竞争性风险分析的预后在患有毛膜黑色素瘤的患者
Ruisheng Huang1,2, Jian Chen2, Jun Lyu3
1Department of Ophthalmology, Shantou Central Hospital, Shantou, 515031, China.
Discover oncology
|December 18, 2025
概括
竞争的风险模型提供了比传统的Cox模型更准确的预后因子识别为毛膜黑色素瘤 (UM) 患者. 这项研究强调了他们对UM生存的优越预测能力.
科学领域:
- 在瘤学瘤学.
- 生物统计学 生物统计学
- 眼科医生 眼科 眼科
背景情况:
- 卵巢黑色素瘤 (UM) 预后评估可能会受到竞争风险的偏见.
- 经典的Cox比例危险模型可能无法充分解决UM患者中的这些竞争性风险.
研究的目的:
- 将竞争风险模型应用于SEER数据库,以确定UM预测因素.
- 将竞争风险模型的发现与传统的考克斯 UM 的比例危险模型进行比较.
主要方法:
- 利用监测,流行病学和最终结果 (SEER) 数据库 (2010-2015) 获取UM患者数据.
- 使用累积发病率函数 (CIF) 和格雷测试进行了单变量分析.
- 通过使用细灰,因果特定 (CS) 和Cox比例危险模型进行了多变量分析.
主要成果:
- 六个变量显著影响了UM患者生存预后 (P<0.05).
- 竞争的风险模型 (细灰,CS) 确定年龄,种族,组织学类型,AJCC阶段和手术作为独立的预测因素.
- 与竞争风险模型相比,考克斯模型在统计显著性和危险比率估计中表现出偏差.
结论:
- 竞争的风险模型可以更准确地评估毛膜黑色素瘤的预后因素.
- 这些模型优于传统方法,这些方法在UM预后中不考虑竞争的风险因素.
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