"测试和治疗"预测生物标志物的性能测量和临床优势值
Neil Hawkins1, Janet Bouttell2, Dmitry Ponomarev3
1Health Economics and Health Technology Assessment, School of Health and Wellbeing, University of Glasgow, Clarice Pears Building, 90 Byers Road, Glasgow, G12 8TB, UK. Neil.Hawkins@glasgow.ac.uk.
Applied health economics and health policy
|September 2, 2024
概括
预测性生物标志物通过估计治疗反应来指导精准医学. 新的性能指标有助于确定最佳的伴随诊断,确保测试策略提供卓越的临床益处.
科学领域:
- 生物标志物的发现和验证.
- 精准医学应用 精准医学应用
- 临床试验的设计和分析.
背景情况:
- 预测性生物标志物对于个性化医疗至关重要,预测个体治疗疗效.
- 目前的方法缺乏标准化措施来评估生物标志物在预测治疗反应中的性能.
- 这项研究解决了对可靠方法的需求,以评估临床决策中的生物标志物的实用性.
研究的目的:
- 开发和评估用于预测生物标志物的新型绩效指标.
- 为确定何时生物标志物测试策略在临床上优于通用治疗建立值.
- 用现实世界的案例研究来证明这些措施的应用.
主要方法:
- 用一个决策模型来比较基于预期的反应概率的"治疗所有"与"测试和治疗"策略.
- 基于R-Shiny的应用程序是为了可视化预测值,灵敏度和特异性的值而开发的.
- 一个涉及RAS状态和转移性结直肠癌中泛慕马布反应的案例研究被用于说明.
主要成果:
- 值灵敏度和特异性可以从当伴随诊断具有预测性时的响应概率比率来估计.
- 当使用预测值时,确定值受到生物标志物阳性个体的流行程度的影响.
- 该研究为量化预测生物标志物的性能提供了一个框架.
结论:
- 预测生物标志物的建议性能测量是直观的和临床相关的.
- 这些措施有助于识别有前途的伴侣诊断候选人.
- 这些发现强调了实施生物标志物导向测试策略的潜在净益.
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