IV. Description of the Approach
A. Overview
1. Assigned Share

Assigned share (AS) for an individual who was exposed to radiation, and who has been
diagnosed with a cancer thought to be related to such exposure, is given by

AS = ERR/(1 + ERR)

where ERR is the excess relative risk associated with the exposure(s) of interest. ERR is a
function of radiation dose (possibly accumulated over a number of exposures), age(s) at
exposure, type of cancer, age at diagnosis, gender, and other factors possibly related to baseline
and/or radiation-related risk.

As previously mentioned (section IL.B), the working group is sympathetic to the view expressed
by the 1984 oversight committee report (NAS, 1984), that the ratio, called “probability of
causation,” or “assigned share” (which we prefer) applies to populations and not individuals and
cannot, for lack of detailed information and the ability to understand its full implications, be
interpreted as the probability that a given cancer was caused by a given radiation exposure. The
working group views assigned share as an actuarial concept, useful for summarizing the existing
scientific evidence bearing on the likelihood that prior radiation exposure might be causally
related to cancer occurrence under various circumstances, and which may in fact be the best
available information pertaining to a particular case. Similarly, a statistical life table is a useful
device on which to base social contracts such as a life insurance contract. A life table is based on
observed frequencies of deaths by age in a large population and, with detailed information, it is
easy to define, and easier still to imagine, subgroups for which life-table predictions based on the
larger population may perform poorly. Yet these departures do not detract from the practicability
of basing decisions about annuities, insurability, and insurance rates on life table predictions in
the absence of such detailed information.

2. Criticisms by Greenland and others

The present working group has considered criticisms of the AS approach by Greenland and
colleagues (Greenland, 1988, 1999; Robins, 1989a, 1989b; Beyea, 1999), who argue that AS is a
logically flawed concept, subject to substantial bias and therefore unsuitable as a guide to
adjudication of compensation claims in cases of possibly radiation-related cancer. Their
argument is based largely on the possibility that radiation exposure might accelerate the time of
appearance of a cancer that, in the absence of exposure, would have occurred later. The working

20


other cancers.

For ail types of low-LET radiation (gamma, x-rays, and electrons), the RBE was assumed to be
1. That is, all low-LET radiation are assumed to have the same effectiveness in inducing cancer
as 50-250 kVp x-rays. This assumption does not take into consideration that low doses of 50-250
kVp x-rays are actually 2-3 times more effective than high-energy gamma rays (Sinclair, 1985).
No adjustments related to the uncertainty in the RBE were included for low-LET radiation.

H. Transfer of ERR from the Japanese to the U.S. population

A major concern in using data from Japanese A-bomb survivors to estimate risks for specific
cancers in a U.S. population is that baseline risks differ between the two populations and the
dependence of radiation risks on baseline risks is not known with certainty. For example, baseline
cancer rates for breast, lung and colon cancer are smaller in Japan than in the United States, while
rates for stomach and liver cancer are much higher in Japan. Estimation of risk for a U.S.
population based on the dose response coefficients derived from A-bomb survivor data is
commonly referred to as the “transfer” or “transportation” problem. A more detailed discussion of
the transfer problem appears in NCRP Report 126 (NCRP, 1997).

Two simple solutions are the so-called “multiplicative” and “additive” transfer models, in which
estimates of excess relative risk (the ratio between excess and baseline risk) and absolute risk (the
difference between the estimated cancer rates with and without exposure), respectively, are
applied to the second population (in this case, the U.S. population). The multiplicative transfer
model is biologically plausible to the extent that ionizing radiation exposure can be assumed to act
as an “initiator” of a process whose likelihood of resulting in cancer depends upon the action of
“promoting” agents, if these “promoting” agents are responsible for the difference in baseline
rates between the two populations, or, alternatively, if radiation were to act as a promoter of the
carcinogenic effects of other agents that are differentially effective in the two populations. In this
view, the excess risk from radiation exposure would be greater in a normally high-risk population
than in a normally low-risk population. The additive transfer model is plausible to the extent that
radiation can be assumed to act mainly as an initiator and the difference between population
baseline rates can be assumed to be due to the differential effects in the two populations of other
“initiator” carcinogens that act similarly to radiation. In this view, the additional cancer risk
burden of radiation exposure would be independent of the population baseline rate.

Several approaches have been used for transferring risk estimates based on the Japanese A-bomb
survivor data to other populations. The multiplicative transfer model was used by UNSCEAR
(1988) for the world population and in the BEIR V report (NAS, 1990) for the U.S. population.

41


O-~- DDREF =5

chronic

~@— DDREF, =
“¥> > DDREF

chronic

V— DDREF

chronic

~-f--- DDREF

chronic

~——i-— DDREF

chronic

acute

DDREF

potiririiii

tt cl Se ee

0 O.5*D D

Radiation dose

Figure IV.F.3. Variation of DDREF,,,,. a8 a function of radiation dose for selected values of
DDREF gronic for a fixed value of D,. the lowest dose at which linearity of dose response is
assumed to apply.

37


All Other Cancers —__

0.8 Breast Cancer '

0.6

0.4

Cumulative Probability

0.2 -

ee ee ee ee ne a ee en Ee ee
0.2 0 02 od 2.6 0.8 : 1.2

Linear Mixture Parameter (y)

Figure IV.H.2 Cumulative distribution functions for the coefficient y used for computing a

weighted average of the additive and multiplicative models for transfer between populations:
transfer model = y x multiplicative model + (1-y) x additive model.

Note that the transfer model for breast cancer places 50% probability on the model in Figure

IV.F.1 and 50% on y=0, whereas for stomach cancer 33% is placed on y=1 and the remainder on

the model in Figure IV.H.1. The multiplicative transfer model is used for thyroid cancer.

46


D. Uncertainty

Sources of biased and unbiased uncertainties, and propagation of errors, were extensively
discussed in Chapter VII of the 1985 report. Biased uncertainties included overestimation of
(absolute) risk 5-14 years following exposure, and underestimation associated with use by the
BEIR Il committee (NAS, 1980) of the T65D dosimetry system (Kerr,1979) for estimating dose-
specific risk among A-bomb survivors. (By 1983-84 it was clear that T65D was going to be
replaced, but the new system, DS86 (Roesch, 1987), was not yet in place.) Unbiased uncertainty
pertained to the use of baseline rates based on the entire region covered by the SEER registry,
modeling of risk as a function of age at exposure, assumptions about dependence of risk on time
following exposure, and assumptions about the curvature of the linear-quadratic dose-response
curve estimated in BEIR III. Other sources of uncertainty were also discussed, but only those
just noted were taken into account in computing combined uncertainty, represented by a
geometric standard deviation value and a bias correction factor, for different cancer sites and
years following exposure. The emphasis of the report was on point estimates; recommendations
were given for modifying tabulated AS values to account for bias and uncertainty.

14


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including especially statistical variability in the risk coefficients and uncertainty resulting from
transferring risk coefficients based on Japanese A-bomb survivors to a contemporary U.S.
population. Second, uncertainty distributions were selected to reflect available data and the best
judgment of the investigators, and were not limited to log-normal distributions as was the case in
1985. Third, Monte Cario simulations were used to combine uncertainties, a feature that made
flexible selection of uncertainty distributions possibie. Fourth, uncertainty was not treated as an
“add-on”, developed after the central estimates had been determined, but rather was a fundamental
part of the process. That is, emphasis was not on determining single point estimates, but on
developing overail uncertainty distributions, calculated by combining the uncertainty distributions
from each of the contributing sources, Given an uncertainty distribution, it is of course possible to
determine medians, means, and various percentiles or credibility limits. Finally, the on-line
computer software (IREP) incorporates “customized” Monte Carlo simulations to obtain the
distribution of a desired AS, taking into account the exposure scenario, certain characteristics of
the individual, and the specific type of cancer.

The above modifications drew heavily on developments in uncertainty analysis that have
occurred since 1985. The BEIR V report used Monte Carlo simulations to evaluate statistical
uncertainty in lifetime risks, but relied on lognormal propagation of errors for evaluating several
ty, both NCRP and EPA have used Monte Carlo
g flexible cacice of distributions to describe uncertainties from individ

other uncertainty sources. More re

wees. However, NCRP anc

A were primarily concerned with uncertainties in lifetime risks
to populations rather than uncertainties in risks for individuals with specific characteristics.
Furthermore, NCRP provided a distribution only for the lifetime risk of all fatal cancers, although
the report contains discussion of specific cancer types. To our knowledge, the work reported here
is the first to evaluate uncertainty distributions for specific AS values associated with any of a

wide range of specific cancer types, individual characteristics, and exposure scenarios.

56


the 1985 report. Note that assigned share (AS) is a simple, monotonic function of the ERR, AS =
ERR /(1+ERR).

5. Radiation dose response and adjustment for low dose-rate exposure Because estimates
obtained directly from epidemiological data on populations exposed only at low doses are very
imprecise, it is necessary to extrapolate from risks that have been estimated from persons exposed
at higher doses (and dose rates) than those of direct interest. The estimates used in this report are
based on Japanese atomic bomb survivor data, and estimates based on these data tend to be
driven by the cancer experience of persons exposed to doses that exceed 1 Gy. This is much
larger than doses for which AS values are usually desired, which are almost always less than 0.1
Gy and often much smaller.

Although most epidemiological data for solid cancers are compatible with a linear dose-response
function in which risk is proportional to dose, curvilinear forms cannot be excluded. On the other
hand, dose-response analyses of leukemia risk have consistently shown evidence of upward
curvature consistent with a quadratic function of dose having a substantial linear component
(“linear-quadratic” or “L-Q” for short).

a. Method used in the 1985 NIH report The 1980 BEIR III committee chose as their “preferred”
aal to D+ D?/1.16, where D is
ttee adopted that form for their

dose response model an L-Q model in 1 isk was prop

organ-specific dose in Gy, and the 1985 N:

port.
Thus, with two exceptions (breast and thyre ‘hich linearity was assumed), the
estimated excess risk per unit dose was a little more than half as high at 0.1 Gy as at 1 Gy.
Another consequence was that the risk per unit dose of the sum of several exposures, each less
than 0.1 Gy and separated in time, or a chronic exposure (treated much the same as the sum of
many very small exposures) was estimated to be about half as high as that for a single, acute

exposure of about 1.2 Gy.

b. Method used in the present report The approach used for the present report was to treat
leukemia risk as proportional to D + D’, since estimates of the D’ coefficient are generally inexact
but in the neighborhood of unity and significantly greater than zero. For all other cancers, the risk
was assumed to be linear (proportional to D) for curve-fitting purposes but with a dose-and-dose-
rate-effectiveness factor (DDREF) applied to reduce estimated risk at low doses and dose rates.
The DDREF approach was chosen because it is consistent with recommendations by the
International Commission on Radiation Protection (ICRP 60) and because instances of a linear
dose response have been observed above a certain level in combination with a DDREF of 2 or
more at lower levels, in experimental studies of radiation carcinogenesis using fractionated
exposures (R. Ullrich, personal communication).

54


of Causation (Final Report). National Academy Press, Washington, D.C., 1984.

NAS/NRC 1988. National Academy of Sciences/National Research Council, Committee on
Health Effects of Exposure to Radon. Health Effects of Exposure to Radon and Other Internally-
Deposited Aipha Emitiers: BETR IV. National Academy Press, Washington, D.C., 1988.
NAS/NRC 1990. National Academy of Sciences/National Research Council, Committee on the
Biological Effects of Ionizing Radiation: The effects on populations of exposure to low levels of
ionizing radiation: 1990, BEIR V. National Academy Press, Washington, D.C.

NAS/NRC 1998. Report of the Committee on Health Effects of Exposure to Low Levels of
lonizing Radiations (BEIR VID) Phase I. Health Effect of Exposure to Low Levels of Ionizing
Radiation. Time for Reassessment? National Academy Press, Washington, D.C., 1998, 76 pp.

NAS/NRC 1999. National Academy of Sciences/National Research Council, Committee on
Health Effects of Exposure to Radon. Health Effects of Exposure to Radon: BEIR VI. National
Academy Press, Washington, D.C., 1999.

National Center for Health Statistics, “Cigarette smoking and Health Care Characteristics, U.S.,
July 1964-June 1965.” Series 10, No. 34, U.S. Department of Health Education and Welfare,
Washington, D.C., 1967.

NC 2! Council on Radiation Protection and Measurements). Ini

ion Protection and Measurements, Bethesda, MD, 19890.

ponse relationships for low-LET radia

National € cil on Radiat:

NCRP (National Council on Radiation Protection and Measurements), 1990. The relative
biological effectiveness of radiations of different quality. NCRP Report No. 104. Bethesda,
Maryland

NCRP (National Council on Radiation Protection and Measurements). Risk estimates for
radiation protection. National Council on Radiation Protection and Measurement, Washington,
D.C., 1993, NCRP Report No. 115, 148 pp.

NCRP (National Council on Radiation Protection and Measurements). A guide for uncertainty
analysis in dose and risk assessments related to environmental contamination. NCRP Commentary
No. 14. National Council on Radiation Protection and Measurements, Bethesda, MD, 1996.

NCRP (National Council on Radiation Protection and Measurements). Uncertainties in fatal
cancer risk estimates used in radiation protection. NCRP Report No. 126. National Council on
Radiation Protection and Measurements, Bethesda, MD, 1997.

NIH (National Institutes of Health). Rall JE, Beebe GW, Hoel DG, Jablon S, Land CE, Nygaard

60


APPENDIX A: Text of Congressional Mandate and Excerpt from Presidential Statement

Public Law 97-414 - January 4. 1983

"7(b)(1) Within one year after the date of enactment of this Act, the Secretary of Health and
Human Services shall devise and publish radio-epidemiologicai tables that estimate the likelihood
that persons who have or have had any of the radiation-related cancers and who have received
specific doses prior to the onset of such disease developed cancer as a result of these doses. These
tables shail show a probability of causation of developing each radiation related cancer associated
with receipt of doses ranging from 1 millirad to 1,000 rads in terms of sex, age at time of
exposure, time from exposure to the onset of the cancer in question, and such other categories as
the Secretary, after consulting with appropriate scientific experts, determines to be relevant. Each
probability of causation shall be calculated and displayed as a single percentage figure.

(2) At the time the Secretary of Health and Human Services publishes the tables pursuant to
paragraph (1), such Secretary shall also publish--

(A) for the tables of each radiation related cancer, an evaluation which will assess the
credibility, validity, and degree of certainty associated with such tables; and

be published i
necessary to deter the probability of causation of any im
radiation related cancer and has received any given dose.

(3) The tables specified in paragraph (1) and the formulas specified in paragraph (2) shall be
devised from the best available data that are most applicable to the United States, and shall be
devised in accordance with the best available scientific procedures and expertise. The Secretary of
Health and Human Services shall update these tables and formulas every four years, or whenever
he deems it necessary to insure that they continue to represent the best available scientific data and
expertise.”

Excerpt from President Reagan’s statement on the occasion of his signing the Orphan Drug Act.
“_. . there is as yet no consensus among radiation experts in relating human cancers and
exposure to low levels of radiation. Yet, Section 7 mandates that probability of causation
tables be calculated for even very small dose levels. Accordingly, I am directing the
Secretary of Health and Human Services to complete the tables to the extent that may be
possible and scientifically responsible, in light of the analysis also mandated by Section 7,
which requires him to ‘assess the credibility, validity, and degree of uncertainty associated
with such tables."

64


persons exposed for medical reasons, or from studies of workers and others exposed at low doses
and dose rates. Estimates based on data from low dose studies would be far too imprecise to meet
the needs of the AS tables, where estimates for specific cancer, ages at exposure and gender are
required. It is noted, however, that considerable uncertainty has been allowed for extrapolation
from high doses and dose rates.

2. Cancer sites evaluated include most of those in the 1985 report. Our choice of cancer sites
includes all of those in the previous report, except for bone cancer associated with injection of
>4Ra and lung cancer associated with inhalation of radon decay products. Some new cancer
categories have been added.

3. Site-specific assigned share estimates based on data for that site alone. The AS values for
each cancer site were based on analyses of A-bomb survivor data for that site only, as in the 1985
report. Estimates of both the overall risk coefficients and parameters expressing the dependence
on age at exposure and gender were based only on data for the site being evaluated. Consideration
was given to conducting joint analyses of several cancer types (see Pierce and Preston, 1993),
testing whether various parameters were comparable among cancer types, and then using common.
estimates of selected parameters in developing site-specific AS values. This approach has the
potential advantage of greater statistical precision in the estimated AS values, but the

disadvantage of difficult-io- ify uncertainty in whether the chosen models are appropriate.

Although we think the approa worthy of consideration for future risk assessments and AS

estimation, we judged it too great a departure from the previous approach to use at this time.

4. Time since exposure was handled in the same manner. For all cancer types except leukemia
and bone cancer, the 1985 models were based on the assumption that, after a minimal latent
period, the excess relative risk per Sv (ERR/Sv) remained constant over time since exposure and
therefore did not depend additionally upon attained age. We have also made these assumptions
unless there was evidence to the contrary based on the data analyzed. In fact, modification by
time since exposure is included only in the models for leukemia, and modification by attained age
is included only in the models for colon cancer and kidney cancer.

C. Important changes

1. Estimates were obtained for all cancer sites for which the calculations could be
performed, not just those established as “radiation-related.” A working assumption was that
radiation exposure might be a causal factor for any site or type of cancer, at some exposure level
and under some conditions. This assumption obviates the question of whether or not a particular
kind of cancer could be caused by radiation; rather, the most pertinent problem is what values of

52


of all ages at exposure, and 0.5% for a working population 20-65 years of age at exposure.

The present report is subject to the same problems of projection of risk beyond the period of
observation. However, the vast majority of claims for which the report might be relevant are
expected to pertain to adult exposures, for which such projection contributes little compared to
other sources of uncertainty. Thus, no special provision was made for uncertainty of
extrapolation beyond the period of observation. On the other hand, trends in time since exposure
and age at cancer diagnosis, which address some of the same issues, were specifically included in
the set of variables used to model radiation-related risk for different kinds of cancer, and were
retained in the model as appropriate on statistical grounds.

B. Source of data

Although much new information on radiation-related risk in human populations has been
published in the 15 years since the 1985 NIH report was prepared, the present report relies
primarily on analyses by the Working Group of A-bomb survivor incidence data. The approach
involves direct calculation of risk estimates and their statistical uncertainties from original data,
in this case from the RERF Tumor Registry for 1958-87 (Thompson et al, 1994), the RERF
Leukemia Registry for 1950-1987 (Preston et al, 1994), and site-specific studies of salivary gland
cancer (Land et al , 1996) and female breast cancer (Land, personal communication) in the LSS
cohort. Thyroid cancer receives a more widely-based approach, involving a new analysis of the
original thycoid cancer data from the international, pooled study of Ron et al (1995).

C. Choice of cancer types and approach to cancer types (each type considered individually)

Adjudication of compensation claims for possibly radiation-related cancer is usually specific to
organ site and often to histological type. Sites for solid tumor incidence data from the RERF
Tumor Registry are specified in Table IV.C.1, and sites for hematopoietic cancers from the
Leukemia Registry are shown in Table IV.C.2. Calculations were completed for individual organ
sites and for broader groups (all leukemia except the chronic lymphocytic type, and for cancers of
the urinary system); the broader groups are intended to provide some basis for adjudicating
claims for organ sites not specifically covered.

Chronic lymphocytic leukemia (CLL) was specifically excluded from the risk calculations
because of a lack of data on which to base an estimate. CLL is almost absent among Japanese
generally and among the A-bomb survivors in particular (Parkin, 1997, Preston, 1994), but
occurs frequently in Western populations, especially at older ages (Parkin, 1997). It has not,
however, been associated with radiation exposure in studies of irradiated Western populations
(NAS, 1990). Malignant melanoma also was excluded, because no convergent estimate could be

24


The additive transfer model was used in the BEIR II report (NAS, 1980) and the 1985 NIH report
(NIH, 1985). The two transfer models can lead to very different estimates of radiation-related risk
for certain cancers for which baseline risks differ greatly between Japan and the U.S. (Land,
1990). Each model receives some support from site-specific comparisons, but there are few sites
for which meaningful analytic comparisons can be made. If population differences in cancer rates
may be due to both initiating and promoting agents, it is likely that both additive and
multiplicative model interactions with radiation may take place, and that some kind of mixture
model may be appropriate. For example, the ICRP (1991) used the arithmetic mean of the ERR
values obtained by the two transfer models for all solid cancer types combined (Land and Sinclair,
1991), and the Environmental Protection Agency (Puskin and Nelson, 1995) used the geometric
mean (except for liver cancer associated with exposure to the radioactive contrast medium
thorotrast, for which a multiplicative transfer model was preferred, and bone cancer from
exposure to injected “Ra, for which an additive transfer model was chosen). More recent reports
have used uncertain (i.e., randomized) linear or geometric combinations, weighted in various
ways, of the additive and multiplicative transfer models for the estimation of total risk of cancer
mortality (EPA, 1999).

Mortality rates for all types of cancer combined vary relatively little by nation, compared to site-
ation. The initial ERR,., value for mortality from all cancers combined used in NCRP

specific vari
Report 126 (NCRP, 1997) was the rounded average of multiplicative and additive transfer modei
estimates from the LSS mortality data for five different national populations @CRP, 1991, Land
and Sinclair, 1991). Thus, the problem for that report was not how to estimate ERR,,, for a US
population, but to determine the uncertainty associated with estimating ERR,s, in a particular way.
Their solution was an uncertainty factor F(T), distributed as LN(1, 1.3).

For the present report, the problem is how to estimate site-specific and age-specific values of
ERR,,, for the US population in the presence of possibly large differences in baseline rates and
the absence of useful information about which model might be correct. Our approach is to use a
random linear combination between the additive and multiplicative models,

(ERR sJus = YX(ERR 19) mur + (1-9) * (ERR 15) ade »

where the random variable y varies between -0.1 and 1.1. Here, (ERR, s,) mi is the site-, sex-, and
age-specific excess relative risk at 1 Sv obtained from statistical analysis of the Japanese A-Bomb
survivor data and adjusted for random and systematic errors in dose to individual A-bomb
survivors (see IV.D above). (ERR, 5,)aaa is the same value, adjusted for the corresponding ratio

42


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I. Executive Summary

The legislative mandate for the 1985 Report of the NIH Ad Hoc Working Group to Develop
Radioepidemiological Tables provided for analyses of existing data linking cancer risk to
ionizing radiation exposure, to facilitate the adjudication of compensation claims for cancers
diagnosed following exposure to ionizing radiation. The 1985 working group did this by
estimating “probability of causation” (PC) values, defined as

PC= Risk due to radiation exposure
Baseline risk + risk due to radiation exposure

for hypothetical instances of cancer following specific histories of radiation exposure. The report
has been used mostly by the Department of Veterans Affairs (VA) as a guide to adjudicating
compensation claims for cancers diagnosed in persons who were exposed during military service.
The amount of new information about radiation-related cancer risk has increased markedly
during the 15 years since publication of the report, and there have been revisions in the system of
dose reconstruction used for the major source of epidemiological data for estimating risk, the
cohort of atomic bomb survivors studied by the Radiation Effects Research Foundation (RERF)
in Hiroshima and Nagasaki, Japan. The VA requested the Secretary of the Department of Health
and Human Services (DHHS) to update the Report, as provided for in the original legislative
mandate, and joined with the DHHS to support the present effort by a working group of the
National Cancer Institute (NCI) and the Centers for Disease Control and Prevention (CDC).

Noting that the National Academy of Science/National Research Council (NAS/NRC)
Committee on Biological Effects of Ionizing Radiation (BEIR VII, phase 2) is expected to
complete within 2 or 3 years a comprehensive survey of the scientific data linking radiation
exposure to health effects in human beings, the NCI and CDC have undertaken to provide an
interim update of the 1985 report based on statistical analyses by the working group of readily
available data on cancer risk following radiation exposure, notably the 1958-87 LSS Tumor
Registry data on survivors of the atomic bombings of Hiroshima and Nagasaki made available on
computer disk by RERF. It is expected that a further update to the present report will be made
following the BEIR VII review. The working group has replaced the tabular format of the 1985
report by an interactive computer program (IREP, for “interactive radio-epidemiological
program”) that eliminates nearly all of the computational labor of estimating PC values and their
uncertainties, and permits a more detailed and comprehensive expression of the various
components of the calculation and their uncertainties.

It has been argued, notably by the NAS/NRC oversight committee that provided critical advice to


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uncertainty in the DDREF.

35


group has concluded that the practical effect of such events is unlikely to be great enough to
affect the viability of the AS approach.

In support of this conclusion, the working group notes that heavily-irradiated populations that
have been studied extensively, like the higher-dose survivors of the atomic bombings of
Hiroshima and Nagasaki, have experienced increases in cancer risk rather than a temporal
redistribution of risk over their lifetimes. The phenomenon of radiation-related “acceleration of
risk,” observed in highly sensitive inbred animal strains with very high lifetime tumor risks in the
absence of exposure, appears to be an artifact in that a radiation-related increase in the number of
tumors per animal is observed as an acceleration in time to first observed tumor -- the first of
many is likely to appear before the first of relatively few (Guess and Hoel, 1977). In any case,
the influence on radiation-related risks in general populations of highly sensitive population
subsets is thought to be relatively minor (ICRP, 1999). At the cellular level, ionizing radiation is
generally believed to be more effective as a cell killer than as a cell mutator (Hall, 1994), and
cancer cells are believed to be more vulnerable than normal cells to radiation-induced cell killing
(this is the basis for radiation-based cancer therapy). It is of course theoretically possible that a
particular cell, having already gone through one or more stages in the multi-stage process of
carcinogenesis, might be moved farther along in the process by a radiation event that
accomplishes what some other event would otherwise have accomplished later. Given the very
large number of potential target cells in the human body or in a particular organ or tissue,
however, it is reasonable to conclude that the carcinogenic effect of radiation in an individual or
a population is dominated by interactions with cells not already destined to develop into cancer.

The acceleration hypothesis does not play a major role in current models of radiation-related risk
in general populations, and particularly not in models directed at radiation protection. The
scientific consensus on which reports like the current one are based is an evolving process, based
on imperfect knowledge. The working group sees no reason why that consensus should not be
used, at any given time, as a guide for adjudication of claims as well as for radiation protection.

3. Emphasis on uncertainty analysis

New emphasis is placed on uncertainty analysis (NCRP, 1996), specifically, estimating an
uncertainty distribution for the ERR (and associated AS), as opposed to a single point estimate.
ERR is expressed as the product of several factors, assumed to be independent. Each factor is
uncertain, and is specified by an uncertainty distribution. The specified uncertainty distributions
depend to some extent on subjective judgments by expert committees and by the authors of this
report. The overall uncertainty distribution of the desired ERR is obtained by Monte Carlo
simulation. These simulations involve sampling from the uncertainty distributions for each of

21


Uterus NOS 179 47 39 86 none
Uterine cervix 180 265 288 553 none
Uterine corpus 182 37 48
Ovary 183 66 67
Other female genital 181, 184 15 19
Male genital 185-187 74 86
Prostate gland 185 61 79
Other male genital 186,187 13 7 20 none
Urinary system? 188-189 172 =| 153 | 325 :
Bladder 188 115 95 210 g
Kidney 189.0 34 39 BB ga
Renal pelvis and ureter 189.1, 189.2 14 14 28 none
Nervous system 191, 192 69 56 125 none
Thyroid gland? 193 129196 | 225 €

‘Except as noted, information based on Thompson et al, 1994.

°¢ = gender, e = age at exposure, a = attained age, t = time following exposure

3Use group estimate for cancers in this group for which site-specific estimates are not provided.
‘Salivary gland data from Land et al, 1996.

“Use site-specific estimates.

"Fitting process did not converge; use group estimate.

Breast cancer data from C. Land, personal communication.

‘Includes non-exposed cases.

°Thyroid cancer data from Ron et al, 1996, reanalyzed for this report.

27


appropriate RBE factor (for relative biological effectiveness); the resulting weighted dose,
sometimes referred to as dose equivalent, is used when applying risk coefficients derived from
studies of populations exposed mainly to low-LET radiation. RBE may depend upon the type of
radiation and the level of dose, and is an uncertain quantity derived from observational data.
Treatment of this uncertainty is discussed in Section IV.G.

5. Transfer of risk estimates form A-bomb survivors to a US population. Baseline risks for

many cancers differ substantially for Japanese and US populations, and there is considerable
uncertainty about how risk estimates derived from observations on an exposed Japanese
population should be applied to an exposed US population. The treatment of this source of
uncertainty is described in Section IV.H.

6. Modification by smoking history. Tobacco smoking and, to a lesser extent, exposure of
nonsmokers to side stream tobacco smoke are powerful risk factors for lung cancer, especially,
and a number of other cancers as well. Studies of uranium miners suggest that risk of radiation-
induced lung is increased among smokers to a greater extent than among non-smokers, but that
this increase is somewhat less than the increase associated with smoking alone (NAS, 1999). The
interaction between radiation exposure and smoking history is discussed in Section IV.I.

The following additional sources of uncertainty have been considered by others, but are not
evaluated here.

1. Diagnostic misclassification in A-bomb survivor data. Both the NCRP (1997) and EPA
(1999) uncertainty evaluations were based on mortality data, for which diagnostic

misclassification is a more serious problem than for the incidence data used for this report. Also,
the present report focuses on specific cancers, and diagnostic accuracy may depend on the cancer
type. Although there is undoubtedly uncertainty resulting from diagnostic misclassification, it
would be very difficult to quantify, and it did not seem likely that this uncertainty would be large
relative to many of the other sources considered.

2. Extrapolation of risk beyond the time period covered by data. The focus of NCRP Report 126
(1997) was lifetime cancer mortality risk associated with radiation exposure, and the report
specifically treated uncertainty about extrapolation of risk beyond the period of observation for
tisk. The concern was that the A-bomb survivor mortality data for 1950-1985 represented
follow-up only until 40 years after exposure, whereas those data were being used to estimate
lifetime risk for persons exposed at various ages including children whose expected remaining
lifetime when exposed was 50, 60, 70, or more years. The NCRP report included a factor whose
uncertainty contributed 6.7% of the overall uncertainty to lifetime mortality risk for a population

23


0.30 +

0.25 4

0.20 4

Probability

0.10 +

0.05 +

DDREF

chronic

Figure IV.F.2 Illustrative probability distribution function for the dose and dose-rate effectiveness
factor applied to chronic exposures. For cancers of the thyroid gland and female breast, the
probability distribution is shifted to the left (see text),

36


calculating “credibility limits” (based on statistical and subjective measures of uncertainty) for
estimates of assigned share. In the intervening years, additional attention has been paid to
quantification of uncertainty in applications to radiation-related risk, and new approaches for
evaluating uncertainty have been developed (NAS, 1990, NCRP, 1996, 1997, EPA, 1999). It
seems clear that considerations of uncertainty are central to radiation protection and adjudication
of claims for compensation in cases of disease following radiation exposure. It is equally clear
that the concept is complex and not easily applied by non-specialists, and would benefit from a
more user-friendly approach as indicated by the following example:

The major U.S. government user of the NIH report is the Department of Veterans Affairs (VA)
which in 1985 asked the Committee on Interagency Radiation Research and Policy Coordination
(CIRRPC) of the Office of Science and Technology Policy, Executive Office of the President, to
provide guidelines on how the NIH report might be used credibly to assist in adjudicating a
veteran’s claim of radiation injury. The Science Panel of CIRRPC interpreted the VA’s charge
as one of quantifying the likelihood that a specified “probability of causation” (assigned share) in
the NIH report would not be exceeded, with an a priori chosen level of credibility (CIRRPC,
1988). Their solution was to tabulate, by type of cancer, gender, age at exposure, and other
relevant factors, the organ doses at which the upper AS credibility limit was 50% (“as likely as
not”) at credibility levels 90%, 95%, and 99%, respectively. The solutions were proposed as
possible screening doses for specific cancers, exposure ages and times following exposure. The
screening procedure was biased toward ensuring that a raarginal claim by an exposed veteran
would not be rejected at this stage of consideration, and it was assumed that a claim not
eliminated by this screening process would be adjudicated on its merits, taking into consideration
the many factors that pertain to an individual claimant, including the AS value calculated
according to the NIH report.

G. Availability of interactive computer programs as an alternative to tabular presentation

The tabular presentation of the 1985 report allowed users to look up tabulated coefficients
appropriate to particular claims, and to calculate assigned share using these coefficients
according to simple algorithms presented in the report. Increased computing power has made it
possible to calculate assigned share and its uncertainty directly, for individual claims, from the
particulars of exposure history, disease, and other relevant factors. This results in quicker, easier,
and less error-prone computation, with tabular and/or graphical output options.

Hi. Use of organ-specific dose equivalent, in sievert (Sv)

The present report expresses organ-specific absorbed radiation dose in units of gray (1 Gy = 1

18


LL)

gunsodxo 20UIs SUI} = ASI, ‘sisouserp ye oe = Gyy ‘emnsodxo ye ode = FVV

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280
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AS§9)
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(ysrp Aqurepisoun jo afsjuaosed ) aa
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Rogot, E., Murray, J.L. Smoking and causes of death among U.S. veterans: 16 years of
observation. Public Health Rep. 95:213-222 (1980).

Ron E, Modan B. Benign and malignant thyroid neoplasms after childhood irradiation for tinea
capitis. INCI 1980; 65:7-11

Ron E, Lubin JH, Shore RE, Mabuchi K, Modan B, Pottern LM, Schneider AB, Tucker MA,
Boice JD, Jr. Thyroid cancer after exposure to external radiation: A pooled analysis of seven
studies. Radiat Res 1995; 141:259-277,

Ron E, Preston DL, Kishikawa M, Kobuke T, Iseki M, Tokuoka S, Tokunaga M, Mabuchi K.
Skin tumor risk among atomic-bomb survivors in Japan. Cancer Causes and Control 1998; 9:393-
401.

SEER 1973-1981 SEER Cancer Statistics Review, 1973-1981, National Cancer Institute. NIH
Pub. No. 84-xxxx.. Bethesda, MD, 1984.

SEER 1973-1994. Ries LAG, Kosary CL, Hankey BF, Miller BA, Harras A, Edwards BK (eds).
SEER Cancer Statistics Review, 1973-1994, National Cancer Institute. NIH Pub. No. 97-2789.
Bethesda, MD, 1997.

Shore RE, Hildreth N, Woodard E, Dvoretsky P, Hempelmann L, Pasternack B. Breast cancer
among women given x-ray therapy for acute postpartum mastitis. J Natl Cancer Inst 1986;
77:689-696. Shore

Shore RE, Albert RE, Reed M, Harley N, Pasternack B. Skin cancer incidence among children
irradiated for ringworm of the scalp. Radiat Res 1984; 100: 192-204.

Shore RE. Overview of radiation-induced skin cancer in humans. Int J Radiat Biol 1990; 57: 809-
827.

Sinclair WK. 1985. Experimental RBE values of high-LET radiations at low doses and the
implications for quality factor assignment. Radiat. Prot. Dosim. 13:319-326

Smith PG, Doll R. Mortality among patients with ankylosing spondylitis after a single treatment
course with x-rays. Br Med J 1982; 284:449-460

Thompson DE, Mabuchi K, Ron E, Soda M, Tokunaga M, Ochikubo S, Sugimoto §S, Ikeda T,
Terasaki M, Izumi S, Preston DL. Cancer incidence in atomic bomb survivors. Part II: Solid

62


II. Background of 1985 report
A. Congressional mandate and its execution

On January 4, 1983 the President of the United States signed Public Law 97-414 (known as the
"Orphan Drug Act"), an act to amend the Federal Food, Drug and Cosmetic Act to facilitate the
development of drugs for rare diseases and conditions, and for other purposes. This legislation
includes a provision (Section 7 (b) of the bill) directing the Secretary of Health and Human
Services (DHHS) to "devise and publish radioepidemiological tables that estimate the likelihood
that persons who have or have had any of the radiation-related cancers and who have received
specific doses prior to the onset of such disease developed cancer as a result of these doses." The
mandate included a provision for periodic updating of the tables.

It may be noted that the section of P.L. 97-414 pertaining to the development of
radioepidemiological tables originally was introduced by Senator Orrin Hatch (Utah) as a part of
Senate bill S 1483: "Radiation Exposure Compensation Act" to provide for damages due to
radiation exposure from nuclear weapons tests in Nevada. Since neither this bill nor the
companion House bill (H.R. 6052) was reported out of the respective committees, the section
relating to radioepidemiological tables was attached as an amendment to the "Orphan Drug Act”
which was passed by both houses and signed into law on January 4, 1983. The complete text of
section 7 (b) of the bill and an excerpt from President Reagan's statement, on the occasion of his
signing the Orphan Drug Act, are given in Appendix A of the present report.

Lead responsibility for the implementation of the enacted charge was assigned to the National
Institutes of Health (NIH) by the Assistant Secretary of Health, DHHS, who also requested that a
National Research Council (NRC) committee be formed to review the recommendations of the
NIH. Subsequently (August 4, 1983), the Secretary of Health and Human Services approved the
Charter for an "Ad Hoc Working Group to Develop Radioepidemiological Tables" to carry out
this mandate. The text of the Charter is included as Appendix B.

An Ad Hoc Working Group, chaired by Dr. J. E. Rall, Deputy Director for Intramural Research,
NIH, was established to carry out the work. The NIH contracted with the National Academy of
Sciences (NAS) for the formation of an Oversight Committee in the NRC’s Commission on Life
Sciences, with the cooperation of the Institute of Medicine. The oversight committee, chaired by
Prof. Frederick Mosteller of Harvard University, reviewed the data sources, assumptions, and
methods of the NIH working group, and discussed wider issues regarding the tables in the
context of their intended and possible uses. The report of the oversight committee was published
in 1984 and the report of the working group was published on January 4, 1985.

10


4) Uncertainty due to systematic bias in neutron dose estimates in Hiroshima, denoted D, in
NCRP 126 with error factor F(D,) distributed as triangular(1.0, 1.1, 1.3).

The overall error factors for random and systematic errors in dosimetry are

FLD) = (+FRe)y/(F NRF DyFO,))

for solid tumors and
FQ(D) = (1+ F(R) MF(Ng)*F(D))XF(D,))

for leukemia. The uncertainty distributions for F,(D) and F,(D), expressed in percent, correspond
reasonably well to normal distributions: N(83.2, 8.36) and N(80.7, 8.05), respectively.

F. Dependence of risk on dose and dose rate for low-LET radiation

Radiations of different quality differ with respect to the shape of the dose-response function for
cancer risk. Risk per unit dose of radiations of high linear energy transfer (LET), such as neutrons,
alpha particles, or heavy ions, tend to be the same (or greater) at low compared to high doses,
whereas for low-LET radiations, such as gamma ray, electrons, x ray, or beta particles, risk per
unit dose is thought to be lower at low dose levels. Evidence for a lower risk per unit dose of low-
LET radiation at low (compared to high) dese levels comes mainly from experimental
radiobiology, much of it involving outcomes other than carcinogenesis (NCRP, 1980). Inferences
about the shape of the dose-response relationship based on epidemiological studies of cancer, on
the other hand, tend to be determined by data in the middle and high dose ranges, i.e., 0.1-1.0 Gy
and 1.0 Gy and higher. For solid cancers, generally, there is little persuasive epidemiological
evidence of nonlinearity of dose response, whereas for leukemia there is good evidence of positive
curvature. The quadratic dose-response model for leukemia used here corresponds to a risk at
0.01 Gy (1 cGy) that is only 0.5% as high as the risk at 1 Gy, or half as high per unit dose. Linear-
model risk coefficients may be reduced by a dose and dose-rate effectiveness factor (DDREF) for
estimating risks at low doses and low dose rates. The International Commission on Radiological
Protection (ICRP, 1991) recommended a DDREF of 2 for purposes of radiation protection, a
value roughly consistent with the default quadratic dose-response model used here for leukemia.
The ICRP recommendation is also accepted by the NCRP (1993). In their most recent discussion
of the application of DDREF, the United Nations Subcommittee on Effects of Atomic Radiation
(UNSCEAR, 1993) recommended that the chosen DDREF be applied to chronic exposures (dose
rates less than 6 mGy per hour averaged over the first few hours) and to acute (high dose rate)
exposures at total doses less than 0.2 Gy, a recommendation that was subsequently adopted by the
EPA (1999). However, such an abrupt transition seems unrealistic in view of observed linearity

33


function 1 + exp((Dose - D/S).

A graphical representation of the DDREF,..,..
is shown in Section IV (Figure IV.C.2). Note that, as the dose approaches zero, the DDREF iy.
approaches the prescribed DDREF.,,,,,,,,.. The value of the “shape” parameter was chosen to obtain
the least steep increase of the logistic function that still reproduces the DOREF.,,.,;, for a zero
dose’.

for fixed D, and selected values of the DDREF,

chronic

' This relationship ensures that the DDREF for a dose equal to D, is larger than 0.99.

69 G-69


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Statistical Uncertainty

Statistical Uncertainty

Leukemia (excl. CLL), by age al exposure and time afier exposure 1ghotkemia (excl CLL), by age at exposure andtime after exposire

19 7
5 : § r
g : 3
5 2
2 os 3
J 2
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5 2 age 20 al exp, 30 yrafter exp
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8 oof °
o 10 20 30 40 50 3 4 s 8

ERR at Sv ERR at 1Sv

Figure IV.D.1. Statistical uncertainty distributions for leukemia (all types except chronic
lymphocytic leukemia), by age at exposure (20 and 30) and time following exposure (5-35 yr).

Siatistical Uncertainty
Colon cancer, by age ai observation for risk

Statistical Uncertainty
cancer, by sex and age at exposure

08

06

~ Males, all exp ages
Females, exp age 0

Females, em age 10
Females, exp age 20
Females, exp age 30

04

02

Cumulative uncertainty distiibution function
Cumulative uncertainty distribution function

00.

3 4 5
ERR at 1 Sv

ope 025 050 O75 100 125 150 175 200
ERR at 1 Sv

Figure IV.D.2. Statistical uncertainty distributions for stomach cancer (by gender and age at
exposure) and colon cancer (by age at observation for risk)..

30


Uncertainty, including the statistical uncertainty inherent in estimates obtained by fitting
observational data to theoretical models and subjective uncertainty inherent in model
assumptions, is the primary focus of this report. One of the many advantages of replacing tables
by an interactive computer program is that much more detail can be made easily available to the
user, including a complete representation of the uncertainty pertaining to a particular AS
estimate.

The 1985 NIH report dealt with 13 different cancer sites for which there was strong statistical
evidence of a radiation dose response in human populations. However, lack of a statistically
significant dose response for a particular cancer type does not preclude a compensation award
based on an upper credibility limit for AS. For example, the upper 99% credibility limit for AS
can be greater than 50% even if the radiation dose response is not statistically significant (or even
if, in extreme cases, the point estimate is less than zero). The present report is based on the
working assumption that any type of cancer can, in principle, be induced by radiation, and that
the most important question concerns the magnitude of the risk associated with particular
exposures. In all, 33 different cancers and groups of cancers are treated, including several cancer
types not significantly associated with radiation dose. The report does not include malignant
melanoma and chronic lymphocytic leukemia, for which adequate data were lacking, or non-
melanoma skin cancer, for which U.S. population baseline rates are unavailable. Lung cancer
associated with radon exposure was not included because the most authoritative risk estimates,
published by the NAS/NRC BEIR VI Committee (NAS, 1999) were judged not to be easily
adaptable for AS purposes and to require more computational and staff resources than those
available to the present working group.

Treatment of uncertainty in the updated report is guided by that in the original report and by more
recent analyses, notably two publications of the National Council on Radiation Protection and
Measurements (NCRP): Commentary 14 (NCRP, 1996), “A guide for uncertainty analysis and
dose and risk assessments related to environmental contamination,” and Report 126 (NCRP,
1997), “Uncertainties in fatal cancer risk estimates used in radiation protection.” Essentially, the
method involves calculation of an uncertain excess relative risk (ERR = excess risk/baseline risk)
for the cancer of interest, as a function of radiation dose for each exposure. Other factors,
represented by a series of randomly distributed factors which are assumed to be statistically
independent, depend on informed but nevertheless subjective judgments from published reports
of expert committees or by the authors of this report. They are designed to contribute bias
correction and expression of additional uncertainty to a Monte Carlo simulation which provides a
corrected ERR estimate, expressed as the product of all factors, and its uncertainty distribution
combining all sources of uncertainty. If more than one exposure is involved, separate ERR


the 1985 NIH working group (NAS, 1984), that the PC values calculated according to the
formula given at the beginning of this summary pertain to populations rather than individuals,
and that they “are not probabilities in the usual sense and are truly properties of the group to
which a person belongs, but in practice are assigned to the person for purposes of compensation.”
The oversight committee recommended a change in terminology, replacing “probability of
causation,” by “assigned share” (AS) to emphasize the difference. The NIH working group did
not disagree, but continued to use “PC” because the term was already in common use. The
present working group feels that the oversight committee’s point is worth repeating, and has
chosen to use “AS” throughout its report. More generally, the working group emphasizes that the
AS values obtained using the report and its computer program represent a summary of scientific
findings about cancer risk following radiation exposure, that may be relevant to adjudication of
individual claims, but that the report makes no claims regarding the influence of individual
factors that have not been extensively studied.

It has also been argued by Greenland (1999) and others that AS is a logically flawed concept,
subject to substantial bias and therefore unsuitable as a guide to adjudication of compensation
claims in cases of possibly radiation-related cancer. The argument is based largely on the
possibility that radiation exposure may accelerate the time of appearance of cancers that, in the
absence of exposure, would have occurred later. The conclusion of the present working group, as
discussed in the text of this report, is that the argument is unpersuasive in the light of current
information about radiation-related risk. Scientific consensus about cancer risk following
radiation exposure is constantly evolving as new information is uncovered. This is a time of rapid
developments in our understanding of the carcinogenic process, and future developments may
force a fundamental changes in our view of radiation carcinogenesis. For the present, however,
the working group feels that current models are relevant both to radiation protection and the
adjudication of claims for possibly radiation-related instances of cancer.

The focus of this report is on quantitative expression of uncertainty in AS, reflecting statistical
uncertainty about risk estimates and more subjective uncertainty about model assumptions
necessary to apply such estimates to the adjudication of compensation claims for cancer
diagnosed following radiation exposure in the United States. In the U.S., unlike the United
Kingdom where a voluntary “Compensation Scheme for Radiation-linked Diseases” allows for
proportional compensation for AS values as low as 20% (Wakeford, 1999), adjudication of
claims revolves around the likelihood that AS may exceed 50%.. When there is a policy bias
(“benefit of the doubt”) in favor of the claimant, focus is on upper credibility limits for AS rather
than on a central estimate. For example, present VA policy is to award claims for which the
upper 99% credibility limit for AS is 50% or higher.


Joule per kilogram of tissue), instead of the previous unit used in the 1985 report, the rad (1 Gy =
100 rad; equivalently, 1 cGy = 1 rad), and equivalent dose, which incorporates different
weighting factors for different types and energies of radiation, in units of sievert (Sv; 1 Sv = 100
rem, where the rem is the previously used unit). For low-LET radiation like gamma ray and x
ray, dose and equivalent dose are numerically equivalent (e.g. 5 cGy = 5 cSv), but for high-LET
radiation like neutrons or alpha particles, a given dose may correspond to many more units of
dose equivalent, depending on the type of radiation and the dose level. In the present report, it is
assumed that the starting point for calculations of AS are tissue-specific dose equivalent values
expressed in Sv or cSv, using the appropriate conversion from tissue dose in Gy.

19


data allowed the working group to conduct its own analyses directed at the needs of this report,
including modeling of dose-response modifiers such as age at exposure, and inclusion of cancer
types not significantly associated with radiation exposure.

Unlike the 1985 report, the current report is based on linear dose-response models for all solid
cancers, with an uncertain DDREF factor to allow for the possibility that risk per unit dose
decreases with decreasing dose and dose rate. This approach is not necessarily better than the
linear-quadratic model approach used previously, but it is accord with recent recommendations
by expert committees. Also, the present report treats relative biological effectiveness of densely
cf, sparsely ionizing radiation as an uncertain quantity. The present report’s treatment of the
problem of transfer of estimates between populations with different baseline rates is an important
change, and accounts for a large part of the total uncertainty for several sites.

As previously mentioned, this is an interim report which is expected to be modified as new
information on radiation-related risk becomes available. It is hoped that the form of the report
may prove to be of more lasting value. In particular, the IREP program is constructed to allow -
new risk estimates and statistical uncertainty distributions to replace old ones, for new cancer
sites to be added, and for the treatment of other sources of uncertainty to be modified. The
program will be made available for use from an NCI web site, and will be maintained and revised
as necessary and appropriate.


obtained on the basis of the limited data available. Thus, there was no evidence that it is
associated with radiation exposure but, also, no persuasive evidence that it is not. Non-
melanoma skin cancer was not included because, although risk, and risk of basal cell carcinoma
in particular, have been found to be associated with radiation dose in the A-bomb survivor
population (Thompson et al, 1994, Ron et al, 1998) and in persons irradiated as children in
connection with treatment for ringworm of the scalp (Shore, 1984), it is not a reportable illness in
the United States and reliable population rates are lacking.

Calculations were performed for the following cancers which were not significantly associated
with radiation dose: cancers of the oral cavity and pharynx as a group, rectum, gall bladder,
pancreas, residual gastric, nasal, larynx and residual respiratory, female genital cancers as a
group, uterus not otherwise specified (NOS), uterine cervix, prostate, testes and residual male
genital, renal pelvis, lymphoma, and multiple myeloma. Modifiers of dose response included in
the fitted model, such as gender, age at exposure, attained age, and time following exposure, are
presented in Table [V.C.1 for these cancers and for others whose associations with radiation dose
are more clearly established.

25


Draft Report of the NCI-CDC Working Group to Revise
the 1985 NIH Radioepidemiological Tables

May 31, 2000

Members of the working group:

Charles Land (chairman) and Ethel Gilbert, Radiation Epidemiology Branch, Division of Cancer
Epidemiology and Genetics, National Cancer Institute

Jim Smith, Radiation Studies Branch, National Center for Environmental Health, Centers for
Disease Control and Prevention

Consultants:
F. Owen Hoffman, Julian Apostoaei, and Brian Thomas, SENES Oak Ridge, Inc.
Advisors:

Pat Buffler, U. of California (Berkeley);

Lars-Erik Holm, Swedish Radiation Protection Institute;
Jerome S. Puskin, EPA Office of Radiation and Indoor Air;
Dan Schafer, Dept of Statistics, Oregon State University;
Lincoln Grahlfs, Atomic Veterans Association;

Seth Tuler, Social and Environmental Research Institute


values greater than zero in calculations performed for the present report. Thus, it appears that very
little additional uncertainty would be contributed by allowing for deviations from the
multiplicative interaction model, for which no adjustment of ERR,,, is required for age at first
full-term pregnancy. This report therefore makes no uncertainty adjustment for this factor.

3. Lung cancer: interaction of radiation dose with smoking history. Interaction analyses of A-
bomb survivors (Blot et al, 1983) and uranium miners (NAS, 1988) failed to discriminate between
additive and multiplicative interaction models, although the BEIR IV committee concluded that
the data were more consistent with a multiplicative interaction (NAS, 1988 ). More recently,
Lubin and Steindorf (1995) modeled joint relative risks for smoking history (ever vs. never) and
exposure to inhaled radon decay products among 6 cohorts of U.S. uranium miners for which such
information was available. They concluded that, at that level of smoking history detail, the best-
fitting interaction model was intermediate between the additive and multiplicative interaction
models. The BEIR VI committee (NAS, 1999) applied the Lubin-Steindorf approach using more
recent data, and concluded that both the multiplicative and (especially) the additive interaction
models were statistically inconsistent with the data.

In the 1985 NIH report, it was assumed that the interaction of smoking and exposure to low-LET
radiation was additive with appropriate assigned shares obtained by multiplying the ERRs by the

icated in columns 2 and 3 of Tabie [V.G.1. These factors calculated as described

on pp. 48-51 of the 1985 report and based on lung cancer t alegory given
by Rogot and Murray (1980) and the disiribution of the U.S. population by smoking status in
1964-65 as published by the National Center for Health Statistics (1967). These factors can be
updated by using 1993 information on the smoking status distribution provided by the Centers for
Disease Control (1995). This distribution differs substantially from that used in the 1985 report as
shown in Table IV.G.2. Because the CDC report did not provide data on amount smoked, it was
assumed that among current smokers the distribution by amount smoked was the same as that
used in the 1985 report (p.50). It was also assumed that the relative risks by smoking category
remained appropriate. The revised factors for additive transportation are given in the last two
columns of Table IV.G.1.

ive risks by

48


Salivary gland | Survey of published results | Exposure ages 0-14 only

(Land, 1984)
Esophagus BEIR Ill
Stomach BEIR II
Colon BEIR Il Exposure ages 20+ only
Liver BEIR Ul Exposure ages 20+ only
Pancreas BEIR Il Exposure ages 20+ only
Lung Low-LET radiation: Kato | Exposure ages 10+ only

& Schull, 1982; high-LET
radiation, Jacobi et al, 1987

Breast Tokunaga et al, 1987 Linear dose response assumed; no effect of
fractionation or protraction of dose

Kidney & BEIR I Exposure ages 20+ only

bladder

Thyroid gland | LSS incidence study Linear dose response assumed; no effect of
(Parker et al, 1973) fractionation or protraction of dose

2. Dose-response models, Based on a review of the experimental and epidemiological literature,
a specific linear-quadratic model was assumed for all of the sites tabulated above, with the
exception of breast and thyroid gland, for which linearity was assumed. The linear-quadratic
model for a single, acute exposure to sparsely ionizing radiation (low-LET, for low linear energy
transfer) was that preferred by the BEIR III committee (NAS 1980, equation V-10),

excess risk = a (D + D7/1.16 ),

where D is dose in Gy and & depends upon site, age at exposure, and sex. The value of & was
equal to the corresponding linear-model risk coefficient from BEIR II or other source, divided
by 2.5. Excess risk associated with a chronic exposure, or with exposure to densely ionizing
(high-LET) radiation, was assumed to be linear in dose, with coefficient «. Different exposures
were considered to be additive in effect; that is, excess risks associated with radiation exposures
at different times were calculated separately and summed.

12


B. “Assigned share”

The National Academy of Sciences committee charged with oversight of the 1985 NIH
radioepidemiological tables report (NRC, 1984) objected to the use of the term “probability of
causation,” or “PC,” for the ratio,

PC= Risk due to radiation exposure
Baseline risk + risk due to radiation exposure

= excess relative risk
1 + excess relative risk

The NAS committee pointed out that a negative ERR would result in a negative “probability” (a
defect easily remedied by specifying boundary conditions for PC) and, more seriously, that the
ratio applied to populations and not individuals and could not be interpreted as the probability
that a given cancer was caused by a given radiation exposure. They recommended using the term
“assigned share” as a more appropriate term, because the computed quantities “are not
probabilities in the usual sense and are truly properties of the group to which a person belongs,
but in practice are assigned to the person for purposes of compensation.” The present working
group is sympathetic to this view and is in large part guided by it.

C. Methodology used in the 1985 report

1, Data sources. Baseline rates were taken from U.S. cancer incidence data for 1973-81 (SEER,
1984), by sex but not by race, and averaged over time . Site-specific average excess rates were
taken from the 1980 report of the NAS/NRC Committee on the Biological Effects of Ionizing
Radiation (BEIR IIB (NAS, 1980, Tables V-14 and V-16) and from other sources, as shown in
Table II.C.1. Lymphoma, multiple myeloma, and cancers of the prostate gland, uterus and
cervix, testis, and brain specifically were not covered, because of insufficient information and
lack of a statistically significant dose response. Chronic lymphocytic leukemia (CLL) was
considered to be unrelated to radiation exposure.

Table II.C.1. Cancer sites covered by the 1985 tables report.

Site/cancer Source of coefficients Comments

Leukemia BEIR Il Absolute risk coefficient for total leukemia
multiplied by 0.68 for AL, 0.32 for CGL

Bone and joint | BEIR III Injected 224-Ra only

11


OF, Upton AC, Yalow RS, Zeve VH. Report of the National Institutes of Health Ad Hoc Working
Group to Develop Radioepidemiological Tables. National Institutes of Health, Bethesda,
Maryland, 1985;355 pp.

Parker LN, Belsky JL, Yamamoto T, Kawamoto 8, Keehn RJ. Thyroid carcinoma after exposure
to atomic radiation. A continuing survey of a fixed population, Hiroshima and Nagasaki, 1958-
1971. Technical Report 5-73. Radiation Effects Research Foundation, Hiroshima, 1973.

Parkin DM, Whelan SL, Ferlay J, Raymond L, Young J, eds (1997) Cancer Incidence in Five
Continents, Voi VII (IARC Scientific Publications No. 143), Lyon, IARC.

Pierce DA, Stram DO, Vaeth M. Allowing for random errors in radiation dose estimates for the
atomic bomb survivor data. Radiat Res 1990; 123: 275-284.

Pierce DA, Preston DL. Joint analysis of site-specific cancer risks for the atomic bomb survivors.
Radiation Research 1993; 134:134-142.

Pierce DA, Shimizu Y, Preston DL, Vaeth M, Mabuchi K. Studies of the Mortality of Atomic
Bomb Survivors. Report 12, Part I. Cancer: 1950-1990. Radiation Research 1996; 146:1-27

Press WH, Teukolsky SA, Vetterling WT, Flannery BP. Numerical Recipes in FORTRAN 7 77.
fic Computing. Second Edition. Volume 1 of FORTRAN Nu al
1996

y Pr

Preston DLL, Kusumi $, Tomonaga M, Izumu 8, Ron E, Kuramoto A, Kamata N, Dohy H, Matsui
T, Nonaka H, Thompson DE, Soda M, Mabuchi K. Cancer incidence in atomic bomb survivors,
Part II: Leukemia, lymphoma, and multiple myeloma, 1950-87. Radiat Res. 1994; 137:S68-S97.

Preston DL, Lubin JH, Pierce DA: Epicure Users Guide. Seattle, Hirosoft International, 1991
Puskin JS, Nelson CB. Estimates of radiogenic cancer risks. Health Phys 1995; 69: 93-101.

Roesch WC, Ed., US-Japan Joint Reassessment of Atomic Bomb Radiation Dosimetry in
Hiroshima and Nagasaki. Final Report (2 vols., Radiation Effects Research Foundation,
Hiroshima, 1987).

Greenland, 1988, 1999; Robins, 1989a, 1989b; Beyea, 1999

Robins JM, Greenland S. Estimability and estimation of excess and etiologic fractions. Statistics
in Medicine, 1989; 8:845-859.

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

61


model and 50% on the trapezoidal distribution. The cumulative distribution functions for these
distributions are compared with that for the “uninformed” distribution in Figure IV.G.2.

44


and its estimated (adjusted) variance, respectively. ERR,s, for any given exposure age €, was
estimated as the exponential of @ calculated with e = exposure age - ey, and was assumed to have
a lognormal uncertainty distribution.

E. Correction for random and systematic errors in A-bomb survivor dosimetry

Our treatment of random and systematic errors in A-bomb survivor dosimetry was based mainly
on the treatment described in Chapter 3 of NCRP Report 126 (1997), and the reader is referred to
this material for details. The NCRP approach was also used by the EPA (1999). For each source
of uncertainty, a bias factor with an uncertainty distribution was specified, and this factor was
used to correct ERR estimates based on the A-bomb survivor data. Sources of bias and
uncertainty that were evaluated by the NCRP are as follows:

1) Uncertainty in the magnitude of random errors in the doses of individual survivors, called R,
in NCRP Report 126, contributed differently to biased uncertainty for solid cancers and the
leukemias, for which the forms of the dose response were linear and linear-quadratic, respectively.
Unlike the NCRP report, the present report is concerned with individual cancer sites and must
consider the two cases separately: uncertain bias correction factors 1+F,(R,) and 1+F(R,) for
cancers with linear and linear-quadratic dose responses, respectively. Pierce et al (1990)
recommended a lognormally-distributed random error in individual dose estimates with
geometric mean (GM) = | and geometric standard deviation (GSD) = exp(0.35), corresponding to
an upward correction in estimated risk of 9.0% for solid cancers and 5.6% for leukemia, with
essentially no effect on the variability of the corrected risk estimates. There is, however, some
uncertainty corresponding to the assumed GSD of the lognormally-distributed random error in
dose estimates: the corresponding upward corrections are 6.8% and 4.3% for solid cancers and
leukemia, respectively assuming log GSD = 0.30, and 11.4% and 7.2% assuming log GSD = 0.40.
If we consider 0.30 and 0.40 to correspond to the 10" and 90" percentiles of an uncertainty
distribution for log GSD, and consider that random error in dose assignment can only bias
estimated risk downward, it seems appropriate to assume that F,(R,) and Fo(R,) are lognormal
with GM=8.8% and 5.56%, respectively, with common GSD=1.22 (i.e., LN(8.8%, 1.22)) and
LN(5.56%, 1.22)).

2) Uncertainty in the appropriate choice of neutron RBE in analyzing A-bomb survivor data,
denoted N, in NCRP 126 with error factor F(N,) distributed according to a triangular distribution
with minimum 0.9, most likely value 1.0, and maximum 1.1 (i.e., triangular(0.9, 1.0, 1.1)).

3) Uncertainty due to systematic bias in gamma dose estimates, denoted D, in NCRP 126 with
error factor F(D,) distributed as triangular(1.0, 1.1, 1.4).

32


Table IV.L1. Factors for adjusting the lung cancer ERR,,, for smoking status under the
assumption of an additive interaction model.

Used in the 1985 report Used in deriving uncertainty
distribution for this report (Ws*)

Smoking category (S) Males Females Maies Females
Total 1.00 1.00 1.00 1.00

Never smokers 6.81 4.64 474 3,90
Former smokers 171 1.17 1.19 0.98
Present smokers (all) 0.604 0.411 0.42 0.35

<10 cigarettes/day 1.75 1.19 1.22 1.00

10-20 cigarettes/day 0.71 0.48 0.49 0.41

21-39 cigarettes/day 0.41 0.28 0.28 0.23

40+ cigarettes/day 0.29 0.20 0.20 0.16

Ever smoker (Present

and former smokers) 0.73 0.47 0.51 0.41

Tabie 1V.i2. Percentage of the U.S. Population in Various Smoking Categories

Used in the 1985 report Used in this report

(Status in 1964-65) (Status in 1993)
Smoking category (S) Males Females Males Females
Never smokers 29.8 59.0 42.4 57.8
Former smokers 19.2 78 29.9 19.7
Current smokers (all) 51.0 33.2 27.7 22.5
<10 cigarettes/day 13.6 13.5 74* 9.2*
10-20 cigarettes/day 24.7 15.0 13.4* 10.2*
21-39 cigarettes/day 11.2 44 6.1* 3.0*
40+ cigarettes/day 14 0.3 0.8* 0.2*

*These percentages were obtained by assuming distribution by amount smoked among current
smokers was the same as that used in the 1985 report (p.50)

49


Statistical Uncertainty Statistica! Uncertainty
Thyroid cancer, by age at exposure Liver cancer, by sex and exposure age

os. 08

exp age 0
~~~ exp age §
exp age 10

08. 08

04 04

~~ Females, all exp ages
Mates, exp age 20
~~ —Males, exp age 30
ales, exp age 40
Males, exp age 50

‘exp age 40
‘exp age 45,
somexp age 50

Cumulative statistical uncertainty distribution
Cumulative statistical uncertainty distribution

fy 10 2 30 05 00 05 10 15 20 25 30 35
ERRat1Sv ERR at 1 Sv

Figure IV.D.3. Statistical uncertainty distributions for thyroid cancer (by age at exposure) and
liver cancer (by sex and, among males, age at exposure).

Thyroid cancer. Thyroid cancer risk, estimated from the combined analysis data used by Ron et
al (1995), required special handling because the data were from 6 different study populations
(treating Hiroshima and Nagasaki survivors separately) with possibly different baseline and
excess risks. The final model (there was no statistically significant dependence on gender or
attained age) was

ERR(D,e) = D exp(0,1,+...+Od, + Be),

where I,, ..., I, are indicator functions for the 6 study populations and where 9, ..., 0, are assumed
to be normally distributed random variables with common mean 0. Parameter estimates 6, ... 0,
and 3, and their estimated asymptotic covariance matrix, were obtained by Poisson regression
(Hirosoft). The parameter estimate @ was calculated as the mean of G, ..., 0,, weighted by the
inverse of their estimated covariance matrix . The off-diagonal elements of were positive,
indicating that 0, ..., 8, were positively correlated.

The variance of the estimate O was adjusted for nonhomogeneity of study populations by the
method of DerSimonian and Laird (1986) for meta-analysis of clinical trials, as adapted by Ron et
al (1995). The method assumes statistical independence among estimates obtained from different
studies, a condition that was not strictly met in the present analysis because a common age-at-
exposure parameter was used for the several studies. Since individual study estimates were
positively correlated, use of the method is likely to have overestimated the variance of @

The uncertainty distribution for 8 was assumed to be normal with mean and variance equal to 0

31


after exposure, the ERR, x, is estimated as 0.25, 0.5, and 0.75, respectively, times the fitted value
for ERR, ., at S years after exposure.

The minimum latency period for thyroid cancer was assumed to be about 5 years, and there was
no statistically significant evidence of a trend in ERR,,, with time following exposure. For a
smooth transition, and to allow for uncertainty in the minimum latent period, reduced values of
ERR, y, were computed for years 3, 4, 5, 6, and 7 years after exposure by multiplying the fitted,
specific to age at exposure, by 0.1, 0.25, 0.5, 0.75, and 0.9, respectively.

For ali other cancers, a minimal latency period of about 10 years was assumed, with a smooth
transition in ERR, ., from zero at 7 years to full estimated value at 13 years; thus, scaling factors
0.1, 0.25, 0.5, 0.75, and 0.9 are applied to years 8, 9, 10, 11, and 12, respectively.

The dose and dose-rate effectiveness factor (DDREF)

As discussed in IVF, for an acute exposure, the value DDREF jo. = 1 is used for doses larger than
arandomly generated reference dose D,, above which the dose response is assumed to be linear.
As the dose approaches zero, DDREF jure approaches the values prescribed for chronic exposure,
DDREF siyonice The mathematical formulation for the transition from DDREF.,,,,=1 at D=D, to

i i Dose = D,
DDREF youre =
geue —___1 if Dose < D,
;-__1_
DDREF ypronic
7 (Dose-1)
l+e §

The parameters J and S are, respectively, the inflection point (J = 0.5*D,) and the “shape”
parameter (S = I/In(500)); the smaller the values for S, the steeper the increase of the logistic

68


values and uncertainty distributions are calculated for each exposure, and combined. The overall
ERR is then transformed to obtain the AS:

AS = ERR((1+ERR).
Credibility limits for the AS are obtained as percentiles of its uncertainty distribution.
The various factors contributing to the overall estimate, and its uncertainty, are as follows:

ERR per unit of dose (or dose plus dose-squared) and its statistical uncertainty distribution are
taken from the tabulated likelihood curve obtained as the final output of statistical model fitting
performed by the working group. If the dose response varies by age at exposure, age at diagnosis,
or time following exposure, the ERR per unit dose may be interpolated among different
likelihood curves corresponding to different values of these variables. ERR per unit dose, as
estimated, may be influenced by random and systematic errors in A-bomb survivor dosimetry,
requiring several uncertain bias correction factors. Radiation dose for the claimant is entered by

the user, either as a known value or as an uncertain value with a user-specified uncertainty
distribution. Doses received at low doses and dose rates are adjusted by a factor (with
uncertainty) known as the dose and dose rate effectiveness factor (DDREF), which may reduce
the ERR per unit dose of gamma ray or other sparsely ionizing radiation. The DDREF does not
apply to neutrons, alpha particles, or other kinds of densely ionizing radiation which are thought
to have greater biological effects than sparsely ionizing radiation and are weighted accordingly.
A separate factor is used to express the uncertainty of this weighting, which may depend upon
type of radiation and the type of cancer.

Site-specific baseline risks for many cancers differ substantially between Japanese and US
populations, and there is considerable uncertainty about how this affects risks resulting from
radiation exposure. A complex and highly uncertain factor is required for transfer of risk
estimates from A-bomb survivors to a US population. Tobacco smoking is known to modify the

carcinogenic effects of radiation to the lung, requiring an uncertain adjustment factor. Finally, an
additional factor is included for miscellaneous sources of uncertainty for AS in populations (not
in individuals).

The present report is considered to be an interim update of the 1985 NIH report. Like that report,
its AS estimates are based primarily on A-bomb survivor data. The present working group has
had the advantage of access to comprehensive cancer incidence data from a greatly improved
RERF Tumor Registry, which are not only more recent but are based on more timely and more
accurate diagnoses than those available from death certificates. Incidence data are also more
relevant to compensation claims for cancers of delayed or low fatality. Direct access to RERF


the factors (or sources) included, and are similar to those conducted by the Environmental
Protection Agency (EPA,1999) and the National Council on Radiation Protection and
Measurement (NCRP,1997). A computer program, here called IREP (for interactive radio-
epidemiological program), has been developed to conduct these simulations individually for any
desired application, taking account of specific characteristics of both the exposure and of the
exposed individual.

The sources of uncertainty that are included are listed below, with details given in the sections
that follow and in the appendices.

1. Sampling variability in the estimated ERRs. Statistical analyses of A-bomb survivor cancer
incidence data were performed to estimate the ERR and its associated statistical uncertainty for
each type of cancer. Dose response was assumed to be linear for solid cancers, after dose-
response analyses found no evidence of departure from linearity. For leukemia, dose response
was assumed to be linear for densely ionizing radiation such as neutrons and alpha particles, and
for sparsely ionizing radiation (e.g., gamma ray, x ray) delivered at low dose rates; but quadratic
for acute exposures to sparsely ionizing radiation. For some cancer types, statistically significant
improvements in fit were obtained by modeling dependence of dose response on sex, age at
exposure, age at diagnosis, and/or time since exposure. For these cancers, sampling variability
reflects statistical uncertainty about the estimated dependency of dose response on these
additional factors. Details are given in Section [V.D and Appendix C.

2. Correction for random and systematic errors in A-bomb survivor dosimetry. Risk estimates
are adjusted for random errors in the doses assigned to individual survivors, and also to several
potential sources of systematic bias in these doses. The latter include systematic underestimation
of gamma rays for Hiroshima survivors, uncertainty in the weighting factor for neutrons, and
uncertainty in the neutron component of the total dose. Details are given in section IV.E.

3. Extrapolation of risk from sparsely ionizing radiation to low doses and dose rates. Doses
received at low doses and dose rates are adjusted by a factor known as the Dose and Dose Rate
Effectiveness Factor (DDREF). The treatment of the uncertainty in this factor is described in
Section IV.F and Appendix C.

4. RBE for high-LET radiation exposure. Densely ionizing radiation, with a high level of energy
transfer per length of radiation track in tissue (high linear energy transfer, or high-LET for short),
such as protons, neutrons, and alpha particles and other heavy ions, generally has a greater
biological effect per unit dose than low-LET radiation such as gamma ray, x ray, and beta
particles. For radiation protection purposes, high-LET radiation dose is weighted by an

22


related risk. Radiat Res 1996;146:28-36.

Land CE, Hayakawa N, Machado S, Yamada Y, Pike MC, Akiba A, Tokunaga M. A case-control
interview study of breast cancer among Japanese A-bomb survivors: II. Interactions between
epidemiological factors and radiation dose. Cancer Causes Control 1994;5:167-76.

Land CE, Boice JD Jr, Shore RE, Norman JE, Tokunaga M. Breast cancer risk from low-
dose exposures to ionizing radiation: results of a parallel analysis of three exposed —_ populations
of women. J Nati Cancer Inst 1980;65:353-75.

Little MP, Boice JD Jr. Comparison of breast cancer incidence in the Massachusetts tuberculosis
fluoroscopy cohort and in the Japanese atomic bomb survivors. Radiat Res 1999;151:280-292.

Lloyd RD, Miller SC, Taylor FW, Bruenger FW, Jee WSS, Angus W. Relative effectiveness of
2°Pu and some other internal emitters for bone cancer induction in beagles. Health Physics 1994;
67:346-353.

Lloyd RD, Angus W, Taylor FW, Bruenger FW, Miller SC. Soft Tissue Tumors Induced by
Monomeric ?°Pu. Health Physics 1995; 69:530-537

Lubin JH, Steindorf K. Cigarette use and the estimation of lung cancer attributable to radon in the

United Siates. Radiat Res. 1995; 141:79-85

tumor regisiries in Hiroshima and Nagasaki for incidence studies. Radiat Res 199.

Mattson A, Holmberg E, Preston D, Boice JD Jr. Radiation effects on breast cancer risk: a pooled
analysis of eight cohorts. Manuscript included among original papers included in the doctoral
thesis of Anders Mattson, “On Ionizing Radiation and Breast Cancer Risk,” presented to the
faculty of the Karolinska Institute, Stockholm, Sweden, 1999.

Mays CW, Spiess H. Epidemiological studies of German patients injected with Ra-224. In:
Epidemiology Applied to Health Phys. Proceedings of the 16th Midyear Topical Meeting of the
Health Physics Society, Albuquerque, N.M.: National Technical Information Service, Springfield,
VA, 1983, CONF-830101; 159-166

NAS/NRC 1980. National Academy of Sciences/National Research Council, Committee on the
Biological Effects of Ionizing Radiation: The effects on populations of exposure to low levels of
ionizing radiation: 1980, BEIR II]. National Academy Press, Washington, D.C.

NAS/NRC 1984. Oversight Committee on Radiodepidemiological Tables. Assigned Share for
Radiation as a Cause of Cancer - Review of Radioepidemiological Tables Assigning Probabilities

59


members, including the chairperson. Members and chair- person shail be selected by the
Secretary, or designee, from outstanding authorities in the fields of endocrinology, radiation
biology and pathology, radioepidemiology, biostatistics, and radiobiology. Members shall be
invited to serve for a period of one year. Management and support services shall be provided by
the Office of the Director, National Institutes of Health,

"Meetings

Approximately eight meetings shall be held at the call of the chairperson who shall also approve
the agenda. A government official shell be present at all meetings. Meetings shall be conducted
and records of proceedings kept as required by applicable laws and Department regulations.
Meetings shall be open to the public, except as determined otherwise by the Secretary; notice of
all meetings shall be given to the public.

«

‘Compensation

Members who are not full-time Federal employees shall be paid at the rate of $100 per day, plus
per-diem and travel expenses in accordance with Standard Government Travel Regulations.

"Annual Cost Estimate

including compensation and

yal man years

imated annual cost for operating the Ad Hoc Working Grow

tra enses for members but exclu

Section 7(b) of Public Law 97-414 directs that within one year after the date of enactment of this
Act (January 4, 1983), the Secretary of Health and Human Services shall publish the
radioepidemiological tables. The Ad Hoc Working Group will complete its task as outlined in the
Function section of this document and submit these findings to the Director, National Institutes of
Health, by October 15, 1983.

“Termination Date

Unless renewed by appropriate action prior to its expiration, the Ad Hoc Working Group to
Develop Radioepidemiological Tables will terminate on May 15, 1984.

Approved:
8-4-83 (signed) Margaret M.. Heckler”
Date Secretary

66


G. Relative biological effectiveness (RBE) factors for high-LET radiation

In this report, it is assumed that dose equivalent or weighted dose, in Sv, used as input for
calculation of AS was obtained from organ dose, in Gy, using a weighting factor appropriate to
the type of radiation and the cancer site involved. The weighting factors account for the relative
difference in effectiveness in inducing stochastic effects between different types of radiation and
50-250 kVp x-rays. Such weighting factors have been referred by different names (e.g., “relative
biological effectiveness” or RBE, quality factor or Q), depending on their derivation and intended
use. For present purposes, “RBE” will suffice.

It is well recognized that there is substantial uncertainty associated with RBE values. Accordingly,
an appropriate multiplicative uncertainty factor, denoted fppz, is introduced here into the
calculation of the ERR and its transformation, the AS. This factor is represented as a probability
distribution function, and it is specific for a given type of radiation and, for alpha particles, may

vary by type of cancer.

For neutrons, it is assumed that the dose provided by the user is based on an RBE value of 10,
which is a reasonable value for exposure to neutrons of mixed energies. The RBE for neutrons
varies as a function of energy, ranging from 5 to 20 (ICRP, 1991). For tumor induction by low
doses from fission neutrons, extreme values up to 200 were reported by Sinclair (1985) and ICRU
(1986). Later revisions of the same data gave values up to 60 (NCRP, 1990). In that report, fase
for neutrons was distributed as iognormal with a geometric mean (GM) of 1 and a geometric
standard deviation (GSD) of 1.75. The factor increases the uncertainty of the dose equivalent
prescribed by the user without changing its central value. The upper and lower 95% limits for this
probability distribution are a factor of 3 above or below the geometric mean. The same
distribution was used for all cancer types.

For alpha radiation, it is assumed that the dose provided by the user is based on an RBE value of
20. Specific factors fggz were derived for lung, liver, and bone cancers, and for leukemia, as
indicated in the dose reconstruction study for individuals exposed to **Pu released from Rocky
Flats (Grogan, 1999). A common adjustment factor was assigned for all other cancers.

ICRP Publication 31 (CRP, 1980) contains the most comprehensive review of the animal studies
(mice, rats, and dogs) relating Jung cancer induction by alpha radiation to that by beta and gamma
emitters. This review indicates that the alpha particle RBE for lung cancer is about 30 with a
range from 10 to 100. Here, fgg, was defined as lognormal with GM = 1.5 and GSD = 1.8. The
upper and lower 95% confidence limits for this probability distribution are a factor of 3.2 above or
below the geometric mean.

39


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NCRP Report No. 104 (1990) summarizes the RBE for various alpha emitters as determined from
animal studies. For inducing bone cancer, Ra is about 20 times more effective than Sr, while
23°Py is 15-17 times more effective than ”°Ra. Lloyd et al. (1994, 1995) also estimated a ratio of
16 by comparing cancer induction by monomeric plutonium and ”*Ra. By combining these
relative values, an RBE of about 320 (20*16) is obtained for ?°Pu. These studies generally refer
to exposures to very low doses. Thus, such a large RBE may represent an upper bound of the
possible values for RBE (i.e., RBE,, as defined by ICRP, 1991). Grogan et al. (1999) concluded
that the RBE for bone tumor induction could range from 15 to 320 with a central value of about
50, and that values of RBE larger than 400 are probably unrealistic. Using *°Pu as a surrogate for
bone-surface-seeking alpha emitters generally, and the central value of 50, a GSD of 2.4 can be
determined so that the upper 99% credibility limit does not exceed 400. The uncertainty factor
raz Was, therefore, defined as lognormal with GM = 2.5 (=50/20) and GSD = 2.4.

For leukemias, an RBE for alpha particles can be derived from the studies of the effects of
Thorotrast in humans. Grogan et al. (1999) reviewed the relevant studies and estimated that the
RBE values for leukemia range from 1 to 10, with a central value of 3. In this case, the fgg. was
defined as lognormal with GM = 0.15 (3/20) and a GSD = 2. The upper and lower bounds of the
95% confidence interval for this probability distribution are a factor of 3.8 above or below the
geometric mean.

The Thorotrast studies in humans as reviewed by UNSCEAR (1994) are used for diver cancer.
‘These studies indicate a range of RBE values from 8 to about 50. Assuming a central value for
RBE of 20, fone was defined as lognormal with GM = 1 and GSD = 1.75. The upper and the lower
bound of the 95% confidence interval for this probability distribution are a factor of 3 above or
below the geometric mean.

The RBE for alpha radiation and cancers other than liver, bone, lung and leukemia was taken to
be the same as for neutrons (i.e., a range of 5 to 60, with a central value of 20; NCRP, 1990;
Grogan et al., 1999). The factor fg, was defined as lognormal with GM = 1 and GSD = 1.75.
The upper and lower bounds of the 95% confidence interval for this probability distribution are a
factor of 3 above or below the geometric mean.

Protons are charged particles lighter than alpha particles or other heavy ions. Little is known
about the effectiveness of these particles in inducing cancer tumors. The dose equivalent
provided by the user is assumed here to be based on an RBE value of 5, as recommended by ICRP
(1991). In that report, the uncertainty in the RBE for protons was considered the same as the
uncertainty in the RBE for alpha particles. That is, the RBE factor fgg, for protons has GM =1,
but GM =1.8 for lung cancer, 2.4 for bone cancer, 2 for leukemias, and 1.75 for liver and for all

40


6. Method for modeling the modifying effects of gender, age at exposure, time after
exposure, and age at observation. The model for the 1985 report was based on separate EAR
coefficients for each of five age-at-exposure categories, and for the two genders; this was done for
all specific cancers other than leukemia although in some cases the younger ages at exposure
were omitted. The approach in the present report was to model the ERR as a function of gender
(g), age at exposure (e), age at observation (a), and time after exposure (t), treating all but gender
as continuous variables, e.g.,

ERR(D,x,¢,,1) = @D exp(Bg + ye + ba + €t).

Modifying factors g, e, a, and t were included in the model only if the improvement in fit was
statistically significant. This allowed us to select the most parsimonious models (in terms of the
number of parameters), and provided the basis for evaluating statistical uncertainty in age- and
gender-specific estimates. With the exception of leukemia and cancers of the colon and kidney, it
was unnecessary to include modifying variables other than gender and age at exposure.

7. Transfer of estimates between populations. An important source of uncertainty is the
applicability of risk estimates derived from Japanese A-bomb survivor data to a contemporary
US. population, especially for cancer types where baseline risks for the two countries differ
markedly. On th i
(BEIR UH, Land et a

s of comparisons of leukemia and breast cancer risk in different populations

< between populations in the 1985 NIH report was based on

the assumption s isks were comparable, and no aitempt was made to evaluate the
uncertainty resulting from this choice. For most cancer sites, however, there are few quantitative
data other than those available from the LSS; and it cannot be excluded that other transfer models
may be appropriate for different cancer sites (Land 1990, Land and Sinclair 1993, NCRP-126,
EPA 1999). Moreover, the choice of transfer model involves considerable uncertainty. In the
current report, uncertainty from this source has been evaluated, with central estimates chosen to
fall in between the NIH model and a model in which relative rather than absolute risks are
assumed comparable for Japanese and US populations. Cancers of the thyroid were treated

somewhat differently, as discussed in IV.G above.

8. Treatment of uncertainty. The treatment of uncertainty is similar to that in the 1985 report in
that uncertainties from each of several components or sources are evaluated separately and then
combined into an overall assessment based on the assumption that uncertainties from different
sources are independent. It is also similar in that many sources could not be evaluated using
rigorous statistical procedures, but required subjective judgements of the investigators. However,
the treatment of uncertainties in the updated report differs from the 1985 report in several
respects. First, components of uncertainty that were not evaluated earlier have been added,

55


Table IV.C.2 Hematopoietic cancers included in the present report, and dose-response
modifiers included in the risk estimate and uncertainty analysis.

Cancer type ICD-9 codes Cancer cases Modifiers in
fitted model!
210 <10 Total
mSv mSv
Leukemia, all types (except 204-208, 143 90 233 get
chronic lymphocytic leukemia) minus 204.1
Acute myelogenous leukemia 205.0 60 43 103 t
Acute lymphocytic leukemia 204.0 24 9 33 t
Chronic myelogenous leukemia | 205.1 41 17 58 gt
Multiple myeloma 203 31 29 60 none
Lymphoma 201-202 86 105 191 none

@ = gender, e = age at exposure, a = age at diagnosis, t = time following exposure

28



Hall E. Radiobiology for the Radioiogist. Lippincott Co., Philadelphia, 1994.

ichimaru M, Ishimaru T, Belsky JL. Incidence of leukemia in atomic bomb survivors belonging
to a fixed cohort in Hiroshima and Nagasaki, 1950-71. Radiation dose, years after exposure, age
at exposure, and type of leukemia. J Radiat Res, 1978; 19:262-282

ICRP (International Commission on Radiological Protection). 1980. Biological effects of inhaled
radionuclides. ICRP Publication 31. Annals of the ICRP Vol. 4, No. 1-2. Oxford, England.

ICRP (International Commission on Radiation Protection). 1990 recommendations of the
International Commission on Radiological Protection. ICRP Publication 60. Annals of the ICRP
1991; 21 No. 1-3:1-193.

ICRP (International Commission on Radiation Protection). ICRP Publication 79. Genetic
susceptibility to cancer. Ann ICRP 1998; 28:1-158.

ICRU (international Commission on Radiation Units and Measurements) 1986. The quality
factor in radiation protection. ICRU Report 40. International Commission on Radiation Units
and Measurements, Bethesda, Maryland.

Jacobi W, Paretzke HG, Schindel F. Lung cancer risk assessment of radon-exposed miners on the

ards model. :. Int. Conf. Occupational Radiation Safety in

cker), Ca: Nuclear Assoc., Toronto, 1985.

Kato H, Schull WJ. Studies of the mortality of A-bomb survivors. 7. Mortality, 1950-1978: Part
1. Cancer mortality. Radiat Res 1982; 90:395-432.

Kerr GD. Organ dose estimates for the Japanese atomic bomb survivors. Health Phys 1979;
37:487-508

Land CE. Carcinogenic effect of radiation on the human digestive tract and other organs. In:
Upton AC, Albert RE, Burns F, Shore RE, eds. Radiation carcinogenesis. New York:
Elsevier/North Holland, 1986;347-378.

Land CE. Projection of risk from one population to another. In: Renz K, ed. Risk estimates for
radiation carcinogenesis. K6In: Institut fiir Strahlenschutz der Berufsgenossenschaft der
Feinmechanik und Elektotechnik und der Berufsgenossenschaft der chemischen Industrie,
1990;42-49. Land CE, Sinclair WK. The relative contributions of different cancer sites to the
overall detriment associated with low-dose radiation exposure. Ann ICRP 1991;22:31-57.

Land CE, Saku T, Hayashi Y, Takahara O, Matsuura H, Tokuoka S, Tokunaga M, Mabuchi K.
Salivary gland tumor incidence among atomic bomb survivors, 1950-87. Evaluation of radiation-

58


APPENDIX C: Computational Details

Uncertainty due to sampling variation

As described in Section IV, uncertainty due to statistical variation was approximated by
likelihood profile distributions. These were based on analyses of A-bomb survivor cancer
incidence data, and were obtained for the ERR associated with each type of cancer. For some
cancers, separate functions were obtained for the two sexes and for specified ages at exposure
and/or times since exposure in 5- or 10-year intervals beginning at 0, or ages at diagnosis in 5- or
10-year intervals beginning at age 20 or 30. Table IV.B.1 shows the cancer types and whether or
not the ERR varied by sex, age at exposure, age at diagnosis, and time since exposure.

For use in IREP, the likelihood profile distributions were specified approximately, using
likelihood-based confidence bounds in place of distribution percentiles: 0.25%, 0.50%, 1.25%,
2.50%, 5.00%, 12.50%, 15.85%, 50% (approximated by the maximum likelihood estimate),
84.15%, 87.50%, 95.00%, 97.50%, 98.75%, 99.50%, and 99,75%. Intermediate values were
calculated by cubic spline interpolation (Press et al., 1996), For all cancer types other than
leukemia, 400 interpolated points were used to define the likelihood functions. For leukemia, the
ERR, s, depends on both age: at exposure 8 and time since exposure {see below). Therefore, only

slat
iat

hundred int

i

ERR, for

TRY gy ©

obt

any age

linear interpolation in the log ulated ERR, y, vai
The ERR, s, for leukemia depends on both the age-at-exposure and time-since-exposure. In this
case a bilinear two-dimensional interpolation was performed (Press et al. 1996). From the
numerical point of view, the cubic spline interpolation between percentiles was performed first.
Then, the log-linear interpolation between ages-at-exposure or times-since-exposure was
performed for each derived percentile of the likelihood function.

amic scale was pe:

Phasing in the latency period

The analyses described in Section IV-C were based on a model in which the risk was assumed to
be zero for a specified minimal latency period after exposure. To avoid an abrupt jump in the
ERR, we used a set of scaling factors to estimate the ERR, s, for the years between the end of the
latency period and the age at which maximum risk occurs.

For leukemia (all types), the latency period is considered to end 2 years after exposure, although
the Life Span Study data cover only the period 5 years and more after exposure. Accordingly, we
phased in the fitted ERR, allowing full expression 5 years after exposure. For 2, 3, and 4 years

67


4. Modeling of the excess relative risk (ERR) instead of the excess
absolute risk (EAR)

5. Radiation dose response and adjustment for low dose-rate exposure

6. Method for modeling the modifying effects of gender, age at exposure,

time after exposure, and age at observation
7. Additional attention to the transfer of estimates between populations
8. New emphasis was placed on the estimation of uncertainty
REFERENCES
APPENDIX A: Text of Congressional Mandate and Excerpt from Presidential
Statement
APPENDIX B: DHHS Charter - Ad Hoc Working Group to Develop
Radioepidemiological Tables
APPENDIX C
Computational details for evaluating uncertainty due to sampling variation
Phasing in the latency period
The dose and dose-rate effectiveness factor (DDREF)

APPENDIX D: Example AS calculations and comparisons with the 1985 report
APPENDIX E: Interactive Radio-epidemiological Program ([REP)
Access Instructions

Users Guide

63

64
66
66
66
67

69

77

77

78


I. Modification by epidemiological risk factors

Site-specific studies of radiation dose and cancer risk, in LSS sample and in other exposed
populations continually followed up over time, generally proceed in a series of steps beginning
with the evaluation of evidence that a dose-related excess risk actually exists. Usually, the first
modifiers of dose response to be considered are gender, age at exposure, age at observation
(attained age), and time following exposure, since information about them is usually obtained at
the same time as information on radiation exposure and disease occurrence. Modification of dose
response by other factors is a more difficult problem, because it usually requires special data-
gathering efforts, such as with an embedded case-control study. Informative studies of interaction
between radiation dose and epidemiological risk factors have been carried out for reproductive
history in the case of breast cancer and for smoking history in the case of lung cancer.

1. General formulation. If radiation dose D and factor fare multiplicative in effect, then the
excess relative risk associated with exposure D is independent of f i.e., ERRp,= ERRp.. If D and
fare additive in effect, then the conditional ERR associated with D given exposure fis

ERR,,= ERR,/(1+ERR).

2. Breast cancer: interaction of radiation and age at first full-term pregnancy. Reproductive
history is known to be an important breast cancer risk factor. In particular, early age at first full-
term pregnency has been shown, in virtually every population that has been studied, to be
protective. A case-control interview study of femaie A-bomb survivors examined the interaction
of this risk factor with radiation dose (Land et al, 1994), and found that an additive interaction
model was rejected, whereas a multiplicative interaction model was consistent with the data. A
general risk model,

Raix(D,X;B,8) = (1 + OD)(1 + BX/{1 + oD},
was used to distinguish between the multiplicative model (corresponding to 0=0),
Ryun(D,X;B) = (1 + @gD)(1 + BX),
and the additive model (corresponding to 6=1),
Ryga(D.X;B) = 1 + gD + BX.

Here, D is radiation dose, X is age at first full-term pregnancy, 0, is a parametric function
describing radiation dose response as a function of age at exposure, and B is an unknown.
parameter corresponding to X. The maximum likelihood estimate of the parameter 0 was
negative (-0.25) (Land, 1994) and the likelihood distribution placed less than 10% probability on

47


08

06

oa F

probability distribution function

02 |]

D1 0 O1 02 03 04 OS 06 07 08 O9 1 Lt
Linear combination coefficient "—*

Figure IV.H.1 Probability density function assigned to the coefficient y for linear combination of
the multiplicative (y=0) and additive (y=1) models for transfer of excess relative risk from one
population to another, for most types of cancer.

45


APPENDIX D
Example AS calculations and comparisons with the 1985 report

This section presents a number of examples of Assigned Share estimated for various hypothetical
cases compared with those included in the 1985 Radioepidemiological Tables report. An
important difference between the 1985 report and the present update is the total number of types
of cancers considered: there were 14 specific and general cancer types included in the 1985 report;
while, currently, risk coefficients and associated uncertainties are available for 33 cancer types.

The cases of leukemia are summarized in Appendix Table 1. The first exampie in that table is for
a female exposed at age 5 to a bone-marrow dose of 5 cGy of low-LET radiation, and diagnosed
with an acute leukemia at age 9, four years after exposure. By using the 1985 tables one obtains
an Assigned Share of 37%. * :

The present updated methodology (IREP) distinguishes between acute lymphocytic leukemia
(ALL) and acute myeloid leukemia (AML).a calculation was performed for each type of disease.
The central AS estimates using IREP were 38% for ALL and 8.4% for AML. IREP also gave
complete uncertainty distributions, with 95% and 99% quantiles 72% and 85% for ALL and 20%
and 27% for AML.

0, a chronic exposure of 9 cSv at age 21, and three acute
exposures to 1.1, 0.6, and 0.7 Sv, respectively, at age 25. The 1985 report gave AS = 6% in this
case, whereas IREP gave a central estimate of 11% with 95" and 99" quantiles 38% and 42%,
respectively.

iand 2 e¢Sv

Similar example cases are presented in Appendix Tables 1 through 12. The differences between
the results produced using the 1985 tables and the current version of the tables are not only due to
an updated set of risk coefficients, but also because of the adjustments that are explicitly taken
into account in applying the risk coefficients to the U.S. population.

70 G-70


Il. Reasons for update
A. New data, new findings

The original NIH report was written in 1984, and based on data available at that time. Site-
specific estimates of excess absolute risk (excess cases per 10° persons per year per rad), by
interval of age at exposure, were obtained from the BEIR Ili report (NAS, 1980), which relied
largely on A-bomb survivor mortality data for 1950-74 but also on other studies. The NIH report
also used more recent risk coefficients from the A-bomb survivor Life Span Study (LSS)
mortality report for 1950-78 (Kato&Schull, 1982) and site-specific, incidence-based studies of
leukemia (Ichimaru, ), thyroid cancer (Parker, 1974, Ishimaru, personal communication), and
female breast cancer (Tokunaga, 1984) in the same population. To a lesser extent, the report
surveyed studies of cancer mortality in British patients given therapeutic radiation for ankylosing
spondylitis (1981), lung cancer among Czech, Canadian, Swedish and U.S. uranium miners
(Jacobi, 1984 ), thyroid cancer in patients given x-ray epilation for treatment of tinea capitis (Ron
and Modan, 1980, 1984), breast cancer among women given medical x rays (Boice, 1977, Shore,
1977), bone sarcoma among German patients treated for benign disease with injected radium
(Mays, 1983), and estimates of salivary gland cancer risk in various irradiated populations (Land,
1984).__

In the succeeding 15 years, the dose reconstruction system for the A-bomb survivors has been.
revised, and a large amount of new information has been obtained relating radiation exposure to
subsequent cancer risk. For example, the number of cancer deaths among members of the cohort
of atomic bomb survivors followed by the RERF in Japan increased from 3842 in 1950-74 (Kato
and Schull, 1982) to 7827 in 1950-90 (Pierce, 1996). Much of the newer information pertains to
cohort members exposed during the first and second decades of life: as these survivors reached
ages at which cancer rates normally become appreciable, the newer data supported statistically
stable risk estimates not obtainable previously. The same is in general true for other exposed
cohorts that include persons exposed at young ages. In the original NIH report it was possible to
estimate risk of radiation-related cancer following exposure before age 10 and at ages 10-19 for
leukemia and cancers of the female breast, salivary gland, thyroid gland, and bone, while lung
and stomach cancer risk estimates were available for exposure at ages 10-19. For other sites
covered by the report (esophagus, colon, liver, pancreas, and urinary cancers), no calculations
were done for exposure ages less than 20.

In addition, national and international committees have evaluated the newer data and used them
for risk assessment (NAS, 1991, ICRP, 1991, UNSCEAR, 1988, 1994). Although none of these
evaluations take account of the latest data, they are based on more recent data than BEIR III and

15


REFERENCES

Beyea J, Greenland S. The importance of specifying the underlying biologic model in estimating
the probability of causation. Health Physics, 1999; 76:269-274.

Blot, W.J., Akiba, 8., Kato, H. Ionizing radiation and lung cancer: A review including
preliminary results from a case-control study among A-bomb survivors. In: Atomic Bomb
Survivor Data: Utilization and Analysis, R.L. Prentice and D.J. Thompson, eds. Philadelphia:
Society for industrial and Applied Mathematics, pp 235-248 (1984).

CDC (Centers for Disease Control). Morbidity and Mortality Weekly Report, Atlanta, GA -
Cigarette smoking among adults - United States 1993. JAMA 1995; 273(5):369-370.

CIRRPC (Committee on Interagency Radiation Research and Policy Coordination) Science Panel
Report No. 6. Use of probability of causation by the Veterans Administration in the Adjudication
of Claims of injury due to exposure to ionizing radiation. Committee on Interagency Radiation
Research and Policy Coordination, Office of Science and Technology Policy, Executive Office of
the President, Washington, D.C., August 1988 (ORAU 88/F-4).

DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled Clinical Trials, 1986; 7:177-
188.

EPA (Env Protection Agency?
402-R-00-003, Washington, D.C., May 1999,

rating Radio

cc Cancer Risks. EPA Report

Greenland S, Robins JM. Conceptual problems in the definition and interpretation of attributable
fractions. American Journal of Epidemiology, 1988; 128:1186-1197.

Greenland S. Relation of probability of causation to relative risk and doubling dose: a
methodologic error that has become a social problem. American Journal of Public Health, 1999;
89:1166-1169.

Griem ML, Kleinerman RA, Boice JD Jr, Stovall M, Shefner D, Lubin JH. Cancer following
radiotherapy for peptic ulcer. J Natl Cancer Inst 1994; 86:842-849.

Grogan HA, Sinclair WK, Voilleque PG. Assessing Risks from Exposure to Plutonium. Final
Report. Part of Task 3: Independent Analysis of Exposure, Dose and Health Risk to Offsite
Individuals. Radiological Assessment Corporation (RAC) Report no. 5, 1999.

Guess HA, Hoel DG. The effect of dose on cancer latency period. J Environ Pathol Toxicol 1977;
1:279-286.

57


tumors, 1958-1987. Radiat Res. 1994; 137:$17-S67.

Tokunaga M, Land CE, Yamamoto T, Asano M, Tokuoka S, Ezaki H, Nishimori I. Incidence of
female breast cancer among atomic bomb survivors, Hiroshima and Nagasaki, 1950-1980. Radiat
Res 1987;112:243-273.

Tokunaga M, Land CE, Tokuoka 8, Nishimori L Soda M, Akiba S. Incidence of female breast
cancer among atomic bomb survivors, Hiroshima and Nagasaki, 1950-1985. Radiat Res
$994;138:209-23.

UNSCEAR 1988. United Nations Scientific Committee on the Effects of Atomic Radiation.
Sources, Effects and Risks of Ionizing Radiation, No. E.88.[X.7, United Nations, New York.

UNSCEAR 1993. United Nations Scientific Committee on the Effects of Atomic Radiation.
Sources, Effects and Risks of Ionizing Radiation, No. E.94.IX.2, United Nations, New York.

UNSCEAR 1994. United Nations Scientific Committee on the Effects of Atomic Radiation.
Annex A: Epidemiological Studies of Radiation Carcinogenesis, pages 11-183 in Sources, Effects
and Risks of Ionizing Radiation, No. E.94.[X.11. United Nations, New York.

63


comprehensive expression of uncertainty, and one that is easily accessible to the user.
D. New attention to cancer sites whose association with radiation exposure is tenuous.

The cancers covered by the 1985 NIH report were those for which a statistically significant
radiation dose response had been demonstrated in one or more major analyses. Statistical
significance is equivalent to having a positive lower confidence limit, at a certain confidence
level, for dose-specific excess relative risk, and therefore also for the AS. The list of cancers
fitting this criterion is not greatly different today, but it is clearly possible for an upper
uncertainty limit for the ERR to be greater than 1, and hence for the corresponding AS limit to be
greater than 50%, even when the AS is not significantly greater than zero. Thus a wider range of
cancer sites is of interest than that covered by the 1985 report.

E. New analytical approaches and ways of summarizing data

The 15 years since the 1985 NIH report have seen enormous advances in accessible computing
power, particularly at the level of personal computers, and the development and refinement of
statistical packages for risk analysis. An important consequence is that statistical modeling of
radiation dose response and its modification by factors such as gender, age at exposure, time
since exposure, age at observation for risk, smoking history, and reproductive history can be
carried out far more quickly and easily than before. New analyses, tailored for particular
applications like the subject of this report, are easily accomplished, especially since the important
LSS mortality and incidence data are available from RERF on request from non-RERF
scientists. These data, grouped to protect the privacy of individual survivors, are those used in
the 1950-85 mortality report (Shimizu et al, 1990) and the 1994 incidence reports based on
RERF Tumor Registry and Leukemia Registry data through 1987 (Thompson et al, 1994, Preston
et al, 1994). The AMFIT algorithm for Poisson model regression, part of the Epicure statistical
package (Preston et al, 1991), is particularly well suited for cohort-based analyses of radiation-
related risk and has become closely identified with analyses of A-bomb survivor data in
particular. These statistical approaches were used, for example, to develop the models used in
the BEIR IV, V, and VI reports (NAS, 1988, 1990, 1999).

F. More attention to uncertainty and presentation of risk

The 1985 NIH report presented illustrative graphs of assigned share estimates, tables of
coefficients for various components needed to compute assigned share, and algorithms for
calculating assigned share from these coefficients for arbitrary values of radiation dose, age at
exposure, and time following exposure. Statistical and other sources of bias and uncertainty
were extensively discussed in a separate chapter, and estimates and algorithms were provided for

17


3. Emphasis on uncertainty analysis
B. Source of data

C. Choice of cancer types and approach to cancer types (each type considered
individually)

D. Estimation of risk coefficients and their statistical uncertainties
E. Correction for random and systematic errors in A-bomb survivor dosimetry
F. Dependence of risk on dose and dose rate for low-LET radiation
G. Relative biological effectiveness (RBE) factors for high-LET radiation
H. Transfer of ERR from the Japanese to the U.S. population
I. Modification by epidemiological risk factors
1. General formulation
2. Breast cancer: interaction of radiation and age at first full-term
pregnancy
3. Lung cancer: interaction of radiation dose with smoking history
J. Susceptible subgroups
K. Additional sources of uncertainty
¥. Features of the Approach
A. This is an interim update
B. Similarities to the 1985 report
1. Assigned share estimates based primarily on A-bomb survivor data.
2. Cancer sites evaluated include most of those in the 1985 report
3. Site-specific assigned share estimates based on data for that site alone.
4. Time since exposure was handled in the same manner
C. Important changes
1. Estimates were obtained for all cancer sites for which the calculations
could be performed, not just those established as “radiation-related.”

2. Assigned share estimates were based on incidence instead of mortality
data.

3. Assigned share estimates are based on analyses conducted for this

specific purpose instead of published risk estimates

21
24

24
29
32
33
39
41
46
46

46
47
49
49
56
50
50
50
51

51
51

52

52


Probability density

T T T T T t
0.00 0.05 040 015 020 025 0.30
Reference dose D,, in Gy

Figure IV.F.4. Log-uniform uncertainty distribution of reference dose D,, below which the
DDREF applies.

38


08-5 Of

TeTaoy sme TO 6 ~«bY «SE
LAT Moy ame 90 «6 hh OSE
LET MoT ome TT 6 th SE
LAL MoT ouoND 6 = EZ by IZ
LAT MOT ome = ZH HHO
Is 8€ SL SZ LE LAT MOT ome | ohh PMY g ayduexy
LaTMoy ame = ZOOL SZ
is fm 6 9 «Sf 8 LAT MOT ome gg ST SZ OT remy, aydurexg
ek ee 4 LAT MOT ome gg 6 aremy ajax
AS?
SALON 66 SG OSS ST ady poy arey pey s) ASL VV AVV 2puH GIOAHL

(asip Aqureyisoun Jo opnusored ) gat

“‘JaOURd PIOIAY] Jo sasvo ajdurexo

10y [o] areyg poudissy om Jo saweumsy — 1] AIqeL xIpueddy


Table IV.C.1 Solid cancer sites covered by the present report, and dose-response modifiers
included in the risk estimate and uncertainty analysis.

Cancer site’ ICD-O codes Cancer cases Modifiers in
fitted model
210 <10 = | Total
mSv_ | mSv
Oral cavity and pharynx? 140-149 64 68 132 none
Salivary glands‘ 142 18 1k
Parotid gland 142.0 7 6
Other salivary glands 142.1-9 11 5
Digestive system 150-159 2355 | 2442
Esophagus 150 84 101
Stomach 151 1305 | 1353
Colon 153 223 234
Rectum 154 179 172 |351 | none
Liver 155.0 283 302 585 ge
Gallbladder 155.1, 156 143 152 295 none
Pancreas , 157. 122 118 240 none
Other digestive 152, 158, 159 16 10 26 none
Respiratory system 160-165 528 499
Nasal cavity 160 34 21 55 none
Larynx and other respiratory 161, 163-165 45 55 100 none
Trachea, bronchus, and lung 162 449 423 872
Malignant melanoma 173 6 7 13
Female breast’ 174 452 514° | 966 e
Female genital® 179-184 430 461 891 none

26


Contents

I. Executive Summary

II. Background of 1985 report

A. Congressional mandate and its execution
B. “Assigned Share”
C. Methodology used in the 1985 report
1. Data sources
2. Dose-response models
3. Minimal latent period and distribution of risk over time following
exposure
4, Dependence of excess risk on sex and on age at exposure
5. Modification of ERR by other exposures and/or by host factors
D. Uncertainty

IE. Reasons for update

A. New data, new findings

B. New availability of risk data at the level of incidence.

C. The use of the NIH report today is somewhat different from that
contemplated at the time the report was written

D. New attention to cancer sites whose association with radiation exposure is
tenuous

E. New analytical approaches and ways of summarizing data

F. More attention to uncertainty and presentation of risk

G. Availability of interactive computer programs as an alternative to tabular
presentation

H. Use of organ-specific dose equivalent, in sievert (Sv)

IV. Description of the Approach

A. Overview
1. Assigned share

2. Criticisms by Greenland and others

10
10
11
il
UW
12

13
13
13
14
15
15
16

16

17
17
17

18
18
20
20
20
20


For the purposes of this report, the ERR,., for lung cancer is multiplied by a factor W, taken to be
x +(1-x)W,*, where S indexes smoking categories, the W,* are the factors given in columns 3
and 4 of Table IV.G.1, and x is assumed to follow a triangular distribution (0, 1, 1.1). This
uncertainty distribution allows the ERR,s, for lung cancer to range from that obtained with an
additive interaction (x = 0) to that obtained with a multiplicative interaction (x = 1), witha
probability of about .10 for a super-multiplicative interaction (x > 1). The median of this
distribution is .74, and at this value, W. = 1.97 for male never-smokers, W, = 0.87 for male ever-
smokers, W, = 1.75 for female never-smokers, and Ws = 0.85 for female ever-smokers. Thus, at
the median value, the ERR,,, for never smokers is a little more than twice that for ever-smokers.
A ratio of two was used by the BEIR VI committee, and was obtained from analyses of uranium
miner data (NAS, 1999, pg. 154).

J. Susceptible subgroups. Genetic susceptibility to radiation carcinogenesis is known to occur in
patients with xeroderma pigmentosum or hereditary retinoblastoma, and the possibility of other
such associations is of great interest for theories of carcinogenesis. However, most known genetic
syndromes predisposing to cancer are rare, and interactions with radiation dose have not been
quantified (ICRP, 1999). Such interactions therefore have not been explored in the present report.

K. Additional sources of uncertainty

As mentioned above (section IV.A), AS is aol intended to represent the probability that a
particular individual’s cancer was caused by his or her radiation exposure, but rather, the fraction
of cases of a particular kind of cancer, diagnosed at a particular age among a large group of U.S.
residents with a similar exposure history, that would not have occurred in the absence of that
exposure. Possible modifying effects of age at exposure, gender, age at diagnosis, and time
following exposure, plus (for certain sites) smoking history and reproductive history have been
studied and that information has been incorporated into the model. The working group has also
introduced crude uncertainty factors for transfer of risk coefficients between populations with
different baseline risks.

It is likely that there are other sources of bias and uncertainty influencing radiation-related risk
and AS, about which we have no useful information and, thus, no solid grounds for taking action.
However, a precedent was established in the original radioepidemiological tables report (NIH,
1985), and in NCRP Report 126 (NCRP, 1997) for use of a catch-all factor for additional, non-
specific sources of uncertainty. We have followed that precedent by introducing a residual “scale
factor,” lognormally distributed with GM = 1 and GSD = 1.5.

50


of dose response for cancer incidence and mortality among acutely exposed A-bomb survivors,
down to and including values below 0.2 Gy (Thompson et al., 1994, Pierce et al., 1996). Also,
continuous uncertainty distributions for DDREF, including values as low as one and as high as
five, have been used by NCRP (1997) and EPA (1999) for calculations of lifetime risk of all
cancer types combined (Figure [V.F.1).

In the present report, ERR is estimated as a function of radiation dose, and modified according to
exposure rate (acute or chronic) by application of an uncertain DDREF. The DDREF is applied to
all chronic exposures whereas, for an acute exposure, the DDREF is phased in as dose is
decreased, beginning at an uncertain reference dose less than 0.3 Sv and decreasing smoothly to
the value appropriate for chronic exposure. Fractionated acute exposures separated by 5 hours or
more are treated as separate exposures; thus, the DDREF is applied to each fraction and their
estimated effects on risk are added together. A discrete, subjective probability distribution of
DDREF (DDREF ojyonj-), based on the NCRP and EPA models (Figure IV.F.1), is applied to most
non-leukemia cancers for chronic exposures and to acute exposures at very low doses. The
distribution assigns subjective probability weights of 20%, 20%, 32%, 16%, 8%, and 4% to
DDREP opyonic Values 1, 1.5, 2, 3, 4, and 5, respectively (Figure IV.F.2). Both the mean and median
of this distribution are close to 2. The evidence for a linear dose-response is especially strong for
cancers of the thyroid gland and female breast (Ron et al, 1995, Tokunaga et al, 1994); for these
cancers, the distribution assigns weights of 40%, 23%, 23%, 10%, 4% and 0%, respectively, to the
specified array of values for DDREF.

chronict

The mean and median of this distribution are,
respectively, 1.7 and i.5.

For an acute exposure, the DDREF (DDREF,,..¢.) is modeled as a random quantity that approaches
DDREF ,j,onic 28 dose decreases to zero. Between zero and an uncertain reference dose, D,
(between 0.03 and 0.3 Gy), DDREF je increases smoothly from DDREF ironic At ZEtO dose to 1 at
D,, and above, according to a logistic function of dose (Figure IV.F.3). The uncertainty in the

reference dose D, is expressed as a log-uniform distribution (Figure IV.F.4).

34


between baseline rates in the two countries:

(eRR,.),,, = (ERR... { Baron )

\ Pus

Here, Bayan aNd Bys are the sex- and site-specific, age-adjusted background cancer incidence rates
in Japan (2 surrogate for the A-Bomb survivor cohort) and the US population, respectively, both
age-standardized to the world population age distribution (Parkin, 1997). The geometric standard
deviation of the ratio, B japay/Bys, Was adjusted by the method of DerSimonian and Laird (see IV.D,
thyroid cancer) for variation in age-standardized rates among the five ethnic subgroups of the US
population (African American, Asian and Pacific islander, Hispanic, Native American, and non-
Hispanic White).

The coefficient y of the linear combination can be used to favor one model or the other according
to the weight of evidence. For instance, y=0 corresponds to the additive model, y = 1 to the
multiplicative model, and y = ¥4 to the arithmetic average of the two. A Monte Carlo simulation
is used to express uncertainty about y, with y values sampled according to the following
probability density distribution:

|9.091-G7+0.1) -0.1<y<0.0
f(y) = 30.9091 0.0<y<10
(9.091-(.i-y)  1.0<ys11

The constant probability density shown above for y values between 0 and 1 reflects a complete
lack of knowledge about the appropriateness of particular weighted averages of the additive and
multiplicative transfer models, and the assignment of a small probability weight (9%) to values
less than zero and larger than one allows for the (subjectively unlikely) possibility that radiation-
related cancer risk might be negatively correlated with population baseline risk.

For breast and stomach cancer, more information is available and, thus, the “uninformed”
trapezoidal density given above and in Figure V.G.1 may be modified by redistributing some of
the weight to the additive transfer model in the case of breast cancer (Land et al, 1980, Little and
Boice, 1999, Mattson, 1999) or the multiplicative model for stomach cancer (Griem et al, 1994).
Thus, for breast cancer, a probability weight of 50% was assigned to the additive transfer model
(y= 0), and 50% was assigned to the trapezoidal probability density distribution. For stomach
cancer, a probability weight of 33% was assigned to the multiplicative model (y = 1), and 66% to
the trapezoidal distribution, while for thyroid cancer the weighting was 50% on the multiplicative

43


D. Estimation of risk coefficients and their statistical uncertainties

General models. Site-specific baseline incidence was modeled as a function of gender, city of
exposure (Hiroshima or Nagasaki), year of birth, calendar time (where indicated), and age at
observation for risk (attained age), as discussed in Thompson et al (1994) and Preston et al
(1994). Default dose-response models were linear (proportional to dose equivalent D in Sv,
henceforth cailed “dose” for brevity) for solid tumors and for leukemia associated with exposure
to high-LET radiation or low-LET radiation delivered at low dose rates (chronic exposure), and
linear-quadratic for leukemia associated with acute exposure to low-LET radiation. The
quadratic model was set to have equal contributions of the dose and dose-squared terms at 1 Sv
(proportional to D+D’). Fitting a general linear-quadratic (proportional to D+(D?) resulted in no
statistically significant evidence of nonlinearity for solid tumors or for lymphoma and multiple
myeloma among hematopoietic cancers. For leukemia generally (all types except chronic
lymphocytic (CLL)) and for acute myelogenous, acute lymphocytic, and chronic myelocytic
leukemia in particular, various estimates of { were obtained, depending on the type of leukemia,
that were greater than zero. However, since all these estimates were statistically consistent with
the default value (=1, the final models for leukemia and its subtypes were based on C=1.

In terms of potential modifying factors such as gender (g), age at exposure (e), attained age (a),
and time since exposure (1), the fitted modei was

ERR(D,g,¢,a,t) = f(D) exp(Bg + ye + da + et),

where f(D) = D for most cancers and f(D) = D+D*for leukemia associated with acute exposure to
low-LET radiation, where &, Bg, > 6, and € are unknown parameters. Parameter 0& was
estimated from the data; parameters Bg, y, 5, and € were estimated from the data or, if they
made no significant contribution to improvement of the fit of the model to the data, set to zero.
(Note that at least one of the parameters ‘y, 5, and € must always be set to zero because t = a-e.)

Uncertainty about all unknown parameters is reflected in uncertainty about ERR. The parameter
& corresponds to the excess relative risk when D=1 (or D+D* =1), g=0, e=0, a=0, and t=0. Thus
(for example) the estimated ERR,,, for leukemia (all types except CLL) among females exposed
at age 20 and observed at age 47 (27 years following exposure) can be obtained by setting 5=0
and assigning values to g, e, and t as follows: g = 0 and 1 for females and males, respectively, e =
exposure age - 20, and t = time since exposure - 27. The statistical uncertainty distribution of
the resulting estimate is described by the profile likelihood distribution of the fitted parameter a
(Figure IV.D.1). Other examples are shown in Figures IV.D.2 (stomach and colon) and IV.D.3
(thyroid and liver).

29


3. Minimal latent period and distribution of risk over time following exposure. For
leukemia and bone cancer, radiation-related risk was assumed to be distributed lognormally over
time following exposure, with a minimal latent period of 2 years. The lognormal distributions
differed by cancer type and subtype and (for acute leukemia) by age at exposure, and were
obtained by fitting original data. For other cancers, excess risk was assumed to be proportional
to age-specific baseline risk (i.e, ERR was assumed to be constant) beginning 10 years after
exposure; it was further assumed that there was no risk up to 5 years following exposure, and that
ERR increased from zero at 5 years to its full value at 10 years according to a symmetric, S-
shaped cubic polynomial function of time.

4. Dependence of excess risk on sex and on age at exposure. Following BEIR III, risk
estimates were given separately by sex and age at exposure categories, regardless of statistical
significance for these factors. Original estimates were in the form of excess (absolute) risk per
unit dose, by sex and interval of age at exposure, averaged over a follow-up time of 5-26, 10-30,
10-33, 10-34, or 10-35 years, depending upon site; this corresponded to the data sets on which
the estimates were based. Original estimates were converted to dose-specific ERR by dividing
estimated excess risk by baseline risk, i.e., obtained as the lifetable-weighted average of age-
specific SEER rates (SEER, 1997) over the same follow-up period. Thus, for sites where the
excess risk estimate was based on Japanese A-bomb survivor data, and where U.S. and Japanese
baseline rates differ, it was assumed that absolute risks, and not relative risks, averaged over the
period of observation, were the same in the two populations.

5. Modification of ERR by other exposures and/or by host factors. The question of host
factor modification was not addressed explicitly. Modification by other exposures was discussed
generally, but specific recommendations were made only for tobacco smoking, in the case of lung
cancer, and for radiation exposures other than those at issue. Different radiation exposures were
treated as additive in effect, as discussed in II.C.1 above. Thus, the excess cancer rate
corresponding to a second exposure was assumed to be independent of the excess cancer rate
corresponding to an earlier exposure. Smoking and low-LET radiation were also considered to
be additive in effect with respect to lung cancer causation, that is, the radiation-related excess
rate was assumed to be independent of smoking history. Thus, a smoker would have a lower
excess relative risk associated with exposure than an otherwise similar nonsmoker, because the
nonsmoker’s baseline rate was smaller. However, smoking and alpha radiation from inhaled
radon decay products were considered to be multiplicative in effect, i.e., computation of ERR for
radon exposure did not depend upon smoking history, since excess risk due to radiation and
baseline risk were assumed to be proportionally affected by smoking history.

13


APPENDIX B: DHHS Charter - Ad Hoc Working Group to Develop Radioepidemiological
Tables

“Purpose

Section 7(b) of Public Law 97-414 directs the Secretary of Health and Human Services to devise
and publish radioepidemiologicai tables that estimate the likelihood that persons with any
tadiation-related cancer who received specific radiation doses before the onset of the cancer
developed the disease as a result of such exposure. The tables must show the probability of
causation for each cancer associated with receipt of doses ranging from i millirad to 1,000 rads in
terms of sex, age at time of exposure, time from exposure to disease onset, and such other
categories as the Secretary, after consultation with appropriate scientific experts, determines to be
relevant. In carrying out this mandate, the Secretary deems it necessary to establish an Ad Hoc
Working Group to Develop Radioepidemiological Tables comprised of scientific experts whose
qualifications will insure a thorough, competent and timely completion of the task.

“Authority
42 U.S. Code 217a, Section 222 of the Public Health Service Act, as amended.

This Ad Hoc Working Group to Develop Radioepidemiological Tables is governed by th the
i lic Law 902-463, which sets forth standard a

In addition to developing radioepidemiological tables, the Ad Hoc Working Group shall:
1. Assess the credibility, validity, and degree of certainty associated with such tables; and

2. Compile the formulas that yielded the probabilities of causation listed in such tables. Such
formulas shall be published in such a manner and together with information necessary to
determine the probability of causation of any individual who has or has had a radiation-
related cancer and has received any given dose.

The tables specified in paragraph (1) and the formulas specified in paragraph (2) shall be devised
from the best available data that are most applicable to the United States, and shall be devised in
accordance with the best available scientific procedures and expertise. The Secretary of Health
and Human Services shall update these tables and formulas every four years, or whenever
necessary, to insure that they continue to represent the best available scientific data and expertise.

"Structure

The Ad Hoc Working Group to Develop Radioepidemiological Tables shall consist of eight

65


APPENDIX E: Interactive Radio-epidemiological Program GREP)
Access Instructions

AS calculations can be performed using IREP by accessing the NCI xxxx web site on the internet,
at wow.
modifications to IREP after installation, the IREP Users Guide, and instructions for mmning [REP
from the web site.

gov/xxxx. The web site contains the present report and a running account of

(This page is a place-holder for material to be provided once installation has taken place.)

81 G-81


VY. Features of the Approach
A. This is an interim update.

As noted in III A and B, in the last 15 years additional epidemiologic data have become available,
and these data have considerable potential for modifying and refining the AS tables now in use.
Also, several efforts have been made to summarize data that were not available at the time the
NIH report was published, and to develop risk estimates based on these data. However, these
efforts have not evaluated data from studies published in very recent years, including particularly
the latest updates of the Japanese A-bomb survivor incidence and mortality data. For example,
the most recent BEIR assessment was published in 1990 and the most recent ICRP assessment
was published in 1991. Thus, much of the available new data has not yet been evaluated by
expert committees charged with developing and recommending risk estimates. In addition, new
data, including updated follow-up for cancer incidence in the A-bomb survivors, are expected to
become available soon.

In part because of this situation, the BEIR VII - Phase 1 Committee has recommended that a
reassessment of the health effects of exposure to low levels of ionizing radiation be conducted,
and the BEIR VII - Phase 2 has been formed to undertake this task. It is anticipated that the

fier the

present report will be revised a’ EIR VI committee recommendations become available,

expected in two or three ye AS algorithms described here must be regarded as an

models endorsed by an official

interim update rather than one based or national or
international committee; therefore, it might differ appreciably from future tables based on the
BEIR VII - Phase 2 report. The current update nevertheless provides AS values that are based on
more up-to-date data and models than previously, and also makes notable improvements in the

treatment of uncertainties.
B. Similarities to the 1985 report

Because this update must be regarded as interim, the time frame and scope for carrying out data
analyses and model development were limited. For this reason, we did not begin from scratch to
develop new models, but instead used the models used for the 1985 AS tables as a starting point,
amending them as needed to reflect the most important changes in risk coefficients and risk
modeling approaches. Specifically, the following features of the 1985 tables were retained:

1. Assigned share estimates based primarily on A-bomb survivor data. The AS values in the
1985 report were based primarily on the A-bomb survivor data, although in some cases other data
were also used. The AS values in the current report are based almost entirely on A-bomb survivor
data and, with the exception of thyroid cancer, did not directly make use of data from studies of

Sl


AS are consistent with current scientific information in a particular instance of cancer following a
particular exposure. The working group therefore has provided for the calculation of uncertainty
distributions for AS, for all cancer types for which there were relevant data available from the
sources on which the present report is based.

2. Assigned share estimates were based on incidence instead of mortality data. Although the
1985 NIH report used incidence data from site-specific studies of leukemia and cancers of the
thyroid gland, female breast, and salivary gland, it relied mainly on data from the LSS mortality
survey. By contrast, the present report bases its estimates and models on data from the LSS
Tumor Registry and, in the case of thyroid cancer, from a pooled analysis of data from several
studies. The RERF Tumor Registry is now a highly reliable source of cancer incidence
information with good coverage of that part (80%) of the surviving LSS sample resident in the
environs of Hiroshima and Nagasaki (Mabuchi, 1994); this coverage goes far toward matching the
main advantage of the LSS death certificate data, viz., completeness of ascertainment for a general
population of both genders and all ages, acutely and simultaneously exposed to a range of whole-
body radiation doses and followed uniformly over time. Follow-up for the mortality series and for
incident diseases covered by the Leukemia Registry began on October 1, 1950, the entry date for
members of the LSS cohort; for the E LSS Tumor Registry, follow-up began on January 1, 1958.

The later beginning of the tumor i
covered by the

tious problem onl cancers of short latency,

most of which are s that involved
special case-ascertainment & otiod 195. 7, and for estimation of excess risk
among persons who were over 50 or 60 years of age when exposed. Comprehensive statistical
analyses of site-specific cancer incidence through 1987 were presented for solid cancers and
leukemia (Thompson, 1994, Preston, 1994) and, especially important for present purposes, the

original data sets were made available by RERF on disk.

3. Assigned share estimates are based on analyses conducted for this specific purpose
instead of published risk estimates. For the 1985 report, assigned shares were estimated from
tabulated published estimates, primarily from the BEIR III report. The availability of grouped
numerator and denominator data from LSS Tumor Registry for 1958-1987, plus similar data for
site-specific incidence studies of salivary gland and female breast cancer, and for a pooled study
of thyroid cancer in several irradiated populations, allowed the present working group to model
site-specific risks directly. This permitted the working group to determine independently the
dependence of dose-specific excess relative risk on important modifying factors, and to choose
models of suitable complexity.

4, Modeling of the excess relative risk (ERR) instead of the excess absolute risk (EAR). The
ERR was modeled directly rather than converted from tabulated estimates of EAR, as was done in

53


their existence and current use for radiation protection purposes underscores the fact that the
estimates used in the 1985 NIH report are out of date. The risk estimates provided in ICRP
Report 60 (1991) (based on the UNSCEAR 1988 report), in particular, are widely used and are
generally higher than those in the BEIR III report.

B. New availability of risk data at the level of incidence.

Perhaps the most important recent development, however, has been a remarkable improvement,
by the Radiation Effects Research Foundation (RERF) and its collaborators in Hiroshima and
Nagasaki, of the. Life Span Study (LSS) Tumor Registry to a high level of accuracy and
efficiency (Mabuchi, 1994). The LSS registry draws on hospital records and physician
notifications accessed by the local tumor registries of Hiroshima City, Nagasaki City, and
Nagasaki prefecture, pathology and hematology records through the Hiroshima and Nagasaki
tissue registries, and the Leukemia Registry developed in the late 1940s and early 1950s, as well
as the virtually complete system of mortality notification and ascertainment of death certificate
diagnosis that is the basis of the LSS mortality studies of atomic bomb survivors. In general,
incidence data, when they can be obtained, are superior to mortality data because they capture
information on cancers of low or delayed fatality and because they are based on diagnostic
information that is more detailed and more accurate than death certificate data.

C. The use of the NIH report today is somewhat different from that contemplated at the
time the report was written.

The circumstances of the legislation mandating the 1985 NIH report suggested that partial
compensation for claims of radiation-related cancer might be made on the basis of assigned share
estimates between 10% and 50%, whereas full compensation would apply for AS = 50%. Thus,
the main graphical displays in the report show computed, “best-estimate” AS values
corresponding to organ doses of 1, 10, and 100 rad (0.01, 0.10, and 1.0 Gy), as a function of age
at exposure and/or time following exposure, and the reader is referred to the chapter on
uncertainty limits for instructions on how to compute them. In fact, the tort law concept of “at
least as likely as not,” corresponding to AS > 50%, continues to dominate the language of claim
adjudication, with the notable modification in some important applications that claims may be
winnowed out only if there little or no reasonable doubt that the true value of the AS is less than
50%. For example, the Department of Veterans Affairs (VA) screens out claims for which the
99% upper limit for the AS is less than 50% (Dr. Neil Otchin, personal communication). This
development suggests that any revision of the 1985 report should seek a more nearly complete
expression of the scientific information related to risk of cancer following exposure to ionizing
radiation, as it applies to particular cases. In other words, emphasis should be placed upon a

16