Sonographic and Clinical Features of Papillary Thyroid Microcarcinoma Less than or Equal to Five Millimeters: A Retrospective Study

The increasing prevalence of chronic lymphocytic thyroiditis in papillary microcarcinoma

Although the incidence of some malignancy has decreased over the recent years, this is not the case of papillary thyroid microcarcinoma (PTMC), whose incidence has increased worldwide. Most PTMC are found incidentally after histological examination of specimens from surgery for benign thyroid disease. Hashimoto's thyroiditis, whose incidence has also increased, coexists in about one in three PTMC patients. Three different mechanisms have been proposed to clarify the association between chronic lymphocytic thyroiditis and PTMC, namely tumor development/growth by: (i) TSH stimulation, (ii) expression of certain proto-oncogenes, (iii) chemokines and other molecules produced by the lymphocytic infiltrate. Whether Hashimoto's thyroiditis protects against lymph node metastasis is debated. Overall, autommune thyroiditis seems to contribute to the favorable prognosis of PTMC. Major limitations of the studies so far performed include: (i) retrospective design, (ii) limited statistical power, (iii) high risk of selection bias, (iv) and predominant Asian ethnicity of patients. Full genetic profiling of both diseases and identification of environmental factors capable to trigger them, as well as well-powered prospective studies on different ethnical groups, may help understand their causal association and why their frequencies are continuing raising.

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

Background

Thyroid 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.

Methods

Herein, 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.

Results

Model 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.

Conclusions

This 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.

Indolent thyroid cancer: knowns and unknowns

Thyroid cancer incidence is rapidly increasing due to increased detection and diagnosis of indolent thyroid cancer, i.e. cancer that is likely to be clinically insignificant. Clinical, radiologic, and pathologic features predicting indolent behavior of thyroid cancer are still largely unknown and unstudied. Existing clinicopathologic staging systems are useful for providing prognosis in the context of treated thyroid cancer but are not designed for and are inadequate for predicting indolent behavior. Ultrasound studies have primarily focused on discrimination between malignant and benign nodules; some studies show promising data on using sonographic features for predicting indolence but are still in their early stages. Similarly, molecular studies are being developed to better characterize thyroid cancer and improve the yield of fine needle aspiration biopsy, but definite markers of indolent thyroid cancer have yet to be identified. Nonetheless, active surveillance has been introduced as an alternative to surgery in the case of indolent thyroid microcarcinoma, and protocols for safe surveillance are in development. As increased detection of thyroid cancer is all but inevitable, increased research on predicting indolent behavior is needed to avoid an epidemic of overtreatment.

Indolent thyroid cancer: knowns and unknowns

Thyroid cancer incidence is rapidly increasing due to increased detection and diagnosis of indolent thyroid cancer, i.e. cancer that is likely to be clinically insignificant. Clinical, radiologic, and pathologic features predicting indolent behavior of thyroid cancer are still largely unknown and unstudied. Existing clinicopathologic staging systems are useful for providing prognosis in the context of treated thyroid cancer but are not designed for and are inadequate for predicting indolent behavior. Ultrasound studies have primarily focused on discrimination between malignant and benign nodules; some studies show promising data on using sonographic features for predicting indolence but are still in their early stages. Similarly, molecular studies are being developed to better characterize thyroid cancer and improve the yield of fine needle aspiration biopsy, but definite markers of indolent thyroid cancer have yet to be identified. Nonetheless, active surveillance has been introduced as an alternative to surgery in the case of indolent thyroid microcarcinoma, and protocols for safe surveillance are in development. As increased detection of thyroid cancer is all but inevitable, increased research on predicting indolent behavior is needed to avoid an epidemic of overtreatment.