Influence Factors for Lymph Node Metastasis in Papillary Thyroid Carcinoma: Hashimoto's Thyroiditis Has a Weak Effect on Central or Lateral Lymph Node Metastasis

Sonographic characteristics and clinical characteristics combined with nomogram for predicting the aggressiveness of papillary thyroid carcinoma coexisted with Hashimoto's thyroiditis

OBJECTIVE

The association between Papillary Thyroid Carcinoma (PTC) and coexistent Hashimoto's Thyroiditis (HT) was controversial. The purpose of this study was to evaluate the presence of HT exerts any influence on the aggressiveness of PTC, and to establish a nomogram for predicting the possibility of aggressiveness in PTC.

METHODS

373 consecutive PTC patients with/without coexistent HT from January 2017 to December 2020 were retrospective reviewed. Patients' clinicopathologic and sonographic characteristics were collected for univariate and multivariate analyses. A nomogram was established based on the risk factors for aggressiveness in PTC.

RESULTS

Male (p = 0.001), tumor size >1.0 cm (p = 0.046) and lymph node metastasis (p = 0.018) were negatively associated with PTC coexisted with HT, while it was significantly positively associated with the frequence of multifocality (p = 0.010). Univariate and multivariate analyses suggested that age ≥55 years (p = 0.000), male (p = 0.027), HT (p = 0.017), tumor size >1.0 cm (p = 0.015), multifocality (p = 0.041), distance to capsular ≤0 cm (p = 0.050) and blood flow (Grade I: p = 0.044) were independent risk factors for predicting the aggressiveness in PTC. A nomogram according to these predictors was further developed and validated. The receiver operating characteristic curve (AUC = 0.734 and 0.809 for training and validation cohorts, respectively) and decision curve analyses indicated that the nomogram model was clinically useful. The calibration curve revealed that the nomogram exhibited an excellent consistency.

CONCLUSIONS

In this study, the coexistent HT might play a protective role in preventing the proliferation of PTC. Dispensable aggressive treatment may be reduced in PTC by pre-operative identification of sonographic and clinical characteristics and incorporating with the predicted nomogram model.

Application of Preoperative Ultrasonography in the Diagnosis of Cervical Lymph Node Metastasis in Thyroid Papillary Carcinoma

Background

The clinical value and application of preoperative ultrasound contrast in the diagnosis of cervical lymph node metastasis in thyroid papillary carcinoma is investigated.

Methods

In total, 126 cases of thyroid papillary carcinoma were selected, the sensitivity and accuracy of color ultrasound and ultrasound contrast were analyzed by comparing preoperative gray-scale ultrasound, color ultrasound, and ultrasound contrast.

Results

The accuracies of preoperative color ultrasound and ultrasound contrast in detecting lymph node metastasis were 74 and 82%, respectively, and their sensitivities were 80 and 94%, respectively. Lymph node metastasis was significantly more severe when the tumor diameter was >4 cm. The lymphatic metastatic rate of the patients with multifocal papillary carcinoma was 96.4%, whereas the lymphatic metastatic rate of the patients with thyroid gland lesions was 87.7%. The central foci of cervical lymph node metastasis included the following pathological subtypes: diffuse sclerosis type (89.3%, 25/28), high-cell type (72.2%, 8/11), and papillary type (40.0%, 4/10).

Conclusion

Ultrasound contrast is more sensitive than color ultrasound in the diagnosis of cervical lymph node metastasis. Primary lesions ≥4 cm, lesion involvement, outer membrane, and high-risk pathologic subtypes and lesions were considered as the criteria for ultrasound contrast application.

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).