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Causality in cancer research: a journey through models in molecular epidemiology and their philosophical interpretation

机译:癌症研究中的因果关系:分子流行病学模型及其哲学解释的历程

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摘要

In the last decades, Systems Biology (including cancer research) has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a) causality in epidemiology and in philosophical theorizing—notably, the “sufficient-component-cause framework” and the “mark transmission” approach; (b) new acquisitions about disease pathogenesis, e.g. the “branched model” in cancer, and the role of biomarkers in this process; (c) the burgeoning of omics research, with a large number of “signals” and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of “cancer causes”. We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called “evidential pluralism”. According to this view, causal reasoning is based on both “evidence of difference-making” (e.g. associations) and on “evidence of underlying biological mechanisms”. We conceptualize the way scientists detect and trace signals in terms of information transmission, which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social—are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level. Electronic supplementary materialThe online version of this article (doi:10.1186/s12982-017-0061-7) contains supplementary material, which is available to authorized users.
机译:在过去的几十年中,系统生物学(包括癌症研究)受到技术,统计模型和生物信息学的推动。在本文中,我们试图将生物学和哲学思想带回来。因此,我们的目标是使不同的思想传统兼容:(a)流行病学和哲学理论上的因果关系,特别是“充分成分原因框架”和“标记传播”方法; (b)有关疾病发病机理的新知识,例如癌症中的“分支模型”,以及生物标志物在这一过程中的作用; (c)组学研究迅速发展,具有大量“信号”和需要解释的关联。在本文中,我们首先总结了有关致癌作用的当前观点,然后探讨了当前有关“癌因”的哲学解释的相关性。我们尝试提供一个统一的框架,将生物标志物和omic数据合并到因果模型中,这称为“证据多元论”。根据这种观点,因果推理既基于“产生差异的证据”(例如,关联),又基于“潜在生物学机制的证据”。我们从信息传输的角度对科学家检测和跟踪信号的方式进行了概念化,这是哲学家韦斯利·萨尔蒙(Wesley Salmon)提出的商标传输理论的概括。我们的方法能够帮助我们将微观和宏观生物学以及心理社会等异类因素之间的因果联系概念化。这不仅对于理解癌症病因很重要,对于设计针对宏观层面正确因果关系的公共卫生政策也很重要。电子补充材料本文的在线版本(doi:10.1186 / s12982-017-0061-7)包含补充材料,授权用户可以使用。

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