对肺状细胞癌患者的死亡风险预测模型的构建和应用:竞争风险分析
Qin Wang1,2,3, Qianqian Wang1,2,3, Di Wang4
1School of Public Health, Shandong Second Medical University, Weifang, China.
Journal of cancer research and therapeutics
|September 4, 2025
概括
这项研究开发了一个新的模型来预测肺状细胞癌 (LUSC) 死亡率,考虑竞争的风险以获得更准确的患者结果. 在精确的LUSC风险评估中,Fine-Gray模型被证明是优越的.
科学领域:
- 癌症学
- 生物统计学
- 流行病学
背景情况:
- 肺状细胞癌 (LUSC) 是一种主要的肺癌亚型,通常在晚期被诊断为转移性.
- 在LUSC中出现症状的延迟有助于晚期诊断和需要准确的预后工具.
- 现有的LUSC预后模型可能会通过不考虑竞争风险来高估发病率.
研究的目的:
- 开发和验证LUSC的竞争风险死亡预测模型.
- 提高个性化LUSC治疗策略的预后评估的准确性.
- 在竞争风险框架内确定LUSC死亡率的关键预测因素.
主要方法:
- 使用了来自SEER数据库的28,312名LUSC患者 (2000-2019) 的数据.
- 使用因果特异性危险和细灰风险模型来分析竞争风险.
- 使用Harrell的对应指数和校准图表评估模型性能.
主要成果:
- 年龄,性别,治疗,婚姻状况,瘤部位,分化和阶段是LUSC的重要预后因素.
- 与因果特异性危险模型相比,Fine-Gray模型对3年和5年LUSC死亡率的预测准确度略高.
- 主要死亡预测因素包括年龄,男性性别,缺乏手术/化疗/放射治疗,未婚状态,特定瘤位置,差异化和晚期.
结论:
- 细灰风险模型有效预测LUSC死亡率,具有显著的临床实用性.
- 准确的竞争性风险分析对于可靠的LUSC预测至关重要.
- 鉴定出的风险因素可以为LUSC患者提供个性化治疗和风险分层.
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