Medical Decision Modeling (MDM) – Treatment Transitions Model (TTM)
The Treatment Transitions Model (TTM) is a Monte Carlo microsimulation model which estimates clinical and economic outcomes for patients with type 2 diabetes mellitus (T2DM) under user-specified treatment paradigms. The TTM simulation begins with creating an individual simulated patient with baseline demographic and clinical characteristics. The baseline characteristics include age, gender, ethnicity, and HbA1c. Clinical characteristics include systolic blood pressure, total cholesterol, high-density (HDL) and low-density lipoprotein (LDL), body mass index (BMI), and estimated glomerular filtration rate (eGFR). Comorbidities estimated from the TTM include nephropathy, neuropathy, retinopathy, stroke, and coronary heart disease.
Based on the comorbidity-related mortality and overall natural mortality, the patient’s mortality is estimated. Treatment escalation within TTM is primarily controlled by increases to HbA1c and the sequence of treatments being evaluated. Patients not achieving durable control of their HbA1c are typically subject to drift after a period of time on a specific treatment (a treatment modifiable input). Once a patient’s HbA1c fails to decline or remain below the target for a prescribed amount of time (treatment specific), the patient will advance to the next step in their treatment progression. The model user can select the specific treatment progression (i.e., series of treatments) to be evaluated.
In the TTM, event and continuing medical costs are estimated along with pharmacy costs. The TTM also includes estimation of medical costs associated with hypoglycaemic events.
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HJ Smolen and X Yu. Using a treatment transition model to evaluate the effects of neglecting Hba1c drift in oral anti-diabetic drugs for type 2 diabetes. Value in Health. May 2015Volume 18, Issue 3, Page A53.
The values below are simulated Quality Adjusted life Years (QALYs) for a set of reference simulations