OBJECTIVES: T2DM is a chronic, progressive disease and proper economic evaluation of alternative treatment interventions requires economic modeling over long time horizons.  As currently available treatments cannot halt disease progression, most patients eventually require therapy intensification to meet HbA1c goals.  This analysis explores the impact of commonly used intensification assumptions on cost-effectiveness estimates using simulations of canagliflozin (CANA) versus maximally-titrated glimepiride (GLIM) in patients with uncontrolled HbA1c on metformin in the US. METHODS: ECHO-T2DM, a validated micro-simulation model, was used to simulate 30-year outcomes and costs associated with using CANA 100 or 300mg versus GLIM as add-on to metformin.  Patient characteristics, treatment effects, and adverse event rates were sourced from a previously reported head-to-head trial.  Health utilities and unit costs were sourced from the literature.  Two types of treatment intensification triggers were modeled: when HbA1c exceeds a target threshold, and after a fixed amount of time.  Treatment was intensified first by adding basal insulin and then prandial insulin, both titrated to maintain HbA1c control (up to pre-specified maximum doses).  A simulation with no intensification was also performed. RESULTS: Incremental cost-effectiveness ratios (ICERs) for treatment strategies starting with CANA 100 and 300mg versus GLIM with insulin rescue at HbA1c >7.0% were $29,032 and $22,106, respectively, largely driven by CANA’s ability to keep HbA1c controlled longer, thus delaying insulin initiation.  Using a fixed (and equal) time on CANA and GLIM (5 and 10 years) favored GLIM by eliminating this benefit, yielding higher ICERs.  The extreme case of no rescue therapy artificially inflated complication costs in both arms, since HbA1c drifts unabated upwards. CONCLUSIONS: Assumptions about treatment intensification matter.  Unrealistic assumptions like fixing time on agents or omitting intensification had large effects, as ICERs depend on how downstream treatment choices are modeled.  Consumers of T2DM economic evaluations should therefore consider these assumptions carefully.