A method for determining weights for excess relative risk and excess absolute risk when applied in the calculation of lifetime risk of cancer from radiation exposure

Comparison and multi-model inference of excess risks models for radiation-related solid cancer

In assessments of detrimental health risks from exposures to ionising radiation, many forms of risk to dose-response models are available in the literature. The usual practice is to base risk assessment on one specific model and ignore model uncertainty. The analysis illustrated here considers model uncertainty for the outcome all solid cancer incidence, when modelled as a function of colon organ dose, using the most recent publicly available data from the Life Span Study on atomic bomb survivors of Japan. Seven recent publications reporting all solid cancer risk models currently deemed plausible by the scientific community have been included in a model averaging procedure so that the main conclusions do not depend on just one type of model. The models have been estimated with different baselines and presented for males and females at various attained ages and ages at exposure, to obtain specially computed model-averaged Excess Relative Risks (ERR) and Excess Absolute Risks (EAR). Monte Carlo simulated estimation of uncertainty on excess risks was accounted for by applying realisations including correlations in the risk model parameters. Three models were found to weight the model-averaged risks most strongly depending on the baseline and information criteria used for the weighting. Fitting all excess risk models with the same baseline, one model dominates for both information criteria considered in this study. Based on the analysis presented here, it is generally recommended to take model uncertainty into account in future risk analyses.

Cancer incidence risks above and below 1 Gy for radiation protection in space

The risk assessment quantities called lifetime attributable risk (LAR) and risk of exposure-induced cancer (REIC) are used to calculate the cumulative cancer incidence risks for astronauts, attributable to radiation exposure accumulated during long term lunar and Mars missions. These risk quantities are based on the most recently published epidemiological data on the Life Span Study (LSS) of Japanese A-bomb survivors, who were exposed to γ-rays and neutrons. In order to analyze the impact of a different neutron RBE on the risk quantities, a model for the neutron relative biological effectiveness (RBE) relative to gammas in the LSS is developed based on an older dataset with less follow-up time. Since both risk quantities are based on uncertain quantities, such as survival curves, and REIC includes deterministic radiation induced non-cancer mortality risks, modelled with data based on the general population, the risks for astronauts may not be optimally estimated. The suitability of these risk assessment measures for the use of cancer risk calculation for astronauts is discussed. The work presented here shows that the use of a higher neutron RBE than the value of 10, traditionally used in the LSS risk models, can reduce the risks up to almost 50%. Additionally, including an excess absolute risk (EAR) baseline scaling also increases the risks by between 0.4% and 8.1% for the space missions considered in this study. Using just an EAR model instead of an equally weighted EAR and excess relative risk (ERR) model can decrease the cumulative risks for the considered missions by between 0.4% and 4.1% if no EAR baseline scaling is applied. If EAR baseline scaling is included, the calculated risks with the EAR- and the mixed model, as well as the risks calculated with just the ERR model are almost identical and only small differences in the uncertainties are visible.

Risk bases can complement dose bases for implementing and optimising a radiological protection strategy in urgent and transition emergency phases

Current radiological emergency response recommendations have been provided by the International Commission on Radiological Protection and adopted by the International Atomic Energy Agency in comprehensive Safety Standards. These standards provide dose-based guidance for decision making (e.g., on sheltering or relocation) via generic criteria in terms of effective dose in the range from 20 mSv per year, during transition from emergency to existing exposure situation, to 100 mSv, acute or annual, in the urgent phase of a nuclear accident. The purpose of this paper was to examine how such dose reference levels directly translate into radiation-related risks of the main stochastic detrimental health effects (cancer). Methodologies, provided by the World Health Organization after the Fukushima accident, for calculating the lifetime and 20 year cancer risks and for attributing relevant organ doses from effective doses, have been applied here for this purpose with new software, designed to be available for use immediately after a nuclear accident. A new feature in this software is a comprehensive accounting for uncertainty via simulation technique, so that the risks may now be presented with realistic confidence intervals. The types of cancer risks considered here are time-integrated over lifetime and the first 20 years after exposure for all solid cancers and either the most radiation-sensitive types of cancer, i.e., leukaemia and female breast cancer, or the most radiation-relevant type of cancer occurring early in life, i.e., thyroid. It is demonstrated here how reference dose levels translate differently into specific cancer risk levels (with varying confidence interval sizes), depending on age at exposure, gender, time-frame at-risk and type of cancer considered. This demonstration applies German population data and considers external exposures. Further work is required to comprehensively extend this methodology to internal exposures that are likely to be important in the early stages of a nuclear accident. A discussion is provided here on the potential for such risk-based information to be used by decision makers, in the urgent and transition phases of nuclear emergencies, to identify protective measures (e.g., sheltering, evacuation) in a differential way (i.e., for particularly susceptible sub-groups of a population).

Estimation of radiotherapy modalities for patients with stage I-II nasal natural killer T-Cell lymphoma

Purpose

The objective of this study is to estimate radiotherapy (RT) modalities for patients with stage I-II nasal natural killer T-Cell lymphoma (NNKTCL), including plan quality, radiation delivery efficiency, cost of RT and excess absolute risk (EAR).

Materials and methods

Twenty-four representative patients with stage I-II NNKTCL treated with fix-field intensity-modulated radiotherapy (FF-IMRT) were re-planned for volumetric modulated arc therapy (VMAT), TomoDirect (TD) and TomoHelical (TH) on the TomoHDA system, respectively. Plan characteristics, cost of RT and EAR were compared.

Results

Compared with IMRT, TD and TH showed significant improvement in terms of D_98%, D_2%, cold spot volume and homogeneity index (HI) of planning target volume (PTV), while achieving worse D_mean and conformity index (CI). The mean dose of oropharynx, thyroid and left salivary, and the maximum dose of right salivary by TD (249.20%, p=0.000; 52.94%, p=0.000; 160.23%, p=0.022; 122.67%, p=0.027), VMAT (15.76%, p=0.000; 23.53%, p=0.000; 34.09%, p=0.000; 31.33%, p=0.000) and TH (250.32%, p=0.000; 58.82%, p=0.000; 120.45%, p=0.020; 117.33%, p=0.032) increased significantly compared to IMRT. VMAT reduced treatment time (p=0.000; 0.000; 0.000) and monitor units (MUs) (p=0.000; 0.000; 0.000) obviously compared with IMRT, TD and TH. The cost of RT for TD and TH increased 150% compared with IMRT and VMAT. IMRT obtained the lowest EAR to oropharynx, thyroid, left and right salivary gland in the four treatment modalities.

Conclusion

The results show that both TD and TH can achieve higher conformal target quality while getting worse organs at risk (OARs) sparing and EAR to some organs than IMRT for patients with stage I-II NNKTCL. IMRT delivers the lowest dose to most OARs, VMAT requires the lower cost of RT and shortest delivery time, and TH obtained the optimal target coverage. The results could provide direction for selecting proper RT modalities for different cases.

Methods to account for uncertainties in exposure assessment in studies of environmental exposures

BACKGROUND

Accurate exposure estimation in environmental epidemiological studies is crucial for health risk assessment. Failure to account for uncertainties in exposure estimation could lead to biased results in exposure-response analyses. Assessment of the effects of uncertainties in exposure estimation on risk estimates received a lot of attention in radiation epidemiology and in several studies of diet and air pollution. The objective of this narrative review is to examine the commonly used statistical approaches to account for exposure estimation errors in risk analyses and to suggest how each could be applied in environmental epidemiological studies.

MAIN TEXT

We review two main error types in estimating exposures in epidemiological studies: shared and unshared errors and their subtypes. We describe the four main statistical approaches to adjust for exposure estimation uncertainties (regression calibration, simulation-extrapolation, Monte Carlo maximum likelihood and Bayesian model averaging) along with examples to give readers better understanding of their advantages and limitations. We also explain the advantages of using a 2-dimensional Monte-Carlo (2DMC) simulation method to quantify the effect of uncertainties in exposure estimates using full-likelihood methods. For exposures that are estimated independently between subjects and are more likely to introduce unshared errors, regression calibration and SIMEX methods are able to adequately account for exposure uncertainties in risk analyses. When an uncalibrated measuring device is used or estimation parameters with uncertain mean values are applied to a group of people, shared errors could potentially be large. In this case, Monte Carlo maximum likelihood and Bayesian model averaging methods based on estimates of exposure from the 2DMC simulations would work well. The majority of reviewed studies show relatively moderate changes (within 100%) in risk estimates after accounting for uncertainties in exposure estimates, except for the two studies which doubled/tripled naïve estimates.

CONCLUSIONS

In this paper, we demonstrate various statistical methods to account for uncertain exposure estimates in risk analyses. The differences in the results of various adjustment methods could be due to various error structures in datasets and whether or not a proper statistical method was applied. Epidemiological studies of environmental exposures should include exposure-response analyses accounting for uncertainties in exposure estimates.

MASM, a Matrine Derivative, Offers Radioprotection by Modulating Lethal Total-Body Irradiation-Induced Multiple Signaling Pathways in Wistar Rats

Matrine is an alkaloid extracted from Sophora flavescens Ait and has many biological activities, such as anti-inflammatory, antitumor, anti-fibrosis, and immunosuppressive properties. In our previous studies, the matrine derivative MASM was synthesized and exhibited potent inhibitory activity against liver fibrosis. In this study, we mainly investigated its protection against lethal total-body irradiation (TBI) in rats. Administration of MASM reduced the radiation sickness characteristics and increased the 30-day survival of rats before or after lethal TBI. Ultrastructural observation illustrated that pretreatment of rats with MASM significantly attenuated the TBI-induced morphological changes in the different organs of irradiated rats. Gene expression profiles revealed that pretreatment with MASM had a dramatic effect on gene expression changes caused by TBI. Pretreatment with MASM prevented differential expression of 53% (765 genes) of 1445 differentially expressed genes induced by TBI. Pathway enrichment analysis indicated that these genes were mainly involved in a total of 21 pathways, such as metabolic pathways, pathways in cancer, and mitogen-activated protein kinase (MAPK) pathways. Our data indicated that pretreatment of rats with MASM modulated these pathways induced by TBI, suggesting that the pretreatment with MASM might provide the protective effects on lethal TBI mainly or partially through the modulation of these pathways, such as multiple MAPK pathways. Therefore, MASM has the potential to be used as an effective therapeutic or radioprotective agent to minimize irradiation damages and in combination with radiotherapy to improve the efficacy of cancer therapy.

Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

PURPOSE

Theoretical dose-response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients.

METHODS

A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagation was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities.

RESULTS

Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry.

CONCLUSIONS

The uncertainty in the dose-response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio of absolute risks between two modalities is less sensitive to the uncertainties in the risk model and can provide statistically significant estimates.

A framework for estimating radiation-related cancer risks in Japan from the 2011 Fukushima nuclear accident

We present here a methodology for health risk assessment adopted by the World Health Organization that provides a framework for estimating risks from the Fukushima nuclear accident after the March 11, 2011 Japanese major earthquake and tsunami. Substantial attention has been given to the possible health risks associated with human exposure to radiation from damaged reactors at the Fukushima Daiichi nuclear power station. Cumulative doses were estimated and applied for each post-accident year of life, based on a reference level of exposure during the first year after the earthquake. A lifetime cumulative dose of twice the first year dose was estimated for the primary radionuclide contaminants ((134)Cs and (137)Cs) and are based on Chernobyl data, relative abundances of cesium isotopes, and cleanup efforts. Risks for particularly radiosensitive cancer sites (leukemia, thyroid and breast cancer), as well as the combined risk for all solid cancers were considered. The male and female cumulative risks of cancer incidence attributed to radiation doses from the accident, for those exposed at various ages, were estimated in terms of the lifetime attributable risk (LAR). Calculations of LAR were based on recent Japanese population statistics for cancer incidence and current radiation risk models from the Life Span Study of Japanese A-bomb survivors. Cancer risks over an initial period of 15 years after first exposure were also considered. LAR results were also given as a percentage of the lifetime baseline risk (i.e., the cancer risk in the absence of radiation exposure from the accident). The LAR results were based on either a reference first year dose (10 mGy) or a reference lifetime dose (20 mGy) so that risk assessment may be applied for relocated and non-relocated members of the public, as well as for adult male emergency workers. The results show that the major contribution to LAR from the reference lifetime dose comes from the first year dose. For a dose of 10 mGy in the first year and continuing exposure, the lifetime radiation-related cancer risks based on lifetime dose (which are highest for children under 5 years of age at initial exposure), are small, and much smaller than the lifetime baseline cancer risks. For example, after initial exposure at age 1 year, the lifetime excess radiation risk and baseline risk of all solid cancers in females were estimated to be 0.7 · 10(-2) and 29.0 · 10(-2), respectively. The 15 year risks based on the lifetime reference dose are very small. However, for initial exposure in childhood, the 15 year risks based on the lifetime reference dose are up to 33 and 88% as large as the 15 year baseline risks for leukemia and thyroid cancer, respectively. The results may be scaled to particular dose estimates after consideration of caveats. One caveat is related to the lack of epidemiological evidence defining risks at low doses, because the predicted risks come from cancer risk models fitted to a wide dose range (0-4 Gy), which assume that the solid cancer and leukemia lifetime risks for doses less than about 0.5 Gy and 0.2 Gy, respectively, are proportional to organ/tissue doses: this is unlikely to seriously underestimate risks, but may overestimate risks. This WHO-HRA framework may be used to update the risk estimates, when new population health statistics data, dosimetry information and radiation risk models become available.

Radiotherapy-induced secondary cancer risk for breast cancer: 3D conformal therapy versus IMRT versus VMAT

This study evaluated the secondary cancer risk to various organs due to radiation treatment for breast cancer. Organ doses to an anthropomorphic phantom were measured using a photoluminescent dosimeter (PLD) for breast cancer treatment with 3D conformal radiation therapy (3D-CRT), intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT). Cancer risk based on the measured dose was calculated using the BEIR (Biological Effects of Ionizing Radiation) VII models. The secondary dose per treatment dose (50.4 Gy) to various organs ranged from 0.02 to 0.36 Gy for 3D-CRT, but from 0.07 to 8.48 Gy for IMRT and VMAT, indicating that the latter methods are associated with higher secondary radiation doses than 3D-CRT. The result of the homogeneity index in the breast target shows that the dose homogeneity of 3D-CRT was worse than those of IMRT and VMAT. The organ specific lifetime attributable risks (LARs) to the thyroid, contralateral breast and ipsilateral lung per 100 000 population were 0.02, 19.71, and 0.76 respectively for 3D-CRT, much lower than the 0.11, 463.56, and 10.59 respectively for IMRT and the 0.12, 290.32, and 12.28 respectively for VMAT. The overall estimation of LAR indicated that the radiation-induced cancer risk due to breast radiation therapy was lower with 3D-CRT than with IMRT or VMAT.

Impact of uncertainties in exposure assessment on estimates of thyroid cancer risk among Ukrainian children and adolescents exposed from the Chernobyl accident

The 1986 accident at the Chernobyl nuclear power plant remains the most serious nuclear accident in history, and excess thyroid cancers, particularly among those exposed to releases of iodine-131 remain the best-documented sequelae. Failure to take dose-measurement error into account can lead to bias in assessments of dose-response slope. Although risks in the Ukrainian-US thyroid screening study have been previously evaluated, errors in dose assessments have not been addressed hitherto. Dose-response patterns were examined in a thyroid screening prevalence cohort of 13,127 persons aged <18 at the time of the accident who were resident in the most radioactively contaminated regions of Ukraine. We extended earlier analyses in this cohort by adjusting for dose error in the recently developed TD-10 dosimetry. Three methods of statistical correction, via two types of regression calibration, and Monte Carlo maximum-likelihood, were applied to the doses that can be derived from the ratio of thyroid activity to thyroid mass. The two components that make up this ratio have different types of error, Berkson error for thyroid mass and classical error for thyroid activity. The first regression-calibration method yielded estimates of excess odds ratio of 5.78 Gy⁻¹ (95% CI 1.92, 27.04), about 7% higher than estimates unadjusted for dose error. The second regression-calibration method gave an excess odds ratio of 4.78 Gy⁻¹ (95% CI 1.64, 19.69), about 11% lower than unadjusted analysis. The Monte Carlo maximum-likelihood method produced an excess odds ratio of 4.93 Gy⁻¹ (95% CI 1.67, 19.90), about 8% lower than unadjusted analysis. There are borderline-significant (p = 0.101–0.112) indications of downward curvature in the dose response, allowing for which nearly doubled the low-dose linear coefficient. In conclusion, dose-error adjustment has comparatively modest effects on regression parameters, a consequence of the relatively small errors, of a mixture of Berkson and classical form, associated with thyroid dose assessment.