Department of Hygiene, Epidemiology and Medical Statistics, University of Athens, Medical School, Athens, Greece.
Environ Health. 2011 Apr 11;10:30. doi: 10.1186/1476-069X-10-30.
Risk assessment requires dose-response data for the evaluation of the relationship between exposure to an environmental stressor and the probability of developing an adverse health effect. Information from human studies is usually limited and additional results from animal studies are often needed for the assessment of risks in humans. Combination of risk estimates requires an assessment and correction of the important biases in the two types of studies. In this paper we aim to illustrate a quantitative approach to combining data from human and animal studies after adjusting for bias in human studies. For our purpose we use the example of the association between exposure to diesel exhaust and occurrence of lung cancer.
Firstly, we identify and adjust for the main sources of systematic error in selected human studies of the association between occupational exposure to diesel exhaust and occurrence of lung cancer. Evidence from selected animal studies is also accounted for by extrapolating to average ambient, occupational exposure concentrations of diesel exhaust. In a second stage, the bias adjusted effect estimates are combined in a common effect measure through meta-analysis.
The random-effects pooled estimate (RR) for exposure to diesel exhaust vs. non-exposure was found 1.37 (95% C.I.: 1.08-1.65) in animal studies and 1.59 (95% C.I.: 1.09-2.10) in human studies, whilst the overall was found equal to 1.49 (95% C.I.: 1.21-1.78) with a greater contribution from human studies. Without bias adjustment in human studies, the pooled effect estimate was 1.59 (95% C.I.: 1.28-1.89).
Adjustment for the main sources of uncertainty produced lower risk estimates showing that ignoring bias leads to risk estimates potentially biased upwards.
风险评估需要剂量-反应数据，以评估暴露于环境应激源与发生不良健康效应的概率之间的关系。人类研究的信息通常有限，并且通常需要动物研究的额外结果来评估人类的风险。风险估计的组合需要评估和纠正这两种类型研究中的重要偏差。在本文中，我们旨在说明一种定量方法，即在调整人类研究中的偏差后，将来自人类和动物研究的数据进行组合。我们使用暴露于柴油废气与肺癌发生之间的关联为例。
首先，我们确定并调整了选定的人类研究中与职业性暴露于柴油废气与肺癌发生之间关联的主要系统误差源。还通过外推至平均环境、职业性暴露于柴油废气的浓度来考虑选定的动物研究中的证据。在第二阶段，通过荟萃分析将偏差调整后的效应估计值组合到共同的效应量中。
在动物研究中，暴露于柴油废气与非暴露的随机效应汇总估计值（RR）为 1.37（95%置信区间：1.08-1.65），在人类研究中为 1.59（95%置信区间：1.09-2.10），而总体为 1.49（95%置信区间：1.21-1.78），人类研究的贡献更大。在没有调整人类研究中的偏差的情况下，汇总效应估计值为 1.59（95%置信区间：1.28-1.89）。
对主要不确定性来源进行调整可降低风险估计值，表明忽略偏差会导致潜在向上偏差的风险估计值。
