Neutra R, Swan S, Mack T
California Department of Health Services, Emeryville 94608.
Sci Total Environ. 1992 Dec 15;127(1-2):187-200. doi: 10.1016/0048-9697(92)90477-a.
The posterior probability of a causal explanation given that an environmental cancer cluster is statistically significant depends on the prior probability of an environmentally caused cluster, the sensitivity of the statistical test and its specificity. The prior probability is low, because it is rare to have enough carcinogen in the general environment to cause a relative risk of cancer high enough to achieve statistical significance in a small geographic area. The sensitivity and specificity are not great. The likelihood that a census tract escapes statistically significant elevations in all 80 types of cancer can be calculated. Many of the thousands of census tracts will, by chance alone, have at least one type of cancer whose elevation is statistically significant. Actual observation from a large cancer registry confirms this probabilistic prediction. Applying the principles of Bayes' Theorem would suggest that most statistically significant environmental cancer clusters are not due to environmental carcinogens. One would have to investigate hundreds of environmental cancer clusters to find one with a true environmental cause.
假定一个环境癌症聚集区在统计学上具有显著性，那么因果解释的后验概率取决于环境导致的聚集区的先验概率、统计检验的敏感性及其特异性。先验概率很低，因为在一般环境中很少有足够的致癌物能导致癌症的相对风险高到在一个小地理区域内达到统计学显著性。敏感性和特异性也不高。可以计算出一个普查区在所有80种癌症类型中都没有出现统计学显著性升高的可能性。仅出于偶然，成千上万的普查区中就会有许多至少有一种癌症类型的升高具有统计学显著性。来自大型癌症登记处的实际观察证实了这一概率预测。应用贝叶斯定理的原理表明，大多数在统计学上具有显著性的环境癌症聚集区并非由环境致癌物导致。必须调查数百个环境癌症聚集区才能找到一个真正由环境因素导致的聚集区。
