The Use of Computer Simulation Modeling to Estimate Complications in Patients with Type 2 Diabetes Mellitus: Comparative Validation of the Cornerstone Diabetes Simulation Model.

ABSTRACT:

Objective

The objective of this study was to assess the validity of the Cornerstone Diabetes Simulation (CDS), a Microsoft Excel^®-based patient-level simulation for type 2 diabetes mellitus based on risk equations from the revised United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2, also known as UKPDS 82).

Methods

Three levels of validation were conducted. Internal validation was assessed through independent review and model stress-testing. External validation was addressed by populating the CDS with baseline characteristics and treatment effects from three major diabetes clinical trials used in the Fifth Mount Hood Diabetes Challenge (MH5) for computer simulation models. Cross-validation of predicted outcomes was tested versus eight models that participated in the MH5. Simulated results were compared with observed clinical outcomes via the coefficient of determination (R²) for both the absolute risk of each clinical outcome and the difference in absolute risk between control and intervention arm in each trial. We ensured transparency of all model inputs and assumptions in reporting.

Results

The CDS could be used to predict 18 of 39 single and composite endpoints across the three trials. The model obtained an R² of 0.637 for predicted versus observed absolute risks, and an R² of 0.442 for predicted versus observed risk differences between control and intervention. Among the other eight models, only one obtained a higher R² value under both definitions, albeit based on only four predicted endpoints.

Conclusions

The CDS provides good predictions of diabetes-related complications when compared to observed trial outcomes and previously validated models. The model has value as a validated tool in cost-effectiveness evaluations.

SUBMITTER: Su ZT 

PROVIDER: S-EPMC7018921 | biostudies-literature |

REPOSITORIES: biostudies-literature