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.

Tobacco industry ownership of pharmaceutical companies: an international survey of people with respiratory disease.

The 2021 purchase of the respiratory pharmaceutical company Vectura by Phillip Morris International has been criticised by the public health and medical community, as a conflict of interest, with little input to date, from the patient community or the public. To address this gap, the COPD Foundation, along with global partners, surveyed 1196 people with chronic respiratory disease. 70% were bothered by a tobacco company making an inhaler to treat lung conditions and 48% reported that they would want to switch inhalers if they knew that a tobacco company made or sold their inhaler devices. Patients care about who makes the therapies used to treat their diseases.

On the choice of methodology for evaluating dose-rate effects on radiation-related cancer risks.

Recently, several compilations of individual radiation epidemiology study results have aimed to obtain direct evidence on the magnitudes of dose-rate effects on radiation-related cancer risks. These compilations have relied on meta-analyses of ratios of risks from low dose-rate studies and matched risks from the solid cancer Excess Relative Risk models fitted to the acutely exposed Japanese A-bomb cohort. The purpose here is to demonstrate how choices of methodology for evaluating dose-rate effects on radiation-related cancer risks may influence the results reported for dose-rate effects. The current analysis is intended to address methodological issues and does not imply that the authors recommend a particular value for the dose and dose-rate effectiveness factor. A set of 22 results from one recent published study has been adopted here as a test set of data for applying the many different methods described here, that nearly all produced highly consistent results. Some recently voiced concerns, involving the recalling of the well-known theoretical point-the ratio of two normal random variables has a theoretically unbounded variance-that could potentially cause issues, are shown to be unfounded when aimed at the published work cited and examined in detail here. In the calculation of dose-rate effects for radiation protection purposes, it is recommended that meta-estimators should retain the full epidemiological and dosimetric matching information between the risks from the individual low dose-rate studies and the acutely exposed A-bomb cohort and that a regression approach can be considered as a useful alternative to current approaches.

A bespoke health risk assessment methodology for the radiation protection of astronauts.

An alternative approach that is particularly suitable for the radiation health risk assessment (HRA) of astronauts is presented. The quantity, Radiation Attributed Decrease of Survival (RADS), representing the cumulative decrease in the unknown survival curve at a certain attained age, due to the radiation exposure at an earlier age, forms the basis for this alternative approach. Results are provided for all solid cancer plus leukemia incidence RADS from estimated doses from theoretical radiation exposures accumulated during long-term missions to the Moon or Mars. For example, it is shown that a 1000-day Mars exploration mission with a hypothetical mission effective dose of 1.07 Sv at typical astronaut ages around 40 years old, will result in the probability of surviving free of all types of solid cancer and leukemia until retirement age (65 years) being reduced by 4.2% (95% CI 3.2; 5.3) for males and 5.8% (95% CI 4.8; 7.0) for females. RADS dose-responses are given, for the outcomes for incidence of all solid cancer, leukemia, lung and female breast cancer. Results showing how RADS varies with age at exposure, attained age and other factors are also presented. The advantages of this alternative approach, over currently applied methodologies for the long-term radiation protection of astronauts after mission exposures, are presented with example calculations applicable to European astronaut occupational HRA. Some tentative suggestions for new types of occupational risk limits for space missions are given while acknowledging that the setting of astronaut radiation-related risk limits will ultimately be decided by the Space Agencies. Suggestions are provided for further work which builds on and extends this new HRA approach, e.g., by eventually including non-cancer effects and detailed space dosimetry.

Valid versus invalid radiation cancer risk assessment methods illustrated using Swiss population data.

After the nuclear accident in Fukushima, the public interest in radiation related cancer-risk assessment increased. However, interpretations of results from epidemiological studies and comprehension of cancer risk assessment methods can be unclear and involve questions about correctness and validity of the approaches. To shed some light on this potential lack of clarity, valid versus invalid radiation cancer risk assessments methods are illustrated here using Swiss population data. This involves a comparison of the cancer risk assessment method based on collective dose and the cumulative risk assessment method, where the latter is recommended with regard to uncertainties and risk of misinterpretation. Further, risk assessment in different dose ranges is discussed and it is concluded that below 100 mSv it cannot be appropriately stated that an adequate strength of evidence of a causal relationship between cancer and radiation is provided, because of the large uncertainties in this dose range. However, the linear non-threshold (LNT) model can be used to model the dose response, because it represents a prudent and parsimonious model, that fits the data well and lies within the given uncertainties. Additionally, treatments of uncertainties in the risk models are illustrated. The EU-project CONFIDENCE software is applied here to obtain example radiation related lifetime cancer risks for exposures of 20 mSv and 5 mSv. Furthermore, the impact of different dosimetry errors on the uncertainties in the cancer lifetime risk calculation is analysed, by including different standard deviations (SD) and by comparing the sampling of the doses from a normal and a lognormal distribution. Using the normal distribution, for females exposed to 20 mSv, the 95% confidence interval (CI) on the cancer lifetime risk increases, when compared to using a SD of 4 mSv, by a factor of 1.5 using a SD of 8 mSv and by a factor of 1.7 using a SD of 10 mSv. The corresponding factors for males for the same exposure are 1.3 and 1.5 respectively. For exposure to 5 mSv, the 95% CIs on the risk increase by a factor of 1.2 for females and 1.4 for men for a SD of 2 mSv using the normal distribution compared to the lognormal distribution and by a factor of 1.5 and 1.8 for a SD of 3 mSv compared to a SD of 1 mSv respectively. Furthermore, differences in the resulting 95% CI on the risk, using different distributions for the dose sampling are visible.

On prognostic estimates of radiation risk in medicine and radiation protection.

The problem of expressing cumulative detrimental effect of radiation exposure is revisited. All conventionally used and computationally complex lifetime or time-integrated risks are based on current population and health statistical data, with unknown future secular trends, that are projected far into the future. It is shown that application of conventionally used lifetime or time-integrated attributable risks (LAR, AR) should be limited to exposures under 1 Gy. More general quantities, such as excess lifetime risk (ELR) and, to a lesser extent, risk of exposure-induced death (REID), are free of dose constraints, but are even more computationally complex than LAR and AR and rely on the unknown total radiation effect on demographic and health statistical data. Appropriate assessment of time-integrated risk of a specific outcome following high-dose (more than 1 Gy) exposure requires consideration of competing risks for other radiation-attributed outcomes and the resulting ELR estimate has an essentially non-linear dose response. Limitations caused by basing conventionally applied time-integrated risks on current population and health statistical data are that they are: (a) not well suited for risk estimates for atypical groups of exposed persons not readily represented by the general population; and (b) not optimal for risk projections decades into the future due to large uncertainties in developments of the future secular trends in the population-specific disease rates. Alternative disease-specific quantities, baseline and attributable survival fractions, based on reduction of survival chances are considered here and are shown to be very useful in circumventing most aspects of these limitations. Another main quantity, named as radiation-attributed decrease of survival (RADS), is recommended here to represent cumulative radiation risk conditional on survival until a certain age. RADS, historically known in statistical literature as "cumulative risk", is only based on the radiation-attributed hazard and is insensitive to competing risks. Therefore, RADS is eminently suitable for risk projections in emergency situations and for estimating radiation risks for persons exposed after therapeutic or interventional medical applications of radiation or in other highly atypical groups of exposed persons, such as astronauts.

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).

Tumour size can have an impact on the outcomes of epidemiological studies on second cancers after radiotherapy.

Obtaining a correct dose-response relationship for radiation-induced cancer after radiotherapy presents a major challenge for epidemiological studies. The purpose of this paper is to gain a better understanding of the associated uncertainties. To accomplish this goal, some aspects of an epidemiological study on breast cancer following radiotherapy of Hodgkin's disease were simulated with Monte Carlo methods. It is demonstrated that although the doses to the breast volume are calculated by one treatment plan, the locations and sizes of the induced secondary breast tumours can be simulated and, based on these simulated locations and sizes, the absorbed doses at the site of tumour incidence can also be simulated. For the simulations of point dose at tumour site, linear and non-linear mechanistic models which predict risk of cancer induction as a function of dose were applied randomly to the treatment plan. These simulations provided for each second tumour and each simulated tumour size the predicted dose. The predicted-dose-response-characteristic from the analysis of the simulated epidemiological study was analysed. If a linear dose-response relationship for cancer induction was applied to calculate the theoretical doses at the simulated tumour sites, all Monte-Carlo realizations of the epidemiological study yielded strong evidence for a resulting linear risk to predicted-dose-response. However, if a non-linear dose-response of cancer induction was applied to calculate the theoretical doses, the Monte Carlo simulated epidemiological study resulted in a non-linear risk to predicted-dose-response relationship only if the tumour size was small (< 1.5 cm). If the diagnosed breast tumours exceeded an average diameter of 1.5 cm, an applied non-linear theoretical-dose-response relationship for second cancer falsely resulted in strong evidence for a linear predicted-dose relationship from the epidemiological study realizations. For a typical distribution of breast cancer sizes, the model selection probability for a resulting predicted-dose linear model was 61% although a non-linear theoretical-dose-response relationship for cancer induction had been applied. The results of this study, therefore, provide evidence that the shapes of epidemiologically obtained dose-response relationships for cancer induction can be biased by the finite size of the diagnosed second tumour, even though the epidemiological study was done correctly.

Incidence of malignancies in patients with juvenile idiopathic arthritis: A retrospective single-center cohort study in Germany.

OBJECTIVES: In recent years, concern has been raised about Juvenile Idiopathic Arthritis (JIA) that it could be associated with an increased risk for malignancies. Therefore, the cancer incidence in the JIA patients was evaluated and compared to the cancer incidence in the German population. METHODS: A retrospective single-center hospital-based cohort study was performed using data on the JIA patients treated between 1952 and 2010 at the German Center for Pediatric and Adolescent Rheumatology (GCPAR) (Garmisch-Partenkirchen, Germany). Self-administered standardized questionnaires were sent out in 2012. Standardized incidence ratios (SIRs) and their corresponding 95% confidence intervals (95%CIs) were calculated. RESULTS: The study cohort consisted of 3691 JIA patients, and the response rate was 66%. Patients age ranged from 3 to 73 years of which 64% were female. Total follow-up time was 60,075 person-years; a history of malignancy was reported by 47 patients. Most common types of cancer were melanoma (n = 11), cervical cancer (n = 8) and breast cancer (n = 7). The overall SIR for women was 1.19 (95%CI: 0.77; 1.60) and for men was 0.67 (95%CI: 0.27; 1.07). The SIR for melanoma was 3.21 (95%CI: 1.60; 5.73) in women, whereas in men no melanoma cases were observed. CONCLUSION: Although no overall increased cancer risk was found, results suggest that the risk of melanoma might be increased in female JIA patients.

Radiation risk models for all solid cancers other than those types of cancer requiring individual assessments after a nuclear accident.

In the assessment of health risks after nuclear accidents, some health consequences require special attention. For example, in their 2013 report on health risk assessment after the Fukushima nuclear accident, the World Health Organisation (WHO) panel of experts considered risks of breast cancer, thyroid cancer and leukaemia. For these specific cancer types, use was made of already published excess relative risk (ERR) and excess absolute risk (EAR) models for radiation-related cancer incidence fitted to the epidemiological data from the Japanese A-bomb Life Span Study (LSS). However, it was also considered important to assess all other types of solid cancer together and the WHO, in their above-mentioned report, stated "No model to calculate the risk for all other solid cancer excluding breast and thyroid cancer risks is available from the LSS data". Applying the LSS models for all solid cancers along with the models for the specific sites means that some cancers have an overlap in the risk evaluations. Thus, calculating the total solid cancer risk plus the breast cancer risk plus the thyroid cancer risk can overestimate the total risk by several per cent. Therefore, the purpose of this paper was to publish the required models for all other solid cancers, i.e. all solid cancers other than those types of cancer requiring special attention after a nuclear accident. The new models presented here have been fitted to the same LSS data set from which the risks provided by the WHO were derived. Although it is known already that the EAR and ERR effect modifications by sex are statistically significant for the outcome "all solid cancer", it is shown here that sex modification is not statistically significant for the outcome "all solid cancer other than thyroid and breast cancer". It is also shown here that the sex-averaged solid cancer risks with and without the sex modification are very similar once breast and thyroid cancers are factored out. Some other notable model differences between those already published for all solid cancers and those presented here for all other solid cancers are also given here. The models presented here can be used to improve on the methodology adopted by WHO after Fukushima and could contribute to emergency preparedness for future nuclear accidents.

The influence of follow-up on DS02 low-dose ranges with a significant excess relative risk of all solid cancer in the Japanese A-bomb survivors.

Determinations of the lowest colon dose, D min, below which there is a statistically significant excess relative risk of all solid cancer, when analyses are restricted to the range [0, D min], are of current interest in research related to radiation protection and risk assessment. In reviewing recent cancer mortality reports on the Life Span Study (LSS) of Japanese A-bomb survivors, reported D min values were found to vary between different reports. The report 12 (follow-up: 1950-1990) found a D min of 50 mGy, but the most recent report 14 (follow-up: 1950-2003) found a D min of 200 mGy. There were small dosimetry changes between report 12, which used DS86, and report 14, which used DS02, but these changes are unlikely to account for a difference in D min of a factor of 4. This short communication examines the reasons for this difference in D min by presenting further investigations into D min using different trial values for D min and various follow-up time spans, all with the same DS02 dosimetry. Magnitudes of the low-dose risks in different dose ranges are also presented. It is shown here that the main influence on D min comes from the length of follow-up and a D min of 50 mGy may also be obtained with the most recent LSS mortality data and DS02, if a restricted follow-up is analyzed. A systematic trend was evident of lower D min values for earlier mortality follow-up periods, consistent with information from earlier LSS reports. Although it may seem surprising that the D min increases with longer follow-up and better statistics, this systematic trend appears to be a consequence of decreasing mortality risks with longer follow-up, even though the error bars on the risks are getting smaller with increasing follow-up. These systematic trends also persisted after accounting for differences between baseline cancer rates for two groups of survivors who were either proximal or distal to the A-bomb hypocenter. Similar systematic trends, although much less pronounced, were also found in the LSS cancer incidence data. Some evidence is provided here that results on low-dose radiation risks from earlier follow-up periods should not be ignored by radiation protection authorities, once the results from the new extended follow-ups are published. This is because of the possibility that the new data for extended follow-up beyond a certain calendar time, which pertain to very long times since exposure, may be contributing to an overall reduction in radiation related risks per unit dose compared to analogous risks determined from earlier follow-up periods, because of the risk effect modification of time since exposure.

Pharmacist-led educational and error notification interventions on prescribing errors in family medicine clinic.

OBJECTIVES: To determine the rate of prescribing errors in a family medicine clinic and the subsequent impact of pharmacist-led educational and error notification interventions on prescribing errors. DESIGN: Single site, pre-post study design. SETTING: An outpatient academic family medicine clinic serving pediatric and adult populations in Oklahoma from March 1, 2011, through April 30, 2012. PARTICIPANTS: 24 resident physicians who prescribed medications during routine outpatient visits. INTERVENTION: A prescribing educational program, audit and feedback methods, and weekly newsletter. MAIN OUTCOMES MEASURE: Percentage of prescription errors and physician error rate before and after intervention among pediatric and adult populations. RESULTS: During the two assessment periods, 24 resident physicians wrote 2,753 prescriptions for 394 pediatric and 899 adult patients. The overall percentage of prescription errors decreased from 18.6% during March 2011 to 14.5% during April 2012 (P = 0.004). Errors were more commonly seen with prescriptions written for pediatric patients (24.9%) than for adult patients (13.9%) (P = 0.001). Individual physician error rates ranged from 5% to 36% (mean ± SD 16.5% ± 8.1). Physicians committed significantly fewer prescribing errors during the postintervention assessment period (14.9%) than during the preintervention assessment period (20.9%) (P = 0.002). Controlling for time, pediatric prescription error rates among physicians who participated in the educational intervention were 36% lower than the error rates among physicians who did not participate (rate ratio 0.64 [95% CI 0.45, 0.91], P = 0.01). CONCLUSION: The pharmacist-led educational program was effective in reducing pediatric prescribing errors among resident physicians in a family medicine clinic.

Application of multi-method-multi-model inference to radiation related solid cancer excess risks models for astronaut risk assessment.

The impact of including model-averaged excess radiation risks (ER) into a measure of radiation attributed decrease of survival (RADS) for the outcome all solid cancer incidence and the impact on the uncertainties is demonstrated. It is shown that RADS applying weighted model averaged ER based on AIC weights result in smaller risk estimates with narrower 95% CI than RADS using ER based on BIC weights. Further a multi-method-multi-model inference approach is introduced that allows calculating one general RADS estimate providing a weighted average risk estimate for a lunar and a Mars mission. For males the general RADS estimate is found to be 0.42% (95% CI: 0.38%; 0.45%) and for females 0.67% (95% CI: 0.59%; 0.75%) for a lunar mission and 2.45% (95% CI: 2.23%; 2.67%) for males and 3.91% (95% CI: 3.44%; 4.39%) for females for a Mars mission considering an age at exposure of 40 years and an attained age of 65 years. It is recommended to include these types of uncertainties and to include model-averaged excess risks in astronaut risk assessment.

Assessing the impact of neutron relative biological effectiveness on all solid cancer mortality risks in the Japanese atomic bomb survivors.

PURPOSE: Risk analyses, based on relative biological effectiveness (RBE) estimates for neutrons relative to gammas, were performed; and the change in the curvature of the risk to dose response with increasing neutron RBE was analyzed using all solid cancer mortality data from the Radiation Effect Research Foundation (RERF). Results were compared to those based on incidence data. MATERIALS AND METHODS: This analysis is based on RERF mortality data with separate neutron and gamma doses for colon doses, from which organ averaged doses could be calculated. A model for risk ratio variation with RBE was developed. RESULTS: The best estimate of the neutron RBE considering mortality data was 200 (95% confidence interval (CI): 50-1010) for colon dose using the weighted-dose approach and for organ averaged dose 110 (95% CI: 30-350). The ERR risk ratios for all solid cancers combined, for the best fitting neutron RBE estimate and the neutron RBE of 10 result in a ratio of 0.54 (95% CI: 0.17-0.85) for colon dose and 0.55 (95% CI: 0.18-0.87) for organ averaged dose. The risk to dose response curvature became significantly negative (concave down) with increasing RBE, at a neutron RBE of 170 using colon dose and at an RBE of 90 using organ averaged dose for males when fitting a linear-quadratic dose response. For females, the curvature decreased toward linearity with increasing neutron RBE and remained significantly positive until RBE of 80 and 40 using colon and organ averaged dose, respectively. For higher neutron RBEs, no significant conclusion could be drawn about the shape of the dose-response curve. CONCLUSIONS: Application of neutron RBE values higher than 10 results in substantially reduced cancer mortality risk estimates and a significant reduction in curvature of the risk to dose responses for males. Using mortality data, the best fitting neutron RBE is much higher than when incidence data is used. The neutron RBE ranges covered by the overlap in the CIs from both the mortality and incidence analyses are 50-190 using colon dose and in all cases, the best fitting neutron RBE and lower 95% CI are higher than the value of 10 traditionally applied by the RERF. Therefore, it is recommended to consider uncertainties in neutron RBE values when calculating radiation risks and discussing the shape of dose responses using Japanese A-bomb survivors data.

European astronaut radiation related cancer risk assessment using dosimetric calculations of organ dose equivalents.

An illustrative sample mission of a Mars swing-by mission lasting one calendar year was chosen to highlight the application of European risk assessment software to cancer (all solid cancer plus leukaemia) risks from radiation exposures in space quantified with organ dose equivalent rates from model calculations based on the quantity Radiation Attributed Decrease of Survival (RADS). The relevant dose equivalent to the colon for radiation exposures from this Mars swing-by mission were found to vary between 198 and 482 mSv. These doses depend on sex and the two other factors investigated here of: solar activity phase (maximum or minimum); and the choice of space radiation quality factor used in the calculations of dose equivalent. Such doses received at typical astronaut ages around 40 years old will result in: the probability of surviving until retirement age (65 years) being reduced by a range from 0.38% (95%CI: 0.29; 0.49) to 1.29% (95%CI: 1.06; 1.56); and the probability of surviving cancer free until retirement age being reduced by a range from 0.78% (95%CI: 0.59; 0.99) to 2.63% (95%CI: 2.16; 3.18). As expected from the features of the models applied to quantify the general dosimetric and radiation epidemiology parameters, the cancer incidence risks in terms of surviving cancer free, are higher than the cancer mortality risks in terms of surviving, the risks for females are higher than for males, and the risks at solar minimum are higher than at solar maximum.

Moon, Mars and Minds: Evaluating Parkinson's disease mortality among U.S. radiation workers and veterans in the million person study of low-dose effects.

BACKGROUND: Radiation is one of the most important stressors related to missions in space beyond Earth's orbit. Epidemiologic studies of exposed workers have reported elevated rates of Parkinson's disease. The importance of cognitive dysfunction related to low-dose rate radiation in humans is not defined. A meta-analysis was conducted of six cohorts in the Million Person Study (MPS) of low-dose health effects to learn whether there is consistent evidence that Parkinson's disease is associated with radiation dose to brain. MATERIALS AND METHODS: The MPS evaluates all causes of death among U.S. radiation workers and veterans, including Parkinson's disease. Systematic and consistent methods are applied to study all categories of workers including medical radiation workers, industrial radiographers, nuclear power plant workers, atomic veterans, and Manhattan Projects workers at the Los Alamos National Laboratory and at Rocky Flats. Consistent methods for all cohorts are used to estimate organ-specific doses and to obtain vital status and cause of death. RESULTS: The meta-analysis include 6 cohorts within the MPS, consisting of 517,608 workers and 17,219,001 person-years of observation. The mean dose to brain ranged from 6.9 to 47.6 mGy and the maximum dose from 0.76 to 2.7 Gy. Five of the 6 cohorts revealed positive associations with Parkinson's disease. The overall summary estimate from the meta-analysis was statistically significant based on 1573 deaths due to Parkinson's disease. The summary excess relative risk at 100 mGy was 0.17 (95% CI: 0.05; 0.29). CONCLUSIONS: Parkinson's disease was positively associated with radiation in the MPS cohorts indicating the need for careful evaluation as to causality in other studies, delineation of possible mechanisms, and assessing possible implications for space travel as well as radiation protection guidance for terrestrial workers.

Neutron relative biological effectiveness for solid cancer incidence in the Japanese A-bomb survivors: an analysis considering the degree of independent effects from γ-ray and neutron absorbed doses with hierarchical partitioning.

It has generally been assumed that the neutron and γ-ray absorbed doses in the data from the life span study (LSS) of the Japanese A-bomb survivors are too highly correlated for an independent separation of the all solid cancer risks due to neutrons and due to γ-rays. However, with the release of the most recent data for all solid cancer incidence and the increased statistical power over previous datasets, it is instructive to consider alternatives to the usual approaches. Simple excess relative risk (ERR) models for radiation-induced solid cancer incidence fitted to the LSS epidemiological data have been applied with neutron and γ-ray absorbed doses as separate explanatory covariables. A simple evaluation of the degree of independent effects from γ-ray and neutron absorbed doses on the all solid cancer risk with the hierarchical partitioning (HP) technique is presented here. The degree of multi-collinearity between the γ-ray and neutron absorbed doses has also been considered. The results show that, whereas the partial correlation between the neutron and γ-ray colon absorbed doses may be considered to be high at 0.74, this value is just below the level beyond which remedial action, such as adding the doses together, is usually recommended. The resulting variance inflation factor is 2.2. Applying HP indicates that just under half of the drop in deviance resulting from adding the γ-ray and neutron absorbed doses to the baseline risk model comes from the joint effects of the neutrons and γ-rays-leaving a substantial proportion of this deviance drop accounted for by individual effects of the neutrons and γ-rays. The average ERR/Gy γ-ray absorbed dose and the ERR/Gy neutron absorbed dose that have been obtained here directly for the first time, agree well with previous indirect estimates. The average relative biological effectiveness (RBE) of neutrons relative to γ-rays, calculated directly from fit parameters to the all solid cancer ERR model with both colon absorbed dose covariables, is 65 (95 %CI: 11; 170). Therefore, although the 95 % CI is quite wide, reference to the colon doses with a neutron weighting of 10 may not be optimal as the basis for the determination of all solid cancer risks. Further investigations into the neutron RBE are required, ideally based on the LSS data with organ-specific neutron and γ-ray absorbed doses for all organs rather than the RBE weighted absorbed doses currently provided. The HP method is also suggested for use in other epidemiological cohort analyses that involve correlated explanatory covariables.

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.

Radiation-related risks of cancer can be transported from one population to another population at risk, for the purpose of calculating lifetime risks from radiation exposure. Transfer via excess relative risks (ERR) or excess absolute risks (EAR) or a mixture of both (i.e., from the life span study (LSS) of Japanese atomic bomb survivors) has been done in the past based on qualitative weighting. Consequently, the values of the weights applied and the method of application of the weights (i.e., as additive or geometric weighted means) have varied both between reports produced at different times by the same regulatory body and also between reports produced at similar times by different regulatory bodies. Since the gender and age patterns are often markedly different between EAR and ERR models, it is useful to have an evidence-based method for determining the relative goodness of fit of such models to the data. This paper identifies a method, using Akaike model weights, which could aid expert judgment and be applied to help to achieve consistency of approach and quantitative evidence-based results in future health risk assessments. The results of applying this method to recent LSS cancer incidence models are that the relative EAR weighting by cancer solid cancer site, on a scale of 0-1, is zero for breast and colon, 0.02 for all solid, 0.03 for lung, 0.08 for liver, 0.15 for thyroid, 0.18 for bladder and 0.93 for stomach. The EAR weighting for female breast cancer increases from 0 to 0.3, if a generally observed change in the trend between female age-specific breast cancer incidence rates and attained age, associated with menopause, is accounted for in the EAR model. Application of this method to preferred models from a study of multi-model inference from many models fitted to the LSS leukemia mortality data, results in an EAR weighting of 0. From these results it can be seen that lifetime risk transfer is most highly weighted by EAR only for stomach cancer. However, the generalization and interpretation of radiation effect estimates based on the LSS cancer data, when projected to other populations, are particularly uncertain if considerable differences exist between site-specific baseline rates in the LSS and the other populations of interest. Definitive conclusions, regarding the appropriate method for transporting cancer risks, are limited by a lack of knowledge in several areas including unknown factors and uncertainties in biological mechanisms and genetic and environmental risk factors for carcinogenesis; uncertainties in radiation dosimetry; and insufficient statistical power and/or incomplete follow-up in data from radio-epidemiological studies.