Dynamic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma
Xianhua Zhuo, Jiandong Yu, Zhiping Chen, Zeyu Lin, Xiaoming Huang, Qin Chen, Hongquan Zhu, Yunle Wan
Abstract
OBJECTIVE: To establish a dynamic nomogram based on preoperative clinical data for prediction of lateral lymph node metastasis (LLNM) of papillary thyroid carcinoma. STUDY DESIGN: Retrospective study. SETTING: The Sixth Affiliated Hospital of Sun Yat-Sen University. METHODS: The data of 477 patients from 2 centers formed the training group and validation group and were retrospectively reviewed. Preoperative clinical factors influencing LLNM were identified by univariable and multivariable analysis and were to construct a predictive dynamic nomogram for LLNM. Receiver operating characteristic analysis and calibration curves were used to evaluate the predictive power of the nomogram. RESULTS: = .004), and lymph node location. The dynamic nomogram constructed with these factors is available at https://zxh1119.shinyapps.io/DynNomapp/. The nomogram showed good performance, with an area under the curve of 0.956 (95% CI, 0.925-0.986), a sensitivity of 0.87, and a specificity of 0.91, if high-risk patients were defined as those with a predicted probability ≥0.3 or total score ≥200. The nomogram performed well in the external validation cohort (area under the curve, 0.915; 95% CI, 0.862-0.967). CONCLUSIONS: The dynamic nomogram for preoperative prediction of LLNM in papillary thyroid carcinoma can help surgeons identify high-risk patients and develop individualized treatment plans.