Nomogram for predicting level V lymph node metastases in papillary thyroid carcinoma with clinically lateral lymph node metastases: A large retrospective cohort study of 1037 patients from FDUSCC

Nomogram for preoperative estimation risk of lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multicenter study

BACKGROUND

Lateral lymph node metastasis (LLNM) is frequent in papillary thyroid carcinoma (PTC) and is associated with a poor prognosis. This study aimed to developed a clinical-ultrasound (Clin-US) nomogram to predict LLNM in patients with PTC.

METHODS

In total, 2612 PTC patients from two hospitals (H1: 1732 patients in the training cohort and 578 patients in the internal testing cohort; H2: 302 patients in the external testing cohort) were retrospectively enrolled. The associations between LLNM and preoperative clinical and sonographic characteristics were evaluated by the univariable and multivariable logistic regression analysis. The Clin-US nomogram was built basing on multivariate logistic regression analysis. The predicting performance of Clin-US nomogram was evaluated by calibration, discrimination and clinical usefulness.

RESULTS

The age, gender, maximum diameter of tumor (tumor size), tumor position, internal echo, microcalcification, vascularization, mulifocality, and ratio of abutment/perimeter (A/P) > 0.25 were independently associated with LLNM metastatic status. In the multivariate analysis, gender, tumor size, mulifocality, position, microcacification, and A/P > 0.25 were independent correlative factors. Comparing the Clin-US nomogram and US features, Clin-US nomogram had the highest AUC both in the training cohort and testing cohorts. The Clin‑US model revealed good discrimination between PTC with LLNM and without LLNM in the training cohort (AUC = 0.813), internal testing cohort (AUC = 0.815) and external testing cohort (AUC = 0.870).

CONCLUSION

Our findings suggest that the ClinUS nomogram we newly developed can effectively predict LLNM in PTC patients and could help clinicians choose appropriate surgical procedures.

A preoperative nomogram model for the prediction of lymph node metastasis in buccal mucosa cancer

OBJECTIVES

We sought to construct a nomogram model predicting lymph node metastasis (LNM) in patients with squamous cell carcinoma of the buccal mucosa based on preoperative clinical characteristics.

METHODS

Patients who underwent radical resection of a primary tumor in the buccal mucosa with neck dissection were enrolled. Clinical characteristics independently associated with LNM in multivariate analyses were adopted to build the model. Patients at low risk of LNM were defined by a predicted probability of LNM of less than 5%.

RESULTS

Patients who underwent surgery in an earlier period (January 2015-November 2019) were defined as the model development cohort (n = 325), and those who underwent surgery later (November 2019-March 2021) were defined as the validation cohort (n = 140). Age, tumor differentiation, tumor thickness, and clinical N stage assessed by computed tomography/magnetic resonance imaging (cN) were independent predictors of LNM. The nomogram model based on these four predictors showed good discrimination accuracy in both the model development and validation cohorts, with areas under the receiver-operating characteristic curve (AUC) of 0.814 and 0.828, respectively. LNM prediction by the nomogram model was superior to cN in AUC comparisons (0.815 vs. 0.753) and decision curve analysis of the whole cohort. Seventy-one patients were defined as having a low risk of LNM, among whom the actual metastasis rate was only 1.4%.

CONCLUSIONS

A robust nomogram model for preoperative LNM prediction is built.

Potential factors of cytokeratin fragment 21-1 and cancer embryonic antigen for mediastinal lymph node metastasis in lung cancer

Objective: Lung cancer is a common malignant tumor, characterized by being difficult to detect and lacking specific clinical manifestations. This study aimed to find out the risk factors of mediastinal lymph node metastasis and explore the correlation between serum tumor markers and mediastinal lymph node metastasis and lung cancer prognosis.

Methods: A retrospective study of 3,042 lung cancer patients (330 patients with mediastinal lymph node metastasis and 2,712 patients without mediastinal lymph node metastasis) collected from the First Affiliated Hospital of Nanchang University from April 1999 to July 2020. The patients were divided into two groups, namely, mediastinal lymph node metastasis group and non-mediastinal lymph node metastasis group. Student’s t test, non-parametric rank sum test and chi-square test were used to describe whether there is a significant difference between the two groups. We compared the serum biomarkers of the two groups of patients, including exploring serum alkaline phosphatase (ALP), calcium hemoglobin (HB), alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), CA125, CA-199, CA -153, cytokeratin fragment 19 (CYFRA 21-1), total prostate specific antigen (TPSA), neuron-specific enolase (NSE) levels and the incidence and prognosis of lung cancer mediastinal lymph node metastasis. Binary logistic regression analysis was used to determine its risk factors, and receiver operating curve (ROC) analysis was used to evaluate its diagnostic value for mediastinal lymph node metastasis.

Results: Binary logistic regression analysis showed that carcinoembryonic antigen and CYFRA 21-1 were independent risk factors for mediastinal lymph node metastasis in patients with lung cancer (p < 0.001 and p = 0.002, respectively). The sensitivity and specificity of CEA for the diagnosis of mediastinal lymph node metastasis were 90.2 and 7.6%, respectively; CYFRA 21-1 were 0.6 and 99.0%, respectively.

Conclusion: Serum CEA and CYFRA 21-1 have predictive value in the diagnosis of mediastinal lymph node metastasis in patients with lung cancer.

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.

Analysis of Risk Factors of Level V Lymphatic Metastasis for Papillary Thyroid Carcinoma with pN1b

Objective

To explore the risk factors of level V lymphatic metastasis in papillary thyroid carcinoma (PTC) patients with pN1b.

Methods

Patients were selected if they presented with a suspicious level III or IV lymph node metastasis and underwent surgery by hemi or total thyroidectomy with a lymph node dissection (levels III, IV, VI, and VII). For these patients, if frozen section showed a positive level III or IV node, then levels II and V nodes were resected. Univariate analysis was performed using the chi-square test for some factors, including age, sex, tumor location, multifocal lesions, tumor size, local invasion of primary focus, status of cervical lymphatic metastasis, TNM staging, tumor deposits (independent tumor nodules), and the metastasis to more than 5 central lymph nodes. Then, the factors with statistical significance indicated by the above univariate analysis underwent multivariate analysis.

Results

Univariate analysis indicated that the level V lymphatic metastasis was significantly associated with simultaneous metastases to levels II, III, and IV, simultaneous metastases to levels III and IV, and tumor deposits (all p < 0.05), but it was not significantly associated with age, sex, tumor location, multifocal lesions, tumor size, local invasion of primary focus, other cervical lymphatic metastasis, TNM staging, and the metastases to more than 5 central lymph nodes (all p > 0.05). Multivariate analysis suggested that the simultaneous metastases to levels III and IV and tumor deposits were the risk factors of level V lymphatic metastasis.

Conclusion

The simultaneous metastases to levels III and IV and tumor deposits are independent risk factors of level V lymphatic metastasis. The patients with pN1b PTC who have simultaneous metastases to levels III and IV or/and tumor deposits may have the risk of level V lymph node metastasis.

Dynamic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma

OBJECTIVE

To establish a dynamic nomogram based on preoperative clinical data for prediction of lateral lymph node metastasis (LLNM) of papillary thyroid carcinoma.

STUDY DESIGN

Retrospective study.

SETTING

The Sixth Affiliated Hospital of Sun Yat-Sen University.

METHODS

The data of 477 patients from 2 centers formed the training group and validation group and were retrospectively reviewed. Preoperative clinical factors influencing LLNM were identified by univariable and multivariable analysis and were to construct a predictive dynamic nomogram for LLNM. Receiver operating characteristic analysis and calibration curves were used to evaluate the predictive power of the nomogram.

RESULTS

The following were identified as independent risk factors for LLNM: male sex (odds ratio [OR] = 4.6, P = .04), tumor size ≥10.5 mm (OR = 7.9, P = .008), thyroid nodules (OR = 6.1, P = .013), irregular tumor shape (OR = 24.6, P = .001), rich lymph node vascularity (OR = 9.7, P = .004), and lymph node location. The dynamic nomogram constructed with these factors is available at https://zxh1119.shinyapps.io/DynNomapp/. The nomogram showed good performance, with an area under the curve of 0.956 (95% CI, 0.925-0.986), a sensitivity of 0.87, and a specificity of 0.91, if high-risk patients were defined as those with a predicted probability ≥0.3 or total score ≥200. The nomogram performed well in the external validation cohort (area under the curve, 0.915; 95% CI, 0.862-0.967).

CONCLUSIONS

The dynamic nomogram for preoperative prediction of LLNM in papillary thyroid carcinoma can help surgeons identify high-risk patients and develop individualized treatment plans.

Lateral Neck Dissection for Well-Differentiated Thyroid Carcinoma: Is Prophylactic Level V Neck Dissection Necessary? A Retrospective Cohort Study

OBJECTIVE

The presence of clinically detectable papillary thyroid carcinoma (PTC) metastases in the lateral neck is an indication for neck dissection (ND) and thyroidectomy. Although there is a consensus regarding the importance of therapeutic selective ND of involved levels II to IV in patients with clinically evident locoregional metastatic disease, the prognostic benefit of level V prophylactic ND remains debatable.

METHODS

All patients who underwent thyroidectomy with ND for metastatic PTC between 2006 and 2019 were included in a single-institution retrospective study. Preoperative characteristics at initial presentation, imaging workup, intraoperative findings, and the final histopathological reports were retrieved from the institutional database.

RESULTS

A total of 189 patients with locally advanced PTC were identified, of whom 22 (11.6%) patients underwent therapeutic selective ND at levels II to IV together with level V dissection due to clinical involvement. Comparison of the patients who were operated on level V to those who were not revealed no significant difference. The disease recurrence rate was 20.1% throughout an average follow-up of 5.1±3.1 years. No significant differences in recurrence rate were found between patients who underwent and those who did not undergo level V ND (22.7% vs 19.8%, P = .648). No recurrence at resected level V was detected during follow-up, while recurrence at level V was found in 4 (2.1%) patients who did not undergo level V dissection. Evidence of macroscopic and microscopic extrathyroidal extension was significant predictors of disease recurrence risk.

CONCLUSION

There were no significant associations between level V dissection and risk for recurrence. Recurrence at level V was rare (4/189 patients, 2.1%). Our study's findings suggest a low prophylactic benefit of an elective level V ND. Elective level V ND should not be done routinely when lateral ND is indicated but should rather be considered after careful evaluation in high-risk patients.

Endoscopic Thyroidectomy With Level Vb Dissection Via a Chest-breast Approach: Technical Updates for Selective Lateral Neck Dissection

OBJECTIVE

To determine the feasibility of endoscopic thyroidectomy with level Vb dissection using a chest-breast approach.

METHODS

Lateral neck level Vb dissection by endoscopic surgery using a chest-breast approach was performed as an update to the previously reported endoscopic selective lateral neck dissection. The demographic data, surgical outcomes, and adverse events were analyzed.

RESULTS

A total of 12 cases were performed successfully, and no patient was converted to the open procedure. The sex ratio was 16/2 (female/male). The average age and primary lesion diameter were 36.3±5.8 years old, and 1.97±0.58 cm, respectively. The average total and lateral lymph nodes dissection time of duration was 154.6±17.0 and 276.3±19.2 minutes, respectively. The lymph node ratio (mean number of metastasis/total number of dissected nodes) at levels II, III+IV, VI, and Vb were 1.6±1.4/6.8±2.0, 5.8±2.4/14.4±3.6, 3.2±1.1/6.5±1.9, and 0.8±0.9/5.8±1.6, respectively. One of 12 patients had lymphatic leakage and 2 of 12 patients had transient hypocalcemia. There was no incidence of uncontrolled bleeding, mental nerve injury, permanent hypoparathyroidism, permanent recurrent laryngeal nerve injury, skin bruise on neck, infection, asphyxia/dyspnea, large blood vessel injury or other complications like tracheal injury, esophageal injury, etc., nor was there any death or recurrence in either of the 2 groups during a short follow-up period.

CONCLUSIONS

It is feasible to perform endoscopic thyroidectomy with level Vb dissection using a chest-breast approach. Such strategy represents another option for selective papillary thyroid carcinoma patients with levels II, III, IV, and Vb lymph node metastasis.

Blood prognostic predictors of treatment response for patients with papillary thyroid cancer

Background: Papillary thyroid cancer (PTC) is a very common malignant disease with high morbidity. We needed some pretreatment indicators to help us predict prognosis and guide treatment. We conducted a study about some pretreatment prognostic indicators.

Methods: This clinical study recruited 705 postoperative PTC patients (211 males, 494 females). Clinical data before radioactive iodine (RAI) treatment were collected. Patients’ response to therapy were classified into two categories: ‘Good Prognosis Group’ (GPG) and ‘Poor Prognosis Group’ (PPG), according to ‘2015 American Thyroid Association Guidelines’. Differences of indicators between different prognosis groups were compared. Odds ratios (ORs) were calculated by univariate/multiple binary logistic regression models. Difference of body mass index (BMI) changes before and after RAI treatment between different prognosis groups was also compared.

Results: A total of 546 (77.45%) belonged to GPG, and 159 (22.55%) belonged to PPG. Platelet (PLT), neutrophil (NEUT), PLT subgroups, and combination of red blood cell distribution width (RDW) and BMI (COR-BMI) were different between two prognosis groups. The significance of the difference between the two groups of BMI disappeared after the Bonferroni correction. PLT and PLT subgroups had detrimental effects on the risk of PPG; T stage had a positive effect on the risk of PPG. PLT subgroup showed a detrimental effect on the risk of PPG when we included additional covariates.

Conclusions: We found that lower pretreatment PLT levels may indicate a poor prognosis for PTC. The relationship between platelet-derived growth factor (PDGF) and radiation sensitivity may be the key to this association.

Prediction of level V metastases in papillary thyroid microcarcinoma: a single center analysis

Background

The rate of level V metastases is significantly low and the necessity of routine level V dissection for papillary thyroid microcarcinoma (PTMC) with clinically lateral lymph node metastasis (LNM) is still controversial.

Methods

This study enrolled 114 consecutive PTMC patients with clinically suspected lateral LNM (N1b) who underwent modified radical neck dissection (levels II to V) at Xiangya Hospital of Central South University from September 2016 to July 2019. Univariate and multivariate analyses were performed to investigate the predictive factors of level V metastasis. The area under the receiver operating characteristic (ROC) curve (AUC), accuracy, specificity and sensitivity were used to determine the predictive value.

Results

The overall and occult rate of level V metastasis were 29.82% (34/114) and 7.02% (8/114), respectively. Univariate analysis showed that level V metastasis was significantly associated with gross extrathyroidal extension (ETE), level IV metastasis and 2-level simultaneous metastasis (all P<0.05). Gross ETE (OR =11.916, 95% CI, 1.404-102.19; P=0.023) and level IV metastasis (OR =8.497, 95% CI, 2.119-34.065; P =0.03) served as independent predictors of level V metastasis in N1b PTMC patients. The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of gross ETE and level IV metastasis in predicting the level V metastasis were 25.3% vs. 82.4%, 97.5% vs. 73.8%, 82.69% vs. 76.32%, 80% vs. 57.04% and 75% vs. 90.77%, respectively. The AUC of gross ETE was lower than level IV metastasis (0.605 vs. 0.781, P=0.041).

Conclusions

Routine level V dissection is necessary in N1b PTMC patients with level IV metastasis or gross ETE. Compared with gross ETE, level IV metastasis is superior in predicting level V metastasis.

Development and validation of a nomogram for preoperative prediction of cervical lymph node involvement in thyroid microcarcinoma

Cervical regional lymph node involvement (CRLNI) is common in papillary thyroid microcarcinoma (PTMC), but the way to deal with cervical lymph node involvement of clinically negative PTMC is controversial. We studied data of patients histologically confirmed PTMC in the Surveillance, Epidemiology, and End Results (SEER) Program and Department of Surgical Oncology in Hangzhou First People's Hospital (China). We screened 6 variables of demographic and clinicopathological characteristics as potential predictors and further constructed a lymph node involvement model based on the independent predictors including age, race, sex, extension, multifocality and tumor size. The model was validated by both the internal and the external testing sets, and the visual expression of the model was displayed by a nomogram. As a result, the C-index of this predictive model in the training set was 0.766, and the internal and external testing sets through cross-validation were 0.753 and 0.668, respectively. The area under the receiver operating characteristic curve (AUC) was 0.766 for the training set. We also performed a Decision Curve Analysis (DCA), which showed that predicting the cervical lymph node involvement risk applying this nomogram would be better than having all patients or none patients use this nomogram.