Hei Hu, Zhou Bin, Gong Wenbo, Zheng Chen, Fang Jugao, Qin Jianwu
Department of Thyroid and Neck, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, 450003, China.
Department of Otolaryngology, Head and Neck Surgery, Thyroid Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China.
Surg Today. 2023 Apr;53(4):507-512. doi: 10.1007/s00595-022-02595-4. Epub 2022 Oct 6.
Central neck metastasis (CNM) is common in patients with papillary thyroid carcinoma (PTC). However, the prediction of CNM risk remains poorly defined, especially for patients with clinically negative lymph nodes. We developed a preoperative clinical nomogram to predict CNM risk in patients with clinical T1-2N0 (cT1-2N0) PTC.
Data from 436 patients with unifocal cT1-2N0 PTC were available. We analyzed the association between preoperative variables and CNM using univariate and multivariate logistic regression and developed a clinical nomogram based on the multivariate regression model. The nomogram was validated externally using an independent dataset.
The CNM rate was 25.5%. Three clinical variables were associated with CNM, including age, gender, and tumor size. We built a CNM nomogram integrating these three variables. It had a poor index of internal discrimination (C-index, 0.655; 95% CI 0.596-0.715) and a poor index of external discrimination (C-index, 0.690; 95% CI 0.611-0.769).
We developed a preoperative nomogram to quantify the risk of CNM in unifocal cT1-2N0 PTC patients. However, our data showed that preoperative clinical parameters were not able to accurately predict the likelihood of CNM. Other variables need to be investigated to improve the prediction capability of this nomogram.
中央区颈部转移(CNM)在甲状腺乳头状癌(PTC)患者中很常见。然而,CNM风险的预测仍不明确,尤其是对于临床淋巴结阴性的患者。我们开发了一种术前临床列线图,以预测临床T1-2N0(cT1-2N0)PTC患者的CNM风险。
有436例单灶性cT1-2N0 PTC患者的数据可供分析。我们使用单因素和多因素逻辑回归分析术前变量与CNM之间的关联,并基于多因素回归模型开发了一种临床列线图。该列线图使用独立数据集进行外部验证。
CNM发生率为25.5%。三个临床变量与CNM相关,包括年龄、性别和肿瘤大小。我们构建了一个整合这三个变量的CNM列线图。其内部判别指数较差(C指数,0.655;95%CI 0.596-0.715),外部判别指数也较差(C指数,0.690;95%CI 0.611-0.769)。
我们开发了一种术前列线图,以量化单灶性cT1-2N0 PTC患者的CNM风险。然而,我们的数据表明,术前临床参数无法准确预测CNM的可能性。需要研究其他变量以提高该列线图的预测能力。