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Background: Acute lymphocytic leukaemia (ALL) and non-Hodgkin lymphoma (NHL) are among the commonest types of childhood cancer. Some previous studies suggested that elevated ultraviolet radiation (UVR) exposures increase ALL risk; many more indicate NHL risk is reduced. Methods: We assessed age<20 ALL/NHL incidence in Surveillance, Epidemiology and End Results data using AVGLO-derived UVR irradiance/cumulative radiant exposure measures, using quasi-likelihood models accounting for underdispersion, adjusted for age, sex, racial/ethnic group and other county-level socioeconomic variables. Results: There were 30,349 cases of ALL and 8062 of NHL, with significant increasing trends of ALL with UVR irradiance (relative risk (RR) = 1.200/mW/cm2 (95% CI 1.060, 1.359, p = 0.0040)), but significant decreasing trends for NHL (RR = 0.646/mW/cm2 (95% CI 0.512, 0.816, p = 0.0002)). There was a borderline-significant increasing trend of ALL with UVR cumulative radiant exposure (RR = 1.444/MJ/cm2 (95% CI 0.949, 2.197, p = 0.0865)), and significant decreasing trends for NHL (RR = 0.284/MJ/cm2 (95% CI 0.166, 0.485, p < 0.0001)). ALL and NHL trend RR is substantially increased among those aged 0–3. All-age trend RRs are most extreme (increasing for ALL, decreasing for NHL) for Hispanics for both UVR measures. Conclusions: Our more novel finding, of excess UVR-related ALL risk, is consistent with some previous studies, but is not clear-cut, and in need of replication. [ABSTRACT FROM AUTHOR]

Background: In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data. Methods: We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability. Results: There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability. Conclusions: Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques. [ABSTRACT FROM AUTHOR]

Background: Many high-dose groups demonstrate increased leukaemia risks, with risk greatest following childhood exposure; risks at low/moderate doses are less clear. Methods: We conducted a pooled analysis of the major radiation-associated leukaemias (acute myeloid leukaemia (AML) with/without the inclusion of myelodysplastic syndrome (MDS), chronic myeloid leukaemia (CML), acute lymphoblastic leukaemia (ALL)) in ten childhood-exposed groups, including Japanese atomic bomb survivors, four therapeutically irradiated and five diagnostically exposed cohorts, a mixture of incidence and mortality data. Relative/absolute risk Poisson regression models were fitted. Results: Of 365 cases/deaths of leukaemias excluding chronic lymphocytic leukaemia, there were 272 AML/CML/ALL among 310,905 persons (7,641,362 person-years), with mean active bone marrow (ABM) dose of 0.11 Gy (range 0–5.95). We estimated significant (P < 0.005) linear excess relative risks/Gy (ERR/Gy) for: AML (n = 140) = 1.48 (95% CI 0.59–2.85), CML (n = 61) = 1.77 (95% CI 0.38–4.50), and ALL (n = 71) = 6.65 (95% CI 2.79–14.83). There is upward curvature in the dose response for ALL and AML over the full dose range, although at lower doses (<0.5 Gy) curvature for ALL is downwards. Discussion: We found increased ERR/Gy for all major types of radiation-associated leukaemia after childhood exposure to ABM doses that were predominantly (for 99%) <1 Gy, and consistent with our prior analysis focusing on <100 mGy. [ABSTRACT FROM AUTHOR]

There is direct evidence of risks at moderate and high levels of radiation dose for highly radiogenic cancers such as leukaemia and thyroid cancer. For many cancer sites, however, it is necessary to assess risks via extrapolation from groups exposed at moderate and high levels of dose, about which there are substantial uncertainties. Crucial to the resolution of this area of uncertainty is the modelling of the dose–response relationship and the importance of both systematic and random dosimetric errors for analyses in the various exposed groups. It is well recognised that measurement error can alter substantially the shape of this relationship and hence the derived population risk estimates. Particular attention has been devoted to the issue of shared errors, common in many datasets, and particularly important in occupational settings. We propose a modification of the regression calibration method which is particularly suited to studies in which there is a substantial amount of shared error, and in which there may also be curvature in the true dose response. This method can be used in settings where there is a mixture of Berkson and classical error. In fits to synthetic datasets in which there is substantial upward curvature in the true dose response, and varying (and sometimes substantial) amounts of classical and Berkson error, we show that the coverage probabilities of all methods for the linear coefficient α are near the desired level, irrespective of the magnitudes of assumed Berkson and classical error, whether shared or unshared. However, the coverage probabilities for the quadratic coefficient β are generally too low for the unadjusted and regression calibration methods, particularly for larger magnitudes of the Berkson error, whether this is shared or unshared. In contrast Monte Carlo maximum likelihood yields coverage probabilities for β that are uniformly too high. The extended regression calibration method yields coverage probabilities that are too low when shared and unshared Berkson errors are both large, although otherwise it performs well, and coverage is generally better than these other three methods. A notable feature is that for all methods apart from extended regression calibration the estimates of the quadratic coefficient β are substantially upwardly biased. [ABSTRACT FROM AUTHOR]

The radiation-related risk of breast cancer among women following the Chornobyl accident remains uncertain. During pregnancy, there is rapid cell proliferation in the breast while radioactive iodine from fallout exposure can concentrate in lactating breast tissues. We conducted a standardized incidence ratio (SIR) analysis of breast cancer in a cohort of 2,631 women who were lactating and/or pregnant at any time during the 2-month period of radioiodine fallout (April 26, 1986–June 30, 1986). There were 37,151 person-years of follow-up, and 26 incident breast cancers were identified through linkage with the National Cancer Registry of Ukraine. Breast cancer rates among pregnant or lactating women were compared to the general population rates, and SIRs were adjusted for oblast, urban/rural, age, and calendar year. The SIR was not significant for women pregnant at the time of the accident (SIR = 0.75; 95% CI 0.44, 1.18) or for women lactating anytime within 2 months of the accident (SIR = 0.96; 95% CI 0.48, 1.68). However, there was a non-significantly elevated risk for women lactating at the time of accident (SIR = 1.30, 95% CI 0.40, 3.01). The increased SIR for breast cancer among lactating women is consistent with the results of a similar study in Belarus and indicates the need to quantify the radiation risk of breast cancer in a larger study of women lactating during the period of fallout exposure. [ABSTRACT FROM AUTHOR]

Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independent variables. There are relatively few adjustable hyperparameters in the standard random forest models, among them the minimum size of the terminal nodes on each tree. The usual stopping rule, as proposed by Breiman, stops tree expansion by limiting the size of the parent nodes, so that a node cannot be split if it has less than a specified number of observations. Recently an alternative stopping criterion has been proposed, stopping tree expansion so that all terminal nodes have at least a minimum number of observations. The present paper proposes three generalisations of this idea, limiting the growth in regression random forests, based on the variance, range, or inter-centile range. The new approaches are applied to diabetes data obtained from the National Health and Nutrition Examination Survey and four other datasets (Tasmanian Abalone data, Boston Housing crime rate data, Los Angeles ozone concentration data, MIT servo data). Empirical analysis presented herein demonstrate that the new stopping rules yield competitive mean square prediction error to standard random forest models. In general, use of the intercentile range statistic to control tree expansion yields much less variation in mean square prediction error, and mean square prediction error is also closer to the optimal. The Fortran code developed is provided in the Supplementary Material. [ABSTRACT FROM AUTHOR]

A large excess risk of thyroid cancer was observed among Belarusian/Russian/Baltic Chornobyl cleanup workers. A more recent study of Ukraine cleanup workers found more modest excess risks of thyroid cancer. Dose errors in this data are substantial, associated with model uncertainties and questionnaire response. Regression calibration is often used for dose-error adjustment, but may not adequately account for the full error distribution. We aimed to examine the impact of exposure-assessment uncertainties on thyroid cancer among Ukrainian cleanup workers using Monte Carlo maximum likelihood, and compare with results derived using regression calibration. Analyses assessed the sensitivity of results to various components of internal and external dose. Regression calibration yielded an excess odds ratio per Gy (EOR/Gy) of 0.437 (95% CI − 0.042, 1.577, p = 0.100), compared with the EOR/Gy using Monte Carlo maximum likelihood of 0.517 (95% CI − 0.039, 2.035, p = 0.093). Trend risk estimates for follicular morphology tumors exhibited much more extreme effects of full-likelihood adjustment, the EOR/Gy using regression calibration of 3.224 (95% CI − 0.082, 30.615, p = 0.068) becoming ~ 50% larger, 4.708 (95% CI − 0.075, 85.143, p = 0.066) when using Monte Carlo maximum likelihood. Results were sensitive to omission of external components of dose. In summary, use of Monte Carlo maximum likelihood adjustment for dose error led to increases in trend risks, particularly for follicular morphology thyroid cancers, where risks increased by ~ 50%, and were borderline significant. The unexpected finding for follicular tumors needs to be replicated in other exposed groups. [ABSTRACT FROM AUTHOR]

Although much is known about the radiation-related risk of thyroid cancer in those exposed at young ages, less is known about the risk due to adult exposure, particularly in men. We aimed to examine the association between thyroid radiation dose received during adulthood and thyroid cancer risk in men. We conducted a nested case–control study (149 cases; 458 controls) of male, Ukrainian cleanup workers who first worked in the Chornobyl zone between ages 18 and 59 years, with cases identified through linkage with the National Cancer Registry of Ukraine from 1988 to 2012. Individual thyroid doses due to external and internal exposure during the cleanup mission and during residence in contaminated settlements were estimated (total dose mean 199 mGy; range 0.15 mGy to 9.0 Gy). The excess odds ratio per gray (EOR/Gy) for overall thyroid cancer was 0.40 (95% CI: − 0.05, 1.48; p-value = 0.118). Time since exposure was borderline significant (p-value = 0.061) in modifying this association so that less time since exposure was associated with a stronger EOR/Gy. An elevated, but nonsignificant association was observed for follicular thyroid cancer (EOR/Gy = 1.72; 95% CI: − 0.25, 13.69; p-value = 0.155) based on a small number of cases (n = 24). Our findings for radiation-related overall thyroid cancer risk are consistent with evidence of increased risks observed in most of the other studies of adult exposure, though the magnitude of the effect in this study is lower than in the previous case–control study of Chornobyl cleanup workers. [ABSTRACT FROM AUTHOR]

Epidemiological studies of cancer rates associated with external and internal exposure to ionizing radiation have been subject to extensive reviews by various scientific bodies. It has long been assumed that radiation-induced cancer risks at low doses or low-dose rates are lower (per unit dose) than those at higher doses and dose rates. Based on a mixture of experimental and epidemiologic evidence the International Commission on Radiological Protection recommended the use of a dose and dose-rate effectiveness factor for purposes of radiological protection to reduce solid cancer risks obtained from moderate-to-high acute dose studies (e.g. those derived from the Japanese atomic bomb survivors) when applied to low dose or low-dose rate exposures. In the last few years there have been a number of attempts at assessing the effect of extrapolation of dose rate via direct comparison of observed risks in low-dose rate occupational studies and appropriately age/sex-adjusted analyses of the Japanese atomic bomb survivors. The usual approach is to consider the ratio of the excess relative risks in the two studies, a measure of the inverse of the dose rate effectiveness factor. This can be estimated using standard meta-analysis with inverse weighting of ratios of relative risks using variances derived via the delta method. In this paper certain potential statistical problems in the ratio of estimated excess relative risks for low-dose rate studies to the excess relative risk in the Japanese atomic bomb survivors are discussed, specifically the absence of a well-defined mean and the theoretically unbounded variance of this ratio. A slightly different method of meta-analysis for estimating uncertainties of these ratios is proposed, motivated by Fieller's theorem, which leads to slightly different central estimates and confidence intervals for the dose rate effectiveness factor. However, given the uncertainties in the data, the differences in mean values and uncertainties from the dose rate effectiveness factor estimated using delta-method-based meta-analysis are not substantial, generally less than 70%. [ABSTRACT FROM AUTHOR]

A meta-analytic summary effect estimate often is calculated as an inverse-variance-weighted average of study-specific estimates of association. The variances of published estimates of association often are derived from their associated confidence intervals under assumptions typical of Wald-type statistics, such as normality of the parameter. However, in some research areas, such as radiation epidemiology, epidemiological results typically are obtained by fitting linear relative risk models, and associated likelihood-based confidence intervals are often asymmetric; consequently, reasonable estimates of variances associated with study-specific estimates of association may be difficult to infer from the standard approach based on the assumption of a Wald-type interval. Here, a novel method is described for meta-analysis of published results from linear relative risk models that uses a parametric transformation of published results to improve on the normal approximation used to assess confidence intervals. Using simulations, it is illustrated that the meta-analytic summary obtained using the proposed approach yields less biased summary estimates, with better confidence interval coverage, than the summary obtained using the more classical approach to meta-analysis. The proposed approach is illustrated using a previously published example of meta-analysis of epidemiological findings regarding circulatory disease following exposure to low-level ionizing radiation. [ABSTRACT FROM AUTHOR]

An intense scientific debate has recently taken place relating to the "bad luck" hypothesis in cancer development, namely that intrinsic random, and therefore unavoidable, mutagenic events would have a predominant role in tumorigenesis. In this article we review the main contributions to this debate and explain the reasons why the claim that cancer is mostly explained by intrinsic random factors is unsupported by data and theoretical models. In support of this, we present an analysis showing that smoking-induced mutations are more predictive of cancer risk than the lifetime number of stem cell cellular divisions. [ABSTRACT FROM AUTHOR]

It has long been known that relatively high-dose ionising radiation exposure (> 1 Gy) can induce cataract, but there has been no evidence that this occurs at low doses (< 100 mGy). To assess low-dose risk, participants from the US Radiologic Technologists Study, a large, prospective cohort, were followed from date of mailed questionnaire survey completed during 1994-1998 to the earliest of self-reported diagnosis of cataract/cataract surgery, cancer other than non-melanoma skin, or date of last survey (up to end 2014). Cox proportional hazards models with age as timescale were used, adjusted for a priori selected cataract risk factors (diabetes, body mass index, smoking history, race, sex, birth year, cumulative UVB radiant exposure). 12,336 out of 67,246 eligible technologists reported a history of diagnosis of cataract during 832,479 person years of follow-up, and 5509 from 67,709 eligible technologists reported undergoing cataract surgery with 888,420 person years of follow-up. The mean cumulative estimated 5-year lagged eye-lens absorbed dose from occupational radiation exposures was 55.7 mGy (interquartile range 23.6-69.0 mGy). Five-year lagged occupational radiation exposure was strongly associated with self-reported cataract, with an excess hazard ratio/mGy of 0.69 × 10−3 (95% CI 0.27 × 10−3 to 1.16 × 10−3, p < 0.001). Cataract risk remained statistically significant (p = 0.030) when analysis was restricted to < 100 mGy cumulative occupational radiation exposure to the eye lens. A non-significantly increased excess hazard ratio/mGy of 0.34 × 10−3 (95% CI − 0.19 × 10−3 to 0.97 × 10−3, p = 0.221) was observed for cataract surgery. Our results suggest that there is excess risk for cataract associated with radiation exposure from low-dose and low dose-rate occupational exposures. [ABSTRACT FROM AUTHOR]

Background:Some highly penetrant familial cancer syndromes exhibit elevated leukaemia risk, and there is evidence for familial clustering of lung cancer and other common cancers. Lung cancer and leukaemia are strongly radiogenic, but there are few indications that high-energy beam irradiation is markedly more effective than lower-energy radiation.Methods:We used a Cox model with familially structured random effects to assess 16 mortality end points in a group of 1850 mice in 47 families maintained in a circular-breeding scheme, exposed to accelerated Si or Fe ions (0.4 Gy) or 137Cs gamma rays (3 Gy).Results:There is periodicity in the effect of familial relatedness, which is most pronounced for pulmonary adenoma, Harderian-gland adenoma, Harderian-gland tumour, ectodermal tumour, pulmonary adenocarcinoma and hepatocellular carcinoma (P=0.0001/0.0003/0.0017/0.0035/0.0257/0.0340, respectively) with families that are 3-4 generations apart most strongly correlated; myeloid leukaemia also exhibited a striking periodic correlation structure. The relative risks of high-energy Si or Fe ions are not significantly different and are less than for 137Cs gamma-rays for most end points at the doses used.Conclusions:There is periodicity in the effect of familial relatedness for various cancer sites. The effects per unit dose of high-energy charged particle beams are no higher than ninefold those of lower-energy gamma radiation. [ABSTRACT FROM AUTHOR]

Background: We previously reported evidence of a dose-response relationship between ionising-radiation exposure from paediatric computed tomography (CT) scans and the risk of leukaemia and brain tumours in a large UK cohort. Underlying unreported conditions could have introduced bias into these findings.Methods: We collected and reviewed additional clinical information from radiology information systems (RIS) databases, underlying cause of death and pathology reports. We conducted sensitivity analyses excluding participants with cancer-predisposing conditions or previous unreported cancers and compared the dose-response analyses with our original results.Results: We obtained information from the RIS and death certificates for about 40% of the cohort (n∼180 000) and found cancer-predisposing conditions in 4 out of 74 leukaemia/myelodysplastic syndrome (MDS) cases and 13 out of 135 brain tumour cases. As these conditions were unrelated to CT exposure, exclusion of these participants did not alter the dose-response relationships. We found evidence of previous unreported cancers in 2 leukaemia/MDS cases, 7 brain tumour cases and 232 in non-cases. These previous cancers were related to increased number of CTs. Exclusion of these cancers reduced the excess relative risk per mGy by 15% from 0.036 to 0.033 for leukaemia/MDS (P-trend=0.02) and by 30% from 0.023 to 0.016 (P-trend<0.0001) for brain tumours. When we included pathology reports we had additional clinical information for 90% of the cases. Additional exclusions from these reports further reduced the risk estimates, but this sensitivity analysis may have underestimated risks as reports were only available for cases.Conclusions: Although there was evidence of some bias in our original risk estimates, re-analysis of the cohort with additional clinical data still showed an increased cancer risk after low-dose radiation exposure from CT scans in young patients. [ABSTRACT FROM AUTHOR]

Background: There are limited data on the histopathology of papillary thyroid carcinomas (PTCs) diagnosed in irradiated populations. We evaluated the associations between iodine-131 dose and the histopathological characteristics of post-Chernobyl PTCs, the changes in these characteristics over time, and their associations with selected somatic mutations. Methods: This study included 115 PTCs diagnosed in a Ukrainian-American cohort (n=13,243) during prescreening and four successive thyroid screenings. Of these PTCs, 65 were subjected to somatic mutation profiling. All individuals were <18 years at the time of the Chernobyl accident and had direct thyroid radioactivity measurements. Statistical analyses included multivariate linear and logistic regression. Results: We identified a borderline significant linear-quadratic association (P=0.063) between iodine-131 dose and overall tumour invasiveness (presence of extrathyroidal extension, lymphatic/vascular invasion, and regional or distant metastases). Irrespective of dose, tumours with chromosomal rearrangements were more likely to have lymphatic/vascular invasion than tumours without chromosomal rearrangements (P=0.020) or tumours with BRAF or RAS point mutations (P=0.008). Controlling for age, there were significant time trends in decreasing tumour size (P<0.001), the extent of lymphatic/vascular invasion (P=0.005), and overall invasiveness (P=0.026). Conclusions: We determined that the invasive properties of PTCs that develop in iodine-131-exposed children may be associated with radiation dose. In addition, based on a subset of cases, tumours with chromosomal rearrangements appear to have a more invasive phenotype. The increase in small, less invasive PTCs over time is a consequence of repeated screening examinations. [ABSTRACT FROM AUTHOR]

We agree with Walsh et al. that in practice the delta-method approach and the method we advocated, based on Fieller's theorem (Fieller [4], [5]), yield results that are reasonably close. [Extracted from the article]

Radiation-induced human papillary thyroid cancer (PTC) is associated with chromosomal inversions that involve the genetic loci H4 and RET on chromosome 10. Recently, experimental data has shown that these loci lie in very close spatial proximity in a high proportion of adult human thyroid cells. Applying the generalized formulation of dual radiation action to this H4-to- RET geometric distance data, we predict here the radiation dose-response of H4- RET induction. The predicted H4- RET dose-response has a linear-to-quadratic transition dose of ∼7 Gy, suggesting the validity of linear risk extrapolations to very low doses for H4- RET mediated radiation-induced PTC. In conjunction with A-bomb survivor data, the predicted H4- RET dose- response yields estimates of the number of PTC target cells that are of the order of ∼106 to ∼107 cells, i.e. considerably less than the total number of follicular cells in the thyroid gland. [ABSTRACT FROM AUTHOR]

Chronic inflammation underlies many autoimmune diseases, including hypothyroidism, hyperthyroidism, and rheumatoid arthritis, also type-2 diabetes and osteoarthritis. Associations have been suggested of high-dose ionising radiation exposure with type-2 diabetes and elevated levels of C-reactive protein, a marker of chronic inflammation. In this analysis we used a proportional hazards model to assess effects of radiotherapy on risks of subsequent inflammatory disease morbidity in 110,368 US radiologic technologists followed from a baseline survey (1983-1989/1994-1998) through 2008. We used a linear model to assess log-transformed C-reactive protein concentration following radiotherapy in 1326 technologists. Relative risk of diabetes increased following radiotherapy (p < 0.001), and there was a borderline significant increasing trend per treatment (p = 0.092). For osteoarthritis there was increased relative risk associated with prior radiotherapy on all questionnaires (p = 0.005), and a significant increasing trend per previous treatment (p = 0.024). No consistent increases were observed for other types of inflammatory disease (hypothyroidism, hyperthyroidism, rheumatoid arthritis) associated with radiotherapy. There was a borderline significant (p = 0.059) increasing trend with dose for C-reactive protein with numbers of prior radiotherapy treatments. Our results suggest that radiotherapy is associated with subsequent increased risk of certain inflammatory conditions, which is reinforced by our finding of elevated levels of C-reactive protein. [ABSTRACT FROM AUTHOR]

High-dose ionising radiation is associated with circulatory disease. Risks associated with lower-dose (<0.5 Gy) exposures remain unclear, with little information on risk modification by age at exposure, years since exposure or dose-rate. Tuberculosis patients in Canada and Massachusetts received multiple diagnostic x-ray fluoroscopic exposures, over a wide range of ages, many at doses <0.5 Gy. We evaluated risks of circulatory-disease mortality associated with <0.5 Gy radiation exposure in a pooled cohort of 63,707 patients in Canada and 13,568 patients in Massachusetts. Under 0.5 Gy there are increasing trends for all circulatory disease (n = 10,209; excess relative risk/Gy = 0.246; 95% CI 0.036, 0.469; p = 0.021) and for ischaemic heart disease (n = 6410; excess relative risk/Gy = 0.267; 95% CI 0.003, 0.552; p = 0.048). All circulatory-disease and ischaemic-heart-disease risk reduces with increasing time since exposure (p < 0.005). Over the entire dose range, there are negative mortality dose trends for all circulatory disease (p = 0.014) and ischaemic heart disease (p = 0.003), possibly due to competing causes of death over this dose interval.These results confirm and extend earlier findings and strengthen the evidence for circulatory-disease mortality radiation risk at doses <0.5 Gy. The limited information on well-known lifestyle/medical risk factors for circulatory disease implies that confounding of the dose trend cannot be entirely excluded. [ABSTRACT FROM AUTHOR]

The atomic bomb, dropped on August 6, 1945, destroyed Hiroshima, Japan. Survivors of the explosion were exposed to two types of radiation: g-rays and neutrons. There have been several estimates of how much radiation they received, based on interviews with survivors and responses to questionnaires about their location at the time of bombings. The most recent set of estimates, the so-called DS86 dosimetry system, was introduced in 1986. Although low-energy neutron radiation represented only a tiny fraction of the total neutron radiation that survivors received, the discrepancy between DS86 and the low-energy neutron measurements had troubling implications for the dosimetry system as a whole. Previous measurements of high-energy neutrons had been unable to verify the accuracy of DS86 at these distances. Taken together with previous validations of the estimated g-ray doses, and of the Nagasaki neutron doses, it is now clear that the DS86 dose estimates correctly reflect all components of radiation dose in the two cities.