Ultrasound and clinical factors predicting central lymph node metastases in patients with unilateral multifocal papillary thyroid carcinoma

OBJECTIVE

This retrospective study involving a large dataset of unilateral multifocal papillary thyroid carcinoma (UM-PTC) sought to identify factors that predict central lymph node metastases (CLNM) in patients.

METHODS

We identified a cohort of 158 patients who underwent cervical ultrasonography followed by UM-PTC diagnosis based on postoperative pathology. The relationship between CLNM and UM-PTC clinical ultrasound features was evaluated using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to determine the ability of total tumor diameter (TTD) to predict CLNM.

RESULTS

Among the 158 UM-PTC patients, the incidence of CLNM was 29.7% (47/158). Univariate and multivariate analyses revealed that a number of similarity of sonographic features (NSSF) ≥4 (odds ratio [OR] = 11.335, 95% confidence interval [CI]: 3.95-32.50, p = 0.000), microcalcifications (OR = 3.54, 95% CI: 1.30-9.70, p = 0.014), a TTD of ≥2 cm (OR = 4.48, 95% CI: 1.62-12.34, p = 0.004), number of nodules ≥3 (OR = 13.17, 95% CI: 3.24-53.52, p = 0.000), and Lateral cervical lymph node metastasis (LLNM) (OR = 5.57, 95% CI: 1.59-19.48, p = 0.007) were independently associated with CLNM in UM-PTC. ROC curve analysis revealed that the TTD cut-off of 1.795 cm had a sensitivity of 0.723 and a specificity of 0.676 for predicting CLNM.

CONCLUSIONS

Patients with UM-PTC are at high risk of CLNM. NSSF ≥4, microcalcifications, TTD of ≥2 cm, LLNM, and a number of nodules ≥3 were independently associated with CLNM. Our data show that ultrasound may guide surgical decisions in the treatment of UM-PTC.

Nomogram model based on preoperative clinical characteristics of unilateral papillary thyroid carcinoma to predict contralateral medium-volume central lymph node metastasis

Objectives

To explore the preoperative high-risk clinical factors for contralateral medium-volume central lymph node metastasis (conMVCLNM) in unilateral papillary thyroid carcinoma (uPTC) and the indications for dissection of contralateral central lymph nodes (conCLN).

Methods

Clinical and pathological data of 204 uPTC patients who underwent thyroid surgery at the Hangzhou First People's Hospital from September 2010 to October 2022 were collected. Univariate and multivariate logistic regression analyses were conducted to determine the independent risk factors for contralateral central lymph node metastasis (conCLNM) and conMVCLNM in uPTC patients based on the preoperative clinical data. Predictive models for conCLNM and conMVCLNM were constructed using logistic regression analyses and validated using receiver operating characteristic (ROC) curves, concordance index (C-index), calibration curves, and decision curve analysis (DCA).

Results

Univariate and multivariate logistic regression analyses showed that gender (P < 0.001), age (P < 0.001), tumor diameter (P < 0.001), and multifocality (P = 0.008) were independent risk factors for conCLNM in uPTC patients. Gender(P= 0.026), age (P = 0.010), platelet-to-lymphocyte ratio (PLR) (P =0.003), and tumor diameter (P = 0.036) were independent risk factors for conMVCLNM in uPTC patients. A predictive model was established to assess the risk of conCLNM and conMVCLNM, with ROC curve areas of 0.836 and 0.845, respectively. The C-index, the calibration curve, and DCA demonstrated that the model had good diagnostic value.

Conclusion

Gender, age, tumor diameter, and multifocality are high-risk factors for conCLNM in uPTC patients. Gender, age, tumor diameter, and PLR are high-risk factors for conMVCLNM in uPTC patients, and preventive conCLN dissection should be performed.

Gene mutations as predictors of central lymph mode metastasis in cN0 PTC: A meta-analysis

Gene mutations could predict the tumor progression and prognosis, which are us to predict CLNM in patients with cN0 PTC, however, these results are not consistent. This meta-analysis tried to identify gene mutations which could predict CLNM in patients with cN0 PTC. A systematic search was performed for identifying relevant literature published prior to July 2023 in three search engines: PubMed, EMBASE and Web of Science. Studies that investigated the gene mutations for CLNM in patients with cN0 PTC were included in our meta-analysis. Sixteen studies, including 6095 cN0 PTC with BRAF mutations were include in our meta-analysis. The prevalence of CLNM in cN0 PTC ranged from 13.7% to 50.6%. The pooled analysis demonstrated that BRAFV600E mutation is significantly associated with CLNM (OR = 2.01, 95% CI: 1.55-2.60, p < 0.001) in PTC and PTMC (OR = 1.70, 95% CI: 0.51-1.81, p < 0.001). Whereas, cN0 PTC with TERT (OR = 1.94, 95% CI: 0.51-7.36, p = 0.33) and KRAS (OR = 0.57, 95% CI: 0.51-1.81, p = 0.34) mutations might not contribute to predict CLNM. Our analysis identified that BRAF mutation was a predictive factor for cN0 PTC, as well as for cN0 PTMC, which could be useful for clinician to accurately choose prophylactic CLND and better manage cN0 PTC.

A nomogram based on multimodal ultrasound and clinical features for the prediction of central lymph node metastasis in unifocal papillary thyroid carcinoma

OBJECTIVES

To build a predictive model for central lymph node metastasis (CLNM) in unifocal papillary thyroid carcinoma (UPTC) using a combination of clinical features and multimodal ultrasound (MUS).

METHODS

This retrospective study, included 390 UPTC patients who underwent MUS between January 2017 and October 2022 and were divided into a training cohort (n = 300) and a validation cohort (n = 90) based on a cut-off date of June 2022. Independent indicators for constructing the predictive nomogram models were identified using multivariate regression analysis. The diagnostic yield of the 3 predictive models was also assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

Both clinical factors (age, diameter) and MUS findings (microcalcification, virtual touch imaging score, maximal value of virtual touch tissue imaging and quantification) were significantly associated with the presence of CLNM in the training cohort (all P < .05). A predictive model (MUS + Clin), incorporating both clinical and MUS characteristics, demonstrated favourable diagnostic accuracy in both the training cohort (AUC = 0.80) and the validation cohort (AUC = 0.77). The MUS + Clin model exhibited superior predictive performance in terms of AUCs over the other models (training cohort 0.80 vs 0.72, validation cohort 0.77 vs 0.65, P < .01). In the validation cohort, the MUS + Clin model exhibited higher sensitivity compared to the CLNM model for ultrasound diagnosis (81.2% vs 21.6%, P < .001), while maintaining comparable specificity to the Clin model alone (62.3% vs 47.2%, P = .06). The MUS + Clin model demonstrated good calibration and clinical utility across both cohorts.

CONCLUSION

Our nomogram combining non-invasive features, including MUS and clinical characteristics, could be a reliable preoperative tool to predict CLNM treatment of UPTC.

ADVANCES IN KNOWLEDGE

Our study established a nomogram based on MUS and clinical features for predicting CLNM in UPTC, facilitating informed preoperative clinical management and diagnosis.

Prospective application of a prediction model for lateral lymph node metastasis in papillary thyroid cancer patients with central lymph node metastasis

Objective

This study aimed to develop and apply a prediction model to estimate the probability of lateral lymph node metastasis (LLNM) in patients with cN0 unilateral papillary thyroid carcinoma (PTC) with central lymph node metastasis (CLNM).

Setting

All study data were collected from a single tertiary hospital.

Methods

Univariable and multivariable logistic regression analyses were used to explore independent predictors of LLNM in the derivation and internal validation cohorts, which were used to construct and validate a nomogram. Another 96 patients were included prospectively to evaluate the efficacy of this nomogram.

Results

Maximum tumor diameter greater than 1.0 cm (OR, 2.712; 95% CI, 1.412-5.210), multifocality (OR, 2.758; 95% CI, 1.120-6.789), the number of CLNM ≥3 (OR, 2.579; 95% CI, 1.315-5.789), CLNM ratio ≥0.297 (OR, 2.905; 95% CI, 1.396-6.043), and tumors located in the upper portion (OR 2.846, 95% CI 1.151-7.039) were independent predictors associated with LLNM. The prediction model showed excellent discrimination with an AUC of 0.731 (95% CI, 0.635-0.827). Novel risk stratification for LLNM was constructed based on this nomogram. In the prospective cohort, we stratified these patients into three risk subgroups: low-, moderate-, and high-risk subgroups and we found that the probability of LLNM was positively correlated with the total points from the nomogram.

Conclusion

This nomogram was applied in prospective clinical practice and distinguished PTC patients with a genuinely high risk of LLNM. Surgeons can use our nomogram to tailor the surgical plan and to credibly determine further postoperative therapy.

Prediction of papillary thyroid metastases to the central compartment: proposal of a model taking into consideration other thyroid conditions

Objective

To construct risk prediction models for cervical lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) under different thyroid disease backgrounds and to analyze and compare risk factors among different groups.

Methods

This retrospective study included 518 patients with PTC that was pathologically confirmed post-operatively from January 2021 to November 2021. Demographic, ultrasound and pathological data were recorded. Univariate and multivariate logistic regression analyses were performed to identify factors associated with CLNM in the whole patient cohort and in patients grouped according to diagnoses of Hashimoto's thyroiditis (HT), nodular goiter (NG), and no background disease. Prediction models were constructed for each group, and their performances were compared.

Results

Analysis of the whole PTC patient cohort identified NG as independently associated with CLNM. The independent risk factors for patients with no background disease were the maximum thyroid nodule diameter and American College of Radiology Thyroid Imaging Reporting & Data System score; those for patients with HT were the maximum thyroid nodule diameter, ACR TI-RADS score, and multifocality; and those for patients with NG were the maximum thyroid nodule diameter, ACR TI-RADS score, multifocality and gender.

Conclusion

Background thyroid disease impacts CLNM in PTC patients, and risk factors for CLNM vary among PTC patients with different background diseases. Ultrasound is useful for diagnosing background thyroid disease, which can inform treatment planning. Different prediction models are recommended for PTC cases with different thyroid diseases.

Risk factors for central lymph node metastasis in patients with papillary thyroid carcinoma: a retrospective study

Introduction

Thyroid cancer is the most prevalent endocrine malignancy, with its global incidence increasing annually in recent years. Papillary carcinoma is the most common subtype, frequently accompanied by cervical lymph node metastasis early on. Central lymph node metastasis (CLNM) is particularly the common metastasis form in this subtype, and the presence of lymph node metastasis correlates strongly with tumor recurrence. However, effective preoperative assessment methods for CLNM in patients with papillary thyroid carcinoma (PTC) remain lacking.

Methods

Data from 400 patients diagnosed with PTC between January 1, 2018, and January 1, 2022, at the Shandong Provincial Hospital were retrospectively analyzed. This data included clinicopathological information of the patients, such as thyroid function, BRAF V600E mutation, whether complicated with Hashimoto's thyroiditis, and the presence of capsular invasion. Univariate and multivariate logistic regression analyses were performed to assess the risk factors associated with cervical CLNM in patients with PTC. Subsequently, a clinical prediction model was constructed, and prognostic risk factors were identified based on univariate and multivariate Cox regression analyses.

Results

Univariate and multivariate analyses identified that age >45 years (P=0.014), body mass index ≥25 (P=0.008), tumor size ≥1 cm (P=0.001), capsular invasion (P=0.001), and the presence of BRAF V600E mutation (P<0.001) were significantly associated with an increased risk of CLNM. Integrating these factors into the nomogram revealed an area-under-the-curve of 0.791 (95% confidence interval 0.735-0.846) and 0.765 (95% confidence interval: 0.677-0.852) for the training and validation sets, respectively, indicating strong discriminative abilities. Subgroup analysis further confirmed that patients with papillary thyroid microcarcinoma and BRAF V600E mutations who underwent therapeutic central compartment neck dissection had significantly better 3-year disease-free survival than those who had prophylactic central compartment neck dissection (P<0.001).

Conclusion

The study revealed that age >45 years, body mass index ≥25, tumor size ≥1 cm, BRAF V600E mutation, and capsular invasion are the related risk factors for CLNM in patients with PTC. For patients with clinically nodal-negative (cN0) papillary thyroid microcarcinoma, accurately identifying the BRAF V600E mutation is essential for guiding the central lymph node dissection approach and subsequent treatments.

Deep learning prediction model for central lymph node metastasis in papillary thyroid microcarcinoma based on cytology

Controversy exists regarding whether patients with low-risk papillary thyroid microcarcinoma (PTMC) should undergo surgery or active surveillance; the inaccuracy of the preoperative clinical lymph node status assessment is one of the primary factors contributing to the controversy. It is imperative to accurately predict the lymph node status of PTMC before surgery. We selected 208 preoperative fine-needle aspiration (FNA) liquid-based preparations of PTMC as our research objects; all of these instances underwent lymph node dissection and, aside from lymph node status, were consistent with low-risk PTMC. We separated them into two groups according to whether the postoperative pathology showed central lymph node metastases. The deep learning model was expected to predict, based on the preoperative thyroid FNA liquid-based preparation, whether PTMC was accompanied by central lymph node metastases. Our deep learning model attained a sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and accuracy of 78.9% (15/19), 73.9% (17/23), 71.4% (15/21), 81.0% (17/21), and 76.2% (32/42), respectively. The area under the receiver operating characteristic curve (value was 0.8503. The predictive performance of the deep learning model was superior to that of the traditional clinical evaluation, and further analysis revealed the cell morphologies that played key roles in model prediction. Our study suggests that the deep learning model based on preoperative thyroid FNA liquid-based preparation is a reliable strategy for predicting central lymph node metastases in thyroid micropapillary carcinoma, and its performance surpasses that of traditional clinical examination.

Factors of Central Lymph Node Metastasis in Papillary Thyroid Cancer Based on C-TIRADS Analysis

To study risk factors for central lymph node metastasis (CLNM) in papillary thyroid cancer (PTC) using the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS). We retrospectively analysed patients who underwent PTC surgery and central lymph node dissection at First People's Hospital of Foshan City. The clinical and ultrasonic data of the patients from 1150 cases were analysed by multivariate regression to evaluate the correlation between grayscale ultrasound (US) features, C-TIRADS score, and the classification of thyroid nodules and CLNM of PTCs. The C-TIRADS score was 3.0±1.0 in the CLNM group, which was higher than that in the non-CLNM group (p<0.001). Sex (male) (OR=1.586, 95% CI 1.232-2.042, p<0.001), age (≤45 years) (OR=1.508, 95% CI 1.184-1.919, p=0.001), location of nodes (lower pole) (OR=2.193, 95% CI 1.519-3.166, p<0.001), number (multifocal) (OR=2.204, 95% CI 1.227-2.378, p<0.001), microcalcification (OR=1.610, 95% CI 2.225-4.434, p=0.002), extrathyroidal extension (OR=2.204, 95% CI 1.941-3.843, p<0.001), maximum diameter of nodule (≥20 mm) (OR=3.211, 95% CI 2.337-4.411, p<0.001), and C-TIRADS score (OR=1.356, 95% CI 1.204-1.527, p<0.001) were PTC in independent risk factors for CLNM. The C-TIRADS score of PTC combined with the location, number, size, and ultrasound features of the lesion and the patient's sex and age are important in predicting whether they present with CLNM and provide a reference basis for the clinical formulation of a reasonable surgical treatment plan.

Development and validation of a dynamic nomogram based on conventional ultrasound and contrast-enhanced ultrasound for stratifying the risk of central lymph node metastasis in papillary thyroid carcinoma preoperatively

Purpose

The aim of this study was to develop and validate a dynamic nomogram by combining conventional ultrasound (US) and contrast-enhanced US (CEUS) to preoperatively evaluate the probability of central lymph node metastases (CLNMs) for patients with papillary thyroid carcinoma (PTC).

Methods

A total of 216 patients with PTC confirmed pathologically were included in this retrospective and prospective study, and they were divided into the training and validation cohorts, respectively. Each cohort was divided into the CLNM (+) and CLNM (-) groups. The least absolute shrinkage and selection operator (LASSO) regression method was applied to select the most useful predictive features for CLNM in the training cohort, and these features were incorporated into a multivariate logistic regression analysis to develop the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were assessed in the training and validation cohorts.

Results

In the training and validation cohorts, the dynamic nomogram (https://clnmpredictionmodel.shinyapps.io/PTCCLNM/) had an area under the receiver operator characteristic curve (AUC) of 0.844 (95% CI, 0.755-0.905) and 0.827 (95% CI, 0.747-0.906), respectively. The Hosmer-Lemeshow test and calibration curve showed that the nomogram had good calibration (p = 0.385, p = 0.285). Decision curve analysis (DCA) showed that the nomogram has more predictive value of CLNM than US or CEUS features alone in a wide range of high-risk threshold. A Nomo-score of 0.428 as the cutoff value had a good performance to stratify high-risk and low-risk groups.

Conclusion

A dynamic nomogram combining US and CEUS features can be applied to risk stratification of CLNM in patients with PTC in clinical practice.

Risk factors associated with lymph node metastasis in patients with small papillary thyroid carcinomas

OBJECTIVE

This study aims to analyze risk factors for central lymph node metastasis (CLNM) in patients with small papillary thyroid carcinoma (PTC).

METHODS

The clinicopathologic data of 375 patients with small PTC admitted to the Affiliated Hospital of Inner Mongolia Medical University from January 2017 to December 2020 were analyzed retrospectively. The patients were divided into two groups, namely, CLNM (n = 177) and non-CLNM (n = 198) groups. Relevant data from the two groups were analyzed using the chi-square test, logistic regression analysis, and the receiver operating characteristic (ROC) curve.

RESULTS

The CLNM rate of the 375 patients with small PTC was 47.2%. The chi-square test revealed that CLNM status was correlated with a patient's gender and age as well as tumor size, number of lesions, and invasion of the thyroid capsule (P < 0.05), but not with BRAF gene mutation, Hashimoto's thyroiditis (HT), or nodular goiter. Multivariate analysis indicated significant differences in gender, maximum tumor diameter, multifocality, and thyroid adventitial infiltration between the two groups (all P < 0.05) but no significant difference between the two groups in regard to HT and nodular goiter. The ROC curve suggested that age ≤ 26.5 years and maximum tumor diameter ≥ 0.75 cm were thresholds for increased risk of CLNM.

CONCLUSIONS

Lymph node metastasis in the central area of small PTC is associated with multiple factors. Careful examination, analysis, and evaluation of these factors can help in developing accurate individualized treatment strategies.

Association between papillary thyroid carcinoma and lymphocytic thyroiditis: A retrospective study

The aim of the present study was to evaluate the association between coexisting lymphocytic thyroiditis (LT) and the clinicopathological features of papillary thyroid carcinoma (PTC). The records of 458 patients with PTC who underwent a total thyroidectomy and lymph node dissection in Sir Run Run Shaw Hospital (Hangzhou, China) were analyzed. In accordance with the histopathology of thyroid parenchyma, the cases were divided into three groups, including Hashimoto's thyroiditis (HT), non-Hashimoto's type LT (NHLT) and no LT. Based on the histopathology, data on age, sex, maximum diameter of tumor, multifocality, extrathyroidal extension, metastatic lymph node size, extranodal extension and tumor grades in the different groups were analyzed and compared. The prevalence of coexisting LT was 29.0% (133/458), of which 7.6% (35/458) was HT and 21.4% (98/458) was NHLT. PTC concomitant with LT was significantly associated with female patients (95.5 vs. 70.2%; P<0.001), a lower rate of extrathyroidal extension and/or capsular invasion (25.6 vs. 39.7%; P=0.004), central lymph node metastasis (CLNM) ratio (10.71 vs. 17.37; P=0.014), higher number of dissected central lymph nodes (16.83 vs. 11.7; P<0.001), larger metastatic lymph nodes (0.66 vs. 0.46 cm; P<0.001), higher occurrence of multifocality (61.7 vs. 50.5%; P=0.029) and earlier pT stage (57.9 vs. 38.8%; P<0.001), regardless of the combined or separate consideration of HT and NHLT. Besides, LT was associated with multifocality [odds ratio (OR), 1.578; 95% confidence interval (CI), 1.046-2.382; P=0.030]. Furthermore, in patients with PTC, CLNM had a significant association with the male sex (OR, 2.000; 95% CI, 1.216-3.288; P=0.006), an age of <45 years (OR, 0.592; 95% CI, 0.398-0.879; P=0.009) and a tumor size of >1 cm (OR, 3.913; 95% CI, 2.431-5.734; P<0.001). In conclusion, patients with PTC and LT showed a greater female preponderance, multifocality, a lower extrathyroidal extension and a lower CLNM ratio. LT was associated with an increased risk of multifocality in PTC.

Correlation between Sonographic Features and Central Neck Lymph Node Metastasis in Solitary Solid Papillary Thyroid Microcarcinoma with a Taller-Than-Wide Shape

Purpose: This study aimed to investigate the correlation between sonographic features and central neck lymph node metastasis (CNLM) in solitary solid papillary thyroid microcarcinoma (PTMC) with a taller-than-wide shape. Methods: A total of 103 patients with solitary solid PTMC with a taller-than-wide shape on ultrasonography who underwent surgical histopathological examination were retrospectively selected. Based on the presence or absence of CNLM, patients with PTMC were divided into a CNLM (n = 45) or nonmetastatic (n = 58) group, respectively. Clinical findings and ultrasonographic features, including a suspicious thyroid capsule involvement sign (STCS, which is defined as PTMC abutment or a disrupted thyroid capsule), were compared between the two groups. Additionally, postoperative ultrasonography was performed to assess patients during the follow-up period. Results: Significant differences were observed in sex and the presence of STCS between the two groups (p < 0.05). The specificity and accuracy of the male sex for predicting CNLM were 86.21% (50/58 patients) and 64.08% (66/103 patients), respectively. The sensitivity, specificity, positive predictive value (PPV), and accuracy of STCS for predicting CNLM were 82.22% (37/45 patients), 70.69% (41/58 patients), 68.52% (37/54 patients), and 75.73% (78/103 patients), respectively. The specificity, PPV, and accuracy of the combination of sex and STCS for predicting CNLM were 96.55% (56/58 patients), 87.50% (14/16 patients), and 67.96% (70/103 patients), respectively. A total of 89 (86.4%) patients were followed up for a median of 4.6 years, with no patient having recurrence as detected on ultrasonography and pathological examination. Conclusions: STCS is a useful ultrasonographic feature for predicting CNLM in patients with solitary solid PTMC with a taller-than-wide shape, especially in male patients. Solitary solid PTMC with a taller-than-wide shape may have a good prognosis.

Nomograms for Prediction of High-Volume Lymph Node Metastasis in Papillary Thyroid Carcinoma Patients

OBJECTIVE

The coexistence rate between chronic lymphocytic thyroiditis (CLT) and papillary thyroid carcinoma (PTC) is quite high. Whether CLT influences metastatic lymph nodes remains uncertain. High-volume lymph node metastasis is recommended as an unfavorable pathological feature. We aimed to investigate risk factors for high-volume central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) in PTC patients.

STUDY DESIGN

Retrospective cohort study.

SETTING

Changzhou First People's Hospital.

METHODS

Clinicopathological characteristics of 1094 PTC patients who underwent surgery in our center from January 2019 to November 2021 were analyzed.

RESULTS

The number of metastatic lymph nodes in the central compartment and lateral compartment were lower in the CLT group. We demonstrated that age, BRAF V600E, shape, and the number of foci were risk factors for high-volume CLNM in patients with CLT. For patients without CLT, sex, age, tumor size, number of foci, and margin were risk factors for high-volume CLNM. Tumor size, number of foci, location, and CLNM were all risk factors for high-volume LLNM in patients with or without CLT. Body mass index was only associated with high-volume LLNM in CLT patients. All the above factors were incorporated into nomograms, which showed perfect discriminative ability.

CONCLUSION

Separate predictive systems should be used for CLT and non-CLT patients for a more accurate clinical assessment of lymph node status. Our nomograms of predicting high-volume CLNM and LLNM could facilitate risk-stratified management of PTC recurrence and treatment decisions.

Combined Conventional Ultrasound and Contrast-Enhanced Computed Tomography for Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma

OBJECTIVES

This study aimed to evaluate conventional ultrasound (US) combined with contrast-enhanced computed tomography (CT) of the neck to predict central lymph node metastasis (CLNM) in clinical lymph-negative patients with papillary thyroid carcinoma (PTC), establish a simple preoperative risk-scoring model, and validate its effectiveness in a two-center dataset.

METHODS

A total of 423 patients with PTC preoperatively evaluated by US and contrast-enhanced CT were included in the modeling group, and 102 patients from two hospitals were enrolled in the validation group. Independent predictive factors were determined using multivariate logistic regression analysis. Diagnostic performance was evaluated using receiver operating characteristic curve analysis.

RESULTS

The independent predictive factors for CLNM were age ≤45 years (odds ratio [OR] = 3.950), nodule presence in the non-upper pole (OR = 2.385), nodule size >12.5 mm (OR = 2.130), Thyroid Imaging Reporting and Data System score ≥9 (OR = 2.857), normalized enhancement CT value ≥0.75 (OR = 3.132), central enhancement (OR = 0.222), and capsular invasion (OR = 3.478). The area under the curve (AUC) of the model was 0.790 (95% confidence interval [CI]: 0.747-0.834), and the sensitivity and specificity were 70.4% and 73.9%, respectively. The AUC in the validation group was 0.827 (95% CI: 0.747-0.907), and the sensitivity and specificity were 88.9% and 63.2%, respectively.

CONCLUSIONS

We found conventional US combined with contrast-enhanced CT of the neck to be useful in predicting CLNM preoperatively and established a simple risk-scoring model that might help surgeons with appropriate surgical plans and prognostic evaluation.

Nomogram for predicting skip metastasis in cN0 papillary thyroid cancer patients at increased risk of lymph node metastasis

BACKGROUND

Skip lymph node metastasis (SLNM) refers to lateral lymph node metastasis (LLNM) without involving central lymph node (CLN). Some microscopic nodal positivity may be difficult to detect before surgery due to atypical imaging characteristics. These patients are misdiagnosed as having clinically node-negative (cN0) papillary thyroid cancer (PTC) even after central lymph node dissection, leading to a high risk of developing LNM after surgery. Current prediction models have limited clinical utility, as they are only applicable to predict SLNM from clinically node-positive (cN+) PTC, not cN0 PTC, and this has little impact on treatment strategies.

OBJECTIVES

This study aimed to establish a nomogram for preoperatively assessing the likelihood of SLNM in cN0 PTC patients with increased risk of LNM, thus optimizing their therapeutic options.

MATERIAL AND METHODS

The records of 780 PTC patients undergoing thyroidectomy along with bilateral central lymph node dissection were retrospectively reviewed. The cN0 patients with postoperative LLNM (occult SLNM) and cN+ patients without central lymph node metastasis (CLNM) (typical SLNM) were included in the SLNM group (n = 82). The CLNM-negative cN0 patients without postoperative LLNM were assigned to the non-SLNM group (n = 698). The independent correlates of SLNM constituted the nomogram for determining the likelihood of SLNM in high-risk cN0 PTC patients.

RESULTS

The independent correlates of SLNM were age (hazard ratio (HR) = 1.016), tumor location (HR = 1.801), tumor size (HR = 1.528), and capsular invasion (HR = 2.941). They served as components in the development of the nomogram. This model was verified to present acceptable discrimination. It showed good calibration and a decent net benefit when the predicted probability was <60%.

CONCLUSIONS

We developed a nomogram incorporating preoperative clinical data to predict the probability of SLNM development in high-risk cN0 PTC patients, which contributed to their optimized treatment options.

Nomogram based on preoperative conventional ultrasound and shear wave velocity for predicting central lymph node metastasis in papillary thyroid carcinoma

OBJECTIVE

To establish a nomogram for predicting cervical lymph node metastasis (CLNM) based on the preoperative conventional ultrasound (US) and shear wave velocity (SWV) features of papillary thyroid carcinoma (PTC).

METHODS

A total of 101 patients with pathologically confirmed thyroid nodules were enrolled. These patients were divided into the CLNM-positive (n = 40) and CLNM-negative groups (n = 61). All patients underwent the preoperative conventional US and shear wave elastography (SWE) evaluation, and the US parameters and SWV data were collected. The association between SWV ratio and CLNM was compared to assess the diagnostic efficacy of SWV ratio alone as opposed to SWV ratio in combination with the conventional US for predicting CLNM.

RESULTS

There were significant differences in shape, microcalcification, capsule contact, SWV mean, and SWV ratio between the CLNM-positive and CLNM-negative groups (P < 0.05). Logistic regression analysis showed that taller-than-wide shape, microcalcification, capsule contact, and SWV ratio > 1.3 were risk factors for CLNM; Logistic(P)=-6.93 + 1.647 * (microcalcification)+1.138 * (taller-than-wide-shape)+1.612 * (capsule contact)+2.933 * (SWV ratio > 1.3). The area under the curve (AUC) of the receiver operating characteristic (ROC) of the model for CLNM prediction was 0.87, with 81.19% accuracy, 77.5% sensitivity, and 85.25% specificity.

CONCLUSION

The nomogram based on conventional US imaging in combination with SWV ratio has the potential for preoperative CLNM risk assessment. This nomogram serves as a useful clinical tool for active surveillance and treatment decisions.

An integrated nomogram combining deep learning, clinical characteristics and ultrasound features for predicting central lymph node metastasis in papillary thyroid cancer: A multicenter study

OBJECTIVE

Central lymph node metastasis (CLNM) is a predictor of poor prognosis for papillary thyroid carcinoma (PTC) patients. The options for surgeon operation or follow-up depend on the state of CLNM while accurate prediction is a challenge for radiologists. The present study aimed to develop and validate an effective preoperative nomogram combining deep learning, clinical characteristics and ultrasound features for predicting CLNM.

MATERIALS AND METHODS

In this study, 3359 PTC patients who had undergone total thyroidectomy or thyroid lobectomy from two medical centers were enrolled. The patients were divided into three datasets for training, internal validation and external validation. We constructed an integrated nomogram combining deep learning, clinical characteristics and ultrasound features using multivariable logistic regression to predict CLNM in PTC patients.

RESULTS

Multivariate analysis indicated that the AI model-predicted value, multiple, position, microcalcification, abutment/perimeter ratio and US-reported LN status were independent risk factors predicting CLNM. The area under the curve (AUC) for the nomogram to predict CLNM was 0.812 (95% CI, 0.794-0.830) in the training cohort, 0.809 (95% CI, 0.780-0.837) in the internal validation cohort and 0.829(95%CI, 0.785-0.872) in the external validation cohort. Based on the analysis of the decision curve, our integrated nomogram was superior to other models in terms of clinical predictive ability.

CONCLUSION

Our proposed thyroid cancer lymph node metastasis nomogram shows favorable predictive value to assist surgeons in making appropriate surgical decisions in PTC treatment.

Central and lateral neck involvement in papillary thyroid carcinoma patients with or without thyroid capsular invasion: A multi-center analysis

PURPOSES

To quantitatively predict the probability of cervical lymph node metastasis for papillary thyroid carcinomas (PTC) patients with or without thyroid capsular invasion (TCI), to guide the decision-making of management strategies for neck regions.

METHODS

A total of 998 PTC patients from three medical centers were retrospectively analyzed.

RESULTS

Patients with positive TCI (TCI group) exhibited higher risks for both CLNM and LLNM than those with negative TCI (no-TCI group). Patients receiving lateral lymph node dissection showed significantly higher incidence of relatively severe postoperative complications. For no-TCI group, factors including age less than 55 years old, male, the presence of bilateral disease and multifocality, and maximum tumor diameter (MTD)>=0.5cm were confirmed to be independent risk factors for CLNM, while the presence of bilateral disease and ipsilateral nodular goiter (iNG), and maximum positive CLN diameter (MCLND)>1.0cm independent factors for LLNM. Independent risk factors of LLNM for patients within the TCI group included MCLND>1.0cm, positive CLN number>=3, and the presence of iNG. Predictive models of CLNM and LLNM were established based on the aforementioned risk factors for patients within no-TCI and TCI groups. A meticulous and comprehensive risk stratification flow chart was established for a more accurate evaluation of central neck involvement including both CLNM and LLNM risk in PTC patients.

CONCLUSIONS

A meticulous and comprehensive stratification flow chart for PTC patients for quantitatively evaluating both CLNM and LLNM was constructed.

A clinical and molecular pathology prediction model for central lymph node metastasis in cN0 papillary thyroid microcarcinoma

BACKGROUND

The frequency of thyroid cancer has rapidly increased in recent years globally. Thus, more papillary thyroid microcarcinoma (PTMC) patients are being diagnosed, including clinical lymph node-negative (cN0) patients. Our study attempted to develop a prediction model for assessing the probability of central lymph node metastasis (CLNM) in cN0 PTMC patients.

METHODS

A total of 595 patients from the Affiliated Hospital of Qingdao University (training cohort: 456 patients) and the Affiliated Hospital of Jining Medical University (verification cohort: 139 patients) who underwent thyroid surgery between January 2020 and May 2022 were enrolled in this study. Their clinical and molecular pathology data were analyzed with multivariate logistic regression to identify independent factors, and then we established a prediction model to assess the risk of CLNM in cN0 PTMC patients.

RESULTS

Multivariate logistic regression analysis revealed that sex, Hashimoto's thyroiditis (HT), tumor size, extrathyroidal extension, TERT promoter mutations and NRAS mutation were independent factors of CLNM. The prediction model demonstrated good discrimination ability (C-index: 0.757 and 0.753 in the derivation and validation cohorts, respectively). The calibration curve of the model was near the optimum diagonal line, and decision curve analysis (DCA) showed a noticeably better benefit.

CONCLUSION

CLNM in cN0 PTMC patients is associated with male sex, tumor size, extrathyroidal extension, HT, TERT promoter mutations and NRAS mutation. The prediction model exhibits good discrimination, calibration and clinical usefulness. This model will help to assess CLNM risk and make clinical decisions in cN0 PTMC patients.

Risk factors of cervical lymph node metastasis in multifocal papillary thyroid cancer

Introduction

Identifying risk variables for cervical lymph node metastases in multifocality papillary thyroid cancer (MPTC) could assist surgeons in determining whether cervical lymph node dissection would be an appropriate surgical option.

Methods

A retrospective cohort of 2006 patients with papillary thyroid cancer were selected. MPTC (N = 460) was defined as the presence of two or more foci of PTC. The risk factors for central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) in MPTC were investigated by univariate and multivariate analyses, including the following items: age at diagnosis, gender, Hashimoto's thyroiditis, extrathyroidal extension (ETE), maximal axial diameter (MAD) and the sum of axial diameters (SAD) of tumor. In addition, CLNM was used to evaluate LLNM.

Results

The incidence of CLNM and LLNM was 44.57% and 17.17%, respectively. The multivariate analysis demonstrated that gender, extrathyroidal extension (ETE), age, maximal axial diameter (MAD), and the sum of axial diameters (SAD) were related to increased risk for CLNM in MPTC (p < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) for age at diagnosis of CLNM was 0.647, the cut-off value was 50 years old. Additionally, by multivariate analysis, CLNM, ETE, MAD, and SAD were independent risk factors for LLNM in MPTC (p < 0.05). ROC curve analysis demonstrates that AUC for MAD and SAD diagnosis of LLNM were 0.639 and 0.757, and the cut-off values were 16 and 26 mm, respectively.

Conclusions

MPTC patients who have risk factors for CLNM were advised to perform prophylactic central lymph node dissection (CLND). Additionally, the presence of risk factors for LLNM should be individually evaluated and analyzed for the necessity of lateral lymph node dissection.

Lateral Involvement in Different Sized Papillary Thyroid Carcinomas Patients with Central Lymph Node Metastasis: A Multi-Center Analysis

Objective: To quantitatively predict the probability of lateral lymph node metastasis (LLNM) for papillary thyroid carcinomas (PTC) patients with central lymph node metastasis (CLNM) in order to guide postoperative adjuvant treatment. Methods: Five hundred and three PTC patients with CLNM from three medical centers were retrospectively analyzed. Results: The LLNM rate for all patients was 23.9% (120 in 503), with 15.5% (45 in 291) and 35.4% (75 in 212) for patients with papillary thyroid microcarcinoma (PTMC) and large papillary thyroid carcinoma (LPTC), respectively. Patients with no fewer than five positive central lymph nodes (CLN) exhibited a higher risk of LLNM. For patients with fewer than five positive CLN, a maximum diameter of positive CLN > 0.5 cm and the presence of ipsilateral nodular goiter were identified as independent risk factors of LLNM for papillary thyroid microcarcinoma (PTMC) patients. The independent risk factors of LLNM for large papillary thyroid carcinoma (LPTC) patients included a tumor located in the upper portion of thyroid, maximum tumor diameter ≥ 2.0 cm, maximum diameter of positive CLN > 0.5 cm, and the presence of thyroid capsular invasion. Predictive nomograms were established based on these risk factors for PTMC and LPTC patients, respectively. The accuracy and validity of our newly built models were verified by C-index and calibration curves. PTMC and LPTC patients with fewer than five positive CLN were each stratified into three subgroups based on their nomogram risk scores, and a detailed risk stratification flow chart was established for a more accurate evaluation of LLNM risk in PTC patients. Conclusions: A detailed stratification flow chart for PTC patients with CLNM to quantitatively assess LLNM risk was established, which may aid in clinical decision-making for those patients.

Cervical Lymph Node Metastasis Differences in Patients with Unilateral or Bilateral Papillary Thyroid Microcarcinoma: A Multi-Center Analysis

Purposes: To quantitatively predict the risk of neck lymph node metastasis for unilateral and bilateral papillary thyroid microcarcinomas (PTMC) that may guide individual treatment strategies for the neck region. Methods: A total of 717 PTMC patients from three medical centers were enrolled for analysis. Results: Bilateral PTMCs were demonstrated to be more aggressive with a much higher cervical lymph node metastasis rate including for both central (CLNM) and lateral lymph node metastasis (LLNM) when being compared to unilateral PTMCs. In unilateral PTMC, five (age < 55 years old, male, maximum tumor diameter (MTD) ≥ 0.5 cm, and the presence of thyroid capsular invasion (TCI) and multifocality) and three (maximum diameter of positive CLN (MDCLN) > 0.5 cm, the presence of multifocality and nodular goiter, iNG) factors were identified as independent risk factors for CLNM and LLNM, respectively. In bilateral PTMC, three (age < 55 and presence of TCI and multifocality in at least one side of thyroid lobe) and two (MDCLN > 0.5 cm and presence of nodular goiter (iNG)) factors were identified as independent factors for CLNM and LLNM, respectively. Predictive models of CLNM and LLNM for patients with unilateral disease and of CLNM for patients with the bilateral disease were established based on the described risk factors. Bilateral patients with positive CLNM were also stratified into different subgroups according to the presence and absence of independent risk factors. Conclusion: An evaluation system based on independent factors of CLNM and LLNM for PTMC patients with bilateral and unilateral disease was established. Our newly established evaluation system can efficaciously quantify risks of CLNM and LLNM for PTMC patients with bilateral and unilateral disease and may guide individual treatment strategy including both surgical and postoperative adjuvant treatment of the neck region for these patients.

Risk Factors for Central Lymph Node Metastases and Benefit of Prophylactic Central Lymph Node Dissection in Middle Eastern Patients With cN0 Papillary Thyroid Carcinoma

Background

Prophylactic central lymph node dissection (PCLND) for adult patients with papillary thyroid carcinoma (PTC) is still a matter of debate. Data on incidence, risk and benefits of PCLND in Middle Eastern patients is lacking. Therefore, we aimed to identify the incidence and predictive clinico-pathological and molecular marker of PCLND in adult patients with clinically node negative (cN0) Middle Eastern PTC.

Methods

This retrospective study included 942 adult Middle Eastern patients with cN0 PTC who underwent total thyroidectomy (TT) or TT+PCLND. Clinico-pathological associations of central lymph node metastasis (CLNM) were assessed. Multivariate analysis was performed using logistic regression and Cox proportional hazards model.

Results

213 patients underwent PCLND and 38.0% (81/213) had positive CLNM. Multivariate analysis demonstrated age ≤55 years (Odds Ratio (OR) = 7.38; 95% Confidence Interval (CI) = 1.59 – 34.31; p = 0.0108), tumor bilaterality (OR = 3.01; 95% CI = 1.01 – 9.21; p = 0.0483), lymphovascular invasion (OR = 2.92; 95% CI = 1.18 – 7.23; p = 0.0206) and BRAF mutation (OR = 3.24; 95% CI = 1.41 – 7.49; p = 0.0058) were independent predictors of CLNM in adult PTC. Furthermore, patients who underwent PCLND showed significant association with improved recurrence-free survival (RFS; p = 0.0379). Multivariate analysis demonstrated that PCLND was an independent predictor of improved recurrence-free survival.

Conclusions

cN0 Middle Eastern PTC patients treated with PCLND showed a significantly better prognosis. PCLND was effective in improving RFS in Middle Eastern PTC patients and should be encouraged for patients with potential risk factors for CLNM.

Predicting papillary thyroid carcinoma cervical lymph node metastases: an algorithm using the American College of Radiology Thyroid Imaging, Reporting and Data System

BACKGROUND

It is important to predict lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively; however, the relationship between the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) score and cervical LNM remains unclear.

PURPOSE

To evaluate the association between the ACR TI-RADS score and cervical LNM in patients with PTC.

MATERIAL AND METHODS

This retrospective study consisted of 474 patients with 548 PTCs. Cervical LNM including central LNM (CLNM) and lateral LNM (LLNM) were confirmed by pathology. Univariate and multivariate analyses were performed to investigate the risk factors of CLNM and LLNM.

RESULTS

Multivariate logistic regression analyses indicated that younger age and multifocality were risk factors for CLNM in PTCs with TR5. In addition, younger age, larger tumor size, and Hashimoto's thyroiditis (HT) were risk factors for LLNM in PTCs ≥ 10 mm with TR5. In PTCs with TR4, ACR TI-RADS scores 5-6 conferred risks for LNM. In PTCs ≥ 10 mm with TR5, ACR TI-RADS scores ≥9 were risk factors for LLNM.

CONCLUSION

A higher ACR TI-RADS score is a predictor for cervical LNM in PTCs with TR4 and PTCs ≥ 10 mm with TR5.

A Proposed Heterogeneous Ensemble Algorithm Model for Predicting Central Lymph Node Metastasis in Papillary Thyroid Cancer

Purpose

To develop a heterogeneous ensemble algorithm model to precisely predict central lymph node metastasis (CLNM), which can provide a reference value on controversial topics of performing prophylactic central lymph node dissection for patients with papillary thyroid cancer (PTC).

Methods

The study included patients with PTC who underwent an initial thyroid resection in a single-center medical institution between January 2014 and December 2018. A total of 18 variables, including clinical features and ultrasound (US) features, were used in the univariate analysis, multivariate analysis, and feature selection and were also used to develop a heterogeneous ensemble model based on five basic machine learning models, including extreme gradient boosting, k-nearest neighbors, random forest, gradient boosting, and AdaBoost. Moreover, a partial dependent plot was used to explain the heterogeneous ensemble model.

Results

The area under the receiver operating characteristic curve of the heterogeneous ensemble algorithm model was 0.67, which is significantly better than that of the basic machine models in predicting CLNM. All machine learning models performed better than US. Based on multivariate analysis and receiver operating characteristic curve analysis, age ≤33 years, tumor size ≥0.8 cm, US-suspected CLNM, and microcalcification were risk factors for CLNM, and anti-thyroid peroxidase antibody and serum thyroglobulin levels were favorable factors for CLNM.

Conclusion

The proposed heterogeneous ensemble algorithm model may be optimal tool to predict CLNM by integrating clinical and US features.

Risk prediction for central lymph node metastasis in isolated isthmic papillary thyroid carcinoma by nomogram: A retrospective study from 2010 to 2021

BACKGROUND

Isthmic papillary thyroid carcinoma (IPTC) is an aggressive thyroid cancer associated with a poor prognosis. Guidelines elaborating on the extent of surgery for IPTC are yet to be developed. This study aims to construct and validate a model to predict central lymph node metastasis (CLNM) in patients with IPTC, which could be used as a risk stratification tool to determine the best surgical approach for patients.

METHODS

Electronic medical records for patients diagnosed with isolated papillary thyroid carcinoma who underwent surgery at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, from January 2010 to December 2021 were reviewed. All patients who underwent thyroidectomy with central neck dissection (CND) for isolated IPTC were included. We conducted univariate and multivariate logistic regression analyses to assess risk factors for ipsilateral and contralateral CLNM and the number of CLNM in IPTC patients. Based on the analysis, the nomogram construction and internal validations were performed.

RESULTS

A total of 147 patients with isolated IPTC were included. The occurrence of CLNM was 53.7% in the patients. We identified three predictors of ipsilateral CLNM, including age, gender, and size. For contralateral CLNM, three identified predictors were age, gender, and capsular invasion. Predictors for the number of CLNM included age, gender, capsular invasion, tumor size, and chronic lymphocytic thyroiditis (CLT). The concordance index(C-index) of the models predicting ipsilateral CLNM, contralateral CLNM, 1-4 CLNM, and ≥5 CLNM was 0.779 (95%CI, 0.704, to 0.854), 0.779 (95%CI, 0.703 to 0.855), 0.724 (95%CI, 0.629 to 0.818), and 0.932 (95%CI, 0.884 to 0.980), respectively. The corresponding indices for the internal validation were 0.756 (95%CI, 0.753 to 0.758), 0.753 (95%CI, 0.750 to 0.756), 0.706 (95%CI, 0.702 to 0.708), and 0.920 (95%CI, 0.918 to 0.922). Receiver operating characteristic (ROC) curves, calibration, and decision curve analysis (DCA) results confirmed that the three nomograms could precisely predict CLNM in patients with isolated IPTC.

CONCLUSION

We constructed predictive nomograms for CLNM in IPTC patients. A risk stratification scheme and corresponding surgical treatment recommendations were provided accordingly. Our predictive models can be used as a risk stratification tool to help clinicians make individualized surgical plans for their patients.

Ultrasound-based radiomics nomogram combined with clinical features for the prediction of central lymph node metastasis in papillary thyroid carcinoma patients with Hashimoto's thyroiditis

BACKGROUND

Hashimoto thyroiditis (HT) is the most common autoimmune thyroid disease and is considered an independent risk factor for papillary thyroid carcinoma (PTC), with a higher incidence of PTC in patients with HT.

OBJECTIVE

To build an integrated nomogram using clinical information and ultrasound-based radiomics features in patients with papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) to predict central lymph node metastasis (CLNM).

METHODS

In total, 235 patients with PTC with HT were enrolled in this study, including 101 with CLNM and 134 without CLNM. They were divided randomly into training and validation datasets with a 7:3 ratio for developing and evaluating clinical features plus conventional ultrasound features (Clin-CUS) model and clinical features plus radiomics scores (Clin-RS) model, respectively. In the Clin-RS model, the Pyradiomics package (V1.3.0) was used to extract radiomics variables, and LASSO regression was used to select features and construct radiomics scores (RS). The Clin-CUS and Clin-RS nomogram models were built using logistic regression analysis.

RESULTS

Twenty-seven CLNM-associated radiomics features were selected using univariate analysis and LASSO regression from 1488 radiomics features and were calculated to construct the RS. The integrated model (Clin-RS) had better diagnostic performance than the Clin-CUS model for differentiating CLNM in the training dataset (AUC: 0.845 vs. 0.778) and the validation dataset (AUC: 0.808 vs. 0.751), respectively.

CONCLUSION

Our findings suggest that applying an ultrasound-based radiomics approach can effectively predict CLNM in patients with PTC with HT. By incorporating clinical information and RS, the Clin-RS model can achieve a high diagnostic performance in diagnosing CLNM in patients with PTC with HT.

Analysis of Risk Factors Associated With Central Lymph Node Metastasis in Papillary Thyroid Carcinoma With cT1N0 Stage

AIM

Annual T1 stage papillary thyroid carcinoma (PTC) incidence rates continue to rise, yet the optimal treatment for this cancer type remains controversial. Central lymph node metastasis (CLNM) is a critical determinant in the context of treatment decision-making. While several prior studies have evaluated patients with clinica l T1a(cT1a) stage PTC, there have been fewer analyses of clinical T1b(cT1b) disease to date. The present study was thus formulated to explore predictors of CLNM in patients with cT1a and cT1b stage PTC.

METHODS

A retrospective analysis of data including clinicopathological characteristics and BRAF^V600E mutation status was conducted for 452 PTC patients undergoing surgical treatment. Logistic univariate and multivariate analyses were performed to identify risk factors associated with CLNM in particular patients' characteristics and the accuracy of the established logistic regression models was evaluated using the R software platform.

RESULTS

Respective CLNM incidence rates in cT1a and cT1b disease were 39.39% and 67.21%. Factors associated with a higher risk of CLNM among PTC(cT1a) patients included male sex, young age, tumor size, contact with capsule, and multifocality as determined through comparisons of the area under the curve for logistic regression models. Whereas male sex and age were associated with CLNM risk in PTC(cT1b) patients in univariate and multivariate analyses, age was the only risk factor associated with CLNM incidence among women with PTC(cT1b).

CONCLUSION

Predictors of CLNM differ between PTC patients with cT1a and cT1b stage disease, and a comprehensive assessment of these risk factors should thus be conducted when designing individualized treatment regimens for PTC patients.

Pretracheal Lymph Node Subdivision in Predicting Contralateral Central Lymph Node Metastasis for Unilateral Papillary Thyroid Carcinoma: Preliminary Results

BACKGROUND

The aims of this study were to assess the clinical value of pretracheal lymph node subdivision in identifying patients with contralateral central lymph node metastasis (CLNM) and risk factors for occult contralateral CLNM in unilateral PTC.

METHODS

A total of 139 unilateral PTC patients with a clinically node-negative neck (cN0) who underwent bilateral central neck dissection (CND) were prospectively enrolled. Intraoperatively, the pretracheal region was further divided into ipsilateral and contralateral subregions. Ipsilateral and contralateral pretracheal lymph nodes (LNs) as well as other CLNs (prelaryngeal, ipsilateral paratracheal and contralateral paratracheal) were labeled separately and sent for pathological examination. Demographic and clinicopathologic variables were analyzed to identify factors predictive of contralateral CLNM.

RESULTS

Of 139 patients, bilateral CLNM was present in 37 (26.6%) patients. Contralateral pretracheal LNM was significantly associated with contralateral CLNM. In multivariate analysis, prelaryngeal LNM (P = 0.004, odds ratio = 3.457) and contralateral pretracheal LNM (P = 0.006, odds ratio = 3.362) were identified as risk factors for contralateral CLNM. Neither neck recurrence nor distant metastasis was observed within the mean follow-up duration of 9.1 ± 1.8 months.

CONCLUSIONS

In most unilateral cN0 PTCs, performing ipsilateral CND is appropriate, while patients presenting with evident nodal disease intraoperatively or preoperatively in the contralateral central neck should undergo bilateral CND. Intraoperative re-evaluation of prelaryngeal and contralateral pretracheal LNs may be helpful in determining the extent of CND.

Pattern and Predictive Factors of Metastasis in Lymph Nodes Posterior to the Right Recurrent Laryngeal Nerve in Papillary Thyroid Carcinoma

OBJECTIVE

The right cervical central lymph nodes include lymph nodes anterior to the right recurrent laryngeal nerve (LN-arRLN) and lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN), and are separated by the right recurrent laryngeal nerve (RLN). LN-prRLN is a common site of nodal recurrence after the resection of papillary thyroid carcinoma (PTC). However, the complexity in anatomical structure brings difficulties in determining the surgical scope, so it is necessary to assess the pattern and predictive factors of right cervical central lymph nodes, especially LN-prRLN metastasis in papillary thyroid carcinoma.

METHODS

A total of 562 diagnosed PTC patients who underwent right or total thyroidectomy were enrolled in this retrospective study. The clinicopathological features were collected, univariate and multivariate analyses were performed to determine predictive factors of the right central lymph node metastasis.

RESULTS

In this study, the metastatic rates of the right CLN, the LN-arRLN and the LN-prRLN were 59.6% (335/562), 51.8% (291/562) and 30.4% (171/562), respectively. And 22.6% (127/562) of patients had both LN-arRLN and LN-prRLN metastasis. Among patients without LN-arRLN metastasis, the rate of LN-prRLN metastasis was 16.2% (44/271), accounting for 25.7% of the LN-prRLN metastasis group. Factors associated with an increased risk of LN-arRLN metastasis include male, age below 55 years, tumor size > 1cm, extrathyroidal extension (ETE), clinical lymph nodes metastasis(cN1), lateral lymph node metastasis, and left CLN metastasis. In addition, ETE, lateral lymph node metastasis, and LN-arRLN metastasis were independent factors of LN-prRLN metastasis. The predictive factors of LN-prRLN in cN0 PTC were further explored, revealing that tumor size ≥1.5cm, ETE, and LN-arRLN metastasis were independent predictors of LN-prRLN metastasis in cN0 PTC.

CONCLUSION

The LN-prRLN should not be ignored in surgery because of its high rate of metastasis. Our findings indicate that thorough dissection of central lymph nodes, especially LN-prRLN is crucial in clinical work.

The Application Value of the Central Lymph Node Metastasis Risk Assessment Model in Papillary Thyroid Microcarcinoma of Stage cN0: A Study of 828 Patients

BACKGROUND

The aim of this study is to build a risk assessment system for central lymph node metastasis (CLNM) in papillary thyroid microcarcinoma (PTMC) of stage cN0 and to explore its application value in clinical practice.

METHODS

A total of 500 patients with PTMC who underwent thyroid operation from 2013 to 2015 in Ningbo First Hospital were selected as the model group. Independent risk factors related to CLNM in PTMC were analyzed and determined, and a risk assessment system for CLNM was preliminarily established. Furthermore, the clinicopathological data from 328 PTMC patients with the same conditions as the model group from 2016 to 2017 were further collected as the validation group to verify the diagnostic value of the risk assessment system.

RESULTS

The risk assessment system was based on the score rating (score ≤ 5 was classified as low risk, 6-8 was classified as medium risk, and ≥9 was classified as high-risk). The area under the receiver operating characteristic curve (ROC) was 0.687 (95% CI: 0.635-0.783). According to the risk assessment system, 328 PTMC patients in the validation group were scored. Among the low-risk group, the moderate-risk group, and the high-group, 96.8%, 58.1%, and 43.2% were the CLNM (-) patients, and 3.1%, 41.9%, and 65.8% were CLNM (+) patients, respectively. The area under ROC was 0.837 (95% CI: 0.778-0.869).

CONCLUSIONS

The risk assessment system in this study is of diagnostic value and can provide a theoretical foundation for intraoperative decision-making of prophylactic central neck dissection (pCND).

LASSO-based machine learning models for the prediction of central lymph node metastasis in clinically negative patients with papillary thyroid carcinoma

BACKGROUND

The presence of central lymph node metastasis (CLNM) is crucial for surgical decision-making in clinical N0 (cN0) papillary thyroid carcinoma (PTC) patients. We aimed to develop and validate machine learning (ML) algorithms-based models for predicting the risk of CLNM in cN0 patients.

METHODS

A total of 1099 PTC patients with cN0 central neck from July 2019 to March 2022 at our institution were retrospectively analyzed. All patients were randomly split into the training dataset (70%) and the validation dataset (30%). Eight ML algorithms, including the Logistic Regression, Gradient Boosting Machine, Extreme Gradient Boosting (XGB), Random Forest (RF), Decision Tree, Neural Network, Support Vector Machine and Bayesian Network were used to evaluate the risk of CLNM. The performance of ML models was evaluated by the area under curve (AUC), sensitivity, specificity, and decision curve analysis (DCA).

RESULTS

We firstly used the LASSO Logistic regression method to select the most relevant factors for predicting CLNM. The AUC of XGB was slightly higher than RF (0.907 and 0.902, respectively). According to DCA, RF model significantly outperformed XGB model at most threshold points and was therefore used to develop the predictive model. The diagnostic performance of RF algorithm was dependent on the following nine top-rank variables: size, margin, extrathyroidal extension, sex, echogenic foci, shape, number, lateral lymph node metastasis and chronic lymphocytic thyroiditis.

CONCLUSION

By incorporating clinicopathological and sonographic characteristics, we developed ML-based models, suggesting that this non-invasive method can be applied to facilitate individualized prediction of occult CLNM in cN0 central neck PTC patients.

Machine learning-based dynamic prediction of lateral lymph node metastasis in patients with papillary thyroid cancer

OBJECTIVE

To develop a web-based machine learning server to predict lateral lymph node metastasis (LLNM) in papillary thyroid cancer (PTC) patients.

METHODS

Clinical data for PTC patients who underwent primary thyroidectomy at our hospital between January 2015 and December 2020, with pathologically confirmed presence or absence of any LLNM finding, were retrospectively reviewed. We built all models from a training set (80%) and assessed them in a test set (20%), using algorithms including decision tree, XGBoost, random forest, support vector machine, neural network, and K-nearest neighbor algorithm. Their performance was measured against a previously established nomogram using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), precision, recall, accuracy, F1 score, specificity, and sensitivity. Interpretable machine learning was used for identifying potential relationships between variables and LLNM, and a web-based tool was created for use by clinicians.

RESULTS

A total of 1135 (62.53%) out of 1815 PTC patients enrolled in this study experienced LLNM episodes. In predicting LLNM, the best algorithm was random forest. In determining feature importance, the AUC reached 0.80, with an accuracy of 0.74, sensitivity of 0.89, and F1 score of 0.81. In addition, DCA showed that random forest held a higher clinical net benefit. Random forest identified tumor size, lymph node microcalcification, age, lymph node size, and tumor location as the most influentials in predicting LLNM. And the website tool is freely accessible at http://43.138.62.202/.

CONCLUSION

The results showed that machine learning can be used to enable accurate prediction for LLNM in PTC patients, and that the web tool allowed for LLNM risk assessment at the individual level.

Hashimoto's Thyroiditis Is Associated With Central Lymph Node Metastasis in Classical Papillary Thyroid Cancer: Analysis from a High-Volume Single-Center Experience

PURPOSE

Central lymph node metastasis (CLNM) is regarded as a predictor for local recurrence in patients with papillary thyroid carcinoma (PTC) but the role of prophylactic central lymph node dissection (CLND) is controversial. Our study aims to identify the clinical factors associated with CLNM and develop a nomogram for making individualized clinical decisions.

METHOD

The perioperative data of 1,054 consecutive patients between Jan 2019 and April 2021, in our center, were reviewed and analyzed. A total of 747 patients with histopathologically confirmed classical PTC were included as the training cohort and 374 (50% training cases) patients were randomly selected to build a validating cohort via internal bootstrap analysis. Univariate and multivariate logistic regression were used to analyze the correlation between clinicopathological characteristics and CLNM.

RESULT

In the training cohort, 33.6% (251/747) of patients with classical PTC were confirmed with CLNM. And the CLNM was determined in 31.4% (168/535) of non-Hashimoto's thyroiditis (HT) patients versus 39.2% (83/212) in HT patients (p=0.043). Four factors including gender, age, size, and HT status were confirmed significantly associated with CLNM. The established nomogram showed good discrimination and consistency with a C-index of 0.703, supported by the internal validation cohort with a C-index of 0.701. The decision curve analysis showed the nomogram has promising clinical feasibility.

CONCLUSION

Our study suggested that classical PTC patients with features like male gender, age<55 years old, tumor size>1cm, and HT condition had a higher risk of CLNM. And the nomogram we developed can help surgeons make individualized clinical decisions in classical PTC patients during preoperative and intraoperative management.

The Differences Between Multifocal and Unifocal Papillary Thyroid Carcinoma in Unilateral Lobe: A Meta-Analysis

Background

As many inconsistent reports on the clinical manifestations and prognosis between unilateral unifocal PTC (UUPTC) and unilateral multifocal PTC (UMPTC), identifying the difference should guide management. The purpose of this study was to investigate other additional differences between UUPTC and UMPTC in addition to their difference in the number of cancer foci.

Data Sources

A systematic literature search was conducted in the PubMed and Web of Science databases for relevant studies published before December 31, 2020. Their reference lists were also reviewed.

Review Methods

Two reviewers independently extracted data and assessed the quality of eligible studies. Studies on patients who underwent an open thyroidectomy with or without neck dissection were included. Data were analyzed using the RevMan 5.3 software.

Results

Fifteen studies comprising 9,665 patients were selected for the meta-analysis. UMPTC occurred in 10% to 36% of all PTC cases. There were no significant differences between UMPTC and UUPTC patients in age, gender, tumor size, and extrathyroidal extension (ETE). However, significant differences (P < 0.05) between UMPTC and UUPTC patients were observed in central lymph node metastasis (CLNM), lateral lymph node metastasis (LLNM), tumor-node-metastasis (TNM) stage I+II, TNM stage III+IV, the recurrence/persistence of the UMPTC group after total thyroidectomy and overall recurrence/persistence.

Conclusion

UMPTC patients are more likely to have CLNM, LLNM, more advanced TNM stage, and recurrence/persistence than UUPTC patients. Compared with UUPTC, UMPTC patients should undergo central lymph node dissection, and pay more attention to LLNM, TNM stage and recurrence/persistence during the follow-up.

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.

[Application of Ultrasound Model for Predicting Central Compartment Lymph Node Metastasis in Papillary Thyroid Carcinoma]

Objective To establish a predictive model for central compartment lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC).Methods We retrospectively evaluated patients with histologically confirmed PTC treated in Chinese PLA General Hospital between January 2018 and January 2019.Totally 855 patients undergoing thyroidectomy with central lymph node dissection were enrolled in this study (577 in the training cohort and 278 in the validation cohort).The clinical manifestations of the patients and the ultrasound features of the tumors were recorded.To predict the probability of CLNM,we developed the clinical-ultrasound model with significant factors selected by the stepwise logistic regression.The Akaike Information Criterion (AIC) was use to select the optimal model,and the area under the curve (AUC) and the calibration curves were used to evaluate the performance of the prediction model.Results Multivariate analysis showed that sex (P<0.001),age 45-55 years (P=0.004) or ≥55 years (P=0.003),tumor size 1-2 cm (P<0.001) or >2 cm (P=0.008),multifocality (P=0.029),microcalcification (P=0.019),diffused distribution of microcalcifications (P=0.001),and vascularity levels 2-3 (P=0.002) were effective for CLNM prediction.The model based on the clinical and ultrasound features showed good performance in both training cohort with AUC of 0.78 (95%CI:0.74-0.82) and validation cohort with AUC of 0.70 (95%CI:0.67-0.76).Conclusions A quantitative model of CLNM in PTC patients was established based on the risk factors.According to the model,central lymph node dissection is recommended for PTC patients with high scores.

Web-Based Ultrasonic Nomogram Predicts Preoperative Central Lymph Node Metastasis of cN0 Papillary Thyroid Microcarcinoma

BACKGROUND

Many clinicians are facing the dilemma about whether they should apply the active surveillance (AS) strategy for managing Clinically Node-negative (cN0) PTMC patients in daily clinical practice. This research plans to construct a dynamic nomogram based on network, connected with ultrasound characteristics and clinical data, to predict the risk of central lymph node metastasis (CLNM) in cN0 PTMC patients before surgery.

METHODS

A retrospective analysis of 659 patients with cN0 PTMC who had underwent thyroid surgery and central compartment neck dissection. Patients were randomly (2:1) divided into the development cohort (439 patients) and validation cohort (220 patients). The group least absolute shrinkage and selection operator (Group Lasso) regression method was used to select the ultrasonic features for CLNM prediction in the development cohort. These features and clinical data were screened by the multivariable regression analysis, and the CLNM prediction model and web-based calculator were established. Receiver operating characteristic, calibration curve, Clinical impact curve and decision curve analysis (DCA) were used to weigh the performance of the prediction model in the validation set.

RESULTS

Multivariable regression analysis showed that age, tumor size, multifocality, the number of contact surface, and real-time elastography were risk factors that could predict CLNM. The area under the curve of the prediction model in the development and validation sets were 0.78 and 0.77, respectively, with good discrimination and calibration. A web-based dynamic calculator was built. DCA proved that the prediction model had excellent net benefits and clinical practicability.

CONCLUSIONS

The web-based dynamic nomogram incorporating US and clinical features was able to forecast the risk of preoperative CLNM in cN0 PTMC patients, and has good predictive performance. As a new observational indicator, NCS can provide additional predictive information.

Predictive Factor of Large-Volume Central Lymph Node Metastasis in Clinical N0 Papillary Thyroid Carcinoma Patients Underwent Total Thyroidectomy

Large-volume central lymph node metastasis (large-volume CLNM) is associated with high recurrence rate in papillary thyroid carcinoma (PTC) patients. However, sensitivity in investigating large-volume CLNM on preoperative ultrasonography (US) is not high. The aim of this study is to investigate the clinical factors associated with large-volume CLNM in clinical N0 PTC patients. We reviewed 976 PTC patients undergoing total thyroidectomy with central lymph node dissection during 2017 to 2019. The rate of large-volume LNM was 4.1% (40 of 967 patients). Multivariate analysis showed that male gender and young age (age<45 years old) were independent risk factors for large-volume CLNM with odds ratios [(OR), 95% confidence interval (CI)] of 2.034 (1.015-4.073) and 2.997 (1.306-6.876), respectively. In papillary thyroid microcarcinoma (PTMC), capsule invasion was associated with large-volume CLNM with OR (95% CI) of 2.845 (1.110-7.288). In conventional papillary thyroid cancer (CPTC), tumor diameter (>2cm) was associated with large-volume CLNM, with OR (95% CI) 3.757 (1.061-13.310), by multivariate analysis. In ROC curve analysis on the diameter of the CPTC tumor, the Area Under Curve (AUC) =0.682(p=0.013), the best cut-off point was selected as 2.0cm. In conclusion, male gender and young age were predictors for large-volume CLNM of cN0 PTC. cN0 PTMC patient with capsule invasion and cN0 CPTC patient with tumor diameter >2cm were correlated with large-volume CLNM. Total thyroidectomy with central lymph node dissection may be a favorable primary treatment option for those patients.

A Nomogram Based on Clinical and Ultrasound Characteristics to Predict Central Lymph Node Metastasis of Papillary Thyroid Carcinoma

BACKGROUND

The status of lymph nodes in the central compartment is crucial to determining the surgical strategies for papillary thyroid carcinoma (PTC). We aimed to develop a nomogram for predicting central lymph node metastasis (CLNM).

METHODS

A total of 886 PTC patients who underwent total thyroidectomy or lobectomy with central neck dissection (CND) from July 2019 to June 2020 were retrospectively retrieved. Clinical and ultrasound features were collected. Univariate and multivariate analysis were performed to determine risk factors of CLNM. A nomogram for predicting CLNM was developed, internal and external calibration was performed for the established model.

RESULTS

Variables (sex, chronic lymphocytic thyroiditis, tumor size, the number of foci, tumor location, margin) significantly associated with CLNM were included in the nomogram. The nomogram showed excellent calibration in the training group and validation group, with area under curves of 0.806 (95% CI, 0.771 to 0.825), and 0.799 (95% CI, 0.778-0.813) respectively.

CONCLUSION

Through this accurate and easy-to-use nomogram, the possibility of CLNM can be objectively quantified preoperatively. Clinicians can use this nomogram to evaluate the status of lymph nodes in PTC patients and consider prophylactic CND for those with high scores.

Surgical Extent of Central Lymph Node Dissection for Papillary Thyroid Carcinoma Located in the Isthmus: A Propensity Scoring Matched Study

INTRODUCTION

To assess the risk factor for the central lymph node (CLN) metastasis and investigated the surgery extent of lymph node dissection for patients with isthmic PTC (papillary thyroid carcinoma).

MATERIALS AND METHODS

A total of 669 patients with a single nodule of isthmic PTC were retrospectively reviewed. The propensity score matching was performed twice separately. 176 patients respectively from patients who underwent thyroidectomy plus bilateral central lymph node dissection (BCLND) and who underwent thyroidectomy plus unilateral central lymph node dissection (UCLND) were matched. 77 patients were respectively selected from patients who underwent thyroidectomy plus BCLND and who underwent thyroidectomy with no central lymph node dissection (NCLND) were matched.

RESULTS

Among all the patients who underwent BCLND, 81/177 (45.76%) was confirmed with histologically positive CLN metastasis, and the occult lymph node metastasis is 25.42%. A tumor size of 1.05 cm was calculated as the cutoff point for predicting CLN metastasis by ROC curve analysis with 177 patients who underwent BCLND. The 5-year recurrence-free survival (RFS) rates were 92.9% in the NCLND group and 100% in the BCLND group with P<0.05, while there was no statistical difference in 5-year RFS between the BCLND group and UCLND group (P=0.11). The multivariate logistic regression analysis identified that age<55, tumor size>1cm, capsule invasion and lymphovascular invasion were significantly associated with CLN metastasis, while only age and lymphovascular invasion were proved to be independent risk factors related to contralateral CLN metastasis.

CONCLUSIONS

The thyroidectomy with NCLND could be insufficient for patients with isthmic PTC especially for those patients with high risk of central lymph node metastasis, considering that the rate of occult lymph node metastasis could not be ignored.

Metastasis of cN0 Papillary Thyroid Carcinoma of the Isthmus to the Lymph Node Posterior to the Right Recurrent Laryngeal Nerve

OBJECTIVE

The association between metastasis to the lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN) and cN0 papillary thyroid carcinoma (PTC) located in the thyroid isthmus remains unknown; therefore, our goal was to analyze the characteristics of LN-prRLN metastasis of cN0 PTCs of the thyroid isthmus and determine its potential predictors.

PATIENTS AND METHODS

This retrospective study included patients who underwent bilateral central neck dissection between January 2018 and January 2021. The specimen was divided into five groups of prelaryngeal lymph node (LN), pretracheal LN, left paratracheal LN, lymph node anterior to the right recurrent laryngeal nerve (LN-arRLN), and LN-prRLN. Univariate and multivariate analyses were used to assess the association between the clinical pathologic variables and LN-prRLN metastases. Surgical complications were presented descriptively.

RESULTS

A total of 357 patients were included, LN-prRLN metastasis occurred in 23 (6.4%) patients, and LN-prRLN was positive only when there were other LN metastases, especially LN-arRLN metastases. Other independent risk factors for LN-prRLN included foci numbers ≥2, tumor size ≥5.0 mm, and extrathyroidal extensions. The rates of permanent hypoparathyroidism and vocal cord paralysis were 1.1% and 2.0%, respectively.

CONCLUSION

LN-prRLN metastases should not be ignored in cN0 PTC located in the thyroid isthmus; however, its dissection is a safe procedure, and the status of LN-arRLN can be a reliable predictor for LN-prRLN metastases.

Preoperatively Predicting the Central Lymph Node Metastasis for Papillary Thyroid Cancer Patients With Hashimoto's Thyroiditis

BACKGROUND

The preoperative distinguishment of lymph nodes with reactive hyperplasia or tumor metastasis plays a pivotal role in guiding the surgical extension for papillary thyroid carcinoma (PTC) with Hashimoto's thyroiditis (HT), especially in terms of the central lymph node (CLN) dissection. We aim to identify the preparative risk factors for CLN metastasis in PTC patients concurrent with HT.

MATERIALS AND METHODS

We retrospectively reviewed and analyzed the data including the basic information, preoperative sonographic characteristics, and thyroid function of consecutive PTC patients with HT in our medical center between Jan 2019 and Apr 2021. The Chi-square and Fisher's exact tests were used for comparison of qualitative variables among patients with or without CLN metastasis. Univariate and multivariate logistic regression analyses were used to determine the risk factors for CLN metastasis. The nomogram was constructed and further evaluated by two cohorts produced by 1,000 resampling bootstrap analysis.

RESULTS

A total of 98 in 214 (45.8%) PTC patients were identified with CLN metastasis. In multivariate analysis, four variables including high serum thyroglobulin antibody (TgAb) level (>1,150 IU/ml), lower tumor location, irregular margin of CLN, and micro-calcification in the CLN were determined to be significantly associated with the CLN metastasis in PTC patients with HT. An individualized nomogram was consequently established with a favorable C-index of 0.815 and verified via two internal validation cohorts.

CONCLUSIONS

Our results indicated that preoperatively sonographic characteristics of the tumor and lymph node condition combined with serum TgAb level can significantly predict the CLN in PTC patients with HT and the novel nomogram may further help surgeons to manage the CLN in this subpopulation.

Nomogram Including Elastography for Prediction of Contralateral Central Lymph Node Metastasis in Solitary Papillary Thyroid Carcinoma Preoperatively

Background

It is controversial whether contralateral prophylactic central neck dissection (PCND) should be performed for patients with solitary and clinical lymph node negative (cN₀) papillary thyroid carcinoma (PTC) although routine ipsilateral PCND is required.

Objective

The aim of this study was to develop an improved nomogram including clinical features, ultrasound, and acoustic radiation force impulse (ARFI) elastography for the prediction of contralateral central lymph node metastasis (CLNM) in patients with solitary and cN₀ PTC in the preoperative period.

Materials and Methods

A total of 340 patients were retrospectively included as the training cohort and 170 patients as the external validation cohort. Patients were grouped according to the pathological results of contralateral CLNM. The association between the clinical characteristics, ultrasound, and ARFI elastography and the risk for contralateral CLNM were analyzed. A nomogram was established based on the result of multivariable logistic analysis to predict the risk of contralateral CLNM, which was assessed by internal and external validation.

Results

CLNM was found in 213 patients (41.8%), among whom 142 (27.8%) had ipsilateral CLNM and 95 (18.6%) had contralateral CLNM (including 68 (13.3%) with bilateral CLNM). Multivariable analysis revealed that patients with younger age, male gender, larger tumor size, closer distance from the capsule, microcalcification, and larger SWV_mean were independent predictors associated with the contralateral CLNM (P < 0.05), which was served as the basis of the nomogram. It showed good discrimination (C-index: 0.856) and calibration (χ² = 9.028, P = 0.340, Hosmer–Lemeshow test) in the training cohort, and good discrimination was maintained in the external validation cohort (C-index: 0.792).

Conclusion

The nomogram utilizing the features of ultrasound combined with ARFI elastography in preoperatively predicting the risk of contralateral CLNM in patients with solitary and cN₀ PTC was established, which showed superior performance both in internal and external validation.

Completion Total Thyroidectomy Is Not Necessary for Papillary Thyroid Microcarcinoma with Occult Central Lymph Node Metastasis: A Long-Term Serial Follow-Up

Simple Summary

The necessity of completion total thyroidectomy is unclear in patients with papillary thyroid microcarcinoma (PTMC) with only pathological central lymph node metastasis (pCLNM). The aim of our study was to determine the necessity of completion total thyroidectomy after an initial surgery by comparing the prognosis according to the presence of pCLNM during a long-term follow-up. We retrospectively compared the pathological central lymph node (pCLN)-positive group of 165 patients who underwent thyroid lobectomy with the pCLN-negative group of 711 patients and found no difference between the two groups in the recurrence rate and disease-free survival rates. Therefore, PTMC patients who underwent thyroid lobectomy with prophylactic central compartment neck dissection and were diagnosed with pCLNM after surgery do not require completion total thyroidectomy.

Abstract

The necessity of completion total thyroidectomy in patients with papillary thyroid microcarcinoma (PTMC) and pathological central lymph node metastasis (pCLNM) who underwent thyroid lobectomy with central compartment neck dissection (CCND) is unclear. We determined the necessity of completion total thyroidectomy by retrospectively comparing the prognosis according to the presence of pCLNM during a long-term follow-up. We enrolled 876 patients with PTMC who underwent thyroid lobectomy with prophylactic CCND from January 1986 to December 2009. Patients were divided according to central lymph node (CLN) metastasis: 165 (18.8%) and 711 (81.2%) in the CLN-positive and CLN-negative groups, respectively. Medical records were reviewed retrospectively, and clinicopathologic characteristics and recurrence rates were analyzed. The CLN-positive group was associated with male sex (p = 0.001), larger tumor size (p < 0.001), and more microscopic capsular invasion (p < 0.001) compared with the CLN-negative group. There was no significant difference between the two groups’ recurrence (p = 0.133) or disease-free (p = 0.065) survival rates. Univariate and multivariate analyses showed no factors associated with tumor recurrence except male sex (hazard ratio = 3.043, confidence interval 1.117–8.288, p = 0.030). Patients who were diagnosed with pCLNM after undergoing thyroid lobectomy with prophylactic CCND do not require completion total thyroidectomy; however, frequent follow-up is necessary for patients with PTMC and pCLNM.

Value of Ultrasound Combined with Immunohistochemistry Evaluation of Central Lymph Node Metastasis for the Prognosis of Papillary Thyroid Carcinoma

Background

Papillary thyroid carcinoma (PTC) is often accompanied by cervical lymph node metastasis (LNM). The accuracy of the preoperative ultrasound diagnosis of central LNM (CLNM) is limited. LNM is a high-risk factor for local recurrence and may affect the prognosis. Factors not directly related to tumor proliferation are used for risk assessment in the tumor-node-metastasis (TNM) staging system for thyroid cancer. The present study aimed to investigate the value of ultrasound and immunohistochemistry in predicting the presence of CLNM and the prognosis of PTC.

Patients and Methods

The ultrasound and immunohistochemistry features of 303 patients with first-ever PTC and who underwent surgery between 01/2014 to 12/2016 were analyzed, as well as the prognosis of the patients. Univariable and multivariable analyses were carried out to determine the risk factors of CLNM and recurrence.

Results

Among 303 patients, 125 (41.3%) were pathologically confirmed with CLNM. Multivariable analysis showed that multifocality, taller-than-wide shape, grade III–IV blood flow, capsular invasion, Ki-67 >10%, p53 ≥5%, T2 or T3 stages were independent risk factors for CLNM. The median follow-up was 56 months. Cox regression analysis showed that age ≥55 years, maximum tumor diameter >20 mm, multifocality, capsular invasion, Ki-67 5–10%, Ki-67 >10%, p53 ≥5%, T3 stage and N1a stage were independent risk factors for PTC recurrence. The Kaplan–Meier showed that recurrence-free survival (RFS) was different according to age (P=0.017), tumor size multifocality, capsular invasion, Ki-67, p53, T stage and N stage (all P<0.001).

Conclusion

For PTC with rich blood flow, taller-than-wide shape, multifocality, capsular invasion, p53 ≥5%, Ki-67 >10%, T2 or T3 stages prophylactic CLNM dissection might be indicated. Age≥55 years, maximum tumor diameter >20 mm, multifocality, capsular invasion, high Ki-67, p53 ≥5%, T3 and N1a stages affected the clinical outcome.

Predicting non-small-volume central lymph node metastases (>5 or ≥2 mm) preoperatively in cN0 papillary thyroid microcarcinoma without extrathyroidal extension

The ability to identify patients with aggressive papillary thyroid microcarcinoma (PTMC) from the low-risk patients is critical to planning proper management of PTMC. Lymph node metastases showed association with recurrence and low survival rate, especially in patients with >5 or ≥2 mm metastatic lymph nodes. Therefore, this study aimed to investigate the preoperatively predictive factors of non-small-volume (metastatic lymph nodes >5 or ≥2 mm in size) central lymph node metastases (NSVCLNM) in PTMC patients. A total of 420 patients with clinically node-negative (cN0) PTMC without extrathyroidal extension underwent thyroidectomy plus central neck dissection (CND) between January 2013 and December 2015, were retrospectively analyzed. Of the 420 patients, 33 (7.9%) had NSVCLNM. The 5-year recurrence-free survival was significantly less in cN0 PTMC patients with NSVCLNM, when compared with patients without NSVCLNM (80.8% vs 100%, P < .001). Multivariate logistic regression revealed age ≤36 years (P < .001), male sex (P = .002), ultrasonic tumor sizes of >0.65 cm (P < .001), and ultrasonic multifocality (P = .039) were independent predictive factors of NSVCLNM. A prediction equation (Y = 1.714 × age + 1.361 × sex + 1.639 × tumor size + 0.842 × multifocality -5.196) was developed, with a sensitivity (69.7%) and a specificity (84.0%), respectively, at an optimal cutoff point of -2.418. In conclusion, if the predictive value was >-2.418 according to the equation, immediate surgery including CND rather than active surveillance might be considered for cN0 PTMC patients.

A miRNA-clinicopathological nomogram for the prediction of central lymph node metastasis in papillary thyroid carcinoma-analysis from TCGA database

It is of significance to evaluate central lymph node status in patients with papillary thyroid carcinoma (PTC), because it can decrease postoperative complications resulting from unnecessary prophylactic central lymph node dissection (CLND). Due to the low sensitivity and specificity of neck ultrasonography in the evaluation of central lymph node metastasis (CLNM), it is urgently required to find alternative biomarkers to predict CLNM in PTC patients, which is the main purpose of this study.RNA-sequencing datasets and clinical data of 506 patients with thyroid carcinoma from the Cancer Genome Atlas (TCGA) database were downloaded and analyzed to identify differentially expressed miRNAs (DEMs), which can independently predict CLNM in PTC. A nomogram predictive of CLNM was developed based on clinical characteristics and the identified miRNAs. Receiver operating characteristics curves were drawn to evaluate the predictive performance of the nomogram. Bioinformatics analyses, including target genes identification, functional enrichment analysis, and protein-protein interaction network, were performed to explore the potential roles of the identified DEMs related to CLNM in PTC.A total of 316 PTC patients were included to identify DEMs. Two hundred thirty-seven (75%) PTC patients were randomly selected from the 316 patients as a training set, while the remaining 79 (25%) patients were regarded as a testing set for validation. Two DEMs, miRNA-146b-3p (HR: 1.327, 95% CI = 1.135-1.551, P = .000) and miRNA-363-3p (HR: 0.714, 95% CI = 0.528-0.966, P = .029), were significantly associated with CLNM. A risk score based on these 2 DEMs and calculating from multivariate logistic regression analysis, was significantly lower in N0 group over N1a group in both training (N0 vs N1a: 2.04 ± 1.01 vs 2.73 ± 0.61, P = .000) and testing (N0 vs N1a: 2.20 ± 0.93 vs 2.79 ± 0.68, P = .003) sets. The nomogram including risk score, age, and extrathyroidal extension (ETE) was constructed in the training set and was then validated in the testing set, which showed better prediction value than the other three predictors (risk score, age, and ETE) in terms of CLNM identification. Bioinformatics analyses revealed that 5 hub genes, SLC6A1, SYT1, COL19A1, RIMS2, and COL1A2, might involve in pathways including extracellular matrix organization, ion transmembrane transporter activity, axon guidance, and ABC transporters.On the basis of this study, the nomogram including risk score, age, and ETE showed good prediction of CLNM in PTC, which has a potential to facilitate individualized decision for surgical plans.

Analysis of Risk Factors for Lymph Node Metastases in Elderly Patients with Papillary Thyroid Micro-Carcinoma

Background

With guidance from the American Joint Committee on Cancer (AJCC) Cancer Staging Manual, 8th edition, we explored the characteristics of central lymph node metastasis (CLNM) of papillary thyroid micro-carcinoma (PTMC) in elderly patients ≥55 years of age. Our goal was to provide references for establishing a lymph node dissection scheme in such patients.

Methods

We retrospectively analyzed the clinical data of thyroid cancer patients admitted to the Head and Neck Surgery Center of Sichuan Cancer Hospital, Chengdu, China, from January 2015 to September 2018. Then, we screened and analyzed eligible PTMC cases in strict accordance with our inclusion and exclusion criteria.

Results

The study included 107 patients, including 24 men and 83 women. Median age was 59.99 ± 4.58 years. The maximum diameter range of the cancer foci was 4-10 mm, and the median was 7.59 ± 1.78 mm. Unilateral lobectomy had been performed in 32 cases, total thyroidectomy in 75 cases and lateral cervical lymph node dissection in 21 cases. There were 60 cases of CLNM (56.07%) and 13 cases of lateral cervical lymph node metastasis (12.10%). The sensitivity of preoperative ultrasound in predicting CLNM was 100%, but its accuracy was only 50.47%. Multivariate logistic regression analysis showed that multiple cancer foci (area under the curve [AUC] = 0.632), extra-thyroidal expansion of cancer focus (AUC = 0.721), and irregular nodules (AUC = 0.603) were independent risk factors for CLNM of PTMC in elderly patients (P < 0.05). Overall predictability for PTMC-CLNM was 80.30%.

Conclusion

1) Preoperative color Doppler ultrasound is not recommended as the basis for cervical lymph node dissection in PTMC patients. 2) For multiple cancer foci, irregular nodules, and elderly patients with PTMC extra-thyroidal expansion, we recommend a prophylactic central lymph node dissecting. 3) Nonsurgical observation of PTMC in elderly patients with low risk should be carefully selected.