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An R-Based Landscape Validation of a Competing Risk Model
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对二进制结果临床意义风险量化的实用主义观点
1Pukyong National University, Busan, Korea.
概括
本研究引入了风险差异 (RD) 作为医学研究的首选效果大小 (ES),提高了临床干预影响和患者益处的清晰度. 它倡导报告具有基线风险的RD,以实现透明,以患者为中心的决策.
科学领域:
- 医学统计 医学统计
- 临床研究方法论 临床研究方法论
- 基于证据的医学基于证据的医学.
背景情况:
- 零假设显著性测试 (NHST) 被补充了估计统计数据,如效果大小 (ESs) 和置信区间 (CI).
- 目前用于二元结果的方法可能无法完全传达临床意义或患者影响.
- 医疗研究中需要改进统计措施,以提高对患者护理的适用性.
研究的目的:
- 评估ESs和CI在医学研究中对二元结果的表达.
- 提出一个实用框架,用风险差异 (RD) 来评估临床意义.
- 在个别研究和元分析中,比较RD与其他指标 (RR,OR,Cohen's h) 的性能.
主要方法:
- 提出了一个实用性框架,强调受益者和影响水平.
- 根据事件大小 (EM) 引入了临床重要的最小风险差异 (MCIRD).
- 在个别研究中,RD与RR,OR和Cohen's h的统计力比较;在元分析中评估了视觉信息传递能力.
主要成果:
- 风险差异 (RD) 保持了与个人研究中的其他措施相比较的统计力.
- RDs提供了对临床干预影响的清晰度,而不会损害统计完整性.
- 使用RD的元分析提高了透明度,揭示了异质性,并解决了错误的假设.
结论:
- 采用RD作为首选的ES,报告基线风险 (BRs),促进了一个透明的,以患者为中心的研究精神.
- 这种方法量化临床有效性,促进研究应用到患者护理和共享决策.
- 建议对 RD 和 BR 进行标准化呈现,以准确地表示治疗效果.
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