Objective To summarize the influencing factors of central lymph node metastasis in thyroid papillary carcinoma. Method Relevant literature about papillary thyroid carcinoma were reviewed and predictive factors of central lymph node metastasis were summarized. Results Studies had shown that, male, younger age, larger tumor size, multifocal, and BRAF mutations were risk factors for central lymph node metastasis in thyroid papillary carcinoma, while tumors located in the upper pole and combined with Hashimoto disease (HT) were the protective factors for central lymph node metastasis. Conclusions The central lymph node metastasis detection rate is low, so it is unable to meet with the preoperative diagnosis in papillary thyroid carcinoma. A large number of studies have confirmed that clinical pathological features have predictive value for preoperative lymph node diagnosis, and can provide a reference for the selection of surgical methods in thyroid papillary carcinoma.
ObjectiveTo investigate the effects of thyroid globulin antibody (TgAb) and thyroid peroxidase antibody (TPOAb) statuses on central lymph node (CLN) metastasis in patients with differentiated thyroid cancer (DTC).MethodsA retrospective analysis was performed on 526 patients with DTC confirmed by pathology from nine participating institutions, who underwent the bilateral thyroidectomy plus bilateral CLN dissection. The clinicopathologic characteristics of different TGAb and TPOAb statuses of patients with DTC were compared, and whether the TGAb and TPOAb statuses were the independent risk factors of CLN metastasis in DTC patients or not was analyzed.ResultsAll of 526 patients with DTC were included in this study, 152 were males and 374 were females. The age was (44±11) years old. There were 63 cases of TgAb＋TPOAb＋, 60 cases of TgAb＋TPOAb－, 30 cases of TgAb－TPOAb＋, and 373 cases of TgAb－TPOAb－. It was found that there was a significant difference in the gender among the four different antibody statuses of patients, that was, women with abnormal antibodies were more common (P<0.001), not found that there were related to the tumor size, blood vessel invasion, nerve invasion, CLN metastasis, tumor multifocality, and bilateral tumor or not (P>0.050). In this study, there were 389 cases of CLN with metastasis and 137 cases of CLN without metastasis. The results of multivariate analysis found that the age and gender of the patients were the independent risk factors (P<0.001), but didn’t find the TgAb and TPOAb Statuses and other factors were related to the CLN metastasis (P>0.050).ConclusionsStatuses of TGAb and TPOAb aren’t obviously associated with CLN metastasis in patients with DTC, which is inconsistent with other studies. It needs to be further researched after expanding existing sample size and determining new predictive factors.
ObjectiveTo investigate the risk factors for central lymph node metastasis (CLNM) in patients with clinically negative lymph node (cN0 stage) papillary thyroid carcinoma (PTC).MethodsThe clinicopathological data of 250 patients with cN0 PTC who underwent thyroidectomy and central lymph node dissection (CLND) in Department of General Surgery of Xuzhou Central Hospital from June 2016 to June 2019 were retrospectively analyzed. The influencing factors of CLNM in patients with cN0 PTC were analyzed by univariate analysis and binary logistic regression, and then R software was used to establish a nomogram prediction model, receiver operating characteristic curve was used to evaluate the differentiation degree of the model, and Bootstrap method was used for internal verification to evaluate the calibration degree of the model.ResultsCLNM occurred in 147 of 250 patients with cN0 PTC, with an incidence of 58.8%. Univariate analysis showed that multifocal, bilateral, tumor diameter, and age were correlated with CLNM (P<0.01). The results of binary logistic regression analysis showed that multifocal, bilateral tumors, age≥45 years old, and tumor diameter>1 cm were independent risk factors for CLNM in patients with cN0 PTC (P<0.05). The area under the curve (AUC) of the nomogram prediction model established on this basis was 0.738, and the calibration prediction curve in the calibration diagram fitted well with the ideal curve.ConclusionsCLNM is more likely to occur in PTC. The nomogram model constructed in this study can be used as an auxiliary means to predict CLNM in clinical practice.
Objective To explore the predictive value of CT signs combined with clinicopathological features for single cN0 papillary thyroid microcarcinoma (PTMC) central lymph node metastasis (CLNM). Methods A retrospective analysis of the CT signs and clinicopathological characteristics of 115 cases of single cN0 PTMC confirmed by surgery and pathology was performed, and univariate and multivariate logistic regression analysis were used to analyze the relationship between the contact between tumor and thyroid edge, tumor calcification, tumor location, tumor diameter, age, gender, thyroglobulin level and CLNM. According to the different contact range between tumor and thyroid edge in CT signs, the patients were divided into three groups: <1/4 group, 1/4–<1/2 group and ≥1/2 group. The proportion of CLNM positive patients in different contact areas between tumor body and thyroid edge was analyzed by using χ2 test. Results Among 115 cases of single cN0 PTMC, there were 26 cases and 89 cases with CLNM positive and negative, respectively. Univariate analysis showed that contact between tumor body and thyroid edge, tumor diameter, age, and gender were associated with CLNM positive (P<0.05). Further multivariate logistic regression analysis showed that thyroid marginal contact, age <45 years old and male were associated with CLNM positive (P<0.05). The proportion of CLNM positive patients in different contact areas between tumor body and thyroid edge (between the three groups ) was statistically different (P<0.05). The pairwise comparison among the three groups showed that the proportion of CLNM positive patients were statistically different (P<0.0167 after correction). Conclusions Tumor body contact with thyroid edge, age <45 years and male were independent risk factors for CLNM in patients with single cN0 PTMC. The combination of multiple risk factors can further improve the preoperative evaluation level of CLNM in patients with PTMC. Excluding clinical characteristic factors, the wider the contact area between the tumor and the thyroid edge, the higher the risk of CLNM, which provides a reasonable basis for selective central lymph node dissection.
ObjectiveTo establish a predictive model for neck lateral lymph node metastasis (LLNM) in unilateral papillary thyroid cancer (uni-PTC) with central lymph node metastasis (CLNM). MethodsThe uni-PTC patients with CLNM were included in this study. The patients underwent thyroid surgery in the 960th Hospital of the PLA Joint Logistics Support Force from May 2018 to December 2021, who were randomly divided into the modeling group and the validation group according to the ratio of 7∶3. The risk factors of neck LLNM were analyzed by univariate and multivariate logistic regression and the nomogram of prediction model was constructed. The receiver operating characteristic (ROC) curve and calibration curve were used to validate the prediction model. ResultsA total of 237 patients were included in this study, including 158 patients in the modeling group and 79 patients in the validation group. The LLNM occurred in the 84 patients of the modeling group and 43 patients of the validation group. The multivariate logistic regression analysis was performed according to the statistical indicators in the univariate analysis results of the modeling group and the risk factors considered in the previous studies. The results showed that the patients with maximum diameter of the lesions >1 cm, multiple lesions, extraglandular invasion, the rate of CLNM ≥0.414, and lesions located at the upper portion had higher probability of LLNM (OR>1, P<0.05). The area under ROC curve of the nomogram in predicting LLNM in the modeling group was 0.834 [95%CI (0.771, 0.896)], which in the validation group was 0.761 [95%CI (0.651, 0.871)]. The calibration curve showed a good calibration degree in the prediction model. ConclusionThe clinical risk prediction model established based on the risk factors can better predict the probability of LLNM.