Ultrasonography for the Prediction of High-Volume Lymph Node Metastases in Papillary Thyroid Carcinoma: Should Surgeons Believe Ultrasound Results?

The Incidence Trend and Management of Thyroid Cancer-What Has Changed in the Past Years: Own Experience and Literature Review

Because of ambiguous and widely debated observations concerning the incidence, trend, and management of TC, we performed this analysis. We drew attention to some events, such as "cancer screening activity", introduction of noninvasive follicular neoplasm with papillary-like nuclear features (NIFTP) to TC types, possibility of papillary thyroid microcarcinoma (PTMC) active surveillance (AS), occurrence of personalized medicine in TC management, and, finally, COVID-19 pandemic time. Because of the opinion that all changes have been made mostly by PTC, we compared it to the remaining types of TC in terms of incidence, clinical and pathological characteristics, and treatment. We analyzed patients treated in a single surgical center in eastern Europe (Poland). The prevalence of TC significantly increased from 5.15% in 2008 to 13.84% in 2015, and then significantly decreased to 1.33% in 2022 when the COVID-19 pandemic lasted (p < 0.0001). A similar trend was observed for PTC, when the incidence significantly increased to 13.99% in 2015 and then decreased to 1.38% in 2022 (p < 0.0001). At that time, the NIFTP category was introduced, and observation of PTMC began. The prevalence of FTC and MTC also increased until 2015 and then decreased. Significant differences in age, types of surgery, necessity of reoperation, and pTNM between PTCs and other types of TCs were observed. The average age was significantly lower in PTC patients than in patients with the remaining types of TC (p < 0.0001). Four milestones, including NIFTP introduction, the possibility of PTMC AS, personalized cancer medicine, and the COVID-19 pandemic, may have influenced the general statistics of TC.

Ultrasonic Feature Prediction of Large-Number Central Lymph Node Metastasis in Clinically Node-Negative Solitary Papillary Thyroid Carcinoma

BACKGROUND

The purpose of this study was to investigate the preoperative prediction of large-number central lymph node metastasis (CLNM) in single thyroid papillary carcinoma (PTC) with negative clinical lymph nodes.

METHODS

A total of 634 patients with clinically lymph node-negative single PTC who underwent thyroidectomy and central lymph node dissection at the First Affiliated Hospital of Anhui Medical University and the Nanchong Central Hospital between September 2018 and September 2021 were analyzed retrospectively. According to the CLNM status, the patients were divided into two groups: small-number (≤5 metastatic lymph nodes) and large-number (>5 metastatic lymph nodes). Univariate and multivariate analyses were used to determine the independent predictors of large-number CLNM. Simultaneously, a nomogram based on risk factors was established to predict large-number CLNM.

RESULTS

The incidence of large-number CLNM was 7.7%. Univariate and multivariate analyses showed that age, tumor size, and calcification were independent risk factors for predicting large-number CLNM. The combination of the three independent predictors achieved an AUC of 0.806. Based on the identified risk factors that can predict large-number CLNM, a nomogram was developed. The analysis of the calibration map showed that the nomogram had good performance and clinical application.

CONCLUSION

In patients with single PTC with negative clinical lymph nodes large-number CLNM is related to age, size, and calcification in patients with a single PTC with negative clinical lymph nodes. Surgeons and radiologists should pay more attention to patients with these risk factors. A nomogram can help guide the surgical decision for PTC.

A novel nomogram for identifying high-risk patients among active surveillance candidates with papillary thyroid microcarcinoma

Objective

Active surveillance (AS) has been recommended as the first-line treatment strategy for low-risk (LR) papillary thyroid microcarcinoma (PTMC) according to the guidelines. However, preoperative imaging and fine-needle aspiration could not rule out a small group of patients with aggressive PTMC with large-volume lymph node micro-metastasis, extrathryoidal invasion to surrounding soft tissue, or high-grade malignancy from the AS candidates.

Methods

Among 2,809 PTMC patients, 2,473 patients were enrolled in this study according to the inclusion criteria. Backward stepwise multivariate logistic regression analysis was used to filter clinical characteristics and ultrasound features to identify independent predictors of high-risk (HR) patients. A nomogram was developed and validated according to selected risk factors for the identification of an HR subgroup among "LR" PTMC patients before operation.

Results

For identifying independent risk factors, multivariable logistic regression analysis was performed using the backward stepwise method and revealed that male sex [3.91 (2.58-5.92)], older age [0.94 (0.92-0.96)], largest tumor diameter [26.7 (10.57-69.22)], bilaterality [1.44 (1.01-2.3)], and multifocality [1.14 (1.01-2.26)] were independent predictors of the HR group. Based on these independent risk factors, a nomogram model was developed for predicting the probability of HR. The C index was 0.806 (95% CI, 0.765-0.847), which indicated satisfactory accuracy of the nomogram in predicting the probability of HR.

Conclusion

Taken together, we developed and validated a nomogram model to predict HR of PTMC, which could be useful for patient counseling and facilitating treatment-related decision-making.

Active surveillance versus immediate surgery: A comparison of clinical and quality of life outcomes among patients with highly suspicious thyroid nodules 1 cm or smaller in China

INTRODUCTION

Active surveillance (AS) is considered an alternative to immediate surgery (IS) for low-risk papillary thyroid microcarcinoma (PTMC) patients. However, it is difficult to decide between AS and IS due to limited evidence regarding risks and benefits for patients in China.

METHODS

This study prospectively enrolled 485 patients with highly suspicious thyroid nodules

RESULTS

The oncological outcomes of the IS and AS groups were similarly excellent. The IS group had significantly higher rates of temporary vocal cord paralysis (VCP) and temporary hypoparathyroidism than the AS group (2.7% vs. 0.2%, p = 0.002; 13.6% vs.1.9%, p < 0.001, respectively). The IS group had significantly more patients on hormone replacement therapy (98.4% vs. 10.9%, p < 0.001) and a significantly higher incidence of neck scarring (94.3% vs. 9.1%, p < 0.001) compared to the AS group. In the early stages, the quality of life questionnaire showed significant differences with respect to three items: voice, throat/mouth, and surgical scarring, with more complaints in the IS group. However, one year or more after surgery, the main complaint was surgical scarring.

CONCLUSION

In China, AS can achieve similar short-term therapeutic effects as IS. As this approach can reduce the occurrence of unfavorable events, achieve better quality of life, it is a feasible option for patients with highly suspicious thyroid nodules.

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Key Words

• Active surveillance
• Adverse events
• Highly suspicious thyroid nodules
• Immediate surgery
• Quality of life

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MESH Headings

• Humans
• Thyroid Nodule/surgery
• Quality of Life
• Watchful Waiting
• Cicatrix/pathology
• Cicatrix/surgery
• Thyroidectomy/methods
• Thyroid Neoplasms/pathology
• China/epidemiology

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Affiliation(s)

Chunhao Liu Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Hao Zhao Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Yu Xia Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Yue Cao Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Liyang Zhang Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Ya Zhao Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Luying Gao Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Ruifeng Liu Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Yuewu Liu Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Hongfeng Liu Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Zhilan Meng Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Shuzhou Liu Department of Otolaryngology Head and Neck Surgery, Hainan General Hospital, Hainan, 570311, China.
Ying Lu Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
Xiaoyi Li Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.

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Development of a Clinical-Radiomics Nomogram That Used Contrast-Enhanced Ultrasound Images to Anticipate the Occurrence of Preoperative Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma Patients

Background and Objectives

Papillary thyroid carcinoma (PTC) is a prevalent histological type of thyroid cancer; however, noninvasive assessment of cervical lymph node metastasis (LNM) poses a challenge. This study aims to develop a novel clinical-radiomics nomogram that utilizes ultrasound (US) images to predict the presence of cervical LNM metastasis in patients with PTC.

Methods

A total of 423 patients with PTC were recruited to participate in this study between January 2020 and December 2022, of which 282 were classified into the training group and 141 patients were classified into the validation set. Contrast-enhanced ultrasound (CEUS) and B-mode ultrasound (BMUS) images were subjected to radiomic analysis, leading to the extraction of 912 radiomic features. Thereafter, a radiomics score (Radscore) was developed to effectively integrate the information derived from BMUS and CEUS modalities. Univariate and multivariate backward stepwise logistic regression analysis techniques were used to construct the clinical and clinical-radiomics models, respectively.

Results

The findings revealed that the clinical-radiomics nomogram incorporated age, sex, CEUS Radscore, and US-reported LNM as risk factors. The nomogram demonstrated good performance using data from the training (AUC = 0.891) and validation (AUC = 0.870) sets. The decision curve analysis implied that this nomogram exhibited good clinical utility, which was further supported by the results of the calibration curves and Hosmer-Lemeshow test.

Conclusion

The CEUS Radscore-based clinical radiomics nomogram could serve as a valuable tool for predicting cervical LNM metastasis in patients with PTC, thereby tailoring individualized treatment strategies for them.

Ultrasound radiomics nomogram for predicting large-number cervical lymph node metastasis in papillary thyroid carcinoma

Purpose

To evaluate the value of preoperative ultrasound (US) radiomics nomogram of primary papillary thyroid carcinoma (PTC) for predicting large-number cervical lymph node metastasis (CLNM).

Materials and methods

A retrospective study was conducted to collect the clinical and ultrasonic data of primary PTC. 645 patients were randomly divided into training and testing datasets according to the proportion of 7:3. Minimum redundancy-maximum relevance (mRMR) and least absolution shrinkage and selection operator (LASSO) were used to select features and establish radiomics signature. Multivariate logistic regression was used to establish a US radiomics nomogram containing radiomics signature and selected clinical characteristics. The efficiency of the nomogram was evaluated by the receiver operating characteristic (ROC) curve and calibration curve, and the clinical application value was assessed by decision curve analysis (DCA). Testing dataset was used to validate the model.

Results

TG level, tumor size, aspect ratio, and radiomics signature were significantly correlated with large-number CLNM (all P< 0.05). The ROC curve and calibration curve of the US radiomics nomogram showed good predictive efficiency. In the training dataset, the AUC, accuracy, sensitivity, and specificity were 0.935, 0.897, 0.956, and 0.837, respectively, and in the testing dataset, the AUC, accuracy, sensitivity, and specificity were 0.782, 0.910, 0.533 and 0.943 respectively. DCA showed that the nomogram had some clinical benefits in predicting large-number CLNM.

Conclusion

We have developed an easy-to-use and non-invasive US radiomics nomogram for predicting large-number CLNM with PTC, which combines radiomics signature and clinical risk factors. The nomogram has good predictive efficiency and potential clinical application value.

Nomogram for preoperative prediction of high-volume lymph node metastasis in the classical variant of papillary thyroid carcinoma

Introduction

The objective of our study was to construct a preoperative prediction nomogram for the classical variant of papillary thyroid carcinoma (CVPTC) patients with a solitary lesion based on demographic and ultrasonographic parameters that can quantify the individual probability of high-volume (>5) lymph node metastasis (HVLNM).

Materials and methods

In this study, a total of 626 patients with CVPTC from December 2017 to November 2022 were reviewed. Their demographic and ultrasonographic features at baseline were collected and analyzed using univariate and multivariate analyses. Significant factors after the multivariate analysis were incorporated into a nomogram for predicting HVLNM. A validation set from the last 6 months of the study period was conducted to evaluate the model performance.

Results

Male sex, tumor size >10 mm, extrathyroidal extension (ETE), and capsular contact >50% were independent risk factors for HVLNM, whereas middle and old age were significant protective factors. The area under the curve (AUC) was 0.842 in the training and 0.875 in the validation set.

Conclusions

The preoperative nomogram can help tailor the management strategy to the individual patient. Additionally, more vigilant and aggressive measures may benefit patients at risk of HVLNM.

Active surveillance of highly suspicious thyroid nodules cohort in China shows a worse psychological status in younger patients

BACKGROUND

Active surveillance has been considered a safe alternative to surgery for low-risk papillary thyroid microcarcinoma. This study aimed to assess the oncological outcomes and psychological status of active surveillance of highly suspicious thyroid nodules ≤10 mm in China.

METHODS

This prospective single-center cohort study enrolled 336 patients with highly suspicious thyroid nodules for active surveillance to assess oncological outcomes and psychological status. The psychological status of patients was assessed by two different questionnaires and compared among different patient groups.

RESULTS

During a median follow-up period of 28.5 months, eight patients underwent delayed surgery for tumor enlargement and one for lymph node metastases. The cumulative incidence of disease progression at 5 and 10 years was 6.0% and 12.8%, respectively. Patients who underwent delayed surgery had no permanent complications, and no patient had distant metastasis or death. Patients ≤30 years old had a higher baseline anxiety score (4.9 vs. 3.8, p=0.024), a higher proportion of baseline anxiety score, i.e., ≥8 points (24.0% vs. 12.6%, p=0.033), and a worse baseline emotional function (62.7 vs. 70.7, p=0.013) than patients >30. During AS, patients ≤30 years of age had higher overall anxiety levels (p=0.005) and a worse overall emotional function (p=0.001).

CONCLUSIONS

Active surveillance in Chinese patients with highly suspicious subcentimetre thyroid nodules has good oncological outcomes and can be used as a safe alternative to surgery. Younger patients (≤30) show a worse psychological status; therefore, more attention should be paid to younger patients.

The clinical significance of thyroid hormone-responsive in thyroid carcinoma and its potential regulatory pathway

The study aimed to evaluate the clinical significance of thyroid hormone-responsive (THRSP) and explore its relevant pathways in thyroid carcinoma (THCA). The gene expression data of THRSP were obtained and the prognostic significance of THRSP in THCA was analyzed through various bioinformatics databases. Then, the factors influencing THRSP mRNA expression were explored, and the function of THRSP in predicting the lymph node metastasis (LNM) stage was determined. We further performed the enrichment analysis and constructed a protein-protein interaction (PPI) network to examine potential regulatory pathways associated with THRSP. THRSP gene expression was significantly increased in THCA compared with the normal tissues. High THRSP mRNA expression had a favorable overall survival (OS) in THCA patients (P < .05). Additionally, the mRNA expression of THRSP was related to stage, histological subtype, and methylation among THCA patients (all P < .05). Besides, THRSP served as a potent predictor in discriminating the LNM stage of thyroid cancer patients. According to Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) on THRSP-associated genes, THRSP was positively related to metabolic pathways. The upregulation of THRSP predicted a good OS in THCA patients. Furthermore, THRSP might inhibit THCA progression through positive regulation of metabolism-associated pathways.

Lymph Node Metastases Identified at the Post-Ablation 131I SPECT/CT Scan Is a Prognostic Factor of Intermediate-Risk Papillary Thyroid Cancer

The intermediate-risk category of papillary thyroid cancer (PTC) comprises heterogeneous patients within a wide range of stages and varied care management. Understanding the risk features of recurrence observed after the initial therapy should be emphasized. We aimed to evaluate the prognostic significance of radioactive iodine-avid lymph nodes observed during the initial treatment of patients with PTC that were considered to be at intermediate risk. Data on patients with intermediate-risk PTC treated from 2012 to 2018 were retrospectively reviewed. Post-therapeutic SPECT/CT (Rx SPECT/CT) was evaluated in the enrolled patients. The clinical, pathologic, and incidence of radioiodine-avid (RAI-avid) lymph node metastasis (mLN) on Rx SPECT/CT were reviewed, and risk factors related to recurrent disease were analyzed. After a median follow-up of 37.26 (30.90, 46.33) months, structural persistent/recurrent disease was detected in 9.81% (36/367) of patients with intermediate-risk tumors. The incidence of recurrence was higher in patients who demonstrated RAI-avid mLN after the initial therapy than in those who did not (p < 0.001). In a multivariate Cox proportional hazard regression analysis, RAI-avid mLN appeared to be a robust risk factor for recurrent disease after the initial therapy (HR: 8.967, 95% CI: 3.433−23.421, p = 0.000). RAI-avid mLN is a significant risk factor for recurrent intermediate-risk PTC after the initial treatment.

Application of Machine Learning Algorithms to Predict Central Lymph Node Metastasis in T1-T2, Non-invasive, and Clinically Node Negative Papillary Thyroid Carcinoma

Purpose: While there are no clear indications of whether central lymph node dissection is necessary in patients with T1-T2, non-invasive, clinically uninvolved central neck lymph nodes papillary thyroid carcinoma (PTC), this study seeks to develop and validate models for predicting the risk of central lymph node metastasis (CLNM) in these patients based on machine learning algorithms. Methods: This is a retrospective study comprising 1,271 patients with T1-T2 stage, non-invasive, and clinically node negative (cN0) PTC who underwent surgery at the Department of Endocrine and Breast Surgery of The First Affiliated Hospital of Chongqing Medical University from February 1, 2016, to December 31, 2018. We applied six machine learning (ML) algorithms, including Logistic Regression (LR), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), and Neural Network (NNET), coupled with preoperative clinical characteristics and intraoperative information to develop prediction models for CLNM. Among all the samples, 70% were randomly selected to train the models while the remaining 30% were used for validation. Indices like the area under the receiver operating characteristic (AUROC), sensitivity, specificity, and accuracy were calculated to test the models' performance. Results: The results showed that ~51.3% (652 out of 1,271) of the patients had pN1 disease. In multivariate logistic regression analyses, gender, tumor size and location, multifocality, age, and Delphian lymph node status were all independent predictors of CLNM. In predicting CLNM, six ML algorithms posted AUROC of 0.70-0.75, with the extreme gradient boosting (XGBoost) model standing out, registering 0.75. Thus, we employed the best-performing ML algorithm model and uploaded the results to a self-made online risk calculator to estimate an individual's probability of CLNM (https://jin63.shinyapps.io/ML_CLNM/). Conclusions: With the incorporation of preoperative and intraoperative risk factors, ML algorithms can achieve acceptable prediction of CLNM with Xgboost model performing the best. Our online risk calculator based on ML algorithm may help determine the optimal extent of initial surgical treatment for patients with T1-T2 stage, non-invasive, and clinically node negative PTC.