Steineck Gunnar, Hunt Hayley, Adolfsson Jan
Division of Clinical Cancer Epidemiology, Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden.
Acta Oncol. 2006;45(4):421-9. doi: 10.1080/02841860600649293.
As epidemiological methods are used increasingly to evaluate the effects of cancer treatment, guidelines for the application of such methods in clinical research settings are necessary. Towards this end, we present a hierarchical step-model for causation of bias, which depicts a real-life study as departing from a perfect setting and proceeding step-wise towards a calculated, often adjusted, effect-parameter. Within this model, a specific error (which influences the effect-measure according to one of four sets of rules) is introduced on one (and only one) of the model's four steps. This hierarchical step-model for causation of bias identifies all sources of bias in a study, each of which depicts one or several errors which can be further categorized into one of the model's four steps. Acceptance of this model has implications for ascertaining the degree to which a study effectively evaluates the effects of cancer treatment (level of scientific evidence).
由于越来越多地使用流行病学方法来评估癌症治疗的效果，因此需要有关在临床研究环境中应用此类方法的指南。为此，我们提出了一个偏差因果关系的分层步骤模型，该模型将实际研究描述为从理想状态出发，并逐步朝着计算得出的、通常经过调整的效应参数发展。在这个模型中，在模型的四个步骤之一（且仅一个步骤）上引入了一个特定误差（根据四组规则之一影响效应测量）。这个偏差因果关系的分层步骤模型识别了研究中所有的偏差来源，每个偏差来源都描述了一个或几个误差，这些误差可以进一步归类到模型的四个步骤之一。接受这个模型对于确定一项研究有效评估癌症治疗效果的程度（科学证据水平）具有重要意义。
