OBJECTIVES: Long-term data are rarely available when reimbursement decisions are made for T2DM therapies.  If properly constructed and applied, economic simulation models can be useful tools for decision-making.  To engender confidence that model results reflect reality as best as possible, the ability to replicate results from actual clinical studies should be assessed through formal validity testing.  ECHO-T2DM has been validated previously; nevertheless, there have been significant model changes and new trial data have become available, so we aim to update and expand the validity tests. METHODS: ECHO-T2DM is a stochastic, micro-simulation model constructed with Markov health states representing key micro- and macrovascular complications.  ECHO-T2DM was used to predict 214 outcomes from 10 published trials, replicating the patient characteristics, treatment effects, and follow-up length of each study individually.  Where published data were incomplete, the most suitable data from other studies were used.  Predicted outcomes were plotted against observed outcomes to assess model fit, as all points would lie on the identity (45°) line when the predicted and observed values match exactly.  A number of concordance metrics were evaluated, including the slope of the best-fitting regression line (which equals 1 when the predictions match observed values).  Concordance was evaluated overall and separately by whether or not the validation studies were used in ECHO-T2DM construction. RESULTS: The best-fitting regression line had a slope of 1.03 and an R of 0.91 when the UKPDS 82 macrovascular and mortality equations were used and all outcomes considered.  The fit was slightly better for the subgroup of dependent than of independent outcomes (1.01 vs. 1.04), though both had Rof ~0.90. CONCLUSIONS: Results suggest the model corresponds well with actual clinical data, even considering studies not used in model construction.  Though model-based results must always be interpreted cautiously, ECHO-T2DM can be considered a useful decision-making tool.