NMAsurv:基于生存数据的网络元分析的R Shiny应用程序
Taihang Shao1,2, Mingye Zhao1, Fenghao Shi3
1Center for Pharmacoeconomics and Outcome Research, China Pharmaceutical University, Nanjing, China.
Research synthesis methods
|February 2, 2026
概括
对生存数据的网络元分析 (NMA) 现在可以通过NMAsurv访问,NMAsurv是一个R Shiny工具,简化了复杂的非比例危险 (非PH) 模型,用于没有高级编程技能的研究人员.
科学领域:
- 生物统计学 生物统计学
- 医疗信息学 医疗信息学
- 医学研究方法学 医学研究方法学
背景情况:
- 网络元分析 (NMA) 对于在不同试验中比较多种干预措施至关重要,特别是在医疗应用中.
- 传统的NMA生存数据依赖于比例危险 (PH) 假设,仅合成危险比率 (HRs).
- 已有先进的非PH NMA 方法,但需要大量的编程专业知识,限制了它们的采用.
研究的目的:
- 介绍NMAsurv,一个用户友好的R Shiny工具,专为基于生存数据的NMA而设计.
- 为了使具有有限R编程经验的研究人员能够进行复杂的生存NMA.
- 为各种NMA功能提供一个直观的平台,包括模型构建和假设测试.
主要方法:
- 开发NMAsurv,这是一个通过Web界面访问的R Shiny应用程序.
- 支持伪个人参与者数据和聚合数据输入.
- 实现一个点击接口用于网络绘图,PH假设测试和NMA模型估计 (包括分数多项式,块式指数式,参数式,Cox PH和通用马模型).
主要成果:
- NMAsurv提供了轻松执行生存NMA,包括生存和HR情节生成.
- 该工具可以容纳各种NMA模型和数据输入类型.
- 通过现实世界NMA示例来展示NMAsurv的实用性.
结论:
- NMAsurv显著降低了执行高级生存NMA的进入障碍.
- 该工具使更广泛的研究人员能够对时间到事件数据进行复杂的分析.
- NMAsurv促进了在医学和其他领域利用生存分析进行强有力的比较有效性研究.
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