Risk factor analysis for predicting cervical lymph node metastasis in papillary thyroid carcinoma: a study of 966 patients

Can pre-operative ultrasound elastography predict aggressive features of solitary papillary thyroid carcinoma?

OBJECTIVE

To investigate whether pre-operative ultrasound elastography (USE) can be used to predict aggressive features of solitary papillary thyroid carcinomas (PTCs).

METHODS

Clinical and USE indices were retrospectively analyzed in 487 patients with surgically confirmed solitary PTCs. The patients were grouped per aggressive features on pathologic testing. Univariate and binary logistic regression analyses were performed to explore independent risk factors of aggressive features.

RESULTS

Univariate analysis revealed standard deviation (SD) values of the tumor shear-wave velocity (SWV) were associated with capsular invasion (p < 0.05). Further, shear-wave elasticity and SWV ratios correlated with extrathyroidal extension (all p < 0.05). The tumor shear-wave elasticity and SWV SD values were associated with cervical lymph node metastasis (CLNM) (all p < 0.05). Binary logistic regression analysis identified location and capsule contact as independent predictive risk factors for capsular invasion (all p < 0.05); size for extrathyroidal extension (all p < 0.05); and sex, age, margin, and suspected CLNM for CLNM (all p < 0.05). However, pre-operational USE indexes were not independent predictors of aggressive features (all p > 0.05).

CONCLUSION

Pre-operative USE indices were not independent risk factors of aggressive features of solitary PTCs. Thus, USE may have a limited value for predicting the aggressive features of PTC.

ADVANCES IN KNOWLEDGE

Pre-operative USE indices may have a limited value for predicting the aggressive features of PTC.

Predicting central lymph node metastasis in patients with papillary thyroid carcinoma based on ultrasound radiomic and morphological features analysis

OBJECTIVES

To build a combined model based on the ultrasound radiomic and morphological features, and evaluate its diagnostic performance for preoperative prediction of central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC).

METHOD

A total of 295 eligible patients, who underwent preoperative ultrasound scan and were pathologically diagnosed with unifocal PTC were included at our hospital from October 2019 to July 2022. According to ultrasound scanners, patients were divided into the training set (115 with CLNM; 97 without CLNM) and validation set (45 with CLNM; 38 without CLNM). Ultrasound radiomic, morphological, and combined models were constructed using multivariate logistic regression. The diagnostic performance was assessed by the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, sensitivity, and specificity.

RESULTS

A combined model was built based on the morphology, boundary, length diameter, and radiomic score. The AUC was 0.960 (95% CI, 0.924-0.982) and 0.966 (95% CI, 0.901-0.993) in the training and validation set, respectively. Calibration curves showed good consistency between prediction and observation, and DCA demonstrated the clinical benefit of the combined model.

CONCLUSION

Based on ultrasound radiomic and morphological features, the combined model showed a good performance in predicting CLNM of patients with PTC preoperatively.

Construction and validation of nomograms to reduce completion thyroidectomy by predicting lymph node metastasis in low-risk papillary thyroid carcinoma

CONTEXT

More than 5 central lymph nodes metastases (CLNM) or lateral lymph node metastasis (LLNM) indicates a higher risk of recurrence in low-risk papillary thyroid carcinoma (PTC) and may lead to completion thyroidectomy (CTx) in patients initially undergoing lobectomy.

OBJECTIVE

To screen potentially high-risk patients from low-risk patients by using preoperative and intraoperative clinicopathological features to predict lymph node status.

METHODS

A retrospective analysis of 8301 PTC patients in Wuhan Union Hospital database (2009-2021) was performed according to the 2015 American Thyroid Association (ATA) and 2021 National Comprehensive Cancer Network (NCCN) guidelines, respectively. Logistic regression and best subsets regression were used to identify risk factors. Nomograms were established and externally validated using the Differentiated Thyroid Cancer in China cohort.

RESULTS

More than 5 CLNM or LLNM was detected in 1648 (19.9%) patients. Two predictive models containing age, gender, maximum tumor size, free thyroxine (FT4) and palpable node (all p < 0.05) were established. The nomogram based on NCCN criteria showed better discriminative power and consistency with a specificity of 0.706 and a sensitivity of 0.725, and external validation indicated that 76% of potentially high-risk patients could achieve preoperative conversion of surgical strategy.

CONCLUSIONS

Models based on large cohorts with good predictive performance were constructed and validated. Preoperative low-risk (T1-2N0M0) patients with age younger than 40 years, male gender, large tumor size, low FT4 and palpable nodes may be at high risk of LLNM or more than 5 CLNM, and they should receive more aggressive initial therapy to reduce CTx.

Multimodal predictive factors of metastasis in lymph nodes posterior to the right recurrent laryngeal nerve in papillary thyroid carcinoma

Objective

The lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN) is a crucial component of the central lymph nodes (LNs). We aimed to evaluate multimodal predictive factors of LN-prRLN metastasis in patients with papillary thyroid carcinomas (PTCs), including the clinical data, pathologic data, and preoperative sonographic characteristics of PTCs.

Methods

A total of 403 diagnosed PTC patients who underwent unilateral, sub-total, or total thyroidectomy with central neck dissection were enrolled in this retrospective study. The clinical data, pathologic data, conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) characteristics of PTCs were collected and evaluated for predicting LN-prRLN metastasis.

Results

In this study, 96 PTC patients with LN-prRLN metastasis and 307 PTC patients without LN-prRLN metastasis were included. Univariate analysis demonstrated that PTC patients with LN-prRLN metastasis more often had younger age, larger size, multifocal cancers, A/T < 1, well-margins, microcalcification, petal-like calcification, internal vascularity, centripetal perfusion pattern and surrounding ring enhancement. Multivariate logistic regression analysis revealed that the CEUS centripetal perfusion pattern, central LN detected by ultrasound and LN-arRLN metastasis were independent characteristics for predicting LN-prRLN metastasis in PTC patients.

Conclusion

According to our research, it is essential for clinicians to thoroughly dissect central LNs, particularly LN-prRLNs.

Patient's age with papillary thyroid cancer: Is it a key factor for cervical lymph node metastasis?

BACKGROUND

Age is one of the important prognostic indicators of papillary thyroid cancer (PTC). However, the distinct metastatic patterns and prognosis of age-related lymph node metastasis (LNM) are unclear. This study aims to investigate the impact of age on LNM.

METHODS

We conducted two independent cohort studies to assess age-nodal disease association using logistic regression analysis and a restricted cubic splines model. A multivariable Cox regression model was utilized to test the impact of nodal disease on cancer-specific survival (CSS) after age stratification.

RESULTS

For this study, we included 7572 and 36,793 patients with PTC in Xiangya and SEER cohorts, respectively. After adjustment, advanced age was linearly associated with decreasing risk of central LNM. Patients of age ≤18 years (OR = 4.41, P < 0.001) and 19-45 years (OR = 1.97, P = 0.002) had a higher risk of developing lateral LNM than patients of age >60 years in both cohorts. Furthermore, CSS is significantly reduced in N1b disease (P < 0.001), not N1a disease, regardless of age. The incidence of high-volume LNM (HV-LNM) was significantly higher in patients of age ≤18 years and 19-45 years than in those of age >60 years (P < 0.001), in both cohorts. In addition, CSS was compromised in patients with PTC of age 46-60 years (HR = 1.61, P = 0.022) and those of age >60 (HR = 1.40, P = 0.021) after developing HV-LNM.

CONCLUSIONS

Patient age is significantly associated with LNM and HV-LNM. Patients with N1b disease or patients with HV-LNM of age >45 years have significantly shorter CSS. Age can, thus, be a useful guide for determining treatment strategies in PTC.

The Size of a Thyroid Nodule with ACR TI-RADS Does Not Provide a Better Prediction of the Nature of the Nodule: A Single-Center Retrospective Real-Life Observational Study

We investigated if thyroid nodule size has a predictive value of malignancy on a par with composition, echogenicity, shape, margin, and echogenic foci, and what would be the consequence of observing the rule of the American College of Radiology (ACR) to perform a fine-needle aspiration biopsy (FNAB). We conducted a retrospective real-life observational study on 86 patients who underwent surgery after a standardized diagnostic protocol. We divided the TR3, TR4, and TR5 classes into sub-classes according to the size threshold indicating FNAB (a: up to the threshold for no FNAB; b: over the threshold for FNAB suggested). We computed sensitivity, specificity, and positive (PPV) and negative predictive value (NPV) for the different sub-classes and Youden's index (Y) for the different possible cutoffs. Each sub-class showed the following PPV (0.67, 0.68, 0.70, 0.78, 0.72), NPV (0.56, 0.54, 0.51, 0.52, 0.59), and Y (0.20, 0.20, 0.22, 0.31, 0.30). In this real-life series, we did not find a significant difference in prediction of malignancy between the sub-categories according to the size threshold. All nodules have a pre-evaluation likelihood of being malignant, and the impact and utility of size thresholds may be less clear than suggested by the ACR TIRADS guidelines in patients undergoing standardized thyroid work up.

Lymph Node Ratio Predicts Recurrence in Patients with Papillary Thyroid Carcinoma with Low Lymph Node Yield

The American Thyroid Association risk stratification system suggests that having >5 metastatic lymph nodes (LNs) increase the recurrence risk in patients with papillary thyroid carcinoma (PTC). However, little is known about PTC with <5 harvested LNs. This study aimed to stratify patients with low-LN-yield (low-LNY) PTC based on lymph node ratios (LNRs). From 2007 to 2017, 6317 patients who underwent thyroidectomies were diagnosed with PTC at Seoul St. Mary's Hospital, and 909 patients with low LNYs were included in the study. Tumor recurrence was compared based on LNR. The LNR cutoff was determined using a receiver operating characteristic curve. Forty-six patients (5.1%) experienced recurrences over a mean follow-up period of 127.24 ± 33.6 months (range, 5-190 months). The cutoff for the low-LNR (n = 675) and high-LNR (n = 234) groups was 0.29 (AUC = 0.676, 95% CI = 0.591-0.761, p < 0.001). The recurrence rate was significantly higher in the high-LNR group compared to the rate in the low-LNR group (12.4% vs. 2.5%, p < 0.001). Multivariate analysis using Cox regression revealed that tumor size and LNR ≥ 0.29 were independent prognostic factors for recurrence. Therefore, LNR can be utilized to stratify the risk of recurrence in patients with low-LNY PTC.

Prediction of Cervical Lymph Node Metastasis in Clinically Node-Negative T1 and T2 Papillary Thyroid Carcinoma Using Supervised Machine Learning Approach

Papillary thyroid carcinoma (PTC) is generally considered an indolent cancer. However, patients with cervical lymph node metastasis (LNM) have a higher risk of local recurrence. This study evaluated and compared four machine learning (ML)-based classifiers to predict the presence of cervical LNM in clinically node-negative (cN0) T1 and T2 PTC patients. The algorithm was developed using clinicopathological data from 288 patients who underwent total thyroidectomy and prophylactic central neck dissection, with sentinel lymph node biopsy performed to identify lateral LNM. The final ML classifier was selected based on the highest specificity and the lowest degree of overfitting while maintaining a sensitivity of 95%. Among the models evaluated, the k-Nearest Neighbor (k-NN) classifier was found to be the best fit, with an area under the receiver operating characteristic curve of 0.72, and sensitivity, specificity, positive and negative predictive values, F1 and F2 scores of 98%, 27%, 56%, 93%, 72%, and 85%, respectively. A web application based on a sensitivity-optimized kNN classifier was also created to predict the potential of cervical LNM, allowing users to explore and potentially build upon the model. These findings suggest that ML can improve the prediction of LNM in cN0 T1 and T2 PTC patients, thereby aiding in individual treatment planning.

Clinical and ultrasonic risk factors for high-volume central lymph node metastasis in cN0 papillary thyroid microcarcinoma: A retrospective study and meta-analysis

OBJECTIVE

Papillary thyroid microcarcinoma (PTMC) comprises more than 50% of all newly detected cases of papillary thyroid carcinoma (PTC). High-volume lymph node metastasis (involving >5 lymph nodes) (hv-LNM) is associated with PTMC recurrence. In half of the clinically node-negative (cN0) PTMC patients, central lymph node metastasis (CLNM) is pathologically present. However, clinical risk factors for high-volume CLNM (hv-CLNM) in cN0 PTMC have not been defined well. Therefore, we aimed to obtain evidence for hv-CLNM risk factors in cN0 PTMC.

DESIGN

Data on patients who visited our hospital between January 2020 and December 2021 were collected; a preoperative diagnosis of cN0 and a postoperative pathological confirmation of PTMC were obtained. After filtering by inclusion versus exclusion criteria, the obtained data (N = 2268) were included in the meta-analysis. Relevant studies published as of 10 April 2022, were identified from the Web of Science, PubMed, WANFANG, and CNKI databases. These eligible studies were included in the meta-analysis and the association between clinicopathological factors and hv-CLNM in cN0 PTMC was assessed. SPSS and MetaXL were used for statistical analyses.

RESULTS

The meta-analysis included 10 previous studies (11,734 patients) and 2268 patients enroled in our hospital for a total of 14,002 subjects. The results of which suggested that younger age (<40, odds ratio [OR] = 3.28, 95% confidence interval [CI] = 2.75-3.92, p < .001 or <45 odds ratio [OR] = 2.93, 95% CI = 2.31-3.72, p < .001), male sex (OR = 2.81, 95% CI = 2.25-3.52, p < .001), tumour size >5 mm (OR = 1.85, 95% CI = 1.39-2.47, p < .001), multifocality (OR = 1.88, 95% CI = 1.56-2.26, p < .001), extrathyroidal extension (OR = 2.58, 95% CI = 2.02-3.30, p < .001), capsule invasion (OR = 2.02, 95% CI = 1.46-2.78, p < .001), microcalcification (OR = 3.25, 95% CI = 2.42-4.36, p < .001) and rich blood flow (OR = 1.65, 95% CI = 1.21-2.25, p = .002) were the significant factors related to an elevated hv-CLNM risk in cN0 PTMC patients. Hashimoto thyroiditis (OR = 0.76, 95% CI = 0.55-1.07, p = .114), irregular margin (versus regular margin, OR = 0.96, 95% CI = 0.68-1.33, p = .787) and hypoechoic (versus nonhypoechoic, OR = 1.27, 95% CI = 0.84-1.92, p = .261) showed no significant association with hv-CLNM.

CONCLUSIONS

Younger age, tumour size >5 mm, males, extrathyroidal extension, multifocality, microcalcification, capsular invasion, and rich blood flow were the significant clinicopathological risk factors for hv-CLNM risk in cN0 PTMC patients. These predictors may compensate for the sensitivity of imaging diagnosis in the preoperative period, thus helping in the effective identification of PTMCs with an invasive phenotype.

A retrospective study of papillary thyroid carcinoma: Hashimoto's thyroiditis as a protective biomarker for lymph node metastasis

PURPOSE

There is approximately 10%-50% of papillary thyroid carcinoma (PTC) patients with Hashimoto's thyroiditis (HT). In this research, we sought to better understand the role of HT in PTC progression as well as lymph node metastasis.

METHODS

It is a retrospective and cross-sectional study, and 4131 PTC patients who underwent thyroidectomy were finally enrolled. Chi-square test, univariate and multivariate logistic regression analyses were employed to evaluate both the risk factors and the critical roles of HT during PTC metastasis.

RESULT

In this cohort, 1555 patients (37.6%) were diagnosed with HT. According to multivariate analysis, male sex, high levels of TG and TPOAb, tumor extrathyroidal extension, maximum diameter >1 cm, and multifocality were independent risk factors for both central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM). In addition, age <55 years and smoking were risk factors for CLNM, while CLNM was one of the risk factors for LLNM. Furthermore, HT was suggested a valuable protective factor for both CLNM and LLNM. In patients with HT, the total number of central lymph nodes was higher, while the positive rate was lower. Compared with those without HT, age and sex did not predict CLNM and LLNM in patients with HT.

CONCLUSION

HT is considered a protective factor for both CLNM and LLNM in PTC. For patients with HT, surgeons should pay more attention to the preservation of parathyroid gland and the protection of recurrent laryngeal nerve due to less lymph node metastasis. Otherwise, radical operation is highly recommended.

Cervical lymph node metastasis prediction of postoperative papillary thyroid carcinoma before 131I therapy based on clinical and ultrasound characteristics

BACKGROUND

The status of lymph nodes is crucial to determine the dose of radioiodine-131(¹³¹I) for postoperative papillary thyroid carcinoma (PTC). We aimed to develop a nomogram for predicting residual and recurrent cervical lymph node metastasis (CLNM) in postoperative PTC before ¹³¹I therapy.

METHOD

Data from 612 postoperative PTC patients who underwent ¹³¹I therapy from May 2019 to December 2020 were retrospectively analyzed. Clinical and ultrasound features were collected. Univariate and multivariate logistic regression analyses were performed to determine the risk factors of CLNM. Receiver operating characteristic (ROC) analysis was used to weigh the discrimination of prediction models. To generate nomograms, models with high area under the curves (AUC) were selected. Bootstrap internal validation, calibration curves and decision curves were used to assess the prediction model's discrimination, calibration, and clinical usefulness.

RESULTS

A total of 18.79% (115/612) of postoperative PTC patients had CLNM. Univariate logistic regression analysis found serum thyroglobulin (Tg), serum thyroglobulin antibodies (TgAb), overall ultrasound diagnosis and seven ultrasound features (aspect transverse ratio, cystic change, microcalcification, mass hyperecho, echogenicity, lymphatic hilum structure and vascularity) were significantly associated with CLNM. Multivariate analysis revealed higher Tg, higher TgAb, positive overall ultrasound and ultrasound features such as aspect transverse ratio ≥ 2, microcalcification, heterogeneous echogenicity, absence of lymphatic hilum structure and abundant vascularity were independent risk factors for CLNM. ROC analysis showed the use of Tg and TgAb combined with ultrasound (AUC = 0.903 for "Tg+TgAb+Overall ultrasound" model, AUC = 0.921 for "Tg+TgAb+Seven ultrasound features" model) was superior to any single variant. Nomograms constructed for the above two models were validated internally and the C-index were 0.899 and 0.914, respectively. Calibration curves showed satisfied discrimination and calibration of the two nomograms. DCA also proved that the two nomograms were clinically useful.

CONCLUSION

Through the two accurate and easy-to-use nomograms, the possibility of CLNM can be objectively quantified before ¹³¹I therapy. Clinicians can use the nomograms to evaluate the status of lymph nodes in postoperative PTC patients and consider a higher dose of ¹³¹I for those with high scores.

Preoperative Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma: A Noninvasive Clinical Multimodal Radiomics (CMR) Nomogram Analysis

This study aimed to evaluate the feasibility of applying a clinical multimodal radiomics nomogram based on ultrasonography (US) and multiparametric magnetic resonance imaging (MRI) for the prediction of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) preoperatively. We performed retrospective evaluations of 133 patients with pathologically confirmed PTC, who were assigned to the training cohort and validation cohort (7 : 3), and extracted radiomics features from the preoperative US, T2-weighted (T2WI),diffusion-weighted (DWI), and contrast-enhanced T1-weighted (CE-T1WI) images. Optimal subsets were selected using minimum redundancy, maximum relevance, and recursive feature elimination in the support vector machine (SVM). For LNM prediction, the radiomics model was constructed by SVM, and Multi-Omics Graph cOnvolutional NETworks (MOGONET) was used for the effective classification of multiradiomics data. Multivariable logistic regression incorporating multiradiomics signatures and clinical risk factors was used to generate a nomogram, whose performance and clinical utility were assessed. Results showed that the nine most predictive features were separately selected from US, T2WI, DWI, and CE-T1WI images, and 18 features were selected in the combined model. The combined radiomics model showed better performance than models based on US, T2WI, DWI, and CE-T1WI. In a comparison of the combined radiomics and MOGONET model, receiver operating curve analysis showed that the area under the curve (AUC) value (95% CI) was 0.84 (0.76-0.93) and 0.84 (0.71-0.96) for the MOGONET model in the training and validation cohorts, respectively. The corresponding values (95% CI) for the combined radiomics model were 0.82 (0.74-0.90) and 0.77 (0.61-0.94), respectively. The MOGONET model had better performance and better prediction specificity compared with the combined radiomics model. The nomogram including the MOGONET signature showed a better predictive value (AUC: 0.81 vs. 0.88) in the training and validation (AUC: 0.74vs. 0.87) cohorts, as compared with the clinical model. Calibration curves showed good agreement in both cohorts. The applicability of the clinical multimodal radiomics (CMR) nomogram in clinical settings was validated by decision curve analysis. In patients with PTC, the CMR nomogram could improve the prediction of cervical LNM preoperatively and may be helpful in clinical decision-making.

A nomogram based on the risk factors of cervical lymph node metastasis in papillary thyroid carcinoma coexistent with Hashimoto's thyroiditis

OBJECTIVE

The purpose of this study was to explore the risk factors of cervical lymph node metastasis(LNM) in papillary thyroid carcinoma(PTC) coexistent with Hashimoto's thyroiditis(HT).

METHODS

The clinical data of patients who underwent thyroid operation between November 2016 and January 2020 in our hospital were analyzed retrospectively. The association between sonographic features and the risk factors of cervical LNM in PTC coexistent with HT was analyzed and a nomogram based on the risk factors was built.

RESULTS

Age, US features as calcification, blood flow type, distance between thyroid nodule and fibrous capsule were risk factors of cervical LNM(P < 0.05).Size, SWVmax and SWVmean of thyroid nodule, SWVratio between thyroid nodule and thyroid gland were higher in PTCs with LNM than those without LNM(P < 0.05). The ROC curve showed that the cutoff value of SWVratio for predicting LNM was 1.29 (Sensitivity = 0.806, Specificity = 0.775, AUC = 0.823, P < 0.001). Based on the risk factors above, a relevant nomogram prediction model was established. The model verification showed that the C-index of the modeling set was 0.814, indicating that the nomogram model had good predicted accuracy.

CONCLUSION

Based on the risk factors above, a relevant nomogram prediction model was established. The model verification showed that the C-index of the modeling set was 0.814, indicating that the nomogram model had good predicted accuracy. The nomogram based on the risk factors above had good prediction ability, which could optimize thyroidectomy and cervical lymph node dissection and improving prognosis.

Incorporation size of lymph node metastasis focus and pre-ablation stimulated Tg could more effectively predict clinical outcomes in differentiated thyroid cancer patients without distant metastases

BACKGROUND

The size of lymph node metastasis (LNM) and pre-ablation stimulated Tg (ps-Tg) were key predictors of clinical prognosis in differentiated thyroid cancer (DTC) patients, however, very few studies combine the above two as predictors of clinical prognosis of DTC patients.

METHODS

Persistent/recurrent disease and clinicopathologic factors were analyzed in 543 DTC patients without distant metastases who underwent LN dissection, near-total/total thyroidectomy, and radioiodine ablation.

RESULTS

In the multivariate analysis, size of LNM, ps-Tg, and the activity of ¹³¹I significantly correlated with long-term remission. The optimal cutoff size of LNM 0.4 cm-1.4 cm (intermediate-risk patients) and >1.4cm (high-risk patients) increased the recurrence risk (hazard ratio [95% CI], 4.674 [2.881-7.583] and 13.653 [8.135-22.913], respectively). Integration of ps-Tg into the reclassification risk stratification showed that ps-Tg ≤ 10.0 ng/mL was relevant to a greatly heightened possibility of long-term remission (92.2%-95.4% in low-risk patients, 67.3%-87.0% in intermediate-risk patients, and 32.3%-57.7% in high-risk patients).

CONCLUSION

The cutoff of 0.4 cm and 1.4 cm for a definition of size of LNM in DTC patients without distant metastases can reclassify risk assessment, and incorporating ps-Tg could more effectively predict clinical outcomes and modify the postoperative management plan.

Developing and validating a multivariable machine learning model for the preoperative prediction of lateral lymph node metastasis of papillary thyroid cancer

Background

At present, preoperative diagnosis of lateral cervical lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) mostly depends on the training and expertise of ultrasound doctors. A machine-learning model for predicting LLNM accurately before PTC surgery may help to determine the scope of surgery and reduce unnecessary surgical trauma.

Methods

The data of patients with primary PTC who underwent thyroidectomy with lateral cervical lymph node surgery at Beijing Tongren Hospital between July 2009 and June 2021 were retrospectively analyzed. All patients had complete ultrasonic examination, clinical data, and definite pathology diagnosis of lymph nodes. LLNM was confirmed by postoperative pathology. The patients were randomly divided into a training set (155 cases) and a test set (98 cases) at a ratio of 6:4. Eleven parameters, including patient demographics, ultrasound results, and tumor-related conditions, were collected, and a prediction model was established using the support vector machine (SVM) algorithm. Several other machine-learning algorithms were also used to establish models for comparison. The accuracy, precision, recall, F1-score, sensitivity, specificity, Cohen's kappa value, and area under the receiver operating characteristic curve (AUC) were used to evaluate model performance.

Results

A total of 87 males and 156 females were included in the study, aged 14-80 years. One hundred and four patients of them had LLNM and 139 did not have LLNM. The pandas Python library was used for the statistical analysis, and the Spearman coefficient was used to analyze the correlation between each parameter and the prediction index. The SVM model performed the best among all the models. Its accuracy, precision, recall, F1-score, sensitivity, specificity, Cohen's kappa value, and AUC were 90.8%, 91.0%, 90.8%, 90.8%, 87.5%, 94.0%, 81.6%, and 91.0%, respectively.

Conclusions

This model can enable surgeons to improve the accuracy of ultrasonography in predicting LLNM without additional examination, thus avoiding missing positive lateral cervical lymph nodes and reducing the sequelae caused by unnecessary lateral neck dissection.

Fibrinogen-to-Neutrophil Ratio as a New Predictor of Central Lymph Node Metastasis in Patients with Papillary Thyroid Cancer and Type 2 Diabetes Mellitus

Background

Many patients have a higher risk of thyroid cancer if they have both papillary thyroid carcinoma (PTC) and Type 2 diabetes mellitus (T2DM). Meanwhile, the primary reason for local PTC recurrence is cervical lymph node metastasis. Therefore, the prognosis of patients affects how cervical lymph nodes are managed during surgery. Due to surgical complications such as laryngeal nerve palsy and hypocalcemia, it is still debatable whether to prevent central lymph node dissection (CLND). Predicting central lymph node metastasis (CLNM) is crucial to direct CLND. It is unclear how important the fibrinogen-to-neutrophil ratio (FNR) is in thyroid cancer, so we looked into how it might help patients with PTC and T2DM predict CLNM.

Patients and methods

Wenzhou Medical University's First Affiliated Hospital provided us with 413 patients with PTC and T2DM, randomly divided into a training set (N = 292) and a validation set (N = 121). Univariate and multivariate logistic regression analyses were used to identify independent risk factors. After constructing a nomogram, the validity of the model was evaluated.

Results

The maximum tumor diameter, high-density lipoprotein, thyroxine, triglyceride, lymphocyte, and FNR were all identified as independent risk factors by multivariate logistic regression analysis. The C index of the training set was 0.775, and the validation set was 0.654.

Conclusion

In patients with PTC and T2DM, preoperative FNR was an independent risk factor for CLNM.

Risk stratification of lateral neck recurrence for patients with pN1a papillary thyroid cancer

BACKGROUND

Lateral neck is not recommended for dissection in patients with pN1a papillary thyroid cancer (PTC), but its recurrence risk has not been well stratified. We aimed to develop a risk stratification system for lateral neck recurrence in patients with pN1a PTC.

METHODS

Patients with pN1a PTC who underwent thyroidectomy and unilateral central compartment dissection from 2000-2016 were enrolled. The association between number of central lymph node metastases (CLNMs) and lateral neck recurrence was comprehensively assessed using a Cox proportional hazards model with restricted cubic spline. Stratification was then performed based on CLNMs and other significant risk factors selected by multivariate analysis. Lateral neck recurrent-free survival (LRFS) rate of each stratification was estimated with Kaplan-Meier curve and comparison was performed using log-rank test.

RESULTS

Ninety-six (3.8%) lateral neck recurrences were identified during a median follow-up of 62 months among a total of 2500 admitted cases. An increasing number of CLNMs was associated with compromised LRFS for up to 6 CLNMs (P < 0.001), and CLNMs > 3 indicated significantly worse 5-year LRFS than that of CLNM ≤ 3 (90.6% vs. 98.1%, P < 0.001). When stratification with CLNMs and primary tumor size (selected by multivariate analysis, HR (95%CI) = 4.225(2.460-7.256), P < 0.001), 5-year LRFS rates of high- (CLNMs > 3 and primary tumor size > 2 cm), intermediate- (CLNMs > 3 and primary tumor size 1-2 cm) and low-risk (primary tumor size ≤ 1 cm or CLNMs ≤ 3) groups were 78.5%, 90.0% and 97.9%, respectively (P < 0.05).

CONCLUSIONS

The number of CLNMs combined with primary tumor size seems to effectively stratify lateral neck recurrence risk for patients with pN1a PTC.

Construction of a novel cuproptosis-related gene signature for predicting prognosis and estimating tumor immune microenvironment status in papillary thyroid carcinoma

BACKGROUND

Cuproptosis, a new form of programmed cell death, has been recently reported to be closely related to tumor progression. However, the significance of cuproptosis-related genes (CRGs) in papillary thyroid carcinoma (PTC) is still unclear. Therefore, this study aimed to investigate the role of the CRG signature in prognosis prediction and immunotherapeutic effect estimation in patients with PTC.

METHODS

RNA-seq data and the corresponding clinical information of patients with PTC were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Comprehensive analyses, namely, consensus clustering, immune analyses, functional enrichment, least absolute shrinkage and selection operator-multivariate Cox regression, and nomogram analysis, were performed to identify new molecular subgroups, determine the tumor immune microenvironment (TIME) status of the identified subgroups, and construct a clinical model. Independent verification cohort data and quantitative real-time polymerase chain reaction (qPCR) was performed to validate the expression of specific prognosis-related and differentially expressed CRGs (P-DECRGs).

RESULTS

In the TCGA database, 476 patients with PTC who had complete clinical and follow-up information were included. Among 135 CRGs, 21 were identified as P-DECRGs. Two molecular subgroups with significantly different disease-free survival and TIME statuses were identified based on these 21 P-DECRGs. The differentially expressed genes between the two subgroups were mainly associated with immune regulation. The risk model and nomogram were constructed based on four specific P-DECRGs and validated as accurate prognostic predictions and TIME status estimation for PTC by TCGA and GEO verification cohorts. Finally, the qPCR results of 20 PTC and paracancerous thyroid tissues validated those in the TCGA database.

CONCLUSIONS

Four specific P-DECRGs in PTC were identified, and a clinical model based on them was established, which may be helpful for individualized immunotherapeutic strategies and prognostic prediction in patients with PTC.

Effects of Patient and Tumor Characteristics on Central Lymph Node Metastasis in Papillary Thyroid Cancer: A Guide for Selective Node Dissection

BACKGROUND

Prophylactic central lymph node dissection (CLND) in papillary thyroid carcinoma (PTC) is still controversial. This study aimed to analyze the factors related to the patient and tumor characteristics affecting central lymph node metastasis (CLNM) in PTC patients and to evaluate the contribution of the results to shaping the surgical treatment algorithm.

METHODS

Two hundred and fifty-five PTC patients who underwent total thyroidectomy and CLND were evaluated retrospectively. Histopathology reports were examined to reveal tumor characteristics. The CLNM ratio and the relationship between CLNM with clinicopathological and demographic characteristics were analyzed.

RESULTS

The incidence of CLNM was 54.9% (95 CI%: 49-60.8). Male gender (P=0.027), age<45 years (P=0.016), tumor size≥9.5 mm (P<0.001), lymphovascular invasion (P<0001) and extracapsular invasion (P=0.007) were factors that increased the risk of metastasis. The follicular variant decreased the risk (P=0.010). There was no relationship between CLNM and focality (P=0.054). A low-to-moderate correlation was found between tumor diameter and the metastatic lymph node (MLN) number/total lymph node number ratio (r=0.396, P<0.001).

CONCLUSION

A selective prophylactic CLND strategy can be applied in cN0 patients. As the tumor diameter increases in PTC, both the risk of CLNM and the number of MLN increase. Lymphovascular and extracapsular invasion are other factors that increase the risk. The follicular variant is associated with a lower risk of CLNM. Male patients who are under the age of 45 and have a tumor diameter of 9.5 mm or more are definite candidates for prophylactic CLND.

A protective factor against lymph node metastasis of papillary thyroid cancer: Female gender

OBJECTIVE

Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer, with good prognosis, but the rate of lymph node metastasis (LNM) is high, and the difference between men and women is significant. Therefore, the related risk factors for LNM of PTC based on gender were examined in this study in order to draw attention to gender factor in PTC.

METHODS

We retrospectively analyzed the clinicopathological data of 2103 patients with surgically confirmed PTC at the Fourth affiliated Hospital of Hebei Medical University West Side between January 2016 and December 2019.

RESULTS

LNM was detected in 1124 of the 2103 cases of PTC. Logistic regression analysis showed that LNM was associated with age (p < 0.001, OR:0.547), gender (p < 0.001, OR:2.609), tumor diameter (p < 0.001, OR:2.995), bilaterality (p=0.003, OR:1.683), and extrathyroid extension (p < 0.001, OR:1.657). After propensity score matching, female gender (p < 0.001, OR: 0.393) remained an independent factor of LNM in patients with PTC. LNM in men was only associated with diameter (p < 0.001, OR: 3.246). LNM in woman was associated with menopausal history (p = 0.012, OR=0.684), reproductive history (p < 0.001, OR=0.360), abortion history (p = 0.011, OR=0.725), tumor diameter >1 cm (p < 0.001, OR=2.807), bilaterality (p =0.006, OR:1.728), and extrathyroid extension (p < 0.001, OR=1.879).

CONCLUSION

Although the invasion is high in female patients, the rate of LNM is significantly reduced due to the influence of sex hormones and reproductive factors. For female patients of childbearing age who were not pregnant and did not have children, it is suggested to take a positive attitude towards their lymph nodes.

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

Background

Lateral lymph node metastasis (LLNM) is a risk factor of poor prognosis in papillary thyroid cancer (PTC). We aimed to determine predictive factors and develop the nomograms for LLNM in patients with papillary thyroid microcarcinoma (PTMC) and macro-PTC.

Methods

We reviewed the medical records of 1,106 patients who underwent surgery between January 2019 and January 2022. Patients were divided into a PTMC and a macro-PTC group. We developed preoperative and postoperative nomograms for predicting LLNM based on results of multivariate analysis. Internal calibration was performed for these models.

Results

The number of metastatic lymph nodes in lateral compartment was higher in macro-PTC patients. LLNM was independently associated with gender, the number of foci, location, shape, and central lymph node metastasis (CLNM) in PTMC patients. For macro-PTC patients, chronic lymphocytic thyroiditis, the number of foci, location, margin, CLNM, and central lymph node ratio were all independent predictors for LLNM. All the above factors were incorporated into nomograms, which showed the perfect discriminative ability.

Conclusion

The diameter of the tumor has an impact on the rate of LLNM. Separate predictive systems should be used for PTMC and macro-PTC patients for more accurate clinical assessment of lateral lymph node status. Through these nomograms, we can not only detect high-risk patients with occult LLNM preoperatively, but also form appropriate treatment protocols for postoperative management of PTC patients with different risks.

Effect of skip metastasis to lateral neck lymph nodes on outcome of patients with papillary thyroid carcinoma

CONTEXT

Lymph node metastasis (N1) is a prognostic factor for disease recurrence in papillary thyroid carcinoma (PTC) patients. Skip metastasis is defined as only lateral N1 with negative central lymph nodes (LNs).

OBJECTIVE

The aim of this study was to explore the outcome of PTC patients with skip N1.

PATIENTS AND DESIGN

All patients who underwent a total thyroidectomy with ipsilateral central and lateral LN dissection for PTC from 1999 to 2019 in a high-volume endocrine surgery centre were included in this study.

MAIN OUTCOME MEASURE

Demographic and outcomes-recurrence and disease-specific survival (DSS)-were compared between three groups: N1a (central N1 only), N1b-CL (central and lateral N1), and N1b-Skip (lateral N1 without central LN involvement).

RESULTS

During the study period, 3046 patients had surgery for PTC, including 1138 with N1 (37%, 860 women, mean age: 44.8 years) comprising 474 N1a (42%), 513 N1b-CL (45%), and 151 N1b-Skip (13%). The median follow-up was 74 months (range 12-216 months). The recurrence rate in the N1b-Skip group was 13% (20/151) and 10% (47/474) in the N1a group. This was significantly lower than that in the N1b-CL group (27%, 140/513) (p < 0.0001). DSS at 10 years was 99% for group N1a, 98% for the N1b-CL, and 99% in the N1b-Skip group.

CONCLUSION

The recurrence rate of N1b-Skip patients was lower than that of N1b-CL patients and similar to that of N1a patients. This result could be used as an indication for the modality of radioiodine therapy, and for the pattern of follow-up procedures.

[Risk factors of skip lateral cervical lymph node metastasis in papillary thyroid carcinoma]

Objective:To investigate the incidence and risk factors of skip lateral cervical lymph node metastasis in patients with papillary thyroid carcinoma（PTC）. Methods:The clinical and pathological data of 85 patients with PTC who underwent total thyroidectomy plus central and lateral neck dissection in the Department of Otolaryngology Head and Neck Surgery, the First Affiliated Hospital of Hebei North University from January 2018 to January 2022 were analyzed retrospectively. SPSS 26.0 software was used to process the data, and univariate and multivariate analysis were performed to assess the relationships between skip lateral cervical lymph node metastasis and clinicopathological characteristics. Results:There were 31 cases（36.5%） of skipped lateral cervical lymph node metastasis. Univariate analysis showed that the largest tumor diameter ≤5 mm（P=0.006） and the tumor located in the upper pole of the thyroid（P=0.002） were associated with the occurrence of skip lateral cervical lymph node metastasis in patients with PTC. Most of the skip metastases involved a single area（18/31, 58.1%）, of which area Ⅲ was most likely to be involved（10/31, 32.3%）, followed by area Ⅱ（5/31, 16.1%）. The results of binary logistic analysis showed that tumor diameter less than 5 mm（OR 7.800, 95%CI 1.710-21.394, P=0.005） and tumor at the upper pole of the gland（OR 4.060, 95%CI 1.468-11.235, P=0.007） were independent risk factors of skip lateral cervical lymph node metastasis in PTC patients. Conclusion:PTC patients with tumor diameter ≤5 mm and tumor located in the upper pole of the gland are more prone to skip lateral cervical lymph node metastasis. When the diameter of the tumor is less than 5 mm and the tumor is located at the upper pole of the gland, careful evaluation should be made before operation, even in the absence of central lymph node metastasis, attention should be paid to the possibility of lateral cervical lymph node metastasis.

Thyroid papillary carcinoma with the 'snowstorm appearance': a clinicopathological analysis of three cases

This current case report presents the detailed clinicopathological analysis of three patients with papillary thyroid carcinoma, each of which presented with the ‘snowstorm appearance’ on ultrasonography. Ultrasonography of this tumour typically shows a diffusely enlarged thyroid with hypoechoic and heterogeneous internal echoes, and diffusely scattered microcalcifications, which form the ‘snowstorm appearance’. Microscopically, case 1 had a large number of psammoma bodies, infiltration of lymphocytes, formation of lymphatic follicles and extensive squamous metaplasia, leading to the diagnosis of a diffuse sclerosing variant of papillary thyroid carcinoma (DSVPTC). Case 2 was diagnosed with follicular papillary thyroid carcinoma. Their tumour had numerous calcifications in the stroma and follicles. Case 3 was diagnosed with a multifocal papillary thyroid carcinoma in the background of Hashimoto's thyroiditis. Their tumour showed calcification in the stroma and follicles, together with cervical lymph node metastasis. DSVPTC is a rare variant of thyroid papillary carcinoma. It has the ‘snowstorm appearance’ on ultrasound, but this can also be found in follicular papillary carcinoma and multifocal thyroid papillary carcinoma. Papillary thyroid carcinoma with the ‘snowstorm appearance’ has a large number of peripheral lymph nodes metastases, thus requiring radical surgery and postoperative adjuvant therapy.

The optimal extent of lymph node dissection in N1b papillary thyroid microcarcinoma based on clinicopathological factors and preoperative ultrasonography

BACKGROUND

The optimal extent of lymph node (LN) dissection in the management of N1b papillary thyroid microcarcinoma (PTMC) is still under debate in clinical practice, so we aimed to identify the risk factors associated with multilevel lateral lymph node metastasis (LLNM) with regard to the extent of LN dissection.

METHODS

The clinical data of 182 N1b PTMC patients between January 2019 and June 2021 at Tianjin Medical University Cancer Institute and Hospital were retrospectively reviewed. The frequency pattern and distribution of LLNM were analyzed for risk factors. We assessed the diagnostic value of preoperative ultrasonography (USG) for identifying levels II-V metastasis in PTMC patients.

RESULTS

The proportion of multilevel LLNM in N1b PTMC was 72.1%, and the most common pattern was metastasis at two levels (41.2%). Capsule invasion [odds ratio (OR) =6.861, 95% confidence interval (CI): 1.462-32.190, P=0.015], upper pole [OR =2.125, 95% CI: 1.010-4.473, P=0.047], central LN ratio [OR =7.315, 95% CI: 1.309-40.877, P=0.023], thyroid-stimulating hormone (TSH) >1.5 mIU/mL [OR =2.773, 95% CI: 1.269-6.060, P=0.011], and extranodal extension (ENE) [OR =2.632, 95% CI: 1.207-5.739, P=0.015] were independent risk factors for multilevel metastasis. In addition, unltrasonography had high sensitivity and specificity in the diagnosis of metastasis at level V (75.0%, 78.4%) and multilevel LLNM (67.2%, 64.8%).

CONCLUSIONS

Modified radical neck dissection (MRND) in N1b PTMC patients may be reserved for patients with simultaneous 3-level LLNM or clinically evident metastasis at level V. Preoperative USG may have certain suggestive significance in the diagnosis of multilevel LLNM in primary PTMC.

The Prognosis of Skip Metastasis in Papillary Thyroid Microcarcinoma Is Better Than That of Continuous Metastasis

CONTEXT

A few papillary thyroid microcarcinomas (PTMCs) may have skip metastasis (SLNM), but the risk factors remain controversial and the prognosis is unclear.

OBJECTIVES

To investigate the incidence, lymph node metastasis (LNM) patterns, risk factors, and prognosis of SLNM in PTMCs.

METHODS

We reviewed the medical records of PTMC patients who underwent thyroid surgery in our institution. Analyses of risk factors were performed for SLNM. Recurrence-free survival (RFS) of SLNM, central lymph node metastasis (CLNM), and continuous metastasis (CLNM and lateral lymph node metastasis [CLNM + LLNM]) were compared after propensity score matching (PSM).

RESULTS

SLNM was detected in 1.7% (50/3923) and frequently involved level III (66.7%). Compared with CLNM + LLNM, SLNM had more LNM at a single level (P < 0.01) and less LNM at 2 levels (P < 0.05). A tumor size of 0.5 to 1 cm (odds ratio [OR], 2.26; 95% CI, 1.27-4.00) and location in the upper pole (OR, 3.30; 95% CI, 2.02-5.40) were independent risk factors for SLNM. A total of 910 (23.2%) PTMCs with LNM were included in the prognostic analysis. At a median follow-up of 60 months, the RFS of SLNM did not differ from that of CLNM (P = 0.10) but was significantly higher than that of CLNM + LLNM (P < 0.01) after using PSM.

CONCLUSIONS

When the tumor size is 0.5 to 1 cm or its location is in the upper pole, we must remain vigilant to SLNM in PTMC. Because its prognosis is comparable to that of only CLNM and better than that of CLNM + LLNM, less intensive treatment should be considered.

Relationship between subgroups of central and lateral lymph node metastasis in clinically node-negative papillary thyroid carcinoma

BACKGROUND

Lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) has a certain regularity and occurs first to the central lymph node and then to the lateral lymph node. The pathway of PTC LNM can guide surgical prophylactic lymph node dissection (LND) for clinical surgeons.

AIM

To investigate the relationship between subgroups of central LNM and lateral LNM in unilateral clinically node-negative PTC (cN0-PTC).

METHODS

Data were collected for 1089 PTC patients who underwent surgical treatment at the Department of Endocrine and Breast Surgery of the First Hospital of Chongqing Medical University from January 2016 to December 2017. A total of 388 unilateral cN0-PTC patients met the inclusion criteria and were enrolled in this study. The clinical and pathological data for these 388 patients who underwent total thyroidectomy + central LND + lateral LND were retrospectively analyzed. The relationship between the central LNM and lateral LNM subgroups was investigated.

RESULTS

The coincidence rate of cN0-PTC was only 30.0%.Optimal scaling regression analysis showed that sex (57.1% vs 42.9%, P = 0.026), primary tumor size (68.8% vs 31.2%, P = 0.008), tumor location (59.7% vs 40.3%, P = 0.007), extrathyroid extension (ETE) (50.6% vs 49.9%, P = 0.046), and prelaryngeal LNM (57.1% vs 42.9%, P = 0.004) were significantly associated with ipsilateral level-II LNM. Their importance levels were 0.122, 0.213, 0.172, 0.110, and 0.227, respectively. Primary tumor size (74.6% vs 30.2%, P = 0.016), pretracheal LNM (67.5% vs 32.5%, P < 0.001), and paratracheal LNM (71.4% vs 28.6%, P < 0.001) were significantly associated with ipsilateral level-III LNM. Their importance levels were 0.120, 0.408, and 0.351, respectively. Primary tumor size (72.1% vs 27.9%, P = 0.003), ETE (70.4% vs 29.6%, P = 0.016), pretracheal LNM (68.3% vs 31.7%, P=0.001), and paratracheal LNM (80.8% vs 19.2%, P < 0.001) were significantly associated with ipsilateral level-IV LNM. Their importance levels were 0.164, 0.146, 0.216, and 0.472, respectively.

CONCLUSION

The LNM pathway of thyroid cancer has a certain regularity. For unilateral cN0-PTC patients with a tumor diameter > 2 cm and pretracheal or ipsilateral paratracheal LNM, LND at ipsilateral level III and level IV must be considered. When there is a tumor in the upper third of the thyroid with prelaryngeal LNM, LND at level II, level III and level IV must be considered.

Glucose-to-Lymphocyte Ratio (GLR) as a Predictor of Preoperative Central Lymph Node Metastasis in Papillary Thyroid Cancer Patients With Type 2 Diabetes Mellitus and Construction of the Nomogram

Background

Detection of metastasis of central lymph nodes in papillary thyroid cancer is difficult before surgery. The role of routine or preventive central lymph node dissection in the management of papillary thyroid cancer remains inconclusive. Moreover, glucose metabolism and systemic inflammation are related to the aggressiveness of several malignant tumors and the prognoses of these patients. This study aimed to construct a nomogram based on the readily available preoperative clinical features for predicting the occurrence of preoperative central lymph node metastasis in patients with papillary thyroid cancer and type 2 diabetes mellitus. The findings may underlie clinical implications for determining the appropriate treatment strategies for these patients.

Methods

A total of 419 patients were enrolled. We used the receiver operating characteristic curves to determine the best cut-off value and converted the continuous into categorical variables. Next, a single-factor logistic analysis for the independent variables was performed, following which a multivariate regression analysis was conducted for the selected significant risk factors. Finally, the nomogram was constructed and verified using external data; the existing data were compared with the original model.

Results

According to the receiver operating characteristic curves, the best cut-off values ​​for glucose-to-lymphocyte ratio and tumor size were 4.23 cm and 0.95 cm, respectively. Findings from the multivariate logistic regression analysis suggested that age, bilateral tumors, maximum tumor size, and the ratio of glucose-to-lymphocytes were independent risk factors for preoperative central lymph node metastasis. The C-indexes in the training and the external validation data sets were 0.733 and 0.664, respectively. Both calibration curves and the Hosmer-Lemeshow tests indicated that the model was well-calibrated. Through decision curve analysis, the predictive model was estimated to have strong clinical applicability and greater benefits. To compare the performance of the new with that of the original model, we performed a net reclassification index and the integrated discrimination improvement analyses, both of which indicated that the new model had a better predictive ability.

Conclusion

In patients with type 2 diabetes mellitus and papillary thyroid cancer, a high preoperative glucose-to-lymphocyte ratio was an independent predictor of the preoperative central lymph node metastasis. The nomogram so constructed could better predict the preoperative central lymph node metastasis in these patients.

Clinical Factors Predictive of Lymph Node Metastasis in Thyroid Cancer Patients: A Multivariate Analysis

BACKGROUND

Early-stage thyroid cancers have excellent survival. However, lymph node metastases (LNM) confer a worse prognosis and are not always known preoperatively. Therefore, investigation on the clinical and histological factors predictive of LNM in thyroid cancers was conducted to tailor the extent of surgery and radioactive iodine therapy.

STUDY DESIGN

Multivariate logistic regressions were performed based on retrospective data from thyroid cancer patients seen between 2013 and 2020 at a single institution.

RESULTS

Among 913 patients, mean age was 49.4 years, 76.5% were female, 58.3% were White, 21.2% were Black, and 27.9% had LNM. In the multivariate analyses in which the outcome was LNM, White (odds ratio [OR] 1.74, 95% CI 0.98 to 3.15, p = 0.064) and Hispanic patients (OR 2.36, 95% CI 0.97 to 5.77, p = 0.059) trended toward higher risk of LNM compared to Black patients, whereas age (OR 0.98, 95% CI 0.97 to 1.00, p = 0.008) showed protective effect. Tumor size (OR 1.04, 95% CI 1.01 to 1.07, p = 0.007), extrathyroidal extension (OR 2.46, 95% CI 1.53 to 3.97, p < 0.001), lymphovascular invasion (OR 6.30, 95% CI 3.68 to 11.14, p < 0.001), and multifocality (OR 1.47, 95% CI 1.01 to 2.12, p = 0.042) were associated with higher risk of LNM. In another model with outcome as >5 LNM, tumor size (OR 1.07, 95% CI 1.03 to 1.11, p = 0.001), age (OR 0.95, 95% CI 0.93 to 0.97, p < 0.001), extrathyroidal extension (OR 3.20, 95% CI 1.83 to 5.61, p < 0.001), and lymphovascular invasion (OR 6.82, 95% CI 3.87 to 12.17, p < 0.001) remained significant predictors.

CONCLUSION

Our analyses demonstrated and confirmed that age, tumor size, extrathyroidal extension, and lymphovascular invasion are independent predictors of significant LNM, thereby conferring higher risk of recurrence. Risk of LNM based on these patient characteristics should be considered when planning an operative approach.

Preoperative Prediction of Central Cervical Lymph Node Metastasis in Fine-Needle Aspiration Reporting Suspicious Papillary Thyroid Cancer or Papillary Thyroid Cancer Without Lateral Neck Metastasis

Purpose

No non-invasive method can accurately determine the presence of central cervical lymph node (CCLN) metastasis in papillary thyroid cancer (PTC) until now. This study aimed to investigate factors significantly associated with CCLN metastasis and then develop a model to preoperatively predict CCLN metastasis in fine-needle aspiration (FNA) reporting suspicious papillary thyroid cancer (PTC) or PTC without lateral neck metastasis.

Patients and Methods

Consecutive inpatients who were diagnosed as suspicious PTC or PTC in FNA and underwent partial or total thyroidectomy and CCLN dissection between May 1^st, 2016 and June 30^th, 2018 were included. The total eligible patients were randomly divided into a training set and an internal validation set with the ratio of 7:3. Univariate analysis and multivariate analysis were conducted in the training set to investigate factors associated with CCLN metastasis. The predicting model was built with factors significantly correlated with CCLN metastasis and validated in the validation set.

Results

A total of 770 patients were eligible in this study. Among them, 268 patients had histologically confirmed CCLN metastasis, while the remaining patients did not. Factors including age, BRAF mutation, multifocality, size, and capsule involvement were found to be significantly correlated with the CCLN metastasis in univariate and multivariate analysis. A model used to predict the presence CCLN metastasis based on these factors and US CCLN status yielded AUC, sensitivity, specificity and accuracy of 0.933 (95%CI: 0.905-0.960, p < 0.001), 0.816, 0.966 and 0.914 in the training set and 0.967 (95%CI: 0.943-0.991, p < 0.001), 0.897, 0.959 and 0.936 in the internal validation set.

Conclusion

Age, BRAF mutation, multifocality, size, and capsule involvement were independent predictors of CCLN metastasis in FNA reporting suspicious PTC or PTC without lateral neck metastasis. A simple model was successfully built and showed excellent discrimination to distinguish patients with or without CCLN metastasis.

Papillary thyroid cancer: the value of bilateral diagnostic lymphadenectomy

Purpose

Papillary thyroid carcinoma (PTC) spreads early to lymph nodes (LN). However, prophylactic central (CND) and lateral neck dissection (LND) is controversially discussed in patients with clinically negative nodes (cN0). The preoperative prediction of LN metastasis is desirable as re-operation is associated with higher morbidity and poor prognosis. The study aims to analyse possible benefits of a systemic bilateral diagnostic lateral lymphadenectomy (DLL) for intraoperative LN staging.

Methods

Preoperative prediction of LN metastasis by conventional ultrasound (US) was correlated with the results of DLL and intra-/postoperative complications in 118 consecutive patients with PTC (cN0) undergoing initial thyroidectomy and bilateral CND and DLL.

Results

Lateral LNs (pN1b) were positive in 43/118 (36.4%) patients, including skip lesions (n = 6; 14.0%). Preoperative US and intraoperative DLL suspected lateral LN metastasis in 19/236 (TP: 8.1%) and 54/236 (TP: 22.9%) sides at risk, which were confirmed by histology. Sixty-seven out of 236 (FN: 28.4%) and 32/236 (FN: 13.6%) sides at risk with negative preoperative US and intraoperative DLL lateral LN metastasis were documented. DLL was significantly superior compared to US regarding sensitivity (62.8% vs 22.1%; p < 0.002), positive predictive value (100% vs 76.0%), negative predictive value (82.4% vs 68.2%), and accuracy (86.4% vs 69.1%), but not specificity (100% vs 96.0%; p = 0.039). DLL-related complications (haematoma) occurred in 6/236 [2.5%] sides at risk, including chylous fistula in 2/118 [1.7%] patients.

Conclusion

DLL can be recommended for LN staging during initial surgery in patients with PTC to detect occult lateral LN metastasis not suspected by US in order to plan lateral LN dissection.

Radiomics from Primary Tumor on Dual-Energy CT Derived Iodine Maps can Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer

RATIONALE AND OBJECTIVES

To develop and validate 2 iodine maps based radiomics nomograms for preoperatively predicting cervical lymph node metastasis (LNM) and central lymph node metastasis (CLNM) in papillary thyroid cancer (PTC).

MATERIALS AND METHODS

A total of 346 patients with PTC were enrolled and allocated to training (242) and validation (104) sets. Radiomics features were extracted from arterial and venous phase iodine maps, respectively. Aggregated machine-learning strategy was applied for features selection and construction of 2 radiomics scores (LN rad-score; CLN rad-score). Logistic regression model was employed to establish two radiomics nomograms (nomogram 1: predicting LNM; nomogram 2: predicting CLNM) after incorporating LN or CLN rad-score with clinical predictors. Nomograms performance was determined by discrimination, calibration and clinical usefulness.

RESULTS

Nomogram 1 incorporated LN rad-score, age (categorized by 55) and CT reported LN status; Nomogram 2 incorporated CLN rad-score, capsule contact >25% and CT reported CLN status. 2 nomograms both showed good discrimination and calibration in the training (AUC = 0.847; AUC = 0.837) and validation cohorts (AUC = 0.807; AUC = 0.795). Significant improved AUC, net reclassification index (NRI) and integrated discriminatory improvement (IDI) confirmed additional great predictive value of 2 rad-scores, compared with clinical models without radiomics. Decision curve analysis indicated clinical utility of nomograms. 2 nomograms both demonstrated favorable predictive efficacy in CT reported LN or CLN negative subgroup (AUC = 0.766; AUC = 0.744).

CONCLUSION

The presented 2 radiomics nomograms are useful tools for preoperative prediction of LNM and CLNM in PTC.

Prophylactic central lymph node dissection performed selectively with cN0 papillary thyroid carcinoma according to a risk-scoring model

BACKGROUND

This study aimed to explore the risk factors of central lymph node metastasis (CLNM) in patients with clinical central lymph node-negative papillary thyroid carcinoma (PTC), and emphasize the guidance of the risk scoring model for prophylactic central lymph node dissection (pCLND) in patients with clinical lymph node-negative (cN0) PTC.

METHODS

A total of 582 patients with cN0 PTC who underwent unilateral/bilateral thyroidectomy and prophylactic central lymph node dissection (pCLND) in the Affiliated Hospital of Nantong University from January 2020 to February 2021 were retrospectively analyzed. Univariate and multivariate analyses were performed to determine the risk factors of cN0 PTC. According to the independent risk factors of patients with cN0 PTC, a risk-scoring model was established. Then, the rationality of this risk scoring model was verified by additional clinical data of 112 patients with cN0 PTC in the Affiliated Hospital of Nantong University from March 2021 to April 2021.

RESULTS

Among 582 cases of cN0 PTC, 53.6% of the patients with cN0 had CLNM. The independent risk factors for CLNM in patients with cN0 PTC included male gender, <45 years of age, tumor with a maximum diameter of ≥1.0 cm, tumor location: middle/lower poles of the thyroid gland, multifocality, and extrathyroidal extension (ETE), and some ultrasound features, such as intra-nodular vascularity, microcalcification, irregular shape, and infiltrative margin. According to independent risk factors, a 24-point risk scoring model was established to predict CLNM in patients with cN0 PTC.

CONCLUSIONS

Currently, prophylactic central neck lymph node dissection is a controversial operation, which should be selectively performed only for high-risk patients with cN0 PTC. For cN0 PTC patients with scores ≥14 and high-risk patients, even if no CLNM is found before surgery, routine prophylactic CLND is recommended. In addition, for cN0 PTC patients with a score of fewer than 14 points, it is recommended to perform fine-needle aspiration (FNA) before surgery, carefully assess the condition of the central lymph nodes, and then select the best surgical plan based on the results of the assessment.

Value of thyroglobulin combined with ultrasound-guided fine-needle aspiration cytology for diagnosis of lymph node metastasis of thyroid carcinoma

BACKGROUND

Surgery for thyroid carcinoma offers a good prognosis; however, cervical lymph node metastasis may occur in the early stage. An effective diagnostic method can accurately guide clinical surgical planning and the scope of lymph node dissection, ultimately improving patient prognosis.

AIM

To explore the diagnostic value of fine-needle aspiration of thyroglobulin (FNA-Tg) combined with ultrasound (US)-guided fine-needle aspiration cytology for cervical lymph node metastasis in thyroid carcinoma.

METHODS

We enrolled 209 pathologically confirmed thyroid carcinoma patients who visited our hospital between Jan 2017 and Dec 2020. Patients were tentatively diagnosed with cervical lymph node enlargement using preoperative US. They underwent US-guided fine-needle aspiration cytology and FNA-Tg. The value of single and combined application of the two methods for the diagnosis of cervical lymph node metastasis was calculated. The factors affecting FNA-Tg for diagnosis were analyzed using univariate and multivariate methods.

RESULTS

FNA-Tg values were significantly higher among patients with positive cervical lymph node metastasis. The sensitivity and specificity of US-guided fine-needle aspiration cytology, FNA-Tg, and US-guided fine-needle aspiration cytology + FNA-Tg were 85.48% and 90.59%, 83.06% and 87.06%, and 96.77% and 91.76%, respectively. The area under the receiver operating characteristic curve for US-guided fine-needle aspiration cytology, FNA-Tg, and the two combined, was 0.880, 0.851, and 0.943, respectively. A long diameter/short diameter ratio < 2, an insufficient number of acquired cells, a low serum thyroglobulin level, and an absence of typical metastatic US features increased the risk of cervical lymph node metastasis in thyroid carcinoma patients misdiagnosed using FNA-Tg.

CONCLUSION

The diagnostic value of FNA-Tg for detecting cervical lymph node metastasis is not high; however, combined with US-guided fine-needle aspiration cytology, it is significantly improved.

Analysis of the Relevance of the Ultrasonographic Features of Papillary Thyroid Carcinoma and Cervical Lymph Node Metastasis on Conventional and Contrast-Enhanced Ultrasonography

Background

Preoperative prediction of lymph node metastases has a major impact on prognosis and recurrence for patients with papillary thyroid carcinoma (PTC). Thyroid ultrasonography is the preferred inspection to guide the appropriate diagnostic procedure.

Purpose

To investigate the relationship between PTC and cervical lymph node metastasis (CLNM, including central and lateral LNM) using both conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS).

Material and Methods

Our study retrospectively analyzed 379 patients diagnosed with PTC confirmed by surgical pathology at our hospital who underwent US and CEUS examinations from October 2016 to March 2021. Individuals were divided into two groups: the lymph node metastasis group and the nonmetastasis group. The relationship between US and CEUS characteristics of PTC and CLNM was analyzed. Univariate and multivariable logistic regression methods were used to identify the high-risk factors and established a nomogram to predict CLNM in PTC. Furthermore, we explore the frequency of CLNM at each nodal level in PTC patients.

Results

Univariate analysis indicated that there were significant differences in gender, age, tumor size, microcalcification, contact with the adjacent capsule, multifocality, capsule integrity and enhancement patterns in CEUS between the lymph node metastasis group and the nonmetastasis group (all P<0.05). Multivariate regression analysis showed that tumor size ≥1 cm, age ≤45 years, multifocality, and contact range of the adjacent capsule >50% were independent risk factors for CLNM in PTC, which determined the nomogram. The diagnostic model had an area under the curve (AUC) of 0.756 (95% confidence interval, 0.707-0.805). And calibration plot analysis shown that clinical utility of the nomogram. In 162 PTC patients, the metastatic rates of cervical lymph nodes at levels I-VI were 1.9%, 15.4%, 35.2%, 34.6%, 15.4%, 82.1%, and the difference was statistically significant (P<0.001).

Conclusion

Our study indicated that the characteristics of PTC on ultrasonography and CEUS can be used to predict CLNM as a useful tool. Preoperative analysis of ultrasonographical features has important value for predicting CLNM in PTCs. The risk of CLNM is greater when tumor size ≥1 cm, age ≤45 years, multifocality, contact range of the adjacent capsule >50% are present.

Lymph node metastasis of papillary thyroid carcinoma in the context of Hashimoto's thyroiditis

BACKGROUND

Whether Hashimoto's thyroiditis (HT) affects the lymph node metastasis of papillary thyroid carcinoma (PTC) remains uncertain. The diagnostic criteria for HT differed in previous studies. Our study focused on analysing the influence of HT on PTC lymph node metastasis (LNM) with stringent diagnostic criteria for HT.

METHODS

A total of 444 patients diagnosed with PTC from 2019 to 2020 were enrolled and divided into two groups: HT group and non-HT group. Diagnostic criteria of HT were as follows: thyroid peroxidase antibody (+) and postoperative histopathology of Hashimoto's disease.

RESULTS

There was no significant difference in the LNM rate between HT group and non-HT group. Patients in the HT group had fewer numbers of metastatic LNs and lower metastatic LNs ratio in central region. In the HT group, age < 55 and tumor size ≥10 mm were independent risk factors for central LNM.

CONCLUSION

The autoimmune response of HT seems to reduce the central lymph node metastasis of HT PTCs. Age < 55 and tumor size ≥10 mm were independent risk factors of central lymph node metastasis in HT PTCs.

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.

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

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

A prognostic nomogram for papillary thyroid cancer lymph node metastasis based on immune score

BACKGROUND

Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer and is characterized by an overall good prognosis and early-stage lymph node metastasis. The immune microenvironment is believed to play a crucial role in PTC initiation, progression and metastasis. However, to our knowledge, prognostic tools for thyroid cancer metastasis based on immune scores have not been adequately explored. This study aimed to construct a clinical nomogram to predict lymph node metastasis in patients with PTC.

METHODS

The genomic data and clinical-pathological characteristics of 447 PTC subjects were obtained from TCGA (The Cancer Genome Atlas data). Logistic regression models were performed for univariate and multivariate analyses to identify significant prediction factors. A prognostic nomogram was built based on the multivariate analysis results. The concordance index (C-index) and calibration curve were used to assess the predictive accuracy and discriminative ability of the model.

RESULTS

The patients were divided into two subgroups based on immune scores. We found that patients with high immune scores had significantly higher lymph node metastasis risks (OR and 95% confidence interval [CI]: 1.774[1.130-2.784]) than those with low immune scores. The C-index for lymph node metastasis was 0.722 (95% CI, 0.671-0.774), which had a favorable performance for clinical prediction. The calibration curve for lymph node metastasis showed significant agreement between the nomogram prediction and actual observation.

CONCLUSION

High immune scores are significantly correlated with higher lymph node metastasis risk in patients with PTC. Immune score-based prognostic nomograms may help to predict lymph node metastasis and have potential clinical application possibilities.

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.

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.

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

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

A radiomics nomogram for the ultrasound-based evaluation of central cervical lymph node metastasis in papillary thyroid carcinoma

PURPOSE

To develop and validate a radiomics nomogram based on ultrasound (US) to predict central cervical lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC).

METHODS

PTC patients with pathologically confirmed presence or absence of central cervical LN metastasis in our hospital between March 2021 and November 2021 were enrolled as the training cohort. Radiomics features were extracted from the preoperative US images, and a radiomics signature was constructed. Univariate and multivariate logistic regression analyses were used to screen out the independent risk factors, and a radiomics nomogram was established. The performance of the model was verified in the independent test cohort of PTC patients who underwent thyroidectomy and cervical LN dissection in our hospital from December 2021 to March 2022.

RESULTS

In the independent test cohort, the radiomics model based on long-axis cross-section and short-axis cross-section images outperformed the radiomics models based on either one of these sections (the area under the curve (AUC), 0.69 vs. 0.62 and 0.66). The radiomics signature consisted of 4 selected features. The US radiomics nomogram included the radiomics signature, age, gender, BRAF V600E mutation status, and extrathyroidal extension (ETE) status. In the independent test cohort, the AUC of the receiver operating curve(ROC) of this nomogram was 0.76, outperformingthe clinical model and the radiomics model (0.63 and 0.69, respectively), and also much better than preoperative US examination (AUC, 0.60). Decision curve analysis indicated that the radiomics nomogram was clinically useful.

CONCLUSIONS

This study presents an efficient and useful US radiomics nomogram that can provide comprehensive information to assist clinicians in the individualized preoperative prediction of central cervical LN metastasis in PTC patients.

A Preoperative Nomogram for the Prediction of High-Volume Central Lymph Node Metastasis in Papillary Thyroid Carcinoma

Background

High-volume lymph node metastasis (HVLNM, equal to or more than 5 lymph nodes) is one of the adverse features indicating high recurrence risk in papillary thyroid carcinoma (PTC) and is recommended as one of the indications of completion thyroidectomy for patients undergoing thyroid lobectomy at first. In this study, we aim to develop a preoperative nomogram for the prediction of HVLNMs in the central compartment in PTC (cT1-2N0M0), where preoperative imaging techniques perform poor.

Methods

From October 2016 to April 2021, 423 patients were included, who were diagnosed as PTC (cT1-2N0M0) and underwent total thyroidectomy and prophylactic central compartment neck dissection in our center. Demographic and clinicopathological features were recorded and analyzed using univariate and multivariate logistic regression analysis. A nomogram was developed based on multivariate logistic regression analysis.

Results

Among the included patients, 13.4% (57 cases) were found to have HVLNMs in the central compartment. Univariate and multivariate logistic regression analysis showed that age (35 years), BRAF with V600E mutated, nodule diameter, and calcification independently predicted HVLNMs in the central compartment. The nomogram showed good discrimination with an AUC of 0.821 (95% CI, 0.768-0.875).

Conclusion

The preoperative nomogram can be used to quantify the probability of HVLNMs in the central compartment and may reduce the reoperation rate after thyroid lobectomy.

Ultrasound Elastography under Deep Learning Algorithm to Analyze the Therapeutic Effect of Clustered Regularly Interspaced Short Palindromic Repeats Short Hairpin Ribonucleic Acid Nanoparticles on Cervical Cancer

This study aimed to analyze the effect of the deep learning algorithm on ultrasound elastography on the treatment of cervical cancer with clustered regularly interspaced short palindromic repeats (CRISPR) short hairpin ribonucleic acid (shRNA) nanoparticles, aiming to provide a reference for the clinical application of deep learning to analyze the therapeutic effect of the disease. In this study, CRISPR and shRNA plasmid nanoparticle drugs were used to treat 55 patients with cervical cancer in the experimental group, and normal saline was injected to another 53 patients in the control group, so compare the effect of nanoparticles in the treatment of cervical cancer. Professional doctors and the recurrent neural network (RNN) intelligent algorithm were used to score cervical cancer based on the ultrasound elastograph images by taking blue, green, and red (BGR) as diagnosis criteria. As a result, the experimental group had a total of 217 points before drug administration and a total of 224 points after drug administration. Each patient had an average increase of 0.13 points. The control group had a total of 200 points before drug administration and a total of 223 points after drug administration, and each patient had an average increase of 0.43 points. The experimental group was obviously different from the control group (P < 0.05). Each tissue image output by the RNN was clearer than the original image, and the score given by intelligent calculation was faster than that of professional doctors. The monitoring effect of the deep learning RNN intelligent algorithm on the therapeutic effect of nanomedicine was analyzed. It was found that the average accuracy of the experimental group and the control group was 98.95% and 90.34%, respectively; and the experimental group was greatly different from the control group (P < 0.05). In short, nano-CRISPR and shRNA drugs had remarkable effects on the treatment of cervical cancer, and the scores given by the deep learning intelligent algorithm were faster and more accurate, which provided theoretical guidance for the clinical application of deep learning algorithms to analyze the treatment effects of diseases.

Analysis of the risk factors for central lymph node metastasis of cN0 papillary thyroid microcarcinoma: A retrospective study

OBJECTIVE

Cervical lymph node (CLN) metastasis (CLNM) can be found in some patients with CLN-negative (cN0) papillary thyroid microcarcinoma (PTMC), while the risk factors are still unknown. This study aimed to examine the risk factors of CLNM in patients with cN0 PTMC, contributing to screening cN0 PTMC patients with high risk in CLNM for preventive CLN dissection (CLND).

METHODS

This retrospective study included consecutive patients pathologically diagnosed with cN0 PTMC and who underwent surgery at the General Surgery Department of China-Japan Friendship Hospital between 07/2016 and 01/2020. The patients were grouped according to whether CLNM was present. Factors associated with CLNM were analyzed, and a risk prediction model was established in logistic regression analysis, and their predictive power was evaluated by receiver operating characteristic curves (ROC).

RESULTS

Finally, 171 patients were included; among them, 71 (41.5%) had CLNM. There were 32 males and 139 females. The multivariable analysis showed that males (OR = 5.619, 95%CI: 2.186-14.446; P < 0.001), age ≤45 years (OR = 2.982, 95%CI: 1.446-6.151; P = 0.003), adjacent to dorsal membrane (OR = 3.022, 95%CI: 1.430-6.387; P = 0.004), and irregular borders (OR = 4.332, 95%CI: 1.104-17.000; P = 0.036) were independent risk factors of CLNM. The risk prediction model composed of the four risk factors showed a relatively high AUC, at 0.760. When the cut-off was 0.38, the sensitivity was 67.6%, and the specificity was 73.0%.

CONCLUSION

Male sex, age ≤45 years, adjacent to dorsal membranes, and irregular borders are independent risk factors for CLNM in patients with cN0 PTMC. This might help identify cN0 PTMC patients needing preventive CLND.

A prediction model incorporating the BRAFV600E protein status for determining the risk of cervical lateral lymph node metastasis in papillary thyroid cancer patients with central lymph node metastasis

BACKGROUND AND OBJECTIVES

Cervical lateral lymph node metastasis (LLNM) is a predictor of poor prognosis for papillary thyroid carcinoma (PTC) patients. However, the risk factors for LLNM remain unclear. The purpose of the study was to examine the risk factors for LLNM and construct a prediction model.

METHODS

With Ethics Committee approval, a total of 1198 PTC patients were retrospectively included in our study. Univariate and multivariate analyses were performed to explore the relationship between clinicopathological characteristics and LLNM. A nomogram for predicting LLNM in PTC patients with central lymph node metastasis (CLNM) was constructed and validated.

RESULTS

The negative BRAF^V600E protein expression was significantly correlated with positive LLNM status in PTC patients. In PTC patients with CLNM, the number of metastatic central lymph nodes (LNN) ≥ 3 and the ratio of metastatic central lymph nodes (LNR) ≥ 0.565 were found to be significantly associated with positive LLNM status. The nomogram for predicting LLNM risk in PTC patients with CLNM incorporated four risk factors: tumor size, the BRAF^V600E protein expression, LNN and LNR. The prediction model showed excellent discrimination, with a C-index of 0.714.

CONCLUSIONS

The negative BRAF^V600E protein expression was more likely to lead to LLNM. LNN ≥3 and LNR ≥0.565 were associated with LLNM risk in PTC patients with CLNM. Our nomogram might assist clinicians in developing individual suitable follow-up strategies for PTC patients with CLNM.

Papillary thyroid microcarcinomas that metastasize to lymph nodes

PURPOSE

We aimed to determine clinicopathological features that can predict lymph node metastasis (LNM) in papillary thyroid microcarcinomas (PTMC).

METHODS

Medical records of 872 patients with papillary thyroid cancer >1 cm (PTC > 1 cm) and 1184 patients with papillary thyroid microcancer (PTMC) (≤1 cm) were reviewed retrospectively. Demographical, clinical and histopathological features of (PTC > 1 cm) and PTMC were compared. Association between clinicopathological features and LNM in PTMC was investigated.

RESULTS

The median age of patients with PTMC was significantly higher than patients with PTC > 1 cm (49 vs 46 years old, p < 0.001). Multifocality, capsular invasion, vascular invasion, extrathyroidal extension (ETE) and LNM were more frequent in patients with PTC > 1 cm compared to patients with PMTC (p < 0.001 for each). In PTMC group, those with LNM had significantly higher proportion of multifocality, capsular invasion, vascular invasion and ETE compared to those without LNM (p = 0.007, <0.001, p = 0.011 and p < 0.001, respectively). Multifocality and ETE were significant factors for LNM with logistic regression analysis. Multifocality increased the risk of LNM by 1.737 times (95% CI: 1.079-2.979) and ETE increased the risk by 3.528 times (95%: 1.914-6.503). Primary tumor diameter ≥ 5.75 mm was predictive for LNM with a sensitivity of 0.782 and a specificity of 0.517 in PTMC.

CONCLUSIONS

LNM should be investigated more carefully in patients with PTMC in the presence of tumor diameter ≥ 5.75 mm, multifocality or ETE.