Selecting controls for assessing interaction in nested case-control studies

Selecting controls for assessing interaction in nested case-control studies
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DOI:
10.2188/jea.13.193
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发表时间:
2003-07-01
影响因子:
4.7
通讯作者:
Langholz, B
Langholz, B
中科院分区:
医学3区
文献类型:
--
作者:
Cologne, J;Langholz, B

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背景:当感兴趣的是在全队列中测量的风险因素X和仅在病例对照样本中测量的另一个风险因素Z之间的相互作用时,比较了在嵌套病例对照研究中选择对照的两种方法--X匹配和X计数器匹配。这一点很重要,因为当X不常见且交互作用为正(大于乘法)时,匹配相对于随机抽样提供效率增益,而计数器匹配通常比随机抽样更有效。方法:将匹配和计数器匹配彼此比较,并与对照的随机抽样进行二分X和Z比较,以日本原子弹幸存者中的辐射和其他危险因素研究为例,通过对指定X和Z的患病率以及它们之间的相关性和相互作用的水平的广泛参数的渐近相对效率计算,进行模拟。重点是利用一般模型对X和Z的联合风险进行分析。结果:在罕见的风险因素X和不相关的风险因素Z的情况下,反匹配在推断交互作用的效率方面优于匹配或随机抽样。此外,更一般的效率计算表明,相对于匹配病例对照设计,反匹配设计在研究交互作用时通常是有效的。结论:由于反匹配设计可以使用标准的统计方法进行分析,并允许调查X的影响的混淆,而匹配设计在拟合一般风险模型时需要非标准方法,不允许调查X的调整后的风险,结论:在嵌套式病例对照交互作用研究中,当X在病例对照抽样时已知时,X上的反匹配可能是比X上匹配更好的选择。
Background: Two methods for selecting controls in nested case-control studies - matching on X and counter matching on X - are compared when interest is in interaction between a risk factor X measured in the full cohort and another risk factor Z measured only in the case-control sample. This is important because matching provides efficiency gains relative to random sampling when X is uncommon and the interaction is positive (greater than multiplicative), whereas counter matching is generally efficient compared to random sampling.Methods: Matching and counter matching were compared to each other and to random sampling of controls for dichotomous X and Z Comparison was by simulation, using as an example a published study of radiation and other risk factors for breast cancer in the Japanese atomic-bomb survivors, and by asymptotic relative efficiency calculations for a wide range of parameters specifying the prevalence of X and Z as well as the levels of correlation and interaction between them. Focus was on analyses utilizing general models for the joint risk of X and ZResults: Counter-matching performed better than matching or random sampling in terms of efficiency for inference about interaction in the case of a rare risk factor X and uncorrelated risk factor Z Further, more general, efficiency calculations demonstrated that counter-matching is generally efficient relative to matched case-control designs for studying interaction.Conclusions: Because counter-matched designs may be analyzed using standard statistical methods and allow investigation of confounding of the effect of X, whereas matched designs require a non-standard approach when fitting general risk models and do not allow investigating the adjusted risk of X, it is concluded that counter-matching on X can be a superior alternative to matching on X in nested case-control studies of interaction when X is known at the time of case-control sampling.