**The Future of Risk Assessment: a Round Table**

*Participants:* FA Cucinotta[^1], AJ Fornace,[^2] RJM Fry,[^3] D
Goodhead,[^4] PG Groer[^5] and W. Schimmerling[^6] (moderator)

[Introductory Remarks]{.underline} (Schimmerling):

In the movie "Marathon Man" Dustin Hoffman is pursued by a mad dentist
who keeps asking him, "Is it safe?" It takes a number of painful moments
before the issue is resolved (not in the affirmative) and the meaning of
"it" becomes clear. At a less dramatic level, the concern and its
urgency are daily felt by the public: is it safe? This, at the barest
and most primitive level, is the critical question addressed by risk
*assessment*. However, safety is always relative and never permanent.
Risk *prediction* (or risk *estimation*) addresses the question: will it
be safe? If either of these answers turns out to be negative, risk
*management* has to address the issue of how to make "it" safe. Finally,
*archival* risk assessment is required, for legal as well as moral
reasons, to assure that, indeed, it was safe (or to establish who was to
blame if it was not!).

What is "safe"? And how can we tell? The participants in this round
table were asked to consider these two interrelated questions in
addressing the future of risk assessment.

In order to answer the first question, it was suggested that the
following should be addressed:

-   How does one establish confidence levels and how does one use them
    to determine a \"safe\" risk level?

-   Who decides what is safe?

-   What are ethical criteria for deciding?

-   What are risk endpoints to use?

-   What are critical data needs to improve the current approach to risk
    assessment and to develop models?

There are two complementary paradigms to examine ethical approaches to
risk assessment and risk management.[^7] One of these is based on
utilitarian ethical principles seeking to balance the societal versus
the individual responsibility for risk while the other is an informed
consent paradigm, whereby each individual accepts risks based on his or
her individual cost/benefit estimates. The former derives from a
consideration of societal needs for individuals (e.g., soldiers,
firemen, police officers, miners, research subjects) to assume risks for
a perceived greater good. The current NASA radiation limits[^8] are
based on a comparison of space radiation risks with risks common to
industries with a median level of risk. The assumption made is that, in
these industries, the levels of risk accepted represent a social
consensus.

The informed consent paradigm is an extension of the principle that
establishes government by consent of the governed. However, there are
limits to consent: no one may sell himself into slavery and society also
establishes limits on other risks to which individuals might otherwise
wish to consent. On the other hand, contractual rights and obligations
of any employment imply acceptance of a compact, whereby the employer is
engaged to minimize the risks associated with the workplace (most often
enforced by law), and the worker accepts to incur the risks associated
with the work performed.

The determination of what is acceptable is an ongoing ethical task that
needs to be reexamined continually. Its foremost purpose is the
protection of individual human beings but, in defining the limits of
exposure to risk, the process also provides for work requirements that
meet societal needs.

How can we tell? The answer to this question requires the development of
risk endpoint predictors. Among predictors of radiation risk are dose,
flux, dose equivalent and biomarkers. The use of risk predictors
involves consideration of a different set of questions:

-   What are the criteria for their validity?

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-   They are different for individual vs. population risk predictors

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-   How should we use them:

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-   To limit career exposure?

-   To limit mission operations?

-   To initiate aggressive medical surveillance? (e.g., should everyone
    with a certain number of chromosome aberrations of a certain type
    have medical diagnostic procedures every 6 weeks, or have a
    restricted diet, or take a Vitamin E pill every day?)

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-   Which biomarkers are ready to be used? For those that are not ready
    to be used (all?) when will they be ready?

-   What is the statistical power for predicting risk of various
    predictors?

The following requirements for such risk predictors, in particular for
biological indicators of radiation risk, need to be considered:

-   **sensitivity** to the levels of radiation exposure of concern

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-   [unequivocal]{.underline}: not sensitive to confounding factors
    (high signal-to-noise ratio)

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-   **accuracy** of predictions

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-   predict risk and health care decisions at a
    [well-defined]{.underline} [level]{.underline} [of]{.underline}
    [confidence]{.underline}

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-   **specificity** of prediction

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-   plausible [causal]{.underline} relationship based on testable
    mechanisms of radiation action, rather than just a contingent
    [correlation]{.underline} with radiation exposure

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-   **precision:** the results are not significantly distorted by
    individual or circumstantial variations in radiation response

-   lead to **diagnostic procedures** that are:

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-   [practical]{.underline} under actual circumstances of exposure
    rather than only under highly restricted laboratory conditions

-   [cost-effective]{.underline} , to screen large populations where
    required

[Notes for the Round-Table Discussion]{.underline} (Fry)

Most, if not all, human endeavors and even daily activity involve risk.
The dividing line with regard to attitude to risk is a combination of
whether the risk is taken voluntarily and a personal unscientific and
pragmatic assessment of the risk/ benefit.

Risk has been examined more extensively in the case of radiation than
any other agent. In medicine the ethical use of radiation is a fairly
easy decision because the benefit can almost always be shown, even if
precise values cannot be placed on the risk and the benefit.

Occupations involving radiation have been long regulated, in part
because it is possible to measure the amount of exposure involved. What
has not been so easy is to assess the risk and having done so come to a
mainly arbitrary decision of what risk workers (and the general
population) should be asked to accept. In the case of radiation risk and
space activities the risks involved in hurtling into space seem much
more significant. But it is the question of what risk there is of late
effects, in particular, cancer later in life after the career in space
is over that is important. The first attempt to deal with this problem
was based on a doubling of the risk of leukemia in a certain age range.
In 1989 NCRP^2^ suggested that a 3% excess in lifetime cancer mortality
might be "acceptable." This was based on the comparative risks entailed
in different occupations. The 3% was representative of occupations that
were neither the safest nor the most risky. Risk in agriculture,
manufacturing and other occupations is based on fatal accidents which
result in a greater loss of lifespan than is the case for cancer, a
disease, in general, late in life. NCRP introduced for the first time
different dose limits taking into account age and gender. The reasoning
was to have the same risk independent of age at first exposure or
gender, which was thought to be more equitable and non-discriminatory.

The new recommendations[^9] are more restrictive and reflect the
increase in data for the atomic bomb survivors. The limits are still
based on 3% excess lifetime cancer mortality but now to make the risks
comparable to those incurred by the occupationally exposed on Earth. The
ICRP and NCRP limits for terrestrial workers have the potential for
about a 3% excess of stochastic effects. While there may be a greater
probability of the maximum dose limits being reached in space NASA has
in the past designed its missions taking into account ALARA (as low as
reasonably achievable).

Hopefully, nobody will be talking to the public about a space mission
that "it is safe" but using the information given above to make the case
that the approach to radiation protection is both reasoned and
reasonable. It is easier to identify areas of uncertainties than to
establish confidence levels but quantification of the uncertainty of
risk estimates of stochastic effects is still a difficult task and full
of uncertainty!

Astronauts and cosmonauts are eager to be chosen for missions but full
information about the risks of effects that may occur both during and
after the career must be available and kept up to date as information
improves. NASA has to have OSHA's agreement on radiation protection
practices and that puts bounds on what missions NASA can undertake.
NCRP's recommendations are based on protection against risk but
cognizant of the problems of accomplishing missions if limits are over
restrictive.

Currently the radiation protection standards for stochastic effects used
internationally are based on mortality and while a move to the use of
incidence may take place in the future it seems sensible to base the
risks to those exposed in space on the same criteria as those used for
occupationally exposed workers.

The major areas of uncertainty in the current estimates of risk for
low-LET radiation lie in the adjustment of the effect of protracting
exposure and lowering the dose rate on both stochastic and deterministic
effect, and in the case of stochastic effects, how to transfer the risk
estimates based on the atomic bomb survivors to other populations.

The choice of the risk projection model has a significant impact because
about 50% of the atomic bomb survivors are still living and what happens
to those that were at a young age when exposed will influence subsequent
risk estimates. The fact that no data exist for the risk of the effects
of exposure of humans to protons, neutrons or heavy ions means we must
rely on experimental data, mainly experimental animal data, and have an
acceptable method of extrapolating the results across species. The lack
of new data for the stochastic effects of the types of radiation
experienced in space is regrettable and has stifled any improvement in
the relevant risk estimates.

While obviously there would be advantages in going to the use of fluence
it appears that we should stick with equivalent doses for the meantime
and that these should be based on quality factors and not WR s.

In the case of deterministic effects there is a need for estimates of
threshold doses of neutrons in the relevant energy range and of heavy
ions for effects in the tissues such as skin, the bone marrow, the lens
of the eye and the gonads. It is the threshold doses of late
deterministic effects for protracted low-dose-rate-exposures that are
particularly important.

Limiting career exposures and preventing high doses of high dose-rate
exposures seem to be to the most effective way of protecting space
workers. Family medical histories presumably will become increasingly
important but is there any evidence that approaches other than good
medical practice in both the selection and surveillance will improve the
chances of space workers of avoiding the risks of radiation? Reduction
of exposure must remain central to protection.

[Gene]{.underline} [Induction]{.underline} [after]{.underline}
[Radiation]{.underline} [Exposure]{.underline} (SA Amundson and AJ
Fornace, Jr.)

The focus of our efforts has been to determine the transcriptional
(mRNA) responses of human cells to ionizing radiation. Our results
indicate that responses in both a human myeloid tumor cell line
(ML-1)[^10] and in peripheral blood lymphocytes (PBL)[^11] irradiated ex
vivo are proportional to dose. Thus, our studies so far indicate a
linear rather than a threshold type dose response at doses as low as 2
cGy. In the case of high LET radiation, we have observed a shift in the
dose response that is roughly proportional to the RBE and again a linear
dose response was observed.

Gene expression profiling, while not yet at a stage where it can be used
to predict risk, is very promising for future risk prediction. The key
will be defining sets of genes that are informative for different
outcomes of interest One approach could exploit differences in gene
expression patterns between different individuals, and using an
informatic analysis determine which expression patterns correlate with
unusual sensitivity to environmental exposures such as ionizing
radiation, or an increased tendency to manifest a certain disease state,
such as cancer. Additional and perhaps more specific information may be
obtained by defining changes in expression profiles that occur after
exposure to a specific agent. A generalized post-exposure profile may
aid in identifying exposed individuals within a population, and it may
even be possible to find identifying fingerprints for different agents,
and for the time and approximate dose of exposure. As such work
continues, it may be possible to identify individual variation in
post-exposure profiles that may correlate with the outcome of exposure.
One example of this might be identifying patients likely to fail
radiotherapy from their gene expression profile following the first
fraction. This would allow alternate therapies to be begun at an earlier
stage of treatment. In the case of occupational or environmental
exposures, such profiles may identify those individuals most in need of
preventive treatment to avoid long term effects

Patterns indicating previous exposure are probably closer than those
defining individual susceptibility. Issues such as dose, time of
exposure and radiation quality may be discernable from gene expression
signatures, although it is likely such diagnosis will be more difficult
if all are unknown. Current technology is at the point of collecting
expression profiles. A significant amount of data will be needed to
search for meaningful correlations with various risks, and any suspected
correlation between profile and outcome must be established and tested
for this tool to become of practical use.

[Notes for the Round Table Discussion]{.underline} (Goodhead)

I should like to make a few comments about what is a "safe" dose, what
are small risks and how we explain these to the people concerned. In
summary, I believe we must be fully open about what we do know, what we
don't know and the very large uncertainties in any numerical estimates.

From the current state of scientific knowledge, we cannot say with
confidence that there is any level of radiation, however small, that is
totally safe. There is quite strong evidence that a single particle
(even a single electron) can produce a chromosome aberration or other
mutation. This may well contribute to cancer. Unless we become nearly
certain that this cannot contribute to cancer under any circumstances,
then we cannot say that each electron does not carry some risk, even
though very small. So, although there are very large uncertainties about
low level effects, even possible thresholds in some or all situations,
we cannot deny from present knowledge that there may be a risk. We may
individually reach different judgements on the likelihood of these
options, but we cannot say that low level radiation is definitely safe.

For high-LET radiations the problem is somewhat less complicated. The
evidence is much stronger that a single high-LET particle does carry a
risk, and so the evidence for a threshold for carcinogenesis in general
(or other effects) is corresponding weaker.

In summary, we cannot with honesty claim a [safe]{.underline} level of
radiation. Therefore we are forced to make quantitative estimates of
risk, even at very low levels, to explain to the public; and at higher
levels, to set limits and to take avoidance measures according to what
is deemed to be an acceptable level of risk -- acceptable by society and
the individuals concerned.

Then I see the major problem that the risk estimates we come up with
have very large uncertainties, not only within the estimation approach
taken but even more so between possible approaches (paradigm shifts).

Uncertainties are large for low levels of low-LET radiation, such as
when the risk estimates are based on very large extrapolations from the
A-bomb survivors, to low doses, dose-rates, across populations, to
individual sensitivities, etc. But for low-LET radiations we do at least
have some firm, although very wide, limits available on the possible
range of the risk. At the one extreme there is the lower limit of zero
risk (to correspond to a true threshold for all cancers and for all
low-level scenarios of relevance). At the other extreme an absolute
upper limit is set by the number of so-called "natural" cancers if these
were attributed entirely to natural background radiation. Geographical
variations would almost certainly suggest that radiation risks are well
below this.

For high-LET radiation in general, the problem is very much worse
because we have so little relevant epidemiology; and we are looking to
quantify the risk for radiation exposures for which large population
experiences are not available.

As I discussed previously[^12] I believe that the quality factors or
tissue weighting factors inevitably have very large uncertainties (order
of magnitude, or maybe even more) when applied to particular radiations.
RBEs for human tumors collectively or for individual type are
essentially not available. Large variations in RBE between tumor types
are to be expected. I should expect that uniform whole body irradiation
of humans with HZE or high energy neutrons would lead to a substantially
different frequency spectrum of tumor types than that of low-LET
exposure (such as from the A-bomb). Thus any suggested quality factor
must be highly uncertain for overall risk, and much more so for specific
tumor sites.

Extreme limits of possible risk are much more difficult to set for
high-LET radiation because there is little natural environmental
exposure (apart from radon and progeny to the lung). The radon
epidemiology of miners suggests that the dosimetric/quality factor
approach is in error by at least a factor 3 for the case of radon
-particles and the lung -- and that is after strong attempts to
manipulate the lung dosimetry model to reach agreement. The miners show
a smaller risk than expected (by the factor of about 3).

But for other high LET exposures, there is very little information to
put limits on the risk. Few people have been exposed to the very
different tracks from HZE ions or high-energy neutrons, so this really
is a step into the unknown. Some limits may be set by epidemiology of
aircrew and space crew but such studies have low power. As an
illustration, the study of some 2700 Canadian pilots by Band *et al*
[^13] should not nearly approach the power needed to detect a risk based
on ICRP risk factors. The actual observation of significant excesses of
prostate tumors and AML (based on quite small numbers) would indicate
large underestimates in the ICRP-based estimates if the excesses were
indeed due to the cosmic radiation. But, alternatively, the observed
excesses may be due to chance or other factors not related to radiation.
So very large uncertainties remain.

In conclusion, it seems that we must continue to make the best estimates
of risk that are possible with current knowledge, but that we must
openly acknowledge that the uncertainties may be very large.

[Some Comments on the Future of Radiation Risk Assessment]{.underline}
(Groer)

The following, mostly technical, comments are divided into two parts.
Part I considers the situation when human data on cancer incidence
and/or mortality after exposure to ionizing radiation are available. The
shorter Part II deals with the situation when such data are not
available. Both parts describe to some extent the *status quo* of
radiation risk assessment and give my opinion on what could/should or
cannot be done in the future.

**Part I:**

If human data are available the tasks of risk assessment are estimation
of survival model parameters and prediction of future probabilities of
cancer occurrence with uncertain parameters. I feel strongly that
Bayesian methods should be used for parameter estimation and prediction.
These methods use exclusively probability to characterize uncertainty.
Graphs of probability densities can be used to show the remaining
uncertainty in figures. Probability based confidence intervals have the
natural interpretation of containing the true value of an uncertain
quantity with a certain probability. The usual frequentist confidence
intervals have a more complicated interpretation, which cannot be
rigorously translated into a probability statement. This causes problems
when derived probabilities (e.g. Probabilities of Causation), are wanted
by decision makers. Formalized decision making under uncertainty
requires assignment of probabilities to uncertain outcomes. Bayesian
methods deliver these probabilities conditioned on available
information. Point estimates are available gratis as the means and/or
modes of probability densities.

A greater variety of survival models should be considered and compared
by calculating the probability of fixed data conditional on the
different models. For example models with and without effect thresholds
should be compared.

A particular endpoint (e.g. leukemia) occurs "entangled"---to borrow an
adjective from physics---with other endpoints (e.g. lung cancer) in data
sets on exposed individuals. Since the common exposure influences both
endpoints they are at a minimum dependent through the effect of the
common exposure. The majority of present analyses assume independence of
times to the occurrence of different endpoints. Influence of dependence
on parameter estimation and model comparison should be studied with
biologically supported forms of dependence.

Often marginal distributions for single parameters are derived from
joint distributions by multidimensional numerical integration. This
poses challenging numerical problems.

Multi-stage (sub) cellular mathematical models for cancer rates may
provide supportive information on aspects of phenomenological models for
the analysis of epidemiological data (e.g. existence of a threshold). I
am however skeptical that it will be possible to formulate a multi-stage
model for cancer and estimate all parameters from the observed cancer
appearance and censoring times. (The "pure" endpoint is modeled the
"entangled" endpoint provides the observations.).

Presently "transportation" of risk estimates between human populations
presents challenges without practical solutions in sight.

**Part II:**

When human data are not available for the radiation type of interest
extrapolation from animal data and/or other systems exposed to the
radiation of interest is the next best thing. Extrapolation with
quantitative characterization of the uncertainty is best done with
hierarchical models. One model is encapsulated in another larger model
and so on...Probability calculus provides the linkage between known and
unknown probabilities and permits calculation of desired quantities and
their uncertainties. (Trigonometric exercises where a missing angle etc.
is determined from certain given pieces provide a good analogy for
extrapolation.)

Anchoring of the extrapolation with a pivotal data set on humans exposed
to a different type of radiation seems absolutely necessary for credible
extrapolation results. The data on A-bomb survivors will be the pivotal
data set for all extrapolations involving external radiation exposures.

An open challenge is extrapolation of the appearance time distribution
for a radiation type of interest from the pivotal data set with the help
of auxiliary information from other systems exposed to the radiation of
interest. Until now only risk parameters have been estimated by
extrapolation.

[Bioethics Perspective]{.underline} (Cucinotta)

NASA applies an informed consent paradigm to radiation exposures below
the accepted limits, as part of the implementation of ALARA (as low as
reasonably achievable) risk management. This requires training
astronauts to follow proper procedures when dealing with radiation and
to acquire a balanced perspective of the risks involved. There exists a
need for expanding this aspect of astronaut training, as well as raising
the consciousness of all personnel involved of the importance of
implementing ALARA.

Adequate support of research on which to base risk assessment is
essential. As shown elsewhere,[^14] a rational approach to risk
management will result in operational limits based on confidence levels
for risk. At present, acceptable confidence levels cannot be established
for very long duration missions. Even for low Earth orbit, establishing
acceptable confidence levels at current levels of uncertainty leads to
expenses far in excess of the cost of research to reduce uncertainty.
Thus, research is the most cost-effective way to manage risk.

Ethical and practical considerations require continuous examination of
the guidelines for radiation exposure limits. This is an ongoing task,
currently performed by the NCRP in the United States, and the ICRP in
Europe. Reconciliation of the sometimes incompatible approaches used by
different national and international organizations will be an important
aspect of ensuring radiation risk management for the International Space
Station and space exploration beyond Earth orbit.

[Selected Questions and Comments from the Audience]{.underline}
(responses are from several panel members if none are identified)

• What is the importance of genetic predisposition?

> Not very great, although there are individuals with a family history
> of radiosensitivity (e.g., *Ataxia telangiectasia*), and loss of
> heterozygocity may be a factor to consider.

• Can one find cancer resistant individuals?

> (Fornace/Groer) Cancer is a disease of aging and occurs late in life.
> It is possible to define a practical threshold, such that the delay in
> expected occurrence is greater than the expected life span.

• What other risks are there besides cancer?

> (Cucinotta) NASA is working on identifying such risks; they are part
> of the "critical path" used for risk management

• How does one compensate for current lack of knowledge?

> (Groer) It is better to use existing studies and their uncertainties
> as the basis of subjective probability distributions; this is the
> reverse of the NCRP approach, where probabilities are assigned to the
> risk and not to the inputs.

• Are there any tests for individual risk using measured fluctuations in
individual responses?

> Individual risks can be assessed by analogy with other fields, e.g.,
> car insurance, where different groups are assigned different risk
> levels, even if there are large fluctuations in the individual risk

• Can one do "stress profiles" as a function of time as a risk
predictor?

> (Fornace) It is too early to tell at this point, but such longitudinal
> studies may become feasible in the future -- aging generally shows up
> late in life!
>
> (comment from M. Story) It is important to note that radiosensitivity
> changes with age.

[^1]: NASA Johnson Space Center, Houston, TX

[^2]: National Cancer Institute, Bethesda, MD

[^3]: Oak Ridge National Laboratory, Oak Ridge, TN

[^4]: Medical Research Council, Harwell, United Kingdom

[^5]: University of Tennessee, Knoxville, TN

[^6]: NASA Headquarters, Washington, DC

[^7]: For an exhaustive discussion of risk in the context of space
    flight, cf. National Council on Radiation Protection and
    Measurements, 1997. Acceptability of Risk from Radiation --
    Application to Human Space Flight. Symposium Proceedings No. 3.

[^8]: National Council on Radiation Protection and Measurements, 1989.
    Guidance on Radiation Received in Space Activities, NCRP Report No.
    98

[^9]: Fry, RJM. Radiation Protection: Exposure in Low-Earth Orbit. These
    Proceedings.

[^10]: Amundson, SA, KT Do, and AJ Fornace, Jr. Induction of Stress
    Genes by Low Doses of Gamma Rays. *Radiat. Res*. *152*: 225-231,
    1999

[^11]: Amundson, SA, KT Do, S Shahab M Bittner, P Meltzer, J Trent, and
    AJFornace, Jr. Identification of potential mRNA markers in
    peripheral blood lymphocytes for human exposure to ionizing
    radiation.  *Radiat. Res*. *154*: 342-346, 2000

[^12]: Goodhead, DT. Challenges in Radiation Risk Assessment. These
    Proceedings.

[^13]: Band, PR, JJ Spinelli, VTY Ng, J Moody, and RP Gallagher.
    Mortality and Cancer Incidence on a Cohort of Commercial Airline
    Pilots. *Aviat. Space Environ. Med.* **61:**299-302 (1990)

[^14]: Cucinotta, FA.. Radiation Risks and Uncertainties for Astronauts.
    These Proceedings