Risk factors and nomogram to predict skip metastasis in papillary thyroid carcinoma.

Background: Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy. Skip metastases of PTCs are easily misdiagnosed before surgery, and it could lead to re-operation and affect the prognosis. Although there are a few studies about nomograms for predicting central lymph node metastases (CLNM) or lateral lymph node metastases (LLNM) of PTCs, there are few studies about nomograms for skip metastases. Based on the clinical and ultrasonographic characteristics of patients with PTCs, the aim of our study was to investigate the risk factors and establish a nomogram for predicting the risk of skip metastases in PTCs. Methods: This study enrolled 218 PTCs patients with lateral cervical lymph node metastases and their data were analyzed retrospectively. According to the postoperative pathological results, the patients were divided into skip-positive group and skip-negative group. In order to establish the nomogram, univariate and multivariate analyses were used to estimate risk factors of skip metastases. The receiver operating characteristic (ROC) curve, internal calibration plot and decision curve analysis (DCA) were used to evaluate the nomogram model's efficacy. Results: There were statistical differences between skip-positive group and skip-negative group in tumor location, the maximum diameter (D) and capsule invasion (P<0.05). No statistical differences were observed in sex, age, Hashimoto's thyroiditis, multifocality, anteroposterior diameter/transverse diameter (A/T) ratio, shape, margin, microcalcification, intra-nodular vascularity and preoperative serum thyroglobulin (Tg) (P≥0.05). The risk factors of skip metastases in PTCs were D ≤10 mm, location in the upper portion and capsule invasion. The area under the curve (AUC) of nomogram was 0.877, the accuracy was 85.32%, the sensitivity was 60.98%, and the specificity was 90.96%. The calibration curve and the Hosmer-Lemeshow goodness of fit test showed that the consistency between the nomogram and the actual observation was good. The DCA showed that most PTC patients might benefit from the predictive nomogram model. Conclusions: A nomogram for predicting skip metastases in PTCs may be useful in clinical diagnosis and treatment.