Minimum latency effects for cancer associated with exposures to radiation or other carcinogens

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.

Lifetime radiation risk of stochastic effects - prospective evaluation for space flight or medicine

The concept of lifetime radiation risk of stochastic detrimental health outcomes is important in contemporary radiation protection, being used either to calculate detriment-weighted effective dose or to express risks following radiation accidents or medical uses of radiation. The conventionally applied time-integrated risks of radiation exposure are computed using average values of current population and health statistical data that need to be projected far into the future. By definition, the lifetime attributable risk (AR) is an approximation to more general lifetime risk quantities and is only valid for exposures under 1 Gy. The more general quantities, such as excess lifetime risk (ELR) and risk of exposure-induced cancer, are free of dose range constraints, but rely on assumptions concerning the unknown total radiation effect on demographic and health statistical data, and are more computationally complex than AR. Consideration of highly uncertain competing risks for other radiation-attributed outcomes are required in appropriate assessments of time-integrated risks of specific outcomes following high-dose (>1 Gy) exposures, causing non-linear dose responses in the resulting ELR estimate.Being based on the current population and health statistical data, the conventionally applied time-integrated risks of radiation exposure are: (i) not well suited for projections many years into the future because of the large uncertainties in future secular trends in the population-specific disease rates; and (ii) not optimal for application to atypical groups of exposed persons not well represented by the general population. Specifically, medical patients are atypical in this respect because their prospective risks depend strongly on the original diagnosis, the treatment modality, general cure rates, individual radiation sensitivity, and genetic predisposition. Another situation challenging the application of conventional risk quantities is a projection of occupational radiation risks associated with space flight, both due to higher radiation doses and astronauts' generally excellent health condition due to pre-selection, training, and intensive medical screening.An alternative quantity, named 'radiation-attributed decrease of survival' (RADS), known in past general statistical literature as 'cumulative risk', is recommended here for applications in space and medicine to represent the cumulative radiation risk conditional on survival until a certain age. RADS is only based on the radiation-attributed hazard rendering an insensitivity to competing risks or projections of current population statistics far into the future. Therefore, RADS is highly suitable for assessing semi-personalised radiation risks after radiation exposures from space missions or medical applications of radiation.

Cardiovascular disease mortality of A-bomb survivors and the healthy survivor selection effect

The latest A-bomb survivor data for cardiovascular diseases are analysed to investigate whether in the first years after the bombings the baseline rates of proximal survivors were markedly different compared with those of the distal survivors. This phenomenon relates to a healthy survivor selection effect. This question is important for the decision whether to include or exclude the early years of follow-up when analysing the biological effects from acute low and high dose exposures following the nuclear weapons explosions in Hiroshima and Nagasaki. The present study shows that for cerebrovascular diseases and heart diseases the baseline rates are not significantly different in the first two decades of follow-up. Thus, for these two detrimental health outcomes, there is no need to exclude distal survivors and the first decades of follow-up time when investigating the shapes of the related dose-responses.

A fast and simple approach for the estimation of a radiological source from localised measurements after the explosion of a radiological dispersal device

After an explosion of a radiological dispersal device, decision-makers need to implement countermeasures as soon as possible to minimise the radiation-induced risks to the population. In this work, the authors present a tool, which can help providing information about the approximate size of source term and radioactive contamination based on a Gaussian Plume model with the use of available measurements for liquid or aerosolised radioactivity. For two-field tests, the source term and spatial distribution of deposited radioactivity are estimated. A sensitivity analysis of the dependence on deposition velocity is carried out. In case of weak winds, a diffusive process along the wind direction is retained in the model.

Modeling of the fate of radionuclides in urban sewer systems after contamination due to nuclear or radiological incidents

After an accidental radioactive contamination by aerosols in inhabited areas, the radiation exposure to man is determined by complex interactions between different factors such as dry or wet deposition, different types of ground surfaces, chemical properties of the radionuclides involved and building development as well as dependence on bomb construction e.g. design and geometry. At short-term, the first rainfall is an important way of natural decontamination: deposited radionuclides are washed off from surfaces and in urban areas the resulting contaminated runoff enters the sewer system and is collected in a sewage plant. Up to now the potential exposure caused by this process has received little attention and is estimated here with simulation models. The commercial rainfall-runoff model for urban sewer systems KANAL++ has been extended to include transport of radionuclides from surfaces through the drainage to various discharge facilities. The flow from surfaces is modeled by unit hydrographs, which produce boundary conditions for a system of 1d coupled flow and transport equations in a tube system. Initial conditions are provided by a map of surface contamination which is produced by geo-statistical interpolation of γ-dose rate measurements taking into account the detector environment. The corresponding methodology is implemented in the Inhabited Area Monitoring Module (IAMM) software module as part of the European decision system JRODOS. A hypothetical scenario is considered where a Radiation Dispersal Device (RDD) with Cs-137 is detonated in a small inhabited area whose drainage system is realistically modeled. The transition of deposited radionuclides due to rainfall into the surface runoff is accounted for by different nuclide-specific entrainment coefficients for paved and unpaved surfaces. The concentration of Cs-137 in water is calculated at the nodes of the drainage system and at the sewage treatment plant. The external exposure to staff of the treatment plant is estimated. For Cs-137 radiation levels in the plant are low since wash-off of cesium from surfaces is an ineffective process.

Modeling the impact of climate change in Germany with biosphere models for long-term safety assessment of nuclear waste repositories

Biosphere models are used to evaluate the exposure of populations to radionuclides from a deep geological repository. Since the time frame for assessments of long-time disposal safety is 1 million years, potential future climate changes need to be accounted for. Potential future climate conditions were defined for northern Germany according to model results from the BIOCLIM project. Nine present day reference climate regions were defined to cover those future climate conditions. A biosphere model was developed according to the BIOMASS methodology of the IAEA and model parameters were adjusted to the conditions at the reference climate regions. The model includes exposure pathways common to those reference climate regions in a stylized biosphere and relevant to the exposure of a hypothetical self-sustaining population at the site of potential radionuclide contamination from a deep geological repository. The end points of the model are Biosphere Dose Conversion factors (BDCF) for a range of radionuclides and scenarios normalized for a constant radionuclide concentration in near-surface groundwater. Model results suggest an increased exposure of in dry climate regions with a high impact of drinking water consumption rates and the amount of irrigation water used for agriculture.

Dose-responses from multi-model inference for the non-cancer disease mortality of atomic bomb survivors

The non-cancer mortality data for cerebrovascular disease (CVD) and cardiovascular diseases from Report 13 on the atomic bomb survivors published by the Radiation Effects Research Foundation were analysed to investigate the dose-response for the influence of radiation on these detrimental health effects. Various parametric and categorical models (such as linear-no-threshold (LNT) and a number of threshold and step models) were analysed with a statistical selection protocol that rated the model description of the data. Instead of applying the usual approach of identifying one preferred model for each data set, a set of plausible models was applied, and a sub-set of non-nested models was identified that all fitted the data about equally well. Subsequently, this sub-set of non-nested models was used to perform multi-model inference (MMI), an innovative method of mathematically combining different models to allow risk estimates to be based on several plausible dose-response models rather than just relying on a single model of choice. This procedure thereby produces more reliable risk estimates based on a more comprehensive appraisal of model uncertainties. For CVD, MMI yielded a weak dose-response (with a risk estimate of about one-third of the LNT model) below a step at 0.6 Gy and a stronger dose-response at higher doses. The calculated risk estimates are consistent with zero risk below this threshold-dose. For mortalities related to cardiovascular diseases, an LNT-type dose-response was found with risk estimates consistent with zero risk below 2.2 Gy based on 90% confidence intervals. The MMI approach described here resolves a dilemma in practical radiation protection when one is forced to select between models with profoundly different dose-responses for risk estimates.

Breast cancer risk in atomic bomb survivors from multi-model inference with incidence data 1958-1998

Breast cancer risk from radiation exposure has been analyzed in the cohort of Japanese a-bomb survivors using empirical models and mechanistic two-step clonal expansion (TSCE) models with incidence data from 1958 to 1998. TSCE models rely on a phenomenological representation of cell transition processes on the path to cancer. They describe the data as good as empirical models and this fact has been exploited for risk assessment. Adequate models of both types have been selected with a statistical protocol based on parsimonious parameter deployment and their risk estimates have been combined using multi-model inference techniques. TSCE models relate the radiation risk to cell processes which are controlled by age-increasing rates of initiating mutations and by changes in hormone levels due to menopause. For exposure at young age, they predict an enhanced excess relative risk (ERR) whereas the preferred empirical model shows no dependence on age at exposure. At attained age 70, the multi-model median of the ERR at 1 Gy decreases moderately from 1.2 Gy(-1) (90% CI 0.72; 2.1) for exposure at age 25 to a 30% lower value for exposure at age 55. For cohort strata with few cases, where model predictions diverge, uncertainty intervals from multi-model inference are enhanced by up to a factor of 1.6 compared to the preferred empirical model. Multi-model inference provides a joint risk estimate from several plausible models rather than relying on a single model of choice. It produces more reliable point estimates and improves the characterization of uncertainties. The method is recommended for risk assessment in practical radiation protection.

Modelling the long-term consequences of a hypothetical dispersal of radioactivity in an urban area including remediation alternatives

The Urban Remediation Working Group of the International Atomic Energy Agency's EMRAS (Environmental Modelling for Radiation Safety) program was organized to address issues of remediation assessment modelling for urban areas contaminated with dispersed radionuclides. The present paper describes the second of two modelling exercises. This exercise was based on a hypothetical dispersal of radioactivity in an urban area from a radiological dispersal device, with reference surface contamination at selected sites used as the primary input information. Modelling endpoints for the exercise included radionuclide concentrations and external dose rates at specified locations, contributions to the dose rates from individual surfaces, and annual and cumulative external doses to specified reference individuals. Model predictions were performed for a "no action" situation (with no remedial measures) and for selected countermeasures. The exercise provided an opportunity for comparison of three modelling approaches, as well as a comparison of the predicted effectiveness of various countermeasures in terms of their short-term and long-term effects on predicted doses to humans.

New developments to support decision-making in contaminated inhabited areas following incidents involving a release of radioactivity to the environment

The Chernobyl accident demonstrated that releases from nuclear installations can lead to significant contamination of large inhabited areas. A new generic European decision support handbook has been produced on the basis of lessons learned on the management of contaminated inhabited areas. The handbook comprises detailed descriptions of 59 countermeasures in a standardised datasheet format, which facilitates a comparison of features. It also contains guidance in the form of decision flowcharts, tables, check lists and text to support identification of optimised solutions for managing the recovery of inhabited areas within a framework consistent with ICRP recommendations. A new comprehensive inhabited-area dose model is also being developed for implementation in the ARGOS and RODOS decision support systems. Shortcomings of previous models are demonstrated. Decision support modelling in relation to malicious dispersion of radioactive matter in inhabited areas is also discussed. Here, the implications of, e.g., particle sizes and dispersion altitude are highlighted.

Lung tumour risk in radon-exposed rats from different experiments: comparative analysis with biologically based models

Data sets of radon-exposed male rats from Wistar and Sprague-Dawley strains have been investigated with two different versions of the two-step clonal expansion (TSCE) model of carcinogenesis. These so-called initiation-promotion (IP) and initiation-transformation (IT) models are named after the cell-based processes that are assumed to be induced by radiation. The analysis was done with all malignant lung tumours taken to be incidental and with fatal tumours alone. For all tumours treated as incidental, both models could explain the tumour incidence data equally well. Owing to its better fit, only the IP model was applied in the analysis of fatal tumours that carry additional information on the time when they cause death. A statistical test rejected the hypothesis that a joint cohort of Wistar and Sprague-Dawley rats can be described with the same set of model parameters. Thus, the risk analysis has been carried out for the Wistar rats and the Sprague-Dawley rats separately and has been restricted to fatal tumours alone because of their similar effect in humans. Using a refined technique of age-adjustment, the lifetime excess absolute risk has been standardised with the survival function from competing risks in the control population. The age-adjusted excess risks for both strains of rats were of similar size, for animals with first exposure later in life they decreased markedly. For high cumulative exposure the excess risk increased with longer exposure duration, for low cumulative exposure it showed the opposite trend. In addition, high cumulative exposure exerted lethal effects other than lung cancer on the rats.

Age-adjustment in experimental animal data and its application to lung cancer in radon-exposed rats

Procedures for age-adjustment of cancer fractions are proposed which do not require fixed age intervals. The full available information on survival times can then be used, which is especially important in small treatment groups. For incidental cancers a non-decreasing prevalence function and for fatal cancers the Kaplan-Meier estimator is used. In the latter case, the estimated competing risk of the control population is standardized, not its true survival. This makes the technique also applicable to treatment groups with high incidence, which otherwise may give adjusted rates above 100%. In the application part these age-adjustment techniques are used here to study lung cancer in radon-exposed Wistar and Sprague-Dawley rats. The data include a classification in fatal and incidental lung cancers. For fatal lung cancer, the lifetime excess absolute risk (LEAR) at 1 WLM averaged over all exposed groups is 0.67x10(-4) for the Wistar rats, while for the Sprague-Dawley rats it is 0.40x10(-4). For the Sprague-Dawley rats, there are several groups exposed later in life. When the averaging is restricted to animals with start of exposure prior to 150 days of age, the weighted average risk among the Sprague-Dawley rats is 0.79x10(-4). Compared to groups with similar exposures as young adults (up to about 150 days), animals exposed later in life have substantially lower lifetime risks. The Wistar rats include groups with roughly equal exposure rates and ages at start of exposure, but with increasing exposure duration. Within these groupings the LEAR at 1 WLM does not decrease with additional exposure at higher age, as would be expected if the risk from exposures at different ages would be additive.

Comparing regression methods for the two-stage clonal expansion model of carcinogenesis

In the statistical analysis of cohort data with risk estimation models, both Poisson and individual likelihood regressions are widely used methods of parameter estimation. In this paper, their performance has been tested with the biologically motivated two-stage clonal expansion (TSCE) model of carcinogenesis. To exclude inevitable uncertainties of existing data, cohorts with simple individual exposure history have been created by Monte Carlo simulation. To generate some similar properties of atomic bomb survivors and radon-exposed mine workers, both acute and protracted exposure patterns have been generated. Then the capacity of the two regression methods has been compared to retrieve a priori known model parameters from the simulated cohort data. For simple models with smooth hazard functions, the parameter estimates from both methods come close to their true values. However, for models with strongly discontinuous functions which are generated by the cell mutation process of transformation, the Poisson regression method fails to produce reliable estimates. This behaviour is explained by the construction of class averages during data stratification. Thereby, some indispensable information on the individual exposure history was destroyed. It could not be repaired by countermeasures such as the refinement of Poisson classes or a more adequate choice of Poisson groups. Although this choice might still exist we were unable to discover it. In contrast to this, the individual likelihood regression technique was found to work reliably for all considered versions of the TSCE model.

Identifying dose dependences of the two-stage clonal expansion model with simulated cohorts

The two-stage clonal expansion model of cancer induction is tested on recorded and simulated cohort data of radon-exposed rats. Unfortunately, different versions of the model, for which radiation acts on different biological processes, can provide a good description of the data. This is the case for an initiation-transformation and an initiation-promotion model when they are applied to lung tumour data of radon-exposed rats and all malignant tumours are assumed to be incidental. However, if one were able to use information on fatal tumours as well, the two models could be separated by their deviances.

Post-chymopapain (chemonucleolysis)--clinical and computed tomography correlation: preliminary results

Chymopapain was first used for treatment of lumbar disc herniation in 1964 and has been used extensively in Canada and Europe for the last decade, but was recently released for general use in the United States. The enzyme is thought to cause decrease in intradiscal pressure and in disc volume; however, little in vivo evidence exists to support this concept. High resolution computed tomography (CT) scans were performed for diagnosis and at a variable period following chemonucleolysis on 17 randomly selected patients. The results of the study were: disc space narrowing occurred almost invariably; retraction of the prolapsed or extruded disc occurred in many patients; clinical improvement was closely related to retraction of the prolapsed or extruded disc; the best clinical results were obtained in patients who were injected at a single level with a clearly demonstrable disc prolapse or herniation.