Semiparametric estimation for joint modeling of colorectal cancer risk and functional biomarkers measured with errors.
Semiparametric estimation for joint modeling of colorectal cancer risk and functional biomarkers measured with errors.
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DOI：
10.1002/bimj.201000070
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发表时间：
2011-05
影响因子：
1.7
通讯作者：
Bostick, Roberd M.
中科院分区：
文献类型：
--
作者：
Long, Qi;Zhang, Xiaoxi;Bostick, Roberd M.
关键词：
这项研究的动机是一个试点结直肠腺瘤研究，其中感兴趣的结果是结直肠腺瘤的存在，代表结直肠癌的风险，和感兴趣的预测因子是蛋白质生物标志物，重复测量误差沿着长度的显微结构在人类结肠，结肠隐窝。这种类型的生物标志物被称为功能性生物标志物。研究人员感兴趣的是确定与结直肠癌风险相关的功能性生物标志物的特征。在本文中，我们研究了一种联合建模方法，其中使用逻辑回归模型以未观察到的真实功能生物标志物作为预测因子对二元临床结果进行建模。大多数现有的方法都是针对线性模型或功能性生物标志物而开发的，没有错误，不能直接应用于我们的数据。适用的方法包括两步法和最大似然法，这都有一定的局限性。我们提出了一个强大的半参数方法，以克服现有方法的局限性。我们研究了所提出的方法的属性，并在模拟中显示，它与其他方法相比毫不逊色，也提供了显着的节省CPU时间。我们分析了飞行员结直肠腺瘤的数据，并表明APC，一种肿瘤抑制基因的表达水平，在过渡区从增殖区到分化区的结肠隐窝可能与结直肠癌的风险。鉴于试点研究的样本量相对较小，我们的结果需要在未来的全面研究中得到验证。
This research is motivated by a pilot colorectal adenoma study, where the outcome of interest is the presence of colorectal adenoma representing risk for colorectal cancer, and the predictors of interest are protein biomarkers that are repeatedly measured with errors along the length of a microscopic structure in the human colon, the colon crypt. Biomarkers of this type are referred to as functional biomarkers. The investigators are interested in identifying features of functional biomarkers that are associated with risk for colorectal cancer. In this paper, we investigate a joint modeling approach, where the binary clinical outcome is modeled using a logistic regression model with the unobserved true functional biomarkers as predictors. Most existing methods are developed either for linear models or for functional biomarkers measured without errors and cannot be directly applied to our data. The applicable methods include a two-step method and a maximum likelihood method, which have some limitations. We propose a robust semiparametric method to overcome the limitations of the existing methods. We study the properties of the proposed method, and show in simulations that it compares favorably with other methods and also offers significant savings in CPU time. We analyze the pilot colorectal adenoma data and show that expression levels of APC, a tumor suppressor gene, in the transitional area from the proliferation zone to the differentiation zone of colon crypts are likely associated with risk for colorectal cancer. Given the relatively small sample size in the pilot study, our results need to be validated in future full-scale studies.
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