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BackgroundWhile there is a robust literature on environmental exposure to iodine-131 (131I) in childhood and adolescence and the risk of thyroid cancer and benign nodules, little is known about its effects on thyroid volume.MethodsTo assess the effect of 131I dose to the thyroid on the volume of the thyroid gland, we examined the data from the baseline screening of the Belarusian-American Cohort Study of residents of Belarus who were exposed to the Chernobyl fallout at ages ≤18 years. Thyroid dose estimates were based on individual thyroid activity measurements made shortly after the accident and dosimetric data from questionnaires obtained 10-15 years later at baseline screening. During baseline screening, thyroid gland volume was assessed from thyroid ultrasound measurements. The association between radiation dose and thyroid volume was modeled using linear regression where radiation dose was expressed with power terms to address non-linearity. The model was adjusted for attained age, sex, and place of residence, and their modifying effects were examined.ResultsThe analysis was based on 10,703 subjects. We found a statistically significant positive association between radiation dose and thyroid volume (P

There is limited evidence that non-leukaemic lymphoid malignancies are radiogenic. As radiation-related cancer risks are generally higher after childhood exposure, we analysed pooled lymphoid neoplasm data in nine cohorts first exposed to external radiation aged  0.4). In six cohorts with estimates of lymphatic tissue dose, borderline significant increased risks (p-trend = 0.02-0.07) were observed for NHL + CLL, NHL, and CLL. Further pooled epidemiological studies are needed with longer follow-up, central outcome review by expert hematopathologists, and assessment of radiation doses to lymphoid tissues.

Abstract Thyroid enlargement can cause problems with swallowing or breathing and a decrease in accuracy of screening for thyroid cancer. Exposure to radioactive iodines after the 1986 Chernobyl accident is known to increase risk of thyroid cancer in those exposed at a young age, but little is known about its effects on thyroid volume, which could have important clinical implications. The objective of this study is to characterize the dose-response association between iodine-131 (131I) exposure and thyroid volume using data from a Belarusian-American cohort study of residents of Belarus exposed during childhood. Persons exposed to Chernobyl fallout in Belarus at the age of 18 years or younger had individual 131I doses to the thyroid gland estimated from direct thyroid activity measurements, radioecological and biokinetic models, and interview data on whereabouts and dietary habits collected during baseline screening in 1996-2001 (N=11,970; median age 21 years). Thyroid volume was estimated from thyroid ultrasound measurements during screening. Individuals with diagnoses of benign or malignant tumors of thyroid gland, any thyroid surgery or aplasia, and missing thyroid volume measurements were excluded (n=1,104). Dose and thyroid volume were log-transformed due to right-skewed distributions. We used a multivariable linear regression to estimate the dose-response association between 131I dose to the thyroid and thyroid volume accounting for confounding effects of sex, age at screening, and place of residence at the time of screening, a proxy for endemic iodine deficiency. To examine nonlinear effects, we added a quadratic term for the log-transformed dose. Among 10,866 participants, dose to thyroid ranged from 0.0005 to 39 gray (Gy) (median=0.3 Gy). In a linear regression model adjusted for confounders, log thyroid volume was best described by a linear-quadratic function of log dose (p

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.

BackgroundSubstantial evidence links exposure to moderate or high doses of ionising radiation, particularly in childhood, with increased risk of leukaemia. The association of leukaemia with exposure to low-dose (

BACKGROUND:Chronic lymphocytic leukemia (CLL) was the predominant leukemia in a recent study of Chornobyl cleanup workers from Ukraine exposed to radiation (UR-CLL). Radiation risks of CLL significantly increased with increasing bone marrow radiation doses. Current analysis aimed to clarify whether the increased risks were due to radiation or to genetic mutations in the Ukrainian population. METHODS:A detailed characterization of the genomic landscape was performed in a unique sample of 16 UR-CLL patients and age- and sex-matched unexposed general population Ukrainian-CLL (UN-CLL) and Western-CLL (W-CLL) patients (n = 28 and 100, respectively). RESULTS:Mutations in telomere-maintenance pathway genes POT1 and ATM were more frequent in UR-CLL compared to UN-CLL and W-CLL (both p

ContextAlthough radiation exposure is an important predictor of thyroid cancer on diagnosis of a thyroid nodule, the relationship between childhood radiation exposure and thyroid nodules has not been comprehensively evaluated.ObjectiveTo examine the association between internal I-131 thyroid dose and thyroid nodules in young adults exposed during childhood.Design, setting, and participantsIn this cross-sectional study, we screened residents of Belarus aged ≤18 years at the time of the Chernobyl nuclear accident for thyroid disease (median age, 21 years) with thyroid palpation, ultrasonography, blood/urine analysis, and medical follow-up when appropriate. Eligible participants (N = 11,421) had intact thyroid glands and doses based on direct individual thyroid activity measurements.Main outcome measuresExcess odds ratios per Gray (EOR/Gy, scaled at age 5 years at exposure) for any thyroid nodule and for nodules grouped by cytology/histology, diameter size, and singularity.ResultsRisk of any thyroid nodule increased significantly with I-131 dose and, for a given dose, with younger age at exposure. The EOR/Gy (95% confidence intervals) for neoplastic nodules (3.82; 0.87 to 15.52) was significantly higher than for nonneoplastic nodules (0.32;

The recently demonstrated radiation-induction of chronic lymphocytic leukemia (CLL) raises the question as to whether the amount of radiation exposure influences any of the clinical characteristics of the disease. We evaluated the relationship between bone marrow radiation doses and clinical characteristics and survival of 79 CLL cases diagnosed during 1986-2006 in a cohort of 110 645 male workers who participated in the cleanup work of the Chornobyl nuclear accident in Ukraine in 1986. All diagnoses were confirmed by an independent International Hematology Panel. Patients were followed up to the date of death or end of follow-up on 31 October 2010. The median age at diagnosis was 57 years. Median bone marrow dose was 22.6 milligray (mGy) and was not associated with time between exposure and clinical diagnosis of CLL (latent period), age, peripheral blood lymphocyte count or clinical stage of disease in univariate and multivariate analyses. Latent period was significantly shorter among those older at first exposure, smokers and those with higher frequency of visits to the doctor prior to diagnosis. A significant increase in the risk of death with increasing radiation dose was observed (p = 0.03, hazard ratio = 2.38, 95% confidence interval: 1.11,5.08 comparing those with doses ≥22 mGy to doses

BackgroundThere 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.MethodsThis 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

Several studies reported an increased risk of thyroid cancer in children and adolescents exposed to radioactive iodines, chiefly iodine-131 ((131)I), after the 1986 Chornobyl (Ukrainian spelling) nuclear power plant accident. The risk of benign thyroid tumors following such radiation exposure is much less well known. We have previously reported a novel finding of significantly increased risk of thyroid follicular adenoma in a screening study of children and adolescents exposed to the Chornobyl fallout in Ukraine. To verify this finding, we analyzed baseline screening data from a cohort of 11,613 individuals aged ≤18 years at the time of the accident in Belarus (mean age at screening = 21 years). All participants had individual (131)I doses estimated from thyroid radioactivity measurements and were screened according to a standardized protocol. We found a significant linear dose response for 38 pathologically confirmed follicular adenoma cases. The excess odds ratio per gray of 2.22 (95% confidence interval: 0.41, 13.1) was similar in males and females but decreased significantly with increasing age at exposure (P < 0.01), with the highest radiation risks estimated for those exposed at

BackgroundRecent studies of children and adolescents who were exposed to radioactive iodine-131 (I-131) after the 1986 Chernobyl nuclear accident in Ukraine exhibited a significant dose-related increase in the risk of thyroid cancer, but the association of radiation doses with tumor histologic and morphologic features is not clear.MethodsA cohort of 11,664 individuals in Belarus who were aged ≤18 years at the time of the accident underwent 3 cycles of thyroid screening during 1997 to 2008. I-131 thyroid doses were estimated from individual thyroid activity measurements taken within 2 months after the accident and from dosimetric questionnaire data. Demographic, clinical, and tumor pathologic characteristics of the patients with thyroid cancer were analyzed using 1-way analysis of variance, chi-square tests or Fisher exact tests, and logistic regression.ResultsIn total, 158 thyroid cancers were identified as a result of screening. The majority of patients had T1a and T1b tumors (93.7%), with many positive regional lymph nodes (N1; 60.6%) but few distant metastases (M1;

Purpose: The projected existence and magnitude of carcinogenic effects of ionizing radiation at low doses and low-dose rates is perhaps the most important issue in radiation protection today. Studies of childhood cancer and natural background radiation have the potential to throw direct light on this question, into a dose range below a few tens of mSv. This paper describes the studies that have been undertaken and their context, discusses some problems that arise and summarizes the present position. Conclusions: Many such studies have been undertaken, but most were too small to have a realistic chance of detecting the small effects expected from such low doses, based on risk projections from higher exposures. Case--control or cohort studies are to be preferred methodologically to ecological studies but can be prone to problems of registration/participation bias. Interview-based studies of the requisite size would be prohibitively expensive and would undoubtedly also run into problems of participation bias. Register-based studies can be very large and are free of participation bias. However, they need to estimate the radiation exposure of study subjects using models rather than individual measurements in the homes of those concerned. At present, no firm conclusions can be drawn from the studies that have been published to date. Further data and perhaps pooled studies offer a way forward. [ABSTRACT FROM AUTHOR]

The overall aim of this contribution to the 'Second Bill Morgan Memorial Special Issue' is to provide a high-level review of a recent report developed by a Committee for the National Council on Radiation Protection and Measurements (NCRP) titled 'Approaches for Integrating Information from Radiation Biology and Epidemiology to Enhance Low-Dose Health Risk Assessment'. It derives from previous NCRP Reports and Commentaries that provide the case for integrating data from radiation biology studies (available and proposed) with epidemiological studies (also available and proposed) to develop Biologically-Based Dose-Response (BBDR) models. In this review, it is proposed for such models to leverage the adverse outcome pathways (AOP) and key events (KE) approach for better characterizing radiation-induced cancers and circulatory disease (as the example for a noncancer outcome). The review discusses the current state of knowledge of mechanisms of carcinogenesis, with an emphasis on radiation-induced cancers, and a similar discussion for circulatory disease. The types of the various informative BBDR models are presented along with a proposed generalized BBDR model for cancer and a more speculative one for circulatory disease. The way forward is presented in a comprehensive discussion of the research needs to address the goal of enhancing health risk assessment of exposures to low doses of radiation. The use of an AOP/KE approach for developing a mechanistic framework for BBDR models of radiation- induced cancer and circulatory disease is considered to be a viable one based upon current knowledge of the mechanisms of formation of these adverse health outcomes and the available technical capabilities and computational advances. The way forward for enhancing low-dose radiation risk estimates will require there to be a tight integration of epidemiology data and radiation biology information to meet the goals of relevance and sensitivity of the adverse health outcomes required for overall health risk assessment at low doses and dose rates. [ABSTRACT FROM AUTHOR]

Age-period-cohort models are a popular tool for studying population-level rates; for example, trends in cancer incidence and mortality. Age-period-cohort models decompose observed trends into age effects that correlate with natural history, period effects that reveal factors impacting all ages simultaneously (e.g. innovations in screening), and birth cohort effects that reflect differential risk exposures that vary across birth years. Methodology for the analysis of multiple population strata (e.g. ethnicity, cancer registry) within the age-period-cohort framework has not been thoroughly investigated. Here, we outline a general model for characterizing differences in age-period-cohort model parameters for a potentially large number of strata. Our model incorporates stratum-specific random effects for the intercept, the longitudinal age trend, and the model-based estimate of annual percent change (net drift), thereby enabling a comprehensive analysis of heterogeneity. We also extend the standard model to include quadratic terms for age, period, and cohort, along with the corresponding random effects, which quantify possible stratum-specific departures from global curvature. We illustrate the utility of our model with an application to metastatic prostate cancer incidence (2004-2013) in non-Hispanic white and black men, using 17 population-based cancer registries in the Surveillance, Epidemiology, and End Results Program. [ABSTRACT FROM AUTHOR]

Background: Flight attendants may have an increased risk of some cancers from occupational exposure to cosmic radiation and circadian disruption. Methods: The incidence of thyroid, ovarian, and uterine cancer among ∼6000 female flight attendants compared to the US population was evaluated via life table analyses. Associations of these cancers, melanoma, and cervical cancer with cumulative cosmic radiation dose and metrics of circadian disruption were evaluated using Cox regression. Results: Incidence of thyroid, ovarian, and uterine cancer was not elevated. No significant, positive exposure‐response relations were observed. Weak, non‐significant, positive relations were observed for thyroid cancer with cosmic radiation and time zones crossed and for melanoma with another metric of circadian disruption. Conclusions: We found little evidence of increased risk of these cancers from occupational cosmic radiation or circadian disruption in female flight attendants. Limitations include few observed cases of some cancers, limited data on risk factors, and misclassification of exposures. [ABSTRACT FROM AUTHOR]

Background: Exposure to ionizing radiation during childhood is a well-established risk factor for thyroid cancer. However, the genetic mechanisms of radiation-associated carcinogenesis remain not fully understood.Methods: In this study, we used targeted next-generation sequencing and RNA-Seq to study 65 papillary thyroid cancers (PTCs) from patients in the Ukrainian-American cohort with measurement-based iodine-131 (I-131) thyroid doses received as a result of the Chernobyl accident. We fitted linear regression models to evaluate differences in distribution of risk factors for PTC according to type of genetic alteration and logistic regression models to evaluate the I-131 dose response. All statistical tests were two-sided.Results: Driver mutations were identified in 96.9% of these thyroid cancers, including point mutations in 26.2% and gene fusions in 70.8% of cases. Novel driver fusions such as POR-BRAF, as well as STRN-ALK fusions that have not been implicated in radiation-associated cancer before, were found. The mean I-131 dose in cases with point mutations was 0.2 Gy (range = 0.013-1.05 Gy), statistically significantly lower than 1.4 Gy (range = 0.009-6.15 Gy) for cases with fusions (P < .001). No driver point mutations were found in tumors from individuals who received more than 1.1 Gy of radiation. Relative to tumors with point mutations, the proportion of tumors with gene fusions increased with radiation dose, reaching 87.8% among individuals exposed to 0.3 Gy or higher. With a limited study sample size, the estimated odds ratio at 1 Gy was 20.01 (95% confidence interval = 2.57 to 653.02, P < .001). In addition, after controlling for I-131 dose, we found higher odds ratios for gene fusion-positive PTCs associated with several specific demographic and geographic features.Conclusions: Our data provide support for a link between I-131 thyroid dose and generation of carcinogenic gene fusions, the predominant mechanism of thyroid cancer associated with radiation exposure from the Chernobyl accident. [ABSTRACT FROM AUTHOR]

There is compelling biological data to suggest that cancer arises from a series of mutations in single target cells, resulting in defects in cell renewal and differentiation processes which lead to malignancy. Because much mutagenic damage is expressed following cell division, more-rapidly renewing tissues could be at higher risk because of the larger number of cell replications. Cairns suggested that renewing tissues may reduce cancer risk by partitioning the dividing cell populations into lineages comprising infrequently-dividing long-lived stem cells and frequently-dividing short-lived daughter transit cells. We develop generalizations of three recent cancer-induction models that account for the joint maintenance and renewal of stem and transit cells, also competing processes of partially transformed cell proliferation and differentiation/apoptosis. We are particularly interested in using these models to separately assess the probabilities of mutation and development of cancer associated with “spontaneous” processes and with those linked to a specific environmental mutagen, specifically ionizing radiation or cigarette smoking. All three models demonstrate substantial variation in cancer risks, by at least 20 orders of magnitude, depending on the assumed number of critical mutations required for cancer, and the stem-cell and transition-cell mutation rates. However, in most cases the conditional probabilities of cancer being mutagen-induced range between 7–96%. The relative risks associated with mutagen exposure compared to background rates are also stable, ranging from 1.0–16.0. Very few cancers, generally <0.5%, arise from mutations occurring solely in stem cells rather than in a combination of stem and transit cells. However, for cancers with 2 or 3 critical mutations, a substantial proportion of cancers, in some cases 100%, have at least one mutation derived from a mutated stem cell. Little difference is made to relative risks if competing processes of proliferation and differentiation in the partially transformed stem and transit cell population are allowed for, nor is any difference made if one assumes that transit cells require an extra mutation to confer malignancy from the number required by stem cells. The probability of a cancer being mutagen-induced correlates across cancer sites with the estimated cumulative number of stem cell divisions in the associated tissue (p<0.05), although in some cases there is sensitivity of findings to removal of high-leverage outliers and in some cases only modest variation in probability, but these issues do not affect the validity of the findings. There are no significant correlations (p>0.3) between lifetime cancer-site specific radiation risk and the probability of that cancer being mutagen-induced. These results do not depend on the assumed critical number of mutations leading to cancer, or on the assumed mutagen-associated mutation rate, within the generally-accepted ranges tested. However, there are borderline significant negative correlations (p = 0.08) between the smoking-associated mortality rate difference (current vs former smokers) and the probability of cancer being mutagen-induced. This is only the case where values of the critical number of mutations leading to cancer, k, is 3 or 4 and not for smaller values (1 or 2), but does not strongly depend on the assumed mutagen-associated mutation rate. [ABSTRACT FROM AUTHOR]

Background: Models for complex biological systems may involve a large number of parameters. It may well be that some of these parameters cannot be derived from observed data via regression techniques. Such parameters are said to be unidentifiable, the remaining parameters being identifiable. Closely related to this idea is that of redundancy, that a set of parameters can be expressed in terms of some smaller set. Before data is analysed it is critical to determine which model parameters are identifiable or redundant to avoid ill-defined and poorly convergent regression. Methodology/Principal Findings: In this paper we outline general considerations on parameter identifiability, and introduce the notion of weak local identifiability and gradient weak local identifiability. These are based on local properties of the likelihood, in particular the rank of the Hessian matrix. We relate these to the notions of parameter identifiability and redundancy previously introduced by Rothenberg (Econometrica 39 (1971) 577-591) and Catchpole and Morgan (Biometrika 84 (1997) 187-196). Within the widely used exponential family, parameter irredundancy, local identifiability, gradient weak local identifiability and weak local identifiability are shown to be largely equivalent. We consider applications to a recently developed class of cancer models of Little and Wright (Math Biosciences 183 (2003) 111-134) and Little et al. (J Theoret Biol 254 (2008) 229-238) that generalize a large number of other recently used quasi-biological cancer models. Conclusions/Significance: We have shown that the previously developed concepts of parameter local identifiability and redundancy are closely related to the apparently weaker properties of weak local identifiability and gradient weak local identifiability-within the widely used exponential family these concepts largely coincide. [ABSTRACT FROM AUTHOR]

Background: Heidenreich et al. (Risk Anal 1997 17 391-399) considered parameter identifiability in the context of the two-mutation cancer model and demonstrated that combinations of all but two of the model parameters are identifiable. We consider the problem of identifiability in the recently developed carcinogenesis models of Little and Wright (Math Biosci 2003 183 111-134) and Little et al. (J Theoret Biol 2008 254 229-238). These models, which incorporate genomic instability, generalize a large number of other quasi-biological cancer models, in particular those of Armitage and Doll (Br J Cancer 1954 8 1-12), the two-mutation model (Moolgavkar et al. Math Biosci 1979 47 55-77), the generalized multistage model of Little (Biometrics 1995 51 1278-1291), and a recently developed cancer model of Nowak et al. (PNAS 2002 99 16226-16231). Methodology/Principal Findings: We show that in the simpler model proposed by Little and Wright (Math Biosci 2003 183 111-134) the number of identifiable combinations of parameters is at most two less than the number of biological parameters, thereby generalizing previous results of Heidenreich et al. (Risk Anal 1997 17 391-399) for the two-mutation model. For the more general model of Little et al. (J Theoret Biol 2008 254 229-238) the number of identifiable combinations of parameters is at most r+1 less than the number of biological parameters, where r is the number of destabilization types, thereby also generalizing all these results. Numerical evaluations suggest that these bounds are sharp. We also identify particular combinations of identifiable parameters. Conclusions/Significance: We have shown that the previous results on parameter identifiability can be generalized to much larger classes of quasi-biological carcinogenesis model, and also identify particular combinations of identifiable parameters. These results are of theoretical interest, but also of practical significance to anyone attempting to estimate parameters for this large class of cancer models. [ABSTRACT FROM AUTHOR]

Abstract: There is much uncertainty about cancer risks at the high radiation doses used in radiotherapy (RT). It has generally been assumed that cancer induction decreases rapidly at high doses due to cell killing. However, this is not seen in all RT groups, and a model recently developed by Sachs and Brenner [2005. Solid tumor risks after high doses of ionizing radiation. Proc. Natl Acad. Sci. USA 102, 13040–13045] proposed a mechanism for repopulation of cells after radiation exposure that explained why this might happen, at least for solid tumours. In this paper, this model is generalized to allow for heterogeneity in the dose received, and various alternate patterns of repopulation are also considered. The model is fitted to the Japanese atomic bomb survivor leukaemia incidence data, and data for various therapeutically irradiated groups. Two sets of parameters from these model fits are used to assess the sensitivity of model predictions. It is shown that in general allowing for heterogeneity in dose distribution and haematopoietic stem cell migration results in lower risks than the same average dose administered uniformly and without such migration, although this does not hold in the limiting case of complete stem cell repopulation between radiation dose fractions. We also investigate the difference made by assuming a compartmental repopulation signal, and a global repopulation signal. In general we show that in the absence of stochastic extinction, compartmental repopulation always predicts a larger number of mutated cells than global repopulation. However, in certain dose regimes stochastic extinction cannot be ignored, and in these cases the numbers of mutated cells predicted with global repopulation can exceed that for compartmental repopulation. In general, mutant cell numbers are highly overdispersed, with variance much greater than the mean. [Copyright &y& Elsevier]

Background: Because many cancer patients are diagnosed earlier and live longer than in the past, second cancers induced by radiation therapy have become a clinically significant issue. An earlier biologically based model that was designed to estimate risks of high-dose radiation-induced solid cancers included initiation of stem cells to a premalignant state, inactivation of stem cells at high radiation doses, and proliferation of stem cells during cellular repopulation after inactivation. This earlier model predicted the risks of solid tumors induced by radiation therapy but overestimated the corresponding leukemia risks. Methods: To extend the model to radiation- induced leukemias, we analyzed—in addition to cellular initiation, inactivation, and proliferation—a repopulation mechanism specific to the hematopoietic system: long-range migration through the blood stream of hematopoietic stem cells (HSCs) from distant locations. Parameters for the model were derived from HSC biologic data in the literature and from leukemia risks among atomic bomb survivors who were subjected to much lower radiation doses. Results: Proliferating HSCs that migrate from sites distant from the high-dose region include few preleukemic HSCs, thus decreasing the high-dose leukemia risk. The extended model for leukemia provides risk estimates that are consistent with epidemiologic data for leukemia risk associated with radiation therapy over a wide dose range. For example, when applied to an earlier case-control study of 110 000 women undergoing radiotherapy for uterine cancer, the model predicted an excess relative risk (ERR) of 1.9 for leukemia among women who received a large inhomogeneous fractionated external beam dose to the bone marrow (mean = 14.9 Gy), consistent with the measured ERR (2.0, 95% confidence interval [CI] = 0.2 to 6.4; from 3.6 cases expected and 11 cases observed). As a corresponding example for brachytherapy, the predicted ERR of 0.80 among women who received an inhomogeneous low-dose-rate dose to the bone marrow (mean = 2.5 Gy) was consistent with the measured ERR (0.62, 95% CI = -0.2 to 1.9). Conclusions: An extended, biologically based model for leukemia that includes HSC initiation, inactivation, proliferation, and, uniquely for leukemia, long-range HSC migration predicts, with reasonable accuracy, risks for radiation- induced leukemia associated with exposure to therapeutic doses of radiation. [ABSTRACT FROM AUTHOR]