DataSheet2_A comprehensive prediction model for central lymph node metastasis in papillary thyroid carcinoma with Hashimoto’s thyroiditis: BRAF may not be a valuable predictor.docx

PurposePapillary thyroid carcinoma (PTC) frequently coexists with Hashimoto’s thyroiditis (HT), which poses challenges in detecting central lymph node metastasis (CLNM) and determining optimal surgical management. Our study aimed to identify the independent predictors for CLNM in PTC patients with HT and develop a comprehensive prediction model for individualized clinical decision-making.
Patients and methodsIn this retrospective study, a total of 242 consecutive PTC patients who underwent thyroid surgery and central lymph node dissection between February 2019 and December 2021 were included. 129 patients with HT were enrolled as the case group and 113 patients without HT as control. The results of patients’ general information, laboratory examination, ultrasound features, pathological evaluation, and BRAF mutation were collected. Multivariate logistic regression analysis was used to identify independent predictors, and the prediction model and nomogram were developed for PTC patients with HT. The performance of the model was assessed using the receiver operating characteristic curve, calibration curve, decision curve analysis, and clinical impact curve. In addition, the impact of the factor BRAF mutation was further evaluated.
ResultsMultivariate analysis revealed that gender (OR = 8.341, P = 0.013, 95% CI: 1.572, 44.266), maximum diameter (OR = 0.316, P = 0.029, 95% CI: 0.113, 0.888), multifocality (OR = 3.238, P = 0.010, 95% CI: 1.319, 7.948), margin (OR = 2.750, P = 0.046, 95% CI: 1.020, 7.416), and thyrotropin receptor antibody (TR-Ab) (OR = 0.054, P = 0.003, 95% CI: 0.008, 0.374) were identified as independent predictors for CLNM in PTC patients with HT. The area under the curve of the model was 0.82, with accuracy, sensitivity, and specificity of 77.5%, 80.3% and 75.0%, respectively. Meanwhile, the model showed satisfactory performance in the internal validation. Moreover, the results revealed that BRAF mutation cannot further improve the efficacy of the prediction model.
ConclusionMale, maximum diameter > 10mm, multifocal tumors, irregular margin, and lower TR-Ab level have significant predictive value for CLNM in PTC patients with HT. Meanwhile, BRAF mutation may not have a valuable predictive role for CLNM in these cases. The nomogram constructed offers a convenient and valuable tool for clinicians to determine surgical decision and prognostication for patients.

目的：甲状腺乳头状癌（Papillary thyroid carcinoma, PTC）常与桥本甲状腺炎（Hashimoto’s thyroiditis, HT）合并发生，这为中央区淋巴结转移（central lymph node metastasis, CLNM）的检测及最优手术方案的制定带来了诸多诊疗挑战。本研究旨在明确合并HT的PTC患者发生CLNM的独立危险因素，并构建适用于个体化临床决策的综合预测模型。

患者与方法：本项回顾性研究共纳入2019年2月至2021年12月期间接受甲状腺手术及中央区淋巴结清扫的242例连续性PTC患者。其中129例合并HT的患者作为病例组，113例未合并HT的患者作为对照组。本研究收集了患者的一般资料、实验室检查结果、超声特征、病理评估结果及BRAF突变（BRAF mutation）情况。采用多因素logistic回归分析（multivariate logistic regression analysis）筛选CLNM的独立危险因素，并为合并HT的PTC患者构建预测模型及列线图（nomogram）。通过受试者工作特征曲线（receiver operating characteristic curve）、校准曲线、决策曲线分析及临床影响曲线评估模型的预测性能。此外，本研究进一步评估了BRAF突变对该预测模型的影响。

结果：多因素回归分析结果显示，性别（OR=8.341，P=0.013，95%CI：1.572~44.266）、肿瘤最大径（OR=0.316，P=0.029，95%CI：0.113~0.888）、肿瘤多灶性（OR=3.238，P=0.010，95%CI：1.319~7.948）、肿瘤边缘不规则（OR=2.750，P=0.046，95%CI：1.020~7.416）及促甲状腺素受体抗体（thyrotropin receptor antibody, TR-Ab）（OR=0.054，P=0.003，95%CI：0.008~0.374）为合并HT的PTC患者发生CLNM的独立危险因素。该预测模型的曲线下面积为0.82，准确率、敏感度及特异度分别为77.5%、80.3%及75.0%。同时，模型在内部验证中展现出良好的预测性能。此外，研究结果提示BRAF突变无法进一步提升该预测模型的临床效能。

结论：男性、肿瘤最大径＞10mm、多灶性肿瘤、边缘不规则及低水平TR-Ab对合并HT的PTC患者发生CLNM具有显著的预测价值。与此同时，BRAF突变在该类患者中对CLNM并无显著预测作用。本研究构建的列线图（nomogram）可为临床医师制定手术决策及评估患者预后提供便捷实用的辅助工具。