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使用序列瘤生物标志物进行动态风险分析以预测个性化结果
David M Kurtz1, Mohammad S Esfahani2, Florian Scherer2
1Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Division of Hematology, Department of Medicine, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA.
Cell
|July 9, 2019
概括
这项研究引入了持续个性化风险指数 (CIRI),这是动态癌症预测结果的新方法. 通过整合患者的实时数据, CIRI 改善了个性化医疗,
科学领域:
- 癌症学
- 生物统计学
- 计算生物学
背景情况:
- 在癌症中准确预测长期结果是具有挑战性的.
- 传统模型依赖于预处理因素,因为序列瘤采样存在困难.
- 在非侵入性诊断的进步使得序列瘤的评估.
研究的目的:
- 引入持续个性化风险指数 (CIRI) 进行动态的实时结果概率确定.
- 与传统模型相比,证明CIRI的预测准确度有所提高.
- 展示CIRI在开发个性化治疗选择预测生物标志物的实用性.
主要方法:
- 开发了CIRI,一种集成纵向风险预测器的动态风险评估方法.
- 应用CIRI扩散大B细胞淋巴瘤患者的数据.
- 在慢性淋巴细胞白血病和乳腺癌模型中验证了CIRI的实用性.
主要成果:
- 在扩散型大B细胞淋巴瘤中,CIRI显示结果预测的准确性有所提高.
- 这种方法在不同类型的癌症中具有更广泛的适用性.
- 概念验证分析说明了CIRI在预测生物标志物开发方面的潜力.
结论:
- CIRI提供一种动态的癌症预测方法, 增强个性化医疗.
- 动态风险评估有助于定制治疗策略.
- CIRI有可能在瘤学中实现创新治疗模式.
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