调整调整:使用外部数据来估计不同混器集对公布协会的影响
Thomas P Ahern1, Lindsay J Collin2, Richard F MacLehose3
1From the Department of Surgery, Larner College of Medicine at the University of Vermont, Burlington, VT.
Epidemiology (Cambridge, Mass.)
|November 22, 2024
概括
调整超重和老年人死亡率的元分析中的混因素可以提高研究的严谨性. 这种新的方法提高了可靠性,并促进了研究结果的共识.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 老年学是一门学科.
背景情况:
- 以前的元分析表明,超重体重体重指数 (BMI) 与65岁及以上人群全因死亡率之间存在保护性关联.
- 对于有助于这些发现的研究中显著的异质性和不足的混因素调整提出了担忧.
- 建议采用一种新的方法来对单个研究进行外部调整,以便在进行元分析之前解决这些局限性.
研究的目的:
- 展示一种新的方法,用于对包含在元分析中的单个研究进行外部调整.
- 为了提高元分析估计值的可靠性,对足够多的混因子进行均调整.
- 用调整的数据重新评估老年人超重和死亡率之间的关联.
主要方法:
- 从2013年的元分析中抽象了33个年龄≥65年级的协会的总结数据.
- 使用外部数据集 (NHANES III) 来推导调整每个研究的多变量模型的共变量.
- 计算了偏差因子以量化调整效应,并比较了随机效应的元分析,并没有调整.
主要成果:
- 最初的元分析重现了超重和老年人死亡率之间的保护性关联 (总结RR = 0.88;95%CI:0.84,0.92).
- 对年龄,性别和吸烟状况进行模拟均调整,导致类似的总结关联 (总结RR=0.90;95%CI:0.86,0.94).
- 与原始 (I2 = 38.4%) 相比,调整后的元分析表明异质性减少 (I2 = 34.6%).
结论:
- 对于足够的混器集的模拟均调整可以提高元分析的严谨性.
- 这种方法方法有可能在研究结果上促进更大的共识.
- 这些发现支持外部调整的有用性,以提高元分析证据的可靠性.
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