Metastasis Of Thyroid Carcinoma Research Articles

Risk factor score for the prediction of central compartment lymph node metastasis in papillary thyroid carcinoma and its clinical significance.

To establish the criteria for a risk factor score (RFS) for predicting the probability of central compartment lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) and to explore the clinical significance of the RFS. The data of 412 patients with PTC who underwent surgical resection between May 2013 and July 2016 were retrospectively analysed and divided into two groups: a central LNM group and a non-central LNM group. In each group, the frequency of six risk factors was documented: sex, age, tumour size, extracapsular spread (ECS), tumour multifocality, and tumour location. The maximum likelihood method of discriminant analysis was adopted to calculate patient scores for the six risk indicators. In addition, the data of 104 patients with PTC admitted between July 2016 and December 2016 were prospectively analysed using this method and these six risk factors. A higher score represented one certain possibility that was the more appropriate for one patient. In the retrospective group, the result was as follows: 129 patients with positive (+) lymph nodes in the central compartment and 168 patients with negative (-) lymph nodes in the central compartment, which was in line with the actual results. In the prospective group, there were 28 patients with positive lymph nodes in the central compartment and 48 patients with negative lymph nodes in the central compartment. The coincidence rates using the RFS were 71.9% for the retrospective group and 73.1% for the prospective group. By simple and quantitative analyses of the presence of central LNM, the RFS is of great significance when choosing surgical approaches and postoperative individual-based treatment plans, as well as when determining the prognosis of central compartment LNM in patients with PTC.

Risk factors and prediction models of lymph node metastasis in papillary thyroid carcinoma based on clinical and imaging characteristics

ABSTRACT Background Papillary thyroid carcinoma (PTC) commonly presents with lymph node metastasis, which may be associated with worsened prognosis. This study aimed to comprehensively evaluate the risk factors of lymph node metastasis in PTC based on preoperative clinical and imaging data and to construct a nomogram model to predict the risk of lymph node metastasis. Methods A total of 989 patients with PTC were enrolled and randomly divided into training and validation cohorts in an 8:2 ratio. Independent risk factors for lymph node metastasis in PTC were analyzed using univariate and stepwise multivariate logistic regression. An importance analysis of independent risk factors affecting lymph node metastasis was performed according to the random forest method. Subsequently, a nomogram to predict lymph node metastasis was constructed, and the predictive effect of the nomogram was evaluated using receiver operating characteristic analysis and calibration curves. Results Univariate regression analysis revealed that age, sex, body weight, systolic blood pressure, free triiodothyronine, nodule location, nodule number, Thyroid Imaging Reporting and Data System (TI-RADS) grade on color Doppler ultrasound, enlarged lymph node present on imaging, and nodule diameter could affect lymph node metastasis in PTC. Stepwise multivariate regression analysis showed that sex, age, enlarged lymph node present on imaging, nodule diameter, and color Doppler TI-RADS grade were independent risk factors for lymph node metastasis in PTC. Combining these five independent risk factors, a nomogram prediction model was constructed. The area under the curve (AUC) of the nomogram in the training and validation cohorts was 0.742 and 0.765, respectively, with a well-fitted calibration curve. Conclusion Our study showed that independent risk factors for lymph node metastasis in PTC were sex, age, enlarged lymph node present on imaging, nodule diameter, and color Doppler TI-RADS grade. The nomogram constructed based on these independent risk factors can better predict the risk of lymph node metastasis.

Prediction of Cervical Lymph Nodes Metastasis in Papillary Thyroid Carcinoma (PTC) Using Nodal Staging Score (NSS).

Background Cervical lymph node metastasis is commonly seen in papillary thyroid carcinoma. Surgery is the preferred treatment for PTC with cervical lymph node metastasis. There is no alternate ultrasound, neck CT, and thyroglobulin (Tg) methods to assess the occult lymph node metastasis. For moderate-and high-risk PTC, the number of lymph nodes to be dissected should be increased to remove the occult lymph node metastasis. Objective This study was designed to develop a nodal staging score model to predict the likelihood of lymph node metastasis in papillary thyroid carcinoma (PTC), and further guide the treatments. Material and Methods. Data were collected from the SEER database. Patients with PTC from 2000 to 2005 were selected. The beta-binomial model was adopted to establish a nodal staging score (NSS)-based model. The NSS-based model was built according to gender, age, extrathyroidal invasion, tumor multifocality, tumor size, and T stage of the patients. A total of 12,431 PTC patients were included in our study. Various types of lymph nodes were examined based on various categories (incidence, risk assessment) to evaluate the results. Results 5,959 (47.9%) patients in the study were positive and 6,472 (52.1%) were confirmed negative for lymph node metastasis. The corrected incidence of lymph node metastasis was higher than that of direct calculation, regardless of the factors that affected lymph node metastasis. There were significant differences in the OS of PTC patients among the four groups and T stage (p is less than 0.05), indicating that cervical lymph node metastasis would have an impact on the prognosis of patients. Conclusion In conclusion, an NSS-based model base on a variety of clinicopathological factors can be used to predict lymph node metastasis. It is important to evaluate the risk of occult lymph node metastasis in the treatment of PTC.. Since, this statistical model can describe the risk of occult lymph node metastasis in patients; therefore, it can be used as basis for decision-making related to the number of lymph nodes that can be dissected in operations.

Radiologist versus Non-Radiologist Detection of Lymph Node Metastasis in Papillary Thyroid Carcinoma by Ultrasound: A Meta-Analysis.

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer worldwide and is known to spread to adjacent neck lymphatics. Lymph node metastasis (LNM) is a known predictor of disease recurrence and is an indicator for aggressive resection. Our study aims to determine if ultrasound sonographers’ degree of training influences overall LNM detection. PubMed, Embase, and Scopus articles were searched and screened for relevant articles. Two investigators independently screened and extracted the data. Diagnostic test parameters were determined for all studies, studies reported by radiologists, and studies reported by non-radiologists. The total sample size amounted to 5768 patients and 10,030 lymph nodes. Radiologists performed ultrasounds in 18 studies, while non-radiologists performed ultrasounds in seven studies, corresponding to 4442 and 1326 patients, respectively. The overall sensitivity of LNM detection by US was 59% (95%CI = 58–60%), and the overall specificity was 85% (95%CI = 84–86%). The sensitivity and specificity of US performed by radiologists were 58% and 86%, respectively. The sensitivity and specificity of US performed by non-radiologists were 62% and 78%, respectively. Summary receiver operating curve (sROC) found radiologists and non-radiologists to detect LNM on US with similar accuracy (p = 0.517). Our work suggests that both radiologists and non-radiologists alike detect overall LNM with high accuracy on US.

Nomogram for preoperative estimation risk of cervical lymph node metastasis in medullary thyroid carcinoma.

ObjectivesCervical lymph node metastasis (CLNM) is common in medullary thyroid carcinoma (MTC), but how to manage cervical lymph node involvement of clinically negative MTC is still controversial. This study evaluated the preoperative features and developed an ultrasound (US)-based nomogram to preoperatively predict the CLNM of MTC.Materials and methodsA total of 74 patients with histologically confirmed MTC were included in this retrospective study and assigned to the CLNM-positive group and CLNM-negative group based on the pathology. The associations between CLNM and preoperative clinical and sonographic characteristics (size, location, solid component, shape, margin, echogenicity, calcification, and extracapsular invasion of the tumor) were evaluated by the use of univariable and multivariable logistic regression analysis. A nomogram to predict the risk of the CLNM of MTC was built and assessed in terms of discrimination, calibration, and clinical usefulness.ResultsThe nomogram was based on three factors (tumor margin, US-reported suspicious lymph node, and extracapsular invasion US features) and exhibited good discrimination with an area under the curve (AUC) of 0.919 (95% CI, 0.856–0.932). The calibration curves of the nomogram displayed a good agreement between the probability as predicted by the nomogram and the actual CLNM incidence.ConclusionsWe constructed and validated a US-based nomogram to predict the risk of CLNM in MTC patients, which can be easily evaluated before surgery. This model is helpful for clinical decision-making.

Prediction of Central Lymph Node Metastasis in cN0 Papillary Thyroid Carcinoma by CT Radiomics

To explore the feasibility of the preoperative prediction of pathological central lymph node metastasis (CLNM) status in patients with negative clinical lymph node (cN0) papillary thyroid carcinoma (PTC) using a computed tomography (CT) radiomics signature. A total of 97 PTC cN0 nodules with CLNM pathology data (pN0, with CLNM, n=59; pN1, without CLNM, n=38) in 85 patients were divided into a training set (n=69) and a validation set (n=28). For each lesion, 321 radiomic features were extracted from nonenhanced, arterial and venous phase CT images. Minimum redundancy and maximum relevance and the least absolute shrinkage and selection operator were used to find the most important features with which to develop a radiomics signature in the training set. The performance of the radiomics signature was evaluated by receiver operating characteristic curves, calibration curves and decision curve analysis . Three nonzero the least absolute shrinkage and selection operator coefficient features were selected for radiomics signature construction. The radiomics signature for distinguishing the pN0 and pN1 groups achieved areas under the curve of 0.79 (95% CI 0.67, 0.91) in the training set and 0.77 (95% CI 0.55, 0.99) in the validation set. The calibration curves demonstrated good agreement between the radiomics score-predicted probability and the pathological results in the two sets (p= 0.399, p=0.191). The decision curve analysis curves showed that the model was clinically useful. This radiomic signature could be helpful to predict CLNM status in cN0 PTC patients.

CREB3L1 promotes tumor growth and metastasis of anaplastic thyroid carcinoma by remodeling the tumor microenvironment

Anaplastic thyroid carcinoma (ATC) is an extremely malignant type of endocrine cancer frequently accompanied by extrathyroidal extension or metastasis through mechanisms that remain elusive. We screened for the CREB3 transcription-factor family in a large cohort, consisting of four microarray datasets. This revealed that CREB3L1 was specifically up regulated in ATC tissues and negatively associated with overall survival of patients with thyroid cancer. Consistently, high expression of CREB3L1 was negatively correlated with progression-free survival in an independent cohort. CREB3L1 knockdown dramatically attenuated invasion of ATC cells, whereas overexpression of CREB3L1 facilitated the invasion of papillary thyroid carcinoma (PTC) cells. Loss of CREB3L1 inhibited metastasis and tumor growth of ATC xenografts in zebrafish and nude mouse model. Single-cell RNA-sequencing analysis revealed that CREB3L1 expression gradually increased during the neoplastic progression of a thyroid follicular epithelial cell to an ATC cell, accompanied by the activation of the extracellular matrix (ECM) signaling. CREB3L1 knockdown significantly decreased the expression of collagen subtypes in ATC cells and the fibrillar collagen in xenografts. Due to the loss of CREB3L1, ATC cells were unable to activate alpha-smooth muscle actin (α-SMA)-positive cancer-associated fibroblasts (CAFs). After CREB3L1 knockdown, the presence of CAFs inhibited the growth of ATC spheroids and the metastasis of ATC cells. Further cytokine array screening showed that ATC cells activated α-SMA-positive CAFs through CREB3L1-mediated IL-1α production. Moreover, KPNA2 mediated the nuclear translocation of CREB3L1, thus allowing it to activate downstream ECM signaling. These results demonstrate that CREB3L1 maintains the CAF-like property of ATC cells by activating the ECM signaling, which remodels the tumor stromal microenvironment and drives the malignancy of ATC.Graphical

Risks of central lymph node metastasis in papillary thyroid carcinoma with or without multifocality in at least one lobe: A multi-center analysis

PurposesTo quantitatively predict central lymph node metastasis (CLNM) risks by comparing the clinicopathological features of different multifocal manifestations in papillary thyroid carcinomas (PTC) patients. MethodsA total of 998 PTC patients from three medical centers were retrospectively analyzed. ResultsPTC patients with multifocal lesions in at least one thyroid lobe (MF group) yielded significantly higher CLNM rates than those with unifocal lesions in one or both lobes (UF group). Multifocality in at least one lobe rather than bilateral presence was confirmed to be an independent risk factor of CLNM for PTC patients. Four (age, gender, maximum tumor diameter, and thyroid capsular invasion (TCI)) and three (age, gender, and TCI) factors were proven to be independent risk factors of CLNM for patients within UF and MF groups, respectively. Predictive nomograms were established for these patients based on their respective high-risk factors. The accuracy and validity of these newly-created models were verified using C-index and calibration curves. Patients within UF and MF groups possessing significantly different CLNM risks based on individualized nomogram risk scores were further classified into different subgroups. A detailed CLNM risk stratification flow chart covering all PTC patients was then established. ConclusionA meticulous evaluating system that quantifiesCLNM risk for PTC patients with unifocal lesions in one or both lobes and multifocal lesions in at least one lobe was established.

Lymph Node Metastasis Prediction From Whole Slide Images With Transformer-Guided Multiinstance Learning and Knowledge Transfer.

The gold standard for diagnosing lymph node metastasis of papillary thyroid carcinoma is to analyze the whole slide histopathological images (WSIs). Due to the large size of WSIs, recent computer-aided diagnosis approaches adopt the multi-instance learning (MIL) strategy and the key part is how to effectively aggregate the information of different instances (patches). In this paper, a novel transformer-guided framework is proposed to predict lymph node metastasis from WSIs, where we incorporate the transformer mechanism to improve the accuracy from three different aspects. First, we propose an effective transformer-based module for discriminative patch feature extraction, including a lightweight feature extractor with a pruned transformer (Tiny-ViT) and a clustering-based instance selection scheme. Next, we propose a new Transformer-MIL module to capture the relationship of different discriminative patches with sparse distribution on WSIs and better nonlinearly aggregate patch-level features into the slide-level prediction. Considering that the slide-level annotation is relatively limited to training a robust Transformer-MIL, we utilize the pathological relationship between the primary tumor and its lymph node metastasis and develop an effective attention-based mutual knowledge distillation (AMKD) paradigm. Experimental results on our collected WSI dataset demonstrate the efficiency of the proposed Transformer-MIL and attention-based knowledge distillation. Our method outperforms the state-of-the-art methods by over 2.72% in AUC (area under the curve).

A Rare Presentation of Second Branchial Cleft Cysts in Adult Patient: Case Report with Literature Review

Second branchial cleft cysts are the most common type of branchial cleft cysts as they make up approximately 95% of all cases. These are congenital conditions that occur in the upper lateral neck just anterior to the sternocleidomastoid muscle and caused by fluids filling spaces during early embryonic development. We present a case of atypical presentation of second branchial cleft cysts in 40 year’s patient, A surgical intervention was performed with complete excision of the cysts. Many of branchial cleft cysts would go unnoticed. However, upper respiratory tract infection can cause a sudden and significant increase in the size of the cyst because of the lymphoid tissue beneath the epithelium, The Differential diagnosis would include lymphadenopathy, lipoma, nerve sheath tumor, inflammatory lesions, carotid body tumor, external laryngocele, cystic hygroma, metastatic squamous cell carcinoma, tuberculosis-related, HIV-related lymphadenopathy, sarcoidosis, cat-scratch disease, lymphoma, and papillary thyroid carcinoma metastasis. Surgical excision is the only known treatment for second branchial cleft cysts; moreover, a complete removal of second bronchial cyst cleft is of paramount importance since it is key to preventing any recurrence of the disease.

Nomograms for the prediction of lateral lymph node metastasis in papillary thyroid carcinoma: Stratification by size

BackgroundLateral lymph node metastasis (LLNM) is a risk factor of poor prognosis in papillary thyroid cancer (PTC). We aimed to determine predictive factors and develop the nomograms for LLNM in patients with papillary thyroid microcarcinoma (PTMC) and macro-PTC.MethodsWe reviewed the medical records of 1,106 patients who underwent surgery between January 2019 and January 2022. Patients were divided into a PTMC and a macro-PTC group. We developed preoperative and postoperative nomograms for predicting LLNM based on results of multivariate analysis. Internal calibration was performed for these models.ResultsThe number of metastatic lymph nodes in lateral compartment was higher in macro-PTC patients. LLNM was independently associated with gender, the number of foci, location, shape, and central lymph node metastasis (CLNM) in PTMC patients. For macro-PTC patients, chronic lymphocytic thyroiditis, the number of foci, location, margin, CLNM, and central lymph node ratio were all independent predictors for LLNM. All the above factors were incorporated into nomograms, which showed the perfect discriminative ability.ConclusionThe diameter of the tumor has an impact on the rate of LLNM. Separate predictive systems should be used for PTMC and macro-PTC patients for more accurate clinical assessment of lateral lymph node status. Through these nomograms, we can not only detect high-risk patients with occult LLNM preoperatively, but also form appropriate treatment protocols for postoperative management of PTC patients with different risks.

A multi-institutional study of association of sonographic characteristics with cervical lymph node metastasis in unifocal papillary thyroid carcinoma.

ObjectivePapillary thyroid carcinoma (PTC) is the most common pathological type of thyroid carcinoma, and is prone to cervical lymph node metastases (CLNM). We aim to evaluate the association between sonographic characteristics of PTC and CLNM before the initial surgery.MethodsClinical information as well as ultrasonographic measurements and characteristics for 2376 patients from three hospitals were acquired in this retrospective cohort study. Univariate and multivariate logistic analysis were performed to predict CLNM in unifocal PTC patients. Receiver operating characteristic (ROC) curve was created to evaluate diagnostic performance.ResultsUnivariate analysis showed that gender, age, maximum tumor diameter and volume, cross-sectional and longitudinal aspect ratio, location, echogenicity, margin, and echogenic foci were independently associated with CLNM metastatic status (P < 0.05). Multivariate logistic analysis showed that gender, age, maximum tumor diameter and volume, cross-sectional aspect ratio (CSAR), location, echogenicity, margin, and echogenic foci were independent correlative factors; CSAR showed a significant difference for PTC2 to predict CLNM. The area under the curve (AUC) of the maximum tumor diameter, tumor volume, margin, and echogenic foci was 0.70, 0.69, 0.65, and 0.70, respectively. The multiple-variable linear regression model was constructed with an AUC of 0.77, a specificity of 73.4%, and a sensitivity of 72.3%. Kruskal-Wallis analysis for positive subgroups, maximum tumor diameter and volume, cross-sectional and longitudinal aspect ratio, margin, and echogenic foci showed statistical significance (P < 0.05).ConclusionsYounger age (< 55 years), male, larger tumor, and echogenic foci were high risk factors for CLNM in patients with unifocal PTC. CSAR had a more effective predictive value for CLNM in patients with larger thyroid tumors. A larger tumor with irregular and punctate echogenic foci was also more prone to the lateral neck, and both central and lateral neck metastasis.

Relationship between pretracheal and/or prelaryngeal lymph node metastasis and paratracheal and lateral lymph node metastasis of papillary thyroid carcinoma: A meta-analysis

ObjectiveWe conducted a meta-analysis to study the relationship between pretracheal and/or prelaryngeal lymph node metastasis and paratracheal and lateral lymph node metastasis in papillary thyroid carcinoma.MethodA systematic literature search was conducted using PubMed, Embase, and the Cochrane Library electronic databases for studies published up to February 2022. The reference lists of retrieved articles were also reviewed. Two authors independently assessed the methodological quality and extracted the data. A random-effects model was used to calculate the overall pooled relative risk. Publication bias in these studies was evaluated using Egger’s test and Begg’s test.ResultsTwenty-five independent studies involving 10,525 patients were included in the meta-analysis. The pooled relative risk for ipsilateral and contralateral paratracheal lymph node metastasis was 3.01 (95% confidence interval [CI]: 1.66, 5.45) and 5.68 (95% CI: 2.50, 12.88), respectively, in patients with pretracheal lymph node metastasis. Among patients with prelaryngeal lymph node metastasis, the pooled relative risk for ipsilateral paratracheal and/or pretracheal contralateral paratracheal, and lateral lymph node metastasis was 2.02 (95% CI: 1.90, 2.14), 2.22 (95% CI: 1.34, 3.67), and 3.85 (95% CI: 2.89, 5.14), respectively.ConclusionPretracheal lymph node metastasis and prelaryngeal lymph node metastasis were significantly associated with an increased likelihood of both ipsilateral lymph node metastasis and contralateral paratracheal lymph node metastasis in papillary thyroid carcinoma. Prelaryngeal lymph node metastasis was positively correlated with the incidence of lateral lymph node metastasis.

Contrast-enhanced ultrasound characteristics of preoperative central cervical lymph node metastasis in papillary thyroid carcinoma

This study evaluated the preoperative diagnostic value of lymph node ultrasonography in distinguishing between benign and malignant central cervical lymph nodes (CCLNs) in patients with papillary thyroid carcinoma (PTC). A total of 176 patients who had PTC with 216 CCLNs (49 benign and 155 malignant) were enrolled in this study and preoperatively imaged by ultrasonography, including conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS). We evaluated the ultrasonography parameters for each lymph node. Binary logistic regression analysis indicated that multifocality of PTC and the absence of Hashimoto’s thyroiditis are independent clinical features related to patients with PTC who also have malignant CCLNs. For preoperative ultrasonography features, heterogeneous enhancement and centripetal perfusion are independent ultrasonographic features to identify malignant and benign CCLNs. This study demonstrated that preoperative CEUS characteristics help to distinguish malignant CCLNs from benign CCLNs.

The Predicting Role of Serum TSGF and sIL-2R for the Lymph Node Metastasis of Papillary Thyroid Carcinoma.

Objective To explore the clinical utility of tumor-specific growth factor (TSGF) and the soluble interleukin-2 (IL-2) receptor (sIL-2R) as immune-related factors for predicting lymph node metastases (LNM) of papillary thyroid carcinoma (PTC). Methods A total of 206 patients with PTC subjected to curative surgery were enrolled. All patients had complete medical records. Serum levels of TSGF were detected using Automatic Biochemistry Analyzer and the serum sIL-2R concentration was detected by enzyme-linked immunosorbent assay (ELISA). Furthermore, we analyzed the relationship between the two indicators and the clinicopathological characteristics and assessed their effect on lymphatic metastasis in patients with PTC by logistic regression analysis. Results Receiver operating characteristic (ROC) analysis revealed that the determined cut-off value of serum TSGF and sIL-2R was 63.35 U/mL and 507 U/mL, respectively. Serum TSGF was associated with focality (χ2 = 4.97, P = 0.026) and lymphatic metastasis (χ2 = 4.154, P = 0.042), while serum sIL-2R was remarkably related to gender (χ2 = 4.464, P = 0.035). Univariate logistic regression analysis indicated that age, tumor size, serum TSGF level, capsule invasion, and nodular goiter were the lymphatic metastasis-related factor of PTC. Multivariate regression analysis revealed that age > 45 years was a protective factor (OR: 0.4, 95% CI: 0.206-0.777, P = 0.007). Conversely, larger tumor size (OR: 4.594, 95% CI: 2.127-9.921, P = 0.000), higher serum TSGF levels (OR: 1.888, 95% CI: 1.009-3.533, P = 0.047), and capsule invasion (OR: 1.939, 95% CI: 1.009-3.726, P = 0.047) were associated with an increased risk of LNM. Conclusion Serum TSGF levels were identified as an independent factor for LNM in patients with PTC.

Radiofrequency Ablation of Recurrent Metastatic Papillary Thyroid Cancer to a Lymph Node

Radiofrequency Ablation of Recurrent Metastatic Papillary Thyroid Cancer to a Lymph Node

Related factor analysis for predicting large-volume central cervical lymph node metastasis in papillary thyroid carcinoma.

The aim of this study was to investigate the factors related to large-volume central cervical lymph node metastasis (LNM) in papillary thyroid carcinoma. A retrospective study of 340 patients with 642 papillary thyroid carcinoma nodules who underwent thyroidectomy in Peking Union Medical College Hospital between 2011 and 2015 was conducted. These nodules were divided into two groups by the number of central cervical lymph node metastases: large‐volume central cervical LNM (>5 metastatic lymph nodes, n = 129) and no central cervical LNM (n = 211). We evaluated the correlations between gender, age, chronic lymphocytic thyroiditis, thyroid ultrasonographic features, and large‐volume central cervical LNM. We found that younger age (≤40 years) (OR = 3.796, 95% CI = 2.842, 5.070), male gender (OR = 4.005, 95% CI = 2.858, 5.61), and ultrasonographic features such as tumor macroaxis size (OR = 2.985, 95% CI = 1.581, 5.633), tumor located in the isthmus (OR = 7.578, 95% CI = 4.863, 11.810), ill-defined margin (OR = 3.008, 95% CI = 1.986, 4.556), microcalcification (OR = 2.155, 95% CI = 1.585, 2.929), and abnormal cervical lymph nodes (OR = 13.753, 95% CI = 9.278, 20.385) were independent risk factors for large-volume central cervical LNM in papillary thyroid carcinoma, while chronic lymphocytic thyroiditis (OR = 0.248, 95% CI = 0.172, 0.358) was a protective factor. Younger age (≤40 years), male sex, and ultrasonographic features such as tumor macroaxis size, tumor located in the isthmus, ill-defined margin, microcalcification, and abnormal cervical lymph nodes were independent risk factors for large-volume central cervical LNM in papillary thyroid carcinoma, while chronic lymphocytic thyroiditis can be considered a protective factor. Our results provide a reference for adjusting clinical treatment approaches.

Metastatic Risk Stratification of 2526 Medullary Thyroid Carcinoma Patients: A Study Based on Surveillance, Epidemiology, and End Results Database.

The risk of distant metastasis in medullary thyroid carcinoma (MTC) has not been well studied. Additional evaluation of MTC metastatic risk can be helpful for improving the quality of medical management. Therefore, we conducted a large population study to develop a method to stratify the risk of metastasis at the initial presentation of MTC patients. We collected 3612 MTC patients from the Surveillance, Epidemiology, and End Results (SEER) database, and included 2526 MTC patients in the study after applying exclusion criteria. We selected the most informative variables from a learning cohort of 2019 patients to obtain 1000 models by repetitive random data splicing into training and regularization cohorts. We selected the optimal model and developed a risk table from that model. Our risk table variables consist of age, gender, tumor size, extrathyroidal extension, and lymph node metastasis. The final model showed good calibration when metastatic risk was < 25% and good performance with areas under the curve (AUCs) of 0.81, 0.84, and 0.84 in the training, regularization, and test cohorts, respectively. We performed K-means clustering analysis on the model's metastatic estimation and determined three risk groups of patients with significant survival differences (p < 0.001). Low-risk patients had 0.88%, 1.3%, and 0.5% while high-risk patients had 19.7%, 15.8%, and 17.8% risk of metastasis in the three cohorts, respectively. The incorporation of our table into the International MTC Grading System (IMTCGS) requires more comprehensive clinicopathological studies.

Nomogram model based on preoperative serum thyroglobulin and clinical characteristics of papillary thyroid carcinoma to predict cervical lymph node metastasis

ObjectivePreoperative evaluation of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) has been one of the serious clinical challenges. The present study aims at understanding the relationship between preoperative serum thyroglobulin (PS-Tg) and LNM and intends to establish nomogram models to predict cervical LNM.MethodsThe data of 1,324 PTC patients were retrospectively collected and randomly divided into training cohort (n = 993) and validation cohort (n = 331). Univariate and multivariate logistic regression analyses were performed to determine the risk factors of central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM). The nomogram models were constructed and further evaluated by 1,000 resampling bootstrap analyses. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) of the nomogram models were carried out for the training, validation, and external validation cohorts.ResultsAnalyses revealed that age, male, maximum tumor size >1 cm, PS-Tg ≥31.650 ng/ml, extrathyroidal extension (ETE), and multifocality were the significant risk factors for CLNM in PTC patients. Similarly, such factors as maximum tumor size >1 cm, PS-Tg ≥30.175 ng/ml, CLNM positive, ETE, and multifocality were significantly related to LLNM. Two nomogram models predicting the risk of CLNM and LLNM were established with a favorable C-index of 0.801 and 0.911, respectively. Both nomogram models demonstrated good calibration and clinical benefits in the training and validation cohorts.ConclusionPS-Tg level is an independent risk factor for both CLNM and LLNM. The nomogram based on PS-Tg and other clinical characteristics are effective for predicting cervical LNM in PTC patients.

Nomograms based on sonographic and clinicopathological characteristics to predict lateral lymph node metastasis in classic papillary thyroid carcinoma.

Lateral lymph node metastasis (LLNM) has been considered a risk factor of recurrence in papillary thyroid cancer (PTC). Preoperative detecting LLNM accurately is difficult. Solitary lateral lymph node metastasis is a special type of LLNM. We aimed to develop nomograms for predicting LLNM and multiple lateral lymph node metastasis (MLLNM). We retrospectively retrieved 528 classic PTC patients that underwent surgery between March 2019 and May 2020. Sonographic and clinicopathological features were collected. Risk factors of LLNM and MLLNM were determined by univariate and multivariate analysis. Nomograms for predicting LLNM and MLLNM were developed. LLNM was independently associated with tumor size, the number of foci, location, margin, central lymph node metastasis, and lymph node ratio. Independent predictors of MLLNM were age, margin, and the number of metastatic lymph nodes in central compartment. By using above variables, we constructed nomograms for predicting LLNM and MLLNM, with area under curves of 0.864 and 0.748, respectively. Through these accurate and easy-to-use nomograms, we can detect the risk of residual LLNM postoperatively for classic PTC patients who did not receive lateral neck dissection and provide an individualized plan for postoperative management of classic PTC patients.