使用风险预测模型为个性化,具有成本效益的治疗建议提供信息
Mariana R Neves1, Molly Franke2, Carole Mitnick2
1Department of Health Policy and Management, Yale School of Public Health, New Haven, USA.
medRxiv : the preprint server for health sciences
|August 20, 2025
概括
新的方法将疾病风险预测与决策建模相结合,以实现个性化,具有成本效益的治疗选择. 这种方法可以改善健康结果和资源使用,特别是当诊断测试无法使用时.
科学领域:
- 卫生经济学 卫生经济学
- 临床决策的过程
- 生物统计学 生物统计学
背景情况:
- 诊断不确定性需要依赖临床判断和预测模型.
- 现有的预测模型往往忽视下游的健康和成本影响.
- 个性化治疗需要将风险评估与决策分析整合起来.
研究的目的:
- 开发和评估将风险预测与决策建模整合的方法.
- 为个人和经济有效的治疗建议提供信息.
- 通过考虑健康和成本结果,最大限度地提高人口净货币效益 (NMB).
主要方法:
- 开发了两种整合方法:基于概率的和基于分类的.
- 这些方法的应用是为了优化对抗利芬辛耐药结核病的治疗选择.
- 该分析考虑了治疗方案的成本,毒性和疗效.
主要成果:
- 这两种整合方法都改善了与标准护理和固定门相比的人口NMB.
- 基于分类的方法证明了对预测模型校准的稳定性.
- 该研究强调了在资源有限的环境中集成模型的价值.
结论:
- 将风险预测与决策模型相结合,为基于价值的治疗决策提供了一个框架.
- 这些方法通过考虑健康和成本后果来提高护理质量.
- 这种方法在诊断不确定性的情况下尤为有益.
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