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

Development and validation of a clinical predictive model for high-volume lymph node metastasis of papillary thyroid carcinoma

The central lymph node metastasis (CLNM) status in the cervical region serves as a pivotal determinant for the extent of surgical intervention and prognosis in papillary thyroid carcinoma (PTC). This paper seeks to devise and validate a predictive model based on clinical parameters for the early anticipation of high-volume CLNM (hv-CLNM, > 5 nodes) in high-risk patients. A retrospective analysis of the pathological and clinical data of patients with PTC who underwent surgical treatment at Medical Centers A and B was conducted. The data from Center A was randomly divided into training and validation sets in an 8:2 ratio, with those from Center B serving as the test set. Multifactor logistic regression was harnessed in the training set to select variables and construct a predictive model. The generalization ability of the model was assessed in the validation and test sets. The model was evaluated through the receiver operating characteristic area under the curve (AUC) to predict the efficiency of hv-CLNM. The goodness of fit of the model was examined via the Brier verification technique. The incidence of hv-CLNM in 5897 PTC patients attained 4.8%. The occurrence rates in males and females were 9.4% (128/1365) and 3.4% (156/4532), respectively. Multifactor logistic regression unraveled male gender (OR = 2.17, p < .001), multifocality (OR = 4.06, p < .001), and lesion size (OR = 1.08 per increase of 1 mm, p < .001) as risk factors, while age emerged as a protective factor (OR = 0.95 per an increase of 1 year, p < .001). The model constructed with four predictive variables within the training set exhibited an AUC of 0.847 ([95%CI] 0.815-0.878). In the validation and test sets, the AUCs were 0.831 (0.783-0.879) and 0.845 (0.789-0.901), respectively, with Brier scores of 0.037, 0.041, and 0.056. Subgroup analysis unveiled AUCs for the prediction model in PTC lesion size groups (≤ 10 mm and > 10 mm) as 0.803 (0.757-0.85) and 0.747 (0.709-0.785), age groups (≤ 31 years and > 31 years) as 0.778 (0.720-0.881) and 0.837 (0.806-0.867), multifocal and solitary cases as 0.803 (0.767-0.838) and 0.809 (0.769-0.849), and Hashimoto's thyroiditis (HT) and non-HT cases as 0.845 (0.793-0.897) and 0.845 (0.819-0.871). Male gender, multifocality, and larger lesion size are risk factors for hv-CLNM in PTC patients, whereas age serves as a protective factor. The clinical predictive model developed in this research facilitates the early identification of high-risk patients for hv-CLNM, thereby assisting physicians in more efficacious risk stratification management for PTC patients.

Clinical and molecular features of progressive papillary thyroid microcarcinoma

In recent decades, the prevalence of thyroid cancer has risen substantially, with papillary thyroid microcarcinoma (PTMC) constituting over 50% of cases. Although most PTMCs exhibit indolent growth and a favorable prognosis, some present an increased risk of recurrence and an unfavorable prognosis due to high-risk characteristics such as lymph node metastasis, extrathyroidal extension, and distant metastasis. The early identification of clinically progressing PTMC remains elusive. In this review, the authors summarize findings from PTMC progression-related literature, highlighting that factors such as larger tumor size, cervical lymph node metastasis, extrathyroidal extension, younger age, higher preoperative serum thyroid-stimulating hormone levels, family history, and obesity positively correlate with PTMC progression. The role of multifocality in promoting PTMC progression; however, remains contentious. Furthermore, recent studies have shed light on the impact of mutations, such as BRAF and TERT mutations, on PTMC progression. Researchers have identified several mRNAs, noncoding RNAs, and proteins associated with various features of PTMC progression. Some studies propose that peripheral and tumor tissue-infiltrating immune cells could serve as biomarkers for the clinical progression of PTMC. Collectively, these clinical and molecular features offer a rationale for the early detection and the development of precision theranostic strategies of clinically progressive PTMC.

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

Objectives

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

Methods

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

Results

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

Conclusion

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

Quantitative analysis of dual-phase enhanced CT in cervical lymph node metastasis of papillary thyroid carcinoma: a comparative study along with pathological manifestations

PURPOSE

This study aimed to investigate the diagnostic value of dual-phase enhanced computed tomography (CT) in the cervical lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) by analyzing the dual-phase enhanced Hounsfield units (HUs) of lymph node and sternocleidomastoid muscle, and the ratio and difference.

METHODS

The CT arterial-phase and venous-phase imaging data of 143 metastasis-positive lymph nodes (MPLNs) in 88 cases and 172 metastasis-negative lymph nodes (MNLNs) in 128 cases with PTC were retrospectively analyzed. All lymph nodes were confirmed by surgical pathology. The arterial-phase HU of lymph nodes (ANHU), venous-phase HU of lymph nodes (VNHU), arterial-phase HU of the sternocleidomastoid muscle (AMHU) and venous-phase HU of the sternocleidomastoid muscle (VMHU) were measured, and their difference and ratio (ANHU-AMHU, ANHU/AMHU, VNHU-VMHU, VNHU/VMHU) were calculated. The cutoff values and corresponding diagnostic efficacy for diagnosing LNM in PTC were sought by performing the receiver operating characteristic curves. The maximum pathological diameter (MPD) measured on pathological sections of lymph nodes was compared with the maximum transverse diameter (MTD) and maximum sagittal diameter (MSD) and their average values on CT images.

RESULTS

The ANHU, and VNHU of MPLNs and MNLNs were 111.89 ± 33.26 and 66.12 (56.81-76.86) (P < 0.001), and 99.07 ± 23.27 and 75.47 ± 13.95 (P < 0.001), respectively. The area under the curve, sensitivity, and specificity of the arterial-phase three parameters (ANHU, ANHU-AMHU, ANHU/AMHU) for diagnosing LNM were (0.877-0.880), (0.755-0.769), and (0.901-0.913), respectively, and the venous-phase three parameters (VNHU, VNHU-VMHU, VNHU/VMHU) were (0.801-0.817), (0.650-0.678), and (0.826-0.901), respectively. Compared with MPD, MTD (Z = -2.686, P = 0.007) and MSD (Z = -3.539, P < 0.001) were significantly different, while (MTD + MSD)/2 was not statistically different (Z = -0.038b, P = 0.969).

CONCLUSION

In the differential diagnosis of cervical LNM of PTC by dual-phase enhanced CT angiography, the arterial phase had higher diagnostic efficacy.

Survival outcomes of low-risk papillary thyroid carcinoma at different risk levels: a corollary for active surveillance

Background

This study aims to compare the outcomes of active surveillance (AS) in low-risk papillary thyroid carcinoma (PTC) patients with different tumor sizes and lymph node metastasis status, in order to establish appropriate management strategies. By analyzing these results, this study provides valuable insights for the effective management of such patients, addressing the issues and challenges associated with AS in practical clinical practice.

Methods

The study utilized the SEER database supported by the National Cancer Institute of the United States, extracting data of PTC diagnosed between 2000 and 2015. Statistical analyses were conducted using inverse probability weighting (IPTW) and propensity score matching (PSM), including Kaplan-Meier survival curves and Cox regression models, to evaluate the impact of different tumor sizes and lymph node metastasis status on thyroid cancer-specific survival (TCSS).

Results

A total of 57,000 PTC patients were included, with most covariates having standardized mean differences below 10% after IPTW and PSM adjustments. The TCSS of PTC with a diameter smaller than 13mm is significantly better than that of tumors with a diameter larger than 13mm, regardless of the presence of lymph node metastasis. Among PTC cases with a diameter smaller than 13mm, the TCSS of patients is similar, regardless of the presence of lymph node metastasis. However, in PTC cases with a diameter larger than 13mm, the presence of lateral neck lymph node metastasis (N1b stage) significantly impacts the TCSS, although the absolute impact on TCSS rate is minimal.

Conclusion

The treatment strategy of AS is safe for patients with T1a stage papillary thyroid microcarcinoma (PTMC). However, for patients with T1b stage, if the tumor diameter exceeds 13mm or there is lymph node metastasis in the lateral neck region, the TCSS will be significantly affected. Nevertheless, the absolute impact on survival is relatively small.

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

Purpose

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

Materials and methods

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

Results

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

Conclusion

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

Accuracy of papillary thyroid cancer prognostic nomograms: a systematic review

Objective

Current staging and risk-stratification systems for predicting survival or recurrence of patients with differentiated thyroid carcinoma may be ineffective at predicting outcomes in individual patients. In recent years, nomograms have been proposed as an alternative to conventional systems for predicting personalized clinical outcomes. We conducted a systematic review to evaluate the predictive performance of available nomograms for thyroid cancer patients.

Design and methods

PROSPERO registration (CRD42022327028). A systematic search was conducted without time and language restrictions. PICOT questions: population, patients with papillary thyroid cancer; comparator prognostic factor, single-arm studies; outcomes, overall survival, disease-free survival, cancer-specific survival, recurrence, central lymph node metastases, or lateral lymph node metastases; timing, all periods; setting, hospital setting. Risk of bias was assessed through PROBAST tool.

Results

Eighteen studies with a total of 20 prognostic models were included in the systematic review (90,969 papillary thyroid carcinoma patients). Fourteen models were at high risk of bias and four were at unclear risk of bias. The greatest concerns arose in the analysis domain. The accuracy of nomograms for overall survival was assessed in only one study and appeared limited (0.77, 95% CI: 0.75-0.79). The accuracy of nomograms for disease-free survival ranged from 0.65 (95% CI: 0.55-0.75) to 0.92 (95% CI: 0.91-0.95). The C-index for predicting lateral lymph node metastasis ranged from 0.72 to 0.92 (95% CI: 0.86-0.97). For central lymph node metastasis, the C-index of externally validated studies ranged from 0.706 (95% CI: 0.685-0.727) to 0.923 (95% CI: 0.893-0.946).

Conclusions

Our work highlights the extremely high heterogeneity among nomograms and the critical lack of external validation studies that limit the applicability of nomograms in clinical practice. Further studies ideally using commonly adopted risk factors as the backbone to develop nomograms are required.

Significance statement

Nomograms may be appropriate tools to plan treatments and predict personalized clinical outcomes in patients with papillary thyroid cancer. However, the nomograms developed to date are very heterogeneous, and their results seem to be closely related to the specific samples studied to generate the same nomograms. The lack of rigorous external validation procedures and the use of risk factors that sometimes appear to be far from those commonly used in clinical practice, as well as the great heterogeneity of the risk factors considered, limit the ability of nomograms to predict patient outcomes and thus their current introduction in clinical practice.

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.

The risk of central nodal metastasis based on prognostic factors of the differentiated thyroid carcinoma: a systematic review and meta-analysis study

BACKGROUND AND AIM

Despite improving the 10-year disease-free-survival, prophylactic central neck dissection (pCND) in differentiated thyroid carcinoma (DTC) should only be considered in patients with high risk factors for lymph node (LN) metastasis due to the increases in the risk of postoperative complications. Our aim was to identify the risk factors for central lymph node metastasis (CLNM) in DTC.

METHOD

We searched PubMed, Scopus, Web of science, Cochrane library for eligible studies from inception to November 1, 2021 and a systematic review and meta-analysis were carried out to identify the risk factors for CLNM in DTC.

RESULTS

We included 41 studies with total of 27,741 patients in this study. The pooled results in this meta-analysis showed that these risk factors were significantly associated with CLNM: age < 45 years (odds ratio (OR) 1.64, 95% confidence interval (CI) 1.34-1.99, p < 0.00001), male sex (OR 1.73, 95% CI 1.54-1.93, p < 0.00001), multifocality (OR 1.87, 95% CI 1.59-2.19, p < 0.00001), bilateral disease (OR 1.43, 95% CI 1.15-1.78, p < 0.001), capsular invasion (OR 1.67, 95% CI 1.10-2.54, p < 0.02), lymphovascular invasion (OR 4.89, 95% CI 2.76-8.66, p < 0.00001) and extra-thyroidal extension (OR 2.43, 95% CI 1.97-3.00, p < 0.00001). In addition, young age (< 45 years), male sex, multifocality, and extra-thyroidal extension were significantly associated with large-volume CLNM in clinically N0 DTC patients. However, the presence of Hashimoto's thyroiditis was not a predictors of large-volume CLNM.

CONCLUSION

Young age (< 45 years), male sex, bilateral disease, multifocality, capsular invasion, lymphovascular invasion and extra-thyroidal extension are significantly associated with CLNM and pCND would be expected to have a higher yield in patients with these risk factors.

[Modern aspects influencing the management of patients with papillary thyroid cancer]

Thyroid cancer (TC) is the most common malignant tumor of the endocrine glands and accounts to 3% of the total structure of oncological morbidity. Papillary thyroid cancer (PTC) is the most common histological variant of thyroid malignancies. It accounts for about 85% of all cases of thyroid cancer. Despite good postoperative results and excellent survival compared to many other malignancies, tumor metastases to the paratracheal lymph nodes are quite common. This review of the literature considers the current personalized approach to patients with papillary thyroid cancer and current aspects influencing the management of patients with PTC.

Diagnostic value of CT enhancement degree in lymph node metastasis of papillary thyroid cancer: A comparison of enhancement, ratio, and difference

OBJECTIVES

To evaluate the value of computed tomography (CT) enhancement degree in diagnosing lymph node (LN) metastasis in papillary thyroid carcinoma (PTC) by determining the ratio and difference between the Hounsfield units (HU) of CT enhancement and plain scan of the LNs, as well as between the HU of CT-enhanced LNs and the sternocleidomastoid muscle.

METHODS

The plain and enhanced CT findings of 114 metastasis-positive LNs in 89 cases and 143 metastasis-negative LNs in 114 cases of PTC were analyzed retrospectively. Plain HU of LNs (PN_HU), enhanced HU of LNs (EN_HU), and enhanced HU of the sternocleidomastoid muscle (EM_HU) were measured. The EN_HU, difference between EN_HU and PN_HU (EN-PN_HU), ratio of EN_HU to PN_HU (EN/PN_HU), difference between EN_HU and EM_HU (EN-EM_HU), and ratio of EN_HU to EM_HU (EN/EM_HU) in metastasis-positive and metastasis-negative LN groups were calculated, the corresponding diagnostic efficacy for differentiating metastasis-positive from metastasis-negative LNs in PTC were sought using the receiver-operating curve. The interobserver agreement between readers was assessed using the interobserver correlation coefficient (ICC).

RESULTS

The EN_HU of 114 metastasis-positive LNs and 143 metastasis-negative LNs was 113.39 ± 24.13 and 77.65 ± 15.93, EN-PN_HU was 65.84 ± 21.72 HU and 34.07 ± 13.63 HU, EN/PN_HU was 2.36 (1.98, 2.75) and 1.76 (1.54, 2.02), EN-EM_HU was 49.42 ± 24.59 HU and 13.27 ± 15.41 HU, and EN/EM_HU was 1.79 ± 0.40 and 1.21 ± 0.24, respectively (all P < 0.001). The area under the curve, cutoff value, sensitivity, specificity, and accuracy of EN_HU for identifying metastasis-positive and metastasis-negative LNs were 0.895, 97.3 HU, 0.746, 0.895, and 0.829, EN-PN_HU was 0.894, 47.8 HU, 0.807, 0.874, and 0.844, EN/PN_HU was 0.831, 1.9, 0.877, 0.650, and 0.751, EN-EM_HU was 0.890, 26.4 HU, 0.807, 0.839, and 0.825, and EN/EM_HU was 0.888, 1.5, 0.728, 0.902, and 0.825, respectively. The readers had an excellent interobserver agreement on these five parameters (ICC = 0.874-0.994).

CONCLUSION

In the preoperative evaluation of LN metastasis in PTC, EN_HU, EN-PN_HU, EN-EM_HU, and EN/EM_HU had similarly high diagnostic efficacy, with EN_HU, EN-PN_HU, and EN/EM_HU having higher specificity and EN-PN_HU and EN-EM_HU having higher sensitivity.

Artificial Neural Network-Based Ultrasound Radiomics Can Predict Large-Volume Lymph Node Metastasis in Clinical N0 Papillary Thyroid Carcinoma Patients

Objective

To evaluate the ability of artificial neural network- (ANN-) based ultrasound radiomics to predict large-volume lymph node metastasis (LNM) preoperatively in clinical N0 disease (cN0) papillary thyroid carcinoma (PTC) patients.

Methods

From January 2020 to April 2021, 306 cN0 PTC patients admitted to our hospital were retrospectively reviewed and divided into a training (n = 183) cohort and a validation cohort (n = 123) in a 6 : 4 ratio. Radiomic features quantitatively extracted from ultrasound images were pruned to train one ANN-based radiomic model and three conventional machine learning-based classifiers in the training cohort. Furthermore, an integrated model using ANN was constructed for better prediction. Meanwhile, the prediction of the two models was evaluated in the papillary thyroid microcarcinoma (PTMC) and conventional papillary thyroid cancer (CPTC) subgroups.

Results

The radiomic model showed better discrimination than other classifiers for large-volume LNM in the validation cohort, with an area under the receiver operating characteristic curve (AUROC) of 0.856 and an area under the precision-recall curve (AUPR) of 0.381. The performance of the integrated model was better, with an AUROC of 0.910 and an AUPR of 0.463. According to the calibration curve and decision curve analysis, the radiomic and integrated models had good calibration and clinical usefulness. Moreover, the models had good predictive performance in the PTMC and CPTC subgroups.

Conclusion

ANN-based ultrasound radiomics could be a potential tool to predict large-volume LNM preoperatively in cN0 PTC patients.

Development and validation of an individualized nomogram for predicting the high-volume (> 5) central lymph node metastasis in papillary thyroid microcarcinoma

PURPOSE

Papillary thyroid microcarcinoma (PTMC) frequently presents a favorable clinical outcome, while aggressive invasiveness can also be found in some of this population. Identifying the risk clinical factors of high-volume (> 5) central lymph node metastasis (CLNM) in PTMC patients could help oncologists make a better-individualized clinical decision.

METHODS

We retrospectively reviewed the clinical characteristics of adult patients with PTC in the Surveillance, Epidemiology, and End Results (SEER) database between Jan 2010 and Dec 2015 and in one medical center affiliated to Chongqing Medical University between Jan 2018 and Oct 2020. Univariate and multivariate logistic regression analyses were used to determine the risk factors for high volume of CLNM in PTMC patients.

RESULTS

The male gender (OR = 2.02, 95% CI 1.46-2.81), larger tumor size (> 5 mm, OR = 1.64, 95% CI 1.13-2.38), multifocality (OR = 1.87, 95% CI 1.40-2.51), and extrathyroidal invasion (OR = 3.67; 95% CI 2.64-5.10) were independent risk factors in promoting high-volume of CLNM in PTMC patients. By contrast, elderly age (≥ 55 years) at diagnosis (OR = 0.57, 95% CI 0.40-0.81) and PTMC-follicular variate (OR = 0.60, 95% CI 0.42-0.87) were determined as the protective factors. Based on these indicators, a nomogram was further constructed with a good concordance index (C-index) of 0.702, supported by an external validating cohort with a promising C-index of 0.811.

CONCLUSION

A nomogram was successfully established and validated with six clinical indicators. This model could help surgeons to make a better-individualized clinical decision on the management of PTMC patients, especially in terms of whether prophylactic central lymph node dissection and postoperative radiotherapy should be warranted.

Predictors and a Prediction Model for Central Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma (cN0)

OBJECTIVES

To screen out the predictors of central cervical lymph node metastasis (CLNM) for papillary thyroid carcinoma (PTC) and establish a prediction model to guide the operation of PTC patients (cN0).

METHODS

Data from 296 PTC patients (cN0) who underwent thyroid operation at the Second Affiliated Hospital of Chongqing Medical University were collected and retrospectively analyzed. They were divided into two groups in accordance with central CLNM or not. Their information, including ultrasound (US) features, BRAF^V600E status, and other characteristics of the two groups, was analyzed and compared using univariate and multivariate logistic regression analyses, and the independent predictors were selected to construct a nomogram. The calibration plot, C-index, and decision curve analysis were used to assess the prediction model's calibration, discrimination, and clinical usefulness.

RESULTS

A total of 37.8% (112/296) of PTC patients had central CLNM, and 62.2% (184/296) did not. The two groups were compared using a univariate logistic regression analysis, and there were no significant differences between the two groups in sex, aspect ratio, boundary, morphology, hypoechoic nodule, thyroid peroxidase antibody, or tumor location (P>0.05), and there were significant differences between age, tumor size, capsule contact, microcalcifications, blood flow signal, thyroglobulin antibodies (TgAb), and BRAF gene status (P<0.05). A multivariate logistic regression analysis was performed to further clarify the correlation of these indices. However, only tumor size (OR=2.814, 95% Cl=1.634~4.848, P<0.001), microcalcifications (OR=2.839, 95% Cl=1,684~4.787, P<0.001) and TgAb (OR=1.964, 95% Cl=1.039~3,711, P=0.038) were independent predictors of central CLNM and were incorporated and used to construct the prediction nomogram. The model had good discrimination with a C-index of 0.715. An ROC curve analysis was performed to evaluate the accuracy of this model. The decision curve analysis showed that the model was clinically useful when intervention was decided in the threshold range of 16% to 80%.

CONCLUSION

In conclusion, three independent predictors of central CLNM, including tumor size (> 1.0 cm), US features (microcalcifications), and TgAb (positive), were screened out. A visualized nomogram model was established based on the three predictors in this study, which could be used as a basis of central cervical lymph node dissection (CLND) for PTC patients (cN0).