Suspicious Ultrasound Characteristics Correlate with Multiple Factors that Predict Central Lymph Node Metastasis of Papillary Thyroid Carcinoma: Significant Role of HBME-1
Thyroid World Congress ePoster Library. Li j. 06/22/19; 272064; 209
Dr. jianming Li
Dr. jianming Li
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Rate & Comment (0)

Abstract



Objective: Papillary thyroid carcinoma (PTC) is frequently associated with central lymph node metastasis (CLNM). Here we aimed to identify possible risk factors, including suspicious ultrasound (US) features coexisting with thyroid diseases, including immunohistochemical markers and BRAFV600E. These were used to establish a model to predict the risk of CLNM.



Methods: From January 2016 to March 2018, we identified a cohort of patients with classic PTC who underwent cervical US and were diagnosed by postoperative pathology. Fine-needle aspiration biopsies were analyzed for the presence of BRAFV600E, and immunohistochemistry was used to detect tumor markers. US imaging was performed in accordance with a standardized protocol. A model to determine the risk of CLNM was established using the outcomes of univariate and multivariate analyses.



Results: Age ≥45 years, male sex, mean tumor diameter ≥1.0 cm, taller-than-wide tumor shape, multiple PTCs, capsule contact, and HBME-1 expression were significant independent risk predictors of CLNM. Hashimoto’s thyroiditis, nodular goiter, and BRAFV600E were not significantly associated with CLNM. The cutoff value (area under the curve = 0.760) for predicting risk was determined from receiver operating characteristic curves (sensitivity, 75.6%; specificity, 60.7%).



Conclusions: Male sex, age ≥45 years, mean tumor diameter ≥1.0 cm, taller-than-wide shape, multiple tumors, capsule contact, and HBME-1 expression were independent predictors of the risk of CLNM of patients with PTC. The risk model may be useful for evaluating patients’ prognoses and selection of the optimal surgical strategy.


Abstract



Objective: Papillary thyroid carcinoma (PTC) is frequently associated with central lymph node metastasis (CLNM). Here we aimed to identify possible risk factors, including suspicious ultrasound (US) features coexisting with thyroid diseases, including immunohistochemical markers and BRAFV600E. These were used to establish a model to predict the risk of CLNM.



Methods: From January 2016 to March 2018, we identified a cohort of patients with classic PTC who underwent cervical US and were diagnosed by postoperative pathology. Fine-needle aspiration biopsies were analyzed for the presence of BRAFV600E, and immunohistochemistry was used to detect tumor markers. US imaging was performed in accordance with a standardized protocol. A model to determine the risk of CLNM was established using the outcomes of univariate and multivariate analyses.



Results: Age ≥45 years, male sex, mean tumor diameter ≥1.0 cm, taller-than-wide tumor shape, multiple PTCs, capsule contact, and HBME-1 expression were significant independent risk predictors of CLNM. Hashimoto’s thyroiditis, nodular goiter, and BRAFV600E were not significantly associated with CLNM. The cutoff value (area under the curve = 0.760) for predicting risk was determined from receiver operating characteristic curves (sensitivity, 75.6%; specificity, 60.7%).



Conclusions: Male sex, age ≥45 years, mean tumor diameter ≥1.0 cm, taller-than-wide shape, multiple tumors, capsule contact, and HBME-1 expression were independent predictors of the risk of CLNM of patients with PTC. The risk model may be useful for evaluating patients’ prognoses and selection of the optimal surgical strategy.


    This eLearning portal is powered by:
    This eLearning portal is powered by MULTIEPORTAL
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.


Save Settings