The thyroid cancer policy model: A mathematical simulation model of papillary thyroid carcinoma in The U.S. population

Abstract

BackgroundThyroid cancer affects over ½ million people in the U.S. and the incidence of thyroid cancer has increased worldwide at a rate higher than any other cancer, while survival has remained largely unchanged. The aim of this research was to develop, calibrate and verify a mathematical disease model to simulate the natural history of papillary thyroid cancer, which will serve as a platform to assess the effectiveness of clinical and cancer control interventions.MethodsHerein, we modeled the natural pre-clinical course of both benign and malignant thyroid nodules with biologically relevant health states from normal to detected nodule. Using established calibration techniques, optimal parameter sets for tumor growth characteristics, development rate, and detection rate were used to fit Surveillance Epidemiology and End Results (SEER) incidence data and other calibration targets.ResultsModel outputs compared to calibration targets demonstrating sufficient calibration fit and model validation are presented including primary targets of SEER incidence data and size distribution at detection of malignancy. Additionally, we show the predicted underlying benign and malignant prevalence of nodules in the population, the probability of detection based on size of nodule, and estimates of growth over time in both benign and malignant nodules.ConclusionsThis comprehensive model provides a dynamic platform employable for future comparative effectiveness research. Future model analyses will test and assess various clinical management strategies to improve patient outcomes related to thyroid cancer and optimize resource utilization for patients with thyroid nodules.

Impact of the new guidelines of the American Thyroid Association on the treatment of the differentiated thyroid tumor in an Italian center with medium-high volume thyroid surgery

“…The diagnosis of thyroid nodules has increased in the last decade and, although most of them turned out to be benign, between 7 and 15% of the cases could present differentiated malignant neoplasms [ 1 ]. The increase in the incidence of differentiated thyroid tumors is largely due to overdiagnosis resulting from ultrasound screening and from cytological examination (needle aspiration) but also in part to a greater exposure to radiating agents [ 2 ].…”

Mathematical models applied to thyroid cancer

“…As for the articles that were included in the systematic review, an overview of each is given as follows. In Lubitz et al (2016), there is a mathematical approach using an ODE model with logistic growth for both benign and malignant thyroid tumors. In the text are modeled some characteristics as tumor volume over time, development rate, and detection rate among others.…”

“…A challenging aspect of the use of mathematical models concerns the estimation of parameters and in some papers of this review the realization of this process is observed (Barbolosi et al 2017;Chen et al 2007;Lubitz et al 2016). However, for accomplishing this task, a database and appropriate methods should be used.…”

“…In this review, several types of mathematical models on thyroid cancer were studied and the ODEs were the means most frequently adopted by the authors. From this tool, aspects such as tumor growth (Lubitz et al 2016;Kolpak et al 2016); effective half-life of radioiodine applied after thyroidectomy (Chen et al 2007); and the efficiency of the treatment with 131 I in metastatic thyroid cancers (Barbolosi et al 2017) could be addressed. Otherwise, the PDEs were considered in the study of the diffusive process of tumors (Kolpak et al 2016) and detection of nodules, with a suggestion of thermal treatment from the results obtained (Gavriloaia and Gavriloaia 2010).…”

“…On the subtypes of modeled cancers, the papers (Barbolosi et al 2017;Lubitz et al 2016;Chen et al 2007) focused on papillary thyroid cancer, Ruggieri et al (2008) and Gavriloaia and Gavriloaia (2010) dealt with thyroid cancer in general, and Traino and Di Martino (2006) refers to differentiated cancer. In Kolpak et al (2016), since the main model predicts a cessation in iodine uptake, and consequently, the nonproduction of thyroglobulin and T4 hormone by the thyroid cells, this work may be related to anaplastic thyroid cancer.…”