Tang Yulong, Wu Peng, Zhou Shiwei, Li Hui, Song Xiaohua, Li Wu, Peng Xiaowei
Department of thyroid surgery, Hunan Cancer Hospital & The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, No. 238 Tongzipo Road, Changsha, 410013, Hunan Province, P. R. China.
Sci Rep. 2025 Aug 21;15(1):30819. doi: 10.1038/s41598-025-16916-3.
Given the scarcity of studies predicting iodine-131 treatment failure based on clinicopathological factors, this study aimed to determine whether clinicopathological features can predict iodine-131 treatment failure in differentiated thyroid carcinoma (DTC) patients. A total of 182 patients were analyzed, including 114 with favorable outcomes and 68 with resistance or poor outcomes. Patients were split into a training set (122 patients) and a validation set (60 patients). Logistic regression identified the number of lateral neck lymph node metastases (P = 0.001) and pre-radioactive iodine therapy serum thyroglobulin levels (P = 0.001) as independent predictors of treatment failure. The predictive model, visualized via a nomogram, achieved area under curves (AUCs) of 0.838 (95% CI, 0.759-0.917) and 0.766 (95% CI, 0.626-0.905) in the training and validation sets, respectively. Calibration curves showed good agreement between predicted and observed outcomes, and decision curve analysis confirmed the model's clinical utility. Subgroup analyses yielded AUCs of 0.777 (95% CI, 0.648-0.906), 0.745 (95% CI, 0.646-0.843), 0.734 (95% CI, 0.649-0.820), and 0.911 (95% CI, 0.769-0.999) for male, female, age < 55, and age ≥ 55 groups, respectively. This model effectively predicts iodine-131 treatment failure risk in DTC patients, providing valuable information for clinical decision-making.
鉴于基于临床病理因素预测碘-131治疗失败的研究较少,本研究旨在确定临床病理特征是否能预测分化型甲状腺癌(DTC)患者的碘-131治疗失败。共分析了182例患者,其中114例预后良好,68例耐药或预后不良。患者被分为训练集(122例患者)和验证集(60例患者)。逻辑回归确定侧颈淋巴结转移数量(P = 0.001)和放射性碘治疗前血清甲状腺球蛋白水平(P = 0.001)为治疗失败的独立预测因素。通过列线图可视化的预测模型在训练集和验证集中的曲线下面积(AUC)分别为0.838(95%CI,0.759 - 0.917)和0.766(95%CI,0.626 - 0.905)。校准曲线显示预测结果与观察结果之间具有良好的一致性,决策曲线分析证实了该模型的临床实用性。亚组分析得出男性、女性、年龄<55岁和年龄≥55岁组的AUC分别为0.777(95%CI,0.648 - 0.906)、0.745(95%CI,0.646 - 0.843)、0.734(95%CI,0.649 - 0.820)和0.911(95%CI,0.769 - 0.999)。该模型有效地预测了DTC患者碘-131治疗失败的风险,为临床决策提供了有价值的信息。