甲状腺髓癌患者无进展生存的预后因素:一个多中心队列研究
Guibin Zheng1, Jianing Liu2, Hao Xu3
1Department of Thyroid Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, 264000, Shandong, China.
Updates in surgery
|May 20, 2025
概括
这项研究确定了状甲状腺癌 (MTC) 无进展生存 (PFS) 的关键预后因素. 转移性淋巴结比率 (LNR) 0.19或更高是MTC患者显著不良预后因素.
科学领域:
- 在瘤学瘤学.
- 手术瘤学手术瘤学
- 内分泌学 在内分泌学.
背景情况:
- 骨髓甲状腺癌 (MTC) 由于其具有攻击性,在手术后经常复发.
- 在MTC中无进展生存 (PFS) 的预后因素仍然不充分理解.
- 确定这些因素对于患者管理和治疗策略至关重要.
研究的目的:
- 在被诊断为MTC的患者中调查和确定与PFS相关的独立预后因素.
- 为了确定转移性淋巴结比率 (LNR) 在预测PFS的最佳切断值.
- 在一个独立的队列中,验证已识别的LNR切线对总生存率 (OS) 和疾病特异性生存率 (DSS) 的预测值.
主要方法:
- 来自中国山东15个中心的MTC患者的回顾性分析 (2010-2021).
- 用单变量和多变量考克斯回归分析来确定PFS的预后因素.
- 接收机运行特征 (ROC) 曲线分析确定了最佳的LNR切线;使用SEER数据库进行验证.
主要成果:
- 在山东队列中,甲状腺外延伸,LNR (HR 2.806) 和T3阶段被确定为PFS的独立风险因素.
- 对于LNR预测PFS的最佳切割值被确定为0.19.
- 与LNR<0.19的患者相比,LNR≥0.19的患者在两个队伍中表现出明显更差的PFS,OS和DSS,而LNR<0.19的患者在两个队伍中都表现出明显更差的PFS,OS和DSS.
结论:
- 甲状腺外延伸,T3阶段和LNR是MTC中PFS显著的独立预后因素.
- 0.19的LNR作为关键值,表明MTC患者的生存结果较差.
- LNR ≥0.19的切线显示了PFS,OS和DSS的强大预测价值,有助于MTC的风险分层.
相关概念视频
02:07Tumor Progression
6.2K
Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
6.2K
01:21Cancer Survival Analysis
315
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
315