Model of lymph node metastasis posterior to the right recurrent laryngeal nerve in papillary thyroid carcinoma

乳头状甲状腺癌右侧喉返神经后方淋巴结转移模型

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Abstract

BACKGROUND: Cervical lymph node metastasis (LNM) is a prognostic factor of papillary thyroid carcinoma (PTC). The way to deal with lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN) is controversial. Nevertheless, if metastatic lymph nodes are not removed during the first operation, the subsequent salvage surgery of recurrent tumor in this area would entail high risk and complication. The purpose of this study was to develop a preoperative prediction model for LN-prRLN metastasis in PTC patients using clinicopathological characteristics. PATIENTS AND METHODS: We performed a prospective study of 595 patients with PTC who underwent LN-prRLN dissection from March 2014 to June 2017. The clinicopathological data were randomly divided into derivation (n=476) and validation sets (n=119). A predictive model was initially established based upon the data of the derivation set via multivariate analyses, and the accuracy of the model was then examined with data of the validation set. The discriminative power of this model was assessed in both sets. RESULTS: Metastases of the LN-prRLN were identified in 102 (17.14%) of 595 patients. Age (odds ratio [OR] 0.971, 95% CI, 0.949-0.994, p=0.013), tumor size (OR 2.163, 95% CI, 1.431-3.270, p<0.001), capsular invasion (OR 1.934, 95% CI, 1.062-3.522, p=0.031), and right LNM (OR 3.786, 95% CI, 2.012-7.123, p<0.001) were significantly associated with LN-prRLN metastasis. The areas under the curves were 0.790 for the derivation set (sensitivity 71.95%, specificity 78.68%) and 0.878 for the validation set (sensitivity 85.00%, specificity 78.79%). CONCLUSION: We developed and validated the first model to predict LN-prRLN metastases in patients with PTC based on clinicopathological parameters.

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