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Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data

INTRODUCTION: The Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) study showed that compared with placebo, canagliflozin 100 mg significantly reduced the risk of major cardiovascular events and adverse renal outcomes in patients with diabetic...

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Autores principales: Willis, Michael, Asseburg, Christian, Slee, April, Nilsson, Andreas, Neslusan, Cheryl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547928/
https://www.ncbi.nlm.nih.gov/pubmed/32930969
http://dx.doi.org/10.1007/s13300-020-00923-w
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author Willis, Michael
Asseburg, Christian
Slee, April
Nilsson, Andreas
Neslusan, Cheryl
author_facet Willis, Michael
Asseburg, Christian
Slee, April
Nilsson, Andreas
Neslusan, Cheryl
author_sort Willis, Michael
collection PubMed
description INTRODUCTION: The Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) study showed that compared with placebo, canagliflozin 100 mg significantly reduced the risk of major cardiovascular events and adverse renal outcomes in patients with diabetic kidney disease (DKD). We developed a simulation model that can be used to estimate the long-term health and economic consequences of DKD treatment interventions for patients matching the CREDENCE study population. METHODS: The CREDENCE Economic Model of DKD (CREDEM-DKD) was developed using patient-level data from CREDENCE (which recruited patients with estimated glomerular filtration rate 30 to < 90 mL/min/1.73 m(2), urinary albumin to creatinine ratio > 300–5000 mg/g, and taking the maximum tolerated dose of a renin–angiotensin–aldosterone system inhibitor). Risk prediction equations were fit for start of maintenance dialysis, doubling of serum creatinine, hospitalization for heart failure, nonfatal myocardial infarction, nonfatal stroke, and all-cause mortality. A micro-simulation model was constructed using these risk equations combined with user-definable kidney transplant event risks. Internal validation was performed by loading the model to replicate the CREDENCE study and comparing predictions with trial Kaplan–Meier estimate curves. External validation was performed by loading the model to replicate a subgroup of the CANagliflozin cardioVascular Assessment Study (CANVAS) Program with patient characteristics that would have qualified for inclusion in CREDENCE. RESULTS: Risk prediction equations generally fit well and exhibited good concordance, especially for the placebo arm. In the canagliflozin arm, modest underprediction was observed for myocardial infarction, along with overprediction of dialysis, doubling of serum creatinine, and all-cause mortality. Discrimination was strong (0.85) for the renal outcomes, but weaker for the macrovascular outcomes and all-cause mortality (0.60–0.68). The model performed well in internal and external validation exercises. CONCLUSION: CREDEM-DKD is an important new tool in the evaluation of treatment interventions in the DKD population. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02065791. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13300-020-00923-w) contains supplementary material, which is available to authorized users.
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spelling pubmed-75479282020-10-19 Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data Willis, Michael Asseburg, Christian Slee, April Nilsson, Andreas Neslusan, Cheryl Diabetes Ther Original Research INTRODUCTION: The Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) study showed that compared with placebo, canagliflozin 100 mg significantly reduced the risk of major cardiovascular events and adverse renal outcomes in patients with diabetic kidney disease (DKD). We developed a simulation model that can be used to estimate the long-term health and economic consequences of DKD treatment interventions for patients matching the CREDENCE study population. METHODS: The CREDENCE Economic Model of DKD (CREDEM-DKD) was developed using patient-level data from CREDENCE (which recruited patients with estimated glomerular filtration rate 30 to < 90 mL/min/1.73 m(2), urinary albumin to creatinine ratio > 300–5000 mg/g, and taking the maximum tolerated dose of a renin–angiotensin–aldosterone system inhibitor). Risk prediction equations were fit for start of maintenance dialysis, doubling of serum creatinine, hospitalization for heart failure, nonfatal myocardial infarction, nonfatal stroke, and all-cause mortality. A micro-simulation model was constructed using these risk equations combined with user-definable kidney transplant event risks. Internal validation was performed by loading the model to replicate the CREDENCE study and comparing predictions with trial Kaplan–Meier estimate curves. External validation was performed by loading the model to replicate a subgroup of the CANagliflozin cardioVascular Assessment Study (CANVAS) Program with patient characteristics that would have qualified for inclusion in CREDENCE. RESULTS: Risk prediction equations generally fit well and exhibited good concordance, especially for the placebo arm. In the canagliflozin arm, modest underprediction was observed for myocardial infarction, along with overprediction of dialysis, doubling of serum creatinine, and all-cause mortality. Discrimination was strong (0.85) for the renal outcomes, but weaker for the macrovascular outcomes and all-cause mortality (0.60–0.68). The model performed well in internal and external validation exercises. CONCLUSION: CREDEM-DKD is an important new tool in the evaluation of treatment interventions in the DKD population. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02065791. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13300-020-00923-w) contains supplementary material, which is available to authorized users. Springer Healthcare 2020-09-15 2020-11 /pmc/articles/PMC7547928/ /pubmed/32930969 http://dx.doi.org/10.1007/s13300-020-00923-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Original Research
Willis, Michael
Asseburg, Christian
Slee, April
Nilsson, Andreas
Neslusan, Cheryl
Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
title Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
title_full Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
title_fullStr Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
title_full_unstemmed Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
title_short Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
title_sort development and internal validation of a discrete event simulation model of diabetic kidney disease using credence trial data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547928/
https://www.ncbi.nlm.nih.gov/pubmed/32930969
http://dx.doi.org/10.1007/s13300-020-00923-w
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