跨学科研究中的挑战和机遇以及医疗技术评估中的治疗序列的现实世界数据
Jen-Yu Amy Chang1, James B Chilcott2, Nicholas R Latimer2,3
1Sheffield Centre for Health and Related Research (SCHARR), Division of Population Health, School of Medicine and Population Health, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK. jy.a.chang@sheffield.ac.uk.
PharmacoEconomics
|April 1, 2024
概括
在卫生技术评估 (HTA) 中评估治疗序列存在挑战. 现实世界数据 (RWD) 和因果推理方法,如目标试验模拟,为评估治疗序列有效性提供了有希望的解决方案.
科学领域:
- 医疗技术评估 (HTA) 是指对医疗技术进行评估.
- 决策科学 决策科学
- 相对有效性研究研究比较
背景情况:
- 越来越多的治疗选择需要对治疗序列进行严格的评估.
- 当前卫生技术评估 (HTA) 方法在评估复杂的治疗序列时面临挑战.
研究的目的:
- 系统地审查在HTA内评估治疗序列的挑战.
- 确定序列评估的方法进步和未来研究方向.
主要方法:
- 对治疗序列评估的方法学研究的系统文献综述.
- 综合发现与现有的HTA指南进行比较.
- 探索跨学科的方法 (统计,流行病学,因果推理,运营研究,计算机科学).
主要成果:
- 关键的挑战包括选择合适的模型,在数据稀缺的情况下获得有效性证据,管理假设,考虑位移和计算优化.
- 对治疗序列有效性的数据稀缺是一个主要问题,因为在临床试验中很少比较序列.
- 现实世界数据 (RWD) 和因果推理方法,特别是目标试验模拟,显示出对评估序列有效性的承诺.
结论:
- 整合多种方法可以解决治疗序列评估中的挑战.
- 未来的研究应该专注于利用RWD和因果推理来评估治疗序列的有效性.
- 这种方法可以为HTA建议和外部控制武器的合成提供信息.
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