A Meta-Regression Method for Studying Etiological Heterogeneity Across Disease Subtypes Classified by Multiple Biomarkers
A Meta-Regression Method for Studying Etiological Heterogeneity Across Disease Subtypes Classified by Multiple Biomarkers
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DOI：
10.1093/aje/kwv040
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发表时间：
2015-08-01
影响因子：
5
通讯作者：
Ogino, Shuji
中科院分区：
文献类型：
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作者：
Wang, Molin;Kuchiba, Aya;Ogino, Shuji
在跨学科的生物医学、流行病学和人口研究中，越来越有必要考虑任何给定的健康状况和结果的发病机制和内在异质性。正如独特的疾病原理所暗示的那样，没有一个单一的生物标志物可以完美地定义疾病亚型。分子病理学和生物学的复杂性要求生物统计学方法同时分析多个生物标志物和亚型。为了分析和检验由多个分类和/或序号标记定义的亚型的异质性假设，我们开发了一种元回归方法，该方法可以利用现有的统计软件进行混合模型分析。该方法可用于评估在控制其他标记的同时，由一个标记定义的子类型之间的暴露-亚型关联是否不同，以及评估由一个标记定义的子类型之间的暴露-亚型关联的差异是否取决于任何其他标记。为了说明这一方法在分子病理流行病学研究中的应用，我们在《护士健康研究》(1980-2010)和《卫生专业人员随访研究》(1986-2010)中研究了吸烟状况与结直肠癌亚型之间的关系，这些亚型由3个相关的肿瘤分子特征(CpG岛甲基化表型、微卫星不稳定性和B-Raf原癌基因、丝氨酸/苏氨酸激酶(BRAF)突变)确定。随着分子诊断和基因组技术在临床医学和公共卫生中成为常规，这种方法可以广泛使用。
In interdisciplinary biomedical, epidemiologic, and population research, it is increasingly necessary to consider pathogenesis and inherent heterogeneity of any given health condition and outcome. As the unique disease principle implies, no single biomarker can perfectly define disease subtypes. The complex nature of molecular pathology and biology necessitates biostatistical methodologies to simultaneously analyze multiple biomarkers and subtypes. To analyze and test for heterogeneity hypotheses across subtypes defined by multiple categorical and/or ordinal markers, we developed a meta-regression method that can utilize existing statistical software for mixed-model analysis. This method can be used to assess whether the exposure-subtype associations are different across subtypes defined by 1 marker while controlling for other markers and to evaluate whether the difference in exposure-subtype association across subtypes defined by 1 marker depends on any other markers. To illustrate this method in molecular pathological epidemiology research, we examined the associations between smoking status and colorectal cancer subtypes defined by 3 correlated tumor molecular characteristics (CpG island methylator phenotype, microsatellite instability, and the B-Raf protooncogene, serine/threonine kinase (BRAF), mutation) in the Nurses' Health Study (1980-2010) and the Health Professionals Follow-up Study (1986-2010). This method can be widely useful as molecular diagnostics and genomic technologies become routine in clinical medicine and public health.