Validation of the CORE Diabetes Model against epidemiological and clinical studies
Palmer, AJ and Roze, S and Valentine, WJ and Minshall, ME and Foos, V and Lurati, FM and Lammert, M and Spinas, GA, Validation of the CORE Diabetes Model against epidemiological and clinical studies, Current Medical Research and Opinion, 20, (Supplement 1) pp. S27-S40. ISSN 0300-7995 (2004) [Refereed Article]
Objectives: The aim of this study was to assess the validity of the CORE Diabetes Model by comparing results from model simulations with observed outcomes from published epidemiological and clinical studies in type 1 and type 2 diabetes. Methods: A total of 66 second- (internal) and third- (external) order validation analyses were performed across a range of complications and outcomes simulated by the CDRE Diabetes Model (amputation, cataract, hypoglycaemia, ketoacidosis, macular oedema, myocardial infarction, nephropathy, neuropathy, retinopathy, stroke and mortality). Published studies were reproduced in the model by recreating cohorts in terms of demographics, baseline risk factors and complications, treatment patterns and patient management strategies, and simulating the progress of the cohort to an equivalent time horizon. Results: Correlation analysis on results from 66 validation simulations produced an R2 value of 0.9224 (perfect fit = 1). A correlation plot of published study data versus values simulated by the CORE Diabetes Model had a trend line with a gradient of 1.0187 (perfect fit = 1). Validation analyses in type 1 and type 2 diabetes were associated with R2 values of 0.9778 and 0.8861 respectively. Correlation of second-order validation analyses (model predictions versus observed outcomes in studies used to construct the model) produced an R2 value of 0.9574, and the value for third-order analyses (model predictions versus observed outcomes in studies not used to construct the model) was 0.9023. Conclusions: The CORE Diabetes Model provides an accurate representation of patient outcomes when compared to 66 studies of diabetes and its complications. Model flexibility ensures it can be used to compare diabetes management strategies in different cohorts across a variety of clinical settings.