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Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease
INTRODUCTION: Dipeptidyl peptidase-4 (DPP-4) inhibitors are a class of oral antidiabetic agents for the treatment of type 2 diabetes mellitus, which lower blood glucose without causing severe hypoglycemia. However, the first cardiovascular (CV) safety trials have only recently reported their results...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4462855/ https://www.ncbi.nlm.nih.gov/pubmed/26089691 http://dx.doi.org/10.2147/CEOR.S75935 |
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author | Schuetz, Charles Andy Ong, Siew Hwa Blüher, Matthias |
author_facet | Schuetz, Charles Andy Ong, Siew Hwa Blüher, Matthias |
author_sort | Schuetz, Charles Andy |
collection | PubMed |
description | INTRODUCTION: Dipeptidyl peptidase-4 (DPP-4) inhibitors are a class of oral antidiabetic agents for the treatment of type 2 diabetes mellitus, which lower blood glucose without causing severe hypoglycemia. However, the first cardiovascular (CV) safety trials have only recently reported their results, and our understanding of these therapies remains incomplete. Using clinical trial simulations, we estimated the effectiveness of DPP-4 inhibitors in preventing major adverse cardiovascular events (MACE) in a population like that enrolled in the SAVOR-TIMI (the Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus – Thrombolysis in Myocardial Infarction) 53 trial. METHODS: We used the Archimedes Model to simulate a clinical trial of individuals (N=11,000) with diagnosed type 2 diabetes and elevated CV risk, based on established disease or multiple risk factors. The DPP-4 class was modeled with a meta-analysis of HbA(1c) and weight change, pooling results from published trials of alogliptin, linagliptin, saxagliptin, sitagliptin, and vildagliptin. The study treatments were added-on to standard care, and outcomes were tracked for 20 years. RESULTS: The DPP-4 class was associated with an HbA(1c) drop of 0.66% (0.71%, 0.62%) and a weight drop of 0.14 (−0.07, 0.36) kg. These biomarker improvements produced a relative risk (RR) for MACE at 5 years of 0.977 (0.968, 0.986). The number needed to treat to prevent one occurrence of MACE at 5 years was 327 (233, 550) in the elevated CV risk population. CONCLUSION: Consistent with recent trial publications, our analysis indicates that DPP-4 inhibitors do not increase the risk of MACE relative to the standard of care. This study provides insights about the long-term benefits of DPP-4 inhibitors and supports the interpretation of the published CV safety trial results. |
format | Online Article Text |
id | pubmed-4462855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44628552015-06-18 Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease Schuetz, Charles Andy Ong, Siew Hwa Blüher, Matthias Clinicoecon Outcomes Res Original Research INTRODUCTION: Dipeptidyl peptidase-4 (DPP-4) inhibitors are a class of oral antidiabetic agents for the treatment of type 2 diabetes mellitus, which lower blood glucose without causing severe hypoglycemia. However, the first cardiovascular (CV) safety trials have only recently reported their results, and our understanding of these therapies remains incomplete. Using clinical trial simulations, we estimated the effectiveness of DPP-4 inhibitors in preventing major adverse cardiovascular events (MACE) in a population like that enrolled in the SAVOR-TIMI (the Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus – Thrombolysis in Myocardial Infarction) 53 trial. METHODS: We used the Archimedes Model to simulate a clinical trial of individuals (N=11,000) with diagnosed type 2 diabetes and elevated CV risk, based on established disease or multiple risk factors. The DPP-4 class was modeled with a meta-analysis of HbA(1c) and weight change, pooling results from published trials of alogliptin, linagliptin, saxagliptin, sitagliptin, and vildagliptin. The study treatments were added-on to standard care, and outcomes were tracked for 20 years. RESULTS: The DPP-4 class was associated with an HbA(1c) drop of 0.66% (0.71%, 0.62%) and a weight drop of 0.14 (−0.07, 0.36) kg. These biomarker improvements produced a relative risk (RR) for MACE at 5 years of 0.977 (0.968, 0.986). The number needed to treat to prevent one occurrence of MACE at 5 years was 327 (233, 550) in the elevated CV risk population. CONCLUSION: Consistent with recent trial publications, our analysis indicates that DPP-4 inhibitors do not increase the risk of MACE relative to the standard of care. This study provides insights about the long-term benefits of DPP-4 inhibitors and supports the interpretation of the published CV safety trial results. Dove Medical Press 2015-06-05 /pmc/articles/PMC4462855/ /pubmed/26089691 http://dx.doi.org/10.2147/CEOR.S75935 Text en © 2015 Schuetz et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Schuetz, Charles Andy Ong, Siew Hwa Blüher, Matthias Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease |
title | Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease |
title_full | Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease |
title_fullStr | Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease |
title_full_unstemmed | Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease |
title_short | Clinical trial simulation methods for estimating the impact of DPP-4 inhibitors on cardiovascular disease |
title_sort | clinical trial simulation methods for estimating the impact of dpp-4 inhibitors on cardiovascular disease |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4462855/ https://www.ncbi.nlm.nih.gov/pubmed/26089691 http://dx.doi.org/10.2147/CEOR.S75935 |
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