Background: The FINE-CKD model was developed to estimate the cost-effectiveness of finerenone in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D).
Objective: To perform internal and external validation by comparing the model estimates with trial results and outcomes from other models.
Methods: Incidence rates from trials were compared with the model predictions. Statistical tests were then performed to assess whether modeled event rates aligned with trial observations. A cross-validation was also performed using the online version of the SHARP CKD-Cardiovascular Disease (SHARP CKD-CVD) model, with population characteristics from the finerenone trials analyzed. Where no finerenone data were available, the default SHARP CKD-CVD values were used. Comparison of the results considered the ranges from both models.
Results: The outcomes of the FINE-CKD model reflect the event rates observed in the trials. Based on the results of the statistical tests, the hypothesis of no difference between observed and modeled events cannot be rejected for any of the outcomes. The results of the FINE-CKD model are within the ranges from the SHARP CKD-CVD model. Disease progressions align across the models; however, incident kidney failure events in the SHARP CKD-CVD model were higher. This can be explained by simulation of more severely affected patients in the SHARP CKD-CVD model.
Conclusions: This study demonstrates that the FINE-CKD model adequately reflects the clinical data and provides reliable extrapolation relative to the existing predictive tools while also being conservative in its approach.