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癌症流行病学:研究设计与数据分析。

Cancer epidemiology: study designs and data analysis.

作者信息

Malats N, Castaño-Vinyals G

机构信息

Centre de Recerca en Epidemiologia Ambiental, Institut Municipal d'Investigació Mèdica, Barcelona, Spain.

出版信息

Clin Transl Oncol. 2007 May;9(5):290-7. doi: 10.1007/s12094-007-0056-x.

Abstract

Among the scientific interests of cancer epidemiology is the identification of both environmental and genetic factors associated with cancer development. Observational designs requiring sophisticated methodology are applied to control for potential confounding factors. The enormous biotechnological potential developed in the last two decades has allowed the integration of a plethora of new biomarkers in epidemiological studies to better define the exposure and "neoclassic" outcomes, as well as incorporating genetic susceptibility factors in both classical and new epidemiological designs. The integration of scopes, objectives, data and tools coming from different disciplines also benefits epidemiology, thus evolving into "systems epidemiology". In this manuscript, we review the basic concepts of study designs and data analysis and introduce readers to the more innovative aspects that are now being applied in epidemiological studies.

摘要

癌症流行病学的科学研究兴趣之一是识别与癌症发生相关的环境和遗传因素。需要复杂方法的观察性设计被用于控制潜在的混杂因素。过去二十年中发展起来的巨大生物技术潜力使得在流行病学研究中整合大量新的生物标志物成为可能,以便更好地定义暴露和“新古典”结局,并将遗传易感性因素纳入经典和新的流行病学设计中。来自不同学科的范围、目标、数据和工具的整合也使流行病学受益,从而演变成“系统流行病学”。在本手稿中,我们回顾了研究设计和数据分析的基本概念,并向读者介绍目前在流行病学研究中应用的更具创新性的方面。

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