by improvements in known biomarker risk factors. 19 Applications with 3 independent diabetes simulation models have failed to replicate these treatment effects based on changes in surrogate biomarkers for most CV outcomes, [20][21][22] highlighting an important challenge for economic decision makers.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

et al. 2020

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The cardiovascular outcomes challenge examined the predictive accuracy of 10 diabetes models in estimating hard outcomes in 2 recent cardiovascular outcomes trials (CVOTs) and whether recalibration can be used to improve replication. Methods: Participating groups were asked to reproduce the results of the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG OUTCOME) and the Canagliflozin Cardiovascular Assessment Study (CANVAS) Program. Calibration was performed and additional analyses assessed model ability to replicate absolute event rates, hazard ratios (HRs), and the generalizability of calibration across CVOTs within a drug class. Results: Ten groups submitted results. Models underestimated treatment effects (ie, HRs) using uncalibrated models for both trials. Calibration to the placebo arm of EMPA-REG OUTCOME greatly improved the prediction of event rates in the placebo, but less so in the active comparator arm. Calibrating to both arms of EMPA-REG OUTCOME individually enabled replication of the observed outcomes. Using EMPA-REG OUTCOME-calibrated models to predict CANVAS Program outcomes was an improvement over uncalibrated models but failed to capture treatment effects adequately. Applying canagliflozin HRs directly provided the best fit. Conclusions: The Ninth Mount Hood Diabetes Challenge demonstrated that commonly used risk equations were generally unable to capture recent CVOT treatment effects but that calibration of the risk equations can improve predictive accuracy. Although calibration serves as a practical approach to improve predictive accuracy for CVOT outcomes, it does not extrapolate generally to other settings, time horizons, and comparators. New methods and/or new risk equations for capturing these CV benefits are needed.

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Section: Discussionmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

et al. 2020

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“…Moreover, a wealth of evidence on head-to-head differences in biomarker changes to inform economic analysis exists. This approach has been shown to capture only part of the cardiovascular benefit [17, 19, 20] using well-established cardiovascular risk prediction equations such as those from UKPDS. When this approach is used to perform economic assessments comparing agents with and without demonstrated cardiovascular benefits, results will be biased.…”

Section: Resultsmentioning

confidence: 99%

“…Based as they are on known biomarkers, existing risk prediction equations may not have good predictive accuracy for modeling agents that have shown cardioprotection since these benefits cannot be explained fully by these known risk factors. Indeed, studies attempting to replicate EMPA-REG OUTCOME [17, 18], LEADER [18], SUSTAIN-6 [19], and the CANVAS Program [20] have confirmed that economic modeling with these risk prediction equations can capture only part of the cardiovascular benefit, and those interested in risk prediction and economic modeling in T2DM have taken notice. For example, CADTH (Canadian Agency for Drugs and Technologies in Health) and NICE (National Institute for Health and Care Excellence) have called into question the ability of the risk prediction equations underlying the UKPDS Outcomes Model to accurately predict event risks for cardioprotective agents [21, 22].…”

Section: Introductionmentioning

confidence: 99%

Challenges and Opportunities Associated with Incorporating New Evidence of Drug-Mediated Cardioprotection in the Economic Modeling of Type 2 Diabetes: A Literature Review

et al. 2019

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IntroductionCardiovascular disease is a leading cause of mortality in people with type 2 diabetes mellitus (T2DM). Beginning in 2015, long-term cardiovascular outcomes trials (CVOTs) have reported cardioprotective benefits for two classes of diabetes drugs. In addition to improving the lives of patients, these health benefits affect relative value (i.e., cost-effectiveness) of these agents compared with each other and especially compared with other agents. While long-term CVOT data on hard outcomes are a great asset, economic modeling of the value of this cardioprotection faces many new empirical challenges. The aim of this study was to identify different approaches used to incorporate drug-mediated cardioprotection into T2DM economic models, to identify pros and cons of these approaches, and to highlight additional considerations.MethodsA review of T2DM modeling applications (manuscript or conference abstracts) that included direct cardioprotective effects was conducted from January 2015 to September 2018. Model applications were classified on the basis of the mechanism used to model cardioprotection [i.e., directly via hazard ratios (HRs) for cardiovascular outcomes or indirectly via biomarker mediation]. Details were extracted and the studies were evaluated.ResultsFive full-length articles and 16 conference abstracts (of which 11 posters were found) qualified for study inclusion. While the approaches used were diverse, the five full-length publications and all but two of the abstracts modeled cardioprotection used direct HRs from the relevant CVOT. The remaining two posters modeled cardioprotection using CVOT HRs in combination with treatment effects mediated through known risk factors.ConclusionThe classification of empirical methods in cardioprotection was intended to facilitate a better understanding of the pros and cons of different methodologies. A substantial diversity was observed, though most used trial HRs directly. Given the differences observed, we believe that diabetes modelers and other stakeholders can benefit from a formal discussion and evolving consensus.FundingJanssen Global Services, LLC (Raritan, NJ, USA).Electronic supplementary materialThe online version of this article (10.1007/s13300-019-00681-4) contains supplementary material, which is available to authorized users.

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“…О практической пользе эмпаглифлозина для этой категории больных говорит и промежуточный анализ результатов лечения 35 000 пациентов в исследовании EMPRISE, подтвердивший, что эмпаглифлозин снижает риск госпитализаций по поводу ХСН на 44% по сравнению с терапией ингибиторами дипептидилпептидазы 4 типа (иДПП4), по данным реальной клинической практики [8]. Данный препарат эффективен, не способствует гипогликемиям, ведет к снижению массы тела [1,9,10,11], уменьшает риск госпитализаций по причине сердечной недостаточности на 35% (в том числе у больных, исходно не имевших ХСН) [3,4], характеризуется такими позитивными плейотропными эффектами, как уменьшение артериального давления без роста частоты сердечных сокращений [4,12], снижение уровня мочевой кислоты в крови [4,13], нефропротективное действие с улучшением тубуло-интерстициальных взаимодействий, уменьшением воспалительных изменений в почках и микроальбуминурии [9,14,15], снижение потребности в инсулине [9], симпатической активности сердца и риска аритмий [16]. При этом позитивный эффект эмпаглифлозина на сердечно-сосудистые риски оказался столь значительным, что его трудно объяснить даже комбинированным воздействием всех перечисленных факторов.…”

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The effect of empagliflozin on the development of chronic heart failure after myocardial infarction according to a 12-month prospective study

Nekrasov¹,

Timoschenko²,

Стронгин³

et al. 2019

Diabetes mellitus

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BACKGROUND: Although the positive cardiovascular effect of empagliflozin has been established, its influence on the formation of heart failure (HF) in patients with type 2 diabetes mellitus (T2D) after myocardial infarction (MI) remains unknown. AIM: To study the effect of empagliflozin on the formation of chronic HF after MI in patients having diabetes mellitus of type 2 (DM 2), according to 12-month follow-up data. MATERIALS AND METHODS: 47 patients with MI and DM 2 were included; 21 received standard therapy for MI and diabetes (group 1); 26 patients, in addition, received empagliflozin (group 2). The patients were investigated in 3 and 12 months, to assess the dynamics of glycemic control, 6-minute walk test, echocardiography. RESULTS: During postinfarction period, the 6-minute walk distance was increasing in group 1 in a lesser degree (p = 0.18) than in group 2 (49.5%, p = 0.0004). The ejection fraction got better particularly in group 2 (p = 0.002). At baseline, the proportions of patients having HF with reduced and mid-range ejection fraction were 85.7% and 82.4% in groups 1 and 2 (p = 0.56) but in 12 months decreased to 71.4% and 29.4% (p = 0.012). In empagliflozin group diastolic function was improved in a third of the patients (p = 0.041). The pulmonary artery systolic pressure was increasing in group 1 (by 10,4%, p = 0.041) but decreasing in group 2 (by 24,0%, p = 0.019). Glycemic control was better in group 2 than in group 1. CONCLUSION: According to 12-month follow-up data, empagliflozin has a positive effect on HF formation and symptoms in patients having MI and DM 2. This effect may be based on the ability of empagliflozin to improve the state of the heart including the delay of postinfarction remodeling, the improvement of pulmonary artery hemodynamics, systolic and diastolic function, the reduction of risk of chronic HF with reduced and mid-range ejection fraction.

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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

Cited by 12 publications

References 20 publications

Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

Challenges and Opportunities Associated with Incorporating New Evidence of Drug-Mediated Cardioprotection in the Economic Modeling of Type 2 Diabetes: A Literature Review

The effect of empagliflozin on the development of chronic heart failure after myocardial infarction according to a 12-month prospective study

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