Institution: | 1. Department of Radiology, First Central Clinical College, Tianjin Medical University, Tianjin, China;2. Department of Ultrasonography, Binzhou Medical University Hospital, Binzhou City, Shandong, China;3. Department of Radiology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China;4. Department of Radiology, National Clinical Research Center for Chinese Medcine Acupuncture and Moxibustion, Tianjin, China;5. Department of Radiology, The Second Hospital of Tianjin Medical University, Tianjin, China;6. Department of Radiology, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China |
Abstract: | ObjectiveTo develop and validate an individualized risk prediction model for the need for central cervical lymph node dissection in patients with clinical N0 papillary thyroid carcinoma (PTC) diagnosed using ultrasound.MethodsUpon retrospective review, derivation and internal validation cohorts comprised 1585 consecutive patients with PTC treated from January 2017 to December 2019 at hospital A. The external validation cohort consisted of 406 consecutive patients treated at hospital B from January 2016 to June 2020. Independent risk factors for central cervical lymph node metastasis (CLNM) were determined through univariable and multivariable logistic regression analysis. An individualized risk prediction model was constructed and illustrated as a nomogram, which was internally and externally validated.ResultsThe following risk factors of CLNM were established: a solitary primary thyroid nodule’s diameter, shape, calcification, and capsular abutment-to-lesion perimeter ratio. The areas under the receiver operating characteristic curves of the risk prediction model for the internal and external validation cohorts were 0.921 and 0.923, respectively. The calibration curve showed good agreement between the nomogram-estimated probability of CLNM and the actual CLNM rates in the 3 cohorts. The decision curve analysis confirmed the clinical usefulness of the nomogram.ConclusionThis study developed and validated a model for predicting the risk of CLNM in individual patients with clinical N0 PTC, which should be an efficient tool for guiding clinical treatment. |