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Published in: Diabetes Therapy 11/2020

01-11-2020 | Stroke | Original Research

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

Authors: Michael Willis, Christian Asseburg, April Slee, Andreas Nilsson, Cheryl Neslusan

Published in: Diabetes Therapy | Issue 11/2020

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Abstract

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 m2, 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.
Appendix
Available only for authorised users
Footnotes
1
Note: this differs from validation of the risk prediction equations in two important ways: (1) the analysis used randomly sampled hypothetical patients (as opposed to actual CREDENCE subjects) and (2) risk prediction equations are evaluated collectively as a system (rather than individually).
 
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Metadata
Title
Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data
Authors
Michael Willis
Christian Asseburg
April Slee
Andreas Nilsson
Cheryl Neslusan
Publication date
01-11-2020
Publisher
Springer Healthcare
Published in
Diabetes Therapy / Issue 11/2020
Print ISSN: 1869-6953
Electronic ISSN: 1869-6961
DOI
https://doi.org/10.1007/s13300-020-00923-w

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