(perhaps by email) a file of input parameters for batch processing and have the output
from the program then emailed back to the user.

It probably is not made adequately clear, however, in the descriptions that appear on the
web for a lay user, that the probability of causation is something that is calculated for an
exposed person already diagnosed with cancer, and is definitely not the same thing as the
probability that an exposed person will either get cancer due to his/her exposure in the
future.

REFERENCES

Robins J, Greenland S. The probability of causation under a stochastic model for
individual risk. Biometrics 45: 1125-1138, 1989

Robins J, Greenland S. Estimability and estimation of expected years of life lost due to a
hazardous exposure. Stat Med 10: 79-93, 1991

Greenland, S. Relation of probability of causation to relative risk and doubling dose: a
methodologic error that has become a social problem. Am J Public Health. 1999 89:1166-
9

Goldgar DE, Easton DF, Cannon-Albright LA, and Skolnick MH. Systematic population-
based assessment of cancer risk in first-degree relatives of cancer probands. J Natl Cancer
Inst, 86:1600-8., 1994

Thomas DC. Resolved: the probability of causation can be used in an equitable manner to
resolve radiation tort claims and design compensation schemes. Pro. Radiat Res.
154:717-8, 2000.

Neriishi K, Stram DO, Vaeth M, Mizuno S, and Akiba S. The observed relationship
between the occurrence of acute radiation effects and leukemia mortality among A-bomb
survivors. Radiat Res, 125:206-13., 1991

Sposto R, Stram DO, and Awa AA. An estimate of the magnitude of random errors in the
DS86 dosimetry from data on chromosome aberrations and severe epilation. Radiat Res,
128:157-69., 1991

Stram DO and Sposto R. Recent uses of biological data for the evaluation of A-bomb
radiation dosimetry. J Radiat Res (Tokyo), 32 Suppl:122-35., 1991

Stram DO, Sposto R, Preston D, Abrahamson S, Honda T, and Awa AA. Stable
chromosome aberrations among A-bomb survivors: an update. Radiat Res, 136:29-36.,
1993


Except for skin cancer, no accounting for minority group membership is done in the
NIOSH-IREP implementation. The main issue is probably not whether different minority
groups vary in their radiosensitivity to radiation (which is certainly possible, but for
which little data exists), but again whether baseline risks vary by ethnic group. Many
other cancers, besides skin cancer, vary by ethnic group within the US. This is a similar
issue as the transport of the risks seen in the Japanese population to the US population as
a whole.

I still believe (as did the NAS committee) that a systematic and thorough comparison of
the older tables with the IREP program needed. Because so many new diagnoses are
considered than covered by the original tables the biggest difference is that many more
cancer cases may now be considered for compensation. However it is important to
understand whether there are instances where the older Radio-Epidemiology tables would
compensate when IREP-based information doesn’t. If so then the reasons for the changes
(improved relative risk estimates, etc.) need to be especially carefully described.

The NAS committee had suggested an approach towards pooling of relative risk
estimates for rare tumors in an effort to reduce the variability introduced into the PC
calculation due poor data for estimating relative risks. While in certain instances pooling
has been done, there unfortunately is still no systematic approach taken for pooling
relative risk estimates across the various subsets of diagnoses and thereby reduce
uncertainty. Statistical tools for pooled analyses exist and are partly outlined in the
Commnittee’s report, and should be considered in future updates. In particular the
problem identified by the committee that individuals with rare tumors (where the excess
RR/Sv is poorly known), are more likely to be compensated using the 99% rule than
subjects with common tumors, is not addressed, but could be, if a random effects analysis
was undertaken (see citations in the NAS report).

Other weaknesses pointed out by the NAS review included a failure to adequately
document and rationalize the choices made about the uncertainties of the RBE factors for
exposures to electrons, neutrons, or alpha particles and also for the DDREF. This is
partially rectified by the technical report provided, however, it is clear that the choices
made reflect the judgment of a relatively small group of investigators (the report authors)
rather than a true consensus of experts. This is probably unavoidable given the lack of
good human data regarding these issues, however, the choices made here are very
important, and are likely to be subject to considerable scrutiny and criticism by other
experts with a different view: particularly of the DDREF.

The web-based NIOSH implementation of the IREP program appears to be quite
satisfactory as a way of implementing the PC calculation for occasional NIOSH usage; I
found the web system to be quite a bit easier to use than the stand-alone version that the
committee reviewed. One problem with the web-based system is that if there is a reason
to run the program repeatedly for a large number of scenarios (perhaps to set up a
comparison of the 1985 tables with the IREP output, for example) then this would be
very tedious over the web. One way to solve this would be to allow a user to submit


81/81/1937 98:15 §267219313 DANIEL STRAM PAGE 62

Depar thent 0!
Peeventive
Medicine

Division’ of


REVIEW OF NIOSH-INTERACTIVE RADIO-EPIDEMIOLOGICAL PROGRAM
TECHNICAL DOCUMENTATION

I served on the recent National Academy of Sciences Committee that reviewed a draft
report of the NCI-CDC Working Group to revise the 1985 Radioepidemiological Tables.
We also reviewed an earlier version of the IREP program which at the time was
implemented as stand alone program rather than being made available on the Web.

One problem that I, and others on our committee, identified at the time of our review was
that the draft report failed to acknowledge that there has been significant and continuing
debate about the validity of the concept of the probability of causation. In fact partly on
this basis an earlier NAS review of the original 1985 Tables, suggested the use of a
different name for the concept, i.e. “assigned share” or AS. I note that the NIOSH
implementation reverts to the use of the term “probability of causation” rather than
assigned share. This may be justified by political or other factors but it strikes me that
some description of the assumptions that are being made upon which the utility of the PC
in compensation decisions is based should be made a part of the documentation of the
IREP program. A critical assumption is that baseline risks of cancer are similar from
person to person.

Key to this debate is the fact that the usual definition of PC = (RR-1)/RR, where RR>1
(RR is the relative risk of disease in exposed individuals) only behaves like a probability
if the populations from which the relative risk is calculated and for which the PC is being
applied are homogeneous with respect to background risks of cancer. In particular, if this
assumption is violated, PCs do not in general “average out” the way ordinary
probabilities do. That is if there is a population of exposed individuals each one of who
are unique in terms of their baseline disease rates then the average of the individual PCs
of persons with disease, which will in general be higher than (RR-1)/RR as estimated
from an epidemiological study.

In fact, a number of statistical articles (Robins and Greenland, 1989, 1991, Greenland
1999) have gone into a great deal of detail concerning this failure of the PC to average
over groups of heterogeneous individuals, and take this as a rationale for abandoning its
use in compensation and in the settling of litigation. Further these articles make the
generic statement that no epidemiological study can address the variation in individual
disease risk and thus even the most extreme models for heterogeneity in baseline risk
cannot be invalidated by epidemiological data.

I myself reject as unwarranted the conclusion of Robbins and Greenland that the PC
should be removed entirely from the compensation debate. In particular I feel that it is
fully appropriate to ignore any truly unmeasureable individual variation in risk. On the
other hand we know that baseline risks of cancer are not completely homogeneous from
subject to subject in large populations; in particular most or all cancers tend to cluster
within families (Goldgar et al1994) implying that either genetic similarities or shared
environmental characteristics are responsible for individual variations in background
rates. This leads to the conclusion that the application of the PC to the individual case is


wrong to some degree because evidence for heterogeneity in personal baseline risk is
being ignored.

In order to deal with this problem I suggest that the IREP program as implemented by
NIOSH utilize the “User defined Uncertainty Distribution” (advanced features). The
parameters for this distribution are evidently set so that no additional “User defined
Uncertainty” is presently included in the calculations. I would rename this from the “User
defined Uncertainty Distribution” to something like “Uncertainty in individual baseline
risk of disease” and that this parameter be set in a disease-specific way. In particular for
diseases (e.g. thyroid cancer, testicular cancer) for which familial clustering in risk
appears to be larger than other cancers some additional variation in the PC should be
allowed by manipulation of this feature, i.e. by setting the GSD for the uncertainty
distribution to a value > 1. Even for the remainder of cancers where more modest
familial clustering has been detected to date this source should be included to some
degree (GSD>1 but smaller than for thyroid or testicular), Note that this suggestion is
my own, and is not incorporated into the NAS review of the IREP report. In fact at the
time that we reviewed the report all members of the committee were quite uncertain as to
the utility of the “User defined uncertainty distribution” and suggested that it be kept at
its null value (GSD=1).

The precise amount of uncertainty to attribute to this source is something that would need
further study, In particular further simulation studies similar in spirit to those described
by Thomas (2000), would need to be performed. As in Thomas’s simulations the general
approach would be to estimate a latent variable distribution for individual baseline risk
based on observed familial clustering and then to empirically estimate the variation in
individual probability of causation around the standard PC applied to the whole
population. I do anticipate that the amount of additional uncertainty justified by familial
clustering is likely to be relatively modest, but it would be worthwhile to try to pin this
down more specifically.

Note that the issue of varying baseline risk is distinct from the question of whether some
individuals may be more radiosensitive than others. At present there is only a small
amount of information available regarding differences in individual radiosensitivity
(much less than there is known about familial clustering of background risk). One
exception is the case of the ataxia telangiectasia (AT) gene where homozygotes for the
variant have extraordinarily enhanced susceptibility to UV and ionizing radiation risk.
However it is not even known presently whether AT heterozygotes (1-2% of the
population) have any increased susceptibility to radiation-induced cancer. My own work
with the A-bomb survivors’ data (Neriishi, et al 1991, Sposto et al 1991, Stram et al
1991, Stram et al, 1993) seemed to indicate little evidence of differential radiosensitivity
between individual in multivariate analyses of early and late radiation effects in that
cohort. At the present I think that there is little reason to try to account for especially
susceptible populations when dealing with the PC (except for those defined by age at
exposure and gender which are important covariates in many cases and have already been
included in IREP). Therefore I agree with the approach of the NIOSH-IREP
implementation, in basically ignoring this issue given present-day knowledge.