Risk Projection Models Research Articles

Improving astronaut cancer risk assessment from space radiation with an ensemble model framework

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty as well as model-form uncertainty associated with differing theoretical or empirical formalisms. Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future models, improve uncertainty quantification, and reduce the impact of subjective bias. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met for future space exploration missions, such as human missions to Mars. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets. Closer agreement is seen at the median ± one sigma due to the inherent similarities in available models. Identification of potential new models, epidemiological data, and methods for statistical correlation between predictive ensemble members are discussed. Alternate ways of communicating risk and acceptable uncertainty with respect to NASA's current permissible exposure limits are explored.

Determination of Chromosome Aberrations in Human Fibroblasts Irradiated by Mixed Fields Generated with Shielding.

To better study biological effects of space radiation using ground-based facilities, the NASA Space Radiation Laboratory (NSRL) at the Brookhaven National Laboratory has been upgraded to rapidly switch ions and energies. This has allowed investigators to design irradiation protocols comprising a mixture of ions and energies more indicative of the galactic cosmic ray (GCR) environment. Despite these advancements, beam selection and delivery schemes should be optimized against facility and experimental constraints and validated to ensure such irradiations are a suitable representation of the space environment. Importantly, since experiments are time consuming and expensive, models capable of predicting biological outcomes over a range of irradiation conditions (single ion, sequential multi ion or mixed fields) are needed to support such efforts. In this work, human fibroblasts were placed behind 20 g/cm2 aluminum and 10.345 g/cm2 polyethylene and irradiated separately by 344 MeV hydrogen, 344 MeV/n helium, 450 MeV/n oxygen and 950 MeV/n iron ions at various doses. The fluorescence in situ hybridization (FISH) whole chromosome painting technique was then used to assess the cells for chromosome aberrations (CAs), notably simple exchanges. A multi-scale modeling approach was also developed to predict the formation of chromosome aberrations in these experiments. The Geant4 simulation toolkit was used to determine the spectra of particles and energies produced by interactions between the incident beams and shielding. The simulated mixed field generated by shielding was then transferred into the track structure code, RITRACKS (relativistic ion tracks), to generate three-dimensional (3D) voxelized dose maps at the nanometer scale. Finally, these voxel dose maps were input into the new damage and repair model, RITCARD (radiation-induced tracks, chromosome aberrations, repair and damage), to predict the formation of various CAs. The multi-scale model described herein is a significant advancement for the computational tools used to predict biological outcomes in cells exposed to highly complex, mixed ion fields related to the GCR environment. Results show that the simulation and experimental data are in good agreement for the complex radiation fields generated by all ions incident on shielding for most data points. The differences between model predictions and measurements are discussed. Although improvements are needed, the model extends current capabilities for evaluating beam selection and delivery schemes at the NSRL ground-based GCR simulator and for informing NASA risk projection models in the future.

Application of the 2017 KDIGO Guideline for the Evaluation and Care of Living Kidney Donors to Clinical Practice.

The Kidney Disease: Improving Global Outcomes (KDIGO) 2017 "Clinical Practice Guideline on the Evaluation and Care of Living Kidney Donors" was developed to assist medical professionals who evaluate living kidney donor candidates and provide care before, during, and after donation. This guideline Work Group concluded that a comprehensive approach to donor candidate risk assessment should replace eligibility decisions on the basis of assessments of single risk factors in isolation. To address all issues important to living donors in a pragmatic and comprehensive guideline, many of the guideline recommendations were on the basis of expert consensus opinion even when no direct evidence was available. To advance available evidence, original data analyses were also undertaken to produce a "proof-of-concept" risk projection model for kidney failure. This was done to illustrate how the community can advance a new quantitative framework of risk that considers each candidate's profile of demographic and health characteristics. A public review by stakeholders and subject matter experts as well as industry and professional organizations informed the final formulation of the guideline. This review highlights the guideline framework, key concepts, and recommendations, and uses five patient scenarios and 12 guideline statements to illustrate how the guideline can be applied to support living donor evaluation and care in clinical practice.

Estimating cancer risk from 99mTc pyrophosphate imaging for transthyretin cardiac amyloidosis

BackgroundIncreasing recognition that transthyretin cardiac amyloidosis (ATTR-CA) is much more common than previously appreciated and the emergence of novel disease-modifying therapeutic agents have led to a paradigm shift in which ATTR-CA screening is considered in high-risk populations, such as patients with heart failure with preserved ejection fraction (HFpEF) or aortic stenosis. Radiation risk from 99mTc-pyrophosphate (99mTc-PYP) scintigraphy, a test with very high sensitivity and specificity for ATTR-CA, has not been previously determined. Methods and ResultsRadiation doses to individual organs from 99mTc-PYP were estimated using models developed by the Medical Internal Radiation Dose Committee and the International Commission on Radiological Protection. Excess future cancer risks were estimated from organ doses, using risk projection models developed by the National Academies and extended by the National Cancer Institute. Excess future risks were estimated for men and women aged 40-80 and compared to total (excess plus baseline) future risks. All-organ excess cancer risks (90% uncertainty intervals) ranged from 5.88 (2.45,11.4) to 12.2 (4.11,26.0) cases per 100,000 patients undergoing 99mTc-PYP testing, were similar for men and women, and decreased with increasing age at testing. Cancer risks were highest to the urinary bladder, and bladder risk varied nearly twofold depending on which model was used. Excess 99mTc-PYP-related cancers constituted < 1% of total future cancers to the critical organs. ConclusionVery low cancer risks associated with 99mTc-PYP testing suggest a favorable benefit-risk profile for 99mTc-PYP as a screening test for ATTR-CA in high-risk populations, such as such as patients with HFpEF or aortic stenosis.

Usefulness of cancer-free survival in estimating the lifetime attributable risk of cancer incidence from radiation exposure

Risk projection models estimating the lifetime cancer risk from radiation exposure are generally based on exposure dose, age at exposure, attained age, gender and study-population-specific factors such as baseline cancer risks and survival rates. Because such models have mostly been based on the Life Span Study cohort of Japanese atomic bomb survivors, the baseline risks and survival rates in the target population should be considered when applying the cancer risk. The survival function used in the risk projection models that are commonly used in the radiological protection field to estimate the cancer risk from medical or occupational exposure is based on all-cause mortality. Thus, it may not be accurate for estimating the lifetime risk of high-incidence but not life-threatening cancer with a long-term survival rate. Herein, we present the lifetime attributable risk (LAR) estimates of all solid cancers except thyroid cancer, thyroid cancer, and leukemia except chronic lymphocytic leukemia in South Korea for lifetime exposure to 1 mGy per year using the cancer-free survival function, as recently applied in the Fukushima health risk assessment by the World Health Organization. Compared with the estimates of LARs using an overall survival function solely based on all-cause mortality, the LARs of all solid cancers except thyroid cancer, and thyroid cancer evaluated using the cancer-free survival function, decreased by approximately 13% and 1% for men and 9% and 5% for women, respectively. The LAR of leukemia except chronic lymphocytic leukemia barely changed for either gender owing to the small absolute difference between its incidence and mortality. Given that many cancers have a high curative rate and low mortality rate, using a survival function solely based on all-cause mortality may cause an overestimation of the lifetime risk of cancer incidence. The lifetime fractional risk was robust against the choice of survival function.

Outcomes of Active Surveillance for Ductal Carcinoma in Situ: A Computational Risk Analysis.

Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with uncertain risk for invasive progression. Usual care (UC) for DCIS consists of treatment upon diagnosis, thus potentially overtreating patients with low propensity for progression. One strategy to reduce overtreatment is active surveillance (AS), whereby DCIS is treated only upon detection of invasive disease. Our goal was to perform a quantitative evaluation of outcomes following an AS strategy for DCIS. Age-stratified, 10-year disease-specific cumulative mortality (DSCM) for AS was calculated using a computational risk projection model based upon published estimates for natural history parameters, and Surveillance, Epidemiology, and End Results data for outcomes. AS projections were compared with the DSCM for patients who received UC. To quantify the propagation of parameter uncertainty, a 95% projection range (PR) was computed, and sensitivity analyses were performed. Under the assumption that AS cannot outperform UC, the projected median differences in 10-year DSCM between AS and UC when diagnosed at ages 40, 55, and 70 years were 2.6% (PR = 1.4%-5.1%), 1.5% (PR = 0.5%-3.5%), and 0.6% (PR = 0.0%-2.4), respectively. Corresponding median numbers of patients needed to treat to avert one breast cancer death were 38.3 (PR = 19.7-69.9), 67.3 (PR = 28.7-211.4), and 157.2 (PR = 41.1-3872.8), respectively. Sensitivity analyses showed that the parameter with greatest impact on DSCM was the probability of understaging invasive cancer at diagnosis. AS could be a viable management strategy for carefully selected DCIS patients, particularly among older age groups and those with substantial competing mortality risks. The effectiveness of AS could be markedly improved by reducing the rate of understaging.

Mathematical Models for Estimating the Risks of Bovine Spongiform Encephalopathy (BSE)

When the bovine spongiform encephalopathy (BSE) epidemic first emerged in the United Kingdom in the mid 1980s, the etiology of animal prion diseases was largely unknown. Risk management efforts to control the disease were also subject to uncertainties regarding the extent of BSE infections and future course of the epidemic. As understanding of BSE increased, mathematical models were developed to estimate risk of BSE infection and to predict reductions in risk in response to BSE control measures. Risk models of BSE-transmission dynamics determined disease persistence in cattle herds and relative infectivity of cattle prior to onset of clinical disease. These BSE models helped in understanding key epidemiological features of BSE transmission and dynamics, such as incubation period distribution and age-dependent infection susceptibility to infection with the BSE agent. This review summarizes different mathematical models and methods that have been used to estimate risk of BSE, and discusses how such risk projection models have informed risk assessment and management of BSE. This review also provides some general insights on how mathematical models of the type discussed here may be used to estimate risks of emerging zoonotic diseases when biological data on transmission of the etiological agent are limited.

Space radiation-associated lung injury in a murine model.

Despite considerable progress in identifying health risks to crewmembers related to exposure to galactic/cosmic rays and solar particle events (SPE) during space travel, its long-term effects on the pulmonary system are unknown. We used a murine risk projection model to investigate the impact of exposure to space-relevant radiation (SR) on the lung. C3H mice were exposed to (137)Cs gamma rays, protons (acute, low-dose exposure mimicking the 1972 SPE), 600 MeV/u (56)Fe ions, or 350 MeV/u (28)Si ions at the NASA Space Radiation Laboratory at Brookhaven National Laboratory. Animals were irradiated at the age of 2.5 mo and evaluated 23.5 mo postirradiation, at 26 mo of age. Compared with age-matched nonirradiated mice, SR exposures led to significant air space enlargement and dose-dependent decreased systemic oxygenation levels. These were associated with late mild lung inflammation and prominent cellular injury, with significant oxidative stress and apoptosis (caspase-3 activation) in the lung parenchyma. SR, especially high-energy (56)Fe or (28)Si ions markedly decreased sphingosine-1-phosphate levels and Akt- and p38 MAPK phosphorylation, depleted anti-senescence sirtuin-1 and increased biochemical markers of autophagy. Exposure to SR caused dose-dependent, pronounced late lung pathological sequelae consistent with alveolar simplification and cellular signaling of increased injury and decreased repair. The associated systemic hypoxemia suggested that this previously uncharacterized space radiation-associated lung injury was functionally significant, indicating that further studies are needed to define the risk and to develop appropriate lung-protective countermeasures for manned deep space missions.

Radiation shielding effectiveness with correlated uncertainties

The space radiation environment is composed of energetic particles which can deliver harmful doses of radiation that may lead to acute radiation sickness, cancer, and even death for insufficiently shielded crew members. Spacecraft shielding must provide structural integrity and minimize the risk associated with radiation exposure. The risk of radiation exposure induced death (REID) is a measure of the risk of dying from cancer induced by radiation exposure. Uncertainties in the risk projection model, quality factor, and spectral fluence are folded into the calculation of the REID by sampling from probability distribution functions. Consequently, determining optimal shielding materials that reduce the REID in a statistically significant manner has been found to be difficult. In this work, the difference of the REID distributions for different materials is used to study the effect of composition on shielding effectiveness. It is shown that the use of correlated uncertainties allows for the determination of statistically significant differences between materials despite the large uncertainties in the quality factor. This is in contrast to previous methods where uncertainties have been generally treated as uncorrelated. It is concluded that the use of correlated quality factor uncertainties greatly reduces the uncertainty in the assessment of shielding effectiveness for the mitigation of radiation exposure.

Radiation-induced cataracts: the Health Protection Agency’s response to the ICRP statement on tissue reactions and recommendation on the dose limit for the eye lens

This paper presents the response of the Health Protection Agency (HPA) to the 2011 statement from the International Commission on Radiological Protection (ICRP) on tissue reactions and recommendation of a reduced dose limit for the lens of the eye. The response takes the form of a brief review of the most recent epidemiological and mechanistic evidence. This is presented together with a discussion of dose limits in the context of the related risk and the current status of eye dosimetry, which is relevant for implementation of the limits. It is concluded that although further work is desirable to quantify better the risk at low doses and following protracted exposures, along with research into the mechanistic basis for radiation cataractogenesis to inform selection of risk projection models, the HPA endorses the conclusion reached by the ICRP in their 2011 statement that the equivalent dose limit for the lens of the eye should be reduced from 150 to 20 mSv per year, averaged over a five year period, with no year’s dose exceeding 50 mSv.

Beyond the bombs: cancer risks of low-dose medical radiation

It’s been a decade since Brenner and colleagues published their landmark paper1 suggesting that the radiation doses from paediatric computed tomography (CT) scans would cause a significant number of cancer deaths, sometime in the future. The following day the story hit the front page of USA Today, and the world of CT scans was changed forever.

Prediction of the variation in risks from exposure to radon at home or at work

On the basis of a review of recent epidemiology, the ICRP recently issued a statement outlining a new approach to radon. The ICRP indicates that the Publication 65 dose conversion convention will be replaced using the dosimetric approach currently used for other radionuclides. Moreover, the ICRP indicates that the dose conversion factor is expected to increase by about a factor of 2. This paper independently examines the risks associated with exposure to radon and decay products through estimation of lifetime excess absolute risks per WLM for a variety of epidemiological risk projection models and baseline cancer and mortality rates. This paper suggests that current ICRP dosimetric models do not reflect the effect of smoking and suggest that basic risk estimates and dose conversion factors be based on risks to non-smoking populations with recognition that lifestyle choices, especially smoking, have a large effect on the risk from exposure to radon.

Myocardial Perfusion Scans

Background— Myocardial perfusion scans contribute up to 20% of the estimated annual collective radiation dose to the US population. We estimated potential future cancer risk from these scans by age at exposure and current frequency of use in the United States. Methods and Results— Usage patterns were determined from national survey data, and radionuclide dosage was based on current guidelines. Cancer risk projection models were generated on the basis of the National Research Council Biological Effects of Ionizing Radiation VII report, under the assumption that risk has a linear relationship with radiation exposure even at low doses. The mean projected number of radiation-related incident cancers and 95% uncertainty intervals were estimated with the use of Monte Carlo simulations. Estimated risks for a scan performed at age 50 years ranged from 2 cancers per 10 000 scans (95% uncertainty interval, 1 to 5) for a positron emission tomography ammonia-13 test to 25 cancers per 10 000 scans (95% uncertainty interval, 9 to 58) for a dual-isotope (thallium-201 plus technetium-99m) scan. Risks were 50% lower at age 70 years but were similar for men and women. The combination of cancer risk estimates and data on frequency of use suggests that the 9.1 million myocardial perfusion scans performed annually in the United States could result in 7400 (95% uncertainty interval, 3300 to 13 700) additional future cancers. Conclusions— The lifetime cancer risk from a single myocardial perfusion scan is small and should be balanced against likely benefit and appropriateness of the test. The estimates depend on a number of assumptions, including life expectancy. They apply directly to asymptomatic individuals with life expectancies similar to those of the general population. For individuals with a symptomatic clinical profile, on whom such scans are typically performed, the risks will be lower because of shorter life expectancy.

TH-B-213A-01: Risks From Occupational Radiation Exposures

Radiologists and radiologic technicians were among the earliest occupational groups to be exposed to ionizing radiation, and still constitute one of the largest groups of workers exposed to man-made sources of radiation whilst at work. Studies of human populations exposed to acute, high doses of ionizing radiation have proved valuable in assessing the link between radiation and cancer and have been used to derive quantitative estimates of risk. However, the applicability of these estimates to the assessment of risks following fractionated or low level exposures remains uncertain. A number of epidemiologic studies have been conducted therefore to assess the potential risks from medical occupational exposure directly, including studies of radiologists in the UK, US and China and a cohort of radiologic technicians radiographers in the U.S. This lecture will provide an overview of these epidemiological studies and their findings, as well as a description of a new study of physicians that perform fluoroscopically guided procedures that we are currently running at the National Cancer Institute. The use of cancer risk projection models that we have developed to estimate potential lifetime cancer risk following specified exposure histories will also be described with examples. Learning Objectives: 1. Understand the strengths and limitations of the epidemiologic studies of medical radiation workers 2. Understand the strengths and limitations of risk projection models to estimate lifetime cancer risks from occupational radiation exposures

Fourth International Workshop on Space Radiation Research (IWSRR)

The goal of understanding the planets and stars provided a unifying perspective to international scientists such as Galileo Galilei, Johannes Kepler and Michail V. Lomonosov who studied the nature of space leading to advances on Earth. Astronauts and cosmonauts from many diverse nations now routinely venture into space, often on joint missions, and share a common perspective of the Earth and Heavens from their unique vantage point. However, the length and destination, such as the moon or Mars, of space missions are currently constrained by the potentially detrimental health risks from space radiation. The reduction of uncertainties in risk projection models for cancer and other late effects, and the development of effective mitigation measures to protect against galactic cosmic rays and solar energetic particles are active areas of scientific research [1]. The fourth International Workshop on Space Radiation Research (IWSRR) held June 5–9, 2006, which included the 17th Annual NASA Space Radiation Health Investigators Meeting, was a unique opportunity to bring leading researchers from all space bearing nations together to create a unifying perspective for realizing solutions to the problem of space radiation. Space radiation research is by its nature an inter-disciplinary science, spanning several areas of biology, physics, and engineering [1]. The fourth IWSRR built on the success of previous meetings held in the cities of Arona in Italy [2], Nara in Japan [3], and Port Jefferson in the United States [4]. However the theme for the meeting, ‘‘From Stars to Stars’’ explored new boundaries since for the first time the meeting was held in two great cities, Moscow and St. Petersburg with a starlight journey by train connecting the cities at the half-way point of the meeting. The life of Michail V. Lomonosov (B. 1711, D. 1765) serves as a fitting symbol for the meeting. Known for his observations of the atmosphere of Venus, he was a member of the faculty at the St. Petersburg Imperial Academy of Sciences, but later founded Moscow State University, and made inter-disciplinary contributions to several areas of science and literature [5]. This special issue of the journal ‘‘Radiation and Environmental Biophysics’’ contains 20 peer-reviewed papers contributed by leading space radiation researcher’s worldwide attending the fourth IWSRR. Manuscripts cover a broad range of topics ranging from radiation environments and transport in shielding and planetary surfaces to new results in understanding the biological effects of protons and high-charge and energy (HZE) nuclei on the risk of cancer, and degenerative diseases such as central nervous system effects, heart disease, and cataracts. The issue provides a snapshot of the state-of-the-art of the research in this field, demonstrating both the important results gathered in the past few years with experiments at accelerators, and the need for more research to quantify the risk and develop countermeasures. The Guest Editors extend a sincere note of gratitude to Dr. Vyacheslav Shurshakov, the Scientific Secretary to this F. A. Cucinotta (&) NASA Lyndon B. Johnson Space Center, Houston, TX 77058, USA e-mail: Francis.A.Cucinotta@nasa.gov

Use of risk projection models to estimate mortality and incidence from radiation-induced breast cancer in screening programs

The authors report on a method to calculate radiological risks, applicable to breast screening programs and other controlled medical exposures to ionizing radiation. In particular, it has been applied to make a risk assessment in the Valencian Breast Cancer Early Detection Program (VBCEDP) in Spain. This method is based on a parametric approach, through Markov processes, of hazard functions for radio-induced breast cancer incidence and mortality, with mean glandular breast dose, attained age and age-at-exposure as covariates. Excess relative risk functions of breast cancer mortality have been obtained from two different case-control studies exposed to ionizing radiation, with different follow-up time: the Canadian Fluoroscopy Cohort Study (1950–1987) and the Life Span Study (1950–1985 and 1950–1990), whereas relative risk functions for incidence have been obtained from the Life Span Study (1958–1993), the Massachusetts tuberculosis cohorts (1926–1985 and 1970–1985), the New York post-partum mastitis patients (1930–1981) and the Swedish benign breast disease cohort (1958–1987). Relative risks from these cohorts have been transported to the target population undergoing screening in the Valencian Community, a region in Spain with about four and a half million inhabitants. The SCREENRISK software has been developed to estimate radiological detriments in breast screening. Some hypotheses corresponding to different screening conditions have been considered in order to estimate the total risk associated with a woman who takes part in all screening rounds. In the case of the VBCEDP, the total radio-induced risk probability for fatal breast cancer is in a range between [5 × 10−6, 6 × 10−4] versus the natural rate of dying from breast cancer in the Valencian Community which is 9.2 × 10−3. The results show that these indicators could be included in quality control tests and could be adequate for making comparisons between several screening programs.

Radiation protection dosimetry for diagnostic radiology patients.

The radiation protection of patients undergoing medical X-ray examinations is governed by the principles of justification and optimisation. Radiation dosimetry is required to inform medical practitioners of the levels of exposure and hence the risks from the diagnostic procedures that they have to justify and to assist the operators of X-ray imaging equipment to determine whether their procedures are optimised. This paper describes the main dosimetric methods that have been developed to meet these requirements. Suitable radiation risk projection models are used to predict the risks to patients in the UK from computed tomography examinations, as a function of age at exposure and sex, and show that the lifetime risk of fatal cancer can reach 1 in 1000 for children. The concept of 'diagnostic reference levels' as an aid to the optimisation of medical exposures is described, and progress in implementing them in the UK is reported.

The use of biologically based cancer risk models in radiation epidemiology.

Biologically based risk projection models for radiation carcinogenesis seek to describe the fundamental biological processes involved in neoplastic transformation of somatic cells into malignant cancer cells. A validated biologically based model, whose parameters have a direct biological interpretation, can also be used to extrapolate cancer risks to different exposure conditions with some confidence. In this article biologically based models for radiation carcinogenesis, including the two-stage clonal expansion (TSCE) model and its extensions, are reviewed. The biological and mathematical bases for such models are described, and the implications of key model parameters for cancer risk assessment examined. Specific applications of versions of the TSCE model to important epidemiological datasets are discussed, including the Colorado uranium miners' cohort; a cohort of Chinese tin miners; the lifespan cohort of atomic bomb survivors in Hiroshima and Nagasaki; and a cohort of over 200,000 workers included in the National Dose Registry (NDR) of Canada.

Lifetime risk of lung cancer due to radon exposure projected to Japanese and Swedish populations.

Lifetime risk projections depend greatly on both background lung cancer rates and the selection of the risk model. Since background lung cancer rates differ from subject populations and the time, etiological risk of lifetime lung cancer mortality per unit radon exposure in WLM should be estimated for each subject population and the time of interest. To answer quantitatively how much are the differences among the projected risks for different populations, the Swedish case-control-study-based risk projection model was applied to the Japanese and Swedish populations from 1962 to 1997 as subject populations because of their distinct trends of lung cancer rates. To compare the results with the reference population and authorized risk projection models, U.S. population 1997 and the two risk projection models in BEIR VI report were applied, respectively. Lifetime risk of lung cancer mortality projected for Japanese, Swedish, and U.S. populations in 1997 per radon progeny exposure were estimated to range from 1.50 (0.40-3.19) x 10(-4) WLM(-1) to 9.86 (2.62-20.9) x 10(-4) WLM(-1), which could be compared to the detriment associated with a unit effective dose. Conclusive dose conversion coefficients in this study ranged from 2.05 (0.55-4.37) to 13.5 (3.59-28.6) mSv WLM(-1), and within this range the discrepancy between dosimetric and epidemiological approaches was included.

Characterization of uncertainty and variability in residential radon cancer risks.

Radon, a naturally occurring gas found at some level in most homes, is an established risk factor for human lung cancer. The U.S. National Research Council has recently completed a comprehensive evaluation of the health risks of residential exposure to radon and developed models for projecting radon lung cancer risks to the general population. This analysis suggests that radon may play a role in the etiology of 10-15% of all lung cancer cases in the United States, although these estimates are subject to considerable uncertainty. In this article, we present a detailed analysis of uncertainty and variability in estimates of lung cancer risk due to residential exposure to radon. We use a general framework for the analysis of uncertainty and variability that we developed previously. Specifically, we focus on estimates of the age-specific excess relative risk (ERR) and lifetime relative risk (LRR), both of which vary substantially among individuals. We also consider estimates of the population attributable risk (PAR), which reflects the proportion of the lung cancer burden attributable to radon. Variability in the ERR and LRR is largely determined by variability in residential exposure levels and in the dosimetric K-factor used to extrapolate from occupational to environmental settings. Uncertainty in the ERR and LRR is due to uncertainty in the model parameters, notably those reflecting the carcinogenic potency of radon and the modifying effect of attained age. Uncertainty in the PAR is determined by uncertainty about the values of the parameters in the risk models used to estimate the PAR. Uncertainty in radon levels in homes and the dosimetric K-factor contribute comparatively little to uncertainty in the PAR. These results suggest that reduction in uncertainty about the PAR for radon induced lung cancer can only be achieved if more reliable risk projection models can be developed.