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Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE
Michael Willis1, Christian Asseburg2, April Slee3
1The Swedish Institute for Health Economics, Lund, Sweden. mw@ihe.se.
Insights
A new simulation model, CREDEM-DKD, was developed to estimate long-term outcomes for diabetic kidney disease (DKD) patients. This tool aids in evaluating treatments like canagliflozin, offering insights into health and economic impacts.
Area of Science:
- Nephrology
- Cardiology
- Health Economics
- Pharmacoeconomics
- Clinical Trial Analysis
Background:
- The Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) study demonstrated canagliflozin's efficacy in reducing cardiovascular and renal events in diabetic kidney disease (DKD).
- A need exists for tools to estimate the long-term health and economic consequences of DKD interventions for patient populations similar to those in CREDENCE.
Purpose of the Study:
- To develop a micro-simulation model, CREDEM-DKD, for estimating the long-term health and economic impacts of DKD treatment interventions.
- To utilize patient-level data from the CREDENCE study to build and validate this predictive model.
Main Methods:
- Developed the CREDENCE Economic Model of DKD (CREDEM-DKD) using CREDENCE patient data.
- Fit risk prediction equations for key DKD outcomes including dialysis, creatinine doubling, heart failure hospitalization, myocardial infarction, stroke, and mortality.
- Constructed a micro-simulation model incorporating these equations and user-defined kidney transplant risks.
- Validated the model internally against CREDENCE trial data and externally against a subgroup of the CANVAS Program.
Main Results:
- Risk prediction equations generally showed good concordance, particularly for the placebo arm.
- The model exhibited strong discrimination for renal outcomes (0.85) but weaker discrimination for macrovascular outcomes and all-cause mortality (0.60-0.68).
- Internal and external validation exercises confirmed the model's robust performance.
Conclusions:
- The CREDEM-DKD model is a valuable new tool for evaluating treatment interventions in patients with diabetic kidney disease.
- This model can support decision-making regarding the long-term management and economic implications of DKD treatments.
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.
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