术前评估甲状腺乳头状癌（PTC）患者侧颈淋巴结转移（LLNM）一直是临床上的主要挑战之一。本研究旨在开发和验证与碘营养相关的百分点图模型，以预测PTC患者的侧颈淋巴结转移。本研究为回顾性研究。分别在187例LLNM患者和289例非LLNM（NLLNM）患者中测量了尿碘浓度（UIC）和血清碘浓度（SIC）。所有患者被随机分成训练组（n = 355）和验证组（n = 121）。利用 logistic 回归分析，分析了碘营养相关因素和临床病理特征对PTC患者LLNM的影响。采用套索回归方法筛选风险因素，并构建了预测LLNM的百分点图。训练组和验证组进行了百分点图模型的接受者操作特征曲线（ROC曲线）、标定曲线和决策曲线分析（DCA）。性别、SIC、吸烟史、饮酒史、PTC家族史、多发性、双侧或单侧肿瘤、TSH、Tg和肿瘤大小被纳入预测LLNM的百分点图模型，其曲线下面积（AUC）为0.795。百分点图模型在训练组和验证组中显示出良好的标定和临床获益。基于碘营养和其他临床病理特征的百分点图模型对预测PTC患者的侧颈淋巴结转移是有效的。

Preoperative evaluation of lateral lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) has been one of the major clinical challenges. This study aims to develop and validate iodine nutrition-related nomogram models to predict lateral cervical lymph node metastasis in patients with PTC.This is a retrospective study. Urinary iodine concentration (UIC) and serum iodine concentration (SIC) were measured in 187 LLNM patients and 289 non-LLNM (NLLNM) patients. All patients were randomized 3:1 into the training cohort (n = 355) and the validation cohort (n = 121). Using logistic regression analysis, we analyzed the influence of iodine nutrition-related factors and clinicopathological characteristics on LLNM in PTC patients. Lasso regression method was used to screen risk factors and construct a nomogram for predicting LLNM. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) of the nomogram models were carried out for the training and validation cohorts.Gender, SIC, smoking history, drinking history, family history of PTC, multifocality, bilateral or unilateral tumors, TSH, Tg, and tumor size were included in the nomogram model predicting LLNM, with an area under the curve (AUC) of .795. The nomogram model showed good calibration and clinical benefit in both the training and validation cohorts.The nomogram model based on iodine nutrition and other clinicopathological features is effective for predicting the lateral lymph node metastasis in PTC patients.