Quan Dai1, Dongmei Liu1, Yi Tao1, Chao Ding2, Shouqiang Li1, Chen Zhao1, Zhuo Wang1, Yangyang Tao1, Jiawei Tian1, Xiaoping Leng3. 1. Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China. 2. Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China. 3. Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nan Gang District, Harbin, 150000, Heilongjiang Province, China. xpleng@ems.hrbmu.edu.cn.
Abstract
OBJECTIVES: To establish a nomogram for predicting central lymph node metastasis (CLNM) based on the preoperative clinical and multimodal ultrasound (US) features of papillary thyroid carcinoma (PTC) and cervical LNs. METHODS: Overall, 822 patients with PTC were included in this retrospective study. A thyroid tumor ultrasound model (TTUM) and thyroid tumor and cervical LN ultrasound model (TTCLNUM) were constructed as nomograms to predict the CLNM risk. Areas under the curve (AUCs) evaluated model performance. Calibration and decision curves were applied to assess the accuracy and clinical utility. RESULTS: For the TTUM training and test sets, the AUCs were 0.786 and 0.789 and bias-corrected AUCs were 0.786 and 0.831, respectively. For the TTCLNUM training and test sets, the AUCs were 0.806 and 0.804 and bias-corrected AUCs were 0.807 and 0.827, respectively. Calibration and decision curves for the TTCLNUM nomogram exhibited higher accuracy and clinical practicability. The AUCs were 0.746 and 0.719 and specificities were 0.942 and 0.905 for the training and test sets, respectively, when the US tumor size was ≤ 8.45 mm, while the AUCs were 0.737 and 0.824 and sensitivity were 0.905 and 0.880, respectively, when the US tumor size was > 8.45 mm. CONCLUSION: The TTCLNUM nomogram exhibited better predictive performance, especially for the CLNM risk of different PTC tumor sizes. Thus, it serves as a useful clinical tool to supply valuable information for active surveillance and treatment decisions. KEY POINTS: • Our preoperative noninvasive and intuitive prediction method can improve the accuracy of central lymph node metastasis (CLNM) risk assessment and guide clinical treatment in line with current trends toward personalized treatments. • Preoperative clinical and multimodal ultrasound features of primary papillary thyroid carcinoma (PTC) tumors and cervical LNs were directly used to build an accurate and easy-to-use nomogram for predicting CLNM. • The thyroid tumor and cervical lymph node ultrasound model exhibited better performance for predicting the CLNM of different PTC tumor sizes. It may serve as a useful clinical tool to provide valuable information for active surveillance and treatment decisions.
OBJECTIVES: To establish a nomogram for predicting central lymph node metastasis (CLNM) based on the preoperative clinical and multimodal ultrasound (US) features of papillary thyroid carcinoma (PTC) and cervical LNs. METHODS: Overall, 822 patients with PTC were included in this retrospective study. A thyroid tumor ultrasound model (TTUM) and thyroid tumor and cervical LN ultrasound model (TTCLNUM) were constructed as nomograms to predict the CLNM risk. Areas under the curve (AUCs) evaluated model performance. Calibration and decision curves were applied to assess the accuracy and clinical utility. RESULTS: For the TTUM training and test sets, the AUCs were 0.786 and 0.789 and bias-corrected AUCs were 0.786 and 0.831, respectively. For the TTCLNUM training and test sets, the AUCs were 0.806 and 0.804 and bias-corrected AUCs were 0.807 and 0.827, respectively. Calibration and decision curves for the TTCLNUM nomogram exhibited higher accuracy and clinical practicability. The AUCs were 0.746 and 0.719 and specificities were 0.942 and 0.905 for the training and test sets, respectively, when the US tumor size was ≤ 8.45 mm, while the AUCs were 0.737 and 0.824 and sensitivity were 0.905 and 0.880, respectively, when the US tumor size was > 8.45 mm. CONCLUSION: The TTCLNUM nomogram exhibited better predictive performance, especially for the CLNM risk of different PTC tumor sizes. Thus, it serves as a useful clinical tool to supply valuable information for active surveillance and treatment decisions. KEY POINTS: • Our preoperative noninvasive and intuitive prediction method can improve the accuracy of central lymph node metastasis (CLNM) risk assessment and guide clinical treatment in line with current trends toward personalized treatments. • Preoperative clinical and multimodal ultrasound features of primary papillary thyroid carcinoma (PTC) tumors and cervical LNs were directly used to build an accurate and easy-to-use nomogram for predicting CLNM. • The thyroid tumor and cervical lymph node ultrasound model exhibited better performance for predicting the CLNM of different PTC tumor sizes. It may serve as a useful clinical tool to provide valuable information for active surveillance and treatment decisions.
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