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在元分析中测量尺度之间的映射,适用于儿童体质指数的测量
Annabel L Davies1, A E Ades1, Julian P T Higgins1
1Bristol Medical School, University of Bristol, Bristol, UK.
Research synthesis methods
|October 2, 2024
概括
研究人员开发了三种方法,将医学试验的连续结果映射到单一尺度上,解决了儿童肥胖预防等干预措施的定量证据综合方面的挑战.
科学领域:
- 生物统计学 生物统计学
- 医疗信息学 医疗信息学
- 量化研究方法 量化研究方法
背景情况:
- 定量证据综合结合了来自多项医学试验的数据,以推断干预效应.
- 当试验在不同的测量尺度上报告连续结果时,出现了一个重大挑战,这阻碍了连贯的分析.
- 将结果映射到单一的尺度上至关重要,特别是在处理汇总数据时,正如使用身体质量指数 (BMI) 对儿童肥胖干预措施的元分析所示.
研究的目的:
- 开发和评估用于将医学试验的总结结果数据映射到单个测量尺度上的方法.
- 为应对结合来自不同尺度上报告连续结果的试验证据的挑战,特别是汇总的BMI数据.
- 为了比较不同的绘图方法的准确性和适用性,用于定量证据合成.
主要方法:
- 开发了三种用于在不同测量尺度之间映射总数据的新方法:使用z分数/百分位数的分析方法和基于采样的两种方法 (直接采样和优化).
- 设计方法是利用已知或估计的测量尺度之间的个人级别关系.
- 使用模拟研究和真实世界试验数据报告结果的评估方法在多个尺度上.
主要成果:
- 三种开发的方法都在重建平均值方面表现出合理的准确性.
- 基于优化的采样方法在准确估计标准偏差方面表现出优异的性能,与分析和直接采样方法相比.
- 优化方法虽然准确,但表现出低估标准偏差的倾向,容易出现收问题.
结论:
- 开发的映射方法提供了可行的解决方案,用于将不同测量尺度的试验的连续聚合数据集成到定量证据合成中.
- 优化方法为标准偏差估计提供了高精度,但由于潜在的低估和趋同问题,需要仔细实施.
- 这些方法提高了执行连贯元分析的能力,特别是针对儿童肥胖的干预措施,使用总体BMI数据.
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