SOURCES, EFFECTS AND RISKSOF IONIZING RADIATION
United Nations Scientific Committee on the
Effects of Atomic Radiation
UNSCEAR 2012
Report to the General Assemblywith Scientific Annexes

Scientific Annexes

UNITED NATIONSNew York, 2015

NOTE
The report of the Committee without its annexes appears as Official Records of the General
Assembly, Sixty-seventh Session, Supplement No. 46 (A/67/46).
The designations employed and the presentation of material in this publication do not imply
the expression of any opinion whatsoever on the part of the Secretariat of the United Nations­
concerning the legal status of any country, territory, city or area, or of its authorities, or­concerning the delimitation of its frontiers or boundaries.
The country names used in this document are, in most cases, those that were in use at the time thedata were collected or the text prepared. In other cases, however, the names have been updated,
where this was possible and appropriate, to reflect political changes.

UNITED NATIONS PUBLICATION
Sales No. E.16.IX.1
ISBN: 978-92-1-142307-5
eISBN: 978-92-1-057798-4© United Nations, December 2015. All rights reserved, worldwide.
This publication has not been formally edited.
Information on uniform resource locators and links to Internet sites contained in the present
publication are provided for the convenience of the reader and are correct at the time of issue.
The United Nations takes no responsibility for the continued accuracy of that information or forthe content of any external website.

ANNEX AATTRIBUTING HEALTH EFFECTS TO IONIZINGRADIATION EXPOSURE AND INFERRING RISKS

17ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 19

CONTENTSI.

INTRODUCTION ................................................................................................................................... 21

II. BASIC ASPECTS .................................................................................................................................... 23
III. ATTRIBUTING HEALTH EFFECTS TO RADIATION EXPOSURE ............................................... 24
IV. INFERRING RISKS AFTER RADIATION EXPOSURE ..................................................................... 26
V. RESEARCH NEEDS ............................................................................................................................... 29
VI. SUMMARY AND CONCLUSIONS .................................................................................................... 29
APPENDIX A. SCIENTIFIC KNOWLEDGE ON HEALTH EFFECTS OF RADIATION EXPOSURE
AND ITS USE ................................................................................................................................................. 33
I.

Introduction.................................................................................................................................. 33

II. Scientific method, science-based inference and application ofscientific knowledge.................................................................................................................. 34
III. Attributing observed health effects to radiation exposure......................................... 43
IV. Inferring risk of health effects from radiation exposure ............................................... 53
V. Research needs............................................................................................................................ 63
VI. Summary........................................................................................................................................ 65
APPENDIX B. CASE STUDIES .................................................................................................................. 69
I.

Skin burn after interventional cardiology procedure .................................................... 70

II. Pregnancy with mentally retarded infant .......................................................................... 71
III. Thyroid cancer after the Chernobyl accident ................................................................... 73
IV. Lung cancer from exposure to radon .................................................................................. 75
V. Estimated risk from computed tomography scans ........................................................ 77
REFERENCES ................................................................................................................................................. 81

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 21

I. INTRODUCTION
1.
The Scientific Committee evaluates (a) levels of exposure to ionizing radiation, and (b) the effects
of exposure on—and associated risks* 1 to—human health and the environment. It provides scientificevaluations for informed policy setting and decision-making (e.g. governments and organizations use
these evaluations for establishing protective measures and other decisions). Thus, it is important that theCommittee communicates not only the results of its evaluations, but also its confidence in, andlimitations of, its evaluations in a balanced and considered manner, so that the findings not be
misinterpreted or misused.
2.
The Committee conducts its evaluations by reviewing scientific data and literature on clinicalobservations of health effects* in exposed individuals, laboratory studies at the molecular and cellularlevel, animal studies, and epidemiological studies of the frequency* of disease occurrence in exposed
populations (see, for example, [U2, U3, U5, U6, U7, U8, U9, U10, U13]). Based on its evaluations of
this information, the Committee has estimated risks associated with exposure to ionizing radiation.
While the Committee has provided detailed reports on estimation of risk, it has not presented
comprehensive information on the uses and limitations of its estimated risks for the general reader.
3.
At the time of the twentieth anniversary of the Chernobyl accident in April 2006, there appeared
to be widely diverging views, often based on misunderstanding, among the general public, media,
authorities and scientists regarding the nature and scale of the health impact of the accident. 2
Subsequently, the General Assembly in its resolution 62/100 of 17 December 2007 requested theCommittee “to clarify further the assessment of potential harm owing to chronic low-level exposures*among large populations and also the attributability* of health effects”. The Committee addressed thisissue in annex D to its UNSCEAR 2008 Report [U14], and the current report expands on that. Thisscientific annex supports the Committee’s findings on the attribution* of manifest health effects toradiation exposure and the inference* of risk of health effects from exposure to ionizing radiation.
4.
The Committee has not attempted in this annex to rigorously review the latest scientificdevelopments, studies and data on the health effects of ionizing radiation exposure since the publicationof the Committee’s last reviews [U10, U11, U13]. Instead, by synthesizing relevant elements of thephilosophy of empirical science and science-based inference, it has drawn conclusions for the General
Assembly on the attributability of health effects—and the inference of risk of health effects—toradiation exposure. Its principal aim is to help government officials, scientists of different disciplines,
radiation protection professionals and other relevant experts understand the approaches taken by theCommittee, and to promote informed use of the Committee’s findings among all readers of this annex.
5.

The following chapters of the main text address two key issues:(a) Whether a manifest health effect in an individual, or an observed increased frequency of3
occurrence of health effects in a population, can be attributed to radiation exposure;(b) Under what circumstances it is valid to infer risk or to predict absolute numbers of healtheffects following radiation exposure, particularly at levels and for time-courses of exposure forwhich an increased frequency of occurrence of radiation-related health effects has not been
convincingly or consistently observed.

1

Technical terms are explained in a detailed glossary, and are marked with an asterisk (*) the first time that they appear.
Official Records of the General Assembly, Sixty-first Session, Supplement No. 46 (A/61/46).
This annex does not rule out the possibility that at low and very low doses, radiation exposure may have some beneficial healtheffects that could lead to a decrease in the frequency of stochastic effects [U7].

23

22 UNSCEAR 2012 REPORT

6.
There are two appendices for specialists. In appendix A, the Committee describes its approaches
to the above issues:(a) Summarizing the fundamentals of scientific rationale, and the scientific knowledge base as it
relates to the attributability of health effects to radiation exposure;(b) Clarifying the differences between attributing manifest health effects to radiation exposure andinferring risks of future health effects from radiation exposure for both individuals and populations;(c) Addressing whether observed health effects can be attributed to exposures, or risks of healtheffects can be inferred from exposures, when there are competing causes, limited data with large
uncertainties, and biologically plausible* but unproven hypotheses for their development (which isparticularly the case for low-level exposure).
Appendix B provides examples showing the possibilities and limitations of attribution and inference ofrisk for specific exposure situations.
7.
For the purposes of facilitating the discussion of health effects of radiation exposure, theCommittee has adopted a terminology to indicate bands of exposure, expressed as approximate rangesof the fundamental physical quantity, absorbed dose.* The terminology is intended to foster consistentinterpretation of the terms: “high”, “moderate”, “low” and “very low” total doses of low-LET*
radiation (e.g. gamma radiation), additional to those from normal background exposure to natural
sources of radiation (see table 1). The Committee recognizes that scientifically it is the total dose fromboth natural and artificial sources that are of interest, there being no intrinsic difference between thetypes of radiation emitted. However, the focus in this annex is on the sum of the relevant incremental
exposures above that from normal background exposure to natural sources, because that is usually thecharacteristic considered in epidemiological studies (and is also of interest to those who might use theCommittee’s information as the basis for policy and decision-making). This focus, while helpful for
discussing the issues of attribution and inference in this report, does not fully encompass thecomplication of attributing health effects to time-varying radiation exposures.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 23

Table 1. Terminology for bands of radiation dose used in this report
The terminology used here indicates, in only approximate ranges, bands of total absorbed dose (to the whole body or to a
specific organ or tissue of an individual) received in addition to the total from normal background exposure to natural
sources of radiation. The bands of radiation dose do not account for the rate at which the dose is delivered

Terminology fordose bands

Range of absorbed dose for
low-LET radiationa, bScenarios

High

Greater than about 1 Gy

Typical dose (whole or partial body) to individuals after
severe radiation accidents or from radiotherapy

Moderate

About 100 mGy to about 1 Gy

Doses to about 100,000 of the recovery operation workers
after the Chernobyl accident (annex D [U14])

Low

About 10 to about 100 mGyc

Dose to an individual from multiple whole-bodycomputerized tomography (CT) scans

Very lowLess than about 10 mGy

Dose to an individual dose from conventional radiology (i.e.
without CT or fluoroscopy)aThere is clear evidence that the thresholds above which deterministic* effects (see para. 8) occur depend markedly on the rate
at which the dose is delivered. For this reason, the Committee has defined low dose rate* to be less than 0.1 mGy/min when
averaged over about an hour [U6]. The extent to which dose rate plays a role in determining the probability of stochastic effects*
is still a matter of some debate in the scientific community.

b

For deterministic effects following high-LET radiation exposure in this high-dose range, an appropriate value of relative
biological effectiveness (RBE)* needs to be applied (see paragraphs A74 to A75 of appendix A). For stochastic effects following
high-LET radiation exposure at moderate or lower doses, nominal radiation weighting factors, reflecting generic values of RBE,
are used by the radiation protection community to derive the equivalent dose expressed in sieverts (Sv) [I10]. Because of thegeneric nature of the radiation weighting factors, equivalent dose is strictly not appropriate for conducting risk assessment.
c

The terminology used to express ranges of doses of low-LET radiation below 100 mGy as “low” for the purpose of assessing
cancer risks reflects annex A, “Epidemiological studies of radiation and cancer”, of the UNSCEAR 2006 Report [U10].

II. BASIC ASPECTS
8.
Radiation health effects. More than 100 years of radiation research have provided extensive
information on the relationship* between radiation exposure and specific health effects, both in the
short and long term, and many mechanisms that may be relevant to explain the relationship. While theCommittee’s remit is evaluation of scientific knowledge, for which other more appropriateclassifications are used, the internationally accepted framework for radiation protection distinguishes
between so-called “deterministic effects”, now often included under the term “tissue reactions”,* and“stochastic effects” [I10]. For the purposes of this annex, the Committee has also used thisclassification. Deterministic effects are those health effects that are caused by extensive cell death
and/or cell malfunctioning. Examples are acute radiation syndrome, skin burns, epilation (loss of hair)and sterility. These health effects are characterized by a threshold, generally at a high dose, that must be
exceeded before the health effect occurs and by an increase in the severity of the health effect withincreasing dose. In contrast, stochastic effects are initiated by the modification of the genetic materialof only one or perhaps a few cells in a way that is still compatible with cell survival. Examples are solidcancers, leukaemia, and heritable diseases. Such a health effect is characterized by a frequency ofoccurrence in a population that depends on radiation dose, whereas the severity of the health effect, if it

24 UNSCEAR 2012 REPORT

occurs, does not. There are some health effects for which it has not been possible to classify them as
either deterministic or stochastic effects. Examples are circulatory diseases and cataracts. For the
purposes of this annex, they are subsumed under the term tissue reactions.
9.
Scientific method.* For developing explanations for phenomena, scientific method is an important
well-recognized approach. It is based on the assumption that nature follows certain laws, and that byusing certain systematic approaches, these laws can often be revealed. Hypotheses about causation* aregenerated from observations and then tested by controlled experiments or careful observational (that is,other than experimental) studies, leading to better understanding. Modern approaches to the scientificmethod consider multiple plausible hypotheses, all of which are tested with new results of experiments
and observations. Hypotheses that with time no longer explain the information are removed or adjusted,gradually reducing the number of plausible hypotheses. Those that do explain the results may
eventually be deemed proven by the larger scientific community as established scientific fact.
10. Science-based inference. When causation has been sufficiently supported by empirical evidence
and generally agreed by the broad scientific community, inferences can be made that are consideredbased on hypotheses deemed proven. Otherwise, if the evidence and level of agreement by the scientificcommunity are insufficient, inferences cannot be considered as being based on hypotheses that havebeen deemed proven. Nevertheless, it is often possible to make science-based inferences using existing
theory, mathematical models,* expert judgement and plausible assumptions. Such inferences caninform decision-making, provided that assumptions and uncertainties are also communicated. To
distinguish between these situations for the purpose of this report, the Committee refers to inferences
based on hypotheses deemed proven as “well-founded predictions”* and inferences based on
hypotheses currently not deemed proven as “conditional predictions”* (i.e. conditional on the validityof the assumptions about the causal hypotheses made in making predictions).
11. Uncertainties. In testing hypotheses within the scientific method and in making science-based
inferences, an important concept is that of uncertainty,* which describes and may quantify the limits ofknowledge. It is an expression of having doubt, or being unsure, about study results, hypotheses,model-based estimations or results of measurements, and specifically the true value of a quantity ofinterest* (for a detailed discussion see annex B).

III. ATTRIBUTING HEALTH EFFECTS TO RADIATION EXPOSURE
12. Attribution is the action of ascribing an outcome to a cause, that is, in the context of this report, ahealth effect to radiation exposure. 4 A crucial question is whether an outcome would have been
observed, if the assumed cause had not been present, or in the context of this report: if radiation
exposure had not occurred, would the health effect still have occurred? (This concept is dealt with inappendix A under the term “counterfactual analysis”*—paragraphs A10 to A12.)
13. In the context of deterministic effects, one can very often observe many characteristics (e.g.
damage evolution and severity) in a differential pathological diagnosis, so that a health effect in an
individual can be unequivocally attributed to a radiation exposure. In contrast, it is not, at present,
4

Attribution in this annex relates to establishing scientifically the set of conditions that are required to cause an event. It is not
used as a relative concept. Note that the set of conditions may well be one in which radiation exposure is not a sole factor. The
idea of conveying the degree of belief that an outcome was caused by something else is expressed using probability of causation
or more correctly, assigned share (see paragraph 23(c)).

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 25

possible to unequivocally attribute a stochastic effect in an individual to radiation exposure; based on
current scientific knowledge, such a health effect is not distinguishable from one that arises from othercauses. Up to now, no marker has been found that beyond doubt identifies a cancer or a hereditarydisease in an individual as being caused by ionizing radiation, irrespective of dose. Even if a biomarker
could be found that identified a radiation-induced cancer, it would not be able to indicate whether it was
induced by radiation from natural or artificial sources. At low and, now even, very low levels of dose,
there are biological indicators of radiation exposure, such as haematological or cytogenetic
modifications, but these modifications in themselves are not health effects and may not necessarily
result in health effects.
14. If the baseline* frequency of occurrence of a particular type of stochastic effect in a population
were low and the radiosensitivity for a health effect of that type were high (as is the case with somethyroid cancers following exposure in childhood), causation of a health effect in a particular individual
by radiation exposure could be plausible, particularly if that exposure were high. But even then, thestochastic effect in an individual could not be unequivocally attributed to radiation exposure, owing toother possible causes.
15. It is possible, however, to attribute an increase in the frequency of occurrence of stochastic effects
to exposure to ionizing radiation from studies of populations of people. This is done by comparing thefrequency of their occurrence in a population exposed to radiation with that in one that was not
exposed, using epidemiological methods. If the increased frequency of occurrence of the stochastic
effect observed were sufficient to overcome the inherent statistical and other uncertainties (including
those due to possible confounding factors*), the results of the study would provide some evidence forcausation. For example, if the baseline frequency of occurrence of the health effect in a population were
low and the radiosensitivity for the relevant health effect were high, and other factors were accounted
for in the analysis, an increase in the frequency of stochastic effects could, at least, be associated with
exposure to radiation, even when the number of cases were small. Consistent results from several
independent studies of various exposed populations may be sufficient to confidently attribute theincreased frequency of health effects to radiation exposure. However, attribution of a particular healtheffect in an individual within those populations to radiation exposure would still not be possible without
a specific biomarker. Currently, an increased frequency of occurrence of certain health effects can be
confidently attributed to radiation exposure at moderate and high doses, while the confidence decreases
with lower doses. One possible exception might be that of exposure of the fetus: the UNSCEAR 2006
Report [U10] discussed several studies of children exposed in utero in the low-dose range, whichindicated statistical association between increased frequency of childhood leukaemia and the mother’s
exposure to radiation during pregnancy; however whether these associations are causal is still debatedby the scientific community.
16. Increased frequencies of occurrence of heritable disease have been demonstrated in animal studies
involving moderate or high doses; however, they have currently not been demonstrated in humanpopulations exposed to radiation in any range (e.g. even in the children of the survivors of the atomic
bombings in Japan). One reason for this could be that any increased frequency of disease due toradiation exposure would have to be very large to overcome the large fluctuation in the baselinefrequency of these diseases in humans.

26 UNSCEAR 2012 REPORT

IV. INFERRING RISKS AFTER RADIATION EXPOSURE
17. Inference is the process of drawing conclusions from scientific observations, evidence andreasoning in the presence of uncertainty. Two principal approaches for statistical inference are relevant:(a) frequentist inference,* which interprets probability as the limit of relative frequency observed in an
increasingly large number of similar trials; and (b) Bayesian inference,* which interprets probability as
a quantity assigned to represent a state of knowledge or state of belief, and involves a logical process to
update estimates of quantities as new information becomes available.
18. For acute exposure* to high doses above the relevant thresholds, there is sufficient evidence,
knowledge and scientific consensus regarding causal relationships to be able to predict relatively
accurately whether or not there will be a deterministic effect in an exposed individual and, if so, thelikely severity of that health effect. For exposures at moderate or high doses (or more strictly, at doses
at which an increased frequency of occurrence of certain health effects in a population can be
confidently attributed to radiation exposure), there is also sufficient evidence, knowledge and scientificconsensus on causal relationships to be able to predict with some confidence an increased risk ofstochastic effects in an exposed population similar to that for which evidence exists. These predictions
would fall within the group of well-founded predictions, as defined in paragraph 10, and the results are
essentially the same irrespective of the method of inference.
19. There are various obstacles to precisely quantifying risks of stochastic effects after exposure.
These include extrapolating from studies of populations exposed at moderate and high doses, oftendelivered at high dose rates, to estimating risks for other populations with different age and sex
compositions and with different baseline rates* of cancer, exposed to low or very low doses of radiationof different quality, at low dose rates (see annex B). For such situations, Bayesian inference may
provide additional insights.
20. The problem is illustrated in figure I showing plausible dose–response relationships for the risk ofcancer from exposures at very low, low and moderate doses. In the ranges of very low and low doses,
there have been no studies that unequivocally indicate statistically significant increases (or indeed
decreases) in the frequency of occurrence of cancer in epidemiological studies of the general
population). However, the Committee considers that risks are unlikely to change dramatically justbelow the dose levels at which a statistically significant increased frequency of occurrence has been
established. Moreover, a gross underestimation of the risk from low and very low doses using thesevarious plausible dose–response relationships is most unlikely because this would have been detectedby those epidemiological studies that have been conducted.
21. When one studies large groups of people (several tens of thousands of individuals), one may
detect a statistically significant increase in the frequency of occurrence of various cancers following
whole-body exposures to low-LET radiation in the range of moderate doses. However, as the dose
decreases, the power of epidemiological studies becomes less and less, although there may be sensitivesubgroups within the population for which increased frequency of occurrence of specific disease types
might be discernible. Moreover, uncertainties become relatively larger, in part due to deficiencies inknowledge of dose–response relationships and mechanisms for cancer induction. In any case,projections of the absolute number of cancer cases in a population have less and less information value
and can be increasingly misleading at lower and lower doses. As a matter of general practice, theCommittee does not use the risks inferred from studies of populations following radiation exposure at
moderate and high doses to project absolute numbers of radiation-induced cancers following exposure
at low and very low doses.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 27

Figure I. Schematic presentation of plausible dose–response relationships for the risk of cancer inthe ranges of very low, low and moderate doses
The doses in the figure are in addition to the total background exposure to natural sources of radiation. The data points andconfidence intervals* marked on the graph represent observations of increased frequency of occurrence of a specific cancer
type in populations exposed to moderate doses. The various lines represent the following plausible dose–response
relationships for inferred risk of cancer for exposures in the ranges of low and very low doses: (a) supralinear; (b) linear nonthreshold (LNT); (c) linear–quadratic; (d) threshold; and (e) hormetic. These relationships are discussed in more detail in

RISKparagraph A82abc

Baseline frequency ofhealth effectde

ABSORBED DOSE
Very low dose

Low dose

Moderate dose

Typical level ofbackground exposure

22. The considerations addressed in the previous paragraph point to a very basic problem: what canbe done, when the standard requirements for testing hypotheses cannot be fulfilled? Or to put it in thecontext of inference of cancer risk in populations after radiation exposure, the following hypotheses
that would give rise to the following relationships cannot be convincingly verified or falsified at the
moment:(a) The currently observed response in the moderate-dose range can be extrapolated linearly down
to zero incremental dose above that from normal natural background radiation (this would be a
linear non-threshold (LNT) relationship);(b) The risk at low and very low doses is substantially higher than expected from an LNT
relationship (e.g. this would be a supralinear relationship);(c) The risk at low and very low doses is substantially lower than expected from an LNT
relationship (e.g. this would be a threshold or hormetic relationship).

28 UNSCEAR 2012 REPORT

23. When hypotheses cannot be or have not been tested and verified or falsified, three main
approaches are available:(a) Excluding untestable hypotheses from consideration; this is the pure scientific approach, but it
cannot be used when, for example, decisions regarding health protection are required.
(b) Making conditional predictions (i.e. based on hypotheses currently not deemed proven) forrisk estimation. Based on interpretations of available scientific information, scientists can generate
extrapolations and estimates, using science-based models and plausible assumptions, andcharacterize uncertainty (see annex B). Such science-based estimates can then be used to informthe decision-making process.
As an example of this approach, although there is no direct evidence from epidemiological studies
of exposed human populations of an increased frequency of occurrence of heritable effects, theCommittee has inferred risks of such heritable effects following human exposure by making
plausible assumptions based on observations on animals. As another example, public health bodies
may need to allocate resources appropriately, and this may involve making projections of numbersof health effects for comparative purposes. This method, although based upon reasonable but
generally untestable assumptions, could be useful for such purposes provided that it were appliedconsistently, the uncertainties in the assessments were taken fully into account, and it were notinferred that the projected health effects were other than notional.
(c) Incorporating non-scientific concerns. This approach may or may not take account of sciencebased inferences. In this case, decision-makers may take account of norms* external to sciencesuch as social responsibility, ethics, utility, prudence, precaution and practicality of application.
Such considerations, while important, are outside of the Committee's remit, and are mentioned here
only for the sake of completeness.
As an example of these considerations, an LNT dose–response relationship is assumed for the
purposes of radiation protection. However, predictions are conditional on this assumption—theyare based on a hypothesis currently not deemed proven (option (b) above). For pragmatic reasons,the International Commission on Radiological Protection (ICRP) has calculated an average
individual risk by dividing the inferred increased frequency of occurrence of cancer in a populationby the number of exposed people in the population, and has used this concept to help establish
protection criteria, such as dose limits. Moreover its adoption of an LNT dose–response
relationship for the purposes of radiation protection also takes account of the importance of nonscientific concerns, such as practicality of application (option (c) above) [I10].
Another example is the concept of assigned share* (often referred to as “probability of causation”),
used to analyse claims that radiation exposure in the past has caused a specific case of cancer. The
idea is to use conditional predictions for risk estimation (option (b) above) to express a probability(reflecting the inferential weight) that the health effect in an individual occurred as a consequenceof a known exposure. If the calculated value is high, decision-makers may choose to deem thehealth effect to have been caused by radiation exposure (option (c) above). Further discussions onthese issues are given in appendix A.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 29

V. RESEARCH NEEDS
24. In order to improve the ability to attribute health effects observed in individuals and populations
exposed to radiation, and to infer risk from radiation exposure, the Committee emphasizes the need forresearch in the following areas (see also section V in appendix A):(a) The search for a biomarker or a set of biomarkers to allow unequivocal attribution of a specificcancer (or health effect in general) in an individual to exposure to ionizing radiation;(b) Epidemiological studies with complete follow-up of the exposed cohorts over the remainder of
their lives (such as the Life Span Study of the survivors of the atomic bombings in Japan, studies of
persons exposed to radiation for medical purposes as infants or in early childhood, and studies ofworkers who were occupationally exposed to radiation over a period of years), describing any
increased frequency of occurrence of health effects by age and sex and how any increased
frequency varies with different baseline frequencies of a particular health effect;(c) Improvement in scientific knowledge of increased frequencies of occurrence of health effects
in populations exposed to low and very low doses of ionizing radiation experienced chronicallyover time, i.e. at a low dose rate. One approach might be to undertake large-scale epidemiologicalstudies of exposed populations that have a reasonable chance to provide consistent and reliable
evidence for a causal relationship, such as case–control studies on childhood leukaemia. The
Committee recognizes nevertheless that even large-scale epidemiological studies have inherent
limitations, related to statistical variation in cancer rates* in populations and the inability to
account for all the non-radiation causes of cancer, and thus may not be able to provide sufficientevidence that increased frequencies of occurrence of health effects in populations could beunequivocally attributed to radiation exposure when doses are very low;(d) The integration of better physical and biological understanding of radiation actions at low
doses with epidemiological findings of health effects in populations over a range of doses. The
Committee expects four current scientific trends, namely developments in systems biology applied
to radiation actions, molecular epidemiology,* modelling of pathogenesis, and radiation dosimetry
to contribute synergistically to the inference of risks;(e) Better characterization of non-cancer effects that occur in the longer term after protracted
exposures* (such as fibrosis, cataracts and circulatory diseases);(f) The rigorous quantification of uncertainty in such analyses (see annex B); and methods tointegrate and synthesize the results of many studies to better make quantitative and qualitative
statements on the confidence that can be placed in causal relationships, hypotheses and predictions.

VI. SUMMARY AND CONCLUSIONS
25. An observed health effect in an individual could be unequivocally attributed to radiation exposure
if the individual were to experience tissue reactions that are deterministic effects, and differential
pathological diagnosis were achievable that eliminated possible alternative causes. Such deterministic
effects are experienced as a result of acute exposure to high absorbed doses (i.e. about one gray ormore), such as might arise following exposures in accidents or from radiotherapy.

30 UNSCEAR 2012 REPORT

26. Other health effects that are known to be associated with radiation exposure, that is, stochastic
effects, such as cancers cannot, if they occur in an individual, be unequivocally attributed to radiation
exposure, because radiation exposure is not the only possible cause and there are at present no generally
available biomarkers that are specific to radiation-induced health effects. Thus, unequivocal differential
pathological diagnosis is not possible in this case. If, however, the baseline frequency of occurrence ofa particular type of stochastic effect were low and the radiosensitivity for a health effect of that typewere high (as is the case with some thyroid cancers after exposure in childhood) would the attributionof a health effect in a particular individual to radiation exposure be plausible, particularly if that
exposure were high. But even then, the health effect in an individual cannot be unequivocally attributed
to radiation exposure, owing to other possible causes.
27. An increased frequency of occurrence of stochastic effects in a population could be attributed toradiation exposure through epidemiological analysis—provided that, inter alia, the increased frequency
of cases of the stochastic effect were sufficient to overcome the inherent statistical and otheruncertainties. In this case, an increase in the frequency of occurrence of stochastic effects in the
exposed population could be properly verified and attributed to exposure. If the baseline frequency ofoccurrence of the stochastic effect in a population were low and the radiosensitivity for the relevant
stochastic effect were high, an increase in the frequency of occurrence of stochastic effects could atleast be related to radiation exposure, even when the number of cases was small.
28. Although demonstrated in animal studies, an increase in the frequency of occurrence of heritabledisease in human populations cannot at present be attributed to radiation exposure; one reason for this
could be the large fluctuation in the baseline frequency of these diseases.
29. Specialized bioassay specimens (such as some haematological and cytogenetic samples) can beused as biological indicators of radiation exposure even at very low levels of radiation exposure.
However, the presence of such biological indicators in samples taken from an individual does notnecessarily mean that the individual would experience health effects due to the exposure.
30. In general, increases in the frequency of occurrence of health effects in populations cannot be
reliably attributed to chronic exposure to low-LET radiation at levels that are typical of the global
average background levels of radiation. This is because of the uncertainties associated with theassessment of risks at low doses, the current absence of radiation-specific biomarkers for health effects
and the insufficient statistical power of epidemiological studies. Therefore, the Scientific Committee
does not recommend multiplying very low doses by large numbers of individuals to estimate numbersof radiation-induced health effects within a population exposed to incremental doses at levels
equivalent to or lower than normal natural background levels.
31. The Scientific Committee notes that public health bodies need to allocate resources appropriately,
and that this may involve making projections of numbers of health effects (such as cancers) at very low
doses for comparative purposes. This method, though based upon reasonable but untestable
assumptions, could be useful for such purposes provided that it were applied consistently, theuncertainties in the assessments were taken fully into account, and it were not inferred that the
projected health effects were other than notional.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 31

ACKNOWLEDGEMENTS
The Committee would like to acknowledge: W.-U. Müller, who helped develop and integrate material
according to the Committee’s directions; J. Boice, A. González, N. Harley, B. Hofmann, F.O. Hoffman,
C.-M. Larsson and F. Mettler for their contributions; and L. Dobrzyński, P. Jacob, P. Smeesters,
R. Wakeford and A. Wrixon for their critical review and helpful suggestions. The interpretations
expressed remain those of the Committee and do not necessarily represent the views of the experts, orof the United Nations or its Member States.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 33

APPENDIX A. SCIENTIFIC KNOWLEDGE ON HEALTH EFFECTS OF
RADIATION EXPOSURE AND ITS USEI.

INTRODUCTION ................................................................................................................................... 33

II. SCIENTIFIC METHOD, SCIENCE-BASED INFERENCE AND APPLICATION OF SCIENTIFICKNOWLEDGE................................................................................................................................................ 34
A. Scientific method........................................................................................................................ 34
B. Science-based inference .......................................................................................................... 41
C. Summary of basics ..................................................................................................................... 43
III. ATTRIBUTING OBSERVED HEALTH EFFECTS TO RADIATION EXPOSURE......................... 43
A. Deterministic effects.................................................................................................................. 46
B. Stochastic effects ........................................................................................................................ 47
IV. INFERRING RISK OF HEALTH EFFECTS FROM RADIATION EXPOSURE.............................. 53
A. Predicting health effects and inferring risks where hypotheses
regarding causal relationships have been deemed proven........................................ 53
B. Inferring risks where hypotheses regarding causal relationships havenot been deemed proven........................................................................................................ 54
C. Application of science-based inference ............................................................................. 61
V. RESEARCH NEEDS ............................................................................................................................... 63
VI. SUMMARY ............................................................................................................................................. 65

I. INTRODUCTION
A1.
This appendix is aimed at more specialist readers and provides material that underpins theconclusions of the annex. The terminology used is more specialized but the structure broadly follows
that of the main text.
A2.
Section II of this appendix elaborates further on the nature of scientific endeavour in generaland the way in which scientific information, in combination with other inputs, is used by society. The
relevant literature on the philosophy of science has not been reviewed exhaustively. Nevertheless,understanding the way in which science operates and the results of scientific investigation are at thecrux of the subject matter and, thus, the section starts with some more detailed discussion on the

34 UNSCEAR 2012 REPORT

scientific method. The intention has been to provide background that clarifies the distinctions between
information that results from empirical science and the inferences that can be drawn from those results,
which may then, in turn, be used by those concerned with policy matters. A key issue is theretrospective concept of attributing observed health effects to an exposure, and the prospective concept
of inferring risk of health effects from an exposure.
A3.
Section III then summarizes the current scientific knowledge on the health effects of radiation
exposure and the attributability of observed health effects to radiation exposure, distinguishing between
deterministic and stochastic effects. Section IV discusses the basis for making inferences regarding
health effects from an exposure, which can then be used as input for various purposes including
establishing policy.
A4.
While much scientific research on the health effects of radiation exposure has been carried out
over the last 100 years, further refinement and new development in scientific knowledge is essential.
Section V therefore elaborates on the research that the Committee considers necessary in order toimprove the ability to attribute observed health effects to radiation exposure and consequently to refineinferences of the risk of health effects occurring in individuals and populations as a result of radiation
exposure. Finally, section VI summarizes the information provided in this appendix.

II. SCIENTIFIC METHOD, SCIENCE-BASED INFERENCE AND
APPLICATION OF SCIENTIFIC KNOWLEDGE
A5.
Science has been defined as “the intellectual and practical activity encompassing thesystematic study of the structure and behaviour of the physical and natural world through observationand experiment” [C3]. A key scientific endeavour is to investigate causal claims and eventually to
explain them by understanding the mechanisms involved. A fundamental distinction is made here
between this endeavour and the application of that scientific knowledge. Application involves the useof science-based inferences, which may be used as an input to broader decisions that may involve otherconsiderations (e.g. ethics, human rights and practicality).

A. Scientific method
A6.
The scientific method for developing explanations for phenomena (also known as “thehypothetico-deductive method” [B10]) is based on the principle that there is an underlying order to thenature of things, and that by following certain systematic approaches, this nature can often be revealed.
Proposed explanations (hypotheses) for the phenomena are generated from observations and then tested
by controlled experiments or careful observational (i.e. other than experimental) studies, leading tobetter understanding. Empirical science (i.e. science based on observation or experimentation rather
than theory or pure logic) is thus concerned with seeking understanding about nature by systematicallybuilding knowledge in the form of testable explanations and predictions. A scientific hypothesis istherefore a proposed explanation for something that can actually be tested.
A7.
The scientific method proceeds as follows: observations of a phenomenon are made, questions
are asked, one or more hypotheses are formulated to explain the observations, falsifiable* predictions

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 35

5

are made based on the hypotheses, analytical studies are designed to test the hypotheses anddiscriminate between them, the resulting data are collected and analysed, outcomes are evaluated, andpredictions are tested that either support or refute the hypotheses. A better understanding leads to morequestions. Testable hypotheses that are repeatedly refuted must be either modified or rejected, or, if
necessary, additional hypotheses generated, with a view to gradually reducing the number of plausible
hypotheses to explain the phenomenon.
A8.
The scientific method does not operate in isolation, but is conducted by the scientificcommunity, which has specific internal norms to guide the activities of scientists in applying thescientific method. These norms include truthfulness, consistency, coherence, testability, reproducibility,
validity, reliability, openness, impartiality and transparency [T6]. An important aspect of scientificwork is open and transparent publication of details of the methods used and results. The process ofscientific publication should involve critical review, conducted anonymously by impartial peers, of themethods and results. Publication of these details also provides the opportunity for other scientists torepeat, substantiate or challenge work.
A9.
When hypotheses have been tested under a wide variety of conditions (“reproducibility”), andthere is strong evidence and critical argument to generalize the results from the large, but still limited
set of data, and the scientific community reaches a high degree of consensus on the validity of a causal
hypothesis to best explain all the information, the hypothesis may be deemed proven as an established6
scientific fact. When enough experimental results have been gathered in a particular area of inquiry,scientists may propose an explanatory framework that accounts for as many of these results as possible.
If this explanation makes falsifiable predictions with consistent accuracy (“testability”) and is wellsupported by many independent strands of evidence, scientists may adopt this framework as part of abroad “scientific theory”.

1.

Establishing causal relationships

A10.
There are many philosophical approaches to discussing causality and causal relationships (e.g.
see [R2]). For the purposes here, three closely interrelated concepts are relevant to the discussion,
namely (see figure A-I):(a) Causation is the action of producing an outcome. In figure A-I, A (an exposure, event or set of
conditions) is said to be a sufficient cause of the outcome B if, whenever A occurs, B follows. This
concept can be extended to include a probabilistic component that, whenever A occurs, there is acorresponding probability that B will occur;(b) Counterfactual analysis of causation relates to considering a (counterfactual conditional)
question in the form: “If A had not occurred, would B also not have occurred?” Thus it considers
whether there are other possible causes of the outcome of interest;(c) Attribution is the act of ascribing an outcome to a cause. If an outcome B occurs, attribution isthe act of concluding that a previous exposure, event or set of conditions, A, was the cause. If A
were a necessary condition for B to occur (i.e. A uniquely causes B), then B can be unequivocally5

According to critical rationalism as advanced by Popper and dominating the empirical sciences, only hypotheses that can befalsified with a severe empirical test belong to the field of science proper [P4]. Note that falsifiable is used here with the meaningof “being able to be shown/proved to be false”; it does not mean “alter information so as to mislead”.
6
Note while the concept of absolute proof exists in the abstract and can apply in mathematical theorems, in the real world,
hypotheses can only be “deemed” proven, i.e. there is a very high degree of confidence generally in their validity.

36 UNSCEAR 2012 REPORT

attributed to A. If, on the other hand, A were a sufficient cause of B (i.e. other possible events orconditions could cause B), then, by counterfactual analysis, B cannot be unequivocally attributed
to A. The term “attributability” here is used to express the ability to attribute B to A.
Figure A-I. Schematic illustration of the relationships between the concepts of causation,
counterfactual analysis and attribution as used in this annex(i) Attribution is the act of ascribing an outcome B to a cause (event or set of conditions) A, as opposed to another possible
cause. It is therefore retrospective (i.e. looking backwards from outcome to cause). (ii) If A is a sufficient cause of B, it does notfollow necessarily that B can be attributed to A, because other possible sufficient causes could have resulted in B. (iii) The
causation hypothesis can be tested by counterfactual analysis which involves asking, would B have occurred, if A had notoccurred?

Sufficient cause A(event or set of conditions)

Not A(event or set of conditions)(i) Attribution(iii) Counterfactual analysis(ii) Causation

Outcome B occurs

A11.
For example, the poliovirus is the necessary cause of poliomyelitis, and there are no otherknown causes. Thus, a counterfactual analysis would ask, “If exposure to the poliovirus had notoccurred, would a case of poliomyelitis also not have occurred?”. For this example, the answer to thecounterfactual question is clearly that the case of poliomyelitis would not have occurred. Thus, amanifest case of poliomyelitis can be attributed to infection by the poliovirus.
A12.
In contrast, smoking is known to be a cause of lung cancer, but it is not a necessary cause.
Following a counterfactual analysis (“If the patient had not smoked, would a case of lung cancer also
not have occurred?”), one can conclude that a case of lung cancer cannot be attributed to smoking. All
that can be done is to express confidence in a judgement about whether smoking may have caused orcontributed to the manifestation of the cancer.
A13.
Causal relationships in science can best be established by experimentation, where specifichypotheses can be directly tested, with counterfactual conditional questions, under controlled
conditions. Such experiments differ fundamentally from observational (i.e. non-experimental) studies.
In experiments, parameters are deliberately manipulated for the purpose of studying outcomes and thispermits testing and verification of hypotheses and eventually the establishment of causal relationships.
In observational studies, no such manipulation is undertaken and therefore causal relationships aremuch more difficult to establish. For example, in medicine, randomized controlled trials of a new drug
under laboratory conditions would be seen as experiments and may well lead to the establishment of
causal relationships. On the other hand, studies of the health of populations exposed to a hazard(epidemiological studies) are essentially observational in nature and, without the ability to control
relevant parameters and the application of the internal norms of empirical science (e.g. coherence andreproducibility), causal relationships are difficult to establish; a strong association in itself is not

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 37

sufficient to prove causation. A brief recollection of the key features of epidemiological studies of
populations exposed to a noxious agent and their limitations follows (see also annex A of [U10] andannex B to this report for more detailed discussion with respect to radiation exposure).

2.

Epidemiological studies

A14.
For obvious ethical reasons, humans cannot usually be deliberately exposed to a noxious agent
under experimental conditions. Thus, observational (epidemiological) studies are essential if one wishes
to determine the actual health impact of a noxious agent on human populations. To conduct thesestudies, epidemiologists have to take advantage of situations in which populations have already been
exposed or may be exposed in the future to the noxious agent under conditions over which theinvestigators have no control.
A15.
Epidemiological studies can be “descriptive” or “analytical”. Descriptive studies (e.g.
geographical correlation studies, often termed “ecological studies”, in which disease rates based on data
aggregated over geographical areas are compared with aggregated data on levels of exposure to anoxious agent) are conducted to generate hypotheses. The possibilities for bias* and confounding* insuch studies are well known and they cannot be used to evaluate convincingly causal relationships (seeannex A of [U10]). In contrast, analytical studies are conducted to test hypotheses and establish
quantitative relationships. They are commonly of two types: cohort and case–control. In a cohort study,
subjects are selected on the basis of their exposure and then the frequency of occurrence of healtheffects is observed over a period of time. In a case–control study, they are selected on the basis ofobserved health effects and then their exposure is determined.
A16.
Observational studies by themselves rarely establish causality, but rather indicate associations,correlations and trends, for which confidence can be expressed for the fit of various mathematicaldescriptions to the data. A major challenge in observational studies is to balance (a) the chance of
missing an important result or missing a signal against the statistical noise (false negative) with (b) the
chance of wrongly characterizing a spurious result or detecting and modelling the noise as if it weresignificant (false positive) [A3].
A17.
When a statistically significant association is repeatedly found in different and independent
analytical studies, the confidence that a causal relationship exists is increased. When a statisticallysignificant association is repeatedly not found in different epidemiological studies, the confidence that a
causal relationship exists is decreased, although, even then, the absence of an association does notnecessarily imply the absence of a causal relationship. Causal inferences are strengthened when dose–
response gradients are apparent and when the strength of the associations are high.
A18.
Uncertainties. The results of observational studies can be spurious because of uncertainties of
two types: (a) those resulting from chance, also known as “aleatory uncertainties”,* which are due tostochastic (random) variation in observations or measurements (e.g. the statistical power and sample
size is too small to detect the outcome under investigation ([U10] annex A on cancer epidemiology),[I13, N5]); or (b) systematic errors,* also known as “epistemic uncertainties”,* which are due to a lackof knowledge (see also [N2]), and include possible bias (e.g. there is something inherently wrong in the
study design [M1], or there is confounding, i.e. there are other causes—counterfactual conditionalquestions that need to be considered—that could not be adequately accounted for in the analysis [T3]).
A19.
A major source of aleatory uncertainty in epidemiological studies relates to the random
fluctuations in the numbers of health effects observed in any given time interval. This influences theability to discern small changes relative to the baseline frequency of disease occurrence. This problem

38 UNSCEAR 2012 REPORT

is analogous to that of discerning a signal from among the background noise in the physical sciences.
The ability to discern a genuine signal depends on the statistical power, the size of the epidemiologicalstudy and the baseline frequency of disease occurrence. Figure A-II illustrates the difficulty of
discerning an excess relative rate (ERR)* of radiation-induced cancer for different sizes of ideal
cohorts.
Figure A-II. Illustrative example of size of cohort study needed to detect an excess relative rate
The graphic illustrates the minimum detectable excess relative rate (ERR) for ideal cohort studies of two equal population
sizes, assumed to be perfectly matched with no confounding factors or bias [W8]. The baseline incidence rates for the four
disease classes were based on [N1]; the significance level used was 5% and the statistical power 80%; a one-sided test wasused; and the notional studies were assumed to continue for 10 years. The four disease classes considered were (a) all cancers
combined; (b) lung cancer; (c) thyroid cancer; and (d) thyroid cancer diagnosed below age 20 years. The graph shows that for
two perfectly matched populations of 100,000 people, the minimum detectable ERR is around 0.05 for all cancers; for smaller
populations and other cancers the minimum detectable rate is much higher. In practice, the minimum detectable ERR will behigher still because of the difficulty to perfectly match the two populations and to eliminate the effects of confounding factors

STATISTICALLY DETECTABLEEXCESS RELATIVE RATE (ERR)

10000
1000
100
10
1
0.1
0.01
100

1000

10000

1000001000000

SIZE OF POPULATION
All cancers

Lung cancer

Thyroid cancer

Thyroid cancer (under 20y)

A20.
In addition, epistemic uncertainties, such as the presence of “selection bias” and “informationbias” and the ability to account for confounding factors, limit the confidence that can be placed in asignal, even if it is statistically significant (see annex B for further discussion of these sources of
uncertainty). Key to avoiding some of these and other biases that can occur when analysing data is toensure that a protocol be defined in advance of a study, which defines the health outcomes to bemeasured, criteria for measuring disease rates, the baseline frequency to be used, how to account forpeople lost to follow-up, and what statistical tests are to be used [M1].
A21.
Effectively, there is a minimum detectable increase in the frequency of disease occurrence for
epidemiological studies of any realistic size of the study population [D3], below which the chance offinding spurious results becomes ever larger [I13] (essentially any excess frequency of diseaseANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 39

occurrence is in the noise). Nevertheless, there remains a possibility that sensitive subgroups exist
within the population (such as young children or cancer-prone subgroups) for which high excess
relative rates of specific disease types might still be discernible.
A22.
Consequence of multiple comparisons in epidemiological studies. In many epidemiologicalstudies, tests are made for increased frequency of several types of disease simultaneously (the problemof “multiple comparisons” as discussed in section I.F, annex A of [U10]). Consequently, because
statistically significant results can arise by chance alone, the more diseases that are considered in thesame study, the more likely that a statistically significant result can appear by chance, and thus lead tospurious conclusions. Although there are statistical methods that attempt to account for multiple
comparisons [R2], caution is still needed in interpreting any association as causal. Multiple
comparisons are of particular concern in studies when the signal (apparent increased frequency of
disease occurrence) is small compared with the noise (baseline frequency of disease occurrence in the
population studied). For example, one statistical test in twenty will, on average, be statisticallysignificant (at the 5% level) by chance. Furthermore, in a study that considers the frequency ofoccurrence of ten independent types of (for example) cancer, the probability of at least one of thesecancer types having a statistically significant increased frequency of occurrence at the 5% level is about
40% purely by chance alone and thus any such observed increase should not be attributed to radiation
exposure without corroboration [U10]. In order to increase confidence in a conclusion from one study,
additional independent studies are needed that give consistent results.
A23.
Other sources of uncertainty include publication bias, whereby studies that have a positive
result are more likely to be published than ones which do not indicate anything significant. Sometechniques exist to indicate the extent of publication bias [E2, M1]. The Committee itself has to beaware of such possibilities for bias when evaluating published studies and drawing general conclusions.
A24.
There is no generally accepted theory of “provability” to combine the results of many
independent and often disparate studies to establish causation. Nevertheless, the consistency of resultsof many independent studies—epidemiological as well as laboratory experiments, for example, withanimals—coupled with sound biological reasoning can be evidence for a causal association. Confidence
that a factor A (e.g. radiation exposure) might be the actual cause of an observed increase in thefrequency of disease occurrence B (e.g. cancer) can be obtained by application of the “Bradford Hill
guidelines” (table A1). This common-sense approach to judge causality was used in the Surgeon
General’s Report [O1] that concluded that cigarette smoking was a cause of lung cancer, and in reportsof the International Agency for Research on Cancer (IARC) [I2, I3, I5] that concluded that ionizing
radiation was a cause of cancer. These bodies relied most heavily on the consistency of findings in
multiple studies, the strength of the association, whether a dose–response relationship (biologicalgradient) was observed and biological plausibility. These guidelines have been extended in recent
years, particularly in the development of evidence-based medicine [M1].

40 UNSCEAR 2012 REPORT

Table A1. Bradford Hill guidelines
A checklist for assessing evidence of causality [H6]

FactorGuideline

Strength

Strong associations (i.e. large relative rates) are particularly compelling because, for weakassociations, it is “easier” to imagine that another possible cause might be responsible for the
association. However, a small association does not mean that there is no causal relationshipConsistency

Consistent findings observed in different studies, by different investigators, in different places,
circumstances and times, increases confidence in causation

Specificity

Two variants of specificity are (a) that a cause leads to a single outcome, not multiple outcomes;and (b) that an outcome has one cause, not multiple causesa (e.g. polio is caused by thepoliovirus)

Temporality

The cause has to occur first, followed by the outcome, and within a credible timescale, i.e. forcancer the increase does not occur immediately after exposure because there is a minimal
latent period* (interval between exposure and disease manifestation) of a few years

Biologicalgradient

Greater exposure to the hazard should generally lead to larger outcomes. Sometimes the mere
presence of the hazard can trigger the outcome. In other cases, an inverse relation is observed:
greater exposure reduces the outcome at high exposure because of increased cell killing

Plausibility

A plausible biological mechanism between cause and outcome is helpful, although not always
available, owing to limited knowledge

Coherence

Coherence between epidemiological data and generally known facts of the natural history andbiology of the disease increases confidence in causation—e.g. radiation exposure does notcause polio (although it could conceivably increase susceptibility)

ExperimentOccasionally it is possible to appeal to experimental evidence (does the removal of a suspectedfactor change the frequency of occurrence of a specific health effect in a population?),although it is unusual to have genuine experimental evidence available from epidemiologicalstudies of populations exposed to noxious agents

Analogy

Analogy relates to similar types of exposure as the one under study causing similar health effects(e.g. if one type of radiation (e.g. gamma rays) causes a particular cancer, then another type(e.g. neutrons) might also be expected to cause that cancer). Like specificity, it is a relatively
weak guideline and is not often usedaThis aspect of specificity is related to conducting a counterfactual analysis, i.e. whether other causes of the disease under study
can be excluded as alternate explanations for the observed association.

A25.
If the evidence is sufficiently compelling, and consensus among the scientific community sohigh that all reasonable challenges are successfully addressed, then the causal relationship may be7deemed proven as an established scientific fact (such as the link between smoking and increased
frequency of occurrence of lung cancer). After successful counterfactual analysis, an increased
frequency 8 of disease occurrence may thus be attributed to the cause, even if an individual instance ofthe disease cannot be attributed to the cause.

7

As mentioned earlier, hypotheses and causal relationships can only be “deemed” proven, i.e. the scientific community at large
has a very high degree of confidence in them. It cannot be ruled out that, over time, with new information, confidence may fall,
and there may be a need to change the explaining hypothesis and causal relationship.
8
These studies often quote results in terms of risk (e.g. excess relative risk) but in this annex risk is used in a prospective sense(see glossary), and observations are expressed in terms of frequency or rates (e.g. excess relative rates).

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 41

B. Science-based inference
A26.
Inference is the process of drawing conclusions from scientific observations in the presence of
uncertainty. Two principal approaches for statistical inference are relevant: (a) frequentist inference,
where an experiment is considered as one of an infinite sequence of possible repetitions of the same
experiment, each capable of producing statistically independent results. It interprets probability as thelimit of its relative frequency in a large number of trials; and (b) Bayesian inference, which interprets
probability as a quantity assigned to represent a state of knowledge or state of belief, and involves alogical process to update estimates of quantities as new information becomes available.
A27.
If causation has been deemed proven, well-founded predictions (i.e. statements that a
particular thing will happen in the future) can be made (based on experimental evidence, together withestimates of uncertainty) that can be considered as being based on hypotheses that have been tested anddeemed proven. The inferences drawn from frequentist and Bayesian approaches often yield similar
results in terms of confidence in the predictions. Otherwise, if the evidence and consensus are as yet
insufficient to confirm causation, only conditional predictions (i.e. statements that a particular thing will
happen that are conditional on the assumptions and models used in making the predictions) can bemade (again with estimates of uncertainty); these predictions are however based on hypotheses that are
not deemed proven. Bayesian inference is usually preferred over frequentist inference to make suchconditional predictions, because other data and assumptions can be more explicitly incorporated.
A28.
Often, information that a particular agent may be hazardous to human health derives fromexperiments with animals exposed to relatively high levels. As mentioned above, it may not be feasible
to test hypotheses generated from such information through observational (epidemiological) studies ofhumans exposed to that agent, because:(a) The health effects are very difficult to measure for technical reasons;(b) The health effects occur infrequently and thus the number of health effects in an exposed
population is so small (and, correspondingly, the study group would have to be extremely large) inorder to obtain a valid result; a serious problem for an extremely large study is that it is difficult, if
not impossible, to control for bias and confounding factors) [L1, L2];(c) The study design would be unethical (e.g. deliberately exposing people to the noxious agent
without any benefit to them);(d) The studies would take too long (i.e. many years or even several decades).
A29.
Hence, in this case, the crucial internal norms of empirical science of testability (andreproducibility) cannot be fulfilled. Three main alternatives are available:(a) Excluding untestable hypotheses from consideration;(b) Making conditional predictions for risk estimation;(c) Incorporating non-scientific concerns.
A30.
Excluding all untestable hypotheses from consideration. This is the pure scientific approach,but may simply not be an option, if science-based decisions, for example, regarding health protection
are required.

42 UNSCEAR 2012 REPORT

A31.
Making conditional predictions for risk estimation. Based on the available scientificinformation and understanding, it may be possible to generate science-based extrapolations, models andestimates, and to characterize uncertainty. Such science-based estimates can then be used to inform thedecision-making process. The strategy is to apply the scientific method, insofar as this is feasible, inorder to ensure that the knowledge is as well characterized as possible. Even though the underlying
hypotheses have not been (or cannot be) tested and thus some of the traditional internal norms of
empirical science are not respected, the hypotheses still have to be well founded and subscribe to otherinternal norms of empirical science, such as consistency, coherence, openness and plausibility [T6].
A32.
This approach uses science-based models and improves them by incorporating empiricalknowledge (possibly using Bayesian approaches, discussed in detail in annex B). Multiple model
inference has also been used to represent more than one biologically plausible hypothesis (see annex B,
section III.C, paras. 60-61). However, knowledge stemming from these hypotheses, which are currently
not deemed proven, is considered not scientific in the strict sense, because certain internal scientificnorms—testability and reproducibility—cannot be followed. Nevertheless, it has important
contributions to make in the application of science.
A33.
It is important that scientists communicate not only the inferred risk, but also its associateduncertainties and assumptions, and make statements as to the general credibility of the analysis in termsof health outcomes. The work is often performed by the same scientists that otherwise do rigorous
hypothesis testing, and the results are presented in the same (quantitative) way as well-corroborated
evidence on which there is scientific consensus. To avoid confusion, it is crucial to recognize the9special status of these conditional predictions. Unfortunately, the distinction is not always made clear.
A34.
Incorporation of non-scientific concerns. The third alternative—incorporation of non-scientificconcerns—may or may not use conditional predictions. In this case, account is taken of norms external
to science such as social responsibility, ethics, utility, prudence, precaution and practicality of
application. The use of such approaches is outside of the Committee’s remit, but, for the sake of giving
context to the discussion, some of the approaches are mentioned here. They include:(a) Prioritizing hypotheses: Although it may not be feasible to test a hypothesis, knowledge of
mechanisms, models, and inferences may make one hypothesis more plausible than another;(b) Assuming a consequence: A health effect can be assumed to be a consequence of exposure to anoxious agent when a defined set of criteria are satisfied;(c) Precautionary approach: The precautionary approach can be described in the following way:
“When human activities may lead to morally unacceptable harm that is scientifically plausible but
uncertain, actions shall be taken to avoid or diminish that harm” [C4, E1, G2, H4, H7, H8, J4, J5,
T1, W9]. In some situations, however, where it is not possible to know whether there is a positiveor negative impact from exposure to a hazard, it may be important to consider the consequence offalse positive as well as false negative assumptions when making decisions.

9

Popper defined hypotheses that were not testable or falsifiable as “non-science” [P4]. Weinberg coined the term “trans-science”
to be “questions that can be asked of science, but cannot as yet be answered by science” [W4].

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 43

C. Summary of basics
A35.
The relationship between scientific method, science-based inference and the application ofscience is illustrated schematically in figure A-III. A clear distinction is made between (a) what resultsfrom hypotheses in empirical science that can be deemed proven—and thus what can be attributed to aparticular cause; (b) what can then be a well-founded prediction (i.e. stated with confidence that, under
defined conditions, a particular thing will happen in the future); and (c) what conditional predictions
can reasonably be made based on scientific evidence but for which the underpinning hypotheses are
currently not deemed proven.
Figure A-III. Relationship between scientific method, science-based inference and applicationof science
The specific internal norms that guide the activities of scientists in applying the scientific method include truthfulness,consistency, coherence, testability, reproducibility, validity, reliability, openness, impartiality and transparency [T6]

Scientific method
Formulate question to
explain observations

Refine set ofplausible
hypotheses

Plausible hypotheses
to explain observations

Ethical considerations

Science-based
inference

PredictionsnoSufficientevidence andconsensus?

Stages where uncertainty
needs to be considered

Causal hypothesis deemed
proven and observableoutcomes attributable to cause

yes

yes

incorporating
non-scientificconcerns

Well-founded predictions(based on hypotheses
deemed proven)

Applicationof science
Conditional predictions
noTestable?

no(based on hypotheses currently
not deemed proven)yes

Refute?

Testing and analysis

Exclude fromconsideration(including counterfactual
considerations)

All internal norms of science must be applied

III. ATTRIBUTING OBSERVED HEALTH EFFECTS TO RADIATIONEXPOSURE
A36.
More than 100 years of experimental radiation research have provided extensive informationon the mechanisms by which radiation exposure can lead to health effects. Radiation exposure can haveactions at the level of molecules, chromosomes, cells, tissues, organs and complete organisms. The
main subcellular targets for radiation damage are the DNA molecules residing in the chromosomes. The
damage might be directly within the DNA molecule (such as strand breaks or modification of44 UNSCEAR 2012 REPORT

nucleotides) and/or epigenetic effects (like alterations of gene expression). While the damage is usually
repaired, the integrity of the DNA may not always be restored perfectly, which can cause the cell to die.
Alternatively, viable cells may survive with DNA mutations that affect cellular behaviour.
A37.
Some cellular changes following radiation exposure may ultimately result in observed healtheffects, but some may not. For example, radiation can induce chromosomal aberrations in circulating
white blood cells that may not result in observable health effects in the individual (see paragraph A50).
Moreover, the killing of a small number of cells is unlikely to result in health consequences. On theother hand, extensive death of stem and progenitor cells in various tissues after high doses of ionizing
radiation causes observed health effects, such as severe haematopoietic or gastrointestinal damage, skinburns and ulcers. These so-called “deterministic effects” usually occur within a short time (hours ordays) after the exposure, although they can occur later in life. Deterministic effects typically occur after
acute exposure to high doses, in excess of a “threshold” dose, with the severity of the health effectincreasing with the dose above this threshold dose. They result from the depletion or the malfunctioningof a sufficient number of cells to cause observable damage to the organ or tissue, and, if the damage
interferes with critical functions of the body, they can lead to the death of the individual—for example,
about half of a healthy adult human population would die within 60 days, if exposed to an acute wholebody dose of 4 Gy of gamma rays and no medical care were given. There are well-documented
observations of deterministic effects in the scientific literature, primarily on people accidentally
exposed to high doses of radiation [U5, U14].
A38.
If a damaged cell is not killed or otherwise rendered inactive, DNA mutations may betransmitted to the cell’s progeny and, ultimately, it is believed, result in observed health effects in theindividual. If mutations in genes in somatic cells lead to initiation, promotion and/or progression ofmalignant cells, cancer may develop in the tissue or organ of the individual. Such cancers may occur along time (many years) after exposure. An increased frequency of occurrence of some cancer types has
been observed in epidemiological studies of populations exposed to moderate doses of radiation [U10].
If the mutations are in germ cells (namely, those that transmit genetic information to an offspring of theindividual), this may result in heritable health effects in an offspring. The possibility of heritable healtheffects has been demonstrated in animal studies [U9]. However, extensive studies of the children(resulting originally from the germ cells) of survivors of the atomic bombings in Japan and of thechildren of patients treated with radiotherapy have not been able to discern a statistically significant
increased frequency of occurrence of heritable effects [U9].
A39.
Because the frequency of occurrence, rather than the severity, of the health effect is related tothe exposure characteristics, these health effects—cancer and heritable effects—are termed “stochastic
effects”. At moderate doses, the frequency of occurrence of certain cancers in an exposed population
appears to increase with increasing radiation dose, while at higher doses, the rate of change of
frequency per unit dose decreases because of the competing influence of cell killing or sterilization(annex F [U5], annex A [U10]). A critical point is that, at present, there is currently no way of
distinguishing pathologically whether or not a specific observed cancer in an individual is caused bythat person’s exposure to radiation.
A40.
The classification of harmful health effects from radiation exposure into deterministic andstochastic is summarized in table A2. This classification, while not entirely appropriate from a purely
scientific perspective, is made because the Committee has used the terms previously and they arewidely used for the purposes of health protection. The scientific evidence for these health effects is
discussed in the following paragraphs.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 45

Table A2. Features of deterministic and stochastic effects [U2, U3, U6, U8, U9, U10, U11, U14, U15]
FeatureDeterministic effecta

Initiatingradiation actionb
and presumed
biologicalmechanisms

Radiation-induced killing or loss offunction of many cells
simultaneously at the tissue level

Radiation action on a single cell

Manifestation

Health effect occurs following acuteexposure above threshold values ofdose. The severity of the healtheffect increases with dose above thethreshold values

The probability, but not the severity, of the healtheffect is related to the dose, the exposure conditions
and characteristics of the individual exposed, inparticular, the sex of the individual exposed and theage at exposure; in addition, there are people who
may be genetically predisposed to such health effects

ExamplesNon-cancerous skin lesions (such as
erythema, burns, dry or moist desquamation), the radiation syndromes(cutaneous, haematopoietic,
gastrointestinal, and central nervous
system), epilation; impact on fertility;
congenital malformations and mental
retardation after in utero exposure

Cancers which individually are indistinguishable fromthose arising from other causes

Evidence

Direct robust evidence from theresponses of patients undergoingradiotherapy and of individuals who
have received high exposures as aconsequence of radiological accidents

Direct evidence mainly from statistically significant
increases in frequency of occurrence of various
cancers in populations exposed to moderate or highdoses. There are statistical limitations & confounding
influences that hinder demonstrating health effects at
low levels of exposure

Results of experiments on animals

Stochastic effecta

The cell with a radiation-induced transformation must
survive and may need to undergo further transformations to lead to a cancer or heritable disease

Heritable health effects demonstrated in animalstudies at high doses, but not in human populations
Scientificconsensus

High degree of consensus on how
radiation induces tissue damage;some understanding of repair
mechanisms with timeMore scientific debate about latehealth effects

A degree of consensus on role of DNA mutation. Cancer
development is believed to proceed in a multistep
fashion. Other factors, such as adaptive response,* impact
on the immune system, genomic instability,* andbystander effects,* may also modify development. These
factors may not be relevant at moderate/high doses(because they are integrated into the exposure–response
relationship evaluated in epidemiological studies), but
their roles at low and very low doses are the subject ofscientific debate [U7, U15]
Consensus that heritable health effects in humans areplausible, but at a much lower frequency than the
induction of cancer in the population exposeda

Deterministic effects appear relatively soon after exposure, and not as a result of doses accumulated from chronic low-dose-rate exposure.
Because they involve major loss of cell function within a tissue, they are also referred to as “tissue reactions” [I10]. However, tissue reactions
also include some health effects (such as cataracts and fibrosis) that are not determined solely at the time of irradiation but can be modified
after radiation exposure. Historically, radiation-induced cataracts were considered to be deterministic effects with relatively high thresholddoses. Recent studies have suggested a much lower threshold dose (0.5 Gy) than previously thought [I11] and even the possibility of a nonthreshold response has been raised [A1]. Similar uncertainties for diseases of the blood circulatory system after radiation exposure have also
been raised [I11, N2]. For scientific purposes, Hulse and Mole had proposed alternative terminology: “polycytic effects” (for deterministic
effects) and “haplocytic effects” (for stochastic effects) [H9], although such terminology is rarely used.

b

The Committee distinguishes here between “radiation actions”, meaning all modifications induced in an organism, and “healtheffects”, meaning observed health disorders with recognizable symptoms.

46 UNSCEAR 2012 REPORT

A. Deterministic effects
A41.
There is a significant and robust body of scientific evidence about the occurrence ofdeterministic effects at high doses (table A3). Such health effects often have a progression ofcharacteristic signs and symptoms, which facilitate discrimination between radiation exposure and othercauses as the principal causing agent. There is a high degree of consensus among specialists on thisbody of knowledge and its interpretation [I11, U5]. Professionals, nevertheless, need to have a solid
knowledge of the specific signs and symptoms that occur after radiation exposure in order to be able toattribute a deterministic effect in an individual to radiation exposure [G4].
Table A3. Approximate threshold doses for deterministic effects from acute exposure of adults to
low-LET radiation
These examples have been selected to illustrate the approximate levels of dose that cause deterministic effects in adults andthe associated time for the health effects to develop. The threshold doses were derived by the International Commission on
Radiological Protection (ICRP) for radiation protection purposes [I11]

Health effectOrgan/tissue

Time to develop

Acute exposure (Gy)

MORBIDITYa
Temporary sterility

Testes

3–9 weeks~0.1

Permanent sterility

Testes3 weeks~6

Permanent sterility

Ovaries<1 week~3

Depression of haematopoiesis

Bone marrow

3–7 days~0.5

Main phase of skin reddening

Skin (large areas)

1–4 weeks<3–6

Skin burns

Skin (large areas)

2–3 weeks

5–10

Temporary hair loss

Skin

2–3 weeks~4

Acute pneumonitisLung

1–3 months

6–7

MORTALITYab

Bone marrow syndrome

Bone marrow

30–60 days

~1 c

Gastro-intestinal syndrome

Small intestine

6–9 days~6 cPneumonitisLung

1–7 months

7–8

Derived by ICRP on the basis of approximately 1% incidence of morbidity or dysfunction in tissues and organs in adults.

b

Derived by ICRP on the basis of approximately 1% incidence of mortality in adults.

cAssuming no medical care.

A42.
For severe deterministic effects, many cells have to be either functionally inactivated [B4] orkilled [F4]. Such a major impact on a tissue or the whole organism can be achieved only by absorbed
doses typically in the high-dose range and delivered acutely. Many deterministic effects occur shortly
after radiation exposure, frequently within a few days or months, so that a link between exposure andhealth effect is evident. Further, in general, these health effects rarely occur without radiation exposure.
The sequence of events is informative: for example, in the case of skin damage, this can start withreddening of the exposed area of skin, followed by itching and skin breakdown within a few weeks, andnon-healing ulceration at about 6–12 months. Thus, severe deterministic effects appearing soon after
high-dose exposure can, in principle, be diagnosed in an exposed individual by a radiation expert andthe health effect can be attributed to the high exposure with a high degree of confidence.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 47

A43.
However, at moderate doses and at longer times after exposure, individual cases of diseases
such as fibrosis, cataracts and circulatory diseases that may be deterministic effects of radiation
exposure cannot be attributed to radiation exposure. This is because (a) clinical diagnosis andpathological findings for such health effects cannot discriminate between radiation and other causes atthe present time; (b) the baseline frequency of these diseases is high; (c) there are many other possible
causes of these diseases; and (d) there are no characteristics that are specific for radiation (i.e.
biomarkers).
A44.
In the case of cataracts and circulatory diseases, it is currently unclear whether or not a dosethreshold exists and whether the amount of damage is dependent on dose. According to the most recent
findings, cataracts, which have a high baseline frequency, are not typical deterministic effects as was
originally thought [A1].
A45.
Because of the well-known and readily observable consequences of high doses, radiation
experts may in many cases confidently attribute a particular deterministic health effect to acuteradiation exposure (and attest as such). In attributing, radiation experts must nevertheless still be able toeliminate possible alternative causes (i.e. by conducting a counterfactual analysis). Case studies I and II
in appendix B illustrate some of the challenges facing radiation experts in attribution, even for
deterministic effects.

B. Stochastic effects
1. Prospects for attribution of an observed stochastic health effect in an
individual to radiation exposure
A46.
In contrast to deterministic effects, the occurrence of a stochastic health effect depends ontransformation, that is, on the modification of a cell that changes its original characteristics without
preventing its proliferation. There are known to be several agents that can initiate such atransformation, and the relatively high baseline rates of cancer and heritable effects in an unexposed
population provide evidence that there are many possible causes. What is critical for discussing
attributability is whether a stochastic effect caused by radiation exposure can be distinguished from one
that is not caused by radiation exposure (i.e. applying counterfactual analysis). A number of avenues
need to be explored.
A47.
Firstly, there is no doubt that genetic predisposition to contracting cancer exists. Various
diseases with congenital chromosomal aberrations and genetic diseases are associated with increased
frequencies of either very specific types of cancer or with a general increase of all types of cancers (fora comprehensive review see [I6]). Some very prominent examples are: (a) Down’s syndrome (increased
frequency of childhood leukaemia [D5]); (b) ataxia telangiectasia (increased frequency of acutelymphoblastic leukaemia [T4] and other cancers [M3, S2]); and (c) xeroderma pigmentosum (increased
frequency of melanoma due to exposure to ultraviolet radiation [K4]). Some of these diseases, such as
ataxia telangiectasia, are characterized by an increase in cancer frequency, but also by an enhanced
radiosensitivity resulting in severe side effects after radiotherapy [P3]). However, even if someone withataxia telangiectasia, for example, contracted acute lymphoblastic leukaemia following radiation
exposure, the leukaemia could not be unequivocally attributed to the radiation exposure.

48 UNSCEAR 2012 REPORT

A48.
Individual radiosensitivity is not confined to those with congenital chromosomal aberrations
and genetic diseases, but is a general phenomenon. As individual radiosensitivity is very important inradiotherapy, many studies have looked for ways to assess the radiosensitivity of individual patients
before radiotherapy [B5, C5, T5]. However, many factors are involved, and it is unlikely that thedetermination of a single factor would be sufficient. In addition, it is still a matter of discussion whichcell type and end point is suitable for a test of individual radiosensitivity. Even then, if suitable factors
could be identified that could be applied to exposures substantially below those received inradiotherapy, it would still not be possible to use them to attribute a manifest cancer in an individual toradiation exposure.
A49.
Epidemiological studies combined with information from radiobiological studies and someunderstanding of the mechanisms involved in the induction of cancer following radiation exposure havebeen successful in determining the radiosensitivity of certain groups to developing a particular cancer.
Only if the baseline frequency of a particular type of stochastic effect were low and the radiosensitivity
for a health effect of that type were high would the attribution of a health effect in a particular
individual to radiation exposure be plausible, particularly if that exposure were high. For example, for achild who contracted papillary thyroid cancer about three or more years [H5] after receiving a high doseto the thyroid from exposure to radioiodine in the months after the Chernobyl accident, then attributionof the thyroid cancer to the high dose to the thyroid may be plausible [W7]. But even then, the healtheffect in an individual cannot be unequivocally attributed to radiation exposure, owing to other possible
causes (recognizing that radiation may not act as a sole cause, but as a contributory factor in the
manifestation of disease). In order to attribute a cancer in an individual to radiation exposure, it would
be necessary to establish some marker that specifically serves this purpose.
A50.
Another avenue to consider is that of biological indicators of radiation exposure, such as thosesummarized in table A4. However, these indicators only provide a means of determining radiation dose;
again, they do not guarantee that a health effect will subsequently manifest in the exposed individual ordescendants. Furthermore, none is uniquely associated with radiation exposure. Consequently, theycannot be used to attribute a manifest cancer in an individual to exposure received previously.
A51.
Up to now, no biological indicator has been found that is able to uniquely identify radiationrelated cancers or heritable effects and thus could be used as a biomarker. If such a biomarker could befound, it would greatly improve the ability to attribute a stochastic health effect in individuals toradiation exposure. There are, however, techniques available that can be used to attribute cancers tochemical inducers (e.g. by an analysis of DNA adducts [F1]) or to ultraviolet radiation [B12]. These
techniques are valuable in the sense that if a specific cancer can be unequivocally attributed to anotheragent, then ionizing radiation can be ruled out as the cause of this health effect.
A52.
Thus, in conclusion, a manifest stochastic effect in an individual cannot be unequivocallyattributed to radiation exposure, because radiation exposure is not the only possible cause and there areat present no generally available biomarkers that are specific to radiation exposure. Unequivocal
differential pathological diagnosis is not possible in this case.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 49

Table A4. Biological indicators of radiation exposure
Lowest dose range
detectable in individuals
after acute exposurea(Gy)

Comment

Reference

Reduction in numbers of lymphocytes. Early
response to radiation exposure[F3]

depends on the end
point;b 0.05 to 2

Allows quantification of partial-body
exposure[H2]

Dicentric chromosomes

0.05–0.1

Some chemicals also cause dicentricchromosomal aberrations[I1]

Reciprocal translocations

0.3–0.5

Useful to assess radiation exposures that
occurred a long time previously[T9]

Micronuclei

0.1–0.3

Sometimes important for monitoring many
people within a short time interval[M5]

Chromosomal breaks thatare identified in prematurely
condensed chromosomes

0.1–0.5

This indicator does not require a metaphasefor expression, so that selection againstheavily damaged cells does not occur[H3]

Valuable in the context of determination of
repair capacity of individuals[M6]

The most sensitive biological indicator
found up to now[S3]

Biological indicator

Blood cells
Hair

0.5–1

Comets c
γ-H2AX foci

0.003

a

The doses quoted give only a crude idea of the lowest dose range where radiation actions can be detected, because many factors
play a role (e.g. how many events are scored, how experienced are the scorers, and whether scoring is conducted manually orwith assistance from a computer).

b

End points are: chromosomal aberrations in the epithelium of plucked hair, apoptotic cells in the follicle (very sensitive),
dysplastic hair, and width of the hair. Unfortunately, the most easily accessible indicators (dysplastic hair and hair width) are theleast sensitive to dose (1 to 2 Gy).

c

Comets are not very suitable for the determination of radiation dose, because the DNA damage is repaired comparatively
quickly. Comets are useful, however, as indicators of repair capacity after in vitro exposure of cells with about 2 Gy and trackingof the speed of repair for about 3 hours.

2. Prospects for attribution of an observed increased frequency ofoccurrence of a stochastic health effect in an exposed population toradiation exposure
A53.
Specifically in the context of radiation exposure, observational (epidemiological) studies have
involved a wide range of populations previously exposed to radiation for various reasons (e.g. exposure
to natural sources of radiation, and to artificial sources, such as in military operations, in medicine,
occupationally or accidentally). Descriptive studies can identify a possible association for further study.
However, analytical epidemiological studies are the primary scientific tool used to critically examine
whether exposures to radiation increase the rate of occurrence of specific diseases. Examples ofanalytical studies that have provided information on the causal association between radiation exposureand frequency of occurrence of health effects include the Life Span Study of the survivors of the atomic

50 UNSCEAR 2012 REPORT

bombings in Japan, children exposed to radiation in the course of treatment for medical conditions,
underground miners exposed to radon and its progeny, and patients who underwent radiotherapy.
A54.
In quantifying the increased frequency of occurrence of cancer in an exposed population, theCommittee has relied heavily on the results of epidemiological investigations (see, for example,
figure A-IV). The Committee’s latest evaluations of the relevant epidemiological studies of exposed
populations were published in its UNSCEAR 2006 Report [U10]. These demonstrate statisticallymeaningful increases in the frequency of occurrence of certain cancers in populations exposed tomoderate or high doses. They also provide quantitative estimates for the magnitude of those increases.
A55.
Although radiation exposure is an established cause of cancer, there are a number of cancer
types that have not been convincingly shown to be caused by radiation exposure. These include cancersof the rectum, prostate, pancreas and uterine cervix, and Hodgkin’s lymphoma and chronic lymphocytic
leukaemia. This does not necessarily mean that radiation-induced transformations do not occur in thosetissues. For example, latency periods* might be so long that the cancers do not become manifest during
lifetime (in a sense, a practical threshold) or the frequency of radiation-induced cancers in those tissues
might be too low, relative to the baseline frequencies for those cancers, to be observable.
A56.
Applying counterfactual analysis to the attribution problem for a population implies
consideration of the question: if a population had not been exposed to radiation, would an observed
increased frequency of occurrence of disease have been observed at the same time and of the same
magnitude. As mentioned earlier, there is no generally accepted theory of provability to establish
causation. Nevertheless, increased frequencies of occurrence of certain stochastic health effects in a
population can be attributed to exposures in the moderate- and high-dose range when the evidence iscompelling and consensus among the scientific community is high, in part by use of the Bradford Hill
guidelines (table A1) and more recent developments [M1]. This can nevertheless be challenging
because: (a) latent periods for cancer development are long; and, as mentioned earlier, (b) the baselinefrequency of cancer occurrence and the variability* of that frequency with time are relatively high, andother uncertainties in both exposure and disease frequency estimation obscure any increased frequencyof occurrence of disease in a population that might be due to radiation exposure, in particular, following
exposure at low and very low doses (see annex B for detailed considerations of uncertainties).
A57.
Knowledge of minimum latent periods, that is, the time interval between radiation exposureand the first possible diagnosis of a health effect, is important. In adulthood, the shortest latent period
for leukaemia is around two years, and for solid cancers, a period of eight to ten years is frequently
quoted (annex G [U8]). Nevertheless, a cancer that is diagnosed, for example, one month after radiation
exposure definitely cannot be caused by such an exposure. The shortest latent periods have been seenfor some types of cancer in children, typically a few years (annex I [U8], annex B [U16]). However,latent periods strongly depend on diagnostic capacities. With more sophisticated techniques that
identify a solid cancer at a smaller size, latent periods will apparently shorten.
A58.
Radiobiological experiments have established various causal relationships between radiation
exposure and resulting actions in biological material. Epidemiological investigations have identified an
association between an increased frequency of occurrence of many types of cancer and radiation
exposure [U10]. However, there is not a complete understanding of how to combine the radiobiologicaland epidemiological information. Further, the various mathematical models that attempt to describe theradiobiological mechanisms are unable to quantify or describe a priori the increased frequency ofcancer seen in human studies, especially following relatively low-dose exposures [D3, M2].

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 51

Figure A-IV. Observed increases in the frequency of mortality from site-specific solid cancers among
the survivors of the atomic bombings of Japan
This graphic adapted from Ozasa et al. [O4] is used here to illustrate observed excess relative rates per unit dose and theassociated aleatory uncertainties at 90% confidence intervals. The uncertainty associated with extending the excess
frequency observed among a living cohort over the rest of their lives is an example of epistemic uncertainty. The values forrectum, pancreas, uterus, prostate, kidney parenchyma and malignant lymphoma, while positive, are not statisticallysignificant. An increased frequency of mortality from cancers in these organs cannot be ruled out, but there is no compelling
evidence from this study to support causation. The arrows indicate confidence intervals that are beyond the limits of thegraph or not specified

Cause of death
All causes
All solid cancer
Cancers of specific sites
Oesophagus
StomachColon
RectumLiver
Gall bladder
Pancreas
Other digestive system
Lung
BreastUterus
Ovary
Prostate
Bladder
Kidney parenchyma
Renal pelvis and ureter
Other solid cancer
Lymphoid and haematopoietic malignancies
Malignant lymphoma
Multiple myeloma
Other neoplasms

52 UNSCEAR 2012 REPORT

A59.
Uncertainties in dose estimation. There are both aleatory and epistemic uncertainties in themeasurements used in estimating doses. The aleatory uncertainties are particularly important when thelevels of exposure are close to those that are typical from natural sources of radiation. For example, thestochastic nature of radioactive decay is inevitably reflected in any measurements of count rate or dose
rate. Studies that investigate possible health effects from exposure at these very low levels are rarely, if
ever, able to account for all the uncertainties in the dose estimation, and usually interpretation of theresults depends on making reasonable but untested assumptions. Annex B discusses the questions of
uncertainties (both aleatory and epistemic) in dose estimation in more detail.
A60.
Uncertainties in frequency estimation. It is extremely difficult to detect excess frequency ofoccurrence of cancer and heritable effects by studying population exposures limited to low dose andvery low doses [I9]. This is because, at low doses and, in particular, at very low doses, the plausible
increased frequency of occurrence of stochastic effects is normally dwarfed by statistical and othervariations in the baseline frequency of their occurrence. As a result, extremely large sample sizes(typically millions of people) would theoretically be required in these dose ranges for a statisticallysignificant increase in frequency to be observed. The zone of noise depends primarily on the number ofsubjects in the population studied and the baseline frequency of incidence of the specific disease (seefigure A-II earlier). However, because factors such as age and sex are apparently very important indetermining the frequency of occurrence, it is important that the populations must be relatively
homogeneous with regard to age and sex, or else these factors taken into account in analysis. Even then,the estimate would often be untrustworthy because of the lack of knowledge of, and thus inability toadjust for, other possible risk factors such as diet, genetic susceptibility, other environmental exposuresand other demographic and lifestyle factors [L1].
A61.
For rare diseases and highly radiosensitive subgroups of the population, for example, thyroid
cancer following exposures in early childhood, a smaller sample size might be sufficient for astatistically meaningful increase to be detected than that required for a more common disease at older
ages. Childhood leukaemia is also thought to be particularly susceptible to induction by radiation. Somestudies of in utero radiation exposure have reported associations with leukaemia and other childhood
cancers at doses from the use of X-rays estimated from historical literature to be of the order of 10 mGy[D4, W2] and the excess relative rate per unit dose for childhood leukaemia reported in the largest ofthese studies was comparable to that derived from the survivors of the atomic bombings in Japan
exposed to higher doses as young children [W1, W3]. However, the conclusions of these studies are notaccepted by many in the scientific community, and the causal nature of the association with low-dose
prenatal X-ray examinations is still much debated [B11, I5, I8].The case of in utero exposure illustrates
the difficulty in interpreting—and obtaining scientific consensus on the interpretation of—reported
increases in frequency when exposures are in the low-dose range, even when the populations exposed
are large and assumed to be particularly radiosensitive.
A62.
In summary, an increased frequency of occurrence of stochastic effects in a population could
be confidently attributed to radiation exposure—provided that, among other things, the increased
frequency of occurrence of the stochastic effect were sufficient to overcome the inherent statistical andother uncertainties. In this case, an increase in the frequency of occurrence of stochastic effects in the
exposed population could be properly verified and attributed to exposure. If the baseline frequency ofoccurrence of the health effect in a population were low and the radiosensitivity for the relevant
stochastic effect were high, an increase in the frequency of occurrence of stochastic effects could atleast be related to radiation, even when the number of cases was small.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 53

A63.
Although demonstrated in animal studies, an observed increase in the frequency of occurrenceof heritable disease in human populations cannot at present be attributed to radiation exposure; one
reason for this is the large fluctuation in the baseline frequency of occurrence of these diseases.

IV. INFERRING RISK OF HEALTH EFFECTS FROM RADIATIONEXPOSURE
A64.
This section considers drawing inference from the existing scientific knowledge base (seefigure A-III), specifically to make inferences about the risk of future health effects either for a
population or an individual exposed to radiation. As discussed earlier (section II.B of this appendix),
two main situations are considered: (a) where hypotheses regarding causal relationships have been
deemed proven (i.e. well-founded predictions); and (b) where hypotheses regarding causal relationships
have currently not been deemed proven (conditional predictions).

A. Predicting health effects and inferring risks where
hypotheses regarding causal relationships have been deemed
provenA65.
For exposure to high acute doses above the relevant thresholds, there is sufficient evidence,
knowledge and scientific consensus regarding causal relationships to be able to predict relatively
accurately whether or not there will be a deterministic effect in an exposed individual and, if so, thelikely severity of that health effect. Such predictions have been sufficiently well tested in observationsof the consequences of past high-dose accidental exposure such that they can be based on hypotheses
regarding causal relationships that have been deemed proven and therefore can be regarded as valid.
Thus, for example, physicians, on the basis of knowledge of the distribution in local tissue of the dose
received in an accident, can determine with reasonable confidence the evolution of necrosis and, as aconsequence, any surgical or other mitigating interventions needed. (This is not the case with thosetissue reactions for which the deterministic nature is unclear, such as cataracts and circulatory diseases.)
A66.
For exposures at moderate or high doses (or more strictly, at doses at which an increased
frequency of occurrence of stochastic health effects has been observed in a population), there is alsosufficient evidence, knowledge and scientific consensus on hypotheses regarding causal relationships tobe able to predict with some confidence an increased risk of such stochastic effects in an exposed
population similar to that for which evidence exists, based on so-called “frequentist inferences”. Again,such predictions can be regarded as well-founded.

54 UNSCEAR 2012 REPORT

B. Inferring risks where hypotheses regarding causal
relationships have not been deemed proven
A67.
As discussed earlier in section II.B of this appendix, for the cases where the crucial internal
norms of empirical science (reproducibility and testability) cannot be fulfilled, three main alternatives
are available: (a) excluding all untestable hypotheses from consideration; (b) making conditional
predictions for risk estimation; and (c) incorporation of non-scientific concerns. While approach(a) could be argued to be the pure scientific approach, this is not an option, if science-based decisions,10for example, regarding health protection are required, and it is not considered further here. This
subsection now discusses matters related to approach (b), making conditional predictions for risk
estimation. Approach (c), incorporation of non-scientific concerns, is discussed in the next subsection,
application of science-based inference.
A68.
With regard to approach (b) on making conditional predictions for risk estimation, there are anumber of issues in extending the data from epidemiological studies to situations other than those underwhich the data were obtained. These include: (i) extrapolation of risks over lifetime, (ii) transference toanother population; (iii) transference from one type of radiation to another; (iv) inferring risks fromlow-dose-rate exposure and (v) inferring risks from low and very low doses.
A69.
These inferred risks of cancer are for a population. There are problems in applying them to anindividual within a population. Firstly the concept of relative frequency has no meaning for theindividual (the outcome for the individual is either that the health effect occurs or it does not). Average
individual risks can be derived from populations of individuals with similar characteristics (e.g. age,sex, smoking, diet, lifestyle and other possible confounding factors) and this can inform the likelihood*of a disease occurring in the individual. However the reality is that any population will be made up ofindividuals with an “inter-individual” variability in their risks, and what is usually considered as thedose–response relationship is actually the relationship between the calculated population-averaged oraverage individual risk and the radiation exposure.

1.

Extrapolation of risks over lifetime

A70.
Because few cohorts have been followed until all individuals have died, epidemiologicalstudies only provide data on increased frequency of cancer in irradiated populations that have been
followed up to a certain date. Thus any observed increased frequency of occurrence of disease has to be
projected over the lives of the remaining individuals to infer lifetime risks* for the population. Bayesianinferences (based on degrees of belief) or subjective assumptions have been used to take account of
epistemic uncertainties (i.e. lack of knowledge) and to project increases in frequency of occurrence
observed up to now into the future.
A71.
Epidemiological studies provide information on the radiation-related increased frequency ofmany different cancer types as a function of age. This is compared with baseline rates of each cancer
10

The Scientific Committee’s mandate is to assess and report levels, effects and risks of exposure to ionizing radiation. Moreover
the General Assembly in the preambular paragraphs to its annual resolutions on the effects of atomic radiation (e.g. resolution
66/70) specifically states its concern about the potentially harmful effects on present and future generations resulting from thelevels of radiation to which mankind and the environment are exposed. While some have argued that the Committee should
confine itself to information resulting from empirical science and hypotheses that have been tested and deemed proven, excluding
all untestable hypotheses from consideration is not an approach that the Committee itself can adopt to meet the expectations of
the General Assembly. As a consequence, the Committee has provided science-based inferences for risk estimation that are basedon hypotheses currently not deemed proven, but considered to be scientifically plausible (see, for example, [U10]).

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 55

type as a function of age (ideally across many different exposed populations) with a view to modellingthe difference between them, and projecting that to where observations do not exist. The two mainmodelling approaches are a multiplicative risk extrapolation (which assumes an increased risk from
irradiation that is proportional to the underlying frequency of cancer) or an additive risk extrapolation(which assumes an increased risk from irradiation that is independent of the underlying frequency ofcancer) [U10]. For some cancer types, it is not at all clear whether either of these approaches is correct,
and expert judgement is required to select a plausible model or combination of models (see annex B).
A72.
Other temporal factors often complicate the general application of evidence obtained fromcohort follow-up studies of increased frequency of health effects in a population to estimating risks
from radiation exposure. Difficulties arise with the multiplicative risk extrapolation model because its
projections depend on underlying disease rates, which change over time owing to important nonradiation factors. For example, in western countries cigarette smoking has declined since 1945 and thus
the underlying rates of disease have also declined. Health care has also changed over time and survival
has increased for cancer patients. Thus, the application of multiplicative risk extrapolation models is
problematic for projecting cancer risks due to irradiation. This and other issues related to extrapolating
risks over lifetime are discussed further in annex B.

2.

Transference to another population

A73.
Despite the relatively large amount of data on the frequency of occurrence of radiogenic healtheffects,* the question of how to transfer risk estimates derived from one population, such as theJapanese survivors of the atomic bombings, to a different population remains unanswered. The
available data suggest that there is no simple solution to the problem. It is also not clear in terms of
mechanisms or biology how data on excess frequencies observed for one population should betransferred to another population with different baseline rates of the pertinent health effects.
Approaches using Bayesian inference and assumptions have been applied to the problem, and themultiplicative and additive risk transfer models introduced above have also been used for the purposesof extrapolating results to other populations, taking account of factors such as age and sex [U12]. The
inferred increases in cancer risk vary with age, with younger people generally, but not always, being
more sensitive, and with the type of cancer [U16]. The uncertainties associated with such inference are
discussed in further detail in annex B.

3.

Transference from one type of radiation to another

A74.
It is well known that to obtain the same biological result, different absorbed doses are needed
depending on the type of radiation, expressed by the relative biological effectiveness (RBE). This is due
to differences in ionization density, resulting in closely adjacent sites of damage in the case of neutrons,
alpha particles and heavy ions, whereas X-rays and gamma and beta radiation ionize only sparsely
along most parts of their tracks. Clustered sites of damage are more difficult for the cell to repair, which
explain in part the higher RBE for densely ionizing types of radiation. RBE is a quantity that isdetermined experimentally by comparing the doses required to achieve a specific level of biologicalresult.
A75.
One issue with RBE is the choice of the reference radiation: X-rays or gamma rays are usedfrequently, but X-rays appear somewhat more effective in producing some end points than energetic
gamma rays. The RBE also strongly depends on the end point studied. If, for example, chromosomal
aberrations are used as an end point, X-rays may be more than a factor of two more effective than high-56 UNSCEAR 2012 REPORT

energy gamma rays, whereas there is little evidence for differences in cancer induction in animal or
human studies. Transference from one type of radiation to another and the associated uncertainties are
discussed in much more detail in appendix C to annex B.

4.

Inferring risks from low-dose-rate exposure

A76.
In all the extrapolations and assumptions considered here, confident estimation of low risks isdifficult with epidemiological studies, because of the underlying statistical limitations (aleatory
uncertainties) and epistemic uncertainties (e.g. confounding). This is particularly a problem for low
dose rates, and for low and very low doses (next subsection). An understanding of the mechanisms ofcancer development after radiation exposure can assist in applying the information obtained fromepidemiological studies to infer risks from exposure at low dose rates. In particular, the application of adose and dose-rate effectiveness factor (DDREF) and the possibility of non-linear and threshold
relationships need to be considered ([U6] annex F). The DDREF reflects the observation that, at least
with respect to studies of cell killing and of cancer induction in animals, low dose rates have tended toresult in fewer biological outcomes than expected on the basis of simple extrapolation from the results
at high dose rates. However, doubts have been raised whether this also applies to cancer in humans [J3].
UNSCEAR in its 2006 Report estimated radiation risks without applying a DDREF [U10].
A77.
A specific dose within a short time (a few days at most, usually less) will induce all thedamage within that short duration of time, whereas the same dose given over longer time intervals
either fractionated (in small portions followed by radiation-free intervals) or protracted (continuously,
thus resulting in low dose rates) induces damage separated in time. The latter situation is morefavourable with respect to mitigating the consequences for the entire organism. First, there are fewer
possibilities for interaction among damaged sites. Second, there are not too many sites that need repair
at the same time, thus, reducing the problem of damage not being repaired or being misrepaired. Third,
the organism can tolerate that cells go into apoptosis, because not too many of them are affected at thesame time; controlled repopulation eliminates problems associated with radiation-induced cell death insuch a situation.
A78.
Indeed, while acute doses exceeding the relevant threshold dose result in deterministic effects,
the same dose delivered in a fractionated or protracted fashion may not ([H1, U3] annex J). The
situation is much less clear in the case of stochastic effects, for cancer induction in particular. (For a
more detailed discussion of dose and dose rate effectiveness, see annex B.)

5.

Inferring risks from low and very low doses

A79.
The fact that epidemiological studies of populations exposed at low and very low doses haveso far generally not been able to unequivocally demonstrate an increase in the frequency of stochastic
effects in a population, does not mean that there was no increase, but rather that any increase (had there
been one) was too small to be detected or the power of the epidemiological analysis was too low to
detect it. Those positive associations that have been reported (e.g. between fetal exposure to X-rays andan increased frequency of childhood cancer) could reflect an underlying action of low doses ofradiation, but not necessarily, because of the difficulty in taking account of all confounding factors.
Causation has therefore not yet been deemed proven in this case [U10, U13, W2].
A80.
At low and very low doses, risk can be inferred using Bayesian inferences that consider:knowledge from disciplines other than epidemiology. Current understanding of the mechanisms that areANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 57

intermediate between radiation exposure and subsequent health effects is substantial enough to deemthat the existence of risk at low and very low doses is plausible [U13, U15]. In principle, models thatspecifically represent biological mechanisms involved in carcinogenesis could help to improve
confidence in quantifying estimates of cancer risk associated with low and very low doses. However,
because understanding of the mechanisms is still limited, application of mechanistic models has, up tonow, not appreciably improved the quantification of cancer risks at these levels of dose. Nevertheless, astrength of these models is their potential to explore the influence of the various postulated
radiobiological mechanisms on cancer induction and thus to help provide insight into the inference ofrisk at these levels of dose [N3, P8].
A81.
Extrapolations from data on the increased frequency of cancer among the survivors of theatomic bombings in Japan, who received acute exposures at either moderate or high doses, to theestimation of cancer risk for populations exposed at low or very low doses have been supported by, atleast, two arguments:(a) Among the survivors of the atomic bombings in Japan, the observed increased frequency of allcancers combined is largely consistent with a linear or linear–quadratic dose–response relationshipover a wide range of dose levels (see UNSCEAR 2006 Report annex A [U10]). There is not,however, complete agreement on this [D6];(b) The scientific consensus is that radiation-related DNA damage plays a fundamental role in the
induction of carcinogenesis, even at doses as low as those from exposure to normal natural
background radiation [I9, N7]. The DNA damage and repair per unit dose at low and very low
doses has been assumed to be similar in nature to that at moderate doses, except that fewer cells areaffected than at moderate doses.
A82.
A number of plausible dose–response relationships for the risk of cancer following exposure at
moderate, low and very low doses were shown in figure I of the main text. Some reasons for the
specific shapes of the dose–response relationships are addressed in the following. This survey is not
exhaustive, but is only meant to indicate that the curves are based on known mechanisms for cancer
induction and are not just imaginary. This does not mean that all five are equally plausible; however,scientific debate continues as to which is the correct causal relationship. It might well be that undervarious conditions, different curves apply under different circumstances. Various plausible hypotheses
are currently being considered:(a) Supralinear. Some mechanisms would appear to indicate that the rate of change of risk perunit exposure would increase in the low- and very-low-dose ranges. A frequently cited example isthe bystander effect, meaning that not only the cell that actually was hit by radiation shows damage,but also the neighbouring cells. Because the bystander effect diminishes with increasing dose, thismechanism taken on its own would suggest that the risk per unit exposure be higher in the low andvery low dose-range than expected from observations in the range of moderate to high doses.
Another hypothesis is that repair mechanisms need a certain amount of DNA damage in order to be
activated. After low and, particularly, very low doses, the amount of damage might be too low totrigger repair. However, those unrepaired lesions might cause problems later in life;(b) Linear. The essential hypothesis to support linear extrapolation (i.e. the LNT hypothesis) are:one modified cell is sufficient to generate a cancer, one hit by radiation can induce the necessary
modification, and the defence systems (e.g. repair mechanisms and immune systems) are less than
100% effective. Under this hypothesis, even one energy quantum could induce a clinically manifest
cancer, although the probability would be extremely low. With increasing dose, more cells would
be modified and, thus, the chances that the defence systems fail, would increase, with an increasing

58 UNSCEAR 2012 REPORT

probability that a cancer will develop. Scientific results obtained during the past one or two
decades challenge the LNT hypothesis. Recent studies of non-targeted effects and of gene
expression suggest that cellular responses to radiation exposure at low doses may differ in naturefrom processes induced by exposures at moderate or high doses ([U10] annex B and [U11]annex C). The Committee has reviewed the evidence for non-targeted and delayed effects ofradiation exposure ([U11] annex C). Biological responses have been shown to have non-linear dose
dependences or even differ in nature at low doses from the response at high doses [M4, N4]. The
dose-dependence of bystander effects clearly differs from linearity. It is characterized by a
response at low doses that does not increase at higher doses. Portess et al. [P5] found that theinduction of programmed death (apoptosis) of precancerous cells by normal cells is increased byexposures to gamma radiation with doses as low as 2 mGy. The response increased with doses up
to around 100 mGy, but no further increase was observed at higher doses. Thus, bystander effects
could in principle influence carcinogenesis at low doses, but may be obscured at moderate or
higher doses by direct radiation actions. Linear extrapolation of estimates of cancer risk fromexposures at moderate or high doses to lower doses does not take such bystander effects into
account;(c) Linear–quadratic. The hypothesis underpinning a linear–quadratic relationship is the idea that
repair might be more effective following exposure at very low and low doses than at higher doses,
simply because not so much work has to be done by the repair enzymes. In addition, fewer sites ofdamage in the DNA would result in fewer opportunities of interactions among the various sites ofdamage (e.g. among two double-strand breaks leading to a chromosomal aberration). It is also
conceivable that some types of damage need several hits in order to be induced and the probabilityof several hits will decrease with decreasing dose;(d) Threshold. One very basic hypothesis that would imply a threshold dose has to do with thequestion whether one modified cell is sufficient to generate a cancer. If more than one cell would
be necessary, then a threshold, in the very-low-dose range, is probable. One possibility to avoid
this conclusion might come from the reasoning that the bystander mechanism can modify theadditional cells required to generate a cancer. The situation is even more complicated when one
considers that other agents may contribute to the development of a cancer, so that radiation could
not be deemed the only cause of a specific cancer.
Another mechanism that might introduce a threshold has to do with immunology. One of thefunctions of the immune system is the permanent control of the cells in the body. This is done bychecking the outer cell membrane for specific markers that signal that this cell belongs to the body.
Cancer cells frequently change their outer membrane giving the immune system the chance todetect and destroy them. If low radiation doses were to increase the effectiveness of the immune
defence, it is conceivable that some additional spontaneously occurring cancer cells would be
eliminated. If as many cancer cells were destroyed by the radiation-stimulated immune system as
are produced by radiation, then a threshold dose would be expected, and an increase in the numberof cases would be observed only when more cancer cells were produced by radiation thanprevented by the more effective immune system.
There might also be a “practical threshold” if latency periods of specific cancer types were longer
than the life time of the person;(e) Hormetic. Extending what has been addressed in the last paragraph, if more cancers areprevented by radiation than induced, one gets some amount of protection against cancer, meaningthat in a population exposed to rather low or very low doses, fewer cancers would be found, whencompared to a population without exposure to radiation above that due to natural sources.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 59

A83.
The radiation protection community has assumed the so-called “linear non-threshold” dose–
response relationship modified by a fixed DDREF for its purposes (see next section). This and the otherdose–response relationships are plausible but currently none of them are definitively verifiable andtherefore cannot be deemed proven or disproven. Further, some scientists [D6] and organizations suchas the French Académie des Sciences have argued in support of a practical threshold for management of
the risk of radiation-induced cancer [T7, T8], although this interpretation of the available evidence iscontroversial [B14, L5]. However, epidemiology alone will not be able to resolve the issue of whether
there are dose thresholds for radiation risks. A better understanding of biological mechanisms isnecessary, and many deserve attention in the ranges of low and very low doses: e.g. adaptive response,
apoptosis, genetic predisposition, and genomic instability. Hopefully, experimentation to test the
hypotheses surrounding the relevant mechanisms will help improve understanding of cancer risks in theranges of low and very low doses.

6.

Other issues related to inference

A84.
Inference from animal studies. There is a considerable body of literature [K1] on the numerous
factors that can influence radiation-related carcinogenesis in animals. These factors include the specificcharacteristics of the radiation (such as radiation type and dose, dose rate, dose fractionation, and dose
distribution) as well as many other contributing elements that are not specific to the radiation exposure(such as the genetic characteristics, age and environment of the animal, dietary factors and whether
specific modifying agents for radiation-related carcinogenesis have been utilized in the studies).
Modifying factors for radiation-related carcinogenesis have been observed in both in vivo and in vitro
systems. Agents have been identified that enhance (e.g. promoting agents) or suppress (e.g. preventive
agents) radiation-related carcinogenesis. These agents in experimental model systems have been shownto lead to health effects equally as significant as other known modifying factors for radiation-related
carcinogenesis (e.g. dose rate, dose fractionation, and linear energy transfer). Dietary factors play animportant role in determining the yields of radiation-related cancers in animal model systems. It is
likely that all these factors also influence estimation of radiation-related cancer risks in humanpopulations.
A85.
In some animal experiments, either threshold-type dose–response relationships have been
observed (e.g. cancers of the ovary or thymic lymphoma in mice) or practical thresholds, meaning thatthe latency period is so long that it exceeds life expectancy (e.g. bone sarcoma in dogs and mice afteralpha-particle exposure from long-lived bone-seeking radionuclides) [U4, U10].
A86.
Inferring risks of heritable disease. In the case of a heritable disease, the modification of one
cell (either sperm or oocyte) can be sufficient to induce the disease. There are indications that this also
applies to the induction of the majority of cancers, meaning that they are of monoclonal origin [T2].
Both situations (heritable disease and monoclonal origin of cancers) are compatible with a linear nonthreshold model. In contrast, there are other indications that quite a number of cancers are of polyclonal
origin [P1]. If this were true, then one could imagine an effective threshold in the low-dose range unlessthe bystander effect produces the multicellular response required to initiate a cancer.
A87.
While information on cancer risk has been obtained from epidemiological studies of
populations exposed to moderate or high doses, the existence of a risk of heritable effects in humans
has not been demonstrated even in populations exposed to doses of such magnitude. Models have,
however, been developed to infer the risk of heritable effects in humans from the data on animals

60 UNSCEAR 2012 REPORT

exposed to high doses 11 [U9]. Clearly, such inferences of risk cannot be unequivocally verified or
refuted at the present time.
A88.
Expressing confidence in the inference. Uncertainty analyses attempt to quantify what is
unknown, unreliable or indefinite. The quantitative expression of uncertainty is discussed in more detailin annex B, using the mathematical language of probability as an expression of the doubt about the true
value of a quantity of interest. The Committee considers that it is reasonable to quantify the uncertainty
about these projections when sufficient data exist to underpin the subjective uncertainty distributions.
This can be done by generalizing estimates of risk from radiation exposure derived fromepidemiological studies to populations that are substantially different, or exposed under very different
conditions (see annex B). The projected increased risk of stochastic effects in an exposed population
represents the population-averaged lifetime risk presumed to be due to the radiation exposure.
A89.
The Committee has addressed the epistemic uncertainties associated with extending theobservations of increased frequency of various stochastic effects in living cohorts over their predicted
lifetimes. It had estimated excess lifetime mortality (averaged over both sexes and all ages in the
population) for five specific populations: (a) for all solid cancers combined, 0.36–0.77% for an acutedose of 0.1 Gy and 4.3–7.2% for an acute dose of 1 Gy; and (b) for leukaemia, 0.03–0.05% for an acutedose of 0.1 Gy and 0.6–1.0% for an acute dose of 1 Gy [U13]. The statistical uncertainty of theestimates was assumed to be in the order of a factor of 2, and lower bounds of the confidence interval
included zero. The Committee discusses a more detailed consideration of the epistemic uncertainties inannex B as part of a selected risk evaluation.
A90.
The Committee notes that risks are unlikely to change dramatically just below the situation inwhich a statistically significant increased frequency in cancer has been detected [B13]. However, atlower and lower doses, quantification of epistemic uncertainty due to indeterminacy and ignorance(lack of knowledge) would have less and less information value and can be increasingly misleading.
This combined with the aleatory (random) uncertainties makes accurate and valid quantification of risks
at very low doses at the present time an impossible challenge. However, a gross underestimation of therisk from low and very low doses using these various plausible dose–response relationships is mostunlikely since this would have been detected by those epidemiological studies that have been
conducted.
A91.
Annex B discusses representing uncertainty in risk estimation associated with incomplete
understanding of biological processes by applying subjective weights to different models andassumptions. The resulting weighted quantity represents the ensemble degree of belief in the risk
estimate, and has been termed “plausibility” by Beninson and Lindell [B3]. An expert elicitation
process to quantify degrees of belief given the evidence can be applied [G3], but such assessments
always have to be treated with utmost care, because expert opinion may well differ in the absence ofclear evidence. Probably the best that can be done is to quantify uncertainty, insofar as this is feasible
and honest, to be transparent about the premises for the models, to be subject to critical peer review
processes, and to increase knowledge through research on specific issues. There have been considerable
developments in approaches in recent years that employ expert judgement within frameworks that canconvey the level of evidence and level of consensus to express a level of confidence in the results of anevaluation [I14, M1].

11

The radiation-risk factor was expressed as 0.41–0.64% of the baseline rate per gray of parental irradiation in the next
generation.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 61

C. Application of science-based inference
A92.
Inference of cancer risk at low and very low doses (including cumulative doses received atchronic low dose rates) can be applied to real-life problems. The objectives of these problems affect the
choice of how to represent risk at these doses. For some purposes, norms external to science, such associal responsibility, utility, prudence, precaution and practicality of application, are used. Some
examples of inferences used for various purposes are discussed below and include:(a) Early indication of potential health impact and directing future scientific research (e.g.
assumptions about credible risks can be used to plan epidemiological and laboratory studies topossibly confirm and quantify them);(b) Public health resource planning (e.g. comparisons of burdens of disease from various competing
causes can be used to allocate resources efficiently, or to optimize health-screening studies);(c) Radiation protection and risk management (which influence for example, the derivation ofprotection criteria);(d) Legal liability purposes (e.g. compensation payments to individuals exposed to radiation from
weapons tests or in the workplace).
A93.
Early indication of potential health impact and directing future scientific research. Estimatesof the risk at low and very low doses and doses received at chronic exposure at low dose rates may need
to be made in order to identify gaps in knowledge and the direction of future research, to provide an
early indication of potential health impact, or to design future epidemiological studies. In this respect,considerations such as the need to avoid false negatives can be important (i.e. there is a need torecognize that studies of high statistical power are necessary in order to be sure that health effects atthese doses have not been missed). This application does not need to adopt norms external to science.
A94.
There are numerous examples of the estimation of risk for such purposes, for example, even inits 1958 Report, the Committee made assumptions to estimate the genetically significant dose andcorresponding risk of heritable effects that might result from exposure due to the atmospheric testing of
nuclear weapons [U1]. Nonetheless, the Committee cautioned that “any present attempt to evaluate theeffects of sources of radiation to which the world population is exposed can produce only tentative
estimates with wide margins of uncertainty” and “although much is known, quantitative estimates ofthe mutational consequences of genetically significant irradiation of human populations remain subject
to grave limitations”. Subsequent research has permitted a better understanding of radiation-induced
risks, including heritable risks, but the consequences of exposure to low and very low doses are still not
fully understood.
A95.
Public health resource planning. While the Committee considers the risks of cancer orheritable effects are plausible at low and even very low doses, it has concluded that it should continue
to refrain from estimating the numbers of radiation-induced health effects at these levels of dose
because they have not been demonstrated scientifically. The Committee notes, however, such
estimations may be made for science-based decision making. If they are carried out for this purpose, thenumbers should be regarded as no more than hypothetical because:(a) Below the minimum detectable excess frequency of cancer, such inferences are not amenable
to being verified by testing, and are not falsifiable); in the case of heritable effects, no statisticallysignificant excess frequency in humans has yet been detected and therefore any inference cannot
again be tested and verified;62 UNSCEAR 2012 REPORT(b) Cancers and heritable effects cannot be attributed individually or collectively owing to thecurrent absence of a known biomarker to discriminate between radiation-induced and baseline
health effects and the inability to control for all the other factors, known and unknown, that cause
cancer (i.e. counterfactual conditional reasoning);(c) The complex network of processes contributing to pathogenesis after exposure at low and very
low doses is not understood, and thus the uncertainties at very low doses render such inferences
highly uncertain and potentially misleading (and, in many cases, quantitative uncertainty analysis
would not exclude zero excess as a possible outcome).
A96.
The Committee recognizes though that public health bodies need to allocate resources
appropriately, and this may involve making estimates of numbers of health effects from low and very
low doses for comparative purposes. Such conditional predictions , although based upon reasonable but
unverified hypotheses, could be useful for such purposes provided that it were applied consistently, theuncertainties in the assessments were taken fully into account, and it were not inferred that the
projected numbers of health effects were other than notional. For example, this has been done for the
purposes of gaining insight into the appropriate age at which to commence screening for breast cancer
among asymptomatic women [B9]. It has also been done to gain insight into the possible health impact
on a population of the Chernobyl accident (e.g. [B1, C1]) and of the diagnostic use of radiation in
medicine (e.g. [B6]). The Chernobyl Forum approached the problem of possible health impact of theChernobyl accident by differentiating between populations with moderate doses for which thepossibility of cancer induction can be predicted and those with low and very low doses for which risk
can only be inferred through the use of dose–response models [W6]. For its part, the Committee has
12estimated the collective effective doses to people outside the former Soviet Union where doses were
low or very low and has made scientific statements that emphasize that any risks would be too low to
be detectable. At the same time, the Committee highlights that the inability to detect any increase in thecancer frequency does not exclude the possibility of a small increase in the percentage of disease at13
these doses.
A97.
Radiation protection and risk management. The ICRP [I10] has taken the Committee’sfindings and used the linear, non-threshold model, which has practical advantages for radiation
protection purposes in order to derive nominal radiation risk coefficients for “a representative
population”. These nominal risk coefficients are coherent with radiobiological knowledge, adhere to
epidemiological information, and incorporate ethical judgements on the relative harm associated withdifferent health effects. The ICRP refers to the overall measure of harm as “detriment” and its weighted
risk coefficients as “detriment-adjusted nominal risk coefficients”, which have been developed forspecific groups of people (workers and members of the public) [I10]. These, in turn, have been used in
the derivation of the protection quantity, effective dose. Effective dose is not a physical quantity, butrather, has the nature of a utility; that is, it can be used to represent preferences for comparative
purposes (such as preferring one radiological procedure to another one). Effective dose is not, however,an appropriate quantity to determine cancer risk.
A98.
Legal liability purposes. In spite of the fact that the risk of a stochastic health effect cannot be
determined for a specific individual, decisions may be required on the possibility that an observed
12

For its evaluations of levels and trends of exposures, the Committee has used two radiation protection quantities, namely
effective dose and collective effective dose. These have the advantage of simplifying comparison of doses from different types ofradiation and different distributions of dose within the body, and of averaging over age and sex; moreover, many regulatory
authorities keep records in terms of these quantities.
13
The Committee has subsequently used the specific word “discernible” to convey the idea that, e.g. at certain level of exposure,risks cannot be excluded but can be inferred to be so small that any associated effects in the health statistics will not be“discernible” [U17]. Conversely, at high levels of exposure, such effects may become “discernible”.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 63

health effect in an individual might have been caused by a specific exposure to radiation. For thispurpose, analysts use the concept of assigned share (also known as the probability of causation) to
respond to legal liability questions following radiation exposure [L3, N3]. The assigned share is definedas the probability that an observed health effect in an individual was caused by a specific radiation
exposure [I12]. As indicated above, the concept of relative frequency for an individual strictly has no
meaning; the outcome for the individual is either that the health effect occurs or it does not. Thus theprobability of a health effect in an individual can only be estimated by assuming that the risk to theindividual was the same as the relative frequency observed in a population of similar exposed
individuals. However, this relative frequency often cannot be determined, and there are particularchallenges when multiple causative agents are present, and thus analysts will need to draw inferencesfrom studies of populations that share some of the relevant characteristics and make allowance forfactors considered to influence the risk (e.g. family history, race, smoking habits). Moreover, theunderlying biological model assumed for the disease process and a precise definition of causation is
critical [B8]. The assigned share (AS) is calculated as follows:
AS = ERR/(ERR + 1) = (RR − 1)/(RR) = ERR/RR
where ERR is the excess relative risk* and RR the relative risk.*

V. RESEARCH NEEDS
A99.
Given the fact that currently there is insufficient scientific evidence to be able to unequivocallyattribute health effects to low and very low doses of ionizing radiation, the Committee suggests that thefollowing research needs be addressed:(a) On epidemiological studies with complete follow-up of the exposed cohorts over theremainder of their lives (such as the Life Span Study of the survivors of the atomic bombings inJapan, studies of persons exposed to medical radiation as infants or in early childhood, and studies
of workers who were occupationally exposed to radiation over a period of years), describing any
increased frequency of health effects by age and sex;(b) On improving the quality of epidemiological studies (e.g. reducing bias by publishingprotocols in advance of studies, addressing incomplete follow-up and determination of outcomes,
and the quality of dosimetry);(c) How increased frequency of specific types of cancer in an exposed population vary withradiation dose; dose rate; the particular type/energy of radiation; the age at exposure and age atmanifestation of health effect; the time after exposure;(d) The latency period between exposure and manifestation of a health effect;(e) The impact of variations in human genetic susceptibility;(f) Interactions* with other carcinogens/factors (e.g. smoking, viruses, and diet/lifestyle factors);(g) Rigorously quantifying uncertainty in such analyses (see annex B).
Large-scale epidemiological studies of exposed populations can be attempted if they have a reasonablechance to answer questions about increased frequency of health effects with dose. For example,

64 UNSCEAR 2012 REPORT

conventional risk models suggest that a case–control study involving around 10,000 matched pairs ofcases and controls could theoretically (i.e. if other sources of bias and confounding factors can bereasonably addressed) have sufficient statistical power to detect an increased frequency of childhood
leukaemia for variations in exposure to natural sources of gamma radiation. The Committee recognizes,
however, that even large-scale epidemiological studies have inherent limitations, related to statisticalvariation in cancer rates in populations and the inability to account for all the non-radiation causes ofcancer, and that such studies may never be able to unequivocally demonstrate that health effects result
from low doses of radiation. Attempts to integrate biological understanding of radiation actions at low
doses with epidemiological findings of health effects over a range of doses should be encouraged. The
Committee expects four current scientific trends, namely developments in radiation dosimetry,radiation systems biology, molecular epidemiology and modelling of pathogenesis, to continue tocontribute synergistically to this task.
A100. Radiation dosimetry. In the low- and, in particular, the very-low-dose range, not all cells arehit. The concept of absorbed dose is not useful in such a situation, because this quantity is based on theassumption that all cells receive more or less the same energy when exposed to radiation. The energy
deposition in just a fraction of cells may markedly change the reaction of a tissue to radiation exposure.
In addition, it is very important to identify the pattern of energy deposition within the cell, for example,
after exposure to organically bound tritium.
A101. Systems biology. A main aim of radiation systems biology is an improvement in theunderstanding of the complex cellular and tissue responses, and their interdependencies, to exposures toionizing radiation [B2, W5]. A vast amount of information is, at present, created by modern molecularmethods including genomics, proteomics and metabolomics (the systematic study of the uniquechemical fingerprints that specific cellular processes leave behind). Mathematical systems aimed at a
description of the cellular and tissue-specific processes are becoming increasingly complex [Q1].
Future research is expected to help improve understanding of the relevant reaction pathways and distil
key knowledge that will be of use for the estimation of risks from low doses.
14

A102. Molecular epidemiology. Molecular epidemiology has revealed molecular factors related tocancer occurring after exposure to ionizing radiation [S1]. Such studies may contribute to improving
understanding of individual predisposition to radiogenic cancer and should be encouraged. One
aspiration of molecular epidemiology for improving the quantification of risks from low-dose exposureis the identification of one or more early molecular markers for radiation-induced cancer. Such markers
might be detectable with epidemiological studies at lower doses than a fully developed disease such as
cancer.
A103. Modelling pathogenesis. The integration of molecular data on cancer and samples of normal
tissue into models of pathogenesis and the evaluation of risk due to radiation exposure with suchmodels is becoming increasingly feasible. Such approaches need large scale studies and have thepotential to improve significantly understanding of risks from low doses of radiation.
A104. In addition, the Committee considers that research should continue: (a) into bettercharacterizing tissue reactions that occur in the longer term after protracted exposures (such as cataracts
and circulatory diseases); (b) into developing and applying methods to integrate and synthesize theresults of many studies (e.g. using Bayesian inference) to better make quantitative and qualitative
statements on the confidence that can be placed in causal relationships, hypotheses and predictions.
14

Molecular epidemiology is a branch of medical science that focuses on the contribution of potential genetic and environmental
risk factors, identified at the molecular level, to the aetiology, distribution and prevention of disease within families and acrosspopulations [I4].

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 65

VI. SUMMARY
A105. Figure A-V highlights in diagrammatic form—the distinction to be made between observed
health effects and inferred risk of health effects.
Figure A-V. Diagram to illustrate the distinction between observed health effects and inferred risk ofhealth effects
This diagram distinguishes between observed health effects and risk of health effects occurring in the future: (a) observed
health effects in an individual; (b) observed increased frequency of health effects in a population; (c) well-founded predictions(i.e. based on hypotheses deemed proven) of health effects in individuals or increased risk of health effects in populations;and (d) conditional predictions (i.e. based on hypotheses currently not deemed proven, but biologically plausible) ofincreased risk of health effects in populations. While risk of a health effect (i.e. the probability that the health effect will occur)can be estimated, a health effect cannot be confirmed until it is observed

Retrospective(a) Observed health effect in an
individual

Diagnosis

Hypotheses
deemed proven
Risk

Observations(b) Observed increased
frequency of occurrence of
health effects in a population

Prospective

Epidemiology

Hypotheses
currently notdeemed proven(c) Well-founded predictions ofhealth effects in individuals or
increased risk of health effects inpopulations

Risk estimation(d) Conditional predictions ofincreased risk of health effects inpopulations

A106. Observations from scientific method. It has been established by applying the scientific methodthat acute exposure to ionizing radiation above certain high-dose levels (thresholds) will cause
deterministic effects in individuals. Such health effects can often be confidently attributed to radiation
exposure by pathological diagnosis.
A107. Furthermore, statistically significant increases in the frequency of cancers (stochastic effects)
have been observed in populations that have previously been exposed to moderate or high doses. Afteraccount has been taken of such matters as bias and confounding, these increases have also been
attributed to radiation exposure. However, it is currently not possible to attribute a cancer in a particular
individual in these populations to radiation exposure.
A108. Table A5 summarizes the conclusions regarding the attributability of observed health effects toradiation exposure.

66 UNSCEAR 2012 REPORT

Table A5. Attribution of observed health effects to radiation exposure
Dose band

Attribution to radiation exposure

Scientific knowledge

Individual

Population

SEVERE DETERMINISTIC EFFECTS
High, acute

Robust direct evidence withindividuals. (However,
severe deterministic effects
have also been observed
after moderate doses toembryo/fetus)
High degree of consensus on
how damage is induced;
some understanding of
repair with timeHigh andmoderate,chronic

Unclear at present whether
some health effects in longterm such as cataracts andfibrosis are deterministic

Following high acute dose,
exceptionally unlikely thatsequence and pattern of signs
and symptoms in short termcaused by other factors. An
observed deterministic healtheffect can thus be attributed if
diagnosis eliminates possible
alternative causesa

Attribution of cases at the
population level is the total
number of cases that have been
individually attributed

Other possible causes cannot be
excluded. Unequivocal
attribution unlikely

CANCER
High andmoderate

Direct robust evidence fromcoherent and statisticallysignificant increases infrequency for various
exposed populations ofincreased frequency ofvarious types of cancer
Medium consensus on role
played by DNA mutationand mechanism for cancer
development

Low andvery low

No unequivocal direct
evidence of statisticallysignificant increases infrequency in populations

Radiation is not the only possible
cause. At present, no specificbiomarkers distinguish between
cancer caused by irradiation and
one due to another cause
An observed cancer in an individual cannot be unequivocallyattributed to radiation
If the baseline frequency is low fora particular cancer andradiosensitivity high, attribution
is plausible, particularly if
exposure was highAn observed cancer in an
individual cannot be
unequivocally attributed to
exposure to radiation

Moderate consensus on role
played by the mutation ofDNA, and mechanism forcancer development

Observed increase in cancer
frequency can be attributed toradiation exposure throughepidemiological analysis provided
that increased frequency is large
enough to overcome inherent
statistical and other uncertaintiesb
and a counterfactual analysis has
been adequately conducted
For a particular cancer, if baselinefrequency low and radiosensitivity
high, an increase in frequency couldat least be associated with exposure,even if number of cases were small
An observed increase in thefrequency of a cancer cannot atpresent be unequivocallyattributed to radiation exposure.
The increase may not be
reproducible and confounding
cannot be ruled out

HERITABLE EFFECTS
High,
moderate,
low andvery low

Demonstrated in animalstudies at high doses. No
direct evidence in humanpopulations. Medium
consensus they could becaused in humans

Radiation not the only possible
cause. An observed heritableeffect cannot at present be
attributed to radiation exposureof the parent

An observed increase in thefrequency of heritable effects
cannot at present be attributed toradiation exposure. The increase
may not be reproducible andconfounding cannot be ruled outaThe health effect could be attributed to the exposure through a qualified radiopathological procedure (and attested as such).

b

An increase in cancer frequency could be properly verified and attributed to exposure by means of a qualified radioepidemiological process.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 67

A109. Well-founded predictions. On the basis of these observed radiogenic health effects, wellfounded predictions can be made on the consequences of radiation exposure. Thus, above the thresholds
for deterministic effects, it can be stated with confidence that these consequences will occur inindividuals, although there may be some variation in the actual threshold for a particular health effectbetween individuals. Below the thresholds, no such health effects are predicted. In addition, it can bestated with confidence that there is an increased risk of certain cancers in a population exposed tomoderate or high doses. For populations exposed under similar conditions to those from which data on
the increased frequency was obtained, the risks of those cancers can be quantified, and thus valid
predictions of future numbers of cases can be made with some confidence.
A110. Conditional predictions. In contrast, only conditional predictions can be generally made about
the possible stochastic effects of exposure to low and very low doses or even of the possible heritableeffects of exposure to high doses. This is because these health effects have not been demonstrated forthese situations. Such conditional predictions can be made using plausible assumptions about thepossible occurrence of such health effects, and the available scientific information, for example, on theinteraction of radiation with cells. Such assumptions are necessary for the purposes of policy anddecision-making. A number of science-based models have been proposed and the radiation protection
community has adopted the linear non-threshold model—but none are based on hypotheses that havepresently all been deemed proven.
A111. Table A6 summarizes the conclusions regarding well-founded and conditional predictions
based on inference of risk.
Table A6. Inference of risk of health effects from radiation exposure
Class of effect

Dose
band

Confidence in inference

Severedeterministic
effect

High,
acute

Sufficiently well-understood science and sufficient data to predict the occurrence
and the severity of health effects with a high degree of confidence (when doses are
significantly above relevant threshold)

CancerHigh andmoderate,chronic

Well-founded prediction is difficult owing to uncertainties

High andmoderate

In most cases, sufficient direct information to make well-founded predictions with ahigh degree of confidence of increased risk of certain cancers in specificpopulations after acute exposures similar to those that have been exposed in thepast, and chronic exposure to radon, and quantify uncertainties
Assumptions are necessary to infer risk of cancer in populations that are different
from those for which observations were made and the exposure conditions aredifferent. These assumptions are based on an understanding of the mechanisms ofradiation-induced carcinogenesis. Uncertainties are however somewhat larger anddifferent analysts may make different assumptions. Predictions should be regarded
as conditional, and have only a medium degree of confidence associated with them

Low andvery low

Increased risk of cancer is plausible but not based on observed increased
frequencies in populations that are deemed proven. Risk estimates are generally
not verifiable through testing with credible-sized radioepidemiological studies;
although there is an upper bound to the value of the absolute risk (i.e. to theincreased frequency that could be observed with such studies)
Conditional predictions can be made to estimate the risk of cancer in exposed
populations. Uncertainties are much larger and more debatable and any predicted
increase in the risk of cancer should be regarded as having low relative confidence
and be no more than notional

68 UNSCEAR 2012 REPORTClass of effect
Heritable
effectDoseband

Confidence in inferenceHigh,moderate,
low andvery low

Increased risk of heritable effects is plausible but not based on observed increased
frequency in populations. Conditional predictions can be made based on data fromanimal studies to estimate the risk of heritable effect in exposed populations.
Uncertainties are very large and debatable and any predicted increase in the risk ofheritable effects should be regarded as having low relative confidence and be no
more than notional

A112. Figure A-VI illustrates schematically the current limitations to knowledge, in a general sense,
regarding the health effects from radiation exposure. It highlights the distinctions between
attributability of deterministic effects in individuals following acute exposures to high doses, theattributability of increased frequency of occurrence in populations following exposures to moderate
doses and higher, and the inferred risks for exposures to low and very low doses.
Figure A-VI. Schematic of the relationship between dose, additional to that from typical exposure tonatural background radiation, and probability of occurrence of health effects
At acute doses above 1 Gy, deterministic effects that are clinically observable in individuals can be attributed to radiation
with increasing confidence as the dose increases. Stochastic effects (e.g. cancer) in an individual cannot be unequivocallyattributed to radiation exposure, however collectively an observed increase in the incidence of such health effects in a
population can in some situations be attributable to radiation exposure when the dose is moderate or high. For low doses,
risks are biologically plausible, though they are not currently verifiable through testingANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 69

APPENDIX B. CASE STUDIESI.

SKIN BURN AFTER INTERVENTIONAL CARDIOLOGY PROCEDURE..................................... 70
A. Scenario.......................................................................................................................................... 70
B. Analysis........................................................................................................................................... 71
C. Conclusion .................................................................................................................................... 71

II. PREGNANCY WITH MENTALLY RETARDED INFANT ................................................................ 71
A. Scenario.......................................................................................................................................... 71
B. Analysis........................................................................................................................................... 72
C. Conclusion .................................................................................................................................... 72
III. THYROID CANCER AFTER THE CHERNOBYL ACCIDENT ........................................................ 73
A. Scenario.......................................................................................................................................... 73
B. Analysis........................................................................................................................................... 73
C. Conclusion .................................................................................................................................... 75
IV. LUNG CANCER FROM EXPOSURE TO RADON........................................................................... 75
A. Scenario.......................................................................................................................................... 75
B. Analysis........................................................................................................................................... 76
C. Conclusion .................................................................................................................................... 77
V. ESTIMATED RISK FROM COMPUTED TOMOGRAPHY SCANS .............................................. 77
A. Scenario.......................................................................................................................................... 77
B. Analysis........................................................................................................................................... 78
C. Conclusion .................................................................................................................................... 79

B1.
The Committee has applied the concepts discussed in the main text of the annex to five casestudies to illustrate the considerations involved in attributing health effects from empirical science andin applying science-based inference. The case studies are only intended as examples of some of theconsiderations and should be interpreted neither as complete analyses nor as formal Committee
statements on these subjects.
B2.
It was stated in the main text of the annex (see paragraph 13) that (a) the sequence of signs andsymptoms after high-dose radiation exposure that result in a deterministic effect is well characterizedand (b) these observable consequences allow radiation experts to make confident diagnoses that a
particular deterministic effect can be unequivocally attributed to radiation exposure (i.e. deemed

70 UNSCEAR 2012 REPORT

proven). In making such diagnoses, the radiation expert must exclude other possible causes (i.e. throughconducting a counterfactual analysis).
B3.
Case I is an example of a situation in which it is straightforward to attribute the observed
health effect to radiation exposure. Case II is an example of a situation in which it is possible to deny
the causative role of radiation in an observed health effect for a number of reasons including the resultsof a counterfactual analysis. Case III is an example of where health effects have been observed in an
exposed population; consideration is given to whether these health effects in the population and inindividuals can be attributed to radiation exposure.
B4.
Case IV is concerned with whether an increased risk of cancer in a particular population can orshould be predicted. The case concerns the exposure of a given population to radon in their homes.
B5.
The general thesis of the annex is that it is acceptable to predict an increased risk of cancer in a
population due to radiation exposure, if and only if, an increased frequency of that cancer in a
population with similar characteristics has been attributed to radiation exposure at the levels of
exposure involved. Where this is not the case, however, predictions are conditional on various
assumptions, but the hypothesis regarding the predicted increased risk would not be testable withcredible-sized radioepidemiological studies. Bodies that have responsibilities for assessing possible
health implications of a particular technology and for decision-making may need to predict such risks.
However, the results of such predictions are conditional and should only be considered as being basedon hypotheses currently not deemed proven. Case V is an example of how such predictions can be
made; it also clarifies the limitations of assessments of this sort.

I. SKIN BURN AFTER INTERVENTIONAL CARDIOLOGYPROCEDURE
A. Scenario
B6.
The subject was a 69-year-old, 140 kg diabetic male with long-standing heart disease. He had
had three prior coronary angiograms in the two preceding years. Because he was having recurrent chest
pain, he underwent a diagnostic nuclear medicine study using myocardial imaging that showed severe
ischaemia in the distribution of the left anterior descending (LAD) coronary artery. As a result, heunderwent a fourth cardiac catheterization that included several attempts at coronary angioplasty(dilatation) and stenting. The fluoroscopy time was recorded as 34 minutes. There were 50 cine runs
with a total of about 6,200 frames.
B7.
About three weeks after the procedure, the subject noted intense itching, pain and blistering
lesions in a square pattern on his back (later reported as an area of 6 cm × 10 cm). Various nonprescription remedies were tried without success. He went to see several physicians without a clear
diagnosis. About seven months after the procedure, there was a chronic eschar with marked indurationand inflammation that was extending out several centimetres from a central necrotic area (10 cm × 8 cm)[G1, I7, K2, K3, V2].
B8.
The question was whether the symptoms could be attributed to radiation exposure during theinterventional cardiology procedure.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 71

B. Analysis
B9.
Firstly, there are two temporal aspects: (a) the lesion was not present before the “very difficultand quite lengthy” cardiac catheterization and attempted stent placement in the coronary artery—it
appeared shortly afterwards; and (b) the temporal sequence of the appearance of reddening, itching
followed by skin breakdown within a few weeks and non-healing ulceration at about 6–12 months wascharacteristic of many radiation burns following high doses.
B10.
The second point is the site of the lesion on the patient’s back. The radiation from afluoroscope used during a cardiac procedure enters from the patient’s back and exits from the front. The
highest dose is to the skin on the back. The site of the lesion in this case was consistent with a rightanterior oblique projection that would be utilized for visualization of the LAD coronary artery. In
addition, a review of the actual images from the procedure showed an exact correlation with anatomical
structures underlying this lesion.
B11.
The third point is that the size of the lesion was consistent with the diameter of the radiation
beam used for this procedure.
B12.
The fourth point is that the absorbed dose to the chest wall or skin almost certainly exceeded
15–20 Gy, a level of dose that is known to result in the observed temporal course and appearance of thelesion. The patient’s records indicated that the dose–area product (DAP) was 1,631 Gy cm2 compared
to an average of 83 Gy cm2 for similar procedures [V1] (in order to compensate for attenuation by thepatient’s body mass and still get an acceptable image, the radiation dose may have needed to be 4–6
times higher than that for a normal patient). The literature also indicates that patients usually get skinchanges when the DAP exceeds 1,000 Gy cm2 and that the average number of cine images for acoronary angioplasty is about 1,000; in this case there were more than 6,000.

C. Conclusion
B13.
Based upon the analysis by the radiation experts, a lesion of this type would be very likely
following such high doses of radiation under these conditions. Moreover, it would be exceptionallyunlikely that any other possible cause could have created such a lesion, i.e. it would not have occurred
if the subject had not incurred the radiation exposure (thus, this counterfactual conditional question was
satisfied). Thus, the subject’s lesion on his back was confidently attributed to the radiation exposure.

II. PREGNANCY WITH MENTALLY RETARDED INFANT
A. Scenario
B14.
A 26-year-old mother of two children took her 2-year-old son to the hospital after a head
injury. A skull film was ordered, and the mother was asked to hold the child during the procedure.
There is some doubt as to whether she wore a lead apron. Subsequently, she discovered that she wasapproximately nine weeks pregnant at the time. She carried the pregnancy to term without incident.

72 UNSCEAR 2012 REPORT

Following a normal delivery of a female infant, the child was subsequently diagnosed to be mentallyretarded. No physical stigmata were associated with the retardation.
B15.
The question was whether the mental retardation could be attributed to the radiation exposure
incurred by the pregnant mother while holding her son for the skull film.

B. Analysis
B16.
During the period from 8 to 25 weeks, and, in particular, 8 to 15 weeks, post conception, thecentral nervous system (CNS) of the fetus is very sensitive to radiation exposure. Doses to the fetus inexcess of 100 mGy may result in a lower than expected intelligence quotient (IQ). The IQ has beenfound to reduce with increasing dose. Doses of around 1 Gy result in a high probability of severe
mental retardation [O3]. The CNS is rather resistant from 26 weeks post conception until birth. In
addition, 95% of those who were exposed in utero as a consequence of the atomic bombings in Japanand subsequently found to be mentally retarded, also demonstrated microcephaly [O2, O3].
B17.
On the sole basis that the radiation exposure was incurred nine weeks post conception, mental
retardation caused by radiation exposure cannot be immediately excluded. Had the exposure occurred at
two to three weeks post conception or, for example, late in the third trimester, mental retardation could
definitely not be attributed to radiation exposure.
B18.
The mother claims that she was not given a lead apron to wear during the procedure. As an
extremely conservative estimate, one might suppose that the mother's pelvis was in the direct X-ray
beam. Most skull films are taken using a peak voltage of 80 kV; on the basis that the uterus was 8 cm
deep in the tissue, a maximal dose to the fetus would have been 2 mGy. If the mother's pelvis had notbeen in the direct beam, which is a much more reasonable assumption, the assessed dose would havebeen 10–20 µGy. Thus, on the basis of dosimetric considerations alone, the mental retardation of theinfant could not be attributed to radiation exposure. Furthermore, in this particular case, there was noevidence of microcephaly, which often accompanies radiogenic mental retardation.
B19.
At the present time, most relevant bodies define mental retardation as having an IQ of
below 70. The normal frequency of people with an IQ below 70 is approximately 3%. The baseline rateof severe mental retardation (in which an individual is unable to care for themselves) is about 1 in 200(0.5%) births. At the present time, over 250 causes of mental retardation have been identified, including
malnutrition, lead poisoning, rubella infections during pregnancy, and maternal alcoholism [M7]. Thus,
many other causes than radiation exposure could have been responsible for mental retardation in thisparticular case.

C. Conclusion
B20.
Although the exposure occurred during the period of pregnancy when the fetus has beenshown to be sensitive to radiation exposure, the dose to the fetus was far below any level at whichmental retardation has been documented; moreover there were no signs of physical findings that may be
associated with radiation-induced mental retardation. Given that the normal frequency of mental
retardation is about 3%, and that there are numerous other possible causes, radiation experts—after
conducting a counterfactual analysis—would conclude that the mental retardation could not be
attributed to the radiation exposure.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 73

III. THYROID CANCER AFTER THE CHERNOBYL ACCIDENT

A. Scenario
B21.
Since the 1986 Chernobyl accident, a substantial increase in frequency of thyroid cancer has
been observed in the whole of Belarus and Ukraine, and the four most affected regions of the RussianFederation, among those exposed at the time as children or adolescents. Among those under age
18 years in 1986, 6,848 cases of thyroid cancer were reported between 1991 and 2005 (annex D of
[U14]). The question is whether this increased frequency in the population and individual cases can be
attributed to radiation exposure from the accident.

B. Analysis
B22.
Figure B−I shows that in Belarus, the frequency of thyroid cancer among children under
10 years of age increased dramatically after the accident. For those born after 1986 (see the data forthose under 10 years in 1996–2005), there was no evidence for an increase in the frequency of thyroid
cancer. The increase in the frequency of thyroid cancer among children and adolescents started about
3 years after the accident [H5] and persisted, at least until 2005. This temporal pattern already suggeststhat the dramatic increase in frequency in 1991–1995 was associated with the accident, though notnecessarily with radiation exposure [J2].
B23.
Various epidemiological studies have shown that the thyroid gland is highly susceptible to the
carcinogenic consequences of external radiation exposure during childhood ([U10] annex A). These
include studies of the survivors of the atomic bombings in Japan and those exposed in childhood forvarious medical reasons (e.g. treatment of tinea capitis). A combined analysis of these studies [R1]
showed a marked influence of the age at exposure with little apparent increase in frequency of disease
after age 20 years; it also showed that the increased frequency began to decline about 30 years after the
first exposure. A pooled analysis* of five epidemiological studies of children exposed to externalradiation showed an average excess relative rate of 7.7 (95% CI: 2.1, 28.7) at 1 Gy. (Further discussion
on the uncertainty of the risk estimates is provided in annex B.)
B24.
The average dose to the thyroid of those who were evacuated was estimated to have been
about 500 mGy (with individual values ranging from less than 50 mGy to more than 5,000 mGy). For
the more than six million residents of the contaminated areas of the former Soviet Union who were notevacuated, the average dose to the thyroid was about 100 mGy, while for about 0.7% of them, the doses
to the thyroid were more than 1,000 mGy ([U14] annex D).
B25.
The increase in frequency of thyroid cancer following the Chernobyl accident was first
identified in a number of geographical (ecological) studies (see para. 462 of annex A [U10]). Althoughthese studies indicated an association between the increased frequency and the accident, they had
inherent methodological problems. Subsequent case–control and cohort studies gave values of excess
relative rate that are consistent with those obtained from epidemiological studies of other groups ofchildren (see appendix D to annex B of this report) and show trends of increased frequency of thyroid
cancer with absorbed dose to the thyroid primarily from internal exposure.

74 UNSCEAR 2012 REPORT

B26.
Nevertheless, other possible causes would need to be considered before attributing theobserved increased frequency to radiation exposure. The increased use of screening of the thyroid may
have played a role in the observed increased frequency of cancer. Ideally, it would be important toreview analytical studies that use estimates of dose to individuals, and to compare the results withstudies of children who were not exposed but were subject to similar screening techniques. Strong
indication that increased use of screening was not the main reason for the higher observed frequency of
thyroid cancer is obtained from studies of those born after 1986 (as indicated above), which showed noevidence for an increase in the frequency of thyroid cancer, even though they could have been
subjected to increased medical surveillance. It has been estimated that 60% of the Belarusian thyroid
cancer cases and 30% of the Ukrainian cases may be related to the radiation exposure [J1]. The
remaining increase in frequency is likely to be related to enhanced surveillance, improved diagnostic
technology and other non-radiation factors.
Figure B−I. Frequency in Belarus of thyroid cancer for children under 10 years old at diagnosis(annex D of [U14])
The baseline rate of thyroid cancer among children under age 10 years is very low (a few cases per million children per year)

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 75

C. Conclusion
B27.
Before the accident, an increased frequency of thyroid cancer had already been shown to be
attributable to external radiation exposure in childhood. As a consequence, an entirely reasonable
hypothesis would have been that internal exposure due to iodine-131 from the Chernobyl accident was
responsible for the observed increased frequency of thyroid cancer in Belarus, Ukraine and the fourmost affected regions of the Russian Federation. Use of the Bradford Hill guidelines (in particular,
strength, plausibility, consistency, specificity, temporality, and biological gradient, see [H6]) would
provide strong support for attributing, at least in part, the observed increased frequency to radiation
exposure in this particular case.
B28.
Counterfactual analysis would indicate that increased screening of the population could
account for some of the observed increased frequency of thyroid cancer, but certainly not all. Suchscreening that was undertaken following the accident would have led to the detection of many thyroid
nodules that would never lead to any clinically observed health effects and, therefore, would never be
detected outside of such screening programmes.
B29.
The analysis was facilitated by the fact that the thyroid of children is particularly
radiosensitive and the baseline rate of childhood thyroid cancer is very low (a few cases per million
children per year). This case study demonstrates that attribution of the increased frequency of cancer
within a radiosensitive population can be relatively straightforward.
B30.
In the absence of a biomarker to distinguish a radiation-related thyroid cancer from one that
occurs due to other causes, an observed thyroid cancer in an individual among the population of those
exposed as children or adolescents at the time of the accident cannot be unequivocally attributed toradiation exposure from the accident.

IV. LUNG CANCER FROM EXPOSURE TO RADON

A. Scenario
B31.
The arithmetic and geometric mean radon concentrations in 117 randomly selected homes in
Winnipeg, Canada, were found in a survey to be 148 and 112 Bq/m3, respectively [C2]. The geometricstandard deviation was 2.07 with 20% of homes exceeding a radon concentration of 200 Bq/m3. The
measured radon concentrations ranged from 20 to 483 Bq/m3. The question is whether it would bereasonable to predict an increased risk of lung cancer among the population and whether in any future
epidemiological study an increased frequency of lung cancer would be discernible.

76 UNSCEAR 2012 REPORT

B. Analysis
B32.
Radon decay products are well established as a cause of lung cancer, and a number of
epidemiological studies had clearly shown an increased frequency of lung cancer associated with theradon exposure of miners ([U11] annex E). Based on this information and the general scientificknowledge regarding the interaction of radiation with living cells, a reasonable hypothesis was that
exposure to radon in homes could also cause lung cancer (even recognizing that the exposure levels andconditions in mines are significantly different from those in homes). Risks from radon exposure inhomes had originally been estimated by extrapolations from the miner studies.
B33.
Now, however, there are more than 20 case–control studies of lung cancer and radon exposurein homes. While individual studies have limited power, pooled analyses of European [D1, D2], North
American [K5, K6] and Chinese [L6] studies provide a clear demonstration that an increased frequencyof lung cancer is significantly associated with radon exposure. Taken together with application of theBradford Hill guidelines (in particular, strength, plausibility, consistency, specificity, temporality, andbiological gradient, see [H6], there is good evidence that an increased frequency of lung cancer can be
attributed to radon exposure in dwellings when concentrations are significantly higher than average. In
one study [D1], the dose–response relationship appeared to be linear without threshold and the excess
relative rate at a concentration of 100 Bq/m3 was statistically significant at the 95% confidence level(annex E of UNSCEAR 2006 Report [U11]). Thus, it could be concluded that an increased risk of lungcancer in a population exposed to a concentration of radon of 100 Bq/m3 could be predicted undercertain conditions.
B34.
On the basis of the results from these studies, the Committee inferred an excess relative risk of
0.16 (95% CI: 0.05, 0.31) per 100 Bq/m3 as an appropriate, if possibly conservative, estimate of the
lifetime risk from exposure to radon in homes.
B35.
Inferences of the lifetime risk of lung cancer for given exposures to radon based on thisanalysis of the epidemiological information and the assumption that the exposure conditions aremaintained over 30 years are given in Table B1. Thus, for a population exposed to an average radon
concentration of about 150 Bq/m3, as in the Winnipeg study, an increased risk of 24% above thebaseline for each sex and smoking category can reasonably be predicted (i.e. can be regarded as wellfounded). The actual number of additional cases of lung cancer due to exposure to radon would bedominated by those who smoke, but is unlikely to be observable in the population in the homes thatwere surveyed here (number of homes, 117, which implies a population of around 500 on the basis ofan average of four individuals in each home). In fact, one case-control study of radon and lung cancer
in 1,438 persons in Winnipeg showed no increase in lung cancer for any histologic type [L4]. However,if the results of the survey were truly representative of the levels of exposure of the population ofWinnipeg as a whole (say 700,000 people), then an increased frequency of lung cancer ought to beobservable in that population.
B36.
An observed lung cancer in a particular individual cannot be unequivocally attributed to
exposure to radon because, at the present time, there is no way of distinguishing a radon-induced lungcancer from one that occurs through other causes, particularly smoking (based on a counterfactual
analysis).

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 77

Table B1. Baseline lung cancer risk and inferred lifetime risk of lung cancer to the average individual
in a population from exposure to radon: values are given separately for men and women, according
to whether they smoke or not
222

Inferred lifetime risk of lung cancera (%)

Rn concentration(Bq/m3)

Increased risk

Men whosmoke

Men who don’t
smoke

Women whosmoke

Women who
don’t smoke

Baselineb

0%

12

0. 9

6.8

0.6

100

16%

14

1.0

7.9

0.7

150

24%

15

1.1

8.4

0.7

300

48%

18

1.3

10

0.9

400

64%

20

1.5

11

1.0

a

The value used in calculation 0.16 (95% CI: 0.05, 0.31) for exposure to 100 Bq/m3 [D1].

bBaseline rate from [N6].

C. Conclusion
B37.
An increased frequency of lung cancer among miners had been attributed to exposure to radonin mines. On the basis of the pooling of results from large epidemiological studies, an increased
frequency of lung cancer in the general population can now be attributed to exposure to radon in homes
at elevated levels, specifically at concentrations greater than about 100 Bq/m3. Consequently, thelifetime risk of lung cancer in a population exposed to such elevated levels of radon (which is the casein the Winnipeg study), can be predicted provided that the exposure conditions remain constant forextended periods. The predicted increased frequency of lung cancer is unlikely to be observable among
the people living in the Winnipeg homes sampled because of the small numbers involved; however, if
the size of the population exposed at the same levels were large enough, then the predicted increased
frequency is potentially observable (i.e. the prediction is, in principle, testable).
B38.
An observed lung cancer in an individual cannot be unequivocally attributed to radon exposure(other possible causes cannot be excluded on the basis of a counterfactual analysis).

V. ESTIMATED RISK FROM COMPUTED TOMOGRAPHY SCANS
A. Scenario
B39.
Scientific knowledge is to be applied to compare the potential benefits and risks of various
types of imaging procedures used in medicine. The specific task is to express the confidence in inferredrisks for future cancer from radiation exposure due to computed tomography (CT) scanning in a
specific year. It is based on a published case study for the United States of America in 2007 (see [B7]).
Some 72 million CT scans were performed there that year. The frequencies of the different types of
examination were estimated from various data sources.

78 UNSCEAR 2012 REPORT

B. Analysis
B40.
A key factor in the estimation of lifetime risk of cancer due to radiation exposure is the life
expectancy of people receiving CT scans. Typically, there is at least a 5-year lag period between
radiation exposure and diagnosis of a solid cancer; therefore, it is very unlikely that patients who do notsurvive that long could have developed an observable cancer as a consequence of the exposure. Whenscans taken in the last 5 years of life as well as those scans related to the diagnosis of a cancer were
excluded, the number of CT scans considered in the study reduced to 57 million. Because radiationrelated cancer risks are known to depend on sex and age at exposure, data were obtained on the age andsex distribution for each type of CT scan.
B41.
Technical parameters (e.g. peak voltage and tube current–time product) for each scan type wereavailable from surveys [F2]. From this, doses to specific organs by age and sex were estimated for each typeof scan and model of scanner. Absorbed doses to organs in the field of the CT scan are of the order of a few
tens of milligrays, which are within the low-dose range defined in table 1 of the main text of this annex.
B42.
The published case study made conditional predictions of the risk to the population taking
account of the doses to individual organs and tissues, age at exposure and the inferred risks for eachcancer type for people exposed at various ages, based on extrapolation of data from epidemiologicalstudies of populations exposed at moderate or high doses. Models for the inference of risk (except forbreast and thyroid cancer) were developed using data from the latest follow-up of the survivors of theatomic bombings in Japan, because that study had the most detailed information available for most cancer
sites [P7]. The models for breast and thyroid cancer were based on the data obtained from pooled analysesof cohorts of the survivors of the atomic bombings and medically exposed people [P6, R1]. For solidcancers, a 5-year lag period and a linear dose–response model was assumed; moreover it was assumed thatthe risk per unit dose was 1.5 times lower for doses equal to or less than 100 mGy than that at higher doses[N7]. For leukaemia, a 2-year lag period and a linear–quadratic dose–response model were assumed.
B43.
Monte Carlo* simulation methods with sampling were used to estimate risks with uncertainty
intervals, accounting for statistical uncertainties in the risk parameters and subjective uncertainties inthe value of the dose and dose-rate effectiveness factor, as well as the transference of the observed
excess frequency in the population of the survivors of the atomic bombings in Japan, to estimate therisk for the United States population. Account was also taken of the uncertainty in the estimates of thebaseline cancer rate. The mean estimates with 95% uncertainty intervals were calculated from thesimulations [B7]. Whether these uncertainty intervals fully account for the uncertainties in thetransference from the 1945 Japanese population to United States children today remains an issue.
B44.
Large-scale epidemiological studies of cancer frequency in individuals who underwent CT
scans as children or adolescents are now being undertaken and some findings have been reported[P2]. 15 These reports indicate an increased frequency of cancer among those exposed to radiation
during CT scans, but one confounding factor is the potential influence of reverse causation: i.e. that thecancer, or factors predisposing to cancer, were present at the time of the scan, so that the cancer caused
the CT scan rather than the CT scan caused the cancer [U16]. While current studies may notdemonstrate unambiguously a link between radiation exposure due to a CT scan and the developmentof cancer, future studies may overcome current difficulties in interpretation and provide (or not)increased confidence in the interpretation (see appendix A).
15
The Committee is aware that studies of CT and cancer have been published after the 2012 findings were submitted to theUnited Nations General Assembly. These studies focus on those considered to be at greater risk (i.e. exposed at young age) andtheir interpretation needs to take into account such factors as pre-existing conditions and pre-disposition to disease. It was notpossible to full evaluate them for the purpose of this annex.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 79

C. Conclusion
B45.
The study results are conditional predictions. It was concluded that approximately 29,000(95% CI: 15,000, 45,000) future cancers could arise as a consequence of the use of CT scans in the
United States in 2007. It also showed that, because of the high frequency of use, the potential publichealth impact would be highest for adults aged 35 to 54 years, particularly among women. Thesecancers would arise over several decades following exposure. For the purpose of decision-making by
policy-making bodies and clinicians, this estimate could be used to compare the potential impact on
health of alternative diagnostic procedures. Even so, there are several points to note:(a) It may seem contradictory that the Committee has decided not to calculate absolute numbers ofcancers after radiation exposure at low and very low doses and, nevertheless, presents this casestudy. There are several reasons for this. Firstly, these analyses have been published on a current
medical practice of great public interest. Secondly, as already stated above, such studies may help
to compare the potential benefits and risks of various types of imaging procedures used in
medicine. And thirdly, some limitations that are outlined in the following have to be observed;(b) The estimated impact was inferred using science-based models. The evidence fromobservational studies is currently insufficient to confirm that the estimated numbers of cancers will
occur as a consequence of CT scans;(c) The estimated risk relates to CT scans conducted in one year. If the number of CT scans
continues at the same rate under the same conditions, then eventually the number of cancers due toCT scans would be expected to reach 29,000 (95% CI: 15,000, 45,000) each year. This would beon top of a baseline cancer frequency, which, in the United States is of the order of 1.4 million
cases each year [A2]. Thus, the inferred increase in the number of cancers would be of the order of
2% above the normal frequency in the general population, although more than 2% in the population
subjected to CT. An epidemiological study to demonstrate such an increase would involve
following hundreds of thousands of people over many years and a similar-sized, matched-control
group. It would also require adequate account to be taken of other factors that might influence theobserved frequency, which may be very difficult.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 81

REFERENCES
A1

Ainsbury, E.A., S.D. Bouffler, W. Dorr et al. Radiation cataractogenesis: a review of recent
studies. Radiat Res 172(1): 1-9 (2009).

A2

American Cancer Society. Cancer Facts & Figures 2008. American Cancer Society, Atlanta,
GA, 2008.

A3

Anderson, D.R. Model Based Inference in the Life Sciences: A Primer on Evidence. Springer,
New York, 2008.

B1

Balonov, M. and D. Louvat. The Chernobyl Forum completed. J Radiol Prot 25(4): 499-501(2005).

B2

Barcellos-Hoff, M.H. and S.V. Costes. A systems biology approach to multicellular and multigenerational radiation responses. Mutat Res 597(1-2): 32-38 (2006).

B3

Beninson, D. and B. Lindell. The evasive plausibility. J Radiol Prot 21(1): 39-44 (2001).

B4

Bentzen, S.M. Preventing or reducing late side effects of radiation therapy: radiobiology meetsmolecular pathology. Nat Rev Cancer 6(9): 702-713 (2006).

B5

Bentzen, S.M. From cellular to high-throughput predictive assays in radiation oncology:
challenges and opportunities. Semin Radiat Oncol 18(2): 75-88 (2008).

B6

Berrington de González, A. and S. Darby. Risk of cancer from diagnostic X-rays: estimates for
the UK and 14 other countries. Lancet 363(9406): 345-351 (2004).

B7

Berrington de González, A., M. Mahesh, K.P. Kim et al. Projected cancer risks from computed
tomographic scans performed in the United States in 2007. Arch Intern Med 169(22): 20712077 (2009).

B8

Beyea, J. and S. Greenland. The importance of specifying the underlying biologic model inestimating the probability of causation. Health Phys 76(3): 269-274 (1999).

B9

Bijwaard, H., A. Brenner, F. Dekkers et al. Breast cancer risk from different mammography
screening practices. Radiat Res 174(3): 367-376 (2010).

B10Blackburn, S. The Oxford dictionary of philosophy, Second edition revised. Oxford University
Press, New York, 2008.

B11

Boice, J.D., Jr. and R.W. Miller. Childhood and adult cancer after intrauterine exposure toionizing radiation. Teratology 59(4): 227-233 (1999).

B12

Brash, D.E., J.A. Rudolph, J.A. Simon et al. A role for sunlight in skin cancer: UV-induced
p53 mutations in squamous cell carcinoma. Proc Natl Acad Sci U S A 88(22): 10124-10128(1991).

B13

Brenner, D.J., R. Doll, D.T. Goodhead et al. Cancer risks attributable to low doses of ionizing
radiation: assessing what we really know. Proc Natl Acad Sci U S A 100(24): 13761-13766(2003).

82 UNSCEAR 2012 REPORT

B14

Brenner, D.J. and R.K. Sachs. Estimating radiation-induced cancer risks at very low doses:
rationale for using a linear no-threshold approach. Radiat Environ Biophys 44(4): 253-256(2006).

C1

Cardis, E., G. Howe, E. Ron et al. Cancer consequences of the Chernobyl accident: 20 years
on. J Radiol Prot 26(2): 127-140 (2006).

C2

Chen, J., E. Schroth, E. MacKinlay et al. Simultaneous 222Rn and 220Rn measurements in
Winnipeg, Canada. Radiat Prot Dosim 134(2): 75-78 (2009).

C3

COED. Concise Oxford English Dictionary. Oxford University Press, New York, 2008.

C4

COMEST. The precautionary principle. World Commission on the Ethics of Scientific
Knowledge and Technology. United Nations Educational, Scientific and Cultural
Organization, Paris, 2005.

C5

Crompton, N.E., M. Ozsahin, P. Schweizer et al. Theory and practice of predictive assays inradiation therapy. Strahlenther Onkol 173(2): 58-67 (1997).

D1

Darby, S., D. Hill, A. Auvinen et al. Radon in homes and risk of lung cancer: collaborative
analysis of individual data from 13 European case-control studies. Br Med J 330(7485): 223(2005).

D2

Darby, S., D. Hill, H. Deo et al. Residential radon and lung cancer--detailed results of acollaborative analysis of individual data on 7148 persons with lung cancer and 14,208 persons
without lung cancer from 13 epidemiologic studies in Europe. Scand J Work Environ Health32(Suppl 1): 1-83 (2006).

D3

Dauer, L.T., A.L. Brooks, D.G. Hoel et al. Review and evaluation of updated research on thehealth effects associated with low-dose ionising radiation. Radiat Prot Dosim 140(2): 103-136(2010).

D4

Doll, R. and R. Wakeford. Risk of childhood cancer from fetal irradiation. Br J Radiol 70:
130-139 (1997).

D5

Dordelmann, M., M. Schrappe, A. Reiter et al. Down's syndrome in childhood acutelymphoblastic leukemia: clinical characteristics and treatment outcome in four consecutive
BFM trials. Berlin-Frankfurt-Munster Group. Leukemia 12(5): 645-651 (1998).

D6

Doss, M. Evidence supporting radiation hormesis in atomic bomb survivor cancer mortality
data. Dose Response 10(4): 584-592 (2012).

E1

EEA. Late lessons from early warnings: the precautionary principle 1896–2000.
Environmental issue report no. 22. European Environment Agency, Copenhagen, 2001.

E2

Egger, M., G. Davey Smith, M. Schneider et al. Bias in meta-analysis detected by a simple,
graphical test. BMJ 315(7109): 629-634 (1997).

F1

Farmer, P.B. and R. Singh. Use of DNA adducts to identify human health risk from exposure
to hazardous environmental pollutants: the increasing role of mass spectrometry in assessing
biologically effective doses of genotoxic carcinogens. Mutat Res 659(1-2): 68-76 (2008).

F2

FDA. Nationwide Evaluation of X-Ray Trends (NEXT): Tabulation and graphical summary of2000 survey of computed tomography. CRCPD Publication E-07-2. US Food and Drug
Administration, Conference of Radiation Control Program Directors Inc., Washington, DC, 2007.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 83

F3

Fliedner, T.M., D. Graessle, V. Meineke et al. Pathophysiological principles underlying theblood cell concentration responses used to assess the severity of effect after accidental wholebody radiation exposure: an essential basis for an evidence-based clinical triage. Exp Hematol35(4 Suppl 1): 8-16 (2007).

F4

Fry, R.J. Deterministic effects. Health Phys 80(4): 338-343 (2001).

G1

Gerber, T.C., J.J. Carr, A.E. Arai et al. Ionizing radiation in cardiac imaging: a scienceadvisory from the American Heart Association Committee on Cardiac Imaging of the Council
on Clinical Cardiology and Committee on Cardiovascular Imaging and Intervention of theCouncil on Cardiovascular Radiology and Intervention. Circulation 119(7): 1056-1065 (2009).

G2

Gray, J.S. Statistics and the precautionary principle. Mar Pollut Bull 21(4): 174-176 (1990).

G3Greenland, S. Introduction to Bayesian statistics. pp.328-344 in: Modern Epidemiology, Third
edition (K.J. Rothman et al., eds.). Lippincott Williams & Wilkins, Philadelphia, 2008.

G4

Gusev, I.A., A.K. Guskova and F.A. Mettler Jr. Medical Management of Radiation Accidents.
Second edition. CRC Press, New York, 2001.

H1

Hall, E.J. and A.J. Giaccia. Radiobiology for the Radiobiologist. Sixth edition. Lippincott
Williams & Wilkins, Philadelphia, 2006.

H2

Hamilton, C.S., C.S. Potten, J.W. Denham et al. Response of human hair cortical cells to
fractionated radiotherapy. Radiother Oncol 43(3): 289-292 (1997).

H3

Hatzi, V.I., G.I. Terzoudi, C. Paraskevopoulou et al. The use of premature chromosome
condensation to study in interphase cells the influence of environmental factors on human
genetic material. Sci World J 6: 1174-1190 (2006).

H4

Health Council of the Netherlands. Prudent precaution. Publication no. 2008/18E. HealthCouncil of the Netherlands, The Hague, 2008.

H5

Heidenreich, W.F., J. Kenigsberg, P. Jacob et al. Time trends of thyroid cancer incidence inBelarus after the Chernobyl accident. Radiat Res 151(5): 617-625 (1999).

H6

Hill, A.B. The environment and disease: association or causation? Proc R Soc Med 58: 295300 (1965).

H7

Hofmann, B., S. Holm, J. Iversen et al. Chapter 1: Philosophy of Science. pp.1-32 in: Research
Methodology in the Medical and Biological Sciences (P. Laake et al., eds.). Elsevier, London,
2007.

H8

Holm, S. and T. Takala. High hopes and automatic escalators: a critique of some newarguments in bioethics. J Med Ethics 33(1): 1-4 (2007).

H9

Hulse, E.V. and R.H. Mole. Reflections on the terms stochastic and non-stochastic as currently
used in radiological protection. Br J Radiol 55(653): 321-324 (1982).

I1

IAEA. Biological dosimetry: chromosomal aberration analysis for dose assessment. Technical
Reports Series No. 260. International Atomic Energy Agency, Vienna, 1986.

I2

IARC. IARC Monographs on the evaluation of carcinogenic risks to humans. Ionizing
radiation, Part 1: X- and gamma (γ)-radiation, and neutrons. Volume 75. International Agency
for Research on Cancer, Lyon, 2000.

84 UNSCEAR 2012 REPORTI3

IARC. IARC Monographs on the evaluation of carcinogenic risks to humans. Ionizing
radiation, Part 2: Some internally deposited radionuclides. Volume 78. International Agency
for Research on Cancer, Lyon, 2001.

I4

IARC. Molecular epidemiology: principles and practices. IARC Scientific Publications No.
163 (N. Rothman et al., eds.). International Agency for Research on Cancer, WHO Press,
Geneva, 2011.

I5

IARC. IARC Monographs on the evaluation of carcinogenic risks to humans. A review ofhuman carcinogens. Radiation. Volume 100D. International Agency for Research on Cancer,
Lyon, 2012.

I6

ICRP. Genetic susceptibility to cancer. ICRP Publication 79. Annals of the ICRP 28(1-2).
International Commission on Radiological Protection, Pergamon Press, Oxford, 1998.

I7

ICRP. Avoidance of radiation injuries from medical interventional procedures. ICRP
Publication 85. Annals of the ICRP 30(2). International Commission on RadiologicalProtection, Elsevier, Oxford, 2001.

I8

ICRP. Biological effects after prenatal irradiation (embryo and fetus). ICRP Publication 90.
Annals of the ICRP 33(1-2). International Commission on Radiological Protection, Pergamon
Press, 2003.

I9

ICRP. Low-dose extrapolation of radiation-related cancer risk. ICRP Publication 99. Annals of
the ICRP 35(4). International Commission on Radiological Protection, Elsevier Ltd., 2005.

I10

ICRP. The 2007 Recommendations of the International Commission on RadiologicalProtection. ICRP Publication 103. Annals of the ICRP 37(2-4). International Commission on
Radiological Protection, Elsevier Ltd., 2007.

I11

ICRP. ICRP statement on tissue reactions / Early and late effects of radiation in normal tissues
and organs – Threshold doses for tissue reactions in a radiation protection context. ICRP
Publication 118. Annals of the ICRP 41(1-2). International Commission on RadiologicalProtection, Elsevier Ltd., 2012.

I12

ILO, IAEA and WHO. Approaches to attribution of detrimental health effects to occupational
ionizing radiation exposure and their application in compensation programmes for cancer.
Occupational Safety and Health Series No. 73 (S. Nui et al., eds.). International Labour
Organization, Geneva, 2010.

I13

Ioannidis, J.P. Why most published research findings are false. PLoS Med 2(8): e124 (2005).

I14

IPCC. Guidance note for lead authors of the IPCC fifth assessment report on consistenttreatment of uncertainties. IPCC Cross-Working Group Meeting on Consistent Treatment ofUncertainties, Jasper Ridge, CA, USA, 6-7 July 2010. Intergovernmental Panel on Climate
Change, 2010.

J1

Jacob, P., T.I. Bogdanova, E. Buglova et al. Thyroid cancer among Ukrainians and Belarusians
who were children or adolescents at the time of the Chernobyl accident. J Radiol Prot 26(1):51-67 (2006).

J2

Jacob, P., T.I. Bogdanova, E. Buglova et al. Thyroid cancer risk in areas of Ukraine andBelarus affected by the Chernobyl accident. Radiat Res 165(1): 1-8 (2006).

J3

Jacob, P., W. Ruhm, L. Walsh et al. Is cancer risk of radiation workers larger than expected?
Occup Environ Med 66(12): 789-796 (2009).

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 85

J4

Johnston, P. and M. Simmonds. Precautionary principle. Mar Pollut Bull 21(8): 402 (1990).

J5

Johnston, P. and M. Simmonds. Green light for precautionary science. New Sci 1780: 4 (1991).

K1

Kennedy, A.R. Factors that modify radiation-induced carcinogenesis. Health Phys 97(5): 433445 (2009).

K2

Koenig, T.R., F.A. Mettler and L.K. Wagner. Skin injuries from fluoroscopically guided
procedures: part 2, review of 73 cases and recommendations for minimizing dose delivered topatient. AJR Am J Roentgenol 177(1): 13-20 (2001).

K3

Koenig, T.R., D. Wolff, F.A. Mettler et al. Skin injuries from fluoroscopically guided
procedures: part 1, characteristics of radiation injury. AJR Am J Roentgenol 177(1): 3-11 (2001).

K4

Kraemer, K.H., N.J. Patronas, R. Schiffmann et al. Xeroderma pigmentosum,
trichothiodystrophy and Cockayne syndrome: a complex genotype-phenotype relationship.
Neuroscience 145(4): 1388-1396 (2007).

K5

Krewski, D., J.H. Lubin, J.M. Zielinski et al. Residential radon and risk of lung cancer: a
combined analysis of 7 North American case-control studies. Epidemiology 16(2): 137-145(2005).

K6

Krewski, D., J.H. Lubin, J.M. Zielinski et al. A combined analysis of North American casecontrol studies of residential radon and lung cancer. J Toxicol Environ Health A 69(7): 533597 (2006).

L1

Land, C.E. Estimating cancer risks from low doses of ionizing radiation. Science 209(4462):
1197-1203 (1980).

L2

Land, C.E. Uncertainty, low-dose extrapolation and the threshold hypothesis. J Radiol Prot
22(3A): A129-135 (2002).

L3

Land, C.E., E. Gilbert, J.M. Smith et al. Report of the NCI-CDC Working Group to Revise the1985 NIH Radioepidemiological Tables. NIH Publication 03-5387. National Cancer Institute,
Bethesda, MD, 2003.

L4

Letourneau, E.G., D. Krewski, N.W. Choi et al. Case-control study of residential radon andlung cancer in Winnipeg, Manitoba, Canada. Am J Epidemiol 140(4): 310-322 (1994).

L5

Little, M.P., R. Wakeford, E.J. Tawn et al. Risks associated with low doses and low dose rates
of ionizing radiation: why linearity may be (almost) the best we can do. Radiology 251(1):6-12 (2009).

L6

Lubin, J.H., Z.Y. Wang, J.D. Boice, Jr. et al. Risk of lung cancer and residential radon in
China: pooled results of two studies. Int J Cancer 109(1): 132-137 (2004).

M1

Mark Elwood, J. Critical Appraisal of Epidemiological Studies and Clinical Trials. UOP,
Oxford, 2007.

M2

Morgan, W.F. and W.J. Bair. Issues in low dose radiation biology: the controversy continues.
A perspective. Radiat Res 179(5): 501-510 (2013).

M3

Morrell, D., E. Cromartie and M. Swift. Mortality and cancer incidence in 263 patients withataxia-telangiectasia. J Natl Cancer Inst 77(1): 89-92 (1986).

M4

Mullenders, L., M. Atkinson, H. Paretzke et al. Assessing cancer risks of low-dose radiation.
Nat Rev Cancer 9(8): 596-604 (2009).

86 UNSCEAR 2012 REPORT

M5

Müller, W.-U. and C. Streffer. Micronucleus assays. pp.185-194 in: Advances in Mutagenesis
Research (G. Obe, ed.). Springer-Verlag, New York, 1994.

M6

Müller, W.-U. Comet assay. pp.161-176 in: Chromosomal Alterations: Methods, Results andImportance in Human Health (G. Obe and Vijayalaxmi, eds.). Springer-Verlag, Berlin, 2007.

M7

Murphy, C.C., C. Boyle, D. Schendel et al. Epidemiology of mental retardation in children.
Mental Retardation and Developmental Disabilities Research Reviews 4: 6-13 (1998).

N1

NCI/SEER. Cancer Stat Fact Sheets. National Cancer Institute, Surveillance, Epidemiology,
and End Results Program. [Internet] Available from (http://seer.cancer.gov/statfacts/)

N2

NCRP. Second primary cancers and cardiovascular disease after radiation therapy. NCRP
Report No. 170. National Council on Radiation Protection and Measurements, Bethesda, 2011.

N3

NCRP. Uncertainties in the estimation of radiation risks and probability of disease causation.
NCRP Report No. 171. National Council on Radiation Protection and Measurements,
Bethesda, 2012.

N4

Neumaier, T., J. Swenson, C. Pham et al. Evidence for formation of DNA repair centers anddose-response nonlinearity in human cells. Proc Natl Acad Sci U S A 109(2): 443-448 (2012).

N5

Nicolich, M.J. and J.F. Gamble. What is the minimum risk that can be estimated from anepidemiology study? Chapter 1 in: Advanced Topics in Environmental Health and Air
Pollution Case Studies (A. Moldoveanu, ed.). InTech, 2011.

N6

NRC. Risk assessment of radon in drinking water (Committee on Risk Assessment ofExposure to Radon in Drinking Water). National Research Council, National Academy Press,
Washington, D.C., 1999.

N7

NRC. Health risks from exposure to low levels of ionizing radiation. Committee to Assess
Health Risks from Exposure to Low Levels of Ionizing Radiation, BEIR VII - Phase 2.
National Research Council, The National Academies Press, Washington D.C., 2006.

O1

Office of the Surgeon General and Office on Smoking and Health. The health consequences ofsmoking: A report of the Surgeon General. Centers for Disease Control and Prevention,
Atlanta, GA, 2004.

O2

Otake, M. and W.J. Schull. In utero exposure to A-bomb radiation and mental retardation; areassessment. Br J Radiol 57(677): 409-414 (1984).

O3

Otake, M. and W.J. Schull. Radiation-related brain damage and growth retardation among theprenatally exposed atomic bomb survivors. Int J Radiat Biol 74(2): 159-171 (1998).

O4

Ozasa, K., Y. Shimizu, A. Suyama et al. Studies of the mortality of atomic bomb survivors,
Report 14, 1950-2003: An overview of cancer and noncancer diseases. Radiat Res 177(3):229-243 (2012).

P1

Parsons, B.L. Many different tumor types have polyclonal tumor origin: evidence andimplications. Mutat Res 659(3): 232-247 (2008).

P2

Pearce, M.S., J.A. Salotti, M.P. Little et al. Radiation exposure from CT scans in childhoodand subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet
380(9840): 499-505 (2012).

P3

Pollard, J.M. and R.A. Gatti. Clinical radiation sensitivity with DNA repair disorders: an
overview. Int J Radiat Oncol Biol Phys 74(5): 1323-1331 (2009).

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 87

P4

Popper, K.R. The Logic of Scientific Discovery. Basic Books, New York, 1959.

P5

Portess, D.I., G. Bauer, M.A. Hill et al. Low-dose irradiation of nontransformed cells
stimulates the selective removal of precancerous cells via intercellular induction of apoptosis.
Cancer Res 67(3): 1246-1253 (2007).

P6

Preston, D.L., A. Mattsson, E. Holmberg et al. Radiation effects on breast cancer risk: a pooled
analysis of eight cohorts. Radiat Res 158(2): 220-235 (2002).

P7

Preston, D.L., E. Ron, S. Tokuoka et al. Solid cancer incidence in atomic bomb survivors:
1958-1998. Radiat Res 168(1): 1-64 (2007).

P8

Preston, R.J., J.D. Boice Jr., A. Bertrand Brill et al. Uncertainties in estimating health risks
associated with exposure to ionising radiation. J Radiol Prot 33(3): 573-588 (2013).

Q1

Qi, J.P., S.H. Shao, J. Xie et al. A mathematical model of P53 gene regulatory networks underradiotherapy. Biosystems 90(3): 698-706 (2007).

R1

Ron, E., J.H. Lubin, R.E. Shore et al. Thyroid cancer after exposure to external radiation: apooled analysis of seven studies. Radiat Res 141(3): 259-277 (1995).

R2

Rothman, K.J., S. Greenland and T.L. Lash. Modern Epidemiology. Third edition. Lippincott
Williams & Wilkins, Philadelphia, 2008.

S1

Sigurdson, A.J. and D.O. Stram. Genetic predisposition to radiation-related cancer andpotential implications for risk assessment. Ann ICRP 41(3-4): 108-116 (2012).

S2

Swift, M., D. Morrell, R.B. Massey et al. Incidence of cancer in 161 families affected byataxia-telangiectasia. N Engl J Med 325(26): 1831-1836 (1991).

S3

Szumiel, I. Analysis of DNA double-strand breaks by means of γ-H2AX foci. pp.145-160 in:
Chromosomal Alterations: Methods, Results and Importance in Human Health (G. Obe andVijayalaxmi, eds.). Springer-Verlag, Berlin, 2007.

T1

Tallacchini, M. Before and beyond the precautionary principle: epistemology of uncertainty inscience and law. Toxicol Appl Pharmacol 207(2 Suppl): 645-651 (2005).

T2

Tanooka, H. X chromosome inactivation-mediated cellular mosaicism for the study of themonoclonal origin and recurrence of mouse tumors: a review. Cytogenet Genome Res
104(1-4): 320-324 (2004).

T3

Taubes, G. Epidemiology faces its limits. Science 269(5221): 164-169 (1995).

T4

Toledano, S.R. and B.J. Lange. Ataxia-telangiectasia and acute lymphoblastic leukemia.
Cancer 45(7): 1675-1678 (1980).

T5

Torres-Roca, J.F. and C.W. Stevens. Predicting response to clinical radiotherapy: past, present,
and future directions. Cancer Control 15(2): 151-156 (2008).

T6

Tranøy, K.E. Science and ethics. Some of the main principles and problems. pp.111-136 in:
The Moral Import of Science: Essays on Normative Theory, Scientific Activity andWittgenstein (A.J.I. Jones, ed.). Sigma Forlag, Bergen, 1988.

T7

Tubiana, M., A. Aurengo, D. Averbeck et al. Dose-effect relationships and estimation of the
carcinogenic effects of low doses of ionizing radiation. Joint Report No. 2. Académie desSciences, Académie nationale de Médecine, Paris, 2005.

88 UNSCEAR 2012 REPORT

T8

Tubiana, M., A. Aurengo, D. Averbeck et al. Recent reports on the effect of low doses ofionizing radiation and its dose-effect relationship. Radiat Environ Biophys 44(4): 245-251(2006).

T9

Tucker, J.D. Low-dose ionizing radiation and chromosome translocations: a review of the
major considerations for human biological dosimetry. Mutat Res 659(3): 211-220 (2008).

U1

UNSCEAR. Official Records of the General Assembly, Thirteenth Session, Supplement No.
17 (A/3838). UNSCEAR 1958 Report. United Nations Scientific Committee on the Effects ofAtomic Radiation. United Nations, New York, 1958.

U2

UNSCEAR. Sources and Effects of Ionizing Radiation. UNSCEAR 1977 Report. United
Nations Scientific Committee on the Effects of Atomic Radiation, 1977 Report to the General
Assembly, with annexes. United Nations sales publication E.77.IX.1. United Nations, New
York, 1977.

U3

UNSCEAR. Ionizing Radiation: Sources and Biological Effects. UNSCEAR 1982 Report.
United Nations Scientific Committee on the Effects of Atomic Radiation, 1982 Report to theGeneral Assembly, with annexes. United Nations sales publication E.82.IX.8. United Nations,
New York, 1982.

U4

UNSCEAR. Genetic and Somatic Effects of Ionizing Radiation. UNSCEAR 1986 Report.
United Nations Scientific Committee on the Effects of Atomic Radiation, 1986 Report to theGeneral Assembly, with annexes. United Nations sales publication E.86.IX.9. United Nations,
New York, 1986.

U5

UNSCEAR. Sources, Effects and Risks of Ionizing Radiation. UNSCEAR 1988 Report.
United Nations Scientific Committee on the Effects of Atomic Radiation, 1988 Report to theGeneral Assembly, with annexes. United Nations sales publication E.88.IX.7. United Nations,
New York, 1988.

U6

UNSCEAR. Sources and Effects of Ionizing Radiation. UNSCEAR 1993 Report. United
Nations Scientific Committee on the Effects of Atomic Radiation, 1993 Report to the General
Assembly, with scientific annexes. United Nations sales publication E.94.IX.2. United
Nations, New York, 1993.

U7

UNSCEAR. Sources and Effects of Ionizing Radiation. UNSCEAR 1994 Report. United
Nations Scientific Committee on the Effects of Atomic Radiation, 1994 Report to the General
Assembly, with scientific annexes. United Nations sales publication E.94.IX.11. United
Nations, New York, 1994.

U8

UNSCEAR. Sources and Effects of Ionizing Radiation. Volume II: Effects. UNSCEAR 2000
Report. United Nations Scientific Committee on the Effects of Atomic Radiation, 2000 Reportto the General Assembly, with scientific annexes. United Nations sales publication E.00.IX.4.
United Nations, New York, 2000.

U9

UNSCEAR. Hereditary Effects of Radiation. UNSCEAR 2001 Report. United Nations
Scientific Committee on the Effects of Atomic Radiation, 2001 Report to the General
Assembly, with scientific annex. United Nations sales publication E.01.IX.2. United Nations,
New York, 2001.

U10

UNSCEAR. Effects of Ionizing Radiation. Volume I: Report to the General Assembly,
Scientific Annexes A and B. UNSCEAR 2006 Report. United Nations Scientific Committee
on the Effects of Atomic Radiation. United Nations sales publication E.08.IX.6. United
Nations, New York, 2008.

ANNEX A: ATTRIBUTING HEALTH EFFECTS TO IONIZING RADIATION EXPOSURE [...] 89

U11

UNSCEAR. Effects of Ionizing Radiation. Volume II: Scientific Annexes C, D and E.
UNSCEAR 2006 Report. United Nations Scientific Committee on the Effects of Atomic
Radiation. United Nations sales publication E.09.IX.5. United Nations, New York, 2009.

U12

UNSCEAR. Sources and Effects of Ionizing Radiation. Volume I: Sources: Report to theGeneral Assembly, Scientific Annexes A and B. UNSCEAR 2008 Report. United Nations
Scientific Committee on the Effects of Atomic Radiation. United Nations sales publication
E.10.XI.3. United Nations, New York, 2010.

U13

UNSCEAR. Report of the United Nations Scientific Committee on the Effects of Atomic
Radiation 2010. Fifty-seventh session, includes Scientific Report: Summary of low-doseradiation effects on health. UNSCEAR 2010 Report. United Nations Scientific Committee on
the Effects of Atomic Radiation. United Nations sales publication M.II.IX.4. United Nations,
New York, 2011.

U14

UNSCEAR. Sources and Effects of Ionizing Radiation. Volume II: Effects. Scientific Annexes
C, D and E. UNSCEAR 2008 Report. United Nations Scientific Committee on the Effects ofAtomic Radiation. United Nations sales publication E.11.IX.3. United Nations, New York,
2011.

U15

UNSCEAR. Biological Mechanisms of Radiation Actions at Low Doses (White Paper).
United Nations Scientific Committee on the Effects of Atomic Radiation. United Nations,
New York, 2012.

U16

UNSCEAR. Sources, Effects and Risks of Ionizing Radiation. Volume II: Scientific Annex B.
UNSCEAR 2013 Report. United Nations Scientific Committee on the Effects of Atomic
Radiation. United Nations sales publication E.14.IX.2. United Nations, New York, 2013.

U17

UNSCEAR. Sources, Effects and Risks of Ionizing Radiation. Volume I: Report to theGeneral Assembly and Scientific Annex A. UNSCEAR 2013 Report. United Nations
Scientific Committee on the Effects of Atomic Radiation. United Nations sales publication
E.14.IX.1. United Nations, New York, 2014.

V1

Vaño, E., J. Goicolea, C. Galvan et al. Skin radiation injuries in patients following repeatedcoronary angioplasty procedures. Br J Radiol 74(887): 1023-1031 (2001).

V2

Vlietstra, R.E., L.K. Wagner, T. Koenig et al. Radiation burns as a severe complication offluoroscopically guided cardiological interventions. J Interv Cardiol 17(3): 131-142 (2004).

W1

Wakeford, R. and M.P. Little. Risk coefficients for childhood cancer after intrauterine
irradiation: a review. Int J Radiat Biol 79(5): 293-309 (2003).

W2

Wakeford, R. Childhood leukaemia following medical diagnostic exposure to ionizing
radiation in utero or after birth. Radiat Prot Dosim 132(2): 166-174 (2008).

W3

Wakeford, R. The risk of childhood leukaemia following exposure to ionising radiation--areview. J Radiol Prot 33(1): 1-25 (2013).

W4

Weinberg, A.M. Science and trans-science. Minerva 10(2): 209-222 (1974).

W5Whitehead, K., A. Kish, M. Pan et al. An integrated systems approach for understanding
cellular responses to gamma radiation. Mol Syst Biol 2: 47 (2006).

W6

WHO. Health effects of the Chernobyl accident and special health care programmes. Report of
the UN Chernobyl Forum Expert Group "Health" (B. Bennett et al., eds.). World HealthOrganization, Geneva, 2006.

90 UNSCEAR 2012 REPORT

W7Williams, E.D., A. Abrosimov, T. Bogdanova et al. Thyroid carcinoma after Chernobyl latent
period, morphology and aggressiveness. Br J Cancer 90(11): 2219-2224 (2004).

W8

Woodward, M. Epidemiology: Study Design and Data Analysis. Second edition. Chapman &Hall/CRC, Boca Raton, Florida, 2005.

W9

Wynne, B.E. and S. Mayer. How science fails the environment: If politicians don't like
uncertainties and scientists often conceal them, how can we make policies that deal with thevagaries of the world around us? New Sci 139(1876): 33-35 (1993).