对于IIB期子宫癌患者的预后不同,这些患者具有单边或双边的参数性侵袭,并同时接受化疗或放射治疗
Xi-Lin Yang1, Li-Chun Wei2, Jian-Li He3
1Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 10000, China.
The oncologist
|October 16, 2025
概括
双边参数侵袭 (BL) 宫癌 (CC) 患者的预后比单边参数侵袭 (UL) 患者的预后更差. 参数体侵袭 (PI) 是预测IIB期CC患者预后的最重要因素.
科学领域:
- 妇科瘤学 妇科瘤学
- 癌症研究 癌症研究
- 医疗成像医学成像
背景情况:
- 宫癌 (CC) 的分期对预后至关重要.
- 参数入侵 (PI) 是高级CC的关键因素.
- 区分单边 (UL) 和双边 (BL) 的PI可以完善预后评估.
研究的目的:
- 为了比较IIB阶段CC患者与UL相比BL参数入侵之间的生存结果.
- 为了评估在IIB阶段的参数入侵 (PI) 的预后意义,CC.
- 使用机器学习开发一个用于IIB CC阶段预后的预测模型.
主要方法:
- 对506名IIB期CC患者的回顾性分析.
- 在倾向性得分匹配 (PSM) 之前和之后,UL和BL组之间的生存率的比较.
- 开发和验证一个随机森林 (RF) 模型与SHAP分析特征的重要性.
主要成果:
- 与BL疾病相比,UL疾病患者在PSM前后显示出明显更好的5年整体存活率 (OS) 和无进展存活率 (PFS),无论是在PSM前后.
- 阴道入侵 (VI) 在这两组中都没有显著影响生存率.
- 射频模型表现出强大的预测能力 (AUCtrain=0.893,AUCval=0.879),确定PI作为最重要的预后特征.
结论:
- 双边参数入侵 (BL) 与单边参数入侵 (UL) 相比,在2018年FIGOIIB期子宫癌 (CC) 中的预后更差.
- 参数突入 (PI) 是这些患者预后预测最关键的因素.
- 机器学习模型,特别是带有SHAP的RF,可以有效预测预后,并确定晚期宫癌的关键预后因素.
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