开发和验证一种多变量预后预测分类器,用于治疗口腔状细胞癌的升级:PREDICTR-OPC研究
Hisham Mehanna1, Davy Rapozo2, Sandra V von Zeidler3
1Institute of Head and Neck Studies and Education, University of Birmingham, Birmingham, United Kingdom.
概括
这项研究开发了一种新的预后分类器,用于口腔状细胞癌 (OPSCC),使用p16和HPV等生物标志物. 该模型预测高风险患者的治疗效益,有助于OPSCC的个性化药物.
科学领域:
- 在瘤学瘤学.
- 翻译研究是翻译研究.
- 生物标志物发现发现
背景情况:
- 口腔状细胞癌 (OPSCC) 缺乏用于治疗选择的验证预测模型.
- 现有的预后分类器不能有效指导治疗决策.
研究的目的:
- 开发和验证临床和/或生物标志物预测模型,用于OPSCC.患者的治疗结果和治疗升级.
- 确定预测对不同治疗策略的反应的因素.
主要方法:
- 追溯分析了来自英国和波兰的985起OPSCC病例 (1999-2012).
- 组织微阵列的构建,10个生物标记物的免疫组织化学和HPV DNA in situ杂交.
- 多变量回归和倾向得分对发展 (600名患者) 和验证 (385名患者) 队列进行调整.
主要成果:
- 一个生物标志物分类器 (p16,幸存者,HPV DNA,TILs) 预测了高风险OPSCC患者的手术+辅助疗法对初级化疗放射治疗的益处.
- 在高风险组的3年整体存活率显著改善 (63.1%对41.1%,HR=0.32,P=0.002).
- 分类器显示中等的预测能力 (一致性指数0.73) 和没有显著的预测在低风险组.
结论:
- 为OPSCC开发了一种新的预后分类器,具有适度的预测能力.
- 该分类器显示了引导治疗选择的潜力,特别是在高风险的OPSCC患者中.
- 未来环境中的外部验证正在进行中,以确认发现并支持临床采用.
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