Epidemiological data on cohorts of occupationally exposed uranium miners are currently used to assess health risks associated with chronic exposure to low doses of ionizing radiation. Nevertheless, exposure uncertainty is ubiquitous and questions the validity of statistical inference in these cohorts. This paper highlights the flexibility and relevance of the Bayesian hierarchical approach to account for both missing and left-censored (i.e. only known to be lower than a fixed detection limit) radiation doses that are prone to measurement error, when estimating radiation-related risks. Up to the authors’ knowledge, this is the first time these three sources of uncertainty are dealt with simultaneously in radiation epidemiology. To illustrate the issue, this paper focuses on the specific problem of accounting for these three sources of uncertainty when estimating the association between occupational exposure to low levels of γ-radiation and lung cancer mortality in the post-55 sub-cohort of French uranium miners. The impact of these three sources of dose uncertainty is of marginal importance when estimating the risk of death by lung cancer among French uranium miners. The corrected excess hazard ratio (EHR) is 0.81 per 100 mSv (95% credible interval: [0.28; 1.75]). Interestingly, even if the 95% credible interval of the corrected EHR is wider than the uncorrected one, a statistically significant positive association remains between γ-ray exposure and the risk of death by lung cancer, after accounting for dose uncertainty. Sensitivity analyses show that the results obtained are robust to different assumptions. Because of its flexible and modular nature, the Bayesian hierarchical models proposed in this work could be easily extended to account for high proportions of missing and left-censored dose values or exposure data, prone to more complex patterns of measurement error.

目前，使用职业暴露铀矿工人群的流行病学数据来评估与长期暴露于低剂量电离辐射有关的健康风险。然而，暴露不确定性无处不在，并质疑这些人群中统计推断的有效性。本文着重介绍了贝叶斯分层方法的灵活性和相关性，以便在估计与辐射相关的风险时考虑容易出现测量误差的放射剂量的缺失和左删减（即仅已知低于固定的检测极限）。据作者所知，这是放射流行病学中首次同时处理这三种不确定性来源。为了说明这个问题，在评估法国铀矿开采者的55个后子群中低γ射线水平的职业暴露与肺癌死亡率之间的相关性时，本文着重于解决这三个不确定性来源的具体问题。在估计法国铀矿开采者的肺癌死亡风险时，这三种剂量不确定性来源的影响至关重要。校正的额外危险比（EHR）为每100 mSv 0.81（95％可信区间：[0.28; 1.75]）。有趣的是，即使校正后的EHR的95％可信区间大于未校正的EHR，在考虑剂量不确定性之后，γ射线照射与肺癌死亡风险之间仍存在统计学上显着的正相关。敏感性分析表明，所获得的结果对于不同的假设是可靠的。由于其灵活和模块化的性质，可以轻松地扩展这项工作中提出的贝叶斯分层模型，以解决高比例的缺失和左删失剂量值或暴露数据，从而导致更复杂的测量误差模式。