The overall aim of this Report is to provide input for the development
of biologically based dose-response (BBDR) models for radiation-
induced cancers and circulatory disease that use an adverse
outcome pathways and key-events approach for providing parameters
for these models. These mechanistic data can be integrated
with the most recent epidemiologic data to develop overall doseresponse
curves for radiation-induced adverse health outcomes.
This integration of the findings from radiation biology and epidemiology
will enhance the risk assessment process by reducing
uncertainties in estimated risk following exposure to low doses and
low dose rates of ionizing radiation.
For many decades the basis for setting radiation protection
guidance for exposure to low absorbed doses and low absorbed-dose
rates of ionizing radiation has been the estimation of the risk of
radiation-induced cancer. In addition, there is ongoing discussion
concerning risks of radiation-induced noncancer effects1 (particularly
circulatory disease). The estimates for radiation-induced cancer
have been derived primarily from exposure to higher doses and
higher dose rates of ionizing radiation and assumptions on how to
extrapolate to low doses and low dose rates. For the purpose of this
Report, for low linear-energy transfer (LET) radiation, a low
absorbed dose is <100 mGy delivered acutely, and a low absorbeddose
rate is <5 mGy h–1 for any accumulated absorbed dose (NCRP
This Report addresses the conclusions and recommendations
from three previous National Council on Radiation Protection and
Measurements (NCRP) reports and commentaries on the topic of
the risks of adverse health outcomes at low doses and low dose
rates of ionizing radiation (NCRP 2012, 2015, 2018a). In this context,
the present Report proposes a path forward to enhance the
estimation of risk at low doses and low dose rates. Such a modified
approach is needed to supplement the information that can be
obtained from the conduct of even large epidemiologic studies such
as the One Million U.S. Workers and Veterans Study of Low-Dose
Radiation Health Effects (million U.S. workers and veterans study)
1For this Report the term noncancer is restricted to somatic noncancer
outcomes and does not include heritable effects.
(Bouville et al. 2015; Boice et al. 2019), the International Nuclear
Workers Study (Leuraud et al. 2015; Richardson et al. 2015), the
European pooled study of radiation-induced cancer from pediatric
computed tomography (Bernier et al. 2019), or other low-dose pooling
studies (Lubin et al. 2017; Little, Kitahara et al. 2018). This
Report presents such an approach based upon the integration of
data from epidemiology and radiation biology.
An essential component of the integration process is the use of
BBDR models with parameters being developed from analyzing
adverse outcome pathways and their associated key events. In
principle, an adverse outcome pathway is the series of necessary
steps that result in an initial molecular event leading to an adverse
health outcome (for this Report, either cancer or circulatory disease).
Definitions of adverse outcome pathways and key events are
given in Section 2 and can be found also in recent reviews (Edwards
et al. 2016; Preston 2017).
Also, when considering mechanistic data underlying the induction
of adverse health outcomes, it is important to distinguish
between potential bioindicators and biomarkers of these outcomes.
A bioindicator is a cellular alteration that is on a critical pathway
to the disease endpoint itself (i.e., necessary, but not by itself sufficient
for the endpoint), such as a specific mutation in a target cell
that is associated with tumor formation. Thus, a bioindicator can
be perceived as informing on the shape of the dose-response curve
for the disease outcome or on cancer frequency itself, and therefore,
is equivalent to a key event. A biomarker is a biological phenotype
[e.g., chromosome alteration, deoxyribonucleic acid (DNA) adduct,
gene expression change, specific metabolite] that can be used to
indicate a response to an exposure at the cell or tissue level. In this
regard, a biomarker is generally a measure of the potential for
development of an adverse health outcome such as cancer (e.g., a
predictor of exposure level).
This Report expands upon this general approach of adverse outcome
pathways, key events, and BBDR models to enhance the process
of low-dose, low dose-rate risk estimation. The arrangement
of this Report for the application of this general approach is: here
is what we know, here is what we need to know, and this is how
we can obtain the necessary knowledge. A synopsis of Sections 2
through 7 is given below.
Section 2 (Introduction) provides an overview of current
approaches to radiation risk assessment, the associated uncertainties
and possible ways forward for enhancing the estimation of
risks of cancer and circulatory disease at low doses and low dose
Section 3 (Epidemiology, Biosamples and Biomarkers: Cancer
and Circulatory Disease) presents a review of the radiation epidemiologic
studies for which biomarker data or biological samples
were used. For noncancer effects it was clear that the only adverse
health outcome for which significant data from radiation biology
are available for use in BBDR models is circulatory disease and
so this forms the basis for the discussion on noncancer effects.
There are a large number of radiation epidemiologic studies available
that are very informative for estimating risks at higher doses
but that can only be used with a fairly high degree of uncertainty
for predicting low-dose risks. A review of the main radiation epidemiologic
studies has been provided in NCRP Commentary No. 27
Section 3.1 briefly describes the major epidemiologic radiation
studies with associated biosamples that potentially can be
employed to conduct investigations of bioindicators of the pathogenesis
of radiation-induced cancer and other health endpoints.
While none of the current investigations has yet been able to identify
definitive bioindicators, there are several suggestions of biomarkers
that merit confirmation through further investigations
and might be informative in the absence of more definitive bioindicator
studies. The details and references for these studies are provided
in Section 3.1.3.
Section 3.2 indicates that it is likely that bioindicators of radiation-
induced noncancer effects at low doses will be restricted to
circulatory disease and so this is the sole topic reviewed for biomarkers
associated with noncancer responses. With current knowledge,
substantive biomarker information is only available in two
major radiation studies: the Japanese atomic-bomb survivors, and
the Mayak Production Association workers (Mayak workers),
although little use has been made of this latter population in analyses
In summary, there is a paucity of radiation-specific bioindicators
of cancer and circulatory disease and a relative lack of radiation-
specific biomarkers predictive of adverse health outcomes.
Thus, it is necessary to consider the mechanisms of formation of
cancers and circulatory disease, especially for radiation-induced
responses, to aid with the identification of bioindicators of adverse
health outcomes and to a lesser extent, biomarkers of association
with an adverse health outcome.
Section 4 (Radiation-Induced Biological Effects Related to Cancer
and Circulatory Disease) reviews the underlying mechanisms
of carcinogenesis and circulatory disease with the aim of identifying
potential bioindicators of the adverse health outcome, and if
possible radiation-associated bioindicators of such responses. There
has been an increased understanding of the underlying mechanisms
of human diseases as a result of new molecular, cellular and
computational approaches, further enhanced by informative experimental
animal systems that model human disease. To a lesser
extent such approaches have been used to better understand the
etiology of radiation-induced diseases. There is a description of
the types of studies that have identified pathways and potential
key events in the carcinogenesis process (Section 4.1).
While currently there are no fully validated bioindicators or biomarkers
of radiation-induced cancer, there is a substantial and
increasing body of knowledge on radiation-induced cancer mechanisms,
particularly in experimental animal systems. Quantification
of inflammation and generation of persistently elevated reactive
oxygen species (ROS) holds promise as a further bioindicator that
is also recognized as an enabling hallmark of cancer in the context
of Hanahan and Weinberg (2011). In addition, cell-survival parameters
can be of importance in mechanistic models of carcinogenesis.
The use of data from experimental animal systems provides
opportunities to demonstrate the added value of building and
applying mechanistic models of radiation-induced cancer. There are
additional opportunities to apply similar models in some human
radiation-induced cancers, most notably thyroid, where some work
utilizing knowledge of the CLIP2 marker is already available. The
incorporation of quantitative mechanistic data into appropriate
cancer models (discussed in Sections 5 and 6) is likely to increase
the precision of estimated risks, particularly at low-dose levels and
so continued efforts to identify and validate bioindicators of radiation-
induced cancers will assist in refining risk estimation.
Section 4.2 outlines the biology of circulatory disease, a significant
radiation-induced noncancer disease2 and the one which currently
offers the best opportunity for bioindicator identification
given the mechanistic data already available. The complex inflammatory
processes underlying most major types of circulatory disease
are reviewed, specifically those associated with atherosclerosis.
The possible ways that low-dose radiation exposure and other
2NCRP (2018a) stated that radiation-induced cardiovascular disease
(a circulatory disease) remains an area where further investigation is necessary.
Although there is evidence that cardiovascular disease may be a
factor at exposures lower than previously estimated, that evidence was
not yet sufficient to allow for development of an approach to including cardiovascular
disease in NCRP’s overall system of radiation protection published
in NCRP (2018b).
biological stressors might affect the circulatory system are also
reviewed. While it is not possible yet to identify bioindicators of
radiation-induced circulatory disease, it appears feasible to build
upon the rapidly increasing knowledge of the mechanisms of formation
of circulatory disease to develop adverse outcome pathways
and at least some of the associated key events.
Section 5 (Biologically Based Dose-Response Models) assesses
biomathematical models of chronic disease, especially those for
cancer and circulatory disease (with particular emphasis in circulatory
disease on models of atherosclerosis). First, general material
outlining the overall goals of biomathematical models is presented,
followed by discussion of modeling considerations, particularly
application of specific models using human, animal or cell data to
cancer and circulatory disease. Biologically based modeling of radiation-
induced cancers of the breast, colon, lung, and thyroid gland
have been conducted.
After considerations of some general features of BBDR models of
cancer development in Section 5.1, a number of BBDR models and
their application to various human and animal datasets are presented
in Section 5.2. Despite some shortcomings (e.g., the fact that
different models might explain the available data using different
mechanistic assumptions), multiple pathway models are considered
a promising conceptual approach to developing a general model
framework for the complex process of carcinogenesis in various tissues.
In certain cases, multiple pathway models may allow predictions
that can be validated against experimental data.
Circulatory disease models are considered in Section 5.3. These
are less well developed than those that have been constructed
to model cancer. A number of candidate models of atherosclerosis
are considered. Atherosclerosis is the disease process underlying
the main types of circulatory disease, specifically ischemic heart
disease (IHD) and stroke, which is thought to have a largely inflammatory
etiology. A number of atherosclerosis models, which share
certain features, have been proposed for these inflammatory
processes, specifically the adhesion and transport of monocytes
through the epithelial cell layer, and diffusion through the intima.
However, it is not yet clear what the radiation-associated mechanisms
may be for most types of circulatory disease.
Having identified the types of BBDR models that could possibly
be used to enhance the estimation of low-dose, low dose-rate radiation
adverse health outcomes, it is necessary to determine whether
there is a generalized model that can be used for: all radiationinduced
cancer types, or circulatory disease as a class.
It was concluded that it would be unlikely that a single model
structure could be used for describing cancer and circulatory disease.
Also, it appears likely that there may be different responses
even for different types of circulatory disease.
The concept of a generalized model is discussed in Section 6
(Proposed Generalized Model Framework of Cancer and Circulatory
Disease). It is proposed that a form of multistage clonal expansion
model would be appropriate for integrating data from epidemiology
and radiation biology for estimating low-dose, low dose-rate
cancer risk. The parameters for such a model structure are proposed
to be developed from an adverse outcome pathways and
key-events approach. In such an approach the key events are considered
to be bioindicators of the adverse health outcome itself. In
support of this proposal to utilize generalized multistage clonal
expansion models, there has been considerable recent discussion on
the use of such parameterized models for environmental chemicals
(OECD 2020). The Organization for Economic Co-operation and
Development (OECD 2020) website provides a considerable amount
of information on developing adverse outcome pathways and their
use in risk assessment and ultimately in risk management practice.
This general approach is also described and applied in the
research program of the U.S. Environmental Protection Agency
A description of biologically detailed models of specific cancers
that have been applied with some levels of success is provided to
indicate the viability of the use of BBDR models for estimating
adverse health outcomes at low doses and low dose rates. While not
definitive at this time, the approach certainly has a real likelihood
of being successful.
Section 7 (Research Needs) provides specific examples of
research activities, both large and small that are designed for
developing adverse outcome pathways and their associated key
events. These include epidemiologic, human sample, laboratory
animal, cellular, and molecular studies. Such research activities
include investigating some general but critical responses, in order
to derive greater insight into the parameters of most importance
for further model development. Currently, one can envisage the following
to be of high relevance:
• target cell population numbers and characteristics;
• survival parameters for these populations after radiation
• target gene(s) critical for pathogenesis and their mutation
or epimutation frequency as a function of radiation dose;
• proliferation characteristics in normal and mutation-carrying
cell populations; and
• timing and frequency of acquisition of further mutational
events in key genes and the impact of these on survival and
For enhanced model development, it is necessary to more fully
identify the mechanisms of cancer development in response to radiation.
The following are of importance in this regard:
• Mechanisms in the development of a radiation-induced disease
may differ from those in sporadic disease.
• Does radiation initiate or accelerate the same processes that
lead to sporadic disease, or are distinct molecular pathways
• BBDR models have the potential to address such questions
if appropriate bioindicators become available for specific
types of cancer or other diseases.
• For transcriptomics, proteomics, metabolomics and epigenomics,
adequate BBDR models ideally might require measurements
at several time points because the profiles of
phenotypic alterations may differ by stage in the pathogenesis
of a disease.
Clearly, the overarching need is the furthering of research targeted
at the underlying mechanisms of radiation-induced adverse
health outcomes (cancer and noncancer disease) leading to the
identification of truly informative bioindicators of the apical endpoint
(i.e., the adverse health outcome). The framework for such an
approach can be the characterization of adverse outcome pathways
for specific outcomes and the identification of key events from the
initial event to adverse health outcome. In this context, a key-event
or informative bioindicator is a true surrogate for the adverse
health outcome. This approach will require the integration of data
from epidemiology and radiation biology to maximize the information
for estimating low-dose responses for adverse health outcomes.
A particularly important result will be the ability to better describe
the form of the dose-response curve for different types of radiation-
induced cancer, for example, and thereby avoid the need to rely
on application of the linear-nonthreshold (LNT) model without sufficient
biological substantiation. A concerted effort will be needed;
this is going to require a well-defined and quite extensive research
effort. The need for this effort is recognized by many in the risk
assessment and risk management arena.