University of Bologna, Ravenna Campus, Ravenna, Italy.
Northern Ontario School of Medicine, Sudbury, Ontario, Canada.
Chem Biol Interact. 2019 Mar 1;301:128-140. doi: 10.1016/j.cbi.2018.11.014. Epub 2019 Feb 11.
Most cancers are multifactorial diseases. Yet, epidemiological modeling of the effect of ionizing radiation (IR) exposures based on the linear no-threshold model at low doses (LNT) has generally not included co-exposure to chemicals, dietary, socio-economic and other risk factors also known to cause the cancers imputed to IR. When so, increased cancer incidences are incorrectly predicted by being solely associated with IR exposures. Moreover, to justify application of the LNT to low doses, high dose-response data, e.g., from the bombing of Hiroshima and Nagasaki, are linearly interpolated to background incidence (which usually has large uncertainty). In order for this interpolation to be correct, it would imply that the biological mechanisms leading to cancer and those that prevent cancer at high doses are exactly the same as at low doses. We show that linear interpolations are incorrect because both the biological and epidemiological evidence for thresholds, or other non-linearities, are more than substantial. We discuss why the LNT model suffers from misspecification errors, multiple testing, and other biases. Moreover, its use by regulatory agencies conflates vague assertions of scientific causation, by conjecturing the LNT, for administrative ease of use.
大多数癌症是多因素疾病。然而,基于线性无阈值模型(LNT)在低剂量下对电离辐射(IR)暴露影响的流行病学建模通常没有包括已知也会导致归因于 IR 的癌症的化学物质、饮食、社会经济和其他风险因素的共同暴露。如果这样,仅与 IR 暴露相关联,就会错误地预测癌症发病率的增加。此外,为了证明 LNT 在低剂量下的应用是合理的,高剂量反应数据(例如,来自广岛和长崎的轰炸)被线性内插到背景发生率(通常具有很大的不确定性)。为了使这种内插正确,这意味着导致癌症的生物学机制和在高剂量下预防癌症的机制完全相同。我们表明,线性内插是不正确的,因为存在大量的生物学和流行病学证据表明存在阈值或其他非线性。我们讨论了为什么 LNT 模型会受到Specification 错误、多重检验和其他偏差的影响。此外,监管机构的使用将 LNT 模糊的科学因果关系的断言混为一谈,通过推测 LNT 来方便管理。