Affiliations of authors: Group Health Research Institute, Seattle, WA (JC, DMB, HSW); Department of Epidemiology (JC, NSW), Department of Pharmacy (DMB, HSW), and Department of Biostatistics (BM), University of Washington, Seattle, WA; Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, WA (NSW).
J Natl Cancer Inst. 2013 Oct 2;105(19):1456-62. doi: 10.1093/jnci/djt211. Epub 2013 Aug 12.
Studies of the effects of exposures after cancer diagnosis on cancer recurrence and survival can provide important information to the growing group of cancer survivors. Observational studies that address this issue generally fall into one of two categories: 1) those using health plan automated data that contain "continuous" information on exposures, such as studies that use pharmacy records; and 2) survey or interview studies that collect information directly from patients once or periodically postdiagnosis. Reverse causation, confounding, selection bias, and information bias are common in observational studies of cancer outcomes in relation to exposures after cancer diagnosis. We describe these biases, focusing on sources of bias specific to these types of studies, and we discuss approaches for reducing them. Attention to known challenges in epidemiologic research is critical for the validity of studies of postdiagnosis exposures and cancer outcomes.
对癌症诊断后暴露对癌症复发和生存影响的研究可以为越来越多的癌症幸存者提供重要信息。解决这个问题的观察性研究通常分为两类:1)使用包含暴露“连续”信息的健康计划自动数据的研究,例如使用药房记录的研究;2)在癌症诊断后一次性或定期从患者那里直接收集信息的调查或访谈研究。在观察性研究中,与癌症诊断后暴露相关的癌症结果通常存在反向因果关系、混杂、选择偏倚和信息偏倚。我们描述了这些偏倚,重点介绍了这些类型研究中特定的偏倚来源,并讨论了减少这些偏倚的方法。在诊断后暴露和癌症结果的研究中,关注流行病学研究中的已知挑战对于研究的有效性至关重要。