Richard Bull

Uncertainties on Lung Doses from Inhaled Plutonium

In a recent epidemiological study, Bayesian uncertainties on lung doses have been calculated to determine lung cancer risk from occupational exposures to plutonium. These calculations used a revised version of the Human Respiratory Tract Model (HRTM) published by the ICRP. In addition to the Bayesian analyses, which give probability distributions of doses, point estimates of doses (single estimates without uncertainty) were also provided for that study using the existing HRTM as it is described in ICRP Publication 66; these are to be used in a preliminary analysis of risk. To infer the differences between the point estimates and Bayesian uncertainty analyses, this paper applies the methodology to former workers of the United Kingdom Atomic Energy Authority (UKAEA), who constituted a subset of the study cohort. The resulting probability distributions of lung doses are compared with the point estimates obtained for each worker. It is shown that mean posterior lung doses are around two- to fourfold higher than point estimates and that uncertainties on doses vary over a wide range, greater than two orders of magnitude for some lung tissues. In addition, we demonstrate that uncertainties on the parameter values, rather than the model structure, are largely responsible for these effects. Of these it appears to be the parameters describing absorption from the lungs to blood that have the greatest impact on estimates of lung doses from urine bioassay. Therefore, accurate determination of the chemical form of inhaled plutonium and the absorption parameter values for these materials is important for obtaining reliable estimates of lung doses and hence risk from occupational exposures to plutonium.

A Bayesian analysis of uncertainties on lung doses resulting from occupational exposures to uranium

In a recent epidemiological study, Bayesian estimates of lung doses were calculated in order to determine a possible association between lung dose and lung cancer incidence resulting from occupational exposures to uranium. These calculations, which produce probability distributions of doses, used the human respiratory tract model (HRTM) published by the International Commission on Radiological Protection (ICRP) with a revised particle transport clearance model. In addition to the Bayesian analyses, point estimates (PEs) of doses were also provided for that study using the existing HRTM as it is described in ICRP Publication 66. The PEs are to be used in a preliminary analysis of risk. To explain the differences between the PEs and Bayesian analysis, in this paper the methodology was applied to former UK nuclear workers who constituted a subset of the study cohort. The resulting probability distributions of lung doses calculated using the Bayesian methodology were compared with the PEs obtained for each worker. Mean posterior lung doses were on average 8-fold higher than PEs and the uncertainties on doses varied over a wide range, being greater than two orders of magnitude for some lung tissues. It is shown that it is the prior distributions of the parameters describing absorption from the lungs to blood that are responsible for the large difference between posterior mean doses and PEs. Furthermore, it is the large prior uncertainties on these parameters that are mainly responsible for the large uncertainties on lung doses. It is concluded that accurate determination of the chemical form of inhaled uranium, as well as the absorption parameter values for these materials, is important for obtaining unbiased estimates of lung doses from occupational exposures to uranium for epidemiological studies. Finally, it should be noted that the inferences regarding the PEs described here apply only to the assessments of cases provided for the epidemiological study, where central estimates of dose were sought. Approved dosimetry service assessments of exposures are unlikely to yield significant underestimates, as pessimistic assumptions of lung solubility would almost always be used.

Concerted Uranium Research in Europe (CURE): toward a collaborative project integrating dosimetry, epidemiology and radiobiology to study the effects of occupational uranium exposure.

The potential health impacts of chronic exposures to uranium, as they occur in occupational settings, are not well characterized. Most epidemiological studies have been limited by small sample sizes, and a lack of harmonization of methods used to quantify radiation doses resulting from uranium exposure. Experimental studies have shown that uranium has biological effects, but their implications for human health are not clear. New studies that would combine the strengths of large, well-designed epidemiological datasets with those of state-of-the-art biological methods would help improve the characterization of the biological and health effects of occupational uranium exposure. The aim of the European Commission concerted action CURE (Concerted Uranium Research in Europe) was to develop protocols for such a future collaborative research project, in which dosimetry, epidemiology and biology would be integrated to better characterize the effects of occupational uranium exposure. These protocols were developed from existing European cohorts of workers exposed to uranium together with expertise in epidemiology, biology and dosimetry of CURE partner institutions. The preparatory work of CURE should allow a large scale collaborative project to be launched, in order to better characterize the effects of uranium exposure and more generally of alpha particles and low doses of ionizing radiation.

A method for calculating Bayesian uncertainties on internal doses resulting from complex occupational exposures.

Estimating uncertainties on doses from bioassay data is of interest in epidemiology studies that estimate cancer risk from occupational exposures to radionuclides. Bayesian methods provide a logical framework to calculate these uncertainties. However, occupational exposures often consist of many intakes, and this can make the Bayesian calculation computationally intractable. This paper describes a novel strategy for increasing the computational speed of the calculation by simplifying the intake pattern to a single composite intake, termed as complex intake regime (CIR). In order to assess whether this approximation is accurate and fast enough for practical purposes, the method is implemented by the Weighted Likelihood Monte Carlo Sampling (WeLMoS) method and evaluated by comparing its performance with a Markov Chain Monte Carlo (MCMC) method. The MCMC method gives the full solution (all intakes are independent), but is very computationally intensive to apply routinely. Posterior distributions of model parameter values, intakes and doses are calculated for a representative sample of plutonium workers from the United Kingdom Atomic Energy cohort using the WeLMoS method with the CIR and the MCMC method. The distributions are in good agreement: posterior means and Q(0.025) and Q(0.975) quantiles are typically within 20 %. Furthermore, the WeLMoS method using the CIR converges quickly: a typical case history takes around 10-20 min on a fast workstation, whereas the MCMC method took around 12-72 hr. The advantages and disadvantages of the method are discussed.

Risk of Lung Cancer Mortality in Nuclear Workers from Internal Exposure to Alpha Particle-emitting Radionuclides

Background: Carcinogenic risks of internal exposures to alpha-emitters (except radon) are poorly understood. Since exposure to alpha particles—particularly through inhalation—occurs in a range of settings, understanding consequent risks is a public health priority. We aimed to quantify dose–response relationships between lung dose from alpha-emitters and lung cancer in nuclear workers. Methods: We conducted a case–control study, nested within Belgian, French, and UK cohorts of uranium and plutonium workers. Cases were workers who died from lung cancer; one to three controls were matched to each. Lung doses from alpha-emitters were assessed using bioassay data. We estimated excess odds ratio (OR) of lung cancer per gray (Gy) of lung dose. Results: The study comprised 553 cases and 1,333 controls. Median positive total alpha lung dose was 2.42 mGy (mean: 8.13 mGy; maximum: 316 mGy); for plutonium the median was 1.27 mGy and for uranium 2.17 mGy. Excess OR/Gy (90% confidence interval)—adjusted for external radiation, socioeconomic status, and smoking—was 11 (2.6, 24) for total alpha dose, 50 (17, 106) for plutonium, and 5.3 (−1.9, 18) for uranium. Conclusions: We found strong evidence for associations between low doses from alpha-emitters and lung cancer risk. The excess OR/Gy was greater for plutonium than uranium, though confidence intervals overlap. Risk estimates were similar to those estimated previously in plutonium workers, and in uranium miners exposed to radon and its progeny. Expressed as risk/equivalent dose in sieverts (Sv), our estimates are somewhat larger than but consistent with those for atomic bomb survivors. See video abstract at, http://links.lww.com/EDE/B232.

An intake prior for the Bayesian analysis of plutonium and uranium exposures in an epidemiology study.

In Bayesian inference, the initial knowledge regarding the value of a parameter, before additional data are considered, is represented as a prior probability distribution. This paper describes the derivation of a prior distribution of intake that was used for the Bayesian analysis of plutonium and uranium worker doses in a recent epidemiology study. The chosen distribution is log-normal with a geometric standard deviation of 6 and a median value that is derived for each worker based on the duration of the work history and the number of reported acute intakes. The median value is a function of the work history and a constant related to activity in air concentration, M, which is derived separately for uranium and plutonium. The value of M is based primarily on measurements of plutonium and uranium in air derived from historical personal air sampler (PAS) data. However, there is significant uncertainty on the value of M that results from paucity of PAS data and from extrapolating these measurements to actual intakes. This paper compares posterior and prior distributions of intake and investigates the sensitivity of the Bayesian analyses to the assumed value of M. It is found that varying M by a factor of 10 results in a much smaller factor of 2 variation in mean intake and lung dose for both plutonium and uranium. It is concluded that if a log-normal distribution is considered to adequately represent worker intakes, then the Bayesian posterior distribution of dose is relatively insensitive to the value assumed of M.

Reconstruction of Internal Doses for the Alpha-Risk Case-Control Study of Lung Cancer and Leukaemia Among European Nuclear Workers.

The Alpha-Risk study required the reconstruction of doses to lung and red bone marrow for lung cancer and leukaemia cases and their matched controls from cohorts of nuclear workers in the UK, France and Belgium. The dosimetrists and epidemiologists agreed requirements regarding the bioassay data, biokinetic and dosimetric models and dose assessment software to be used and doses to be reported. The best values to use for uncertainties on the monitoring data, setting of exposure regimes and characteristics of the exposure material, including lung solubility, were the responsibility of the dosimetrist responsible for each cohort. Among 1721 subjects, the median absorbed dose to the lung from alpha radiations was 2.1 mGy, with a maximum dose of 316 mGy. The lung doses calculated reflect the higher levels of exposure seen among workers in the early years of the nuclear industry compared to today.

Ratio of nose blow results to intakes during the decommissioning of a facility at Dounreay.

During the decommissioning of a large glove box facility at Dounreay, in addition to engineering and administration controls, workers wore pressurised suits to minimise their intake of radionuclides. The workers provided nose blows after each suited operation to provide an indication of the effectiveness of protective measures. The nose blows were also used as indicators of radiological significant intakes. This paper examines the distribution of ratios of nose blow to assessed intake. A geometric mean and variance of the ratio of nose blows to intakes have been derived. The nose blows were provided over a period of 2 y and the alpha-emitting nuclides present are 239Pu, 241Am and 238Pu. Twenty-two nose blow results each with follow-up urine and faecal results are included in the study. The effectiveness of nose blows as an indicator of radiological conditions and as a trigger for the investigation of significant doses is considered. The ratio between assessed intake and nose blow result was shown to be very large.

Distribution of uranium in Dounreay workers due to uptake from the environment

At Dounreay, there are a number of facilities in which the main radiological hazard is the intake of uranium. The hazard is managed through the implementation of controls and contamination surveys in order to reduce the risk of intake. In order to provide reassurance that radiological significant intakes are not taking place, a routine urine sample programme is in place. As well as being exposed to work place sources of uranium workers are also exposed to the intake of uranium from foodstuffs and water, which are not associated with their work at Dounreay. In order to characterise the intake of the radionuclides from the environment, urine samples were collected from a group of Dounreay personnel who are not exposed to uranium in their workplace. The distribution of the uranium isotopes 234U, 235U and 238U has been assessed for these workers. The distributions will be used to assess the likelihood of uranium detected in urine for a uranium worker being due to an intake in the workplace. The best match to distributions of 234U and 238U was found to be a combination of normal and lognormal distributions.

An intake of C14-labelled dichlorobenzene.

An intake of C14 in the form of dichlorobenzene was followed up with 90 spot urine samples over a period of almost 2 weeks. This dataset has been fitted by a model consisting of three exponential terms. The intake and effective dose have been calculated. This case has been used to examine the effects of recent proposals by ICRP concerning the calculation of effective dose and the use of non-standard biokinetic models.