Fig 1.
State transition diagram.
Fig 2.
Schematic of decision tree representing a simulated patient during an annual cycle.
Each year individual patients have a chance of death from all causes, developing new (subclinical, undetected) nodules, or of moving from pre-clinical to clinical state of detecting existing nodules. Each simulated patient has the potential to develop multiple nodules, each of which can be benign or malignant, unilateral or bilateral to replicate realistic clinical presentation. Each cycle tumors may grow, shrink, or remain stable in size.
Table 1.
Model input parameters.
Table 2.
Calibrated parameter sets.
Fig 3.
Model assessment of fit to primary calibration target: Thyroid Cancer Policy Model incidence output versus observed SEER incidence data (2010–2012) by five-year age intervals.
Fig 4.
Size distribution at detection of malignancy: Model versus SEER data.
Fig 5.
Proportion of simulated population with underlying thyroid nodules in TCPM, benign and malignant, by age.
Fig 6.
Probability of nodule detection by diameter of nodule (mm) with variation in probability range based on age as predicted by the model.
Fig 7.
Model estimates of growth over time stratified by benign versus malignant and by age groups.
Fig 8.
Comparison of Thyroid Cancer Policy Model output for prevalence of thyroid nodules (benign or malignant) by age category compared to published cross sectional data of the German population.