Department of Nuclear Medicine, Guilin Medical University Affiliated Hospital, Guilin, China.
Front Endocrinol (Lausanne). 2024 May 30;15:1361683. doi: 10.3389/fendo.2024.1361683. eCollection 2024.
The objective of this study was to develop a predictive nomogram for intermediate-risk differentiated thyroid cancer (DTC) patients after fixed 3.7GBq (100mCi) radioiodine remnant ablation (RRA).
Data from 265 patients who underwent total thyroidectomy with central lymph node dissection (CND) and received RRA treatment at a single institution between January 2018 and March 2023 were analyzed. Patients with certain exclusion criteria were excluded. Univariate and multivariate logistic regression analyses were performed to identify risk factors for a non-excellent response (non-ER) to RRA. A nomogram was developed based on the risk factors, and its performance was validated using the Bootstrap method with 1,000 resamplings. A web-based dynamic calculator was developed for convenient application of the nomogram.
The study included 265 patients with intermediate-risk DTC. Significant differences were found between the ER group and the non-ER group in terms of CLNM>5, Hashimoto's thyroiditis, sTg level, TgAb level (P < 0.05). CLNM>5 and sTg level were identified as independent risk factors for non-ER in multivariate analysis. The nomogram showed high accuracy, with an area under the curve (AUC) of 0.833 (95% CI = 0.770-0.895). The nomogram's predicted probabilities aligned closely with actual clinical outcomes.
This study developed a predictive nomogram for intermediate-risk DTC patients after fixed 3.7GBq (100mCi) RRA. The nomogram incorporates CLNM>5 and sTg levels as risk factors for a non-ER response to RRA. The nomogram and web-based calculator can assist in treatment decision-making and improve the precision of prognosis information. Further research and validation are needed.
本研究旨在为接受固定剂量 3.7GBq(100mCi)放射性碘残留消融(RRA)治疗的中危分化型甲状腺癌(DTC)患者建立预测列线图。
分析了 2018 年 1 月至 2023 年 3 月在一家单中心接受全甲状腺切除术和中央淋巴结清扫术(CND)并接受 RRA 治疗的 265 例患者的数据。排除了具有某些排除标准的患者。对这些患者进行单因素和多因素逻辑回归分析,以确定 RRA 治疗非完全缓解(non-ER)的危险因素。根据危险因素建立列线图,并使用 1000 次重采样的 Bootstrap 方法验证其性能。开发了一个基于网络的动态计算器,方便列线图的应用。
本研究纳入了 265 例中危 DTC 患者。ER 组与 non-ER 组在 CLNM>5、桥本甲状腺炎、sTg 水平、TgAb 水平方面存在显著差异(P<0.05)。多因素分析显示 CLNM>5 和 sTg 水平是 non-ER 的独立危险因素。列线图具有较高的准确性,曲线下面积(AUC)为 0.833(95%CI=0.770-0.895)。列线图的预测概率与实际临床结局吻合较好。
本研究为接受固定剂量 3.7GBq(100mCi)RRA 治疗的中危 DTC 患者建立了预测列线图。该列线图将 CLNM>5 和 sTg 水平作为 RRA 治疗 non-ER 反应的危险因素。列线图和基于网络的计算器可以辅助治疗决策,并提高预后信息的准确性。需要进一步的研究和验证。