Clinical outcome and influencing factors of differentiated thyroid cancer with biochemical incomplete response.

IF 2.6 4区医学 Q2 ONCOLOGY

Future oncology Pub Date : 2025-09-01 Epub Date: 2025-08-20 DOI:10.1080/14796694.2025.2548161

Congcong Wang, Guohua Qin, Shuhui Wang, Yutian Li, Yaqi Lu, Xia Shen, Wei Sun, Jiao Li, Na Han, Chenghui Lu, Guoqiang Wang, Yingying Zhang, ZengHua Wang, Zengmei Si, Fengqi Li, Xufu Wang, Yansong Lin, Xinfeng Liu

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引用次数: 0

Abstract

Purpose: The aim of our study was to investigate the clinical outcomes and predictive factors in patients with biochemical incomplete response (BIR) after initial radioiodine therapy (RAI).

Materials & methods: This retrospective study enrolled 198 patients with BIR from two institutions and stratified them into a training cohort (Qingdao cohort, n = 144) and an external validation cohort (Beijing cohort, n = 54). The patients were classified as having incomplete response (IR) or non-IR disease at the final follow-up. Univariate and multivariate analyses identified IR predictors in the training cohort. A nomogram was developed using the training cohort and was validated in the validation cohort using calibration curves, decision curve analysis (DCA), and receiver operating characteristic analysis.

Results: Age, recurrence risk, pre-stimulated thyroglobulin (ps-Tg), and BRAF^V600E mutation were independent predictors of IR in the training cohort. The nomogram identified ps-Tg as the strongest predictor of IR risk, followed by the BRAF^V600E mutation, age, and recurrence risk. The calibration curves demonstrated excellent agreement between the predicted and observed probabilities. DCA confirmed favorable clinical utility.

Conclusions: This validated nomogram provides a clinically useful tool for quantifying IR risk in BIR patients, supporting personalized management decisions after initial RAI.

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分化型甲状腺癌生化反应不完全的临床结局及影响因素分析。

目的：探讨放射性碘初始治疗（RAI）后生化不完全缓解（BIR）患者的临床结局及预测因素。材料与方法：本回顾性研究纳入来自两个机构的198例BIR患者，并将其分为培训队列（青岛队列，n = 144）和外部验证队列（北京队列，n = 54）。在最后的随访中，患者被分为不完全缓解（IR）或非IR疾病。单变量和多变量分析确定了培训队列中的IR预测因子。在训练队列中建立nomogram，并在验证队列中使用校准曲线、决策曲线分析（decision curve analysis， DCA）和受试者工作特征分析进行验证。结果：年龄、复发风险、预刺激甲状腺球蛋白（ps-Tg）和BRAFV600E突变是训练队列中IR的独立预测因素。nomogram发现ps-Tg是IR风险的最强预测因子，其次是BRAFV600E突变、年龄和复发风险。校正曲线显示了预测概率与观测概率之间的良好一致性。DCA证实了良好的临床应用。结论：这个经过验证的nomogram为量化BIR患者的IR风险提供了一个临床有用的工具，支持初次RAI后的个性化管理决策。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Future oncology ONCOLOGY-

CiteScore

5.40

自引率

3.00%

发文量

335

审稿时长

4-8 weeks

期刊介绍： Future Oncology (ISSN 1479-6694) provides a forum for a new era of cancer care. The journal focuses on the most important advances and highlights their relevance in the clinical setting. Furthermore, Future Oncology delivers essential information in concise, at-a-glance article formats - vital in delivering information to an increasingly time-constrained community. The journal takes a forward-looking stance toward the scientific and clinical issues, together with the economic and policy issues that confront us in this new era of cancer care. The journal includes literature awareness such as the latest developments in radiotherapy and immunotherapy, concise commentary and analysis, and full review articles all of which provide key findings, translational to the clinical setting.