The sex-specific tests of trend with dose result in p-values of .03 for
males and .02 for females (28).

Overall, the more recent data support the BEIR III risk coefficients
for liver cancer, except that the data are too fragile, for persons
exposed under age 20, for the BEIR estimate for that age-group to be used
(see Chapter VII-F). The BEIR III coefficients have been adjusted to the
period 1!-30 years after exposure.

Neither dose-response nor time-response has been adequately investi-
gated for cancer of the liver and, except for the Thorotrast patients,
whose irradiation 1s essentially continuous, there are too few cases of
radiogenic liver cancer for such analyses. Accordingly, the Working
Group has assumed that the appropriate dose-response functions are Linear-
quadratic for low-LET and linear for high-LET radiation and the appropriate
time-response function the constant relative risk wodel.

The baseline risk of liver cancer in the US population has been taken
from the data of the SEER program of the National Cancer Institute for
the years 1973-|981. Published data from the contributing registries for
the years 1973-1977 (8) reveal great variation (see Tables VII-1 and
VI1-2) and it should be stressed that it is the set of rates for all
areas (except Puerto Rico) combined and for all races combined that is
used in the calculations here.

Although lonizing radiation is clearly a risk factor for liver cancer,
there are far more important risk factors. These include exposure to
arsenic, vinyl chloride, probably hepatitis B virus, and alcohol (41).

For none of these factors are quantitative estimates of relative risk
firm enough for specific guidance in this context. Nor is there information
on any interaction between such risk factors and radiation in the etiology
of liver cancer. As noted in Chapter IV-G and in Chapter 1X, risk factors
other than ionizing radiation may be taken into consideration in interpre-
ting the PC values derived by the procedures presented here. If it is
believed that some other risk factor operates additively with radiation,
and the individual is thought to have been exposed to that risk factor to
an extent greater than the average for the population generally, then the
PC obtained from the present procedures may be somewhat excessive. But

if it is believed that the second risk factor may combine with radiation
to enhance risk in multiplicative fashion, the PC estimates based on

these procedures should be unbiassed.

The procedures for calculating PC values for liver cancer are based
on the assumptions and principles of Chapter V and the procedures of
Chapters VI and IX. As with most other sites, for liver cancer the
relative excess, R, in the baste equation

PC = R/(1 + R)
is found as the product of three functions, i-e.,

R = F(D) x T(Y) x K(A],S)

where F(D) represents the influence of the tissue dose (D} in rad of low-

- 219 =



wena od

emitting radon daughters) received over a period of years. in any case,
we will illustrate the calculations appropriate to the AIM.

(1) The Additive Interaction Model for Cigarette Smoking
and Lung Cancer.

The AIM formula (see Chapter I¥-G) for a given level s of smoking
iss

R(Dis) = RCD) x Ws)
where
W(s) = 1/(1 + R(s)), (1v-4)

and where R(s) represents the relative excess for smoking levels as
compered to baseline lung cancer incidence.

Baseline incidence depends upon age; however, from Kahn's data (8),
it is evidence that R(s) can be treated as independent of age. Because
baseline incidence corresponds to the general population of smokers and
nonsmokers, R(s) is negative for smoking levels s corresponding to lung
cancer risks less than average, such as nonsmoking, and the average over
all levels of R(s) is zero. Thus, if p(O), p(1),.-.,p(k) is the distribu-
tion of the general population over integer values of s from s = 0 for
nonsmokers to s = k for heavy smokers,

p(O)(1+R(0))+..,+p(k)(1+R(k)) = 1, CIV-5)

Published values of the relative risk RR(s) of lung cancer at
various smoking levels compare the rate at each level to that among
nonsmokers, and can therefore be written as

RR(s) = (14+R(s))/(1+R(0)). (19-6)
Therefore equation (1V-5) can be rewritten as
pCO) + pCL)RR(1)+...+p(k)RR(K) = 1/(1+R(0)) = WCO), (Iv-7)

If the values p(s) and RR(s) are known then W(0) can be calculated from
IV-7 and W(s) can be calculated from W(O), IV-6, and IV-4 for s =
1,2,+++,k as Ws) = W(O)/RR(s). (Iv-8)

The data on incidence of lung cancer used here refer to the period
1973-1981; we use data concerning smoking habits for the year July, 1964
- June, 1965 published by the National Center for Health Statistics (9).
Since the SEER incidence data for the years 1973-1981 center on the year
1977, we apply the smoking percentages obtained in 1964-1965 to the
incidence rates at ages ten years later; that is, for example, we apply
the percentages obtained in 1964-1965 at ages 25-44 to incidence data for
ages 35-54,

- 49 -


Relative Excess
Sex

Femate Breast Cancer:

KCA SD by Expesure Aga A,
Sex

1

Table X-1¢.
a

Female

Male

Female

Male

wroeon me

WADI ONO — ON — OW EK WOM OM RM RMA
SV FOOTE ANG REA GH OOM OFM OORT NO POMS Ae
ANCOR CAT SE ST NMMMOIOMNNANNNNN ST He HH COO OS UIO
KIT e ec eens cccese Ean COe COCO OUOoEoCeoEOSe
Seesesocvsoerscovcsccen coos c on eeneoaee
SOR OPES SOOCG05SO70 OR OGSOO CEOS EGAOGaLS

SOS et NOR MRO” NOE NON MOOK NM THON WOOK NMEA
OEE EEE TEE TAMIA DODO OOD DOOR AEN

4i

POR SEMIN KROwNeWOr — HEIN
Fy SPSL OOS FORME AMEE ONMEAN AON ODE MOO
BP 0 A OOO SOU AE POE OE INT PEMD OI ICL OU KEOUEAE
NUNN HOR eRe ee

SUNN ENON MOSH NOT NON OFO- AM SHOR wro-— nM Non
N

TTT TTR RR RR NAN NAN NNN

- 248 -



Table VII-8

Factors to be Used for Limits of a 90 Percent Credibility Interval

Factor for

Lower Upper
Kind of Cancer Years after Exposure Linit
All leukemia
except CLL Any 0.76 3.47
Acute or chronic
granulocytic leukemia Any 0.74 3.55
Bone Any 0.48 2.10
Salivary gland 5-14 0.28 1.78
15+ 0.41 2.42
Esophagus 5-14 0.39 3.36
15+ 0.57 4.58
Stomach, lung 5-14 0.44 3.00
15+ 0.65 4.03
Colon, kidney and 5-14 0.49 2.70
bladder 15+ 0.73 3.62
Liver 5-14 0.25 2.01
15+ 0.37 2.73
Pancreas 5714 0.32 1.60
15+ 0.47 2.214
Breast 5-14 0.62 2.14
15+ 0.93 2.82
Thyroid 5-14 0.35 1.44
18+ 0.52 1.93

~ 113 -



oben

lawned

- containing radioactive minerals. People in poorly ventilated buildings

are exposed to elevated levels of the radioactive gas radon, given off by
building material and by the natural radioactivity in the underlying soil
(9,10). The average dose equivalent to the bronchial epithelium, which
reflects exposure to radon, is now thought to be 3 rem annually (11).
This represents an increase of the previous estimate of 0.5 rem and re-
flects (a} a decision to employ a quality factor of 20 in place of the
factor of 10 previously used, and (b) recent measurements of the indoor
exposure to radon daughters inhalation, which has increased because of
reduced exchange with the outside air.

Average radiation doses from man-made sources are of the same
order of magnitude as from natural background, about 100 millirem per
year (4). By far the largest contribution is from medical diagnosis.
individuals receiving radiation therapy for benign or malignant disease
can get very large doses to certain parts of che body, up to several
thousand rad, but relatively few people get such treatment. Similarly,
the number of people occupationally exposed to ionizing radiation is not
large and, because the average exposures are within a few hundred millirem
per year, the contribution to the population average is quite small (4).
The dose from global fallout produced by nuclear weapon tests and from
radiation-emitting components of consumer products like television sets
and smoke detectors is negligibly small (4,6,12).

D. The Evidence for Radiation Carcinogenesis in Man

We know that ionizing radiation can cause cancer in man because .
Studies of different populations with documented exposures to high radia-
tion levels (hundreds or rhousands of times natural background) have
consistently found higher cancer rates than those seen in comparable,
non-exposed populations (13). lonizing radiation was used in diagnosis
and to cure or alleviate the symptoms of disease long before its carcino-
genic potential was fully appreciated, and is the treatment of choice for
some diseases (including cancer) for which the potential benefit outweighs
the risk of subsequent cancer.

Studies of patient populations highly exposed to X radiation during
diagnostic or ctherapeutic procedures constitute much of the epidemiologic
basis for our knowledge of radiation carcinogenesis (14). Information on
che effects of alpha-particle radiation comes from studies of workers who
ingested radium while painting instrument dials with luminous paine (15)
and from studies of uranium and other hard-rock miners working in atmos-
Pheres heavily contaminated with radon (16-17). There have been intensive
Studies of the survivors of the atomic bombings of Hiroshima and Nagasaki
in 1945 (5), and of natives of the Marshall Islands, who in 1954 were
€xposed to radioactive fallout from a nuclear weapons test in the Pacific
(18). The largest number of persons studied who were exposed to low-LET
radiation at low dose and dose rate were patients who received oral
fodine-131 for the treatment of hyperthyroidism (19).

From many studies it appears that, at some level of exposure,

fonizing radiation can increase the risk for many, and perhaps most, of
the types of cancer that occur in man. In general, it is clear that

-15-



Table PC-11 (Continued), Kidney and Bladder Cancer 10 or
More Years After Exposura to Low-LET Radiation, by age A
zt Exposure, Sex, and Dose in Rad. PC in Percent. to Two
Significant Digits or Three Decimal Places.

4; Sex
Male Famala

Dose
1 1g 130 1 16 100
61 «027 .29 4.8 +090 38 14
62 +027 «29 4.8 090 +97 %
63 +027 «29 4.3 +09t 97 16
64 027 +29 4.8 .09T 97 14
65 +027 +29 4.8 091 98 14,
6S 028 +30 4.9 «092 298 35.
6? 028 -39 4.9 «093 39 13.
43 628 30 4.9 2093 199 15,
69 1029 31 3.9 +096 .¢ 1S.
70 -029 add 5.f -095 t.g 1s.
71 029 -3t 5.1 «096 1.0 1$.
72 -030 «32 5.2 .097 1.0 15.
73 030 =32 3.3 098 1.0 15.
74 OST 33 5.3 099 Pa tS.
7s +031 33 5.4 «3G Wt 16.

- 336 +

peren

sasel

Slaw


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

20

10

Fig X-1-8-6

ACUTE LEUKEMIA
EXPOSURE AGE 50

aaa a.
100 RAD aa
fe" 19 RAD Se
$0 3s 60 6s 70 1s 90 es
AGE AT DIAGNOSIS Male
Female-----

~ 144 ~


tH

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

20

40

Fig X-1!-B-]

ACUTE LEUKEMIA
EXPOSURE AGE 0

40 30 35

Male ——
AGE AT DIAGNOSIS Female---

- 139 -



DAG Go Tre

sneer

vdaatned

REPORT OF THE NATIONAL INSTITUTES OF HEALTH

AD HOC WORKING GROUP TO DEVELOP RADIOEPIDEMIOLOGICAL TABLES

Responding to the Congressional Mandate under Section 7(b) of the

Orphan Drug Act of January 4, 1983 (PL 97-414)

January 4, 1985

Published by the
Office of the Director
National Institutes of Health

NIH Publication No. 85-2748

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
Public Health Service National Institutes of Health

Por vale Uy the Superintendent of Ducuments, US, Government Printing Office
Waxbington. D.C. 20402


Table VII-6

Summary of Uncertainties and the Effect of Their

Resolution on PC Values

Source of Uncertainty

Resolution by the
Working Group

Practical Effect on
PC Caiculations

Dose to individual

Source tables on
cancer incidence

influence of age at
exposure

Sex differences

Sites and cell-types

Minimal latent
period

Risk coefficients

Dosimetry in
epidemiologic
studies

Outside purview of
Working Group

SEER tables for all
races and regions
combined, but
specific by age

and sex; only 1973-
1981 data used

Many coefficients for
younger ages omitted;
interpolation is neces-
sary to obtain values
for single years

The few known sex dif-
ferentials are used

Lymphomas and multiple
myeloma excluded;
liver, pancreas,
salivary gland included

Minimum of 2 years for
leukemia and bone;
smoothed 5-10 for solid

BEIR III linear coeffi-
cients for solid tumors
adapted to linear-
quadratic model, except
breast and thyroid

As reflected in the
BEIR III coefficients

- 109 -

Highly variable,
especially if unbadged

Without further adjust-
ment for ethnic and re-
gional differences, bi
values may be high, or
low; ignoring changes
in incidence over tine
affects some PC's for
early onset of certain
cancers

Fewer PC values obtain-
able for younger ages;

PC’s for exposure

after age 65 epecially

uncertain

Unknown

Exclusion makes PC ap-
proach inapplicable;
inclusion may provide
wrong guidance

There will be fewer
zero PC values within
10 years of exposure

Essential statistical
uncertainty carried
forward into PC cal-
culations

A-bomb revision may
increase pany risk
coefficients by factor
of 1,2-2.2 and PC
values somewhat less



of follow-up on the Japanese A-bomb survivers and other irradiated groups
(see Chapter III-H), helped the Working Group to arrive at a number of
assumptions needed for its calculations.

The 1980 BETR report, as well as the published analyses reviewed in
Chapter ILI-H, suggested that time from an acute exposure until diagnosis
for radiation~induced bone cancer and leukemia follows wave-like distributions
like the lognornal. Accordingly, the Worging Group conducted analyses of
data on time to diagnosis from a German series of patients treated by
vadiuau-224 injections for ankylosing spondylitis, and who later developed
bone cancer at a rate more than 250 times that expected from baseline
population rates (10), and leukemia data from A-bomb survivors with high
radiation doses (11), supplemented by leukemia data from a British series
of patients treated with X radiation for ankylosing spondylitis (12).
Lognormal time-response models were fitted to these data, for all exposure
ages combined and as partitioned by age at exposure,

sad

The bone cancer data were found to conform closely to a lognormal
distribution for time to response, with minimum 1.52 years, and for which
the mean and variance on the logarithmic scale, after subtraction of the
minimum, were 2.12 and 0.48, respectively (Figure V-1). The ainimum
value was the least precise of the three estimated quantities; virtually
the same fitted probability distribution was obtained when the BEIR IIt
minimum of 2 years was assumed a priori. There was no evidence that the
distribution of rime to response depended on age at exposure or on radia-
tion dose.

The leukemia data were less easy to work with, partly because the
possibility that a given high-dose case was not radiogenic could not be
tuled out with as much confidence as with the bone cancer data, but
mainly because the cancer date for the A-bowb survivors for the first 5
years after exposure lacked suitable denominators (11). The BELR III
minimum of 2 years for the latent period was assumed. Based on the
British ankylosing spondylitis data (12), it was estimated rhat the
average annual excess leukemia rate during the period 2-5 years after
exposure was about half that during the next five years. From published
analyses of the A-bomb survivor data (3,13) it was determined that acute
leukemia (AL) and chronic granulocytic leukeuta (CGL) have different
temporal distributions following exposure, and that for AL, but not CGL,
time to diagnosis depends on age at exposure, (Very few of the leukemias
fn the series are of types other than AL or CGL.) According to the Work-
ing Group's analysis, the fitted lognormal distribution for CGL had mean
2.68 and variance 1.51 on the logarithmic scale of time in years minus
the assumed 2-year minimum (Figure V-2), while that for AL required an
adjustment for age at exposure. The estimated mean on the logarithmic
scale was 1.61 + .015 A, + .0005 a’, where A, denotes age at exposure,
and the variance was 0.35. For AL, therefore, the fitted distribution
predicts that with increasing age at exposure, radiation~induced cases tend
to occur longer after exposure and to be more widely dispersed in time
{Figure V-3). For leukemia in general, excluding the chronic Lymphocytic
form that apparently is not caused by radiation, the Working Group used a
mixture of the estimated time-to-response curves for CGL and AL, weighted
by .32 and .68, respectively (Figure V-4).

- 58 -


Liver Cancer: Relative Excess KCAy,S)
1 and Sex $

by Exposure Age A

Table X-7,

Sex

A

Sex

Female

Male

Female

Male

lnbAnbabed ite Lelad <intalt ated td
ONT COP MORK WOM Ss +

Cea TORY Wer en wewoenmmcog~
TIO OMS se FMM AMUN ED
Seeeeecevoovescesmoscccacoucas

scenonccese

Peovvesnces CDC SGESS

ROOK NMS H ON WEO- VM EMOR WHOH NM
STUNTING ODODECOOGR ANE

tT OUNR KR
VANNCORO— MING

MNsKNONKe YE OT WHE
BLL NYF ee NOOR ONIN HK OF MOM ROD
WSITMMMONNNNNT HK eH Klee oUoee
Seeeoancee

POST COCGCBBD OF OBCOS

ROROT NS NOK One NOS nen
ANNO MMMM MSs FESR TES

26

- 224


ESTIMATED PROBABILITY OF CAUSATION (PERCENT?

$o

20

Fig X-1-B-4

ACUTE LEUKEMIA
EXPOSURE AGE 30

- 142 -



TIA: Y)

0
0 5 10 15 20 25 30 35 40 45 50

Time Y in Years Following Exposure

i} Figure V-4. Time-to-tumor model for leukemia (all
types except chronic lymphocytic leukemia) induced

5 by a brief exposure to fonizing radiation at age

j Aj» T(Az,Y) is the probability of diagnosis within

one year after time ¥Y. Nuwbers within the graph

indicate age at exposure. (Data from refs, 12 and 12.)

- 69 =


single exposure because estinated risk under the linear model depends
only upon the total dose, Similarly, the three exposures at age 35 can
be treated as a single exposure.

Exposure I:

F(D) = 1

WY) = 24) 21 ~

K(20,f) = .0374

Ry = Fx Tx K= 1x 2 x 00374 = .0374
Exposure 2:

F(D} = 2

T(23) = 1°

K(20,£) = .0374

Rg =F xTxK= 2x 1x .0374 = .0748
Exposure 3;

F(D) = 9

T(23) = 1

K(21,f) = .0331

Rg = Fx Tx kK = 9x1 x 60331 = .2979

Exposures 4, 5, and 6:

F(l.1 + 0.6 + 0.7) = F(2.4) = 244
T(9) = .926
K(35,£) = .0175

Ras5.6 = FX Tx K = 264 x 0926 x 0175 = .0389

R= Ry + Ro + Ry + Ry5,6 = .0374 + 0748

+ 42979 + 0389 = .449

PC = R/(1 + R) = .449/1,449 = 4310 or 31%.

The uncertainty Surrounding PC estimates is discussed in Chapter VII,
and Section VII-O includes a derivation of approximate 90 percent credibility
intervals for PC estimates,

- 258 -


Chapter II: THE ETIOLOGY OF CANCER

A. Introduction

Cancer is the second leading cause of death in the United States
and has recently become one of the most intensively studied of diseases.
Many forms of human cancer are now recognized to have multiple causes.
In addition, a number of theorfes have been proposed to explain the
biological mechanisms of carcinogenesis. While our understanding of such
mechanisms is still very limited, it is apparent that the overall incidence
of cancer is related in large measure to cancer-causing factors in the
“environment” defined broadly to encompass air, water, food, and such
other factors as individual lifestyle, occupation, smoking habits, sexual
activity, etc.

This chapter surveys briefly some of the current theories of cancer.

It also summarizes what is known about the more important risk factors
that determine the likelihood of cancer in an individual.

B. Current Theories of Carcinogenesis

For many carcinogens the process of tumor development is postulated
to involve successive phases, three of which have traditionally been des-
ignated the initiation phase, the promotion phase, and the progression
phase. During che initiation phase, the DNA of the target cell, which
contains the genetic code, is presumed to be damaged or structurally
altered as the resule of exposure to radiation, a carcinogenic chemical,
or some other initiating agent. A variety of molecular mechanisms has
been hypothesized to explain the alteration of cellular DNA, including
random point mutation, gene rearrangement, chromosomal translocation, and
altered DNA methylation (1,2).

The promotional phase of cancer development is concerned with the
subsequent changes in the initiated cell that lead to development of an
overt tumor. It differs from initiation in a number of respects, being a
much slower process, which may cover a major portion of the human lifespan.
While a single exposure to an initiating substance can suffice to alter
DNA, promoting effects typically are induced only by prelonged contact
with the agent in question (2). Promotion may thus be based on different
mechanisms; for example, interference with normal regulation of cell
growth or with the body's natural defense mechanisms, including repair of
DNA damage, conjugation and detoxification of toxicants, immunological
resistance, hormone balance, etc. The progressive phase involves the out~
growth of progressively more malignant variants of the original neoplasm.

Together, the promotion and progression of neoplasia are envisioned
to involve a series of changes in the regulation of cell growth, with
variations in rhe malignancy of the resulting tumors by .the time they
become detectable clinically. Some forms of cancer, for example, are
known to grow rapidly and metastasize early, while others grow slowly and
remain localized indefinitely. These differences, which remain to be
fully explained, affect the probability of ascertainment of the cancers
in question.



LET radiation, T(y) Tepresents the variation in R over time in years (y)
after exposure, and K(Ay,8} represents the relative excess risk of liver
cancer for a person of age at exposure Ay and sex S$, when both F and T= 2,

Under the linear-quadratic model assumed for liver cancer, when expo->
sure is to low-LeT radiation .

F=D+ v2/116.

For liver cancer the influence of time (T) on the relative risk
depends entirely on years from exposure to diagnosis {¥). The function T
{s tabled below:

Y 0-4 5 6 7 8 9 10+
T iv} 2074 +259 +500 +74t +926 i,

The Standardized Tekative risk of excess liver cancer, K, is given
in the accompanying Table x-7 for low-LeT tadiatfon and for each sex and
year of completed age from 20 to 756 A few examples should clarify the
actual computational Procedures for ltver cancer following exposure to
ionizing radtation,

Example I a typical male, exposed at age 31 to 10 Tad of low-LET rad{a-
tion to the liver, with diagnosis of liver cancer at age 59, Then D =
10, A] = 31, and ¥ = 28,
F(D) = 10 + 102/116 = 10.86
TY) = T(28) = 1
K(Ay,S) = K(3l,m) = .00755
then R= Fx x K = 10,86 x i x +00755 = 0820
and PC = R/(1 + R) = +0820/1.0820 = -076 or 8%.
Example 2 4 typical female given 10 rad of low-LET radiation to the Liver
at age 36, with a diagnosis of liver cancer at age 55, 19 years after
exposure. Then Dp = 10, Ay = 36, and Y = 19,
FC10) = 10 + 102/116 = 10.86
TC19) =
K(36,£) = .0129
then R=FxeTxxK = 10.86 x 1 x .0129 = +140
and PC = R/(1+R) = 7160/(1.140) = 1123 or 12%,

Example 3 4 liver cancer was diagnosed at age 44 in a woman following
Several exposures to Low~LET tadiation at various ages. The first, of


2.

tel

8.

10.

li.

12.

REFERENCES - Chapter X

Ichimaru, M+, Ishimaru, T., Mikami, M., Yamada, Y., and Ohkita, T.,
Incidence of Leukemia in a Fixed Cohort of Atomic Bomb Survivors and
Controls, Hiroshima and Nagasaki, October 1950-December 1978. Technical
Report 13-91, Hiroshima, Radiation Effecte Research Foundation, 1981.

United Nations Scientific Committee on the Effects of Atomic Radiation,
“Sources and Effects of Ionizing Radiation.” Report to the General
Assembly, Publ. E.77.1X.1. United Nations, New York, 1977.

Smith, P. G. and Doll, R., Mortality among Patients with Ankylosing
Spondylitis after a Single Treatment Course with X-Ray. Bre Med. i.
284: 449-460 (1982).

Committee on the Biological Effects of Ionizing Radiation, “The Effects
on Populations of Exposure to Low Levels of Ionizing Radiation: 1980."
National Academy Press, Washington, D.C., 1980.

Boice, Je De, Jr. and Day, M. E., Cancer Risk Following Radiotherapy of
Cervical Cancer, In “Radiation Carcinogenesis: Epidemiolgy and
Biological Significance” (J, D. Boice, Jr. and J. F. Fraumeni, Jr.,
Eds.}, pp. 161-179. Raven Press, New York, 1984.

Stewart, A. M. and Kneale, G. W., Prenatal Radiation Exposure and
Childhood Cancer. Lancet 1: 42-43 (1971).

Monson, R. R., and MacMahon, B., Prenatal X-ray Exposure and Cancer

in Children. In “Radiation Carcinogenesis: Epidemiology and Biological
Significance” (J. BD. Boice, Jr. and J. F. Fraumeni, Jr., Eds.), pp»
97-105. Raven Press, New York, 1984.

Young, J. L., Jr., Percy, C. Ls, and Asire, A. J. (Eds.), “Surveillance,
Epidemiology, and End Results: Incidence and Mortality Data, 1973-1977."
National Cancer Institute Monograph 57. NIH Publication No. 81-2330.
U.S. Government Princing Office, Washington, D.Cc., 1981.

Heath, C. W., Jr., The Leukemtas. In "Cancer Epidemiology and Preven-
tion” (PD. Schotcenfeld and J. F. Fraumeni, Jr., Eds»), pp» 728-738.
W. Saunders, Philadelphia, 1982.

Rowland, R. E., Stehney, A» F., and Lucas, H. Fe, Jr., Dose-Response
Relationships for Female Radium Dial Workers, Radiat. Res. 76: 368-
383 (1978). .

Mays, C. W., Spiess, H., and Gerspach, A., Skeletal Effects Following
224-Ra Injections into Humans. Health Phys. 35: 83-90 (1978).

Mays, C. W. and Spiess, H., Epidemiological Studies of German Patients
Injected with 224Ra. In “Epidemiology Applied to Health Physics”
(Proceedings of the Sixteenth Midyear Topical Meeting, Health Physics
Society, Albuquerque NM, January 9-13, 1983), pp. 159-166, National
Technical Information Service CONF~830101, Washington, D.C., 1983.

- 263 -



Table PC-t-A-30. Chronic Granulocytic Leukemia Following
Exposure at Age 30, by Age 4z at Diagnosis, Sex, and Dosa
in Rad of Low-L€T Radiation. PC in Percent, to Tne
Significant Digits or Three Decimal Places.

A, Sex
Fale Female
Dese

1 19 190 t 18 100
32 1.9 17. 78. 1.6 1$. 75.
33 9.6 34. 90. 3.9 32. 83.
34 3.2 37. oN, 8.4 33. 89.
35 5.1 37. gi. 4.2 32. a9
36 4.7 35, 99, 3.9 30. 83
37 46.4 33. 87. 3.5 28. 8?
38 4.9 st. so 3.f 26. 36.
39 3.7 29. 8a 2.8 4. a4
40 3.3 27. 36 2.5 22. 82
G1 get 25. as. 2.2 29. Si.
42 2.8 24, 8¢. 2.0 18. 79
4&3 2.6 22. és. 1.8 17 77
44 2.3 ra 82. 1.8 46 7?
45 2.1 19. 3¢. 1.7 16 77
46 2.9 18. 79. 1,7 16, 76.
47 1,8 17, 77. 1.5 14, 74.
48 1.6 15. 75. t.3 13, 74.
49 1.4 43, 72. 1.t 11, 67.
so 1.2 $4, $9. oot 9.4 63.
3! +99 9.7 65. +77 7.8 59.
$2 84 &.4 61. 63 6.49 56.
$3 «72 7.2 37. +61 4.2 53.
$4 +62 6.3 53. +56 $.? $3,
$5 53 3.5 50. «52 5.3 49,
36 +48 4.8 46. 47 4.8 47.
37 «40 4.2 $3. +43 4.4 $4.
56 +35 3.6 39. +39 4.0 42.
59 “3! 3.2 36. .35 3.4 33.
69 +2? 33. 33 3.2 36.
1 +24 $1, «28 2.9 34.
62 +21 28. +25 2.6 32.
63 9 26. +22 2.3 29.
64 18 2¢. +20 2.1 27.
65 16 23. 1? 1.8 24.

- 276 -

eres

pres)

need


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

400 +

50

20

10

Fig X-2-5

BONE AND JOINT CANCER *
EXPOSURE AGE 40

“0 RAD ~~=. 100 RAD
yf
|
t
t SL
‘ e) ~sy
if 80 :
i
¥y
|
i
7
q
q
tj
i}
40 45 “so 3S 60 65 70 78
Male ———
AGE AT DIAGNOSIS tale —

*Alpha radiation from radium-224 only

- 187 -


Table PC-1-€-70. leukemia Excluding CLL Following Exposure
at Aqe 70, by Age A, at Diagnosis, Sex, and Dose in Rad
of Low-LET Radiatiad. PC in Percent, to Tuo Significant
Digits or Three Dacimal Places.

A2 Sex
Male Female
Dose

7 Ty Or) i 1 Toe
72 +23 2.4 30. 3.6 34.
73 $5 5.6 50. 7.0 56.
74 +60 6.5 53. 7.7 59.
75 +57 3.8 st. 7.4 58.
76 55 $.3 49. 6.7 35.
7 45 4.7 46. 5.3 52.
78 48 a. 42. 5.1 48.
79 +34 3.6 33. G4 44.
89 30 3.1 36. 3.8 40,
gi +26 2.8 33. 3.5 37.
a2 123 2.5 30. 2.9 34.
a3 set 2.2 28. 2-7 32.
84 19 2.90 26. 2.4 30.
85 18 4.9 25. 2.2 28.
a6 17 1.8 24. 2.1 27.
8? 16 1.7 23. 2.0 26.
é3 1s 1.6 22. 1.9 25.
89 14 1.5 21, 1.8 24.
92 \4 1.4 20. 1,7 23.
oi 13 1.4 19. 1.6 22.
92 212 1.35 19. 1.6 ai.
93° 112 1.3 18. 1.5 21.
a4 Pn 1.2 17, 1.4 29.
$5 Us t.2 17. 1.4 20,
36 tt 18 1. 1.4 19.
97 10 it 1§. 1.3 19.
bz 210 1d 1$. 3 18,
$9 1098 1.0° 15. 41.2 1B.
103 6096 1.0 15. 4.2 17,
194 1094 1.9 15. 4.2 97,
102 G92 98 1S. 1.2 17.
193 2095 9? 16 1.1 s7,
104 089 95 1q 14 1g,
105 088 94 14 1.3 to.

- 296 -

‘ated

nm

4


CHAPTER IX: THE GENERAL FORM OF THE PC CALCULATION

The probability of causation (PC) for a cancer diagnosed after one
or more exposures to fonizing radiation has the general form, simplified
from formula IV-2,

C= R/{1 + R).

The relative excess, R, in the case of a 6ingle exposure of short duration
to a subject typical of the US population, is given by the product of
three quantities:

R=FxTxk.

In the above expression F quantifies the dependence of R on the radiation
dose to the relevant tissue, and its quality, The use of a mere badge or
environmental reading would lead to erroneous PC values; absorbed cissue
dose must be used in the procedures described here. T gives the dependence
of Ron time after exposure. K indicates the dependence of R on age at
exposure, sex, and, for some cancers, age at diagnosis.

For low-LET radiation, the exposure factor F depends only upon radia=
tion dose D and whether the assumed dose-response function is linear or
linear~quadratic, The value of F is presented below as a function of
absorbed tissue dose (D), measured in rad, by cancer site and radiation
quality:

Radiation Quality Cancer Site

Bone Thyroid or Breasc Other
Low LET --- D D+ 02/116
High LET D --- ---

The above procedures are not intended to be used for cases involving
exposure from internal emitters, with che exception of radium-224 in rel-
ation to bone cancer.

The factor T = T(A,,Y) represents the relative likelihood thar a can-
cer induced by an exposure at age 4; will be diagnosed after ¥ years (1.¢.,
at least Y years but less than Y + 1 years). In this report both age and Y¥
are integer-valued variables: a person exposed 17 years and 4 months
after birth is considered to be 17 years old at exposure, and if a cancer
is diagnosed 12 years, 11 months after exposure Y is considered to be
12 years.

Under the constant relative risk model, which has been used here for

cancers other than leukemia and bone cancer, T depends only on Y, and this
dependence {s extremely simple (see Chapter V):

- 118 -


Table PC-!-B-60. Acute Leukemia Following Exposure at Age 60,
by Age A, at Diagnosis, Sex, and Bose in Rad of Low-LET
Radiation. PC in Percent, to Two Significant Digits or
Three Dacimal Places.

Ae . Sex
Male Female
Dose

i i) 109 4 10 700
62 +090 .000 002 600 +d00 +062
63 oor O41 19 600 099 17
64 2008 .088 1.5 007 +077 13
65 028 «30 4.9 025 «26 4.3
66 +962 67 1G, 7055 259 9.3
$? aff 4.2 17, «058 1.a 18.
68 «16 1.7 23. 38 1.6 2).
69 +2! 2-2 28. +20 2.1 27.
70 +25 2.6 32. +25 2.6 33,
7 629 3.0 35. «29 3.0 35.
72 -32 3.3 37. +33 3.5 38.
73 235 3.6 3%. 37 3.9 41,
74 38 3.9 41. +49 4.2 43.
75 +40 6.1 42. «43 4.4 44.
76 a4t 4.3 43. 345 4.7 4$.
77 43 4.4 44. 4? 4.8 47.
78 4% 4.5 45. 47 4.9 47.
79 145 4.6 45. 46 4.8 56.
bo +45 4.7 46, 145 4.7 46.
Bt 46 4.7 46. 45 4.6 4&5.
82 346 4.8 G6, +4@ 4.7 46.
83 47 4.8 46. 46 4.8 S$.
bo +48 4.9 47. 4? 4.9 47.
85 +49 5.9 47. +48 $.¢ 47.
6 «59 5.1 48, +50 5.4 48.
87 +5t 5.3 43. 81 $.3 49,
88 -$3 3.4 a9. 53 5.4 $9.
83 54 5.5 $4. 34 $.5 54.
90 755 5.6 50. -55 3.6 so.
91 +56 $.7 St. 55 $.2 $1.
92 -56 5.7 $1. $6 3.7 Si,
93 5? 3.8 Bi, 57 5.3 $1.
94 57 $.9 $2. .$? $.8 $2.
$5 +58 5.9 52. 58 5.9 52.

- 287 -



Tespectively, were received on consecutive days, 9 years and 2 months
prior to diagnosis. .

The first, second, and third exposures should be considered separately,
because exposures 1 and 2 correspond to different values of Y, and exposures
2 and 3 to different exposure ages. The 9~rad continuous exposure delfvered
over 36 hours should be treated as 2 exposures because it required more than
one day, but less than two. The partition giving the maximum risk estimate
assigns 3 rad to one 24-hour period and 6 rad to another. The three ex-
posures at age 35 can be treated as one because they correspond to the
Same values of A) and Y, and because the total dose ds less than 5 rad.

Exposure 1]:
F(D) = F(1) = 1 + 12/116 = 1.01
TCA] ,¥) = 1(20,24) = .0101 (Table x~1-p)

E(A),8) = E(20,f) = .914 (Table X-1-£)

T(Az,8) = 1(44,f) = 2.73 (Table X-1-F)
K = E/T = .914/2.73 = 0,335
Ry = Fx Tx K= 1.01 x -O101 x .335 = .00342.
Exposure 2:
F(2) = 2 + 22/116 = 2.03
T(20,23) = .0114
E(20,f) = 924
1(44,f) = 2.73
K = E/E = .914/2.73 = 0.335
Ro = Fx Tx K = 2.03 x .0114 x .335 = .00775
Exposure 3a:
F(3) = 3 + 32/116 = 3.08

T(21,23) = .0120 -

E(21,f) = .912
1(44,£) = 2.73
K = E/T = .912/2.73 = 0.334

R3q = Fx Tx K = 3.08 x .0120 x .334 = 20123

- 124 -


Baseline rate —

the cancer experience observed in a population in the absence of the
specific agent being studied; the baseline rate might, however, include
cancers from a number of other causes, such as smoking, background
tadiation, etc. The Working Group has used data from the SEER program
(see this) as baseline rates for the present report.

BEIR III -
refers to the third National Academy of Sciences' Committee on ty
Biological Effects of Ionizing Radiation, as well as to the report ]
published by this committee in 1980; the 1972 BEIR L report was also
used by the Working Group. ”
Beta particle ~ , : ~
a charged particle emitted from the nucleus of certain unstable atomtc
nuclei (radioactive elements), having the charge (+ 1 or -1) and mags of
an electron.
Biologically equivalent dose (BED) ~
for a given dose and quality of radiation, and for a given cancer
site, the BED is the dose of 250 kVp X rays required to produce the
same increase in cancer risk.
Cancer -
a malignant tumor of potentially unlimited growth, capable of invading
surrounding tissue or spreading to other parts of the body by metastasis.
Carcinogen =
an agent that may cause cancer. Ionizing radiations are physical
carcinogens; there are also chemical and biologie carcinogens and
biologic carcinogens may be external (e.g., viruses) or internal
(genetic defects). .
Carcinoma —
a malignant tumor (cancer) of epithelial origin.
Case-control study — .
4
an epidemiological study in which people with disease are compared with ud
2 similarly composed group of people without disease and the histories

of exposures to a putative causative agent are compared.

Cohort study -
ot follow-up study; an epidemfological study in which groups of people
are identified with respect to the presence or absence of exposure to

a disease-causing agent and the outcomes in terms of disease rates are
compared.

- 346 -


10. Cancer of the Female Breast (174 in ICDA-8)

Risk estimates for radiation-induced cancer of the female breast are
the most secure for any site. The 1980 BEIR report was preceded by
publication of incidence data on the Life Span Study sample of Japanese
A-bomb survivors (70), former patients at Massachusetts tuberculosis
sanitorla who received substantial cumulative breast doses from multiple
fluoroscopic examinations (71), and women treated with X rays for acute
postpartum mastitis (72), The estimates in the 1980 BEIR report were
based on an analysis in parallel of data from these three sources (73,74).

A remarkable feature of the analysis in parallel was that similar
estimates of the absolute magnitude of risk were obtained from the three
samples for similar ages at exposure and lengths of follow-up, despite 3
to 5-fold differences in baseline risk between Japanese and US women
(75). A possible interpretation of this finding is that factors in the
American lifestyle responsible for the difference (American women of
Japanese descent have breast cancer rates approaching chose of other
American women) are additive with radiation in the causation of breast
cancer. The data also were highly consistent with proportionality between
radiation dose and excess risk, and with the constant relative risk model
for induction period.

Estimates for women exposed after age 40 were uncertain because the
two medical series contained few relevant data and the A-bomb survivor
data, which were consistent with little or no excess risk, suggested the
possibility that a radiation effect on ovarian function might have reduced
the risk of breast cancer among older women. Evidence for excess risk
among Swedish women treated with X rays for benign breast disease (76) at
ages above 40 seemed questionable because of the possibility that the
excess aight be attributable to the indication for treatment, e.g.,
chronic cystic mastitis, known to be a risk factor for breast cancer.

This uncertainty was resolved by the BEIR committee at the time by applying
ris« coefficients for exposures at ages 20-39 to those at older ages,

with the implicit understanding that this might overestimate risk from
exposure after age 40.

At the time of the 1980 BEIR report no persuasive evidence of excess
breast cancer risk in Women irradiated before about age 10 had been
presented, and while it seemed possible that an excess would appear when
the youngest A-bomb survivors reached ages at which breast cancer normally
reaches appreciable levels, it also seemed possible that lack of different-
iated breast target tissue might preclude a carcinogenic effect of radiation.
Further follow-up studies of A-bomb survivors (77,78) and American women
treated in infancy for supposedly enlarged thymus gland (79) have shown
that irradiation during early childhood does increase the risk of breast
cancer, that this risk does not appear until after about age 30, wher
breast cancer rates normally increase, and that the excess, when it does
appear, is comparable to that seen in women irradiated during their
teens, previously considered to be rhe ages of greatest sensitivity. The
two studies make it plain that the BEIR coefficient of 0 for women exposed
under ten years of age is inappropriate and should be replaced. Moreover,
the more recent study of A-bomb survivors (78) is based on a sufficiently
large experience at the older ages to provide adequate estimates for

- 242 =


Table X-t-1. Levkenias All Types Except CLL? Beseline
Incidence 1(a2,$) by Age ut Diagnosis 2z and Sex §

} ay Sex At Sex
Hale Fensie Kele Fewale

o 7.00 5.70 43 4.22 3.47
1 7.00 5.70 aa 4.82 3.70
. 2 7.00 5.70 45 4.87 3.97
3 6.65 5.4q 46 5.24 4.25
4 5.83 4.BO 4a? $.60 4.50
5 4.80 4.01 43 §.98 4,73
6 3,86 3.27 ao 6.38 4.95
7 3.30 2.80 50 6.80 5.56
. & 3.04 2.54 Bt 7-25 5.38
5 2.84 2.34 $2 7.71 5.40
10. 2.64 2.10 53 8.20 5.as
11 2.54 1.93 56 8.77 G15
12 2.50 4.80 55 9.47 6.54
13 2,53 1.668 5é 10.3 6.92
1G 2.58 1.86 $7 11.4 7.44
+S 2.65 1.66 58 12.7 7.97
16 2.69 4.40 59 14.0 6.60
17 2.70 1.60 60 18,3 9.29
18 2.63 1.46 st V6.7 10.0
19 2-49 1.68 62 18.0 10.7
20 2.34 1.52 63 19.2 1.5
21 2.25 1.56 6G 20.4 12.2
22 2-20 #.60 6s 21.6 13.0
23 2.29 1.64 66 22.9 13.8
24 2.45 1.68 67 24.2 14.6
25 2.64 1.72 68 26.2 15.5
26 2.80 1.76 6? 28.9 16.6
27 2.90 1.80 70 (32.3 17.7
28 2-93 1.84 cal 35.9 18.9
29 2.96 1.88 t2 39-6 20.2
30 2.94 1.93 v3 43.3 21.6
34 2.96 2.00 7 47. 23.3
32 3.50 2.10 2s 50.9 25.1
33 3.07 2.22 76 546.8 27.0
36 3.15 2.34 77 58.6 29.9
35 3.28 2.66 78 62.8 31.5
36 3.31 2.58 79 67.2 34.5
37 3.40 2.70 50 73.6 37.5
38 3.49 2.82 Bi 75.8 40.2
39 3.89 2.9q 82 79.4 42.4
4o 3.74 3.06 BS 82.1 43.5
41 3.86 3.18 8484.0 54.6
42 4-00 3.30 es 35.3 45.5

- 179 -



Table PC-9-C. Lung Cancer 19 or More Years After Exposure to
Low-lET Radiation, by Aga Ay at Exposure, Sex, and Dose
in Rad, for Former Smokers." PC in Percent, to Two Signi f=
feant Digits or Three Decimal Places

Ay Sex
Male Famsle
Dose

1 10 100 1 1g 100
10 -66 6.7 $5. «65 6.6 55.
Ww -$9 6.3 $3. 60 6.1 33.
42 .53 5.8 50. +55 3.6 50.
43 -47 4.9 47, +50 $5.1 48.
14 +42 4.3 44. +85 4.6 4S.
15 -37 3.8 4i. .$t 4.2 3.
16 33 3.4 38. «3? 3.9 4,
7 +29 3.8 35. 134 3.6 39.
18 +26 2.7 32. «32 3.3 3.
19 +23 2.5 3a. 129 3.3 35.
26 621 2.2 28. +27 2.8 33-
21 1 2.0 26. +25 2.6 32.
22 wd? 1.8 24. +23 2.5 30.
2s +16 1.7 23. 622 2.3 29.
24 215 1.8 2t. +20 2.2 2?
25 S53 1.4 . 19 2.0 26.
26 312 1.3 218 t.9 2s.
2? aft 1.2 17 1.8 24.
28 mt i. ~16 ti? 23.
23 -999 ed 4S 1.6 22.
39 +093 +99 18 3.6 2t.
3) . 037 93 wt@ 1.5 rans
32 .03f 87 14 1.4 20.
33 1077 +82 43 1.4 49,
36 072 7? 42 3 19,
35 068 173 $2 1.3 18,
36 2065 -70 22 1,3 18,
3? 062 165 12 1.3 18.
38 .059 63 12 1.2 18,
39 087 .f uM 1,2 7,
42 055 59 1 1.2 7.
41 +053 -37 1 1.2 17,
42 .0Sf 35 1 1.2 17.
43 -050 +53 W 1.2 17,
4% -048 -52 8.2 1t 17.
65 047 51 8.9 \t 17,
46 1046 +30 7.3 tt 17,
47 2045 43 7.7 VW 17.
68 045 48 7.6 v1 17,
49 20464 47 7.5 42 1.2 8.
53 2144 +47 7.5 12 1.3 48.

- 320 -

few!

te

aon


Table X-1-F.  deute Leukemia: Baseline Incigence 1(a;.8)
by Age at Diagnosis bz and Sex 5

aa Sex ay Sax
Mate Fearle Male Fonale
9 6,90 5.70 433.17 2.46
1 6.90 35.70 4% 3.47 2.73
2 6.99 5.70 45 3.79 3.05
3 6.55 5.63 56 4.18 3.36
4 5.72 4.76 ST 4.40 3.60
5 4.69 3.94 48 6.69 3.73
& 3.76 3.18 “4? 4.97 3.7
7 3.20 2.70 50 8.24 3.81
8 2.96 2.45 St 5.82 3.87
9 2,73 2.22 52 8.8t 4.00
1D 2,56 2.92 $3 6.10 4.24
1900 2.45 1.84 $4 6.44 4.45
120 2.40 41.70 55 6.87 4.76
13 2.44 4.57 56 7.45 5.14
14 2.45 1.43 $7 8.23 5.64
1S 2.50 1.32 5B 9.48 6.16
16 2.52 1.23 59 10.2 6.68
17 2.80 1.20 60 18.8 7.22
18 2.38 1.22 41 12,4 1.77
19) 2.19 1.27 6213.5 a.3t
201,99 1.33 $3 18.4 8.86
2t 0 4.84 1.38 64 "18,2 9.49
22 1.80 1.40 65 6. 9.95
Z23 1.84 $2.40 ry ee 40.5
24 $88 1.60 67 18.8 4.4
25° 4.92 1.40 68 20.2 189
26 1.96 1.40 69 22.7 12.9
27 2.00 1.40 70 25.5 14.4
282.04 1.40 71 | 28.6 15,3
29 2.08 4.40 720 34.5 16.5
302.12 1.41 73 34.6 47.6
Bi 2.46 1.44 74 37.2 18.9
$200 2.20 1.89 75 40.5 20.1
330 2.24 1.58 7 42.9 21.4
34 0 2.28 1.66 77 45.8 22.7
3500 2.32 1.746 76 48.6 26.6
36 2.36 1,82 79 51.4 26.9
37) 2.49 1.90 BD 54.4 29.4
3B 2.66 1.98 a1 56.7 31.5
39 2.49 2,06 82 59.2 32.7
40 2.56 2.1% BS 61.2 33.6
41 2.70 2.22 85 62.6 34.2
42 2.90 2.30 85 63.6 34.7

~ 168 -



2
z
i

i

3
+
5
3
2
5

3

F
:

3
>

5

1973-59

3 per 110,004 per Yeord,

Banaltna Cancer Incidence Rates (Ca

SEER

Age at Slagn

Table V-1,

Males

a
.
7
rd
€
4a
é

Age

aL teux BONE = -SALIV «ESOPH STOM = GOLOM LIVER PANCR LUNG BRST UREN THR

co.

coe ee HS SR SSR
eet Tere Sire be ied

Srengewone
MegseragSenaRsssee
Sassnen as

znanee

Cancer Site: Fenates

ab CEUk  BOME = SALIV) ESOPH «© STOM = COLGN LIVER PANCR LUNG Okst ouRtHoTHYR

cot

- 64

s
Arne Ne Keone
ee SNe d

nectssen
en tnanes ron

Seensé

nee
Reereernnnee tt

bade nei gcgen
Mire cdnneninn lanes

puddon

adedl


The uncertainty surrounding PC estimates is discussed in Chapter VII,
and Section VII-0 includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig X-10 has been drawn
for tissue doses of 1, 10, and 100 rad of low-LET radiation, and PC
values plotted by age at exposure and on the assumption chat the minimal
latent period has been satisfied. ‘The vertical scale is logarithmic and
curves are presented for only three radiation dose levels. For these and
other reasons interpolation is to be discouraged.

~ 246°-


Table PC-8 (Continved). Pancreas Cancer 10 or Hore Years
After Exposure to Low-LET Radiation, by Fe at Exposure,
Sax, and Dose in Rad. PC im Percent, wo Significant
Digits or Three Decimal Places.

Ay Sex
Male Female

Dose
t +e 109 $ 10 199
ét att Wt 16. 5 1.6 21.
62 ott t.t 17, 1S 1.6 Qt,
63 a3) 1.2 17, 215 1.6 22.
64 1 1.2 17. 15 1.6 22.
6s ft 1.2 17. +18 1.6 22.
66 aff 1.2 18. «16 1.7 22.
$7 Pars 1.2 18, +16 1.7 23.
63 12 1,3 18. 16 1,7 23.
6? 12 1.3 18. Pars 1.7 23.
70 12 13 48, 1 1.8 23.
7t «12 13 18. +17 1.8 24.
72 12 1.3 18. «17 1.8 24,
73 2 1.3 18. 1? 1.8 24.
74 Par 4.3 18. 17 1.8 24,
73 «12 1.3 18. 17 1.8 24.

- 315 -



Table PC-9-I. Lung Cancer, by Cumulative Exposura to to Radon
avohters, in WiM, and by Assumed Risk Factor,
Exposure 10 or More Years Before Diagnosis, bc fn

Percent.

WLM Assumed Percent Excess Risk per HLM
2.7 1.2 4.5
t 0.7 1.2 1.5
2 1.4 2.3 2.9
3 2.4 3.5 4.3
4 2.7 4.6 §.7
5 3.4 5.7 7.0
6 4.0 6.7 8.3
7 4.7 7.7 9.5
8 5.3 8.8 1t.
tf 3.9 9.7 12.
ta 6.5 it, t3.
1 7.4 2. 14,
12 7.7 13. 15.
43 8.3 13. 16,
14 8.9 14, 7.
15 9.5 15. 18,
16 tO. 16, 19
17 4, 7. 20,
18 qf, 18, 2t
19 12. 19, 22.
20 12. 19, 23.
25 15, 23. 27.
30 17, 26. 3t
35 2a. 30. 34
40 22. 32 38,
45 24. 35 40.

$0 26. 38.

60 30. 42. q7
70 33. 46. 54
30 36. 49. 55
99 39. 52. 57.
100 41, 55. 69
129 46. 59 64
149 49. 63 63
160 53. 66 71,
180 56. 68. 73
200 58. 71, 75
250 64. 75. 79.
300 68. 73. 82
350 7f. 81, 84,
400 74 83. 8&
$50 76 84. 87,
500 78 B86. 88.
600 &1, 88. 90
700 83. 89. 91.
800 85 91, 92,
900 86. 92. 93.
1990 3. $2. 34.

- 332 -

We.

Beat


go undetected for a long time unless special efforts have been made at
detection, as has been the case for A-bomb survivors and practically
every other trradiated group in which an excess has been demonstrated.
Thus the somewhat anomalous Finding of a continuing observation of an
excess among A-bomb survivors who were under 20 years old in 1945, and an
apparent disappearance of excess risk over time among older survivors
(24), could conceivably be an artifact of screening in which cancers that
might otherwise have been discovered in recent years had been picked up
earlter through improved surveillance.

Schematic representations of leukemia risk as a function of time
after exposure based on A-bomb survivor data resemble lognormal or gamma
distributions. These distributions, moreover, may differ by histological
type and age at exposure (47). Formal statistical comparisons of dates of
diagnosis among heavily exposed A-bowb survivors with chose among lightly
exposed survivors or non-exposed residents of Hiroshima and Nagasaki are
consistent with this interpretation (48).

Comparisons of response time distributions between cancers of the
breast, lung and stomach among heavily exposed persons and otherwise
similar persons with little or no exposure are remarkable for the simi-
larity they reveal (5,49,51). That is, heavily exposed persons have mote
cancers of the breast, lung, and stomach than they would otherwise have,
but the temporal distributions of the excess cancers are not distinguishable
from those of non-radiogenic cancers. This finding is plausible in terms
of a multi-stage model for carcinogenesis, in which radiation produces an
early-stage change that can also be produced by other common agents, and
in which late-stage changes are caused by events that are highly age-dependent.
If, in fact, the Likelihood of early-stage changes for these sites declines
with increasing age in about the same way that the relative risk of radiation-
induced cancer declines with increasing age at exposure, and if the likeli-
hood of late-stage changes increases with increasing age in about the same
way as population cancer rates increase with age, the observed temporal pat-
terns of radiation-induced and baseline cancer rates following a radiation
exposure should be very similar (52).

Congruence between radiation-induced and baseline cancer rates of
the same site, in persons of similar ages at observation, with respect to
temporal distribution of risk, is equivalent to the relative risk projection
model used by the BEIR IIL Committee. The relative risk projection model
asserts that, for a cohort of persons of given age, after the passage of
a necessary latent period, the relarive risk of radiation—-induced cancer
is essentially constant. It {s inconsistent with the absolute risk model,
according to which the relative Frequency of radiation~induced cancers
compared to baseline cancers should decline over time for those sites for
which baseline cancer rates inccease with age, and it is also inconsistent
with another model, proposed by Gofman (53), in which this relative
frequency is assumed to increase for about 40 years after exposure, and
then decline. The justification given by Gofman for this model is uncon-
vincing; the increase with time in relative risk that he noted depended
upon an analysis that ignored age; the increase was a consequence of
cohort effects, in which increasing numbers of younger (and more radiation-
sensitive) women entered upon the ages at which breast cancers occur.
The decrease in relative risk postulated by Gofman is entirely speculative.

-22-


Exposure 2:
F(2) = 2 + 22/116 = 2.03
1(23) =
K(20,£) = .00153

Ro =F x Tx K = 2.03 x 1 x .00153 = .00311

Exposure 3a;
F(3) = 3 + 32/116 = 3.08

23) = 1

a

K(21,£) +00143

R3q = Px Tx K = 3.08 x 1 x .00143 = .00440
Exposure 3b:

F(6) = 6 + 62/116 = 6.31

T(23) = 1

K(21,£) = 00143

Rap= F x Tx K = 6.31 x 1 x .00143 = .00902
Exposures 4, 5, and 6:

FCL.1 + 0.6 + 0.7) = F(2.4) = 2.4 + 2.42/116 = 2.45

T(9) = .926

K(35,£) = .000558

Raogs6 = Fx Tx K = 2.45 x .926 x .000558 = .00127

R= Ry + Ro + Ryq + R34 + R4r526 = -00155
+ 00311 + 00440 + .00902 + .00127 = .0194
PC = R/C1+R) = .0194/1.0194 = .0190 or 2%.
The uncertainty surrounding PC estimates {s discussed in Chapter VII,

and Section VII-0 includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig. X-6 has been drawn
for tissue doses of 10 and 100 rad of low-LET radiation, and PC values

- 214 -


wd
3

States; a different baseline rate may, however, apply to a parti~
cular individual, based on geography of residence. Table VII-1
shows, for each of the ten SEER areas, the age~adjusted incidence
rate for each cancer. Geometric standard deviations (¢.$.D.s) of
the rates have been calculated for each cancer for males and females
separately; they ranged from a low of 1.076 for acute leukemia in
males to a high of 1.636 for liver cancer in males. In general, the
G.S.D.s for particular cancers were of similar magnitude for males
and females. Upon pooling the G.S.D.s for cancers for which the
values were similar, the following values were obtained:

Geometric Standard Deviation
among SEER Registries

Kind of Cancer Sj
AL] leukemia except chronic 1.10
lymphatic

Acute or chronic granulocytic leukemia,
bone, breast, pancreas, colon and

kidney and bladder 1.17
Salivary glands, thyroid, lung and

stomach 1.36
Esophagus and liver 1.53

o Influence of Age at Exposure. Risk estimates have been
provided for only those ages at exposure for which adequate data
are available. From Table VI-1 it can be seen that for most
cancers excess risk per rad varies by a factor of about 4 as
between ages 20-34 and 50+. Exceptions are leukemia, liver,
breast and thyroid cancer. Taking account of the stepwise
nature of che age variations shown in Table VI-l, @ total un-
certainty of about 50 percent is suggested. If U and L are
estimated as 1.5 and 0.667 times the stated values, then U/L =
2.25, and the G.S.D. is calculated as Sq = 1.23.

o Time Response. As explained in Chapter V, a wave-
like, lognormal functional form has been used to express the
time course following exposure for radiation-induced leukemia
or bone cancer. For allt other cancers, following an initial
latent period, relative risks per rad are assumed to be constant.
It is unlikely that the time course for leukemia is in error by
more than about two years - that is, the peak year for chronic
granulocytic leukemia is estivated to be five years after
exposure; the body of data concerning human radiation leukemo—
genesis is sufficiently large and consistent that an error of
more than two years in the timing of that peak is most unlikely.
The temporal distribution curve following exposure (Table X-
1-4) shows that an error of two years in the placement of the
curve seldom changes the value of the curve by much more than
10 percent, and amounts to about 20 percent as between three

- 93 -


the distribution of excess risk over time should not follow the constant
relative risk model in both populations. Yet the evidence which suggests
that both models hold, or rather, that the two models are simultaneously
consistent with epidemiological experience, was obtained largely from
extensive follow-up data on breast cancer among Japanese atomic bomb
survivors and North American populations exposed to medical X ray (49,50).

The apparent contradiction in the case of breast cancer would appear
to have been resolved by Moolgavkar and Lee (87), who point out that pub-
lished age-specific population cancer rates of the type cited above
(e.g-, from reference 82) are based on relatively short observation
periods, and that rates for different ages at observation correspond to
different birth cohorts. Moreover, they offer evidence that, within
cohorts, the distribution of baseline breast cancer risk among Japanese
women follows a common pattern, similar to that seen in western societies,
but that the. overall level of risk, at similar ages at observation, varies
considerably by birth cohort. Breast cancer risk has steadily increased
in Japan, and women born within the last 50 years or so are at higher
risk than women born earlier. This trend is reflected in published
population rates, which show proportionally lower risks at older ages
because the women whose experience contributes to these rates are members
of cohorts whose overall breast cancer risk is low. In the United States,
on the other hand, breast cancer risk has been remarkably stable over at
least the past 30 years (88), and therefore published age-specific rates
are a better indication of the temporal distribution of baseline risk
within a birth cohort. It should be noted that the analyses of Japanese
atomic bomb survivor data, on which the inference of a constant relative
risk over time after exposure is largely based, involved comparisons of
cancer risk between heavily exposed and lightly exposed or nonexposed
members of the same birth cohorts (5,48,49,50).

The above discussion demonstrates that no contradiction exists
between the constant relative risk model for distribution in time and the
constant absolute risk model for projection of risk from one population
to another in the case of breast cancer. It does not demonstrate a
similar lack of contradiction for all other cancers to which the models
might be applied. In general, however, patterns of age-specific cancer
risk do not differ between Japan and the United States to the same extent
for such other cancers as they do for breast cancer (82), and it is there-
fore less likely for a contradiction between the two models to become
apparent. To the extent that risk variation by age in the United States
may reflect cohort effects, it would of course be preferable to apply the
constant relative risk model, if appropriate, to cohort~specific baseline
rates. That may be possible decades from now, when extensive cancer
incidence data have been accumulated over many years, but it fs not
practicable at the present time.

Overall, the evidence favors absolute, as opposed to proportional
transport of risk from one irradiated population to another. It should be
noted, however, that the choice of the absolute model is based on data
for only a few cancers and populations. For example, some population
differences in cancer risk conceivably might depend upon differential
exposure to an agent that interacts synergistically, or antagonistically,
with radiation, and in such cases, the absolute model would not hold. As

~ 29 -



»$)

Ralative Excess K(A

Lung Cancer:

by Exposure Age a) and Sex $

Table X-9-A

Sex

Famale

Mole

Female

Male

uAMooan
FF EI. DON ORV EM NH ONE OOK Te
PRARKROGRNOGIOOD# & HNN SE FADD ONO DORA
COE S een mee er
LEVeeocIdoCI CCV OOD BOD OE OC OOUNMECFOROS
SPOSSHAGOHTDEGCADVVGGORCOROOOSOSO00R

APN ON DNO- NOTIN AKNOK AMT
AN OMNMAINN000OO OOO OBER ERA

STAM Hen ODO - AMHR AMOK NMS NO
RR RR ER NNN ONAN MMM

37

- 240 -


Table PC-2-40. Bone and Joint Cancer Following Exposure at
Age 40, by Age A, at Diagnosia, Sex, and Dose in Rad of
Alpha Radiation.” PC in Percant, to Two Significant Digits
ar Threa Decimal Places.

a, Sax §
Male Fomaie
Dose

v 40 100 1 10 160
4 013 -13 .019 1.9
42 §.0 29. 5.4 8&5.
43 17. 67. 2%. 36.
44 24. 76. 3s. 98.
45 25. 77, 34. 98. TM
46 24, 76, 34, 98.
4? 22. 24. 32. 98.
4s 20. 71, 39. 98.
oF 18, 68. 28. 98.
50 15. 64. 27. 97.
51 13, 60. 24. 97.
52 1s, 56. 21. 96.
53 9.6 $3. 17. 9s.
5¢ gut 47. 14, 94,
55 6.8 42. 1s. 93.
56 5.7 38. 9.6 91.
3? 4.8 34. 7.3 a9.
58 4.2 So. $3.9 86
59 3.6 27. 4.8 84
$0 3.2 25. 4.0 at,
61 2.9 23. 3.3 7?.
$2 2.4 20. 2.7 76.
$3 2.0 7, 2.3 70.
64 1.6 44. 2.1 68.
65 1.3 42, 3.9 66.
66 15 9.7 1.8 6s.
67 88 at 1.5 6t.
&& 274 6.9 V3 57,
69 -62 5.¢ at $2.
70 +83 $.0 «90 48.
71 45. 4.3 +76 43.
72 38 3.7 +64 39.
73 ot 3.¢ +33 35.
74 +25 2.4 +45 3.
75 +20 2.0 +33 27.

- 301 -


A few examples should make it clear how the PC values are to be
obtained for individual cases:

Example t A non-smoking male, exposed to 5 rad of low-LET radfation to

the lung at age 20, with a diagnosis at age 50, otherwise typical of his

age-sex group with respect to the risk of lung cancer. Then D = 5, Ay =

20, Y = 30, and W = 6.81
F(D) = 5 + §2/116 = 5.22 i
T(Y) = T(30) = 1 -

K(A],8) = KC20,m) «00122

W = 6.81
then R= Fx Tx Kx W= 5.22 x 1 x .00122 x 6.81 = .0434
and PC = R/{1 + R) = .0434/1.0634 = .042 or 4%,

Example 2 A lung cancer was diagnosed at age 44 in a non-smoking woman
following several exposures to low-LET radiation at various ages. The
first, of one rad to che lung, occurred at age 20, 24 years and 2 months
before diagnosis (¥ = 24), The second, to 2 rad, occurred 4 months later,
at the same age (A; = 20) but 23 years and 10 months before diagnosis (¥
= 23). At age 21, 23 years and 3 months before diagnosis, a 9 rad total
dose was received over a 36-hour period at the continuous rate of 250
miliirad per hour (Y = 23). Finally, at age 35, three exposures, to 1.1,
0.6, and 0.7 rad, respectively, were received on consecutive days, 9%
years and 2 months prior to diagnosis (Y = 9). For a non-smoking female
W = 4.64,

The first, second, and third exposures should be considered separately,
because exposures 1 and 2 correspond to different values of Y, and ex-
posures 2 and 3 to different exposure ages. The 9-rad continuous exposure
delivered over 36 hours should be treated as 2 exposures because it re-
quired more than one day, but less than two. The partition giving the
maximum risk estimate assigns a 3-rad exposure to one 24-hour period and
6 rad to another. The three exposures at age 35 can be treated as one
because they correspond to the same values of Ay and Y, and because the
total dose is less than 5 rad.

Exposure 1:

F(D) = F(1) = 1 + 12/116 = 1.01 .
od

T(Y) = 1024) = 1

K(Az 8) = K(20,£) = .00230 4

Rp > Fx TxKx Wes 1,01 x 1 x .00230 x 4.64 = ,0108
Exposure 2:

F(2) = 2 + 22/116 = 2.03

= 236 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

4100

so

20

10

Fig X-1-c+8

LEUKEMIA: ALL TYPES EXCEPT CLL

EXPOSURE AGE 70

70

7$

a0

as so

AGE AT DIAGNOSIS

- 154 -

200 108

Hale ame
Female---


15. “The Oversight Committee recommends that the current assumptions
about the relationships between radiation and smoking be reviewed as new
information on both low- and high-LET exposures accumulates.”

The human data on the interaction between smoking and radiation
leave much to be desired and the Working Group can only endorse
this recommendation.

7 16. "The Oversight Committee recommends that the Working Group provide
4 sufficient further documentation of its approach to handling dose rate
for the calculations to be reproduced independently. Graphic displays
showing the distribution of dose over time may be useful.”

The handling of dose-rate effect has been discussed in
Chapter V, Section B. Spectfic examples are provided
in Chapter 1X, Example 5, and in examples for the
specific sites in Chapter X.

17. “The Oversight Committee recommends investigation of the possibility
of modeling the response to radiation to include a variable for dose
rate as well as dose, age at exposure, and age at diagnosis, with a
smooth variation in response to changes in any variable.”

The Oversight Committee's recommendation suggests that there is
some intrinsic advantage in using smooth models to analyze data
as opposed to smoothing estimates derived from partitioned data.
This seems debatable in the absence of theoretical models specifying
the dependence of risk on various factors used to define the par~
tition, Such models do exist for dose response, and the Working
Group's calculations and those of the BEIR Committee incorporate
them. Such models do not exist for the effect of age at exposure,
on the other hand, and it seems reasonable to base the method of
smoothing, if any is to be employed, at least partly on the way
in which risk is observed to vary with exposute age.

18. “The Oversight Committee recommends that the Working Group discuss in
detail the methods, data, assumptions, and calculations that need to be
made to estimate assigned shares for radiation as a cause of cancer.

Such a discussion would be useful to the users, as well as in the production
of improved versions of the tables.”

The Working Group believes that it has performed this necessary
task in a way that will aid in the use as well as the revision
of the tables,

19. “The Oversight Committee recommends that, before the Working Group
i disbands, it document completely the derivation of the factors used in
the calculation of an assigned share.”

The Working Group believes that it has provided adequate
documentation.

20. “The Oversight Committee recommends that a well-documented set of
computer programs be developed to facilitate both tabulation of the

- 343 -



Table PC-t-€-0. Leukemia Excluding CLL Following Exposure
at Age 0, by Age A, at Diagnosis, Sex, and Dose in Rad
of Low-LET Radiatién. PC tn Percent, to Two Significant
Digits or Three Decimal Places.

ay Sex
Male Famale
Dose

t 10 CT) 7 70 190
z 2.4 19, 8a. 1.6 13. 76.
3 8.5 $0. 94. 6.7 4. 93.
4 2, 53. 96. 9.5 33. 95.
$ 14, 63. 9?. Mt, $6. 36.
6 16, 65. 97. it. $8. 6.
7 14, 64. 97. it, 57. $6.
& 13, 62. 97. 10, 35. 35.
9 12. $9. 96, 9.5 53. $s.
19 1. 56. 96. 8.8 $t. 95.
11 9.5 53. $$. Bul 49. oo.
12 8.3 49. 94. 7.4 46. 34.
13 7A 45. 93. 6.8 44. $3
14 6.0 “tf. 92. 6.3 42. 33
13 3.1 37. 9. 5.9 49, $2.
16 4.4 33. 9a. $.4 38. 41
7 3.9 3o. 88. 4.7 38. 90.
18 3.8 28. a7, 4.1 32. a3
19 3.3 27. 8s. 3.6 28. 87
20 3-2 26. a6. 3.1 26. 8s.
2t 3.0 2s. &5. 2.7 23. Bs
22 2.7 23. a4. 2.4 21. ge
23 2.4 21. g2. 2.1 19, $8.
2¢ 2.5 18. 79, 1.9 7. 78.
25 1.7 16, 7?. 1.7 16. 76.
26 1.5 14, 74. 1.5 14. 74,
27 1.4 13. 72. 1.6 13, 72.
28 1.2 12. 70. 1.3 12. 79.
23 1,1 M1, 68. Vt 19, 68.
30 tt 19 67. 1.6 19. 66.
31 +99 9.7 é$. .93 9.2 63.
32 98 9.9 63. 83 8.3 6,
33 +83 a.3 61, 74 58.
34 225 7.6 59. 66 35.
35 +70 7.8 57. 59 Se.

- 289 -



CHAPTER Vi DATA SOURCES, ASSUMPTIONS , AND MODELS
Ay Data Sources

The calculation of probabilities of causation for radiogenic cancers
requires baseline data for individual cancers and parallel quantitative
visk estimates for cancer arising from exposure to fonizing radiation.
Although the bulk of the data on the risk of cancer is in the form of
mortality rates, in the late 1930s the National Cancer Institute began
periodic surveys of cancer incidence and survival. As the Surveillance,
Epidemiology, and End Results (SEER) program, this effort, covering about
10 percent of the U.S population, now provides systematic, national
incidence data for the period beginning with 1973 that are unequivocally
the best source of data on cancer incidence for the U.S. Data for 1973-77
are published (1); the Working Group has had access to the unpublished
tabulations through 1981 (Table V-1). Site-specific baseline incidence
data by age and sex have been used here as the basis For PC calculations
without regard to ethnic or geographic sources of variation that often
are considerable. .PC estimates are necessarily sensitive to the baseline
incidence used in the calculation of relative excess risk, and choices
must be made whenever incidence is known to vary with characteristics of
individuals for whom such estimates are required. Although the SEER data
extend to geographic and ethnic variation, there is some uncertainty
about the statistical stability of much of this variation, and the extent
to which it may reflect the influences of factors whose interaction with
radiation in the causation of cancer is simply unknown. With the single
exception of smoking related to lung cancer, the methods and calculations
presented here are appropriate to “average” Americans whose baseline risk
levels are represented by the combined SEER registries.

The use of a single set of rates also takes no account of changes in
population incidence over time, but these have been considerable only for
stomach cancer and lung cancer.

The PC calculations have been limited to sites and types of cancer
for which radiation is know to be a cause and for which reasonable data
exist for purposes of calculation. (See chapters VII and X for further
discussion). Site-specific estimates of radiation-induced cancer risk in
terms of incidence have been taken from Tables V-14 and V-l6 of the 1980
BEIR report (2) with updating for several sites and with deletions appro
priate to the calculation of PC values (Table V-2). The BEIR report is
the only comprehensive source of human, site-specific incidence data
velating radiation exposure to cancer risk and the time constraints
placed upon the Working Group have precluded any systematic reworking of
the relevant literature, much less the original data upon which it is
based.

The A-bomb survivor data for leukemia (3) were subdivided by type to
develop separate sets of risk estimates for acute leukemia and chronic
granulocytic leukemfa. The BEIR leukemia coefficients themselves were
modified to achieve a more stable, and plausible, dependence of risk on
age at exposure (see Section ), below). The lung cancer coefficients
were revised on the basis of new data from the A-bomb survivor series (4)
(see Chapter X-9). Recent reports of thyroid cancer and breast cancer

- 54 -

tual,


although there is very little published thyroid cancer information with
which to test this assumption.

The PC estimates calculated for thyroid cancer pertain to external X
and gamma irradiation, not to the radioisotopes of fodine. Although
lodine-131 is chought to be the major source of irradiation of thyroid
tissues in individuals exposed to fallout from the weapons tests, the
existing humap-data are not of sufficient cogency to provide a direct
basis for quantitative estimates of riks; furthermore, there is contro- !
versy over the biological effectiveness of fodine-131 beta radiation a
relative to X rays and gamma rays. An Ad Hoc Working Group on Thyroid/
Iodine Assessment, also mandated by the Orphan Drug Act (Public Law

97-414, Section 7a) is currently reviewing the available data and research
needs in this area.

It is the SEER data on the incidence of thyroid cancer for all repor=
ting areas combined except Puerto Rico, and all races combined, for the
period 1973-1981, that is the source of the normal incidence rates employed
here (8). For thyroid cancer known risk factors are neither numerous nor
influential (92); chere 1s, however, some variation in the SEER tables:
for individual reporting areas (see Tables VII-l and VII-2).

For thyroid cancer the relative excess, R, in the basic equation
PC = R/(1 + R}
is found as the product of three functions, t.e.,
R= F(D) x T(Y) x K(A),S)
where F(D) represents the influence of Che low-LET tissue dose (D), TCY)
represents variation in R over rime in years (Y) after exposure, and K(A;,5)
represents the relative excess thyroid cancer per rad for a person of sex §
and age at exposure Ai, when both F and T = 1.
Under the linear model assumed for thyroid cancer, F = D where D is
the low-LET tissue dose in rad. For the thyrotd the influence of time
(T) on relative risk depends only on years from exposure to diagnosis
(Y). The simple function T, the latency factor, 1s tabled below:
Y 0-4 5) 6 7 8 9 10+
T 0 2075 +259 +500 2741 2926 1.
The standardized relative risk of excess thyroid cancer, K, is given

in the accompanying Table X-12 for each sex and individual year of age
(completed years) from birth to 75. .

A few examples should make it clear how the PC values are to be obtained.

Example | A female, aged 10 when exposed to 5 rad of low-LET radiation to
thyroid tissue, with diagnosis 9.9 years later, and assumed to be typical of
her age and sex with Tespect to the normal risk of thyroid cancer. That is,
D=5, Ay = 10, and Y= 9.

~ 256 +


Teble X-2-C.

Bone and Joint Cancer

Ttai.5) by Age at Diagnosis &; and Sex 5

Baseline Incidence

ad Sex ad Sex
Kale Feaale Mele
o 100 100 43 +337
1 2108 100 aa 379
2 100 -109 4s #424
3 108 118 46 +465
4 2186 165 47 +500
5 178 +234 as «S10
6 +238 +315 “9 ~493
7 +300 «60D be 471
& 434 +528 31 467
9 1 6G6 a?1G 52 +501
1 +856 96 53 561
st 1.43 1.09 54 +625
42 4.30 1.20 55 +631
1s t645 1.26 5é 74d
14 1.69 1.25 5? +801
45 1.54 1.22 se 861
16 1-86 147 5g 2921
17 1.80 1.10 40 98d
18 1.40 1.05 i 1.16 1.04
19 1.27 +895 $2 1.20 1310
20 4.12 781 e3 1.29 1642
cal +987 «677 +6 1.39 1.09
22 +900 +€00 65 1.50 1.03
23 +845 +553 66 1.61 P91
26 +798 94 6? 1,71 1.00
2s +783 -&53 68 1.79 1.08
26 +720 1424 69 1.87 1.tf
27 .70¢ +400 7 1.98 1.47
28 696 392 cal 2.03 1.26
29 +703 1396 2 2.41 1.30
30 1713 404 73 2.28 1.38
at .715 408 m4 2.54 1.46
se +700 +400 7s 2-83 4.55
33 +667 +36F 76 3,07 1.63
34 +627 +358 77 3.24 1.71
35 +582 «263 78 3,07 1.72
36 +538 1216 v9 2.71 1.68
37 +500 +200 80 2,29 1.62
38 +465 +205 B1 1.597 1.59
39 434 -220 82 1495 1.61
40 1409 +262 83 2.00 1474
at +396 +269 84 2.15 1.95
42 +400 300 as 2.34 2.24

- 193



Table PC-t-C=30. Leukemia Excluding ¢tL Following Exposure
at Age 30, by Age A, at Diagnosis, Sex, and Dosa in Rad
of Low-LET Radiation. PC in Percent, to Two Significant
Digits or Three Decimal Places.

AL Sex
Mala Female
Dose d
1 10 106 q 10 100
32 47 4.38 48, 43 4.4 44, .
33 1.7 16. 76. 1.$ 14, 74
34 2.8 23. 34. 2.4 21. 82.
35 3.4 28. ar. 2.3 24, 85.
36 3.8 3o. 88. Pal 26. 86.
37 3.8 30. as. 3.1 26. 85.
38 3.7 29. as. 3.0 25. 35.
34 3.5 28. a7. 2.8 . a4,
40 3.2 26, 6. 2.5 22. a3.
41 2.9 25. 85. 2.3 20. ai,
42 2.6 23. 83. 2.t 18, ao.
43 2.3 20, 82. 1.8 17, 77.
44 2.0 18. 793, 1.6 15. 75.
45 1.7 16, 77. 1.4 13, 72.
4$ 1,5 14. 74. 1.2 Me $9.
47 1.3 $2. ran (a 10. 46.
43 1.4 1h. 67, 90 3. 63.
49 96 9.5 64. 79 7.9 60.
50 -83 8.3 &i. 79 7.1 57. -
31 22 7.3 $7. $2 6.3 54.
52 +3 §.4 $4. 55 $3.6 51,
53 4 5.6 5a. 43 5.0 47,
$4 +47 4.8 47, -43 4.4 46,
55 40 4.2 43 «38 3.3 qt.
56 «34 3.6 39 33 3.4 33.
s? +23 3.0 35. +28 3.0 34,
38 24 2.5 3. 25 2.6 3.
53 +20 2.1 27. .2t 2.2 28.
49 -17 V8 24. 18 1.9 25.
$1 +15 4.6 2i. 216 1.7 23-
&2 -13 1,4 19, may 1.5 20.
$3 o1f 1.2 17. 742 1.3 13,
8S ~099 td 15, Pan 1t 16.
6s +037 +93 14. Q93 99 5. .

~ 292 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

30

20

10

Fig X-1-A-8

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 70

7s to as 90 9s 1co 105,

AGE AT DIAGNOSIS Hale —

- 138 -


The above considerations do not apply to high-LET radiation, for
which close spacing of the ionizing events along the radiation tracks is
the rule, rather than the exception. Both theoretical and experimental
studies suggest that, for high-LET radiation, the dose-response tends to be
linear but is modified by negativé curvature, mainly at high dose levels,
due to cell inactivation. The data also indicate that fractionated or
protracted exposures to high-LET radiation tend to be no less effective
than acute exposures for the induction of stochastic effects (4).

Data on laboratory animals can provide principles to guide extra-
polation from effects at high radiation doses to predict effects at low
doses. For measuring small effects, however, such large numbe’ + of animals
are required that no experiment has been performed on a scate that suffices
to define the dose-incidence relationship for carcinogenesis in different
organs at doses below 10 rad. Furthermore, in most species of laborator.
animals that are convenient to use (mice, rats), the “natural” incidence
of cancers differs markedly among strains, as do the shapes and slopes of
the dose-incidence curves for radiation-induced cancers (6). In some
strains of mice, for example, breast cancers occuT spontaneously in nearly
100% of females, whereas the incidence is 1% or less in the females of
other strains; the effects of radiation on the incidence of such cancers
vary similarly. These differences among strains appear to depend on
genetic variations which are magnified by the highly inbred character of
laboratory mice. Because of the highly outbred character of the human
population--in which the incidence of cancer appears to be influenced
more by differences in the environuent, diet, and lifestyle than by gv
etic factors--animal-to-human extrapolations are fraught with uncertai::+.
Por this reason, quantitative risk estimates for man have generally reli
primarily on human epidemiological data (4,6)+

Epidemiological data are not very informative about the choice of a
dose-response model, for the same reasons that low-dose data tend not te
be informative about excess risk (71). This is true even when the possi-
bility of high-dose cell inactivation is ignored. The two cancer sites for
which linearity with low-LET radiation is strongly suggested, the thyroid
and the female breast, are in fact the only two for which there is much
direct evidence for an excess risk from external exposures under 50 raj
(24,72,73). Por other cancers, including leukemia, dose-response an: «ses
using general models, in which details of curvature are not fixed i-
advance, tend to yield risk estimates with very wide confidence lim. .
Also, less general models with specified curvature, which may be loci.’ ed
anywhere in the range from linear to pure quadratic, tend to fit the
available data more or less equally but produce a great variation in the
estimated risk at low dose levels (4,71).

The related phenomena of variable increases in risk per rad depen-
ding on dose or dose rate can be handled crudely by the use of a dose-rate
reduction factor, according to which the effectiveness of a high rasiation
dose delivered at a low dose rate or in many fractions is assumed to be
several times smaller than that of the same dose delivered acutely. A
more refined method uses a linear-quadratic dose-response model in which
the quadratic coefficient is assumed to depend on dose rate - that is,
the model as given corresponds to acute exposures and the quadratic co~
efficient is reduced for protracted exposures. Various official bodies

=~ 25 -



of a single exposure to Dy + D2 rad, which is proportional to (Dy + D2) +

(Dy + D))°/116. Thus for low-LET radiation there is a reduction in effect
for fractionation and protraction of exposure, for all cancers except those
of the thyroid gland and the female breast.

In practice, the reduction in effect due to fractionation of exposure
in the above example is slight unless the sum of Dy and Do is greater than
5 rad or so. (Jf D, + Dy is Igss than 5 rad, then (D, + Dy) + (Dy + D9)7/116
exceeds Dy + D, /1}6 + Dy + Do /116 by 2% or less.) hecordingly, for cancer
sites for which the linear-quadratic model is appropriate, the Working Group
suggests the following approach for calculating PCs for low-LET exposures
separated in time or protracted over time: Generally, exposures occurring
within a few months of each other can be combined (i-e., treated as a single
exposure, with dose equal to the sum of the separate doses), provided that
the sum of their doses is less than 5 rad. Consecutive acute exposures
should not be combined if the total.combined dose is greater than 5 rad.
For protracted exposures, accumulations of 5 rad or less need not be
subdivided unless the exposure extended over more than one year. Indepen-
dence of effect cannot be assumed for exposures separated by less than 24
hours or so. In the absence of a detailed and reliable model, the Working
Group recommends that cumulative exposures of 5 rad or more within a period
of 24 hours or less be treated as if from,a single acute exposure. This
rule may result in the overestimation of the effects of exposures separated
by a few hours. For very low dose rates the above approach gives results
that are virtually the same (within 4%) as would be obtained if the quadratic
(dose~squared) term were ignored. For a detailed example, see Chapter TX,
Example 5. Also, see site-specific examples in Chapter X-

C. Time after Exposure

Clearly, time is required for a single transformed cell to develop
into a clinically detectable cancer, and for that reason alone, a cancer
detected within a few weeks or months after a particular radiation exposure
would not be considered a possible consequence of that exposure» More
generally, assumptions about the distribution of excess risk over time
following exposure can strongly influence the PC calculations. There are
two issues: how long does it take before there is a non-negligible
excess risk, and how does the risk vary over time subsequently?

The BEIR 1II Committee used a plateau model for leukemia and bone
cancer and both a constant absolute risk projection model and a constant
relative risk projection model for other cancers, in order to extend
their estimates of average excess risk, obtained from follow-up periods
of 30 years or so, to estimated lifetime cancer risks. The Working Group
faced a much more difficult problem, for two reasons: First, a PC calicul-
ation pertains to a specific cancer diagnosis at a particular time following
one or more exposures to radiation, and not to risk averaged over a life-
time. Second, the charge to the Working Group was to provide a single
“best” estimate and not an array of more or less plausible ones. Thus it
was necessary to use specific time-to-response models which could, however,
depend upon cancer site and upon individual characteristics such as age
at exposure, sex, and radiation dose. Fortunately, research subsequent
to the 1980 BEIR report, made possible mainly by the increased duration

- $7 -


2. Cancer of Bones and Joints (170 in ICDA~8)

Bone cancer is relatively uncommon and radiogenic bone cancer has
been seen mainly in association with internally deposited isotopes of
radium, especially in radium-dial painters exposed to long-lived radiLum-226
and -228 (10), and in German patients treated with short-lived radium-224
for tuberculosis and ankylosing spondylitis (1!}. Radiogenic bone cancer
has also been reported following high doses of X rays (4), especially
among ankylosing spondylitis patients. It has not been seen in the
A-bomb survivors (4).

For the BEIR {Ii report, risk coefficients were first calculated for
repeated acute exposures to radium-224 and the “provisional” Low“LET co-
effictents, as they are termed in the BEIR report, were derived from then
through the use of the ICRP quality factor of 20 for alpha particles.
Tables were prepared for leukemta plus bone cancer and not for each
separately. This was done because the temporal distribution of excess
bone cancer is rather like that for leukemia: the latent period is
short, four years or less, and the total period of expression, perhaps
20-25 years.

Since the only human data on the risk of bone cancer following ex-
posure to low-LET radiation pertain to therapevtic levels of dose, the
Working Group decided that it should not make PC estimates for bone
cancer resulting from low-LET radiation but should confine its calcula-
tions to the alpha radiation on which the BEIR estimates rest. The BEIR
TII linear estimate, based on the radium-224 experience, is one excess
bone cancer per wiliion persons per year per rad of alpha radiation to
endosteal tissue (4), Hence Table X-2-B will not be used for the purpose
of PC estimation for exposure to low~LET tadiation, or to greatly protracted
high-L&T radiation from, e.g., radium-226.

The BEIR report provides little basis for a choice for either the
dose-response or the time-response model. -The linear function is assumed
for high-LET radiation, but more for consistency with experimental results
for tumors generally rather than because of the empirical evidence on the
induction of bone cancer in man following exposure to radium-224. For
alpha particles from radium-224 the BEIR risk coefficient of L per million
persons per year per rad of endosteal dose is a fairly stable linear
estimate, being based on 54 cases vs. an expectation of only 0.2 cases
(11). Information on variation with age is only fair, but the indications
are that younger patients experienced a risk very little higher chan that
of adult patients, and no sex differential was observed {4}. The lowesr
doses at which excess cases have been observed in the radium-224 series
are above 50 rad of alpha radiation to the endosteum, so that the applica-
bility of the data to lower doses remains uncertain. The best PC estimates
would be those for doses of radium-224 alpha radiation within the observed
range, average skeletal doses being mostly above 90 rad. !

The BEIR committee employed a constant absolute risk (plateau) for
bone cancer in combining it with leukemia, with no dose threshold, but
the Working Group has used a wave function, as it has for leukemia, and
for this assumption there is good recent evidence (12). Published data
from the German radium-224 series were used to fit a lognormal induction

~ 180 =~



Table PC-1-B-79. Acute Leukemia Following Exposure at Age 70,

by Age A, at Olagnesis, Sex, and Desa in Rad af Low-LeT
Radiatiod. PC in Percents to Tue Significant Digits or
Thres Decimal Places,

ay Sex
Male Female

Dese
T 0 To 1 10 100
g 900 +060 «900 «006 -00
a -000 «O13 +000 +000 O01
] 008 35 +000 008 +16
3 2942 72 -403 «040 69
2 213 2.1 2011 ~t2 2.0
4 ~28 &.6 02s .27 4.4
3 $2 8.2 +045 +49 7.8
8 -85 13. -073 +78 12.
1.3 1B. aa 1,8 16.
1.8 24. +14 1.5 at.
2.4 23. NG 2.9 26.
3.0 35. +25 2.6 32.
3.8 40. +32 3.3 32.
4.6 45. +39 4.1 42.
5.6 $e. 48 4.9 47,
6.6 $5. «5? 3.8 Si.
. 7.7 59, «67 6.8 $5.
: 3.8 62. .78 7.8 59.
90 1.0 9.9 65. 89 8.8 62.
91 wd th. 68. 1.0 3.8 6s.
92 1,3 12, 7. tii mW, $8.
93 +64 13. 73. 1.2 12, 70.
94 1.6 15. 74, 1,4 13. 72.
35 1.7 te. 76. .$ 44, 74.
96 1.8 17. 73. 1.6 1S. 75.
9? 2.8 1a." TF. 1,7 16, 77.
93 Q.1 19, $6. 19 WW, 78,
99 2.3 29. 81 2.0 18. 79.
199 2.4 ran &2 2.1 19, go.
108 2.5 22 83. 2.2 29. 8,
192 2.7 23 a4, 2.4 2!. 82,
103 2.8 24 a4. 2.5 22. Be.
104 3.0 25 &5. 2.6 22. 83.
105 3.4 2¢ 5. 2.7 23. 4.

- 288 -

r=

igen


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

160

so

20

ic

Fig X-2-4

BONE AND JOINT CANCERTM*
EXPOSURE AGE 30

30 40 48 $0

AGE AT DIAGNOSIS Male ———
Female---

*Alpha radiation from radium-224 only

~ 186 -



Table PC-2-19. Bone and Joint Cancer Following Exposure at
Ace 10, by Age A, at Diagnosis, Sex, and Dose in Rad of
Alpha Radiation. * PC in Percent, to Two Significant Digits
or Theres Decimal Places.

Ay Sex
Male Famale

Dose i

’ 10 1G0 T 319 108 -

q

1 204 047 004 049 49 :
12 1.3 12. 1.5 3. 60.
13 6.3 40. m4 43. 88.
14 Ww. 54. 13. 59. 93.
15 13 60, 16. 65. 35.
16 4 61. 17. 68. $5.
17 ts 61. 48. 69. 96.
18 14 61. 18. 69. 96.
19 16. 61, 1%. 69. 96.
28 16. &t, 19. 70. 96.
21 14. 61, 19, Te. 96.
22 13, 60. : 19. $9, 96.
23 12. 58. : 43. 68. 96.
26 ae 56. : 17. 67. 98.
25 10. 54. : 16. 66. 95.
26 9.4 $1. : 15. 64. 95.
27 a. 48. : 16. 62. 34.
28 7.4 45. : 43, $3. 93.
29 6.4 41. a7. 11, 55. 92.
30 3.5 37. 35. 9.4 : a,
3t 4.8 4s. 84. 8.2 90
32 4.3 31, 32. 7.4 89,
33 4.9 29. 40. 7.0 38.
34 3.7 28. 79. 7.0 88.
35 3.5 26. 78. 7.4 33.
35 3.3 25. 77. 7.8 83.
37 3.4 24. 76. 7.5 ag.
38 3.0 23. 78. 6.5 a7,
39 2.8 22. 74, 5.4 as.
49 2.6 21, 73. 4.4 az.
41 2.4 20, 7A, 3.5 78,
42 2.1 18. 6a. 2.8 74,
43 1.7 15, $3. 2.2 74.
44 1.3 1. 58. 1.8 64.
45 +94 8.6 43. 14 39.

- 298 -


and five years after exposure. The G.$-D. can be estimated,
then, to be no more than 1.10.

With respect to the solid cancers, the Working Group has
adopted the constant relative risk time projection model.
Available data indicate that this model is at least an excel-
lene first approximation; there may, however, be some variation
with time in the relative risk, especially for persons young at
the time of exposure, and after fatervals of twenty-five to
thirty years. Such uncertainty is assessed to be no more than
a factor of about 1.3; the G.S.D. is estimated as 1.15.

o Ratio of the Linear Coeffictents in the Linear (L) and
Linear-Quadratic (LQ) Dose-Response Models.
4s explained in Chapter V, the 1980 BEIR regtession analyses of
mortality from all forms of cancer except leukemia yielded co-
efficients in the ratio of 2.5. That is,

EL/ELQ = 2656

This ratio depended on the assumed crossover dose of 116 rad,
an estimate derived from the data on mortality from leukemia.
Had a different cross-over value been selected, a different
ratio would have resulted. The ratio depends on the cross-over
dose, C, as follows:

EL/Eyg = 1 + 174/¢.
The consequences of assuming that C is as small as 33 rad, or as

large as infinity, in alternative fits to the original data of
the BEIR Committee, are shown below:

Cross-over Value Ratio EL/ELQ

(red)

33 . 6.3

50 4.5

75 3.3

116 2.5

200 1.9
Infinity 1.0

The formula for the “effective” dose is D + D2/c and thus
effective dose varies little with the value C if the dose is less
than 5 rad, but uncertainty in che linear term, 2.5, illustrated
above, strongly affects the PC.

ft fs thought that the true value of the cross-over dose

~ 94 -


Table X-t-C. Chronic 6r
Incidence I(A2.5) by &

locytic Levkemio? Baseline
at Diagnosis d: and Sex S

at Sex At Sex
Hele Fewale Male Feazle
© .t00 +0590 34,82 +.04
+. 400 +9500 4 4616 2969
2.100 0500 45 4.56 1958
3.00 10562 46488 +885
4.100 +0645 47 4.20 ~900
S  .100 oO777 SB 1.626 +983
6.400 +9906 49 1,37 teat
2? .190 2100 50 4.53 1.26
. 8.500 +303 544.7 1.49
%  .100 +102 52 4.90 4.50
10.100 +9986 B53 2.50 1.57
14.00 10968 54° 2.31 $.62
12.180 100 55 2.53 3.67
13.586 2188 56 2.76 4.73
14 4123 1134 57 3.01 1.80
15 147 +158 5B 3.28 1.99
16 1174 «BZ 59 3.56 2.01
17.200 +200 60 38S 2.13
18.225 +202 61 4.16 2.26
19 26S +190 62 4641 2.40
20.307 «178 63 4.66 2.57
21 +17? 44 4.87 2.78
22 +200 65 5.08 3.00
23 .240 66 5429 3.21
26892 -280 67 «5.52 3.41
25 719 +320 6b 5.82 3.47
26 ABE +360 69 6.24 3.39
27.900 +400 70 6.47 3.30
280.940 +440 TY PND 3.34
29° A78 +680 720 (7.97 3.52
3D. B32 +520 75 8.48 3B.et
34. 297 560 74 9.346 6.37
3e «800 +600 75 40.3 4.87
33.838 +640 764443 5.44
34. 884 +680 7? 12.4 5.95
2S 934 +720 7B 13.8 6.51
36.972 760 79 18.7 7.40
371.00 +800 ep 17.4 7.68
3H 1.02 +840 Bi 18.6 8.25
. 391,06 -880 62 19.6 8.78
40 1.06 +920 83 19.0 9.28
411.08 960 BG 49.0 9.74
42 1.10 4.00 B5 19.9 10.5

~ 157 -


CHAPTER VIII — FUTURE REVISION OF THE TABLES

The tables cannot now provide precise measures of the probability
that certain cancers have resulted from previous exposures to known
doses of ionizing radiation. The tables represent, however, a first
and important step in the direction of a rational basis for assigning to
rad{ation exposure a measure of the likelihood of its role in the causation
of individual cancers.

The PC tables will have to be revised periodically as new information
and new insights become available. The Orphan Drug Act provides a criterion
for the frequency of revision: every 4 years or whenever the Secretary of
Health and Human Services “deems it necessary to ensure that they continue
to represent the best available scientific data and expertise.” The
United Nations Scientific Committee on the Effects of Atomic Radiation
CUNSCEAR) has in preparation another of its periodic reports that is
scheduled to include a section on carcinogenesis, the last such section
having been published in the 1977 report. The National Academy of Sciences
is forming a new committee that will first study the effects of high-LET
radiation and then move on to low-LET radiation. In perhaps two years
the revision of the dosimetry of the Japanese A-bowb survivors may have
begun to yield revised risk estimates based on that experience. The BEIR
III report was based on the world literature as it existed in 1979, and
the mortality data on the A-bomb survivors at that time had been reported
only through 1974. Their mortality through 1978 has now been reported
and within a year or two there should be an update through 1982. These
several efforts, at least, ought to be completed before any overall
revision of the tables would seem useful, unless the effort to revise the
tables were to duplicate those efforts.

On the other hand, it would be well to keep in mind the possibility
that some portion of the data on which this first version of the tables
rests may become obsolete before a general revision is indicated. In
that event, a supplement might well be issued with respect to a particular
site for which greatly improved estimates could be provided, or for a site
excluded from the present report. Or, perhaps as a result of the initial
deliberations of the new NAS Committee, it may be evident that estimates
could be made for certain exposures to high=LET radiation, Another possible
candidate for a supplement is a revision of the material on thyroid cancer
to include the effects of exposure to internally deposited iodine-131 for
which the Working Group concluded that PC estimates could not be made at
this time. Section 7a of the Orphan Drug Act also provided for a study
of the effect of iodine-13] on the likelihood of thyroid cancer, and an
Ad Hoe Working Group on Thyroid/Iodine-131 Assessments has been formed to
address this task.

The BEIR Ii report was not created with the needs of the radioepi-
demiologic tables in view and the Working Group has found that some of
the factors developed in that report to enable estimates to be made for
the effect of continuous exposure of the entire population from birth to
the end of life lack the reliability needed for the present purpose (cf
Chapter VII). The BEIR Report also provided no systematic basis for
estimating the effects of exposure to internal emitters, a difficult
subject at best and one for which few data adequate for PC estimation

- 116 -



Table x-9-8
W, The Factor Used To Adjust Average
Poputation Incidence for Smoking kistory

Smoking Category W

Males Females

Total 1.00 4.00
Nonsmokers 6.81 4.64
Former smokers 1.71 1.17
Present cigarette smokers, a11 0.604 0.412
under 10/day 1.75 1.19
10 - 20/day . 0.707 0.482
21 - 39/day 0.408 0.278
80 +/day 0.287 0.196

- 241 -



4

,
i

55.

56.

57.

58.

59.

60.

6l.

62.

63.

64.

65.

66.

67.

68.

NCRP Report No. 64. “Influence of Dose and its Distribution in
Time on Dose-response Relationships for Low-LET Radiations.”
National Council on Radiation Protection and Measurements,
Washington, D.C., 1980.

Whittemore, A- and Keller, J. B-, Quantitative Theories of
Carcinogenesis. SIAM (Soc. Ind. Appl. Math.) Rev. 20: 1-30 (1978).

Brown, C. C., Fears, T. R., Gail, M. H. et al., Models for Carcino-
genic Risk Assessment. Science 202: 1105-1109 (1978).

Crump, K. S-, Dose Response Problems in Carcinogenesis. Biometrics
35: 157-167 (1979).

Interagency Regulatory Liaison Group, Scientific Bases for Iden fi-
cation of Potential Carcinogens and Estimation of Risks. J. Natis
Cancer. Inst. 63: 241-268 (1979).

Pialkow, P, J., Clonal Origin and Stem Cell Evolution of Suman
Tumors. In: "Progress in Cancer Research and Therapy”, Vol. 3:
“Genetics of Human Cancer” (J. J» Mulvihill, R. W. Miller, and

J. F. Fraumeni, Jr., Eds.), pp. 439-453. Raven Press, New York, 1977.

Cairns, N., The Origin of Human Cancers. Nature (London) 389:
353-357 (1981).

Straus, D. S., Somatic Mutation, Cellular Differentiation, and
Cancer Causation. J. Natl. Cancer Inst. 67: 233-241 (1981).

Upton, Ae C., Role of DNA Damage in Radiation and Chemica? Carcino~
genesis. In “Environmental Mutagens and Carcinogens.” P: ceedings

of the 3rd International Conference on Environmental Mutagens

(R. Sugimura, $. Kondo and 8. Takebe, Eds.), pp. 72-80. University of
Tokyo Press, Tokyo/Alan R, Liss, Inc-, New York, 1982.

Moolgavkar, S. H. and Knudson, A. G., Mutation and Cancer: A Model
for Human Carcinogenesis. J. Natl. Cancer Inst. 66: 1037-1052 (1981).

Bartsch, H., Tomatis, L. and Malaveille, C., Qualitative and Quanti-
tative Comparison between Mutagenic and Carcinogenic Activities of
Chemicals. In “Mutagenicity”: New Horizons in Genetic Toxicology”
(J. A. Heddle, Ed.), pp- 35-72. Academic Press, New York, 1982.

Yunis, J. J., The Chromosomal Basis of Human Neoplasia. Science
221: 227-236 (1983).

United Nations Scientific Committee on the Effects of Atomic Radiation,
"Ionizing Radfation: Sources and Biological Effects.” (Report to

the General Assembly, with Annexes). United Nations, New York, 1982.
(Report E.82.1X.8.)

Crump, K. S., Hoel, D., Langley, C. and Peto, R., Fundamental Carcino-

genic Processes and Their Implications for Low Dose Risk Assessment.
Cancer Res. 361 2973-2979 (1976).

-35-



Table VI-1-B. Linear-model BEIR Absolute Risk Coefficients by Sex for
Bone and Joint Cancer Following Exposure to Alpha Particle Radiation
from Injected Radium-224: Absolute Excess Incidence per 100,000
Persons per Year per Rad to the Endosteal Layer

Exposure Age Years Follow-up! Sex
M F

All 0-30 +10 =«.10

Table VI-1-C. Linear-Model Relative Risk Coefficient R for Lung
Cancer Following Exposure to Alpha Particle Radiation from Inhaled
Radon Daughters: Percent Excess Incidence per Working
Level Month, by Source of Data (Reference 5)

Exposure Age Source of Data’ Estimate (R)
All Combined Uranium Miner Data 1.2
All U.S. Miners, Exposed Before 1961 0.7
All U.S. Miners, Exposed 1961 or Later 1.5

lobserved years of expression over which excess risk was averaged to
produce the risk coefficients shown. PC estimates for events beyond the
intervals shown lack a direct observational basis.

2coefficients derived by Working Group; see Chapter X for details.
3coefficients derived from BEIR (reference 4, p. 198, Table V-14).
Conversion of the linear-model BEIR coefficients to linear coefficients

in a linear-quadratic model involved dividing them by 2.5. Note that the
original BEIR coefficients were given per 10° person-year-rad.

-~77 -



and assess the various sources of uncettainty and to combine these uncer—
tainties into single measures for individual cancers. The combined un-
certainties, while not small, are not so large as to negate the useful-
ness of the PC's, especially at the low and high ends of the seale.

Chapter VIII discusses how the present PC estimates may he updated and
describes what new information may become available, and how it might be
handled. Chapter IX describes how to calculate the probability of causation
for any radiation dose and any cancer using only a few tables, which appear
in Chapter X. In Chapter X each cancer for which a probability of causation
can be calculated is discussed and specific exauples of calculations are
presented, together with tables of the constants necessary for these
calculations. This arrangement has necessarily given rise to some redund—
ancy, but the Working Group believes that the present format permtts any—
one to obtain all the basic information for calculation of PC for a specific
cancer in any specific case from just one of the subsections of Chapter KX.

In Appendix I, tables of the probability of causation for individual
cancers are presented for radiation doses of 1, 10 and 100 rad. For any
specific case, the reader is encouraged to use the simple formulae in
Chapter X for calculation of a probability of causation.

In Appendix I1, the Working Group has Teproduced the specific recom-
mendations of the NAS Oversight Committee with respect to the July, 1984
draft of the present report and its future revisions (17). Since this
final version of the Tables incorporates most of the recommendations made
by the Oversight Committee, each recommendation is annotated as to its
status in the final report presented here.

Appendix III is a glossary of some of t erms used in this report.

ako
J. E. Rall, M.D., PheD., Chairman,
NIH Ad Hoc Working Group to Develop

Radioepidemiological Tables
January 4, 1985

-vi-

Peper)


Exposure, Sex,
cank Digits or

Liver Cancer 10 or More Years After

LET Radiation. by age
PC im Parcent, to Two Signi

Three Decimal Places.

Exposure to Low-

Table PC-7 (Continued).
Dose in Rad.

Sex

Fenale

Male

Dose

109

16

19

Ronan SHMANAN
PIN MM AEE EE

Nreeawunnw.
MANBANAINnE

26
+26
+25

COFCO FOKEEEROTOS
Nee were eee eee

wreverserersrrs

HNN TNR WOOT NMI,

POPC OOODOR RE REE

- 313 -


Page
Chapter V: DATA SOURCES, ASSUMPTIONS, AND MODELS . 2... eee ee aes 54

A. Data Sources 2s ep et ee ee ee eee ee eee ne 54
B. Dose Response and Dose-Rate-Effect Models 1... 4... 55
Cc, Time after Exposure ss. + ee ee ene ee eee ees 57
D. Age at Exposure «ss eee ee eves eer enn eva 60

ot Chapter VI; METHOD FOR ESTIMATING RELATIVE EXCESS RISK AND
_ CALCULATION OF PROBABILITY OF CAUSATION... 2... 02 ee ee TL

A. Coefficients of Absolute Excess Risk ..-. eee eee ZL
B. Derivation of Coefficients for Calculating
Relative Excess Risk «+ +e ee eee cae e eee e 72
1. Leukemia and bone cancer «2 ee eee ee eee 72
2. Cancers other than leukemia and bone cancer... 73
3. The special case of lung cancer following
exposure to inhaled radon daughters ...... 74

Chapter VII: SOURCES OF ENCERTAINTY «. . eee ee eee ee ee eae ae FY

Ae Introduction 2 2 ese te ee ee eee eee ew wwe 79
B.. Sites of Cancer and Cell~Types . +. ee ees ee een 79
| C. Source Tables of Cancer Incidence in the U.S. Population 80
De. Minimal Latent Period » «ee eae eee eee ee eee BL

E. Dose-Response Function 6 6 11. eee eee ew te we ee BZ
| F. Influence of Age at Exposure 2.144 ee eee ee ae 83
. Ge Sex nee ee ee ee he ee ee he te ee ew BS
H. Dosimetry ss eee eee eee ww ee ee eee ee ee 85

I. Coefficients Describing the Dependence of Risk on Dose. . 87
| Jo Dose-Rate ee ee ee ee ee we ew ee we 8B
Ke Time-Response Models . 6 ss ea et eee ewe ee ee 88
Le Interactions with Other Carcinogens . 2.6 ee es eee 90
| M. Other Sources of Uncertainty ... 20)
i N. Effects of Variation in Density of Energy Deposition (LET) 91

: O. Propagation of Uncertainties and Their Effect upon the
Probability of Causation 2... 16. s eee eee ee 91
2. Unbiassed uncertainties »... eee eee ene 92
2, Biassed uncertainties . 6... 2... ee eee ee 95
3. Combined uncertainty .. 6... 2 eee ere ee 96

i 4. Effect of uncerrainty of risk upon che

probability of causation . 1.1.22 ee ee es 96

Chapter VIII: FUTURE REVISTON OF THE TABLES . 2.40200 eee eee ee LIB
ral Chapter IX: THE GENERAL FORM OF THE PC CALCULATION . . 2. ses ee eo © 128

“y Chapter X: THE CALCULATION OF PROBABILITIES OF CAUSATION FOR CANCERS
{ OF SPECIFIC TISSUES » 1 6 4 ee eee ee eee wee eo ow 126

1. Leukemia s+ esa ee ee eee se ee wo ow 6 126
2. Cancer of Bones and Joints...

3. Salivary Gland Cancer «+...

eee
eee
wee

194

«

+
+
.


Relative Excess
Sex

Kidney and Bladder Cancer:

KA),S) by Exposure Age A; and Sex §
Sex

1

Table X-11,
&

Female

Male

Female

Maie

BPESI LF RONK NM es oO- eEMONNOOWNoN
QFN EK OL RAAROAER SOOM — VE So Oe

QE SK NOE NOR OR OK NM ENON OFOHK NOE
OO DODO SOR RE

win
Onn nMOnTATR
ANN HH OOO
eee ee Seles
eeogevecccce
ScC0c90GGGfeS

- 254 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT?

100

50

20

10

Fig X-1-B-2

ACUTE LEUKEMIA
EXPOSURE AGE 10

40

20

AGE AT DIAGNOSIS pee

- 140 -


Table PO-1~A-20. Chronic Granulocytic Leukemia Following
Exposure at Aga 20, by Age &, ak Diagnosis, Sex, and Dose
in Rad of Low=LET Radiation.” PC in Percent, to Twe
Significant Digits or Three Decimal Places.

A, Sex
Be Male Female
Bese

1 10 300 F 10 00
22 3.5 23. a7. 4.4 33. 89.
ra 7.3 SE. 94 git $2. 9s.
26 7.4 45. 93 9.3 53. 95.
25 4.9 i. 92 8.4 30. 94.
26 5.1 37. $1 7.3 $6. $4.
27 4.5 34. 90 6.3 2. 93.
28 6.2 32. 89 5.4 3a. $1.
rs) 4.0 31, 83. 4.6 34, 90.
38 3.9 31. gs. 4.0 31. 88.
31 3.3 30, 8s 3.5 2b. a7.
32 3.5 28. 87, 3.0 25. 83.
33 3.1 26. 86 2.6 23. 83,
34 2.8 24, 84. 2.3 20. Bt.
35 2.5 23. g2. 2.0 $8, To.
36 2.2 20. es. 1.8 7. 77.
3? 2.0 18, 79. 1.6 18. 78.
38 +.8 17. 7a. 1.4 16, 73.
34 1,7 16, 76. 3 12. 7h,
40 1.6 $$. 75. 1.2 at, $8,
G7 1.4 14, 73. 1.0 10. 66.
42 1.3 13. Tt. 794 9.3 $4.
43 1,2 12. 70, +88 8.7 62.
44 1.2 Vie 68. 37 8.6 2.
65 1,1 10, 67. 36 8.6 62.
46 1.0 9.8 65. +85 8.4 61,
4? «93 9.2 63. 79 7.9 6c.
48 84 8.4 6. -69 6.9 56.
49 +73 7.4 $8. +58 3.9 se.
50 -63 6.3 $4. 48 5.0 47.
si 53 3.5 30. 241 4.3 43.
52 146 4.7 46. 37 3.8 at.
53 “39 4.4 42. 34 3.5 33
56 34 3.6 39. 35 3.2 36.
35 +30 3.4 36 29 3.¢ 35.

- 275 -


15.

16.

17.

18.

19.

20.

21.

22.

23.

24,

25.

26.

Rowland, R. £4, Stehney, A. F. and Lucas, H. F., Jr., Dose~
response Relationships for Female Radium Dial Workers. Radiat.
Res. 76: 368-383 (1978).

Archer, V. E., Gilliam, J. D. and Wagoner, J. K., Respiratory Disease
Mortality Among Uranium Miners. Ann. New York Acad. Sct. 271:
380~293 (1976). .

NCRP Report No. 78, “Occupational and Environmental Exposures
to Radon and Radon Daughters in che United States.” National
Council on Radiation Protection and Measurements, Bethesda, MD, 1984.

Conard, R. A., Paglia, D. &., Larsen, P. R,, et ale, "Review of
Medical Findings in a Marshallese Population Twenty-six Years after
Accidental Exposure to Radioactive Fallout.” BNL Report 51261.
Brookhaven National Laboratory, Upton, New York, 1980.

Saenger, E. L., Thomas, G. EB. and Tompkins, &. A., Incidence of
Leukemia Following Treatment of Hyperthyroidism. J. Am. Med. Assoc.
205: 855-862 (1968).

Schull, W. J. and Kato, H., Malignancies and Exposure of the Young
to Tonizing Radiation. Cancer Bull. 34: 88-89 (1982).

Ichimaru, M., Ishimaru, T. and Belsky, J. L., Incidence of Leukemia
in Atomic Bomb Survivors Belonging to a Fixed Cohort in Hiroshima
and Nagasaki, 1950-71, J+ Radiat. Res. 19: 262-282 (1978).

ichimaru, M., Ishimaru T., Mikami, M., Yamada, Y¥., and Ohkita, T.,
Incidence of Leukemia in a Fixed Cohort of Atomic Bomb Survivors and
Controls, Hiroshima and Nagasaki, October 1950-December 1978.
Technical Report 13-81, Hiroshima, Radiation Effects Research
Foundation, 1981.

Tokunaga, M., Land, C. E., Yamamoto, T., Asano, M., Tokuoka, S.,
Ezaki, E., Nishimori, 1. and Fujikura, T., Breast Cancer Among
Atomic Bomb Survivors. In “Radiation Carcinogenesis: Epidemiology
and Biological Significance" (J. D. Boice and J. F. Fraumeni, Jr.,
Eds.), pp. 45-56, Raven Press, New York, 1984,

Ishimaru, T., gt al., Incidence of Thyroid Cancer among Atomic Bomb
Survivors and Controls, Hiroshima and Nagasaki, 1958-1979: Relationship
to Radiation Dose Absorbed by Thyroid Gland. Unpublished manuscript
dated September 20, 1983.

Tokunaga, M., Land, C. E., Yamamoto, T., Asano, M., Tokuoka, S.
Ezaki, H. and Nishimori, I., Breast Cancer in Japanese A-bomb
Survivors. Lancet 2: 924 (1982).

Hildreth, M. G., Shore, R. E. and Hempelmann, L. H«, Risk of Breast

Cancer among Women Receiving Radiation Treatment in Infancy for Thymic
Enlargement. Lancet 2: 273 (1983),

= 32 -



ESTIMATED PROBABILITY OF CAUSATION (PERCENT?

106

30

20

10

Fig X-1-C-5

LEUKEMIA: ALL TYPES EXCEPT CLL
EXPOSURE AGE 40

60

AGE AT DIAGNOSIS Kale

Female----~

- 151 -


13.

14.

15e

16.

17.

18.

19.

20.

21.

22.

Land, C. E. and Norman, J. E., Latent Pertods of Radiogenic Cancers
Occurring among Japanese A-bomb Survivors. In: “Late Biological
Effects of Ionizing Radiation”, Vol. 1, pp. 29-47. International
Atomic Energy Agency, Vienna, 1978.

Tokunaga, M., Land, C. E., Yamamoto, T., Asano, Me, Tokuoka, Ss,
Ezaki, H. and Mishimori, I., Breast Cancer in Japanese A-bomb
Survivors. Lancet 2: 924 (1982).

Hildreth, M. G-, Shore, R. E. and Hempelmann, L. H., Risk of Breast
Cancer among Women Receiving Radiation Treatment in Infancy for Thymic
Enlargement. Lancet 2: 273 (1983).

Baral, E., Larsson, L. and Mattsson, B., Breast Cancer Following
Irradiation of the Breast. Cancer 40: 2905-2910 (1977).

Howe, G. R., The Epidemiology of Radiogenic Breast Cancer.

In “Radiation Carcinogenesis: Epidemiology and Biological Sig-
nificance” (3. D. Boice, Jr., and J. F. Fraumeni, Jr., Eds.),
pp- 119-129. Raven Press, New York, 1984.

Darby, S. C,, Nakashima, E. and Kato, He, Parallel Analysis of Cancer
Mortality awong Atomic Bomb Survivors and Patients with Ankylosing
Spondylitis Given X-ray Therapy. RERF Technical Report 4-84, Riroshima,
Japan, Radiation Effects Research Foundation, in press.

Bithell, J. F. and Stewart, A. M., Prenatal Irradiation and Childhood
Malignancy. A Review of British Data from the Oxford Survey.
Br. J. Cancer 31: 271-287 (1975).

Stewart, A. M., Radiation Cancers and A-bomb Survivors. Lancet 2:
1203 (1971).

Sasaki, S., Kasuga, T., and Kawashima, N., Influence of Physical

and Biological Factors on Radiation Carcinogenesis: Age-dependence

of Susceptibility to Radiation Carcinogenesis. In "Final Report:
Risks due to Low Level Radiation Exposure,” Project Research in

FY 1973-1982. National Institute of Radiological Sciences (NIRS-N-47),
Anagawa, Chiba, Japan, 1983.

Sasaki, S., Tsutomu, K., Sato, F., and Kawashima, N., Late Effects
of Fetal Mice Irradiated at Middle or Late Uterine Stage. Gann 69:
167+1977 (1978).

Sasaki, S. and Kasuga, T., Life Shortening and Carcinogenesis in Mice
Irradiated Neonatally with X Rays. Radiat. Res. 88: 313-235 (1981).

Sasaki, $. and Kasuga, T., Life Shortening and Carcinogenesis in Mice
Irradiated at the Perinatal Period with Gamma Rays. In “Life Span
Radiation Effect Studies in Animals: What Can They Tell Us?"
(Proceedings of the 22nd Hanford Life Sciences Symposium, Richland,
WA, Sept. 27+29, 1983.) DOE Symposium Series, Technical Information
Center U.S. Department of Energy (in press).

- 63 -


others), For lung cancer, the trend was linear over all ages (see Chapter
X-9). For breast and thyroid cancers the trend in Table VI-1 from 10~19

co 0~9 was extended linearly te age 0, while for leukemia the interpola-
tion routine produced an approximately linear extension which appeared to
require no correction. For extrapolation to older ages an interpolation
endpoint of zero risk at age 75 was used for breast cancer (see Chapter
V-D), but for other sites the interpolation algorithm continued a smooth
trend with increasing age at exposure which seemed ta require no correction
in view of the extremely limited information available on cancer risk from
tadiation exposures at age 60 or older.

B. Derivation of Coefficients for Calculating Relative Excess Risk

The interpolated absolute risk coefficients e(A,S), where A denotes
age at exposure and S denotes sex, were used to calculate coefficients
from which the relative excess pertaining to a given year after exposure
could be computed. For any given cancer site, age at exposure, and sex,
let P(Y) denote the absolute excess risk coefficient for Y years after
exposure. The coefficient e was based upon observed cancer risk over a
period of years after exposure, ¥) S YS y2 (see Table VI-1). The observed
population was subject to attrition, mainly from the usual age-dependent
force of mortality. Therefore, to an acceptable level of approximation,
e is defined as the lifetable average of P(Y) over the period yy < ¥ < yo.
Depending upon the way in which P(Y) varies with time and with the age-
specific baseline rate, the needed coefficients can be defined in terms
of e. Two algorithms were used, one for leukemia and bone cancer, and
the second for all other cancers.

wi. Leukemia and bone cancer

For leukemia (AL and CGL) and bone cancer following brief irrad-
iation type-specific lognormal distributions were obtained by fiteing to
gata, and made specific to each age at exposure (see Chapter V-C). The
distribution for all types of leukemia, from which chronic lymphoevtic
leukemia (CLL) was specifically excluded, was defined as a mixture of the
distributions for AL and CGL, weighted by .68 and .32, respectively. The
distribution, denoted by T(A,,¥) or T(Y), depended upon age at exposure
(Ap) for AL and therefore also for all leukemia except cLL, considered as a
#roup, but T did not depend upon 4; for CGL or bone cancer.

For each cancer type, for given (A;,S), the time-specific cnefficient
?(Y) can be written as

P(Y}) = E x TY),
where E = E(A,,S) denotes the probability that a radiation-induced cancer
will be observed at some time after exposure, provided that no other
cause of death intervenes. Therefore the coefficient e, which is the
lifetable average of P over yi & ¥ ¢ yg, can be written as the product E,
times the lifetable average of T. Solving for E, we obtain

Ese x [Lyp tee otLh (yg) 1/1 Ty, LC yy te + Pvg)U(y2) }

-72-

ey

ba wok


REPORT OF oe 4

- THE NATIONAL INSTITUTES OF HEALTH

| ~ AD HOC WORKING. GROUP
~ ‘TO DEVELOP

_ RADIOEPIDEMIOLOGICAL TABLES

“7 U.S: DEPARTMENT OF HEALTH AND HUMAN SERVICES:
=" Public Heaith, ice National Institutes of Health



Acute leukemia ~ PC is calculated as 10%. From Table VII-8
the lower and uppet factors are 0.74 and 3.55. From Table YII-9
the bounds on the credibility interval are 7% to 29%,

Breast cancer - PC at 15 or more years post-exposure is
calculated as 5%. The factor bounds (Table VII~8) are 0.93 and
2.82, The bounds om the credibility interval (Table VII-9) are :
5% ta 13%. :

Table VII-10 shows the calculated PC for which (with 95%
credibility) the “true” PC is more than 50%. For example, from
Table VII-8 it is found that for acute leukemia, the factor for
the lower limit is 0.74. From Table VII-10 it is found that the
value of the calculated PC, for which the “true” PC is at least ‘
50%, with credibility 0.95, is between 56% and 59%. Exact
calculation inverting Eq. (1) shows the value to be 57%.

In summary, although the effect of uncertainty is somewhat variable
depending upon the particular cancer and the latent period, certain gen-
eralizations can be made:

1. If the PC as calculated here fs 2% or less, the “true” PC almost
surely would be 7% at most (upper limit) even if we had sure knowledge
concerning all the unknowns which contribute to the uncertainties.

2. If che PC is in the range of S$ to 10% the “true” PC might be
quite smali (1%), but might be as large as 30%. .

3. Tf the PC is calculated to be at least 20%, the “true” PC is most
unlikely to be less than 5% and may be as large as 40%.

- 98 -


ws500°
°
a °
ct " ss zs os ae we a
’ a
\ 'y o6y ae wonrodny seysy 4 sted
AQ AAT WL WOFanaisseyg Tesodmey 1722 aderKg aed, CTY

Siweqoe] -tpenujauoa) Qat-x #taeL

- 172 -


F(D) = F(70) = 70

T(Y) = T(5) = .0814 (Table X-2-A)

E(A],$) = E(i5,m) = 2.79 (Table X-2-B)
: I(A2,8) = 1(20,m) = 1.12 (Table X-2-C)
K = E/I = 2479/1612 = 2.49

R=>FxTxK = 70 x 0814 x 2.49 = 14.19

C = R/(1+R)

14.19/15,19 = .934 = 93%

* ke *

The calculation of the relative excess where diagnosis occurred fol~
lowing several radiation exposures should be made by adding the relative
excesses for each exposure. If doses D(1}, D(2), and D(3) occurred at
ages A(i), AC(2), and A(3), respectively, the relative excess for the
combined exposures is given by

R= R(1) + R(2) + R(3).
The PC of all these exposures is
PC = R/(1+R).

The PC for any one of them (say the first}, given the change in risk ¢ ad
by the others, is

PC(1) = RCE)/C1+R).

a

Example 3 (Thyroid Cancer):

Aman diagnosed with thyroid cancer at age 25, following a 30-rad X
Tay exposure to the thyroid at age 17, 8.2 years previously. As an
infant (age 0, 24.7 years prior to diagnosis of thyroid cancer) the man
was successfully treated by high-voltage X radiation for Wilms' tumor and
it is estimated that his thyroid gland received 100 rad because of X-ray
scatter. The PC for the combined exposures is calculated as follows:
For the first exposure, completely ignoring thé second,
i F(D) = F(100) = 100
T(Y) = T(24) = 1
K(A],5) = K(O,m) = .106 (Table x-12)

R(t) = Fx Ex K= 100 x 1] x 2106 = 10.6

- 121 -



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

$0

20

10

Fig X-1-C+3

LEUKEMIA: ALL TYPES EXCEPT CLL
EXPOSURE AGE 20

20

AGE AT DIAGNOSIS Male ——

7 149 ~


vane

EXECUTIVE SUMMARY

Chapter {:

Chaprer [1:

Chapter ITI:

Chapter IV:

TABLE OF CONTENTS

Ce

LEGISLATIVE AUTHORITY 6 6 se et ee te ee ees

A.
B.
C

THE

Ae
B.
c.

Background » eee ee ee tt eee es
Public Law 97~414 = January 4, 1983 ....
Charter - Ad Hoc Working Group to Develop

Radioepidemiological Tables . . «2 2 a ae

ETIOLOGY OF CANCER 2 4 6 ew ee ee we es

Introduction « 6 1 a ee ee ee ee ewe
Current Theories of Carcinogenesis +». + » ~
Environmental and Life Style Risk Factors

Le Smoking «6 6 ee twee ee ewe ee we
2. Alcohol consumption «6 - «1 6 ee wee
3. Diet «6 eee we twee wet were
4. Occupational exposures . s+ ee es eee

5. Pollution . 2 6 ee ee er ree
6. Medical therapy and diagnosis . . + «6 +
7, Sexual development and behavior... «+
8. Viral infections ~. 2 1 6 4 se ee eae
9. Interactive effects ++ ++ + ee ee ae

RADTATION AS A CAUSE OF CANCER « «© 2 2 2 ew eae

Ae
B.
c.
dD.

THE

Ae
Be
on
De
Re
Fe
Ge

He
I.

Tatroduction «s+ ee ee ee eee ee ee
Characteristics of Ionizing Radiation ..-
Sources of Radiation Exposure «24 6 6 2 «+
The Evidence for Radiation Carcinogenesis in
Quantification of Risk » «6 2 ee ee ee
SOX 6 ee ww te we eh ee ee ee ew
Age at Exposure » . «1 6 ee eo ew ee eh we
Time to Response ¢ 6 es ee ee we roe
Models for Dose Response and Dose Rate « +
Modifying Effects of Other Exposures « .
Extrapolation from One Population to Another

PROBABILITY OF CAUSATION «2» se es ee we

General «ee eee ne see eee
Nefinition » «+» eee
Specifics 1. 2. 1 se eee
Calculational Formulas . 2. 1 2 see eee
Cases in Which U.S. Baseline Incidence Does

Multiple Radiation Exposures » 2. ss eae

ey

oo

Not

Apply

Modification of the PC Formula Tn Take Account of the
Effects of Exposure to Carcinogens Other Than

Radiation «1 we we ee ee mee ee
Cigarette Smoking and Lung Cancer... ..

ae

eee

Subpopulations with Non-standard Cancer Risks » « « +

Page

46
48
51



period model (13). The fitted model had a minimum induction period of
1,52 years and the natural logarithm of time after the minimum had a mean
of 2.12 and a variance of 0.48.

United States incidence data for cancers of bones and jointe have
been taken from the SEER data bank for 1973-1981 (8). As may be seen
from Tables VII-1 and ViI-2, there is relatively little variation among
the SEER reporting areas (8), although a sex differential is well estab~
lished, females having about 60 percent of the level reported for males.
Radiation is the only environmental factor that is known to play an
etiologic role in bone cancer (14). Statistical studies of ractal dif-
ferences in the incidence of Ewing's tumor and studies of family aggre-
gations point to the influence of genetic factors on some forms of bone
cancer (15). If an individual is known to be a member of a sub-population on,
with an elevated baseline risk, then the PC estimate obtained on the .
basis of the SEER rates will be excessive (see Chapter IV-G and Chapter IX).

For bone cancer, as for leukemia, the relative excess, R, in the basic
equation

PC = R/(] + R)
is found as the product of three functions, i-.e.,
R=FxTxk

where F = F(D) represents the alpha radiation dose to endosteal tissue
(D); T = T(Y) represents the influence of the interval from exposure to
diagnosis; and K = K(A),A9,S) represents relative excess of bone cancer
for a person of sex S and ages A, and Ap at exposure and diagnosis,
respectively, when both F and-T = 1. Here K is found as

K = E(A,,$)/1(Ag,8)
where E(A),8) 1s derived from BEIR III and is an estimate of the prababi-
lity that a radiation-induced bone cancer will be diagnosed at some time
after exposure to radium-224, and is expressed in units of dose. For
each exposure age Ay and sex S, E(A,,S} was determined such that the average
of E(4),S) x T(Y) over the BEIR III plateau period (Y¥ = 2 through 28) was

equal to the BEIR coefficient, 0.1 excess cancers per hundred thousand
persons per year per tad.

Look-up tables are provided below for the following coefficients:
T(Y), Table X-2-A;
E({A],S), Table X-2-B;
I(A2,$), Table X-2-C.

Here, under the linear model assumed for high-LET radiation, the endosteal
dose in rad is

Fed.

- 181 -



F 2 19 + 192/116 = 22.21
T(4) = 0
K(55,m) = .000603

then R = 0

and PC = 0 also

Example 3 An esophageal cancer was diagnosed at age 44 in a woman follow-
ing several exposures to low-LET radiation at various ages. The first,

of one rad to the esophagus, occurred at age 20, 24 years and 2 months
before diagnosis (Y = 24). The second, to 2 rad, occurred 4 months later,
at the same age (Aj = 20) but 23 years and 10 months before diagnosis,

(¥ = 23). At age 21, 23 years and 3 months before diagnosis, a 9-rad total
dose was received over a 36-hour period at the continuous rate of 250
millirad per hour (¥ = 23). Finally, at age 35, three exposures, to 1.1,
0.6, and 0.7 rad, respectively, were received on consecutive days, 9

years and 2 months. prior to diagnosis (¥ = 9).

The first, second, and third exposures should be considered separately,
because exposures 1 and 2 correspond to different values of Y, and exposures
2 and 3 to different exposure ages. The 9-rad continuous exposure delivered
over 36 hours should be treated as 2 exposures because it required more
than one day, but less than two. The suggested partition assigns a 3-rad
exposure to one 24-hour period and 6 rad to another. The three exposures
at age 35 can be treated as one because they correspond to the same values
of Ay and Y, and because the total dose is less than 5 rad.

Exposure 1:

F(D) = 1 + 32/116 = 1.01

T(¥) = T(24) = 1

K(20,f) = .00562

Ry = Fx Tx K= 1.01 x 1 x .00562 = .0057
Exposure 2:

F(2) = 2 + 22/116 = 2.03

T(23) = 1

K(20,f) = .00562

Rg =F xTxK- 2.03 x 1 x .00562 = .0114

~ 201 -



1.

8.

10,

ll.

REFERENCES - Chapter VII

Committee on the Biological Effects of Ionizing Radiation, "The
Effects on Popylations of Exposure to Low Levels of Ionizing Radiation:
1980." National Academy Press, Washington, D.C., 1980.

United Nations Scientific Committee on the Effects of Atomic Radiation,
"Sources and Effeces of Ionizing Radiation.” Report to the General
Assembly Publ. E771X1, United Nations, New York, 1977.

U.S Interagency Task Force on the Health Effects of Llonizing Radiation,
“Report of the Work Group on Science, June 1979.” Office of the Sec-
retary, U.S Dept of Health, Education and Welfare, Washington, D.C.,
1979.

ICRP Publication 26, Annais of the ICRP, “Recommendations of the
International Commission on Radiological Protection.” Pergamon
Press, Oxford, 1977.

Ron, E. and Modan, B., Thyroid and Other Neoplasms Following Child-
hood Scalp Irradiation. In “Radiation Carcinogenesis: Epidemiology
and Biological Significance” (J. D. Boice, Jr., and J. F. Fraumeni, Jr.,
Eds.), pp. 139-151. Raven Press, New York, 1984.

Coleman, M., Kirsch, M. and Creditor M., Tumors Associated with
Medical X-ray Exposure Therapy in Childhood. In "Late Biological
Effects of lonizing Radiation,” Proceedings of a Symposium,
Vienna, 1978, pp. 167-179, International Atomic Energy Agency,
Vienna, 1978.

Young, J. Le, Percy C. L. and Asire, A. J. (Eds.), “Surveillance,
Epidemiology, and End Results. Incidence and Mortality Data: 1973-1977,”
NCI Monogr. 57. U.S Govt Prtg. Off., Washington, D.C., 1981.

Cutler, S. J. and Young J. L. (Eds.), “Third National Cancer Sutvey:
Incidence Data,” NCI Monogr. 41. U.S. Govt. Printing Office, Washington,
D.C., 1975.

McKay F. W., Hanson, M. R., and Miller, R. W., “Cancer Mortality in
the United States: 1950-1977,” NCI Monogr. 59. U.S. Govt. Printing
Office, Washington, D.C., 1982.

Stewart, A. M., Leukaemia and Prenatal X-rays. Br. Med. J. 2:
1381-1382 (1960).

Monson, R. R. and MacMahon, B-, Prenatal X-ray Exposure and Cancers
in Children. In “Radiation Carcinogenesis: Epidemiology and
Biological Significance” (J .D. Boice, Jr, and J. F. Fraumeni, Jr.,
Eds.), pp 97-105. Raven Press, New York, 1984.

Oppenheim, B. E., Griem, M. D., and Meier, P., Effects of Low-dose

Prenatal Irradiation in Humans: Analysis of Chicago Lying-in Data
and Comparison with other Studies. Radiat. Res. 57: 508-544 (1974).

=~ 99 -



the carcinogenic process. Another marked contrast that distinguishes
leukemia and bone cancer from most other cancers that have been identified
as radiation-related is that leukemia and bone cancer risk appears to
return to near-normal levels within a period of 30 years or less after
irradiation, whereas for other types of cancer, the period of increased
risk is much longer and may extend to the end of life.

Reports of expert committees concerned with cancer risk from ionizing
tadiation have dealt with response time mainly in relation to lifetime
estimates of risk, a purpose for which sophisticated modelling is not
always necessary. For example, in the 1980 BEIR report, radiation-induced
leukemia and bone cancer were judged to have limited expression periods
following an exposure of brief duration and lifetime risk was calculated
as if excess risk were constant during the third to 29th years after expo-
sure and zero before and after (4). This “plateau” model gave about the
same lifetime risk as would have been obtained from a biologically more
reasonable model. We know, however, as did the BEIR Committee, that
leukemia and bone cancer risk increase over time to a peak followed by a
more gradual decline, and that (for example) a radiation-induced bone
cancer is much more likely to be diagnosed during the 10th year after
exposure than during (say) the 4th or 28th years. The plateau model is
thus unsuitable for calculating probability of causation, and should be
replaced by models that more closely reflect observed temporal patterns.

Nl
Nene

sda

The BEIR Committee rejected « plateau model of finite length for
cancers other than leukemia and bone cancer, because after approximately
30 years of follow-up in the major exposed populations, excess risk has
shown no sign of declining. It was noted that evidence of an excess risk
was much slower to develop than for leukemia and bone cancer, however,
and the first 10 years after exposure were ignored in the risk calculations.
Alternative models were used to project estimated risk beyond the period
of follow-up to the end of life. The “absolure risk” model is a plateau
model that extends to the end of life; in other words, given that an
exposure of brief duration has caused a cancer, the time to diagnosis in
different members of che population is assumed to be uniformly distributed
over the remainder of life following che minimum response time, assumed
by the BEIR Committee to be 10 years. This projection model was used in
parallel with the “relative risk" model, so called hecause the ratio
between the risk of a radiation-induced cancer and the average risk in
the absence of exposure, as determined from population rates, is assumed
to be the same for each year of life following the minimal response time.
Under the relative risk model, therefore, the distribution of response
time is non-uniform, varying in proportion to baseline rates which depend
upon age at observation.

Depending upon age at exposure, Lifetime risk projections according
to the absolute and relative risk models can vary markedly, with the
greatest deviation corresponding to young exposure ages. Averaged over
all exposure ages, the relative risk model lifetime projection on the
basis of follow-up data now available tends to be about 3 times as high
as the absolute risk model lifetime projection (4), hecause population
vates for the most important cancers tend to increase steeply with increas-
ing age. Even during the first 30 years or so after exposure, for which
the total excess risk estimated by the two models must agree because this

~ 20 -


4

pe

ead

rl

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

700

$o

20

10

Fig, x-4

ESOPHAGUS CANCER

T

“
“
yon S weerces
s -
.
.
‘
n
\
ay
s
‘
s
‘. eons
we *, -
AN ‘, *
* 7
Q Pa
Sal oat
wh. wna
ao 20 30 40 50 40 70
wit
AGE AT EXPOSURE Foret coon

- 203 -


Chapter VII: SOURCES OF UNCERTAINTY
A. Introduction

P.L 97-414 requires that the tables on probability of causation
“shakl 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 statement by the President, on the occasion of his signing
the Orphan Drug Act, expresses the Administration's reservations in
tegard to the preparation of the tables:

"eeethere is as yet no consensus among radiation experts in
relating human cancets 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.*”

What follows is a discussion of the many sources of uncertainty that
should be recognized in connection with the use of the tables.

The probability-of-causation (PC) tables bring to bear on the adjudi-
cation of claims the very extensive information available on the risk of
radiogenic cancer. Although we know more about the effects of ionizing
radiation than any other carcinogen, and much of the knowledge is quanti-”
tative in form, our present knowledge is far from complete, and the tables
can be regarded as no more than a guide to causation in the particular
case. However, even an imperfect guide that summarizes the relevant
literature in such a way that it can be brought to bear on the individual
case should be helpful in determining whether a prior exposure to radiation
was a significant factor.

Each element of the PC calculation has its own uncertainties, some
of which are interdependent: choice of sites and cell-types for which
tables can be prepared, baseline incidence, absorbed radiation dose, dose
Tate, minimum latent period, time to tumor recognition, choice of dose-
response function, radiation risk coefficient, choice of time-response
function, and the influence of individual host factors and competing
etiologic influences. In Section VII-O an effort has been made to
integrate most of these sources of uncertainties into an overall assess—
ment of the accuracy that can be ascribed to any value of PC.

RB. Sites of Cancer and Celi-Types

Although ionizing radiation has been shown to produce a very wide
array of human cancers, for certain cell-types, e.g., chronic lymphocytic
leukemia, radiation seems not to be detectably carcinogenic, For many

- 79 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

20

10

Fig X-2-7

BONE AND JOINT CANCER *
EXPOSURE AGE 60

if 10 RAD
aan
/ \
izi=. .
Afi RAD
t
if
~S
N
SS
~.
60 65 70 90 35
Hale ae
AGE AT DIAGNOSIS Female---

*xAlpha radiation from radium-224 only

— 189 -


For Y > 10 years, the relative excess risk is simply K(A],$) multi-
plied by an appropriate function F of radiation dose, There was, there-
fore, no requirement to tabulate the temporal distribution of risk or the
baseline risk, as was done for leukemia and bone cancer. But because the
telative excess must begin at zero and reach its full value after 10
years, and because biological considerations demand a smooth transition
(see Chapter III-H), we have represented this transition by T, as given

below and in Chapter V-C, in che case of cancers other than leukemfa or ‘
bone cancer.

Yr 0-4 5 6 7 8 9 10+ ot
TY): 0 6074 «6259-500 741 926 1.000

As before, Y denotes the integer part of time in years from exposure
until cancer diagnosis, Thus, the relative excess Y years following
tadiation exposure at age 41, for a person of sex S, is

R(Ar,Y,S) = F x T(Y) x K(Ay,S).

3. The special case of lung cancer following exposure to inhaled radon

daughters

The 1980 BEIR report (4) gave a single set of linear-model coefficients
to be applied to low-LET radiation and, with a suitable Q factor, to high-
LET radiation from inhaled radon daughter products. The Working Group found _
the BEIR coefficients to be difficult to use, as discussed in Chapter X-9,
and calculated separate absolute risk coeffictents for exposures from extern-
al, low-LET radiation based on A-bowb survivor data. For inhaled radon daugh+
ter products, the Working Group adopted relative risk coefficients based on
a review by Jacobi (5) of data from various studies of uranium miner popula-
tions. These estimates, as discussed in Chapter X~9, pertain to cumulative
exposure in Working Level Months (WEM), and express excess risk as a percen-
tage of underlying risk per WLM. The estimates do not depend upon sex or :
age at exposure, but take account of a possible difference in the method .
of measuring radon levels in U.S. mines before about 1961 as compared to
after that time and in other countries (Table VI-1-c).

~ 74 ~


and such other categories as the Secretary, after consulting with approp-
riate scientific experts, determines to be relevant. Fach probability of
causation shall be calculated and displayed as a single percentage figure.

(2) At the time the Seccetary of Health and Human Services publishes
che tables pursuaat to paragaph (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

(B) a compilation of the formulas that yielded the prob-
abilities 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.

(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 cepresent the hest available scientific data and expertise.”

Excerpt from President Reagan's statement on the occasion of his
signing the Orphan Drug Act

“, . . there its as yet no consensus among tadiation experts
in relating human cancers and exposure to low levels of
tadiation. Yet, Section 7 mandates that probability of
Causation tables be calculated for even very small dose
levels. Accordingly, 1 am directing the Secretary of
Health and Human Services to complete the tables

to the extent that may de 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.'"

C. Charter - Ad Hoc Working Group to Develop Radiocepidemiological Tables

Purpose

Section 7(b) of Public Law 97-414 directs the Secretary of Health and
Human Services co devise and publish radioepidemtological tables that
estimate the likelihood that persons with any radiation-related cancer
why 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 1 millirad to 1,000 rads in cerms of sex, age at time



for cancers of most other sites, the relative excess, R, in the basic
equation

C= R/(1 + R)
ts found as the product of three functions, tee.,
R = F(D) x T(¥Y) x K(Az,5)
where F(D) represents the tissue dose (D) in rad, T(Y) the influence of
the time from exposure to diagnosis (Y), and K(A;,S} the relative excess
risk of salivary gland cancer for a person of age at exposure A; and sax

$, when both F and T= 1.

Under the linear-quadratic model assumed for cancers of the salivary
gland, when exposure is to low-LET radiation

F= D+ D2/116.

For cancers of the salivary glands, the influence of time, T, depends
entirely upon completed years from exposure to diagnosis (Y). The function
T is tabulated below.

Y 0-4 5 6 7 & 9 10+

T 0 +074 2259 +500 274) +926 1
The standardized relative risk of excess cancer of the salivary glands, K,
is given in the accompanying table for low-LET radiation and for each sex

and year of age (completed years) from birth to age 14.

A few examples should clarify the actual computational procedures for
cancers of the salivary glands following exposure to fonizing radiation.

Example #1 A typical female, exposed at age 5 to 3 rad of low-LET radia-—
tion to the salivary glands, with diagnosis at age 12, 7.2 years after
exposure. Then D = 3, Ay = 5, and Y= 7.

F(D) = 3 + 32/116 = 341

TY) = T (7) = 005

K(A, 8) = K(5,£} = .0300
and R may be found from the relation

R=Fx Tx K = 3.1 x 0.5 x .030 = .0465

and PC = R/(14R) = .0465/1.0465 = .044, or 4%.

Example #2 A typical male, exposed at age 18 to 5 rad of low-LET radia-
tion to the salivary glands, with diagnosis at age 30. No estimate can

be made because the information ig not available for estimating the risk
associated with exposure after age 14.

- 195 -



occur, then PC(C, D;X) is the probability that D is the “cause” in
the sense described above. In short, PC(C, D;X) will usually be of
interest only retrospectively; supposing event C (a cancer) has
occurred, what is the probability that D was the cause?

C. Specifics

The discussion above is purposely quite general. To be more
specific:

The event C will be the occurrence (clinical detection)
of a particular cancer chat is known to be inducible by
ionizing radiation and for which specific estimates of the
risk from particular radiation doses can he made.

The cause D will be the receipt, by the organ in which the
cancer has atisen, of a specified radiation dose.

The characteristics X of the person under consideration
will include, at a minimum, the age at which the radiation
was received, the number of years after radiation when the
cancer was diagnosed and the sex of che individual.

We shall usually he concerned with annual rates of occurrence,
the rate representing the yearly number of cases of C per 100 ,000 or
per million persons.

The values P(C, D;X) will be identified with the incidence rates
provided by the SRER Program (2) for the years 1973-1981 for all
areas, excluding Puerto Rico. Although, formally, an incidence rate
is not a probability, the numerical difference is trivial over any
interval for which the probability of death from all causes is small.
We shall refer to these rates as the “Baseline Rates.”

D. Calculational Formulas

There is a calculational advantage in expressing the PC in terms
of the relative excess risk R = R(C, D;X), defined as the increase
due to D as a proportion of the probability of C in the absence of D:

RCC, DsX) = Ex(C,D3X)/PCC, Dzx).

Writing P(C,D;X} as the sum of Ex(C,D;X) and P(C, dD: KR) and dividing
both the numerator and denominator in (IV-1) by P(C, D;X), we obtain

PO(C,D;X) = RCC,D3X)/(1 + ROC,D;X)). (1v-2)

The advantage of expressing the PC in terms of R is that R is
the simple product of several quantities that are naturally thought of
separately, and that can be either calculated using simple formulae or
presented in tables. For example, in Chapter X, Section 10, we find
that the relative excess of breast cancer following exposure to radiation

- 44 -



3 After Exposure to
Sex, and Dose
7 ta fwo Significant

7)

at Exposur:
in Percant

i”
imal Places.

by Age A
ry Ag) PC

Lung Cancer 19 ar More Yaar
ers.

ation,
tor Nensmok

LomeLET Radi
Digits er Threa Dec

Tabla PC-5-3.
in Rad,

Sex

penmeee

~ Female

Mate

Dose

een.

100

14

PNODKRAM NOON IM NOON OE NT OF OR ROO EIN KINAMAN
PRA E NEN OCLC OOOMANONMNMMNE TICES TEL TE SSS

bee eee eae PIP TOT ONG IND OF ORR CEN OOR RO
todo te-dhd pak Ld eek aE EE a al rah alah tah
TT ORK RAMON OOONMNMNNMNMNS TEESE TT CERO

IOS UI OM OO NOWOF NR OR CAM COf Oh Com
POE RE BBO BAM EEE OMI EIN OI EU Se
tee eee TK MOATON KN HOOT NOER OMEN KH COCA RO RA
DBR MEO ee ee ee NE IN OO cheer
NNT TR MO ROR RONNIE TMM MM MN NUNN NON Oe
CT ROTH OM MOONE ONE ME NOOR ONE COTE QO
areterarstarers RON DOMME SEMMMMMNNNNAUNNNON Oe

PNM THOR WEOK- NM ENON WOOK NM EHO
AVN NNN MMMM ETS ST SSS

1
1
1
1
a]
20

= 318 -


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SOY A TOL AG AAS "eDL UOLTNG LIE; TesedeeL ieymennD] BANDy <(penUiyueZ) G-1-x TAL

161


Table PG-1-4-50. Chronic Granuiccytic Leukemia following
Exposure at Age $0, by Age A, at Diagnosis, Sex, and Dose
in Rad of Low-L€T Radiation.” ®C in Percent, te THo
Significant Digits er Three Decimal Places.

a, Sex
Maile Female
Dose
t 19 tee 7 TF 109
52 1.1 14, 91 9.0 63. ia
53 2.6 22. 2.2 20. gi, :
s4 2.8 24. 2.6 22. 83.
$5 2.6 22. 2.6 22. 33.
36 2.3 ra 2.4 24. 2.
57 2.9 18, 2.2 20. ai.
38 1.7 16. 2.0 18. 79,
39 1.5 14, 1,7 16, 76.
60 1,3 12. 1.8 14, 74.
61 V1 tf. 1,3 13, 71,
62 +97 9.5 1,2 Ry 68.
63 85 8.5 1.6 9.9 65.
64 -76 7.6 87 $.6 62.
65 68 6.8 +78 7.5 $8.
66 -6t €.2 +65 6.6 3s.
67 «34 5.6 57 5.9 $2.
68 +48 3.0 -53 3.4 $0.
69 +42 4.4 «St 3.2 48.
70 37 3.9 AD $.0 4a,
71 +32 3.4 46 4.7 46.
72 -23 3.0 oh 4.2 43.
73 +24 2.6 34 3.6 39.
74 .2t 2.2 «29 3.4 35.
75 13 1.9 25 2.6 31,
76 +15 1.6 «21 2.2 28.
27 53 1.4 ts 1.9 25.
78 ott 8,2 16 7 23.
79 +695 ,0 16 8 20.
$0 Oat -8? 12 4.3 1a.
a +072 -77 wit tt 16,
Fd 467 72 2095 1.0 43.
83 +964 +69 «036 292 14,
&4 ost 46 078 83 13.
8s esa 43 1022 27 12.
4
os

~ 278 -


to determine for such reasons as the following: (a) attenuation by

overlying tissues will in general vary with photon energy; and (b) in

the case of partial-body exposure, or whole-body exposure to highly

directional radiation fields, calculation of a mean organ dose may be

very uncertain. In the case of partial-body irradiation, the dose to an ‘
organ may be markedly non-uniform; this is especially true for an organ

like the active bone marrow, which is widely distributed in the body. If

the dose-response function were truly linear, it would be appropriate to

utilize the average dose over the entire organ and, for small doses+-of }
the order of 10 rad or less~-Linearity can be assumed. Tf, however, the 4
maximum and minimum doses to different parts of the organ are very different,
serious errors can result--in either direction. If the maximum dose is not ry
too large, and the response function is linear-quadratic, then the “effective” <j
dose will be under-estimated by the averaging process, but if the maximum

dose is large enough to cause substantial cell sterilization, the "effective"
dose can be over-estimated.

The quality of the dosimetry on which risk coefficients are based is
best for series derived from therapeutic trradtation. Treatment plans
ate carefully made and usually recorded in a fashion that permits the
calculation of doses, even to organs outside the primary radiation field.
The dose estimates for diagnostic irradiation are more uncertain and can
be difficult to reconstruct and describe with precision, e2.g-, in the
case of Fluoroscopy used to mon{tor artificial pneumothorax therapy for
tuberculosis (16). Average values may be fairly accurate, but individual
doses highly variable.

Because the dosimetry for the A-bomb survivors is now being revised
(17,18), the age- and sex-specific risk estimates which depend on their
experience are now uncertain. Various attempts have been made (19-21) to
predict the extent to which the next generation of dose estimates will
change previously calculated risk coefficients, and it appears that
certain low-LET risk coefficients may be increased, but probably by no
more than a factor of 2 (20). The types of cancer for which the co-
efficients depend essentially on the A-bomb data are: leukemia and
cancets of the esophagus, stomach, colon, lung, breast, bladder, and
kidney. Sites for which the risk coefficients are telatively independent
of the A-bomb data, at least as to level of risk, are: bone, salivary
gland, liver, pancreas, and thyroid. Charles et al (22) Tecently reviewed
the 1977 UNSCEAR report (2) to estimate the overall risk of radiogenic
cancer based on all sources of human data except the experience of the
A-bomb survivors. Their estimate also differs from current risk estimates
by a factor of about 2,

The dosimetry for the British ankylosing spondylitis series (23), a
major source of data for the calculation of risk coefficients, has been
under investigation by a British team for some time but, except for
leukemia, the only published estimates are the preliminary figures given
in the BEIR ILI repore (1).

:t
;
}

A particularly difficult dose-reconstruction has been that for the
thyroids of patients with tinea capitis treated with epilating doses of
X rays in Israel (24). The attribution of excess thyroid cancer to an
average tissue dose of about 9 rad has important implications for the

- 86 -


Table PC-1-8-S0. heute Leukemia Following Exposure at Age 50,
by Age A, at Diagnests, Sex, and Dese in Rad of Low-LET
Radiaticd. PC in Paccent. to rao Significant Digits or
Three Decimal Places.

Ay Sex
Male Female
Dose

1 10 199 i Te 198
$2 2000 004 -03t 000 0046 074
33 «916 17 2.3 3016 23S 2.5
34 -034 86 13, .o7t 75 12.
55 +19 2.1 26. i? 1.8 24.
$6 -33 3.4 38. 129 3.0 33.
37 +45 4.6 45. -44 4.1 $3.
58 54 3.6 se. ~49 5.1 43.
39 61 4.2 53. -56 5.8 St.
60 $5 6.6 35. 62 6.3 53.
61 68 $.9 56. +66 $.6 55.
62 +69 7.9 56. «68 6.8 S6.
63 70 74 57. 69 6.9 $6.
64 76 7.3 $7. 69 7.0 56.
65 +70 7.0 56, «683 $.? 36.
66 +83 6.9 36. +8? 6.8 $5.
67 .65 6.6 $$. +65 $.6 55.
68 +69 6.1 53. -62 6.3 33.
69 +54 5.6 5a. +38 3.9 $2.
74 149 5.0 47. -53 5.4 50.
71 43 $.5 45. 649 3.3 48,
72 39 4.1 42. «45 4.7 $6.
73 +36 3.7 40. +42 4.4 44,
74 33 3.4 iH. +39 6.4 42.
75 30 3.2 36. 36 3.8 4a,
78 +28 2.9 34. 34 3.5 38.
7? +28 2.7 32. -3t 3.3 i?.
78 -24 2.5 30. +28 3.0 34.
79 «22 2.3 29, +25 2.7 32.
80 +20 2.2 27. 223 2.4 39.
al -19 2.0 26. 121 2.2 28.
82 +18 wg 2s. -20 2.1 27.
83 17 v.38 24. 719 2.9 26.
84 16 +7 23. 18 3.9 25.
85 «16 1.6 22. 17 t.8 26.

~ 286 -

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Tesodwe, +179 3deoxg seddy [Ty “elmennet

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eet}

The first, second, and third exposures should be considered separate~
ly because exposures 1 and 2 correspond to different values of Y, and expo-
sures 2 and 3 to different exposure ages. The 9-rad continuous exposure
delivered over 36 hours can be treated as a single exposure because estima—
ted risk under the linear model depends only upon the total dose. Similarly,
the three exposures at age 35 can be treated as a single exposure.

Exposure 1:

F(D) = F(1) = 1

T(Y) = 1(24) = 3

K(A,,5) = K(20,f) = .00606

R) = FxetxK=1 x it x .00606 = .00606
Exposure 2:

F(2) = 2

1(23) = 1

K(20,£) = -00606

Ro= Fx TxK=2x 1x .00606 = 0121
Exposure 3:

POO) = 9

T(23) = 1

K(21,£) = 00523

R35 Fx PxK>=9x 1 x .00523 = .047)

Exposures 4, 5, and 6:

F(1.1 + 0.6 + 0.7) = F(2.4) = 2.4 |
T(9) = £926
K(35,f) = .00214

Rys556 = Fx Tx K = 2.4 x 1926 x .00214 = .00476

R= Ry + Ro + Ry + R 4556 = -00606 + .0121 + .0471
+ .00476 = .0700

PC = R/{1 + R) = .0700/1-0700 = .0654 or 7%,

~ 245 ~



Exposure 3a:
F(3) = 3 + 32/tt6 = 3.08
T(23) = 1

K(21,£) = .00287

Ryg = F x Tx K = 3.08 x 1 x .00287 = .00884
Exposure 3b:

F(6) = 6 + 62/116 = 6.31

(23) = 1

K(21,£) = .00287

R3p = Fx Tx K = 6.31 x 1 x .00287 = .0181
Exposures 4, 5, and 6:

FCLsL + 066 + 047) = F(2.4) = 2.4 + 2.42/116 = 2.45

T(9) = .926

K(35,£) = .00142

Raig06 = Fx Tx K = 2.45 x .926 x 00142 = .00322

R= Ry + Ro + Raa + Ray + Rys5rg = -00304
+ .00611] + .00884 + .0181 + .00322 = .0393
PC = R/CI#R) = .0393/1.0393 = .038 = 4%.

The uncertainty surrounding PC estimates is discussed in Chapter Vil,
and Section ViI+0 includes a derivation of approximate 90 percent credibility
intervals for PC estimates,

To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig X-11 has been drawn
for tissue doses of 10 and 100 rad of low-LET radiation, and PC values
plotted by age at exposure, for both males and females, and on the assump-
tion that the minimal latent period has been satisfied. The vertical scale
is logarithmic and curves are presented for only two radtation dose levels,
For these and other reasons interpolation is to be discouraged.

~ 252 -

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- 160 -


Acs)

Sex

Relative Excess KCA

Pancreas Cancer:
Sex

by Exposure Age 4, and Sex §

Table X~8.

Famale

Male

Female

Male

Lat hapatdlat-o\ taped ad) al ph atelalal: tds dcakabs Sete: tal
TIT MNO NAMOM ve TONS LOCOCO LS

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NM DOOM ONAN

Lab Sela aol int takchede lak ab iek Lakcdeds lana)
FT AMMO NMI ODO LOW OOOOR AR RAE
ATOWTOPOER OMRON TAN DOK ON OD
MOOME NDT TH MOTH FON BNTMMNNR A
RENN FAM ONAANAS Hoe eee ee
ee et tt tet ttt et ee a
SOOO GHODTODEOCESCOEHOGOOOCOOSS

CHAM sR WOO-— NM NOR WmO~ OH
AVN MOM MMAMM eres

6a

- 231 -


190

Femala
19

at Exposure, Sex, and

reent, to Two Significant Digits or
100

PC in Pe:

iT)

Male

-. Pancreas Cancer 19 of More Years After Exposure
LET Ragiatien, by Age a

to Low=
Dose in 3d,
Three Decimal Places.

Table PC-8

A

aetn]
NANAK Ree ee NNNNS

§
5
5
5
4
4
6
3
3
3
3
3
3
2
27

TROL QO OONOR HH OOM ONS FINE:

BOOKS SAMMANANNANSD Soe eee

12
12
12
4
12
12
2
2
3
3
3
3
3
4
4
S

i]
9
8
?
6
5
5
4
4
3
3
3
3
3
3
3
4
14
14
14
15
15
15
15
16
16.
16

Donmon—
NANNING meee ee eee eee

SroerNNNNNY
WN SMA T OD HMO N DODO DME OEEAROOA
oheehehetebetel 1-1-2 1-t-2°1-1 2-94

9
18

SNE NA OP OT NIT NON ONO NMOS NOM WHOM VME OR Am
NNN NANA MMS oT ET EE SIN INININa e

- 314 +


TABLE V-2,

Individual Types of Cancer for Which the BEIR III

Report Provides Incidence Risk Coefficients and Those for Which the

Working Group Has Calculated the Probability of Causation

BEIR TIL

Working Group

Leukemia (all except CLL)
+ bone cancer

Bone

Thyroid

Breast

Lung

Esophagus
Stomach
Intestine (colon)
Liver

Pancreas
Urinary organs
Lymphoma

Levkemia, all except CLL
acute forms
chronic granulocytic

Bone and joint*

Thyroid

Breast

Lung

Esophagus

Stomach

Colon

Liver

Pancreas

Kidney and urinary bladder

Salivary gland

*Alpha radiation from radium-224 only.

- 65 -



‘For cancer of the pancreas the influence of time (T) on the relative risk

depends entirely on years from exposure to diagnosis (Y¥). The function
T is tabled below:

Y O-4 5 6 7 8 9 10+

T 0 2074 +259 +500 +74) +926 1.

The standardized relative risk of excess cancer of the pancreas, K,
is given in the accompanying Table X-8 for low-LET radiation exposure in

trad and for each sex and age in completed years from 20 to 75.

A few examples may clarify the actual computational procedures for
pancreatic cancer following exposure to fonizing radiation.

Example 1 A typical female, exposed at age 35 to 10 rad of low-LET radi-
ation to the pancreas, with diagnosis at age 50. Then D = 10, Ay = 35,
and Y = 15.

F(D) = 16 + 102/116 = 10.86

t

T(Y) = T(15) = 1
K (Ay, 8) = KC35, £) = .00184
then R= F x T x K = 16.86 x I x .00184 = .020
and PC = R/(1 + R) = .020/1.020 = .0196 or 2%.
Example 2 A typical male, exposed to 5 rad of low-LET radiation to the
pancreas at age 40, with a diagnosis at age 51, 11 years after exposure.
Then D = 5, Ay = 40, and Y= 11,
F(5) = 5 + 52/116 = 5.22
Tdlt) = 1
K(40, m) = .000933
then R= F x Tx K = 5.22 x 1 x 000933 = .00487
and PC = R/(1 + R) = .00487/1.00487 = .0049 or less than 1%.
Example 3 A pancreatic cancer was diagnosed at age 44 in a woman follow-
ing several exposures to low-LET radiation at various ages. The first,
of one rad to the pancreas, occurred at age 20, 24 years and 2 months
before diagnosis (Y = 24). The second, to 2 rad, occurred 4 months
later, at the same age (Ay = 20) but 23 years and 10 months before diagnosis
(¥ = 23). At age 2!, 23 years and 3 months before diagnosis, a 9-rad total
dose was received over a 36-hour period at the continuous rate of 250 miili-
rad per hour (Y = 23). Finally, at age 35, three exposures, to l-l, 0.6,

and 0.7 rad, respectively, were received on consecutive days, 9 years and
2 months prior to diagnosis (Y¥ = $).

- 227 -



Exposure 3b;
F(6) = 6 + 62/116 = 6.31
T(23) = 1
K(21,£) = .00959
Ry, = Fx Tx K = 6.31 x 1 x .00959 = .0605 oS

Exposures 4, 5, and 6:

wed

F(1.1 + 0.6 + 0.7) = P(2.4) = 2.4 + 2.62/116 = 2.45
T(9) = .926
K(35,£) = .00458

Rasg06 = Fx Tx K = 2.45 x .926 x 00458 = .0104

R= Ry + Ry + Rga + Roy + Ryy5.6 = 0101
+ 0203 + .0295 + .0605 + .0104 = .131
PC = R/(1 + BR) = 6131/2.13L = 116 = 12%

The uncertainty surrounding PC estimates is discussed in Chapter VII,
and Section VII-0 includes a derivation of approximate 90 percent credibility
intervals for PC estimates,

To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig X-5 has been drawn
for tissue doses of 1, 10, and 100 rad of low-LET radiation, and PC
values plotted by age at exposure, for both males and females, and on the
assumption that the minima] latent period has been satisfied. The vertical
scale is logarithmic and curves are presented for only three radiation dose
levels. For these and other reasons interpolation is to be discouraged.

- 208 -


cata

asty

have used different approaches. The United Nations Scientific Committee
on the Effects of Atomic Radiation (6) used a dose-rate reduction Factor
of 2.5, while the National Council on Radiation Protection and Measurements
(55) gave a range of 2-19 for this factor and recommended the use of a
linear-quadratic dose-response function. The 1980 BEIR Committee chose a
linear-quadratic model for low-LET radiation in which the excess risk is
proportional to D + 0.0086D2, where D'is the dose in rad (4). The Linear
term (proportional to dose) dominates below a so-called crossover dose of
116 (= 1/0.9086) rad and the quadratic term (proportional to dose-squared)
dominates above that dose. This crossover dose, which was obtained by
curve-fitting to A-bomb survivor leukemia data, is consistent with those
obtained for chromosome aberrations in circulating human lymphocytes and
in a number of studies involving chromosome aberrations and mutations in
experimental animals or mammalian cells in culture (74).

Anatase

It is generally agreed (4,55) that the linear term of the Linear-
quadratic dose~tesponse model is unaffected by dose fractionation and by
variations in dose rate, and that the quadratic term should become smaller
as fractionation increases or the dose rate decreases. Thus, the BELR
committee used only the linear term of the linear-quadratic model to
estimate risk from continuous exposures to 1 rad per year (4). Based on
the data for mutation production in Tradescantia by gamma radiation (55),
it appears that one may reasonably apply the linear term alone to continuous
exposures to low LET radiation at dose rates several orders of magnitude
higher (e.g., 0.01 rad per hour which corresponds to about 90 rad per year
continuous exposure),

For cancers of the breast and thyroid gland, linearity of the dose-
incidence relationship is suggested by the available data. For example,
the risk coefficients derived from the carcinogenic effects of high
thyroid doses in infants treated for thymic enlargement (30) are similar
to those derived from average thyroid doses of 9 rad in Israeli children
treated with X rays for tinea capitis (73). Similarly, risk coefficients
for breast cancer in A-bomb survivors are essentially the same whether
derived from the effects of doses below 30 rad or from the entire range
of doses (72); furthermore, the incidence of breast cancer per unit dose
in women who received their {rradiation in daily occupational exposures a
as dial painters (75) or in many small, widely spaced exposures during :
multiple fluoroscopic examinations of the chest appears to be essentially
the same as in women who received their irradiation {n a single {nstantan~
eous exposure to atomic bomb radiation or in a few brief. exposures during
radiation therapy (50).

The BEIR Iii Committee did not incorporate the competing effect of
cell inactivation, mainly at high dose levels, into its risk calculations,
although it did consider the problem theoretically (4, p. 182). There

- appear to have been three reasons for this: First, the Committee had

great difficulty obtaining useful information by fitting even a linear-
quadratic dose-response model to the available data, and better results
could not be expected from a more complex model. Second, the Committee
relied heavily on data from the studies of Japanese A-bomb survivors, for
whom exposures were fairly uniform over the entire body. Doses high
enough to reduce the carcinogenic response appreciably through the com~
peting effect of cell inactivation might well be in the lethal range for

- 2%6-


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- 171 -

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AG CAMYDL aVanqysamig Txsodwey 119 Yd¥oKy SedAL TTY “R{weXna) “¢penu; wen) O-1-K TORE


Relative Excass K(A,,$)

Stomach Cancer:
, and Sex $

by Exposure Age A

Table X-5.

Sex

Sex

Female

Male

Female

Male

Neen vwwren cease cecccactewn pn wonmnewn
BAO RRR RR RRR RE RRR REAR ODOM LO MOOD ODIN

1
9
7
6
6
&
?
&
3
a
2
4
5
7?
3
0
5
2
2
3
3
3
43

MANNA MMMM SETS

EW Of ORO TM NM TINO OROH- AMEN OR MEO AE
CF TEE TFONONDHOMONNHN OCS OCSEOOCOORARARE

PANN NONNOMNOM AMAT CWR WOOF
OM ONY ER NOU TH RAO EU WINN OOM = DOT
MORI S ANT © DODO QR ORO DINIING FF FID
Norco THK DAES FC OSCE DT CCORDADOSOOCS
SHOSSSCOSCECOOCOCOETS TSEC OODEDS2aAS

WNW SMONNNOH aM COKE NOH NER In
NIH FON NON ONE Fo OH TRIN ORR OME
RENT OO OR ONS FS OM MMA NE oe
TT TK BOCOCOS HOC FODDER UOOCODSGGGR000000
PPCDCOCOTOGD SO OSCESDOMSCOO COSCO FEKGES

OT NM TNE BROT IME NOR QROT NOY NON OOOH N
alehekelabetalal TP NNNKON NNN MM OOM OMINE oe

- 210 -



Natura) Sources ¢

Environmental
Cosmie Radiation
Terrestrial Radiation
Interna! Radioactive
tsotopes

Manmade Sources:

Environmental
Technologically Enhanced
Global} Fallout
Nuclear Power

Mesical
Diagnostic
Radiopharmaceuticals

Occupational

Consumer Products
and Miscellaneous

Figure III-l. Radiation exposure of a typical person in the U.S.

from natural and man-made sources.

~ 38 +

20 40 60
Dose Per Year (Millirern)

{Redrawn from ref. 12.]

aka


aay

Table VII-4
Numbers of Deaths from Cancers of Various Organ Systems, 1950-

1974, in A-bomb Survivors under Age 10 in 1945.

Number -f Deaths
Total With 10+ Rad

All malignant neoplasms except leukemia 26 lL
Digestive organs and peritoneum 16 5
Stomach 12 4
All other digestive organs combined 4 L
Trachea, bronchus and lung 0 0
Lymphatic and hematopoietic 3 I

-107 -


eancer, and if D is exposure of the lung to 20 rad of gamma radiation,
while X and Y represent, respectively, being a regular cigarette smoker,
or a non-smoker, then according to our definition, PC(C, D;X) measures
the probability of causation of lung cancer from 20 rad among smokers and
PC(C, D;¥) chat among non-smokers.

Although it can be argued that cigarette smoking is a far more
important cause of lung cancer than is tonizing radiation, ovr work
addresses the radiation risk exclusively: Given a person, with whatever
risk factors may apply to him, what is che probability that the documented
radiation dose that he received was the “cause” of his cancer? This may
be interpreted as: what proportion of his total risk resulted from the
radiation? Although the question might be asked (and answered), we do
not address “What proportion of the risk resulted from smoking?” or “What
proportion arose from the combination of smoking and radiation?”

The phrase “Probability of Causation” is intuitively appealing, but
the ratios so designated are not probabilities in a mathematically rigorous
sense. it must be recognized that different persons vary as to their
(prospective) chances of having cancer. Besides age and sex, other
characteristics such as diet, exposures to carcinogenic chemicals, genetic
factors and a host of others, some of which can only be guessed at, all
combine to increase or decrease from the average value the chance that a
specific person will contract a particular kind of cancer. For present
purposes it is possible to take account of only a limited number of such
characteristics, principally age, sex and cigarette smoking habit. The
probabilities of cancer, then, are average values for all persons in a
given class, for example, male non-smokers aged 35 years. The Probability
of Causation that is calculated for an individual in that class will be
more or less correct as his personal characteristics match or vary from
the average in the class. Nevertheless, our procedure assigns the same
PC to all members of the class. :

Evidently, were the classes defined differently - for example, by
specification of residence in Utah, the calculated PC might well change.
In effect, our procedure partitions the population of the United States
into a set of mutually exclusive classes, by sex, age and smoking charac-
teristics. These characteristics were chosen because 1) they affect
cancer rates in important ways which can be specified from available
data, and 2) every person can be assigned unequivocally to one of the
classes.

it has been suggested that the term "Assigned Share” would more
accurately describe the ratios that are calculated (1). We are, however,
constrained by che legislative mandate embodied in Public Law 97-414
wherein the specific term “Probability of Causation” is employed.

Although the PC as defined can be calculated prospectively, it
would have little meaning for any person because of its specificity as to
type of cancer and date of diagnosis, as well as tissue dose and age at
exposure. Following the imposition of cause D, an individual may be
interested in P(C, D;X) ~ “What is the probability that C will occur?” or
in P{C, D;X) = P(C, D3X) - “By how much has the probability that C will
occur been increased?", but PC(C, D;X) tells him that if the event C does

-43-



3. Salivary Gland Cancer (142 in ICDA-8)

The 1980 BELR report (4) included the salivary glands among the sites
Sensitive to radiation carcinogenesis, but probably only at high dose
levels, and summary risk coefficients were not presented. The evidence
for a radiation effect reses mainly on follow-up studies of patients with
histories of therapeutic irradiation to che head and neck during infancy
or childhood, with doses to the Salivary gland ranging from about 40 rad
for X-ray epilation of the scalp to as much as 800 rad for irradiation of
the thymus gland or the tonsils (16-22). A recent review (23) included a .
linear regression analysis of dose Tesponse in which data from these
studies were combined. The several studies agreed reasonably well with
an estimated excess risk per rad of 0.26 cases per million person-years,
when a minimal iaduction petiod of 5 years was assumed. Estimates also
were derived from two studies of A-bomb survivors (24,25), but these
estimates seemed less reliable because of limited data in one and uncertain
dosimetry and uncertain numbers of person-years in the other.

The Working Group considers that available data support an estimated
risk of 0.26 excess salivary gland cancers per million person-years per
rad following a radiation exposure during infancy or childhood, that is,
before age 15, This level of risk applies 10 years after exposure, with
somewhat lower risks 5-9 years after exposure. No estimate was calculated
for exposures at older ages.

The available data are much too fragile for critical examination of
dose~response and time-response models appropriate to che salivary glands,
and the Working Group has assumed that excess cancer of the salivary
glands could be adequately described by means of the linear~quadratic
dose-response model and the constant relative risk time-response model.
The standard assumptions as to absence of thteshold and 10-year latent
period, smoothed as described in Chapter VI, have also been made.

Incidence data for the U.S. have been extracted from the data bank
for the SEER Program of the National Cancer Institute. The rates used to
represent normal or baseline incidence are for the period 1973-1981, all
races combined, and all reporting areas combined except Puerto Rico.
There is little variation among the reporting areas as to level of risk,
but the rates for females are about 75 percent of those for males (8).

As noted in Chapter IV-G and in Chapter IX, risk factors other than
fonizing radiation may be taken into consideration in interpreting the PC
values derived by the procedures presented here. If it is believed thar
some other risk factor operates additively with radiation, and the individual
is thought to have been exposed to that risk factor to an extent greater
than the average for the population generally, then the PC obtained from
the present procedures will be somewhat excessive. But 1 icv is believed
that the second risk factor may combine with radiation to enhance risk in
multiplicative fashion, rhe PC estimates based on these procedures should
be unblassed,

The procedures for calculating PC values for cancers of the salivary

glands based on the assumptions and principles of Chapter V and are
detailed in Chapters VI and IX. For cancers of the salivary glands, as

- 194 -


For leukemia, the relative excess, R, in the basic equation
PC = R/(L + R)
is found as the product of three functions, i.e.,
R= F(D) x T(Ay,¥) x K(A] ,A7,8)

where D is the tissue dose in rad for low-LET radiation; T(A,,Y)
represents the conditioning influence of age at exposure A) and time to
diagnosis (Y); and K(A],49,S) represents the relative excess of leukemia
for a person of sex S, age at exposure A}, and age at dtagnosis Ap, when
both FP and T= 1. The standardized relative excess K = K(A),A7,S) for an
exposure at age Ay and diagnosis at age Az is the ratio of the estimated
lifetime absolute excess E = E(Ay,S) and the background incidence I =
T(A2,8):

K (Ay,A2,5) = E(A],8)/1(42,$).
The coefficient E was derived from the BEIR LIZ coefficients, fitted to a
quadratic. function in age Ay (see Chapter V-D}, and is an estimate of the
probability that a radfation-tnduced leukemia of the specified type will be
diagnosed at some time after exposure given F(D) = 1. For each exposure
age A, and sex $, E(A],S) was determined such that the average of E(A),S)
x T(A),¥) over the period ¥ = 2 through 28 was equal to the interpolated
BEIR coefficient for age A, and sex S$.
The following look-up tables are provided below:
for CGL: T(Y¥), Table X-1-A;
E(Aj,8), Table X-1-B;
1(A],$), Table X-1-c;
for all acute forms of leukemia: T(Ay,Y), Table X~1-D;
E(A],S), Table X-1-E;
I(Aj,5), Table X-1-F;
for all forms of leukemia except CLL: T(A;,¥), Table X-1-G;
E(Az,S), Table x-1-H;
1(A2,8), Table X-1-I,

Under the linear-quadratic model assumed for leukemia when exposute is to
low-LET radiation, and the dose, D, is expressed in tad,

F=D+ D2/tie.

~ 128 -


Table PC-2~59. Bane and Joint Cancer Following Exposure at
Ase 50, by Age A, at Diagnosis, Sex, and Dose in Rad of
Alpha Radiatten.? PC in Percent, to Two Significant Digits
or Three Decimal Places.

42 Sex
Male Female
i}
Dose a

7 0 190 T 19 199
$1 +004 048 48 O11 wif 1.0
s2 15 13. 69. 3.2 25. 76.
$3 7.3 44. 8. 14. 6), 94.
54 12. 59 93. 2t. 73. $6.
35 1S. 64 38. 2 76. 92
56 15. 65. 9s. 23 75. 97
57 18. 63. 95. 22 73. 97.
58 14, 61, 94, 49 71, 96.
39 13. 59. 94. 7, 67. 95.
60 12. 57. 93. 14. 63. 94,
et ta. 34, 92. 12, 38. 93.
62 8.9 49. $1 10. 53. $2.
63 7.3 44, a9 3.8 43. Fl,
64 $.3 34. 4. 7.3 46. 90.
65 4.8 33. 83 7.3 44, 89.
66 3.9 29. 60. $.6 oi, 8a.
6? 3.2 2s. 77, $.? 38. 86.
63 2.8 21. 73. 4.7 33. 83.
69 2.2 18, 6}. 3.9 29. 80,
70 1.8 16. 65. 3.2 25. 77.
73 1.5 13, et, 2.6 at. 73.
22 1,3 i 56. 2.2 18, 69.
73 1.0 9.5 51, 1.8 16. $3.
7¢ 3) 7.6 4s. 1.5 13. 60
75 -84$ 6.0 39. 1.2 Mh $4
76 +32 6.9 34. to 9.5 31,
77 +43 4.2 30. +87 8.9 47.
78 +43 3.8 29. 76 7.t 43.
79 740 3.8 23. 68 6.4 41,
ao 41 4.0 29. -63 5.9 39.
ai .43 $.1 30. 88 3.4 36
8 139 3.8 28. 49 4.7 33.
83 33 3.2 25. 4h 3.3 29.
a4 .27 2.7 2t. 232 3.t 24.
BS -23 2.2 13, +25 2.5 29.

~ 302 -


235

—
. Or 735
A
= r Relative Risk 44
g 20+ 7
= Absolute Risk ao “
® | \ lu i y 3
&

—
Oo
F

0 10 8620 300—« 40 50 ~=—s«60
Age At Time Of Bomb

Figure Il1-2. Measures of leukemogenic effect among A-bomb survivors,
by age at the time of the bomb, average for both cities.

The footnotes explaining the two ordinate scales are:
*Risk of 100+ versus 0-9 rad.
**Excess cancers per million persons per year per rad.

[Redrawn from Beebe, G. W., Kato, H., and Land, €. E+, Radiat. Res.
75: 138-201 (1978), Fig. i-}

- 39 -

Absolute Risk °°


frees

5. Stomach Cancer (151 in ICDA-8)

The risk coefficients used in the derivation of PC values for
stomach cancer are taken from the BEIR ILI report (4) and adjusted to the
period 11-30 years after exposure, but the BEIR coefficient for those
exposed under age 10 is not used for reasons presented in Chapter VII.
The inclusion of stomach cancer in the lise of radiogenic cancers rests
primarily on the experience of the British patients with ankylosing
spondylitis treated by X rays (26) and of the A~bomb survivors (27) but
ts supported by animal experimentation (4). On the other hand, the
recently published series on cervical cancer patients treated with X ray
and radium had 201 observed cases of stomach cancer, several times the
size of the ankylosing spondylitis series, but lacked evidence of a
carcinogenic effect on stomach tissue (5). The relationship in the A-bomb
survivors at the time the BEIR II1 report was prepared rested entirely on
the experience of the Hiroshima survivors (27), but more recent data on
the Nagasaki survivors indicate that the effect is by no means confined
to the Hiroshima sample (28,29). The numbers are very large, 1754 deaths
from stomach cancer through 1978, 1443 in Hiroshima, 311 in Nagasaki, but
relative risk estimates are low: Kato and Schull estimate that only 42
of the deaths from stomach cancer may have been caused by radiation (28).

The Nagasaki Tumor Registry data on stomach cancer incidence were
examined by Wakabayashi et al. for goodness of fit to the linear, linear-
quadratic, and “pure” quadratic functions, and none of the models could
be rejected by the usual statistical criterion (29). The Working Group
has adopted the linear-quadratic dose-response function for stomach can-
cer as for most tumors in the expectation that further accumulation of
data may in time demonstrate non-linearity, which is suggested by the
combined A-bomb data of the two cities.

The Working Group has adopted the constant relative risk time-
response model on the basis of Land and Tokunaga's analysis of other
sites (33) and the demonstration by Kato and Schull (28) that, for all
sites combined except leukemia, the picture is one of constant relative
tisk rather than absolute risk over time. (See also Chapter V~C.)

Environmental factors evidently play a dominant role in the etiol-
ogy of stomach cancer, the incidence of which has been falling rapidly in
the U.S. and many other countries, but few specific etiologic factors
have been identified. The influence of smoking and alcohol is described
as equivocal, but many studies have yielded crude associations between
various aspects of diet and the risk of stomach cancer (34). There is no
information on the joint effect of ionizing radfation and other risk
factors. When the SEER incidence data, used here as the baseline data on
the risk of stomach cancer, are examined by reporting area a wide range
of variation is seen (Tables VII-1 and VII-2). As noted in Chapter I¥-G
and in Chapter IX, risk factors other than fonizing radiation may be taken
into consideration in interpreting the PC values derived by the procedures
presented here. If it is believed that some other risk factor operates
additively with radiation, and the individual is thoughe to have been ex-
posed to that risk factor to an extent greater then the average for the
population generally, then the PC obtained from the present procedures
may be somewhat excessive. But if it is believed that the second risk

- 205 -



Table PC-1-C-20. Leukemia Excluding CLi Following Expesura
at Age 20, by Age Az at Diagnosis. Sex, and Dese in Rad
of Low-LET Radiation. PC in Percent, to Tro Significant
Digits or Three Decimal Places.

as Sex
Male Female
Dese

t 17 700 7 Te 139
22 +81 8.1 $0. 72 7.2 57.
23 3.6 29. 87. 3.2 26. 36,
24 5.4 38. 91, $.0 36. 91,
2s 5.8 40, 92. 5.7 4a. 92.
26 5.6 33. 92. $.7 34. $2.
2? $.2 37. 91. $.3 3a. 91
28 4&8 35. 50. 4.8 33. 90
23 4.3 33. a3. 4.3 33. 89
36 3.9 30. 88. 3.8 3o. 88,
31 3.5 28. &?. 3.3 v, a6
32 3.4 25. as. 2.8 24. BS,
33 2.7 23. $3. 2.4 21. 82.
34 2.3 20. ai. 2.0 18. 79
35 2.9 18, 75. 1.7 16. 76.
36 1.8 16, 77. 1.5 14, 73.
37 1.8 14, 74, 12 2. 76,
38 1.46 13, 72. wi 19, 67.
39 1.2 1t, 65. +93 9.2 63.
40 1.9 10. 66. +81 8.0 6e.
4) 94 9.6 63. +70 7.1 37.
42 279 7.9 60. +61 6.2 53.
43 -68 6.9 56. 53 5.4 SG.
44 +58 $.9 52. «45 4.7 4S.
45 49 5.1 48. +39 4.0 42.
4&6 42 4.3 44, 33 3.5 38.
47 36 3.8 40. +29 3.0 35.
48 3? 3.3 37. 625 2.6 32.
49 -27 2.8 33. +22 2.3 29.
5S 23 2.5 30. +20 2.1 27.
St +20 2.5 27. 21? V8 24.
32 18 tr. 2s. ~ 16 V7 22.
53 1$ 1.6 22. 14 1.8 29,
34 Pars 1G 20, 12 1.3 1B.
55 +12 1.2 18. wit 1.2 17,

- 291 -



7

cat

4. Esophageal Cancer (150 in ICDA-8)

The esophagus is apparently not especially sensitive to the carcino-
genic influence of fonizing radiation, but is included among the sites
for which risk estimates have been made by both the BEIR LII committee
(4) and the UN committee in its 197? report (2}. The Working Group has
employed the BEIR III risk coefficients (adjusted to the period 11-30
years after exposure) for individuals exposed after age 20; those for
exposure under age 20 were considered unreliable for the present purpose
(see Chapter VII-F). The BEIR III committee relied heavily on both experi-
mental and human data in selecting the esophagus for inclusion among the
sites for which risk might be estimated. Human data, however, are rather
few and derive largely from the small series among the British ankylosing
spondylitis patients (26) and the larger series among A-bomb survivors
(27). The BEIR committee used the risk coefficients for fatal esophageal
cancer among the A-bomb survivors as its incidence estimates, since the
case-fatality of esophageal cancer is so very high. More recent reports
on the experience of the A-bomb survivors have not altered the evidence
of the relative sensitivity of esophageal tissue to the carcinogenic
action of radiation (28-30).

Neither the dose-response nor the time-response characteristics of
tadiation-induced esophageal cancer have been studied sufficiently to pro-
vide independent evidence as to the functions most suitable for this
site. The Working Group has chosen, therefore, to employ the linear-
quadratic dose-response function, with no threshold, and the constant
relative risk model to describe the distribution of excess cases over
time with a latent period of 10 years smoothed as described in Chapter
v-C.

Estimates of baseline incidence are based on the SEER data bank of
the National Cancer Institute (8). The rates are for the period 1973-1981,
for all races combined, and for ali reporting areas combined except
Puerto Rico. As noted in Chapter VII-C, Tables VII-1 and VII-2, there is
considerable variation among the SEER reporting areas with respect to the
incidence of esophageal cancer. The major risk factors that have been
identified are alcohol consumption and cigarette smoking (31). As noted
in Chapter IV-G and in Chapter IX, risk factors other than ionizing
radiation may be taken into consideration in interpreting the PC values
derived by the procedures presented here. If it is believed that some
other risk factor operates additively with radiation, and the individual
is thought to have been exposed to that risk factor to an extent greater
than the average for the population generally, then the PC obtained from
the present procedures will be somewhat excessive. But if it is believed
that the second risk factor may combine with radiation to enhance risk in
multiplicative fashion, the PC estimates based on these procedures should
be unbiassed. Day and Munoz (31) cite the data of Tuyns et al. (32) as
providing evidence that a multiplicative model fits wel] the combined
influence of alcohol consumption and smoking upon the risk of esophageal
cancer. There are, however, no good data bearing on the issue with
respect to ionizing radiation and no numerical adjustment is provided
here.

- 199 -



Tabla PC+9-E (Continued). Lung Cancer 10 or More Years After
Exposure £0 Low-LET Radiation, by Ago a, at Exposure, Sex,
and Dose in Rad, for Present Cigarette Bmokers, Under 10
per Day. PC im Parcent, to Two Significant Digits or Three
Decimal Places.

: 4 Sex
ue Male Famate
Dose

7 1) 100 7 rT) 00

$e 2045 48 7.6 +12 1.3 18.
Si 0446 48 7.6 «12 1.3 18,
$2 O48 47 7.6 ~12 1.3 19,
53 046 +47 7.5 +13 3.4 19.
54 +044 47 7.5 13 1.4 19,
$5 - 944 147 7.6 213 4.4 20.
56 044 +43 7.6 216 5 20.
$s 065 48 7.6 +14 1.5 21,
58 +045 48 2.7 NS 1.6 2,
$9 046 +49 7.8 rar) 1.6 22.
60 046 49 7.8 tS 1.6 22.
61 087 -50 7.9 716 1? 23.
62 = 0467 51 gt 216 1.7 23.
63 048 $2 8.2 17 1.8 24.
64 ~04F .53 B.4 ¢ 17 1G 24,
65 -051 $4 8.6 18 19 25.
66 +082 -56 &.8 +19 2.0 26.
67 954 +88 9.4 19 2.t 26.
63 956 60 o.4 +20 2.1 27.
69 058 «63 $.7 12d 2.2 28.
70 061 65 10, 121 2.3 23.
7T 063 67 10, 122 2.3 29.
72 «065 -70 Vt, 123 2.4 29.
73 2088 72 1, +23 2.4 39.
74 070 75 it. .23 2.4 30.
78 +072 -78 iz. "624 2.5 30,

- 325 -



factor may combine with radiation to enhance risk in multiplicative
fashion, the PC estimates based on these procedures should be unbiassed.
Caution should be exercised, however, because the appropriate interaction
model for radiation in combination with any other carcinogens for stomach
cancer is not known. .

The calculational routine for stomach cancer is based on the assump—
tions and procedures detailed in Chapters V, VI, and IX. For stomach
cancer the relative excess, R, in the basic equation

PC = R/(1 + R)
is found as the product of three functions, f-e.,

R= F(D) x TCY) x K(A),5)

where F(D) represents the contribution of a Low-LET radiation dose to the
relevant tissue (D), T{Y) represents the conditioning influence of years
from exposure to diagnosis, and K(A],$) represents the standardized re-
lative excess risk of stomach cancer per rad for a person of sex S and
age at exposure A,, when both F and T = 1.

Under the linear-quadratic model assumed for stomach cancer when ex-
posure is to low-LET radiation,

F=D+ p2/116.

For the stomach the influence of time (T) on the relative risk depends only
on years from exposure to diagnosis (Y), The function T is tabled below.

Y O-4 5 6 7 8 g 10+
T 0 +074 «259 +500 +741 +926 1

The standardized relative risk of excess cancer, K, is given in the
accompanying Table X-5 for low-LET radiation and for each sex and year of
age (completed years) from 10 to 75.

A few examples should make it clear how PC values are to be obtained
for stomach cancer.

Example } A typical woman aged 25 with an exposure of 10 rad of X rays
to the stomach, and with a diagnosis of stomach cancer at age 50, 25
years later. Then D = 10, Ay = 25, and Y = 25.

F(10) = 10 + 102/116 = 10.86

T(25) 1

K(25,f) = .00782
then R= F x Tx K = 10.86 x 1 x .00782 = .0849

and PC = R/{1 + R) = .0849/1,0849 = .078 or 8%.

~ 206 ~


TIA, Y)

.15

1125 +

.075

0375

_t

0 5 10 15 20 25 30 35 40 45

Time Y in Years Following Exposure

Figure V-3. Fitted time-to-tumor model for acute
leukemia induced by a brief exposure to ionizing
tadiation at age Aj. T(A,,¥) is the probability
of diagnosis within one year after time Y.
Numbers within the graph indicate age at exposure.
(Data from refs. 11 and 12.)

= 68 =

bike


factors used in the formulas and unambiguous application of the assigned—
share forumlas.”

The Working Group has prepared a documented version of the
programs used in ite calculations. There should be little diffi-
culty in adapting these programs, which are written in MLAB, to
other programming languages.

21. “The Oversight Committee recommends that an alternative expression be
considered for ‘probability of causation,’ such as ‘assigned share,‘ that
more accurately reflects what is being estimated.”

The Working Group preferred to use the language of the enabling
Orphan Drug Act.

22. “The Oversight Committee recommends that the possibility of using a
different partition of the populations be kept in mind when new versions
of the tables are being produced, to be consistent with relevant newly
available information.”

This recommendation also is for the Future and one the Working
Group can endorse.

23. “The Oversight Committee recommends that the available radioepidemiologic

data be analyzed with techniques that exploit the inherent smoothness of
the relevant biologic processes.”

See response to recommendation no, 17.

24, “The Oversight Commitree recommends that the Working Group conduct a
quantitative appraisal, such as a sensitivity analysis, to evaluate the
uncettainties in the assumptions, data, and methods used in constructing
the tables;. their influence on the reliability of the tables of assigned
shares; and their implications for possible uses of the tables.”

The Working Group has included a discussion of the elements that
contribute to uncertainty in Chapter VII. A quantitative analysis
of the influence of these elements on the reliability of the
estimates of the tables of Probability of Causation has been
included as Chapter VII, Section 0.

25. “The Oversight Committee recommends chat the tables of assigned shares
be updated promptly after the revised atomic-bomb dosimetry is released,
with cancer data through 1982 or lacer if available and analysis with
improved techniques if possible.”

In Chapter VIII the Working Group has taken this position.

= 344 ~~

as

ssanread


Table PC-1~C-S0.  Laukenia Excluding CLL Following Exposure
at Age 50, ty Aca aA, at Diagnosis, Sax, and Dese in Rad
of Law" LET Radiatio#. PC in Percent, to Tuo Significant
Digtts or Three Decimal Places.

ay Sex
Maie Female
vd
Dose va

1 10 tog i 10 189
32 .43 4.5 45. 3.9 4t.
33 14 10. 67, 9.3 64.
S¢ 1.2 12. 70. Vw, 67.
35 1.2 t2. 70. tt, 68.
56 1.2 1, 69, tf, 67.
3? wd i, 67. 10, 66.
58 1.9 9.8 65. 9.8 65.
39 93 9.2 63. 9.3 64,
60 +86 8.6 $2. 8.8 62.
61 -89 8.9 $a. 8.4 6).
$2 +75 7.5 $8. 7.9 60.
63 74 7.4 $7, 7.3 38.
64 +67 6.8 38. 7.F $7.
6s -63 6.4 54. 6.6 5S.
64 59 6.4 $2. 6.3 SS.
47 +56 5.7 $1, 5.9 $2.
63 31 5.2 48. 3.5 Sa.
6? +45 4.7 46. $.1 48.
a 40 $.t 43, 4.7 “46.
71 35 3.7 $0. 4G 4&4.
72 31 3.3 37. 4.0 42.
73 +28 3.0 34. 3.7 4).
74 -25 2.7 32. 3.4 3.
75 «23 2.4 se. 3.1 33.
76 021 2.2 28. 2.8 33.
77 19 2.0 26. 2.5 34
78 1? 1.8 2¢. 2.3 29.
79 6 1.7 23. 2.0 26.
89 +14 5 2t. 1.8 24.
gt 33 1.4 20. 1.7 22.
82 +12 1,3 18. 1.5 21.
g3 -12 1.2 38. 1.4 2c.
84 oad 1.2 7. 1.4 19.
as 10 1.4 16. 1.3 19,

- 294 =


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- 78 -


ceey

data

27.
28.

29.

30.

31.

32.

33.
34.

354

36.

37.

38.

39.

40.

MacMahon, B. and Hutchison, G. B-, Prenatal X Ray and Childhood Cancer:
A Review. Acta Unio. Int. Contra Cancrum, 20: 1172-1174 (1964).

Totter, J. R. and MacPherson, H. G., Do Childhood Cancers Result
from Prenatal X Rays? Health Phys. 40: 511-524 (1981).

Monson, Re R. and MacMahon, B., Prenatal X-ray Exposure and Cancer
in Children. In “Radiation Carcinogenesis: Epidemiology and
Biological Significance” (J. D. Boice, Jr. and J. F. Fraumeni, Jr-,
Eds.}, pp- 97-105. Raven Press, New York, 1984.

Hempelmann, L. H., Rall, W. J., Phillips, M., Cooper, R. A. and
Ames, W. R-, Neoplasms in Persons Treated with X-rays in Infancy:
Fourth Survey in 20 Years, J. Natl. Cancer Inst. 55; 519-530 (1975).

Jablon, $. and Kato, H., Childhood Cancer in Relation to Prenatal
Exposure to Atomic~bomb Radiation. Lancet 2, 1000-1003 (1970).

Kneale, G. W. and Stewart, A. M., Mantel-Haenszel Analysis of Oxford
Data. I. Independent Effects of Several Birth Factors Including
Fetal Irradiation. J. Natl. Cancer Inst. $6: 879-883 (1976).

Mole, R. H., Antenatal Irradiation and Childhood Cancer: Causation
or Coincidence? Br. J. Cancer 30: 100-208 (1974).

Harvey, E. L., Prenatal X Ray and Childhood Cancer in Twins. Johns
Hopkins Univ. Unpublished Doctoral Dissertation, 1983.

Upton, A. C., Odell, T. T. and Sniffen, E. P., Influence of Age at
Time of Irradiation on Induction of Leukemia and Ovarian Tumors
in RF Mice. Proc. Soc. Exp. Biol. Med. 104: 769-772 (1960).

Brent, R. L., Effects of lonizing Radiation on Growth and Development.
Controversies in Epideriology and Biostatistics 1: 147-183 (1979).

Sasaki, $., Kasuga, T., and Kawashima, N., Influence of Physical

and Biological Factors on Radiation Carcinogenesis: Age~dependence
of Susceptibility to Radiation Carcinogenesis. In “Final Report:
Risks due to Low Level Radiation Exposures, Project Research in FY
1973-1982." National Institute of Radiological Sciences (NIRS-M-47),
Anagawa, Chiba, Japan, 1983.

Sasaki, S., Tsutomu, K., Sato, F., and Kawashima, N., Late Effects
of Fetal Mice Irradiated at Middle or Late Uterine Stage. Gann
69: 167-177 (1978).

Sasaki, S$. and Kasuga, T., Life Shortening and Carcinogenesis in Mice
Irradiated Neonatally with X Rays. Radiat. Res. 88: 313-325 (1981).

Sasaki, $. and Kasuga, T., Life Shortening and Carcinogenesis in Mice
Irradiated at the Perinatal Period with Gamma Rays. In “Proceedings
of the 22nd Hanford Life Sciences Symposium, Richland, Washington,
Sept. 27-29, 1983" (in press).

-33-


¥ 0-4 5 6 ? 8 9 10+
T(Y) 0 +074 .259 .500 .741 .926 1.000

The constant relative risk model has not been assumed to hold for
leukemia and bone cancer. For these cancers T denotes the conditional
probabilicy, assuming that a cancer has been caused by an exposure at
age A), that it will be diagnosed Y years later. T is calculated as
the lognormal probability that a radiation-induced cancer is diagnosed
between Y and Y + ] years after exposure at age Az» For bone cancer
and chronic granulocytic leukemia, T depends only upon ¥, while for acute
leukemia and for leukemia generally, without regard to type, T depends
upon’ exposure age Aj as well as Y. T is tabulated separately in Chapter
X for each of these sites, for integer values of Y between 0 and 49
and, where required, for Ay between 0 and 75.

As noted in Table VI-1, the observational base for the risk co-
efficients is generally no more than 30 or 35 years after exposure.
The various specifications of T(Y) or T(A,,Y) for specific cancer sites
invite application beyond the period of 30-35 years or so of follow-up
that form the observational basis for the risk coefficients used in
this report, and indeed this seems the most reasonable course to take
if estimates must be made for cancer cases occurring long after exposure.
But it should be recognized that we do not in fact have much information
on the risk -f radiation-induced cancer for periods beyond 35 years or
so after exposure. Unpublished data on cancer mortality among A~bomb
survivors through 1982 (H. Kato, personal communication) appear to be
supportive of a continued increase in risk in absolute terms, a finding
consistent with the constant relative risk model, and excess leukemia
risk, which already had fallen to a level difficult to detect, remains
low, as would be predicted according to a lognormal model for temporal
distribution of risk. The fact remains, however, that making probability
of causation estimates for cancers diagnosed more than 35 years or so
after exposure involves projections in time beyond our present observa—
tional basis, and that there is more uncertainty involved in such pro-
jections as they are removed farther and farther in time from that
observational basis.

The factor K = K(A,,A7,S) is the relative excess at age Ap for a
person of sex S exposed at age Aj, when F = 1 and T= 1. For cancers other
than leukemia and bone cancer K does not depend upon Ag and is tabulated
by site. For leukemia and bone cancer

K = E/E.

In this formulation E = E(A,,S) has the following theoretical interpreta—
tion: it is the estimated probability, for F=l, that a radflation-i-* ced
cancer will be diagnosed at some time after an exposure at age Aj, svided
that no other cause of death intervenes. A quantity of more practical
importance is T(Y) x E, which is the probability of cancer Y years after
exposure, assuming survival to that year. I(A2,S) is the (site-specific)
baseline cancer incidence for persons of age Az and sex S. E and I are
tabulated separately for bone cancer and for each leukemia type considered.

~ 119 -



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- 103 -


178?

Relative Excess K(A

Thyrotd Cancer?
by Exposure Age 4, and Sex §

Table X-12,

$ax

Sex

Female

Male

Female

Male

DDB BOBMINT MNT OR OM OMINGE TFET TN OO DE DOR ENS
REBKOHOO NAAN ever eve wesc vvewvesowooooN
SOSCOBTOCESCSSCEOCECTBOABDSO GB SGeADPeTOoCAOBLOBOS

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Pesce anC ET eaCCGECeees
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FEF NOON NS 08 SOOO COUR RRA

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OOOH OK RN MART YODR NM ANN SH DOMAINS HOOK Oe
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9898000080000 66860008000 BOOS 200868850

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SRR REE RK MUNN NNN NNO MMe

nm

- 261 -


Table VII-7

Combined Uncertainties and Bias Correction Factors

Years after Combined Bias Correction
Kind of Cancer Exposure Uncertainty (S) Factor
All leukemia Any 1.59 1.62
except CLL
Acute or chronic
granulocytic leukemia Any 1.61 1.62
Bone Any 1.57 1.00
Salivary gland 5~14 1.75 0.71
iS+ 1.72 1.00
Esophagus. 5-14 1.92 1.15
15+ 1.88 1.62
Stomach, lung 5-14 1.79 1.15
15+ 1.74 1.62
Colon, kidney and 5-14 1.68 1.15
bladder 15+ 1.63 1.62
Liver 5-14 1.88 0.71
15+ 1.84 1.00
Pancreas 5-14 1.64 0.71
15+ 1.59 1.00
Breast 5-14 1.46 1.15
15+ 1.40 1.62
Thyroid 5-14. 1.54 0.71
15+ 1.49 1.00

- 112 -


For esophageal cancer the relative excess, R, in the basic equation
PC = R/() + R)
is found as the product of three functions, i.e.,
R = F(D) x T(Y) x K(A),8)
where F(D) represents the contribution of the tissue dose, T(Y) represents
the conditioning influence of years from exposure to diagnosis CY), and
K(A],S) represents the relative excess risk of esophageal cancer for a

person of sex S and age at exposure Ay, when both F and T= 1.

Under the linear-quadratic model assumed for esophageal cancer when
exposure is to low-LET radiation

F=D + p2/116

For the esophagus the influence of time (T) on the relative risk depends
only on years from exposure to diagnosis (¥). The function T is tabulated
below:

YX 0-4 5 6 7 8 9 10+
T 0 2074 2259 +500 «74h +926 1.

The standardized relative risk of excess esophageal cancer, K, is given
in the accompanying Table X.4 for low-LET radiation and for each sex and
year of age (completed years) from 20 to 75.

A few examples should make it clear how the PC values are to be calcu-
lated in individual cases:

Example | A male, exposed to 5 rad of low-LET radiation to the esophagus
at age 20, with a diagnosis of esophageal cancer at age 50, otherwise
typical of his age-sex classification with respect to the risk of esophageal
cancer. Here D = 5, Ay = 20, and Y = 30.

F(D) = 5 + 52/116 = 5,22
T(Y) = 7030) = 1
K(Ay,S) = K(20,m) = .00207

then R = 5.22 x 1 x .00207 = .0108

and PC

R/(1 + R) = «O11 or 1%,
Exaaple 2 A typical male, exposed at age 55 to 19 rad of low-LET radiation

to the esophagus, with a diagnosis of esophageal cancer at age 59, 4.6 years
after exposure, Here D = 19, Ay = 55, and Y = 4,

- 200 -


weal

exist. Internal emitters are important sources of exposure, especially
plutonium and radon daughters, and a comprehensive set of procedures for
PC calculations ideally should make provision for them. The NAS committee
preparing the next BEIR report should be sensitive to the need for

PC estimates and provide the kind of statistical information that is re-
quired for their calculation. If che Department of Health and Human
Services were to maintain a standing group charged with responsibility for
the tables, liaison between this group and the NAS committee will also be
necessary if supplements to the tables are to be issued as updates on
particular sites of cancer prior to any full-scale revision. A standing
committee might also observe the use of the PC tables in compensation
cases by the courts or by administrative boards and consider how the
tables might be improved for judicial use.

In brief, four or five years hence, authoritative information concern-
ing the radiation induction of solid tumors will be much improved from
its present state; not only will the data be more robust statistically in
consequence of larger numbers, but the data on A~bomb survivors, now
available only through 1978, will have been extended to 1982 or 2986.
Thus, it should be possible either to verify that the relative risk
time-response model applies to follow-up periods as long as 40 years, or
to learn what modifications are required; additional evidence concerning
the shape of the necessary dose-response curves should help to clarify
this controversial subject and data from other human studies way cast
additional light on the general applicability of risk estimates generated
from particular populations. Further, greater confidence in the appropriate-
ness and reliability of some of the key assumptions, especially those relat~
ing to dose-rate effect, dose-response model, and time-response model, will
depend on a better understanding of the mechanisms of malignant transformation
at the molecular and cellular levels where research is presently very active.

- 117 +


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

160

so

20

40

Fig. X-7

LIVER CANCER

—r

wee

bas
sel
~
we
.
.
“

|

10 zo 30 40 $0 60
AGE AT EXPOSURE

- 223 -



also fdentified a number of familial and hereditary factors that influence
the risk of colon cancer and have shown that persons with chronic uleer-
ative colitis are at high risk of colon cancer (39). For none of these
factors are quantitative estimates of relative risk firm enough for
specific guidance in this context. Nor is there information on any
interaction between such risk factors and radiation in the etlology of
colon cancer. As noted in Chapter IV-G and in Chapter IX, risk factors
other than ionizing radiation may be taken into consideration in {nter~
preting the PC values derived by the procedures presented here. If it is
believed that some other risk factor operates additively with radiation,
and if the individual is thought to have been exposed to that risk factor to
an extent greater than the average for the population generally, then the
PC obtained from the present procedures may be somewhat excessive. But
if it is believed that the second risk factor may combine with radiation
to enhance risk in multiplicative fashion, the PC estimates based on
these procedures should be unbiassed.

The procedures for calculating PC values for colon cancer rest on
the general strategy outlined in Chapters V, VI, and IX. For colon
cancer, as for other sites, the relative excess, R, in the basic equation

PC = R/(1 + R)
is found as the product of three functions, i.e.,
R = F(D) x T(Y) x K(Aq,5)
where F(D) represents the influence of the low-L&T tissue dose (D), T(Y¥)
represents the influence of years from exposure to the diagnosis of colon

cancer (¥), and K(A],S) represents the relative excess risk of colon
cancet for a person of age at exposure A, and sex S, when both F and T = l.

Under the linear-quadratic model assumed for colon cancer when exposure
is to low-LET radiation

F-D+ D216.

For colon cancer the influence of time (T) on the relative risk de-
pends entirely on years from exposure to diagnosis (Y}. The function T
is tabulated below:

4 0-4 5 6 7 8 9 10+
T 0 +074 +259 +500 +741 +926 1
The standardized relative risk of excess colon cancer, K, is given in
the accompanying Table X-6 for low-LET radiation, for each sex and completed

year of age from 20 to 75.

4 few specific examples should illustrate the way in which PC values for
colon cancer may be derived from the material presented here.

Example 1 A typical female aged 45 given 5 rad of low-LET radiation to
the colon, with a diagnosis of colon cancer at age 48, 3.5 years after

~ 212 ~



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

20

10

Fig X-1-B-3

ACUTE LEUKEMIA
EXPOSURE AGE 20

20

AGE AT DIAGNOSIS Male au
Femate---

- 141 -



y
4
Hy

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

zo

10

Fig X-1-B-7

ACUTE LEUKEMIA
EXPOSURE AGE 60

a —<—==
100 RAD
$0 6s 76 7s #0 8s 90 95
AGE AT DIAGNOSIS Male
Female---

~ 145 -


Table PC~9-F.

Low-L&T Radiation,
in Rad, for Present Cigaree

Lung Cancer

10 ¢r More Years After Exposure to

by Age A at Exposure, Sax, and Dose
e

Smokers, 10 to 20 per Day.

PC in Percent, te Twe Significant Digits or Three Decimal

Places.
4 Sex
Male Female
Dose

7 17 106 1 6 100
10 +28 2-9 34. +2? 2.8 33,
WwW +25 2.6 31. -25 2.6 34,
12 622 2.3 29. +23 2.4 29.
13 -20 2.1 27. +20 2.2 27.
44 !7 1.8 24. 39 2.0 26.
15 15 4.6 22. Pas 1.8 24.
16 214 1.4 20. tS 1.6 22,
17 12 1.3 18, 14 t.5 21.
18 15 1.1 17. 13 v4.4 19.
19 037 1.9 15, 12 t.3 58,
20 -087 +93 1, wit 1.2 $7.
21 079 85 13, +10 1.4 16.
22 2972 77 12. 097 1.6 5.
23 +966 71 WW, +999 +96 14.
24 -661 «65 ia, 635 90 14,
2s 056 +60 9.3 Q73 -85 13.
26 051 «55 a.? 47s +40 12,
27 048 «51 $e.) e790 35 42,
28 - 046 -47 7.5 067 72 th,
2g 045 644 7.0 2064 68 it.
30 .038 at 6.6 O65 6S 10.
3! 036 +38 6.2 +058 +62 9.7
32 -034 -36 3.9 056 +6@ 9.4
33 032 34 $.5 054 38 9.a
34 030 32 5.2 052 +56 8.8
35 628 «30 5.0 051 +84 8.5
36 .027 +23 4.7 ase -$3 8.4
37 -026 +27 4.5 043 +$2 8.2
38 028 +26 4.3 O48 .ot g.1
39 -024 +25 4.2 047 -50 8.6
40 «023 +24 4.0 647 59 7.9
Gt +922 +24 3.3 O46 +49 7.9
42 021 ~23 3.8 046 49 7.8
43 O25 +22 3.? 046 149 7.8
44 ~620 21 3.6 046 49 7.8
45 «020 .2t 3.5 046 49 7.8
46 2019 -2t 3.4 046 49 7.9
a7 «019 +20 3.3 +047 -$0 7.9
48 +015 .20 3.3 a47 St 8.4
49 018 +20 3.3 048 -St Bit

- 326 ~

rani

ai
uy

ovata


fos!

vised

AD HOC WORKING GROUP TO DEVELOP RADIOEZPIDEMIOLOGICAL TABLES

ROSTER OF MEMBERS

J. Edward Rall (Chairman)

Deputy Director for Intramural Research
National Institutes of Health

Shannon Building, Room 122
Bethesda, Maryland 20205

(301) 496-1921

Gilbert W. Beebe

Clinical Epidemiology Branch
National Cancer Institute
Landow Building, Room 8C41
Bethesda, Maryland 20205
(301) 496-5067

David G. Hoel*

Director of Biometry and
Risk Assessment Program

National Institute of Environmental
and Health Sciences

PO Box 12233

Research Triangle Park, NC 27709

(919) 541-3441 (FTS 8-629-3441)

Seymour Jablon

National Research Council
2101 Constitution Avenue
Washington, D.C. 20418
(202) 334-2825

Charlies E. Land

Radiation Epidemiology Branch
National Cancer Institute
Landow Building, Roos 3422
Bethesda, Maryland 20205
(301) 496-6600

*taddress during 1983-84:

Board of Directors

Radtation Effects Research Foundation
2-5 Hijiyema Park, Minami-ku
Hiroshima-shi, 730

Japan

Oddvar F. Nygaard, Director ooo
Division of Radiation Biolc

Department of Radiology

Case Western Reserve University

2058 Abington Roz?

Cleveland, Ohio 106

(216} 844-3539

Arthur C. Upton

Professor and Chairaan

Department of Environments} Medicine
New York University Medical Center
550 First Avenue

New York, NY 10016

(212} 340-5280

Rosalyn S. Yalow

Senior Medical Investigator

Veterans Adwinistration Medical Center
130 West Kingsbridge Road

Bronx, NY 20468

(212) 579-1644

Victor H. Zeve (Executive Secretary)
Special Assistant

Office of the Director

National Cancer Institute

Building 31, Room 4B47

Bethesda, MD 20205

(301) 496-5854


ens

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

300

50

20

190

Fig X-9

LUNG CANCER

T

‘
=
,
‘
‘
‘
.
.
‘
10 RAD .
an ad
. .
ae
*se 8 rae
40 20 30 40 50 60 70
AGE AT EXPOSURE - pe

- 239 -



women aged 40 or older and these indicate that the flat projection of

risk from age 20 in the BEIR report can no longer be supported. Accord-
ingly, age-specific coefficients developed from that more recent study
have been substituted for those given in the BEIR report (see Chapter V-D).

Other recent developments include a record~linkage study (80) of
breast cancer mortality among some 110,000 Canadian women given multiple
chest fluoroscopies during treatment at tuberculosis sanitorta in Canada.
The radiation exposures were highly fractionated and delivered over
periods of years. The data from this study were interpreted as suggestive
of a strongly quadratic, rather than linear, dose response. This inter~
pretation, which seems contradictory to the general observation from
experimental radiobiology that fractionation end protraction of dose
reduce nonlinear components of the dose response (81), appears to rest on
a difference between data from Nova Scotia, where total doses tended to
be high, and other Canadian provinces, where doses tended to be Lower
because patients usually were examined with their backs to the X-ray
source. Considerable uncertainty surrounds the dosimetry data for the
Canadian series, and it is of interest that the initial publication of a
small Nova Scotia series (82), which employed incidence rather than
mortality, suggested linearity of dose-response to the first BEIR committee
(83).

Despite its general preference for the linear-quadratic dose-response
function, the Working Group considered that atl the data for breast cancer
except those in the recent Canadian report were so strongly linear that it
was important to make an exception of breast cancer and to assume linearity
of dose-response in developing the PC estimation procedure for this site.
The time-response data on breast cancer definitely point to the constant
relative risk model as the basis for distributing excess cases over time,
with a latent period (for incidence) of 10 years smoothed as described in
Chapter V-C. Since the underlying data on breast cancer are extensive,
are derived from numerous exposure situations, and are relatively non-
controversial, PC estimates for this site are probably more reliable than
for any other site. The general procedures for estimating PC values are
described in Chapters VI and IX.

Breast cancer baseline rates vary somewhat by geographic region.
Tables VII-1 and VIT-2 fllustrate the variability seen in the SEER data
of the National Cancer Insitute from which the baseline or normal incidence
data were taken (8), There are many risk factors for breast cancer in
addition to exposure to ionizing radiation, especially early menarche,
nulliparity, delayed age at first completed pregnancy, positive family
history, and pre-existing proliferative breast disease (84). As noted in
Chapter IV-G and in Chapter IX, risk factors other than ionizing radiation
may be taken into consideration in interpreting the PC values derived by
the procedures presented here. If it is believed that some other risk
factor operates additively with radiation, and the individual is chovght
to have been exposed to that risk factor to an extent greater than the
average for the population generally, then the PC obtained from the present
procedures may be somewhat excessive. If it is believed that the second
tisk factor may combine with radiation to enhance risk in multiplicative
fashion, the PC estimates based on these procedures should be unbiassed.
For breast cancer the relative excess, R, in the basic equation

- 243 -



66.

67.

68.

69,

70,

71.

72.

73.

74.

75.

764

77.

Ellett, W. E. and Nelson, N., Epidemtology and Risk Assessment.
In: “Proceedings of the Seventh ORNL Life Sciences Symposium:
Indoor Air and Human Health”, Knoxville, TN, Oct. 29-31, 1981.
Oak Ridge Associated Universities, Oak Ridge, TN, in press.

Darby, S- C., Nakashima, 8., and Kato, R., "Parallel Analysis of Cancer
Mortality among Atomic Bomb Survivors and Patients with Ankylosing .
Spondylitis Given X~ray Therapy.” RERF Technical Report, Radiation |
Effects Reseach Foundation, Hiroshima, Japan, in press.

Steer, A., Land, C. E., Moriyama, I. M., Yamamoto, T., Asano, M., and 4
Sanefuji, A., Accuracy of Diagnosis of Cancer Among Autopsy Cases:

JNIH-ABCC Population for Hiroshima and Nagasaki. Gann 67: 623-632

(1976).

Fraumeni,:‘J. Fe, Jr. and Blot, W. J., Lung and Pleura. In “Cancer
Epidemiology and Prevention” (D. Schottenfeld and J. F. Fraument, Jre,
Eds.), pp- 564-582. W, Bs Saunders, Philadelphia, 1982.

Tokunaga, M., Norman, J. E., Jr., Asano, M., Tokuoka, S., Ezaki, H.,
Nishimori, I., and Tsuji, Y., Malignant Breast Tumors Among Atomic
Bomb Survivors. Hiroshima and Nagasaki, 1950-1974, J. Natl. Cancer
Inst. 62: 1347-1359 (1979). [RERF TR 17-77].

Botce, J. D., Jr. and Monson, R. R., Breast Cancer in Women after
Repeated Fluoroscopic Examinations of the Chest. J. Natl. Cancer
Inste 59: 823-832 (1977).

Shore, R. E., Hemplemann, L. He, Kowaluk, E., Mansur, PB. S., Pasternack,
B. Ss, Albert, Re E., and Haughie, G. E., Breast Neoplasms in Women
Treated with X-rays for Acute Postpartum Mastitis. gu. Nati. Cancer
Inst. 59: 813-822 (1977).

Boice J. D., Jr., Land, C, E+, Shore, R. E., Norman, J. £., and
Tokunaga, M., Risk of Breast Cancer Following Low-Dose Exposure.

Radiology 131: 284-296 (1979),

Land, C. E., Boice, J. D., Jr-, Shore, R. £., Norman, J. E+, and
Tokunaga, Me, Breast Cancer Risk from Low-dose Exposures to Ionizing
Radiation: Results of Parallel Analysis of Three Exposed Populations
of Women. J. Natl. Cancer Inst. 65: 353-376 (1980).

Waterhouse, J., Muir, C., Shanmugarathan, K., and Powell, J., Eds.,

“Cancer Incidence in Five Continents”, Vol IV. International Agency ach
for Research on Cancer, Lyon, 1982. ct
Baral, E., Larsson, L., and Mattsson, B., Breast Cancer Following ry
Irradiation of the Breast. Cancer 40: 2905-2910 (1977). ed

Tokunaga, M., Land, C. Ee, Yamamoto, T., Asano, M., Tokuoka, S.,
Ezaki, H., and Nishimori, I., Breast Cancer in Japanese A-bomb
Survivors. Lancet 2: 924 (1982).

- 268 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

Fig X-]-a-5

CHRONIC GRANULOCYTIC LEUKENIA
EXPOSURE AGE 40

100

so

20

16

40 70

Male ——
AGE AT DIAGNOSIS fale ——

- 135 -


3.

of the esophagus, stomach, colon, lung, breast and kidney and
bladder.

In addition to the uncertainty which results from prospect—
ive revision of the A-bomb dosimetry, additional uncertainty
follows from the fact that the low-LET radiations in that
situation were high-energy gamma trays, while 250kVp X rays, in
experimental situations, have been reported to be more effective
by a factor of 2 or 3 at doses on the order of two or three rad
(32,41,42). This will not affect the use of the tables in
cases where the radiations ia question are hard gamma rays, as
for workers in nuclear power plants or persons Present at tests
of nuclear weapons.

Combined Uncertainty

Recapitulating the uncertainties, and combining them, we
have:

Source G.$.D.(S1)
Baseline values
Esophagus and liver cancer 1.53
Salivary glands, thyroid, lung & stomach cancers 1.36
All leukemia except chronic lymphatic 1.10
All other cancers 1.17
Effect of age at exposure . 1.23

Time responses

Leukemia & bone cancer 1.10
Other cancers 1.15
Ratio of the L to LQ linear coefficient 1.43

(Except breast & thyroid cancer)

Latent period (years 5~14 after exposure only)
(Except leukemia and bone cancer)
with bias correction factor = 0.71 1.19

Risk coefficteats derived from A-bomb survivors
Leukemia, cancers of esophagus, stomach,
colon, lung, breast, kidney & bladder
with bias correction factor = 1.62 i.l7

Risk coefficients for other tabulated cancers 1.17

The combined uncertainties for each form of cancer are shown in
Table VII-7,

Effect of Uncertainty of Risk upon the Probability of Causation

To obtain a 90 percent “eredibility interval” for the PC

- % -



Millirem
1/1000 of a “rem.”

Mortality (rate) ~

the rate at which people die from a disease, e.g., 2 specific
type of cancer, often expressed as number of deaths per 100,000
per year.
Multiplicative interaction model (MIM) -
the assumption that the relative risk (= the relative excess risk
plus one) resulting from the exposure to two risk factors is the
product of the relative risks from the two factors taken separately.
NAS -
National Academy of Sciences.
NCRP -

National Council on Radiation Protection and Measurements.

Neutron -

uncharged subatomic particle capable of producing free radicals in
matter by indirect fonizarion.

Norgal distribution ~
a random variable X is said to be normally distributed if, for some
number p and some positive number 0, Y = (X - y)/o has a standard
normal distribution with probabilicy density function
fy) = (20) 3/2 exp(y2/2).
NRC -
National Research Council (in this report); a unit of the NAS.
PC = probability of causation -
a number that expresses the probability that a given cancer, in a
specific tissue, has been caused by e previous exposure to a carcinogenic
agent, such as radiation; essentially synonymous with “assigned share.“ H
Probability of causation —
see PC,

Projectfon model ~

a mathematical model that simultaneously describes the excess cancer

- 351 -


Table PC-1-B-10, Acute Leukemia Following Exposure at Ace 12,
by Ace Az at Diagnosis, Sex, and Dose in Rad oF Low=LET
Radiation. PC in Percent, ta Two Significant Digits or
Three Decimal Places.

aD Sex
Male Female
Dose

1 19 ida 1 1g 12a
t2 er) 10. 94 3.3 $4.
13 3.6 33. $.5 33. 92.
14 a.1 49. 8.8 $i. 95.
35 8.3 49. 9.8 54. 95.
16 7.6 47. 9.8 54. 95.
17 .8 44, 8.8 $1. 95.
18 6.1 41, 7.58 $7. 94,
19 3.6 39. 6.1 at $2.
20 5.2 3. 3.0 36. gi,
ral 4.7 35. 4.1 34, 89.
22 4.t 3. 3.4 27. 37.
23 3.4 27. 2.9 24, 84.
24 2.8 24. 2.4 at. 82.
25 2.3 21, 2.1 18. 89.
26 2.0 18, 18 te. 77,
27 1.6 1S. 1.5 1g, 74.
28 1.4 13. 1.3 12. 74,
29 1.2 WW. 1.1 1a. 67.
34 99 9.7 +95 9.4 64,
31 .84 8.4 8! 8.) 6a,
32 +72 7.2 .67 6.8 56.
33 62 $.3 +56 5.7 $1.
34 SS 3.4 48 4.8 45.
35 «46 4.7 39 G.0 42.
36 39 G4 33 3.4 38.
37 +34 3.6 28 2.9 34,
38 .30 3.1 .23 2.5 30.
39 +26 2.7 20 2.t 27.
40 +22 2.3 17 1.8 24.
at 19 2.0 5S 1.5 2t.
42 1§ t.? ft 1.3 19.
43 13 1,4 10 tt 16.
a4 10 1.1 ~08$ «90 14,
45 086 ot 068 73 1,

- 282 ~


Table PC+f-a-40. Chronic Granylocytic Leukemia Following
Exposure at Age 40, by Age Ay at Diagnosis, Sex, and Desa
in Rad of Low-LET Radiation.“ PC in Percent, to Two
Signiftcant Digits or Threa Becimal Places.

Ae Sex
hl fale Female
Dose

1 10 190 D Te 100
42 1,6 15. 75. 3.1 tt. 63
43 3.9 31. 8s. 2.9 24. 84.
44 4.6 34. 90 3.6 23. 37
45 4.7 3, 90. 3.8 ae, 8
46 4.4 33. 99. 3.8 3. 88
4“? &.F 32. 8. 3.6 25. 87
43 3.7 23, as. 3.1 25. 8s
4s 3.2 26. 86. 2.5 22 33
$e 2.6 23. 83. 2.1 19, eo.
$1 2.2 20. Bi. 1.7 16 77,
32 1.9 17, 78. 1.8 14, 74,
33 1.6 18, 735. 1,3 13 72.
56 1.3 13. Tt, 1.2 12, 69.
55 Td 41. 68. 1.4 4t. 67,
$é -96 9.5 64. 99 9.7 65.
57 «83 8.2 Gt, 89 8.8 62.
38 od 7.2 57. «79 7.9 60.
$9 61 $.2 $3. «70 7.1 $?,
6c 53 $.5 50. ~62 4.3 54,
61 47 6.8 6S. +35 3.6 BS,
62 Gt 4.3 $3. «49 3.0 48.
63 37 3.8 G1 +43 4.5 44.
64 33 3.5 38. +38 3.9 at
65 +30 3.2 36. +33 3.46 38.
66 +2? 2.9 34, +29 3.4 35.
@? +25 2.6 3. «26 2.7 32.
68 +22 2.4 29. +26 2.5 3t.
69 +20 2.1 27. +24 2.5 30.
70 18 9 25. +23 2.4 30.
7 Pary 1,? 22. +22 2.3 29.
72 114 1.5 20. «20 2.t 27.
73 Pars 1.3 ig. ii? 1,8 24.
746 to ty 16. 214 1.5 21.
78 099 96 14. 12 1.3 18.

~ 277 +


linear-quadratic models with Tespect ¢o total mortality from all types of
cancer other than leukemia, considered as a group (reference 2, Tables
V-i9 and ¥-20). The ratio of these coefficients,

e1/e19 = 3.470/1.397 = 2.48 = 2.5,
and the crossover dose of 116 rad weré used by the Working Group to

convert the BEIR IIT linear-model coefficients to the corresponding
linear~quadratic coefficients for the appropriate sites.

The present radioepidemiological cables have been prepared primarily
for low-LET radiation exposures. The tables and algorithus may, however, be
applied to high-LET radiation exposures by substituting for dose the "bio-
logically equivalent dose" (BED) determined for the particular exposure.
This calculation involves the assumption that for high-LET radiation the dose-
response relationship is approximately linear, which may be justified for doses
below 10 rad. In its simplest form, the BED is the product of the dose in rad
and a “relative biological effectiveness” (RBE) factor for the given radiation
{see Chapter III-B). ‘The RBE factor depends on the end point selected and
varies with the dose and with the LET of the radiation, which is a function
not only of the energy of the incident radiation but also of the attenuarion
and scatter in the tissues surtounding the target tissue. for internally
deposited radionuclides, estimates of equivalent doses are further complicated
by spatial and temporal variations in the distribution of the sources of
radiation. Therefore for a best estimate of the cancer risk from a given
exposure Co high-LET radiation, biologically equivalent doses must be
calculated on a case-by~case basis, and it clearly would make little sense
to produce separate PC tables for any given high-LET radiation. Exposure
of bone to high~LET radiation from internally deposited radium=-224 and
lung exposures from radon daughters are a special case since since there
is a direce observational basis for risk estimation (see Chapter X-2 and X~9).

aeees

The calculation of BED is a complicated process, and particularly so
for radiation from internally deposited radionuclides. The Ad Hoc Working
Group has made no attempt to Pursue the issue beyond this point.

Considerations of dose rate and dose-fractionation effects influenced
the Working Group's choice of the linear~quadratic model for cancer sites
other than the breast and thyroid (see Chapter ITI-I). By treating ex-
exposures widely separated in time as independent, and therefore additive
in effect, 2 model-dependent approach co dose rate was obtained. The
sctentific basis for this procedure is that repair of DNA sublesions is
Tapid, generally occurring withia hours following irradiation. Consider
a case in which exposures to D) and Do rad occurred during successive :
months. Under the linear model, the effects of the two exposures are a
proportional to Dy and D9, respectively, and their combined effect is
therefore proportional to D] + O27, just as if the two exposures had
occurred simultaneously. Thus for Fast neutrons and alpha particles in the
lower-dose range (below 19 rad), and for low-LET radiation in the case of
breast cancer or thyroid cancer, there is no reduction in effect due to
fractionation or protraction of exposure. Under the linear~quadratic
model, on the other hand, the effects of the two exposures are proportional
to Dy + Dy“/ 116 and Dy + Do*/116, respectively. The combined effect is
Proportional to the sum of these two mumbers, and is less than the effect

aa]
ead

- 56 -


Chapter IV: THE PROBABILITY OF CAUSATINN

A. General

The word “probability” has a number of definitions, but even more
protean is “cause” or “causation.” We are satisfied that the “cause” of
the light going on is the closing of che electric circuit. But what is
the “cause” of a case of tuberculosis? The answer is usually “infection
with the tubercle bacillus, of course." But the inhalation of a modest
oumber of tubercle bacilli will be followed by clinical disease in only
a minority of persons or experimental animals. Some individuals are more
susceptible than others. Ts the “cause” of clinical disease in a given
person the bacillus or the susceptibility, or both? Those who consider

this example strained might reflect that, 100 years ago, virtually everyone

who lived in a crowded, poor, urban environment was infected by tubercle
bacilli, yet only a minority contracted clinical disease. In some sense,
in that situation, the “cause” of tuberculosis was susceptibility.

The above is preliminary to a definition of what we mean here by
“probability of causation." We must define the term not only precisely,
but so that it leads to a unique mathematical formulation that will
govern the calculations required for the radioepidemiological tables.
The definition that we give below is the operational definition for this
expression. The definition carries with it certain implications, some of
which reflect important policy decisions.

B. Definition

Let a particular possible outcome event be denoted C. Let X (a
vector) denote the particular set of individual characteristics. Denote
the presence of a possible cause by D and its absence by D.

Then P(C, D;X) is the probability of outcome C if_D is present,
conditional on the characteristics X. Similarly, P(C, D;X) is the prob-

ability of outcome C if D is not present. Then D is a possible “cause”
of C only if

PCC, D;X) > PCC, D;X).
Define Ex(C, D;X) = P(C, D;X) - PCC, D;X).

as the increase in the probability of C due to the presence of D. Then,
the probability of causation of C by D, the PC, is defined as:

PC(C, DX) = Ex(C, D3X)/P(C, DjX)- (Iv-1)

In words, the PC is defined as the increase in the probability of C
due to D as a proportion of the probability of C given D, everything
conditional on the characteristics X.

Note that the PC does not allocate causation as between character-
istics X and Y. If, For example, the event C is the occurrence of lung

- 42-


53.

54.

55.

56.

57.

58.

59.

60,

61.

62.

63.

64.

65.

Edling, C., Lung Cancer and Smoking in a Group of Iron Ore Miners,
Am. J. Ind. Med. 3: 191-199 (1982).

Radford, E. P. and St. Clair Renard, K. G., Lung Cancer in Swedish
Iron Miners Exposed to Low Doses of Radon Daughters. ‘Ne Engl. J. Med.
310: 1485-1494 (2984),

Thomas, D. C. and McNeill, K. G., "Risk Estimates for the Health Effects
of Alpha Radiation” (INFO-0081). Atomic Energy Control Board, Ottawa,
Canada KIP 589, 1982.

Archer, V. E., Wagoner, J. K. and Lundin, F. E., Uranium Mining and
Cigarette Smoking: Effects on Man. J. Occup. Med. 15: 204-211 (1973).

Damber, L. and Larsson, Le G., Combined Effects of Mining and Smoking in

~
the Causation of Lung Carcinoma, Acta Radiol. Oncol. 21: 305-313 (19B2).-

Larsson, L. G. and Damber, L., Interaction between Underground Mining and
Smoking in the Causation of Lung Cancer: A Study of Non-Uranium Miners
in Northern Sweden, Cancer Detect. Prev. 5: 385-389 (1982).

Whittemore, A. S. and McMillan, A., Lung Cancer Mortality Among U.S.
Uranium Miners: A Reappraisal, J. Natl, Cancer Inst. 71: 489-499 (2983).

Jacobi, W., Paretzke, H. G., and Schindel, F., Lung Cancer Risk Assessment
of Radon-Exposed Miners on the Basis of ‘a Proportional Hazards Model.

In “Proceedings of the International Conference on Occupational Radiation
Safety in Mining”, Oct. 14-18, 1984, Toronto, Canada, in press.

Lundin, F. E., Jr., Wagoner, J. Ke, and Archer, V. E., "Radon Daughter
Exposure and Respiratory Cancer: Quantitative and Temporal Aspects.”
National Institute for Occupational Safety and Heaith, National
Institute of Environmental Health Sciences Joint Monograph No. 1,
National Technical Information Service, Springfield, VA, 1971.

NCRP Report No. 78, “Evaluation cf Occupational and Environmental
Exposures to Radon and Radon Daughters in the United States.” National
Council on Radiation Protection and Measurements, Washington, D.C., 1984.

Barley, N. H. and Pasternack, B. S., A Model for Predicting Lung Cancer
Risks Induced by Environmental Levels of Radon Daughters, Health Phys.
40: 307-316 (1981).

Jacobi, W., The New ICRP Recommendations on Occupational Limits for
Radon Daughters, in: “Radiation Hazards in Mining” (M. Gomez, Ed-),
pp. 503-510. Society of Mining Engineers of the American Institute

of Mining, Metallurgical and Petroleum Engineers, Inc., New York, 1981.

ICRP Publication 32, “Limits for Inhalation of Radon Daughters by

Workers.” International Commission on Radiation Protection,
Pergamon Press, Oxford-New York, 1981.

- 267 -



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- 163 -


the tumor. Assigning to each known carcinogen its share of responsibility
in the process, however, requires far more information than is presently
available in quantitative form, and the Working Group has been able to go
no farther in this direction than to account for the influence of smoking
status in instances of lung cancer (see Chapter VI-H}. The PC calculations
ere unaffected, however, by exposure to carcinogens which interact multi-
piicatively with lonizing radiation. Finally, if completeness of ascertain-
ment for slowly progressing tumors, like thyroid cancer, has been greater
for exposed subjects than for the general population, an upward bias is
introduced into any PC calculation.

N. Effects of Variation in Density of Energy Deposition (LET)

The above discussion has dealt largely with low-LET radiation. There
are, however, two exceptions: the tables for bone cancer apply only to alpha
radiation from radium=224, and tentative estimates have been provided for lung
cancer following exposure to alpha particles from inhaled radon daughters. -
Data on the induction of bone cancer by low-LET radiation are inadequate
as a basis for PC estimation and the Working Group, following the BEIR
Ill report, has used the medical experience with radium-224 as a basis for
PC estimation, but with no intention that it be applied to the long-lived
isotopes of radium much less to low-LET radiation. This means that the
bone tables are of very restricted applicability.

Although the Working Group has assumed, throughout, that X and gamma
radiation are equivalent in terms of RBE, this is not strictly so since the
LET and, therefore, generally the RBE for any given type of radiation,
will diminish as the energy is increased. For this reason, energetic
gamma radiation is less effective than 250kV¥p X rays. The difference is
relatively small at higher doses and dose rates, but may be quite signifi~
cant at low doses and dose rates. For example, for mutations in Tradescantia
and chromosome aberrations in animal cells, cobalt-60 gamma radiation at
low doses was observed to be between 3/3 to 1/2 as effective as the
reference 250kVp X radiation (32,33). This implies that at low doses and
dose rates exposures to energetic gamma radiation is less damaging than
exposure to so-called ortho-voltage X rays and that the tables will yield
PC's in excess of the crue values. It also implies that, insofar as some
of the site-specific risk factors derive in part from the Hlroshima—Nagasaki
experience, these risk factors may be somewhat lower than they would for
kVp X rays. The Working Group does not have the data that would allow it
te address this issue at the computational level.

oO. Propagation of Uncertainties and Their Effect upon the Probability of
Causation

Table VII-6 summarizes the various sources of uncertainty, how they
were handled, their estimated magnitude and how their resolution by the
Working Group may have influenced the PC values that can be calculated
from the procedures detailed here. It is desirable to estimate the
effect that these uncertainties, acting jointly, may have on the calculated
value of the PC.

-$91-



ll. Cancer of Kidney or Bladder (188, 189.0, 189.] in ICDA~8)

Sensitivity to the carcinogenic effect of ionizing radiation is con-
sidered to be relatively low for both the kidney and the urinary bladder.
Reported dose-specific risks are seldom high and in some studies no
excess cancers have been found. Malignant tumors of the kidney, of the
bladder, or of the undifferentiated “urinary organs” have been reported
to be increased in frequency among the A~bomb survivors, persons treated
with irradiation of the spine for ankylosing spondylitis, persons who
received injections of Thorotrast in retrograde pyelography, and persons
with cervical cancer treated by radiation (4,23). In some studies the
relationship with radiation dose is uncertain or simply not demonstrable,
and the data from the cervical cancer series are especially inconclusive
(5). The strongest relationship is seen in the mortality experience of
the A-bomb survivors over the period 1950-1978 (28), especially since it
appears within each sex and within each city, but death certificate
diagnoses are much less reliable for these sites then for many others.

The BEIR III coefficients, adjusted to the period 11-30 years after
exposure, have been used itn the PC calculations as described in Chapters
Vi and IX, except that estimates were not made for those under age 20 at
exposure for the reasons given in Chapter VII~F.

The normal or baseline risk of cancers of the kidney and bladder has
been taken from the data bank of the SEER program of the National Cancer
Institute (8). The rates are for the period 1973-1981, for all races
combined, and for all reporting areas combined except Puerto Rico. There
is appreciable geographic variation within the US (see Tables VII-1 and
VII-2) that apparently rests on differentials in industrial exposures
that are of major importance for cancer of the bladder (85). Exposure to
dyestuffs, rubber, leather, and certain organic chemicals has been associated
with excess cancer of the bladder (86).- An association between cigarette
consumption and bladder cancer is well documented, and there is some
evidence of an association with cancer of the kidney (85). As noted in
Chapter IV-G and in Chapter 1X, risk factors other than ionizing radiation
may be taken into consideration in interpreting the PC values derived by
the procedures presented here. If it 1s believed that some other risk
factor operates additively with radiation, and the individual is thought
to have been exposed to that risk factor to an extent greater than the
average for the population generally, then the PC obtained from the present
procedures may be somewhat excessive. But if it is believed that the
second risk factor may combine with radiation to enhance risk in multipli-
cative fashion, the PC estimates based on these procedures should be
unbiassed.

The Working Group had no information available to it concerning the
most appropriate dose-response function for cancers of the kidney and
bladder, or the most suitable time-response function, or whether radiation
may interact with other risk factors in multiplicative or additive fashion.
It chose, therefore, to employ the preferred linear-quadratic model of
dose-response, with no threshold, and the constant relative risk model
for distributing excess cancers over time. The minimum latent period was
taken as 10 years but smoothed as described in Chapter V-C.

~ 249 -


radiation does not create unique forms of cancer, but increases the risk
of some cancers that occur naturally. For the acute forms of leukemia,
chronic granulocytic leukemia, and female breast cancer, the association
is so strong as to appear certain (4). There is fairly strong evidence
that ionizing radiation does not cause chronic lymphatic leukemia (4,6).
For wost other forms of cancer, the evidence lies somewhere between these
two extremes, although for many the position on this scale is uncertain
because there is very little information. .

Lee

The credibility of a presumed causal association between risk and
radtation exposure depends upon several factors, which must be considered
in evaluating the evidence that radiation exposure affects risk for a
particular cancer site:

vend

1) Statistical significance ~ This depends on the total
number of cancer cases observed and the apparent size of
the excess relative to the baseline risk. For a fixed
number of cases, the strength of the association is
greater if the excess risk is relatively large and, for
a fixed relative excess, the association is more credible
if the evidence is based on many cases.

2) Specificity - How certain is it that the association
was not due to something else? Credibility is helped by
comparison with a non-exposed population, otherwise similar
to the exposed population. It is especially important to
satisfy this requirement in studies of medically exposed
populations, for which the conditions leading to exposure
may themselves be related to the risk of subsequent cancer.
Since population groups that have been exposed to radiation
actually differ in many ways from the general population,
differences in rates of disease from general population
rates may be difficult to interpret or to attribute to the
radiation exposure.

3) Dose response — The level of risk should appear to
increase with increasing radiation dose to the tissue

of interest. Each of us is exposed to natural background
radiation at the very least, and so the concept of increased
risk from additional exposure involves the assumption of a
gradient of risk with increasing exposure. As already
mentioned, it is always possible that an increased risk among
medically exposed persons may be attributable to the reasons
for exposure rather than ro the exposure itself. This possibility
is less likely if there is an association of risk with level of
exposure among the exposed persons.

4) Consistency - 1s the association seen in a number of
exposed populations, and are the apparent excesses similar
when such Factors as dose, age, and period of observation
have been taken into account? “Statistically significant”
associations will occur as a consequence of mere chance in a
small proportion of studies ~ and in the field of radiation
carcinogenesis the number of studies is large. Further, spur~

- 16 -


7. Cancer of the Liver (155.0 and 197.8 in ICDA-8)
wancer of the Liver

Primary cancer of the liver is wel] known as a late effect of radlo-
graphy employing the contrast medium, Thorotrast, a colloidal thorium
dioxide compound emitting alpha particles (2,4,40). There is, however,
some uncertainty as to the etiologic significance of its chemical vs. its
radiation properties. Human data on the assoctatfon between ionizing
radiation and liver cancer are otherwise Sparse. In the British series
of ankylosing spondylitis patients treated hy X rays no excess liver
cancer was found, but the liver was classified as one of the “lightly
irradiated sites", for which the observed numbers of deaths from cancer
were not significantly greater than expectation based on the British 3
mortality statistics (3). The 1977 UNSCEAR report (2) provides a “tenta~ :
tive risk assessment” of 10-20 excess cancers per million persons per rad
of alpha radiation. With a mean latency of 25 years these coefficients
become approximately 0.40 to 0.80 per million per year per rad. The BEIR
HII report (4) provides an estimate of 300 per million persons per rad of
alpha radiation, 15 per million persons per rad of low-LET radiation on
the assumption of a RBE of 20, and an annualized risk coefficient of 0.70
excess cancers per m{llion per year per rad of low-LET radiation.

The most extensive human data on liver cancer following external ex-
posure to ionizing radiation derive from the experience of the Japanese
A-bomb survivors: 55 incident cases in Nagasaki (29) and 118 in Hiroshima
(30). The Nagasaki Tumor Registry report for 1959-1978 yields a risk
estimate of 0.70 + 0.52 excess cancers per million persons per year per
rad (29), and the Hiroshima Tumor Registry for the same period an estimate
of 0.72 + .18 (30). The death certificate diagnoses for the Life Span
Study sample of 82,000 A-bomb survivors have vot been tabulated for liver
cancer in the most recent report (1950-1978) (28) but cancers of the
liver are included in rie category of “other or unspecified digestive
organs,” that is, cancers of digestive organs other than the esophagus,
Stomach, pancreas, colon, and rectum and rectosigmoid junction. Thus,
cancer of the liver is a significant Part of the "all other" category
that includes 595 deaths and for which a test of trend with dose returns
a highly significant p of .0033.

None of the reports cited Provides age- or sex-specific risk esti-
mates for cancer of the liver, but trend tests on the age-specific mortal-
ity tables of Kato and Schull (28) for “all other” gastrointestinal
organs yield p-values as follows for the observed numbers of deaths in
tests of the relation between mortality and dose:

pin Test of
Age at exposure Number of deaths Trend with Dose
0-9 4 264 ,
10-19 30 202
20-34 82 +08
35-49 284 204
50+ 195 +20

- 218 -


for younger individuals having been judged insufficient for the present
purpose (Chapter VII-F). The BEIR coefficients were, however, adjusted

to the period 11-30 years after exposure, There appears to be no published
analysis of dose-response functions appropriate for the pancreas, and the
available data are too few to make such analysis very meaningful. Accord-
ingly, the Working Group has employed the preferred linear-quadratic
dose-response model for this site as for most of the solid tumors.
Similarly, although time-response models have not been explored, the
Working Group considered that the constant relative risk model was a
reasonable choice.

The baseline data needed for the calculation of PC values have been
taken from the data tapes for the SEER program of the National Cancer
Institute for the years 1973-1981 and for all Taces combined and all
areas combined except Puerto Rico. Published data for the reporting
areas in the period 1973-1977 show only a moderate degree of variation,
but an appreciable difference between the sexes, males having the higher
rates (8). (See Tables VII-1 and VII-2.)

Cancer of the pancreas is also associated with alcohol consumption,
exposure to certain chemicals, and smoking (47). The Working Group found
no information on the pattern of interaction between such well-established
visk factors and radiation. As noted in Chapter IV-G and in Chapter IX,
tisk factors other than tonizing rad£ation may be taken into consideration
in interpreting the PC values derived by the procedures presented here.

Ef it is believed that some other risk factor operates additively with
tadiation, and the individual is thought to have been exposed to that

risk factor to an extent greater than the average for the population
generally, then the PC obtained from the present procedures-may he somewhat
excessive, But if it is believed that the second risk factor may combine
with radiation to enhance risk in multiplicative fashion, the PC estimates
based on these procedures should be unbiassed.

The procedures for calculating PC values for the pancreas are based
on the principles and assumptions of Chapter V and the procedures of
Chapters VI and LX. As with most sites, for cancer of the pancreas the
relative excess, R, in the basic equation

PC = R/(1 + RD
is found as the product of three functions, i.e.,
R= F(D) x T(¥) x K(Ay,S)
where F(D) represents the influence of the Low-LET tissue dose (D), T(Y)
Tepresents the variation in R over cime in years (Y) after exposure, and
K(A4),S) tepresents the relative excess of Pancreatic cancer for a person

of age Ay and sex $, when both F and T = 1,

Under che linear-quadratic dose~response model assumed for pancreatic
cancer, when exposure is to low~LET radiation

F=p+ p2/116,

- 226 -

4



1?,.

18,

Hogan, M. D., Chi, P., Hoel, D. G. and Mitchell, T. J., Association
Between Chloroform Levels in Finished Drinking Water Supplies and
Various Site-Specific Cancer Mortality Rates. J. Exp. Pathol. Toxicol.
2: 873-887 (1979),

Popovic, M., Sarin, P. S., Robert-Gurroff, M., Kalyanaraman, V. S.,
Mann, D., Minowada, J., and Gallo, R. C., Isolation and Transmission
of Human Retrovirus (Human T-Cell Leukemia Virus). Science 219:
856-859 (1983).

-12-


is almost certainly in the range from 33 rad to infinity. The
ratios which correspond to those values are 6.3 and 1, with a
geometric mean of 2.5. If the probability that the stated
range does cover the true value is assessed at 99%, then the
G.8.D. for the ratio is 1.43 = 6.31/5+12, This value applies
to all cancers except breast cancer and thyroid cancer, for
which a linear dose response model has been used.

An infinite cross-over value, which corresponds to the
value of 1.0 for the ratio E,/E,g, characterizes the linear
dose-response model. The pure quadratic dose response model
would correspond to a cross-over value of zero tad, and an
infinite ratio. Even for a cross~ovet value as low as 33
rad, the dose-squared term adds no more than 15 percent to
the effective dose for an organ dose of 5 rad.

Biassed Uncertainties

o Latent Period. There seems little doubt that beyond 15
years from exposure, the full radiation risk applies for ali
cancers except leukemia and bone cancer and that at least five
years is required for a radiation exposure to result in an
overt cancer. The Working Group has chosen to calculate PC's on
the assumption that full expression occurs as early as 10 years
after exposure and has assumed that risk rises in a smooth way
from the fifth to the tenth year. While there is little reason
to question the estimates on the basis of latent period except
in the interval 5 to 14 years, within that interval uncertainty
does exist. This uncertainty is biassed, in the sense that the
estiwates, if erroneous, are likely to be erroneously high.

If it be supposed that, in the interval 5 to 15 years, the risk
estimate is, with credibility 95 percent, between one-half of
that embodied in the Working Group's formula, and the full
value, then the range .50 to 1.00, with geometric mean 0.73
(bias correction factor) has a G.$.D, of 1.19.

o Risk Coefficients. Many, but not ali, of the risk
coefficients used here are based mainly upon the experience
of the Japanese A-bomb survivors; the exceptions are for can~
cers of bone, salivary glands, liver, pancreas, and thyroid
gland. Recently it has become apparent that the dosi-
metry system, designated T-65, upon which the Japanese data
are based, was seriously in error (34-36). An intensive
effort co provide a new and better dosimetry system is under
way (37,38) but has not yet been completed at this time
(December, 1984), Estimates have been provided, however, of
the changes that may result in the dose-effect coefficients
for gamma rays, by Fujita as increases by a factor of 1.2 to
1.7 (39) and by Jablon as 1.6 to 2-2 (40). If it is assumed
that a 95 percent credibility interval on the factor ranges
from 1.2 to 2.2, the geometric mean would be 1,62, with a
G.S.D. of 1.17. These values would apply only to those cancers
for which the BEIR TII risk estimates were based, in large part,
upon the A-bomb survivor experience: the leukemias and cancers

~ 95 -


Wee.

na

APPENDIX III - GLOSSARY

Absolute risk —

an expression of excess risk based on the assumption that the excess
risk from radiation exposure adds to the underlying (baseline) risk,
by a constant increment dependent on dose; an absolute risk time-
response model distributes the radiogenic risk after exposure
independently of the underlying natural risk.

Additive interaction model (AIM) -

the assumption that the total excess risk from exposures to radiation
and to another risk factor is equal to the sum of the excess risks
from the.two taken separately.

Alpha particie -
a charged particle emitted from certain unstable atomic nuclei (radio-
active elements), having the physical characteristics of a helium
nucleus (mass 4, charge 2+).

Ankylosing spondylitis -
arthritis of the spine.

Assigned share -
a number that expresses the probability that a given cancer is caused
by a previous exposure to a carcinogenic agent, such as radiation; here
synonymous with “probability of causation” (PC).

Ataxia telangiectasia (AT)
an inherited disorder associated with an increased risk of cancer,
lymphoma in particular, and characterized by immunologic, chromosomal,
and DNA defects.

ATB ~

at the time of the bomb; referring to the dropping of the atomic
bombs at Hiroshima and Nagasaki in 1945.

Background radiation >

the amount of radiation to which a member of the population is exposed
from natural sources, such as terrestrial radiation from naturally
occurring radionuclides in the soil, cosmic radiation originating in
outer space, and naturally occurring radionuclides deposited in the
human body, The natural background radiation received by an individual
depends on geographic location and living habits. In the U.5., the
background radiation is on the order of 100-200 mrem per year.

- 345 -



ESTIMATED PROBABILITY OF CAUSATION (PERCENT 3}

Fig X-1-C-6

LEUKEMIA: ALL TYPES EXCEPT CLL
EXPOSURE AGE 50

100 :
100 RAD
-)
i
20 =
10
s
2
S
sw
1 RAD way
; ferry ;
so 55 60 6S 70 7s to 8s
Male ——

AGE AT DIAGNOSIS fale

- 152 ~


Table PC-2-20. Bone and Joint Cancar Following Exposure at
at Diagnosis, Sex, and Dore in Rad of
PC in Percent, to Two Significant Digits
or Three Decimal Places.

; Ay Sex
ul
~ Male Female
dose

1 to 190 1 10 109
21 . +055 .53 -007 .079 78
22 1 16, 66. 2.9 23. 75.
23 ia. 53. 92. 15. 64.
24 1 69. $6. 27, 78.
2s 2 75. $7. 33. 83.
26 2 77. $7. 3?. 8s.
27 2 77. 97. 37. 36.
23 2 76. 97. 36. as.
23 2 74, 97. 34, 84.
30 2 71, 96. 3}. 82.
33 1 63. 96. -28, 79. g
32 1 66. 9s. 2s. 7?. 9
33 1 64. $5. 24, 76. 3
34 1 62. 94, 24. 7, 9
35 1 6c. 94. zs. 77, 9
36 s) 38. 93. 26. 73. 9
37 ity 56. 93. 25. 76. 9
33 Vs, 34. 92. zt. 73. 9
39 10. $3. 92. $3, 69. 9
$o 9.2 so. ot. 15. 63. 93.
4) 8.4 £3. $o. 2. 53. 93.
42 7.3 44, 89. 3.5 51, ot.
43 $.8 38. BS. 7.6 45. 89.
44 4.3 3). 82. 6.0 33. Bs.
“5 3.2 25. 77. 4.7 33. 83.
46 2.4 20. an 3.8 28. 80.
47 2.0 7. 67, s.t 24. 76.
43 1.6 14, 63. 2.7 22. 74.
49 1.4 te. $8. 2.5 20. 72.
se 1.2 11, 5S, 2.3 19, 76,
$1 1.0 9.2 30. 2.0 7, 68.
52 +85 7.9 46. 1.7 13. 63,
$3 +73 6.8 $2. 1.3 12. 58.
$4 +62 $.9 38. if 9.9 52.
$5 +53 5.1 35. +88 8.2 4a?.

- 299 -


te bie

Tabla X-{-4.) Chronic Granulecytic Leukemia:
Temporal Distributian TCT) by Year ¥
After Exposure

Y TOY) Y TY)

8 Qo 2s 0128

t 0 26 +0126

2 +0146 27 0015

3 10384 28 0109

4 +6461 29 6103

5 0472 30 1009382
6 0456 33 00934
? 0431 32 00889
8 0402 33 60857
9 0374 34 00808
10 0367 35 00774
11 +6322 36 00736
12 0298 3? 60704
13 0277 38 03673
14 +0258 33 00646
1$ 0240 60 00617
16 +0224 «1 109592
‘7? 0209 $2 00568
18 0196 43 60565
19 9186 4% 00523
20 20172 $5 00503
21 -0162 46 00685
22 +9152 4? 00665
23 9166 8 00447
24 0136 49 00631

- 155 -


99¢000°  ze90R0" — z90D0" —_zzs000" Zeysoo” — vyyo00- erage:
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159 =


role of DNA or chromosomal damage in carcinogenesis (61-66), the heritable
nature of the neoplastic transformation in somatic cell lines, and che
linear-nonthreshold nature of the dose-effect relationship for radiation-
mutagenesis and chromosome eberration induction in the Low-dose region
(6,67) imply thac radiation-induced damage to the DNA or to the chromosomes
of a single somatic cell may, under certain conditions, exert a potentially
carcinogenic stimulus, even at the lowest radiation exposure level.

The extent to which host factors such as immune surveillance can
introduce a practical threshold by delaying the onset of detectable can-
cer beyond the life span cannot be calculated at present. The existence
of a complicated series of enzymes that repair DNA does not favor any par-
ticular mode] for interpolation of cancer incidence at low doses of radia-
tion, since repair does not operate with total effectiveness. In addition,
unless other carcinogenic agents act through unrelated mechanisms, the
heterogeneity of the human population and the baseline incidence of cancer
are high enough so that any dose of radiation may be conceived to increase
the risk of cancer in the most sensitive members of the population (68-70).
For these and other reasons, the assumption of a threshold for radiation
carcinogenesis is currently not considered to be tenable for purposes of
risk assessment.

f we are interested in the risk from lower-dose exposures, it is
necessary to have an extrapolation rule or dose-response model by which
the estimated high-dose risk determines lower-dose risk estimates. A
fairly simple rule is to assume that excess risk is proportional to the
number of ionizations produced in the tissue at risk, that is, proportional

to absorbed dose. This rule is equivalent co drawing a straight line from

a point representing zero excess risk at zero dose (natural background
radiation levels) to the point representing the excess risk estimated at
whatever dose was received by the population studied (the so-called linear
model), Other rules, not based on 2 simple proportionality between dose
and risk, cotrespond to curved lines. A general model widely accepted in
experimental and theoretical radiobiology for stochastic effects (muta-
genesis and carcinogenesis) of low-LET radiation allows for an unspecified
degree of positive curvature corresponding to interactions between two
tadiation tracks, and negative curvature, influential mainly at high dose
levels, corresponding to the competing effect of cell inactivation (4).
The model assumes that two ionizing events are more likely to produce a
biological effect if they occur very close together than if they are
separated; because ionizing events tend to be widely spaced along low-LET
tracks, closely-spaced events are likely to be at the intersections of
different tracks and their probabilities are approximately proportional to
the square of dose. A frequently observed, and related, ‘phenomenon is
that acute exposures to low-LET radiation tend to be more effective than
the same amount of radiation delivered continuously over time or delivered
in several fractions separated by periods of time. This, too, is thought
to reflect variations in the likelihood chat two ionizing events will
occur close together in time and space. Such an occurrence is less
likely if the events are not simultaneous, because the damage caused by
the first ionizing event may be repaired before it can interact with the
damage from the second event.

-~ 24 -

J



wSeooge” = Sti 000"

yev00"
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- 165 -


40,

41.

42.

43.

44.

45.

46,

47.

48,

49.

50.

51.

52.

Mays, C. We, Ed., Biological Effects of 224Ra and Thorotrast.
Proceedings of an International Symposium. Health Phys. 35: 1-174,
(1978).

Falk, He, Liver. In "Cancer Epidemiology and Prevention”
(D. Schottenfeld and J. F. Fraumeni, Jr. Eds.}, pp. 668-682.
W. B. Saunders, Philadelphia, 1982.

Steer, A., Moriyama, I. M., and Shimizu, K., ABCC-JNIH Pathology
Studies. Hiroshima and Nagasaki. Report 3. The Autopsy Program
and the Life Span Study, January 1951 - December 1970. Technical
Report 16-73. Atomic Bomb Casualty Commission, Hiroshima, 1973.

Mancuso, T. F., Stewart, A., and Kneale, G., Radiation Exposures of
Hanford Workers Dying from Cancer and Other Causes. Health Phys.
33: 369-385 (1977).

Hutchinson, G. B+, MacMahon, B., Jablon, $-, and Land, C. E., Review
of Report by Mancuso, Stewart, and Kneale of Radiation Exposure of
Hanford Workers. Health Phys. 37: 207-220 (1979).

Gilberc, E. S., and Marks, $., An Analysis of the Mortality of Workers
in a Nuclear Facility. Radiat. Res. 79: 122-148 (1979).

Gilbert, E. S., and Marks, $., An Updated Analysis of Mortality of
Workers in a Nuclear Facility. Radiat. Res. 83: 740-741 (1980).

Mack, T. Me, Panereas. In “Cancer Epidemiology and Prevention",
(D. Schottenfeld, and J. F. Fraument, Jr., Eds.), pp. 639-667.
W. B. Saunders, Philadelphia, 1982.

Seve, J., Kunz, E., and Placek, V., Lung Cancer in Uranium Miners and
Long-term Exposure to Radon Daughter Products. Health Phys. 30:
433-437 (1976).

Archer, V. E., Gilliam, J. D., and Wagoner, J. K., Respiratory Disease
Mortality Among Uranium Miners. Ann. NY Acad. Sci. 271: 280-293 (1976),

DeVilliers A, J. and Wigle, D. T., Unpublished manuscript concerning
Newfoundland fluorspar miners. Cited in reference 4: "Effects on
Populations of Exposure to Low Levels of Ionizing Radiation: 19807,

ep» 322-323, National Acadeny Press, Washington, D.C., 1980.

Blot, W. J., Akiba, $., and Kato, He, Ionizing Radiation and Lung Cancer:
A Review Including Preliminary Results from a Case-Control Study

among A-Bomb Survivors. In: “Atomic Bomb Survival Data: Utilization
and Analysis” (R. Le Prentice, R. L. and De J. Thompson, Eds.), pp.
235-248. STAM (Soclety for Industrial and Applied Mathematics),
Philadelphia, 1984.

Axelson, 0. and Sundell, L., Mining, Lung Cancer and Smoking, Scand. J.
Work Environ. Health 4: 46-52 (1978).

- 266 -

oevinei


diagnosis (Y = 24). The second, to 2 rad, occurred 4 months later, at

the same age (Aj = 20) but 23 years and 10 months before diagnosis (¥ = 23).
At age 21, 23 years and 3 months before diagnosis, 9 rad total dose was
received over a 36-hour period at the continuous rate of 250 millirad per
hour (Y = 23). Finally, at age 35, three exposures, to 1.1, 0-6, and 0.7
rad, respectively, wete received on consecutive days, 9 years and 2

months prior to diagnosis (Y = 9).

i The first, second, and third exposures should be considered separate~
ly, because exposures 1 and 2 correspond to different values of Y, and ex-
posures 2 and 3 to different exposure ages. The $-rad continuous exposure
delivered over 36 hours should be treated as 2 exposures because it te~
quired more than one day, but less than two. The suggested partition assigns
a j-rad exposure to one 24~hour period and 6 rad to another. The three ex~
posures at age 35 can be treated as one because they correspond to the same
values of Ay and Y, and because the totel dose is less than 5 rad.

Exposure 1:

F(D) = F(1) = 1 + 12/116 = 1.01

T(¥)

T(24) = 1
k(20,£) = .0503
R) = Fx Tx kK = 1.01 x 1 x .0503 = .0508
Exposure 2:
P(2) = 2 + 22/116 = 2.03
T(23) = 2
K(20,£) = .0503
Ro = Fx Tx K = 2-03 x 1 x -0503 = «102
Exposure 3a:
F(3) = 3 + 32/116 = 3.08
1(23) = 1
K(21,f) = .0463
ma Ryg =F x Tx K = 3.08 x i x .0463 = 143
ry Exposure 3b:
F(6) = 6 + 62/116 = 6.31
T(23) = 1

K(21,f) +0463

Ryp = Fx Tx K = 6.31 x 1 x 20463 = .292

~ 221 -



Table ViI-2

Lergest and Saslleet Ratios of Individual Registry Age-Adjusted
Cancer Incidence Reces to Al] Areas Rate

Hates Fesales
Site Largest Kario Sws:lest Ratio Largest Ratio Smallest Ratio
Leukemia -
Acute 1.09 0.83 1.22 0.76 oo
(San Francisco) (Decroi¢) (Rewati) (Hew Mexico)
. Chronic
Granulocytic 1.22 0.78 1636 0.64
(lowa) Cutan) (Utah) (Seartle and
Puget Sound)
. All Forne® 1.33 0.90 1,07 0.86
(Detrote) Ciew Bexico) (Hewett) (CFew Mexico)
Bones & Jointe 1.3 0.8 LS 0.7
(atlanta) (CT & Detroir) (Utah) (Hevais)
Salivary 1.60 0.53 1.42 0.75
(Rev Orleans) Ulowa) (Sen Francisce) (Iowa and
rah)
Esophegua 1.32 0.47 1.37 0.26
(Detroit) (Wew Mexico} (San Pranciaco) (Utah)
Stomach 2b 0.70 2H 0.66
(Baveit} (Atlanta) (Hawaii) Clowa).
Colon 1.20” 0.65 ith 0.73
(Convecticut) (Kev Mexico) (Connecticut) (deah)
. Liver 2.7 O64 2.5 0.8
(Rewait) (tab) (Rawaii) (Seattte and
Puget Sound)
Pancrear 3.24 0.76 1.29 0.76
(atlanta) (Utah) (Hew Mexico) {Urah)
Lung & Bronchus 1.45 0.53 1634 0.38
(New Orlesne) (Utah) (San Francisco) (Orah)
Breast —_ —_ 1.12 0.83
+ (San Francisco) (Urah)
Thyroid 2.48 0.68 1.92 0.76
{Hewsit) {Jowa) (Hawaii) {lows}
> * Excluding chronic lymphocytic leukemia.

- 105 -


12. Thyroid Cancer (193 in ICDA~8)

The thyroid tables were constructed on the basis of the assumptions
and principles of Chapter V and the procedures described in Chapters VI
and IX. The risk coefficients used in making the tables, however, were
modified from the published BEIR III values and are given in Table VI~l.
The BEIR Ill coefficients were based largely on the exposure of children
and the data available in 1978-79, when the report was prepared, seemed
insufficient to support clinical impressions of age differentials in risk
(4). A-central value of 4.0 excess cancers per million persons per year
per rad was postulated on the basis of the literature available at that
time, and the female/male ratio of risk, 2.6, was taken from preliminary
data (40 clinical cases) on the A~bomb survivors (87) to yield estimates
of 5.8 for females and 2.2 for males, regardless of age at exposure.

Data concerning the incidence of thyroid cancer are especially uncer-
tain because of difficulty of ascertainment. Thyroid cancers are usually
indolent; they are often slow growing and may not cowe to medical attention
unless they are sought by active investigation. Since active screening for
thyroid cancer will often be undertaken upon population groups in which
it is suspected that thyroid cancers may have been induced by radiation,
excesses may be found, not only because the incidence is increased but
because diligent investigation has identified cancers that would otherwise
not come te attention.

Since the BEIR ILI report was prepared, additional data have been
published on the Israeli tinea capitis series (88) and on the A-bomb
survivors (29,89). In addition, the Working Group has had access to a
near-final manuscript on 178 clinical cases among the A~bomb survivors
(90). The Israeli series is limited ta persons who were children at the
time of exposure, but the recent reports on the A-bomb survivors contain
clear evidence of age variation in risk and also provide a more stable
estimate of the ratio of female to male risk coefficients, 3.5. The US
literature suggests an average risk coefficient of about 3.3 excess
cancers per million persons per year per rad for those exposed as children,
and the Working Group has employed this value, rather than 4.0, together
with the female/male ratio of 3.5, to obtain the final coefficients of
1.5 for males and 5.0 for females. Since the observed risks in A-bomb
survivors 20 or older at exposure are about one-third of those for survivors
exposed before age 20, this fraction was used to estimate approximate
coefficients for the older group, 0.5 for males and 1.5 for females.

Although there is some evidence favoring a minimum latent period of
5 years for thyroid cancer ($1), it was decided to use the standard
assumption of 10 years (smoothed over the interval 5-10 years) made for
all solid tumors as described in Chapter VC. Published dose-response
information on radiation-induced thyrofd cancer is not extensive, but it
clearly suggests linearity (91). In addition, in the large unpublished
series of Ishimaru et al. the excess thyroid cancer incidence among
A-bomb survivors is best fitted by a linear function of dose (90).
.Despite its general preference for the linear-quadratic dose-response
function, therefore, the Working Group chose to base its PC estimation
procedures for thyroid cancer on linearity. The distribution of radiation-
induced cases over time was assumed to follow the relative risk model

~ 255 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

so

20

16

Fig X+2~2

BONE AND JOINT CANCER*
EXPOSURE AGE 10

io 45s 20 25 390 3s 40 4s
AGE AT DIAGNOSIS fone

*Alpha radiation from radium-224 only

- 184 -


3 After Exposure to
Sex, and Dose

at Exposure,
40 or More per Day.

Smokers,
to Twa Significant Digits or Threa Decimal

ke

y Age A.

Lung Cancer 19 or More Year
for Prasent Cigaret

Low~LET Radiation, b

in Rad
PC in Percent,

Table PC-9-H.
Places,

Sax

eed

conn

Female

Mal@

Dose

ivenees

100

19

196

ROWMNKO ee ee te et et te ee ts
To EO OI SEF EI OD

NOW FRAN MENNE RN FORME YONA - - OC OBOOBO~—

NAOMMOMOM UAE FVOTM MINTO HO
OR OR OOIINE F FMM MMANNNANNUNNENR SE He en re
“BOS COO COC BOOT COSOECOCOCS

were
NT OND OE NE NOE HOO ENT DOR ONE ONT HORT TH OO
acoo0

real
TOOK ONE FMMMNUNANT HTT Tr ree Peer ec20Rn
200

- 330 -


ESTIMATED PROBABILITY OF CAUSATION {PERCENT}

300

$o

20

30

"Fig. X21

KIDNEY .AND BLADDER CANCER

T

100 8d
N 10 mad *s
36 20 30 i] “x0 60 ro *
ale
AGE AT EXPOSURE Female ~o-

- 253 -



ESTIMATED PROBABILITY OF CAUSATION { PERCENT)

100

3o

30

Fig. X-10

BREAST CANCER

“s
—
“~
s
a
.
‘
x
x
.
-
~ >
rs .
x
.
i ‘
» s
.
. ‘
30 ap’,
v
‘
. ‘
‘ 1
‘ ‘
4 \
\ ‘
N ~
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s .
“
wsy .
be
‘ . .
Ty 7
vere. \
‘ ‘
. ‘
\
‘ ‘
=o AY
io 20 a 40 $0 60 76
famste oon

AGE AT EXPOSURE

= 247 -



13. Excluded Sites

Although it is generally accepted that ionizing radiation may increase
the risk of virtually any form of cancer, for many sites compelling human
data on its causative role are lacking, and for still others the existing
data are inadequate for the present: purpose. For example, the BEIR III
report lists the following sites or tissues under the category of those
in which radiation-induced cancer has not been observed: prostate, uterus
and cervix, testis, mesentery and mesothelium, and chronic lymphocytic
leukemia. Sites or tissues in which the magnitude of the dose-specific
risk is uncertain are specified as: larynx, nasal sinuses, parathyroid,
ovary, and connective tissues (4). In addition, the BEIR III committee
presented estimates for lymphoma that no longer seem supportable; if,
indeed, certain malignant lymphomas are radiogenic, the evidence remains
too tenuous and inadequate to serve as the basis of PC calculations.
Although excess mortality from malignant lymphoma has been reported in
the British ankylosing spondylitis series (3), among the U.S. radiologists
(93), and among the Japanese A-bomb survivors (94), most of the evidence
has been based on death certificate diagnoses and on small numbers. No
statistically significant excess is evident in the most recent report on
mortality among the A-bomb survivors (28) or in the reports based on the
tumor registries (29,30). In their 1972 review of the evidence Anderson
et al. pointed to differences in the pathogenesis of leukemia and malignant
lymphoma and concluded chat radiation-induced malignant lymphoma can be
observed only following very high-dose, possibly near-lethal, exposures
(95). :

Mulciple myeloma is a special case, worthy of further discussion.
Popularized as a radiogenic form of cancer by the first Hanford report (43),
multiple myeloma continues to have uncertain status as a radiogenic tumor.
Cuzik has summarized the data From 12 irradiated populations in which some
association has been reported between multiple myeloma and exposure to
jonizing radiation, but these provide no basis for quantitative risk
estimates (96). Miller and Beebe have questioned Cuzitk's pooling of
dissimilar studies, some of which do not show a wave of leukemia before
suall excesses of multiple myeloma (97). Another perplexing factor was
that, in no study, no matter how heavy the dose, was the excess of multiple
myeloma more than marginal. A numerical basis for risk estimation can be
derived from recent reports on mortality from multiple myeloma among
A-bomb survivors (28,98) but histologically confirmed cases in the Nagasaki
Tumor Registry (29) and the Hiroshima Tumor Registry (30) are considerably
fewer and place the relationship in doubt.

Brain cancer has been reported in both of the tinea capitis series
(20,88) but not in suffictent numbers of provide stable statistical
estimates. Skin cancer is well-established as an effect of exposute to
ionizing radiaton but not to low doses. No threshold dose has been
agreed upon and there is no quantitative basis for risk estimates in the
region of practical interest (4).

~ 262 -


plotted by age at exposure, for both males and females, and on the assump-
tion that the minimal latent period has been satisfied. The vertical scale
is logarithmic and curves are presented for only two radiation dose levels.
For these and other reasons interpolation is to be discouraged.

- 215 -


CHAPTER X: THE CALCULATION OF PROBABILITIES OF CAUSATION FOR CANCERS

OF SPECIFIC TISSUES

1. Leukemia (204-207, except 204.1, in 8th Interaational Classification
of Diseases Adapted for Use in the United States {1TcDa))

The derivation of PC values, described in Chapters IV-VI and IX, is
more complex for the leukemias than for the solid tumors. The leukemogentc
effect of fonizing radiation does not extend to all forms of leukemia,
chronic lymphocytic leukemia (CLL) being the notable exception and there
being possibly others of Lesser importance, such as hairy-cell leukemia.

The major forms of leukemia know to be caused by radiation, the acute
forms (AL) and chronic granulocytic leukemia (CGL), differ in the likelihood
of their occurrence following exposure to vadiation, in their dependence
upon .age at exposure, and in their distribution over time following
exposure.

The only series of radiation~induced leukemias that even approaches
the size needed to describe the leukemogenic effect of radiation derives
from the studies of A-bomb survivors {1}, and for the present purpose it
was necessary to analyze those data in greater depth than was required
for the BEIR III report in which the risk coefficients for leukemia were
derived from the same source. Other human data on radiation leukemogenesis
are in reasonable agreement as to the general magnitude of the risk per
tad, the role of age at exposure, and the distribution of the radiogenic
excess over time (2-4). There is, however, a question as to the conpara~
bility of risk coefficients based on partial-body irradiation with those
based on whole-body exposure. As a working hypothesis for radiation
Protection purposes it has generally been assumed that a dose to a portion
of the marrow can be averaged over the entire marrow so that, e.g., a dose
of 800 rad to 40 percent of the marrow would average 32f) over the whole
bedy.s This hypothesis, while consistent with a linear dose response,
clearly is inconsistent with a model incorporating terms that are quadratic
or otherwise nonlinear in dose. For example, if partial-body doses are
high enough to kill or otherwise render ineffective a significant number
of cells, as seems to be the case, @.g., with X-ray therapy for cervical
cancer (5), the hypothesis is surely invalid,

The Working Group has employed the linear-quadratic dose-response
function preferred by the BEIR committee for low-LET radiation, but che
present tables for calculating PC values distinguish between acute forms
and chronic granulocytic leukemia, while providing coefficients for
all forms considered as a group but excluding CLL. The material for ail
forms except CLL may be used in those instances where the precise type
cannot be established and for chronic leukemias other than CLL and CGL.
The A-bomb survivor material on which the BELR estimates were based
reflects diagnoses that generally were the latest and most definitive
obtainable. Leukemia that is neither acute nor chronic at initial diag-
nosis eventually becomes acute. Therefore, the acute leukemia coeffictents

- 126 -



iS)

Female

Risk Coefficiant ECA
Sex
Male

Acute Leukemia?
and Sex $
Sex
Male Female

by Exposure Age A,

a

Table X-t+E.

MOK NNER ROM OM ET ROR MEME R= OINR WM 2 es co
FOE VOTM MOOUNONNG OHM 6 ee oe is TOME ROM
2

SARAH eR oNMOwO War rine

DR MONS RH OPNRPOTNENE OOTNIOROMINDNMHOTM NATO”
ORT NOMR MEN HOR oNMNT en NMR BOGOR KK NM
fepetarerorsscPatorer stare, Ce oe tk a ee

NE NOLEN OH NONNMA ORNS OMEN OMODOTH SON TOM
SHOR FH FOSTNOMROMN TIT ETE LESTER ODE WORM

24

Potts Srose PeENTNT

- 167 -


Tabla PC~1-a-60.

in Rad of Low*LET Radtati

Chronic Granulocytic Leukemia Following
Exposure at Age 69, by Age A» at Diagnosis, Sex, and Dose

PC in Percent,

Significant Digits or Three Decimal Places.

to Two

Ad Sex
Male Female
Dose

1 10 100 1 19 169
62 ~5? 5.9 52. 68 6.9 56.
63 1.4 53. 73. 7 18, 76.
64 1.6 15. 75. 1.8 17. 78.
€5 1.6 1S. 75, 1.7 16. 7).
6s 1.5 44, 74, t.6 15. 75.
67 1.3 13. 72. 1.4 13. 72.
63 1.2 ii. 9. 1.3 12. 71,
69 1.0 19. 46. t.2 12. 70,
70 - 90 8.9 $3, 1.2 1, $9.
74 -77 7.8 59. ted 1t. 67.
72 .67 6.7 55. +95 9.3 64,
73 5? 5.8 5). .79 7.9 ea.
74 +48 $9 47, «$6 6.7 £5.
75 4h 6.2 43. 55 5.7 Sa.
76 +36 3.6 39. 47 4.8 46.
7? -2¢ a.t 35. +40 4.1 42.
78 225 2.6 31, 34 3.5 39.
79 -20 2.t 27. .29 3.9 $s.
80 «17 1.8 24. .25 2.7 32.
a1 215 1s 22. +22 2.3 29.
82 +14 5 21. -20 2.3 27.
83 -13 1,4 20. o'7 1.8 24.
as 112 1.3 19, 16 1.7 23.
85 12 1.3 +8. +14 4.5 21.
a6 wi 1.2 12. 2 1¢ tr. 20.
8? WW 1,7 16. 13 1.4 13.
8s 10 it 46. 12 1.3 18.
89 695 1.9 15. 212 1,2 18,
990 090 98 ta, Ww 1.2 17,
91 086 +92 14. +10 11 16.
92 eae 187 43. 099 1.1 16.
93 «078 .83 13. +095 1.0 15.
94 074 a7d 12. 090 +98 14,
$5 O74 76 12, 086 $2 14,



Table PC-9-G (Continved?. Lung Cancer 10 or More Years After
Exposure to Low-LEY Radiation, by Age at Exposure, Sex,
and Dese in Rad, for Present Cigarette Smokers, 21 to 39
per Day. PC in Percent, ta Two Significant Digits or Three
Decimal Places. -

4 Sex
Male Female
Dose

1 to 106 1 10 0a
50 -010 an) 1.$ - 028 +38 4-9
5% +010 ait 1.9 029 +30 $.3
52 +018 oft 1.9 2829 St 5.4
33 06 wf 1.9 030 «32 5.2
54 ~Ott wt V9 203! 33 $.3
$5 2040 Pa 1.9 O31 134 5.5
56 +910 alt 1.9 032 +335 5.6
3? «O10 it 1.9 033 3 5.8
$8 +010 alt 1.9 034 37 $.9
s$ «O11 Par) 1.9 O35 138 $3
60 Ot par 1.9 O36 39 €.3
61 -O84 42 2.6 037 240 6.4
62 Ott 212 2.0 +038 «44 $.6
63 -O1t 212 2.0 040 43 6.8
64 O42 212 2.1 O41 4 7.0
65 2012 i3 2.1 ae2 45 7.2
66 -012 «13 2-2 046 47 7.5
67 O13 «34 2.3 9465 49 7.7
6s 2013 tg 2.4 +047 +50 8.0
69 +016 35 2.5 2049 +32 8.3
79 1016 215 2.5 2950 56 8.5
74 2015 = 16 2.8 952 .55 8.7
72 2015 16 2.7 +053 +36 a.
73 916 v? 2.8 2054 37 3.9
74 -016 18 2.9 ~ 054 -53 9.1
75 O87 38 3.8 055 be .3

- 329 -



LET = Linear energy transfer -
a measure of fonization density of a given radiation. LET is the
average loss in energy per unit length of path of the incident
radiation. See high-LET and low-LET radiation.

Linear energy transfer
see LET.

Life Span Study -
see LSS.

Life Table -
a table showing the number of persons who, of a given number born
or living at a specified age, live to attain successive higher
ages, together with the numbers who dfe in the intervals.

Linear (L) model -

also, linear dose-effect relationship; expresses the effect (e.g.,
mutation or cancer) as a direct (linear) function of dose.

Linear~quadratic (LQ) model -
also, linear-quadratic dose-effect relationship; expresses the effect
(e.g., mutation or cancer) as partly directly proportional to the
dose (linear term) and partly proportional to the square of the dose
{quadratic term). The linear term will predominate at lower doses,
the quadratic term at higher doses (see crossover dose).

Lognormal distribution -
if the logarichms of a set of values are distributed according to
a normal distribution they are said to have a lognormal distribution,
or be distributed “lognormally.”

Low-LET radiation -

radiation producing low ionization density, such as X and gamma
vadiation, and accelerated electrons (see LET).

Life Span Study, refers to the study of a population of Japanese
atomic-bomb survivors selected for lifetime follow-up study.

Millicad (mrad) -

1/1000 of a "rad.*

- 350 -



The PC for radiation given the other factor is

PC(D3Z) = RCDSZ)/(L+R(D32)) = CRED) x WEZ)I/CL + ROD) x WCZ))~

(2) The Multiplicative Interaction Model (MIM)

If the relative risk (the relative excess plus one) due to two risk
factors is the product of the relative risks for the two factors taken
separately, we say the two factors interact multiplicatively. Thus, if
radiation interacts multiplicatively with another factor, the relative
excess for radiation at dose D and the other factor at level 2 is

R(D,Z) = (1 + RCD) x (1 + R(Z)) - 1,
and the relative excess for D given Z is

R(D3Z) = (ECD,2)-E(Z))/1? = CR(D,Z)-R(Z)) x C2)

a

= RCD) x (14+R(Z)) x W(Z) = RCD),

and PC(D;2) = PCCD).

H. Cigarette Smoking and Lung Cancer

The most important risk factor which may be confounded with radiation
in the causation of cancer is cigarette smoking, especially in relation
to cancer of the lung and bronchus.

As has been shown, if a multiplicative interaction holds then the
PC's for radiation causation do not vary according to the smoking history
(nor would the PC's for smoking history vary according to the radiation
history). Whittemore and McMillen (5) concluded that in a group of
nearly 3,4CO uranium miners, an MIM appeared to hold as between exposure
to radon measured in cumulative Working Level Menths and cigarette smoking
measured as accumulated pack-years (one pack-year is one year's experience
smoking one pack daily).

On the other hand, Prentice et al. (6) found that in a group of
more than 40,900 residents of Hiroshima and Nagasaki, some of whom were
exposed to a wide range of acute doses of radiation from the atomic bombs
in those cities, the MIM definitely did not hold for death from all
non-hematologic cancers and, specifically for lung cancer, the AIM fit

the data better than the MIM.

Further, Blot et al. (7), in a case-control study of lung cancer in

Hiroshima and Nagasaki have demonstrated that radiation and smoking inter-
act in an additive way in the causation of lung cancer.

It is possible that the difference in results obtained by the
several groups stems from an intrinsic difference between a radiation
dose of sparsely ionizing radiation (gamma rays) received in a matter of
seconds (A-bomb) and a dose of densely ionizing radiation {alpha-particle~

~ 48 -

fom



376

38.

39.

40.

4h.

42.

Radtation Effects Research Foundation, “U.S. Japan Joint Workshop for
Reassessment of Atomic Bomb Radiation Dosimetry {n Hiroshima and NagaskaiTM
Proceedings of a Workshop Held at Nagasaki, Japan, February 16-17, 1983.

Radiation Effects Research Foundation, "Second U.S. Japan Joint Workshop
for Reassessment of Atomic Bomb Radiation Dosimetry in Hiroshima and
Nagasaki”, Proceedings of a Workshop Held at Hiroshima, Japan, November
8-9, 1983,

Fujita, S., Potential Addicional Data Sources for Dosimetry and Bio-
logical Re-evaluation. In “Atomic Bomb Survivor Data: Utilization
and Analysis,” pp. 183-193. SIAM (Society for Industrial and Applied
Mathematics), Philadelphia, 1984.

Jablon, $., Characteristics of Current and Expected Dosimetry. [n
“Atomic Bomb Survivor Data: Wwetlization and Analysis," pp. 143-152,
SIAM (Society for Industrial and Applied Mathematics), Philadelphia, 1984.

NCRP Report No. 64, “Influence of Dose and its Distribution {n Time
on Dose-response Relationships for Low-LET rad{ations.” National
Council on Radiation Protection and Measurements, Washington, D.C,, 1980.

Borek, C., Wall, E. J., and Zaider, M., X-rays May Be Twice as Potent

as Gamma Rays for Malignant Transformation at Low Doses. Nature 301:
156-158 (1983).

- 102 -


TY)

075 F 7

025 F- 7

0 as ee ee | re |
0 5 10 15 20 25 30 35 40 45 50

Time Y in Years Following Exposure

Figute Vol. Fitted time-to-tumor model for bone sarcoma
induced by a brief exposure to radium-224, T(¥) is the
probabilicy of diagnos{s within one year after time Y.

(Data from reference 10.) 0}

- 66 -


Rad of

g Exposure at
to Two Significant Digits

Sex, and Dose in

Bone and Joint Cancer Followin
at Diagnosis,

Alpha Radiation,’ PC in Percent,
or Three Decimal Places.

Age 63, by Age A

Table PC-2-60.

Sex

Female

Male

Dosa

160

+0

100

10

BONNE BH DON HFK ONE INNOO
FADIA RR CDOS SMM

cr rs OR Mewnninen-wnn
ONT ONR RF OOK OH NNER OMOIN ee
1 PO OO DOIN FM MN ANT HH POR OIE TOMA

s
ND ee. NOON HONK SOMO RON HRN OH
OP NOR RMIT Fe ee Rows OMAN
Ie ORO KOON MMNUNE OKO ee ee eee

ADK NEN ROOM OMOW TH OMRON OT OIE INNO
DOD A099 19 OT OOM MMS TOMA A NNR

w

EE ee) WHOM NOWN—InNS

BOVOF ENON OAT RO OMOUVNNT e e
1 AA ESE Rr ee oneness

”

POO) OWN ONE DONENE ET EMH NOH SROR NO OMO

Stee ete i aaten Om OA MONA
HNO HH OR ONMNE Ee Eee ee eee ve

TNO SWORN OTOH NIT NOR ARON MN Rn WeOot NM
ODO OO DBO EEE RE RE 001010 IO MOREA OAT

~ 303 -


populations studied for radiogenic cancer risk are wholly or predominantly
male or female, the roughly equal sex distribution of the Japanese A-bomb
survivor population allows sex-specific risk estimation for most cancer
sices for which a radiation related risk has been established (4),

G. Age at Exposure

One of the most interesting observations to come out of the Japanese
A-bomb survivor studies, which are based on a large population of all ages
in 1945, is that the risk of radiation-induced cancer depends strongly on
age at exposure (5,20). This dependence is complicated by a strong re=
lationship between age and the time from exposure to cancer diagnosis but,
in general, children appear to be more sensitive to radiation than are
adults. This pattern has long been recognized for leukemia, for which we
appear to have a more or less complete picture of the excess risk among
A-bomb survivors (21,22). All age groups experienced a temporary increase
in leukemia risk, which was higher telative to the baseline risk among the
very young. In terms of the absolute number of leukemias per capita,
however, the excess among the oldest group was fully as high as that in
the youngest group (Pig. [II-2).

The pattern of age dependence has emerged only gradually for the
solid tumors, as A-bomb survivors exposed as children have reached ages
at which cancer is ordinarily au important contributor to mortality.
Relative to baseline cancer rates, radiogenic cancer risk appears to
decline with increasing age at exposure. This pattern is very clear for
cancer of the female breast (Fig. I11-3) and for the thyroid, but it also
seems to hold for all solid cancers as a group (Fig. IlI~4). There is
clear evidence of an excess risk following exposure after age 50 for
leukemia and for digestive and other cancers (5), but not for cancers of
the female breast and thyroid (23,24). In general, observations on other
exposed populations are consistent with chose obtained from the A-bomb
survivors, but do not have a similar breadth of coverage with respect to
age (4).

The bulk of epidemiological data on cancer risk in populations
exposed to ionizing tadiation is based on follow-up of 35 years or less.
For many cancer sites, no excess risk is discernible until ages at which
baseline population rates are appreciable, and as a result, risk esti-
mation for persons exposed at very young ages can be difficult because,
so far, observations are few. For example, it was not until very recently,
when follow-up of the Japanese A-bomb survivors and thymically-irradiated
children in the United States was extended to 35 years or so, that it
became clear that there was an excess risk of breast cancer associated
with radiation exposure in early childhood (25,26). Age-specific risk
estimates for cancers of the esophagus, intestine, and pancreas were
formulated by the BEIR II1 Committee through the expedient of assuming
that radiogenic digestive cancers as a group share a common pattern of
variation by age at exposure (4). Without such an assumption, it is
difficult to justify estimates for these cancer sites following exposures
at young ages. Reasonable estimates can he calculated, however, for
leukemia and cancers of the thyroid, breast, bone and salivary glands.

- 18 -


Sex,
40 or More

10 of More Years After
at Exposure,
okers:

hy
te bm
to Two Significant Digits or Three

Lung Cancer

nm Rad, for Present Cigaret

PC in Percent,

o Low-LET Radiation, by &
Decimal Places.

8-H (Continued).

Exposure ¢
and Dose i
per Day.

Table PC

Sex

Female

Male

Dose

100

10

19

WERROTE“MYENCNR- ATR MOTMTINeN

HANNS sen Ramon NS
ALCS AOS OLN OF O80 IED

36
37
3

33
40

RRR RRR AER WOOD WMMORMAROOOW TING
SeeorcooVesaocecoegcer TTT Ts
SS oe ce oe eC OED COBO OSOCB0C0O

ON NOR Amar aMyNoNRwOmor AM siIn
FRA AAA aT SD DO

- 331 -


present purpose. The most recent mortality data concerning the Japanese
A-bomb survivors that were available to the BEIR Committee apply to the
period from five to thirty years following the radfation exposures (15).

Age 0-9 in 1945. For the digestive organs and peritoneum, there
evidently were barely enough data to support an estimate of risk for the
class as a whole; risk estimates for pancreas, liver, etc are supported
by no data. For these cancers in children, no data were available to the
BEIR Committee except those from the Japanese survivors. Table VII-4
provides no basis for calculating PC's for exposures at ages under 10
years for cancers of any of the digestive or respiratory organs. PC's
cannot be calculated because the underlying BEIR risk coefficients are
nok supported by adequate data.

Age 10-19 in 1945. The data in Table VII-5 may be sturdy enough to
support PC's for stomach cancer, but not for any other individual digestive
organ, The number of deaths from respiratory cancer is also very small,
but the coefficients in Table VI-1] were based on the later 1950-1978
report (10), with 15 deaths in this age group from lung cancer. The tables
in Chapter X, therefore, provide the basis for calculating PC’s for this
age group at exposure only for the stomach among the digestive organs, as
well as for lung cancer, bone cancer, leukemia, thyroid cancer, breast
cancer, and cancer of the salivary gland.

The next BEIR report will be able to take advantage of extensive
data compiled since the BEIR 1980 report (1) was prepared, including
eight additional years of follow-up of the Japanese A-bomb survivors.
Risk estimates for young persons, and knowledge of latent periods applic—
able to them, will be much improved, and future versions of these tables
can then provide PC's for ages and cancer types for which presently
available data are inadequate.

In addition to the extreme uncertainties that make it inadvisable
to attempt estimates of risk at the younger ages, the statistical uncer-
tainties in age-specific risk coefficients arising from sampling error,
and the possibly atypical character of some of the populations whose
experience has been drawn upon for epidemiologic studies, there is the
technical problem of interpolation among the risk coefficients calculated
for age intervals to produce estimates for single years of age, as well
as the problem of extrapolation in the age range beyond the given data
points. Knowledge of age at exposure as a determinant of risk is too
limited to provide sure guidance for the choice of a fitting procedure
for each site, and different methods naturally give somewhat different
results, especially at the oldest ages. The BEIR coefficients are given
in age~at-exposure intervals of 0-9, £0~19, 20-34, 35-49, and 50+. For
some sites it makes a great deal of difference, particularly at ages 65
and older, how the fitting is performed. Linear interpolation between
the midpoints of adjacent age intervals would produce a sequence of
irregular changes with age and leave undefined the regions under age 5
and over age 65. A cubic spline ‘interpolation provides a smoother sequence
of values within the range bounded by the midpoints of the extreme age
groups, e.g., 4.5 co 58 or 59 in the case of leukemia, and 24.5 to 58 or
$9 in the case of colon cancer, but the behavior of the spline function
outside this range can be difficult to predict. These problems have been

- 84 -

oy
}

x
sé


It may well be that ali tissues in which cancers arise are sus-
ceptible to the carcinogenic effect of fonizing radiation, but this
has not been shown. The Working Group employed three criteria in
selecting sites:

(1) The available evidence indicates that cancers of
the site in question may be caused by ionizing
radiation;

Dou.

(2) There are risk coefficients of sufficient specificity
as to age and sex to permit the calculation of Pc
tables; and

ane!

(3) The risk coefficients have sufficient stability to
watrant the calculation of PC estimates.

4, “The Oversight Committee recommends that, in compiling assigned shares
in the future, greater use be made of original radioepidemiologic data, ‘
including the latest updates available, and thar correspondingly less use

be made of derived risk coefficients, such as those from the BEIR III report.” -

The Working Group agrees that future revisions of the Tables should
include original risk estimates from the latest available data and
notes that a somewhat larger committee operating in a longer time
frame would be desirable. However, care should be taken ta avoid
unnecessary duplication between a future committee's work and that
of a new BEIR committee of the NAS.

3. “The Oversight Committee recommends that the use of mortality data be
considered for improving the understanding of the baseline incidence data
and for identifying the uncertainties in the trends for those data."

The Working Group examined mortality trends over time and in+
cluded in Chapter VII-C remarks concerning the several sites for
which such trends are most important.

6. "The Oversight Committee recommends that the Working Group explain in

gceater detail the consequences of different time-projection models,

Different models not only distribute observed cancer risks differently

over the period of observation, but also lead to different estimates or

risk for longer periods after exposure. The best choice of model is still 7
uncertain, and the users of the tables should understand their limitations.”

The Working Group agrees with the Oversight Committee that the
choice of a time-projection or time-to-tumor model can have
profound implications for PC, or assigned share, calculations.
Many pages of text have been devoted to this topic in Chapters eg
III, V and VII, in addition to text and tables in the site-specific j
sections of Chapter X. Much discussion has been devoted to the j
fitting of lognormal time-to-tumor distributions to data for bone

cancer and leukewia, and to the choice of the constant relative

tisk model for the other cancer sites treated. The latter choice

was based on the Plausibility of the model in the context of a

multi-stage hypothesis for radiation carcinogenesis, in which

- 340 -


aa wd

10.

dl.

13.

REFERENCES - Executive Summary

Committee on the Biological Effects of lonizing Radiation, “The
Effects on Populations of Exposure to Low Levels of Ionizing Racia-
tion: 1989." National Academy Press, Washington, D.C., 1980.

NCRP Report no. 17. “Permissible Dose from External Sources of
Tonizing Radiation", National Bureau of Standards Handbook No. 59,
issued September 24, 1954,

Borek, C., Radiation Oncogenesis in Cell Culture. Adv. Cancer Res~
37:. 159-232 (1982).

“Report of the Interagency Task Force on the Health Effects of
Ionizing Radiation. Work Group on Science.” U.S. Department of
Health, Education and Welfare, Washington, D.C., June 1980.

Comptroller General, “Report to the Congress of the United States,
January 2, 1982 (EMD-81-1): ‘Problems in Assessing the Cancer Risks
of Low-Level Ionizing Radiation.'“ Accounting Office, Document
Handling and Information Handling Facility, P.O. Box 6015,
Gaitbersburg, MD 20760.

Interagency Radiation Research Committee, “Federal Strategy for
Research into the Biological Effects of Ionizing Radiation” (NIH
Publication No. 81-2407). U.S. Department of Health and Human
Services, Public Health Service, National Institutes of Health,
June 1981.

United Nations Scientific Committee on the Effects of Atomic Radiation,

"Sources and Effects of Ionizing Radiation.” United Nations, New York,
1977.

Land, C. &., Estimating Cancer Risks from Low Doses of Ionizing
Radiation. Science 209: 1197-1202 (1980).

High Background Radiation Research Group, China. Health survey in
high background radiation areas in China. Science 209: 877-880
(1980).

NCRP Report No. 64. “Influence of Dose and Its Distribution in Time
on Dose-response Relationships for low-LET Radfations.” National

Council on Radiation Protection and Measurements, Washington, D.C.,
1980.

Gofman, J, W., “Radiation and Human Health." Sierra Club Books,
San Francisco, 1981.

Stewart, Aw Me, Health Risks of Low Level Radiation - 4 Guide to

the Use of MSK Risk Estimates for Radiation Workers. (Presented

by Dr. Stewart at a meeting in Philadelphia, PA, December, 1982.)
Octent, J. M., A Critique of the Statistical Methodology in Radiation
in Human Health, John W. Gofman. Health Phys. 45: 823-824 (1983).

~ vil -



0375

—

= 025
0125

-

5 a i A 1 1 i 1 i

0
0 § 10 15 20 25 30 35 40 45

Time Y in Years Following Exposure

Figure V-2. Fitted time-to~tumor model for chronic
granvloctyic leukewia induced by a brief exposure to ~
lonizing radiation, T(¥} is the probability of diag-
nosis within one year after time Y. (Data from refs.
2L and 12.)

- 67 -



In the above formulation, L(y) denotes the lifetable value for the ex-
pected number of person-years at age Ay + y (the average of the lifetable
probabilities of reaching ages A) + y and A, + y + 1), using the 1970 U.S.
lifetables (2) (see Table VI-2). The relative excess at age Az, Y years
after an exposure at age Aj, is given by

R(Ay,A9,¥,8) = F x T(Ay,¥) x E(A].S)/1(A2,8),

where F denotes an appropriate function of dose. I{Az,S) denotes the
baseline incidence of cancer of the given site and type for a person of
age A and sex $, as determined from the SEER values in Table VI-3 by an
interpolation process analogous to that used to obtain the values e(A),S).
in the above formulation Y assumes only integer values, being the integer
part of the time in years from exposure to diagnosis (e.g. 1f that time
is }2 years and 1] months, ¥ = 12).

Although the 1989 BEIR Committee presented risk coefficients for
bone sarcoma resulting from exposure to low-LET radiation, these coeffici~
ents were derived by the use of conventional quality factors from coeffici-
ents appropriate for exposure to alpha radiation (4, pp. 411-418). Bone
sarcomas were seen above 67 rad alpha dose to the endostial layer, which
corresponds, using a constant quality factor of 20, to 1300+ rem dose
equivalent. Bone sarcoma has not been observed in excess among the
Japanese atomic bomb survivors (4, p. 416), and in patients treated by X
radiation for ankylosing spondylitis cases have been seen only in associa-
tion with bone doses well above 1000 rad (4, p. 413). The Working Group,
while convinced of the validity of the BEIR estimate for bone sarcoma
following brief irradiation from radium 224, did not feel that there was
2 sufficient basis for extending it to low-LET radiation at doses below
1000 rad or to other forms of high-LET radiation, Accordingly, estimates
for bone cancer are presented only for high-LET radiation, from radium-224
(see Table V1~1-B).

2. Cancers other than leukemia and bone cancer, following exposures
to low-LET radiation

For other cancers, the temporal distribution of excess risk over
time after exposure was assumed to be proportional to the variation of
baseline incidence by age, at least beyond 10 years after exposure. In
other words, for given (A),S), the ratio

RK = P(Y)/1(A2,5),

where (roughly) A2 = Ay + Y, was assumed to be constant for Y> 10. It was
enough, therefore, to calculate, and tabulate, this ratio. Because the
absolute risk coefficient e = e(A;,S) is the lifetable average of P(Y) over
the follow-up period ¥, < Y < yg given in Table VI~l, it can also be expressed
as the lifetable average over that period of K x I’(¥), where I'(Y) = 1(A2,8)
for Ap = A] + Y. Because K does not depend upon Y for Y > 10, the relation-
Ship can be inverted to solve for K = K(A,,S):

K =e x (LC yy ee tL (yg) UL Cy LCyp +00 tL Cy) L(y) )-

-~ 73+



18)

gex

u

Relative Excess K(A
a

Colon Cancer:

by Exposure Age ay and Sex $
Sax

Table X-6.

Female

Male

Female

Mate

HH OWN ON WE TOMANE KH AAO BOER OSIM
MAMAS TANK PORE OOO REGOK TO TN
ire relelalalalelalatalalalalalalatalal a ee ae eee
SOCoCeHseasooDAAATDDeCooGo0000
BOGSOSTSOCOCEO DOB ORDOEDRE0CNDN0S

WOMAN AME FPMONMs Nop oOONTN
=O - aea eeeT TT tela lalalalaiainiaiatataded
PererT TP alalalaletalaluiaielalalelaletalataiaiatalated

DRO“ NN SNA QROK“ NM HER ONOT NMEA
FF ARNON CODD DWOCORE RAED

POUIVOIOIM A MWCHDNONNE BONE
FSS OE OO ON mH HE ID
WS FON OR IO OUI FS FOIA
Her er KK ACOSO SGOSASHEOSGIOAUR0A0
PODHOAOHOSDCOSCHSCGDGTIOHODSB000

°o

ANN SON OME wMMeaNwD
RTE PNR ONE HBT EMDONORMNMT CONN
ONTO ORR OL OOM FE FMM MONON
pape ie oon t-t-1-1-4-5-4-5-2-1-5-2-8adatehd beaded
SPECDoCoeGGaDoOCdVOOGCOoLVeeGnuG
BOCOSESCOHLOSSSE BOIS HAOGODO0S

SNORMROMK NM THO OOO NM
ANNANNO MMM MMOMIM Ss toe

- 217 -


Table Pl~16 (Continue
After Expesure to
and Dose in Rad.

dd. Female Sreast Cancer !0 of More Years

Cow-LET Ra
PC in Pere

or Three Decimal Places.

diation, by Age Ay at Exposure
ent, to Two Significant Digits

A, Sex
Male Female
Desa

| tS 100 t ¢ 190
41 eee oss 83 V7
42 - 087 +66 $.3
43 - O55 54 5.2
44 - 048 G8 4.6
45 - 045 45 4.3
46 - O63 -43 4.1
47 ~ 041 +4! 3.9
48 - O39 3% 3.8
49 - G37 37 3.6
53 hed G36 +36 3.5
St +034 -34 3.3
$2 033 33 3.2
53 932 +32 3.1
54 $39 +36 3.9
35 G29 -29 2.38
56 028 +28 2.7
57 ” 626 -25 2.6
53 ad 325 -25 2.4
59 - 023 +23 2.3
6a ~ 921 21 2.1
61 - +929 +29 2.0
62 - 058 18 1.8
63 - O17 ~U 1.7
44 - O15 fs 1.5
63 ited -914 = 14 1.4
6$ iieted -213 43 1.3
67 -o- Of wit Pa
$2 ila 010 16 99
63 ahead +028 +086 -85
77 7s ~$97 -272 .7t
71 oc +005 -058 +58
72 iaeed 2004 7044 44
73 wen .002 2029 -23
74 oom 00) 2015 35
7$ bateiad 7-7 +990 -000 000

- 334 ~

a een

seat

erat

gee

errs


soos ogee . oot ot . : woe po in, ed

a DP ee ee tae
ooo > | MOR TMK ON ON SNA HK RO DDON OF ROHN TOR ONE FES
Son — | ORR REAR OO OCC OCONIININNMINNE oe TMM MMMM
>
noe
oom

ano

a
o 5 °

bow -* La iid ce TINS SOMOR NNER MME MONMNAT CORO D
anc " > fmm EMME KO ee tet tet et net ete tet tee tytn ne boe
tug 5 Rf ee NNN COENEN EE EMM MMMM NNO
tO TM

+

ose

Lec

can
> xe POR ENN B90 FF BEINN HOE HMI OM WOM
ea ML GN ee OR SOONG oF MMMM MON NAN
bed _
ex :

° * °

rd “ 2°

° e

wes
oO a ee CR PLR
-<c lo | PM OR Ne Oy KH ERM NOOR INNO EMO TAN - SOT RAREAD
ws HK | RR ROC OOM YS EEE EE MOM MMNNNNNAN AINA Oe
ene

aos

Goa -

acin
occa

<n BD
co” 8 . Se GUI NNIN OSs CMON wr nnNenwr contre TET ETT
CO a0- ad DP ON ete Tt te Et we nN ee
a5oe ia = | HR RK ROR OOMN ET FT EMNONNNNNN ER He Oe eee woe eee
On ne
wasn
VE

ee

toe @

+
wi ca RENT RK MNO NOY HOMO OR NEN SON WON se EMME
bere — LLIN Ces e SMM MNNNANNR HORE ER eee ree
anew ff OP |] HHS Se Peete eee rerererararasans Prrarararars
tvoo

we

wooL
aOR
a - OT NNN OR OTOH NM EN CN AT OT NMS NER OHDOT NM NOR Woo
* « TR ER RR EEE ENN NNN NOM MMMM MMM SETS TEESE

- 308 -


Attempts to estimate the probability that an observed effect resul-
ted from one of several possible causes are not uncommon, even in the
more exact physical sciences. Decay of short-lived subatomic particles,
where only a small number of events can be observed and several potential
mechanisms exist, is in some respects analogous to the problems involved
in constructing radiocepidemfological tables. in both cases, probabilities
are calculated from a small number of events. There is, however, an
important difference. In physics a large number of well~tested and
comprehensive theories exists to guide calculations, whereas in biology
and medicine there are few well-established general and predictive theories
and the systems are immeasurably more complex. This becomes particularly
important for calculation of che probability that radiation caused a
certain cancer when the dose of radiation was small. Such calculations
are therefore subject to great uncertainty (see Chapter VII).

In order to construct the radicepidemiological tables, several
fundamental decisions were made, which are explained in the remainder of
this Summary.

I. The Working Group first had to decide what data should be used
to develop the numbers in the tables. In general, epidemiologic data
derived from radiation exposure to humans were utilized. However, effects
in experimental animals, largely rodents, and additional data from in
vitro studies of effects of radiation on cell cultures, which can provide
useful information on principles, were also considered. The animal data
on low levels of ionizing radiation. are constrained by the sawe limitations
as the data on humans--the difficulty that the small effects require very
large numbers of animals. Furthermore, the studies on rodents have been
restricted almost entirely to highly inbred strains of animals and to
types of tumors that occur with high frequency. Hence their relevance to
the carcinogenic effects of low-level irradiation in the human population
is uncertain. The in vitro experiments suffer because the cells are
studied under conditions that differ profoundly from those in vivo, and
are of uncertain relevance to the carcinogenic effects of irradiation in

man (3).

Il. Secondly, the Working Group had to resolve how to estimate the
risks from low doses of radiation. Although effects of moderate-ro-high
doses on large populations can be estimated reasonably well, several gov-
ernment reports, such as the 1979 Report of the Work Group on Science of
the Interagency Task Force on the Health Effects of Ionizing Radiation
(4), the 1981 report of the Comptroller General to the U.S. Congress
(5), and the 1981 report of the Interagency Radiation Research Committee
(6), as well as such authoritative reports as the 1980 (BEIR III} report
of the National Academy of Sciences (1) and the 1977 report of the United
Nations Scientific Committee on the Effects of Atomic Radiation (7),
testify to the uncertainty of the carcinogenic effects of very low doses
of radiation. Thus, che BEIR III committee was unwilling to make estimates
of the carcinogenic effects of radiation for acute doses below 10 rad or
for continuing exposure ta doses below 1 rad per year. Although the
non-threshold hypothesis is accepted for rad{ation protection purposes,
empirical evidence as to the existence of a threshold is lacking.

~ iif -



Table PC-S (Continued). Stomach Cancer 18 or More Years
After Exoosure to Low-LET Radiation, by Age A, at Exposure,
$ex, and Dese in Rad. PC in Percent, te two Significant
Digits or Thrae Dacimal Places.

: 4, Sex
Bale Female
fa Dosa

t +9 100 1 1g Teg
5s) ft} 4 3 +27 2.9 34.
52 233 1.4 9. +27 2.8 33.
33 13 1.4 28. +2? 2.8 33.
3¢ 233 1.4 20. +27 2.8 33.
$$ oth 14 26. 27 2.8 33.
36 336 t.5 2¢. 27 2.8 33.
3? ~ 14 1.5 20. +27 2.8 33.
53 4 1.5 21, -27 2.8 33.
39 - 14 1.5 21. «27 2.8 33.
60 ar) 1.8 21. «27 2.8 33.
$1 ~4 1.3 2%. 227 2.8 33.
62 14 1.5 2t. +2? 2.8 33.
63 +14 1S 2%. +27 2.8 33.
$4 14 1.5 2t. +27 2.8 33.
5 ~t¢ 1.$ 21, +27 2.8 33.
66 216 1.5 21, +2? 2.8 33.
67 14 1.5 21. +27 2.8 33.
68 +18 1.3 ran -2? 2.8 33.
69 215 1.5 Qt. +2? 2.8 33.
70 =15 1.5 21. +27 2.8 33.
Tt +15 1.5 ra -25 2.8 33.
22 215 1.5 21. +26 2.8 33.
73 rar 3 3.8 21. +26 2.7 33.
74 ts 1.6 21. +26 2.7 32.
73 rar] 1.6 21. 2s 2.7 32.

- 309 ~


babe

sin ask

25.

26.

27.

28.

29.

30.

31.

34.

35.

36.

Kato, H« and Schull, W. J: Studies of the Mortality of A~bomb Sur-
vivors. 7. Mortality, 1950-1978: Pare 1. Cancer Mortality.
Radiat. Res. 90: 395-432 (1982).

Hall, E. J., Radiation Dose Rate: A Factor of Importance in Radio-
biology and Radiotherapy. Br. J. Radiol. 45: 81-97 (1972).

National Academy of Sciences Advisory Committee on the Biological Effects

of lonizing Radiation: “The Effects on Populations of Expox.:e to Low
Levels of Ionizing Radiation.” National Academy of Sciences-National
Research Council, Washington, D.C., 1972.

Land, C. E. and Tokunaga, M. Induction Period. In "Radiation
Carcinogenesis: Epidemiology and Biological Significance” (J. D.
Boice, Jr., and J. F. Fraumeni, Jr., Eds»), pp. 421-436. Raven
Press, New York, 1984.

Whittemore, A. S., and McMillan, A., Lung Cancer Mortality among U.S.
Uranium Miners. J. Natl. Cancer Inst. 72: 489-499 (1983).

Radford, E. P. and St. Clair Renard, K. G., Lung Cancer in Swedish
Iron Miners Exposed to Low Doses of Radon Daughters. N. Engl. J. Med.
310: 1485-1494 (1984),

Blot, W. J., Akiba, $., Kato, H., Tonizing 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. Le Prentice, and D. J. Thompson, Eds.), pp- 235-248.

SIAM (Society for Industrial and Applied Mathematics), Philadelphia, 1984.

Bond, V. P., Meinhold, C. B., and Rossi, He He, Low-dose RBE and Q for

X-ray Compared to Gamma-ray Radiations. Health Phys. 34: 433-438 (1978).

Lloyd, D. C. and Purrott, Re J., Chromosome Aberration Analysis in
Radiological Protection Dosimetry. Radiat. Tech. Dosimetry 1: 19-28
(1981).

Loewe, W. E. and Mendelsohn, £., Revised Dose Estimates at Hiroshima
and Nagasaki. Health Phys. 41: 663-666 (1981).

Loewe, W. E., Revised Estimates of Neutron and Gamma-ray Doses at
Hiroshima and Nagasaki. In “Reevaluations of Dosimetric Factors,
Hiroshima and Nagasaki,” (V¥. P. Bond and J. W. Thiessen, Eds.), pp.
25-47, Technical Information Center, U.S. Department of Energy
Symposium Series No. 55 (CONF-810928). U.S. Govt. Prtg. Off.,
Washington, D.C., 1982.

Kerr, G.- De, Findings of a Recent Oak Ridge National Laboratory Review
of Dosimetry for the Japanese Atom-bomb Survivors. In “Reevatuations
of Dosimetric Factors, Hiroshima and Nagasaki,” (V. P. Bond and J. W.
Thiessen, Eds.), pp. 52-95. U.S. Department of Energy Symposium
Seties No. 55 (CONF-810928). U.S. Govt. Prtg. Off., Washington,

D.C., 1982,

- 101 -


Table PC-19. Female Sreast Cancer 10 or More Years After
Exposure to Low-LET Radiation, by Age A, at Exposure and
Dose in Rad. PC in Percent, to Yue Significant Digits or
Three Decimal Places.

Ay Sex
Male Female
Dose

T 10 Too 7 16 166
t -“ -- 2.3 19, 70.
1 oe 2.3 19. 74.
2 edad 2.2 19, 70.
3 -—-- 2.2 18. 63.
4 --- 2.0 17, $8.
5 --- 1.9 17. 66.
6 aaa 1.8 16. 65.
7 _- 1.7 15. 64.
& ocr 1.6 14. 62.
3 ven 1.5 43. 6G.
10 --- 1.4 3. 59.
1t oo: 3 12. 37.
12 — 1.2 as, 56,
13 -- 1,2 tf, 54.
16 + 11 10. $3.
i5 = Wf 9.7 52.
16 bane +98 3.9 so.
7 woe 89 a.2 47.
48 Steal 79 7.4 a4.
19 oor 69 6.5 qt.
20 o- «60 3.7 38.
21 - -52 5.0 34.
22 245 4.3 31,
23 +39 3.8 28.
24 235 3.4 26.
25 «33 3.2 25.
26 +3! 3.0 24.
2? +39 2.9 23.
28 «23 2.8 22.
29 -28 2.7 22.
30 +e? 2.6 Zi,
3! +28 2.5 21,
32 25 2.4 20.
35 -24 2.4 19,
34 +23 2.2 19,
35 -21 2.1 18.
36 19 1.9 16,
3? AT 1.7 15.
38 15 1.8 13.
39 +83 1.2 it,
40 --- --- 110 1.0 9.4

- 333 -



CHAPTER VI: METHOD FOR ESTIMATING RELATIVE EXCESS RISK
AND CALCULATION OF PROBABILITY OF CAUSATION

A. Coefficients of Absolute Excess Risk

The model assumed here for breast and thyroid cancer, for low~LET
radiation, is that of risk as a linear function of organ dose, without
threshold. For all other cancers considered, the linear~quadratic model
is used for low-LET radiation (see Chapter V-B).

Table VI-1-A shows linear and linea: -:uadrati< model risk coefficients
for the incidence of excess cancers for specified periods after radiation
exposure, by site, sex, and age at exposure, and for low-LET exposure, as
adapted from the 1980 BEIR Report or from more recent data (see Chapter
V, sections, A, B, and D). The tabulated coefficients represent the
average absolute excess risks per 190,000 per year per unit increment in D
or D+ pe/2i6, depending upon the dose-response model, where D is given
in rad, over the specified follow-up periods for persons in the given
ranges of age at exposure. Type-specific coefficients for acute and
chronic granulocytic leukemia were derived from coeffictents for leukemia
of all types as follows: From A-bomb survivor data (1) it was determined
that acute leukemias (AL) accounted for 68% of the excess leukemia risk
due to radiation and chronic granulocytic leukemia (CGL) for the remaining
32%. Because this proportion did not appear to vary by age, the tabulated
coefficients for leukemia were distributed accordingly. Tables V1-1-B and
VI-1~-C are for high-LET radiation and are only applicable to cancers of
bone and joint and to lung cancer associated with exposure to radon.

PC calculations pertain to situations in which exposure age may be
given for a single year of age, rather than an interval of 10 or more
years, and smoothness of transition from one year of age to another is a
desirable property of any calculational method that might be devised.
Although the variation by age at exposure of the coefficients in Table
VI-] and in the BEIR report surely has a large random component, the
Working Group did not, except in the cases of levkemfa (see Chapter V-D)
and lung cancer (see Chapter X-9), feel justified in smoothing this
variation by assuming a parametric model for risk as a funetion of expo-
sure age.

Accordingly, the tabulated coefficients were made specific to single
years of age at exposure by an interpolation procedure. Each tabulated
value was treated as if it pertained to the mean age of the corresponding
interval, weighted by the expected length of follow-up, assuming a lifetable
distribution (2) (see Table Vi-2) of ages at exposure within the interval.
Coefficients for single years of age were obtained by a cubic spline
interpolation algorithm (3). For ages outside the range of interpolation
(eeg., less than 5 for breast cancer or less than 25 for colon cancer,
and greater than 58 for most sites), for which interpolation methods are
notoriously unreliable, the following methods were used to minimize the
effects of minor variations in the tabulated coefficients: BEIR coefficier’s
for ages 0-9 or 10-19 deemed by the Working Group to have insufficient
evidential basis for PC calculations were used as interpolation points to
extend risk estimates to age 10 (stomach) or 20 (esophagus, colon, and

~7li-



Risk

Leukemia, All Types Except CLL:
)°5) by Exposure Age A, and Sex §

cefficient ECA

Table X+1-H,

Sex

A

Sax

Female

Male

Female

Male

Rewever er oNwornn oN NAAN OM ame NEN
HAM NOCORM MOOK TOKNOTRSRE RTO oe et ee
tee ete et et eet pet te oe ee eer rc annnnna
ANANAN MOM ETE AN OWEN ROMO E KK eee

DR RE MORN OHNO DT ee NM pkateierths :
toe ee et eee Orr any sneonneonnarrooe

AMEE ET ANCOR NOME RK Rm OTe eee NNN
REST AMIN ON WROW Ning NON ORO“ NM E NER ame MEIN
OTE EEE ETE ET ANAM OOOO CO ODDEN ARERR

LOST MATMOWRNOO- RMN OBR ROM“ MUNK MAMR NOS wo
OMT DOANE NIN VOT EN OOINMOUAMN TEE MMNMNNDOOOR NOUR OS

BNE MORO SCORNNONT OF MONE ORORNWMN OR EON
MOET MOONONMOR In FMM

1
1
1
1
1
1
1
1
1
!
2
2
2
2
2
2
2
2
2
2
3
3
3
3
34
35
36
37

- 178 +


we first obtain limits for the value of R in the formula:
PC = R/(1 + R).

1f upper and lower limits on R are substituted in this formula
corresponding limits on thé PC are obtained.

Suppose R is multiplied by some factor, V, giving

R'= Rx Ve
If PC' is the “true” value of the PC which corresponds to R’, then
PCh eae Rx V/K1L + RXV)
The value of PC' can be expressed directly in terms of PC and V as:
pct = Vx PC/(1 + PC x (¥V - 1)). Eq. (1)

Note that in Eq. (1) the PC is expressed as a fraction, rather than a
percent,

The upper limit of the 90 percent “credibility interv.
R is obtained by multiplying the value of R by $ ' the
ponding lower limit is obtained by multiplying by the reciprocal
of that value. Both limits must then be multiplied by the “bias
factor” if it 1s different from 1.0.

For example, for bone cancer the value of § is 1.57 (Table
VII-7). Raising this to the power 1.645 gives the result 2.10.
The 90 percent credibility limits on R, for bone cancer, are
obtained by multiplying by 2.10 and its reciprocal, 0.48.

For All Leukemia the value of S is 1.59 which, when raised to
the power 1.645 yields 2.14. For leukemia, however, the bias
factor 1.62 applies, so the upper and lower limit factors

; must be multiplied by 1.62, yielding 3.4? and 0.76. These
values can be used for V in Eq. (1) to obtain the 90% limits
that correspond to any calculated PC. For bone cancer and All
Leukemia, respectively, the 90% limits for a PC calculated as
5% would be

Bone cancer 2% to 102%
All leukemia except CLL 42 to 15%

The bounds for leukemia are quite asymmetrical because of the
bias correction factor.

Table VII-8 shows, for each cancer, the factors ¥ to be used
to obtain lower and upper limits for the 90% credibility interval
on any PC.

Table VII-9 shows for certain PC values and factor V values

the corresponding lower and upper limits for the 90% credibility
interval on the PC. As examples:

-9o -


latent periods of two years for leukemia and bone (brief irradiation
only) and 10 years for the other cancers, to avoid the sharp step-up from
0 to full effect at these points, it has “smoothed” the minimum latent
period as described in Chapter VC, For leukemia and bone cancer, for
which a fitted “wave” function represents the distribution of excess
eases over time, no such additional smoothing was necessary. For the
other forms of cancer, however, the process of smoothing is rather arbit-
rary as empirical data are lacking. The interval 5.0-9.9 years after
exposure may not be the optimal choice, and the cubic function used to
graduate the effect of time to diagnosis within this interval may not be
the best function to use.

For bone cancer and leukemia the minimal latent periods, 1.5 and 2
years, respectively, have a range of uncertainty from about 1 to 4 years.
For the solid tumors the Working Group has assumed that the full expression
of the increased relative risk occurs as early as ten years after exposure,
and that the increased risk builds up in the interval 5 to 9 years after
exposure. it is thought that rhese assumptions, in all probability,
under-estimate the required period of latency. It is only with respect
to intervals of 5-14 years between exposure and diagnosis that this
source of uncertainty is meaningful.

E. Dose-Response Function

In general, it has not been possible to show that doses of a few rad
have any influence on the likelihood of cancer since the risk, if any, is
lost in the background of natural incidence. It should be noted that the
BEIR committee was unwilling to make estimates for acute doses below 10
rad or for continuous exposure to less than 1 rad per year. Although it
has been suggested that a dose as low as 2-3 rad during fetal life may be
Jeukemogenic (10,11), these studies have been questioned by some because
exposure generally occurred on a selective basis associated with che
medical indications for X-ray pelvimetry. Comparable studies in which
radiation exposure occurred on a non-selective basis from routine pelvimetry
(12) or atomic bomb radiation (13) do not Suggest that doses of 2-3 rad
have any effect, but these series are small (see Chapter IZI~G).

In the very low dose region useful estimates cannot be made without
interpolation between the risk at 0 rad and the demonstrable and measurable
risk in the relatively high dose region, generally at or beyond 100 rad.
In the absence of a satisfactory theory of radiation carcinogenesis to
guide the choice of mathematical function with which to perform rhe
interpolation, considerable uncertainty attaches to interpolated risk
coefficients ia the low-dose vrange. In the BEIR ILI report, for example,
the calculated linear coefficients (1.e., the Limiting slopes of the
dose-response cutves at very low doses) for the risk of leukemia from
low-LET radiation are 0.99 + 0.93 excess cases per 106 persons per year
per rad under the so-called linear~quadratic model and 2.24 + 0.60 under
Che linear model. In the “pure” quadratic model, of course, the linear
term vanishes entirely. At 2 rad the risk of leukemia under these three
models is 2.0 per million persons per year for che linear-quadratic, 4.5
for the linear, and 0.056 for the “pure” quadratic. Corresponding: values
for all forms of cancer, other than leukemia, considered as a group, are

- 82 -


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- 173 -


We copy the values of RR(s) from Rogot and Murray (10).

Text Table A

}
uf

p(s)*

RR(s) Males Females

Nonsmokets 1.00 29.82 59.01
Former smokers** 3.97 19.23 7.81
Present cigarette smokers - all 11.28 50.95 33.18

Present amount***

<10/day 3.89 13.56 13.50

10~20/ day 9.63 24,72 15.92

21-39/day 16.70 11.24 4.37 .
40+/day 23.70 1.43 0.30

*NCHS 10-34 shows a small number (3.3 percent of male smokers
and 1.6 percent of female smokers) Of unknown present amount;
we have distributed these proportionately to the categories
of known amount.

**The value of W for former smokers applies to persons who stopped
smoking cigarettes at least five years prior to onset of lung
cancer. The data of Rogot and Murray (10) show that during the
firse five years after cessation of smoking, the risk of death
from lung cancer is actually more than one and one-half times
that of current smokers, implying that some stop smoking because
of early symptoms of what eventually will prove to be lung cancer.
It seems most appropriate to treat such persons as if they were
current cigarette smokers.

***The class intervals shown here are those used by Rogoc and Murray 4
(10); the NCHS 10-34 intervals are slightly different; less than il;
11-20; 21-40; 41 and over.

- 50 -


agents, personal history with respect to factors telated to cancer risk,
or membership in a particular population subgroup, is fraught with uncer~
tainty. The prodlem is not difficult given certain assumptions, as
illustrated in subsequent sections, bur with very few exceptions the
informational basis for such assumptions is lacking. Without such inform-
ation, any tule for making use of additional cancer data {is necessarily
arbitcary, and it may be preferable simply to proceed as if the subject
were a typical member of the U.S. population,

Fe. Multiple Radiation Exposures

If two radiation exposures to doses Dy and Dy, tespectively, would,

if given alone, result in excess risks E(D,) and &(Dz) at an age for which
the baseline risk is I, and if they are separated in time by a day or more so
that they do not interact, it is assumed that the excess From the two expos—
ures is the sum of the respective excesses, E(D],D2) = E(Dy) + E(D2). The
telative excess for the two exposures, R(D),D2) = E(D],D2)/I, is therefore
the sum of the separate relative excesses, each computed as if only one had
occurred:

.
3

RCD) D2) = ECD, ,D2)/1 = EC(Dy)/T + E(D2)/t = RCD) + RODg).

Clearly, a PC calculation should be based on both the exposures
or, if only one is of interest (perhaps one was voluntary and the other
involuntary), the calculation should take account of the fact that the
total risk was altered by the other exposure. If the first exposure is
the one of interest, the calculated relative excess should take account
of that by replacing I with

I! = Lx (1 + R(D9))-

It will be convenient to write W(D9) = 1/(1 + R(Dg)), so that I/I' = W(D9).
The relative excess for the first exposure given the second then is

R(Dy;D2) = CE(D],D2)-E(Do))/1* = ECD))/1* = RCD) x W(D2). (iv-2}
The role of W(Dj), therefore, is to put the relative excess due to Dy in the

context of the baseline risk as altered by Do. The PC value for the first
exposure given the second is

PC(D13D2) = RCDy;D2)/C1+ RCD]3D2)) = CRED, RCD) )/C1#R(Dy)W(D2)),
a number different from and, in this example, smaller than the value

PC(D)} which would have resulted if the second exposure had not taken
place.

G. Modification of the PC Formula To Take Account of the Effects
of Exposure to Carcinogens Other Than Radiation

A person with a malignant neoplasm of a kind that can be induced hy
radiation may have 2 history not only of radiation exposure, but also of
exposute to other carcinogens that may be significant with respect to
that particular cancer. Cigarette smoking or benzene exposure are examples.
The PC has been defined as being conditional upon individual characteristics,

- 46 -


time

(aflatoxin), environmental contaminants (pesticide residues, heavy metals,
PCBs, etc.), and additives for coloring, flavor (cyclamates and saccharin),
and food preservation. Dietary carcinogens may act as tumor initiators

Or promoters, may facilitate the formation of carcinogens {n the body, or
may affect the transport, activation, or deactivation of carcinogens
already present in the body (4).

4, Occupational exposures

Exposure to various occupational risk factors can increase the
likelihood of cancer. Carcinogens that have been identified in the
workplace include arsenic, asbestos, benzene, coal tar pitch volatiles,
2-naphthylamine, vinyl chloride, nickel and radiation. Moreover, there
ate a number of industries such as the petrochemical industry, the rubber
Industry, and coal mining, {n which workers seem to have an excess risk
of developing cancer, even though the specific risk factor or agent has
yet to be identified. Because of the relatively long latencies associated
with wost forms of occupationally related cancers, current incidences of,
or deaths from, occupationally related cancers are typically the result
of exposures that occurred one or more decades in the past, when exposure
levels were usually much less well-controlled and not as well-documented
as are prasent~day levels. Furthermore, since workers frequently change
jobs, both within and between industries, they may be exposed to a variety
of potentially carcinogenic agents, the individual effects of which are
not easily isolated.

5. Pollution

Manmade pollution of air and water is another source of potential
cancer tisk for humans. The frequently observed increase in lung cancer
death rates among inhabitants of the more urban areas of the United States
has been iaterpreted as evidence that air pollution, primarily polycyclic
aromatic hydrocarbons from auto exhaust contributes to the risk of cancer.
This argument is confounded, however, by the fact chat the typical urban
dweller is more likely to smoke than his rural counterpart and more
likely to come into contact with a variety of occupational/ industrial
tisk factors as well. Although it ts extremely hard to separate the
impact of polluted air from the effects of these other risk factors, most
researchers seem to believe that the actual percentage of all cancers
specifically attributable to air pollution, while perhaps not negligible,
is likely to be small (4).

The carcinogenic effects of water contamination, which may arise as
a result of industrial pollution, agricultural runoff, waste dump seepage,
and as 4 byproduct of drinking water purification {17}, are even more
difficult to assess than those associated with air pollution (4). Even
in the few instances where case-control studies have been conducted,
results have not always been consistent (4).



rem
cee

8. Cancer of the Pancreas {157 in ICDA-8)

Risk estimates for pancreatic cancer are less reliable than those
for most sites, perhaps because most data are derived from death certifi-
cate diagnoses that do not fare well in pathology reviews. The UNSCEAR
(2) and BEIR III (4) reports rely heavily on the excess reported for the
British ankylosing spondylitis patients treated with X rays (26), but the
relationship is weak in the most recent report on that serfes (3}. The
pancreas was a "heavily irradiated site,” and although Doll and ris
colleagues have yet to publish a dose estimate for the pancreas, the BEIR
ILI report gives a value of 90 rad. There were 18 deaths from pancreatic
cancer vs. 9.5 expected in the latest report, but 5 occurred within the
first two years after treatment (vs. | expected) and the 13 vs. 8.5
comparison for the period 3+ years after therapy returns a p-value in

excess of .10. Land has calculated an estimate of 0.70 + .61 excess deaths

per million per year per rad for this experience (23), The BEIR III
estimate is .90 for males and .99 for females, with age-specific coeffici-
ents varying in direct proportion to those for all gastrointestinal cancer
deaths among the A-bomb survivors, 1950-1974,

Death certificate diagnoses for the large Life Span Study sample of

A-bomb survivors reveal no statistical evidence that the risk of pancreatic

cancer depends on dose (p = .67 in a test of linear trend on 148 deaths)
(28), but the pathology confirmation and detection percentages for cancer
of the pancreas are low, 62 and 37 respectively, in a series of 61 autopsy
cases (42). In a report on 36 cases in the Nagasaki Tumor Registry series
for 1959-1978, Wakabayashi et al. report a trend p of .06, for which the
risk coefficient 1s 1.15 + .92 (29). In the unpublished Hiroshima Tumor
Registry report for the same time period there are 143 cases with a
non-significant risk coefficient of .18 (90-percent confidence interval
of -.14 to +.50) (30). Overall, therefore, the experience of the A~bomb
survivors provides very weak support for a relationship between pancreeci->
cancer and radiation dose.

In their first report on deaths among workers at the Hanford Works
in Richland, Washington, Mancuso et al. reported a probable excess of 6
deaths from pancreatic cancer among 3}, and estimated the doubling dose
at 7.4 rad (43). The statistical significance of the association was
verified by Hutchison et al. in independent calculations (44) and by
Gilbert and Marks in a cohort analysis of the worker population (45).
These and numerous other commentators stressed the fragility of the data

{death certificate diagnosis and the likelihood of exposure to carcinogenic

chemicals), The association was later weakened by the finding that, for
1 of the 4 critical deaths in the 15¢ rem dose group, medical records
showed that the primary cancer was probably in the stomach (46).

The pancreas barely meets the criteria for inclusion among the sites
for which PC estimates are to be made. There are human data from which
the necessary risk coefficients can be derived, but the statistical
reliability of the association between cancer and dose is low and consis-
tency among the few available series is minimal.

The Working Group chose to employ the BEIR III coefficfents except
for exposure before the age of 20, the basis for the BEIR III coefficient

~ 225 -

7


82.

83.

B84.

85.

86.

87.

88.

Waterhouse, J., Muir, C., Shanmugaratnam, K. and Powell, J.
(Eds.), “Cancer Incidence in Five Continents,” Vol. IV. Inter-
national Agency for Research on Cancer, Lyon, 1982.

Land, C. E., Cancers of the Digestive Tract and Accessory Organs.
In “Radiation Carcinogenesis” (A. C. Upton, R. E. Shore and R. E.
Albert, Eds.), in press. Elsevier North-Holland, New York, 1985.

Darby, $. C., Nakashima, E. and Kato, He, Parallel Analysis of
Cancer Mortality among Atomic Bomb Survivors and Patients with
Ankylosing Spondylitis Given X-ray Therapy. RERF Technical
Report, Hiroshima, Japan, Radiation Effects Research Foundation,
in press,

Haenszel, W., Kurihara, M., Segi, Me, et al., Stomach Cancer among

Japanese in Hawaii. J. Natl. Cancer Inst. 49: 969-988 (1972).

Oversight Committee on Radioepidemiologic Tables, "Assigned Share
for Radiation as a Cause of Cancers Review of Radioepidemiologic
Tables Assigning Probabilities of Causation.” National Academy
Press, Washington, D-C., 1984.

Moolgavkar, S. He and Lee, J. A. H., Temporal Trends in Breast
Cancer. Am. J. Epidemiol. 115:759-777 (1982).

Riggan, W. B., Van Bruggen, J., Acquavells, J. F., Beaubier, J.
and Mason, T. Ja, "U.S. Cancer Mortality Rates and Trends, 1950-
1979", Vol. Il, U.S. Govt. Printing Office, Washington, D.C., 1983.
[EPA+600/1-83-015b. ]

- 37 -



To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig X-12 has been drawn
for tissue doses of 1, 10, and 100 rad of low-LET radiation, and PC
values plotted by age at exposure, for both males and females, and on the
assuuption that the minimal latent period has been satisfied. The vertical
scale is logarithmic and curves are presented for only three radiation dose
levels. For these and other reasons interpolation is to be discouraged.

~ 259 ~



Table PO-4 (Continued). Esophagus Cancer tt or More Years
after Expesura to Low-LET Radiation, by Aga ay at Exposure,
i

Se and Dose im Rad. PC im Percent, to Two gnificant
Bigits or Three Decimal Places.
ay Sex
4 Male Female
dese
7 To 00 T 1) TES
6f 979 85 13 225 2.7 3
62 +083 +88 13 +26 2.7 3
63 2085 92 1¢ +2? 2.38 3
64 7090 96 19 .2? 2.8 3
65 093 299 15 +28 2.9 3
66 098 1.0 5 +28 2.3 3
67 0399 11 18. «28 3.9 3
68 10 Ww 16. -29 3.0 3
69 10 1.14 16, +29 - 3.0 3
70 12 1,4 16. 129 3.0 35.
71 ait 1.3 16. +29 3.0 35.
72 Pan 1.4 17, «23 3.0 35.
73 Pani Ff 17. +29 3.9 35.
7% Pant 1.2 17, +28 3.0 34.
75 an V4 V7, +28 2.3 34,

- 307 -



Ls4

20

16

“12 aN

Relative Risk

re) A { 1 ri t —F
0 10 20 30 40 50 ~=—s« 60
Age At Time Of Bomb

Figure I1f-4. Relative risk of all forms of cancer except leukemia
among Japanese A-bomb survivors, mortality 1950-1978, 200+ rad versus
under l rad, by age at the time of the bombings, both cities combined.
[Redrawn from Kato, H-, and Schull, W. J., Radiat. Res. 90: 395-432
(2982), Fig. 4.) —

- 41 -


Example 2 A typical male, aged 55 at exposure to 5 rad of low-LET radia—
tion to the kidney, with diagnosis at age 60, 4.9 years after exposure.
That is, D«© 5, Ay = 55, and Y= 4.

F= 5 + 52/316 = 5,22

T(4) = 0

K(55,m) = .000275

whet

then R= Fx Tx K = 5.22 x 0 x .000275 = 0
and PC = 0

Example 3 A kidney cancer was diagnosed at age 44 in a woman following
several exposures.to low-LET radiation at various ages. The first, of

one rad to the kidney, occurred at age 20, 24 years and 2 months before
diagnosis (¥ = 24). The second, to 2 rad, occurred 4 months later, at

the same age (A, = 20} but 23 years and 10 months before diagnosis (Y = 23).
At age 21, 23 years and 3 months before diagnosis, a 9-rad total dose was
received over a 36-hour period at the continuous rate of 250 millirad per
hour (¥ = 23). Finally, at age 35, three exposures, to J.-1, 0.6, and 0.7
rad, respectively, were received on consecutive days, 9 years and 2

months prior to diagnosis (Y = 9).

The first, second, and third exposures should be considered separately,
because exposures 1] and 2 correspond to different values of Y, and exposures
2 and 3 to different exposure ages. The 9-rad continuous exposure delivered
over 36 hours should be treated as 2 exposures because it required more
than one day, but less than two, The suggested partition assigns a 3-rad
exposure to one 24-hour period and 6 rad to another. The three exposures
at age 35 can be treated as one because they correspond to the same
values of Al and Y, and because the total dose is less than 5 rad.

Exposure 1:

F(D) = F(1) = 1 + 12/116 = 1.01

TC(Y) = T(24) = 1

K(20,f) = -00301

Rp = Fx Tx K = 1.01 x 1 x .00301 = .00304
Exposure 2:

F(2) = 2 + 22/116 = 2.03

7(23) 21

K(20,f) = .00301

Ro = Fx Tx K = 2.03 x 1 x 0030) = .00611

- 251 -


Temporal Factor T(Y)

Cubic model as a
smooth function of time

-75 — Values to be epplied
on 8 whole —year basis

—_f I n } n
0 2 4 6 8 10 12

Time in Years After Exposure

Figure V-5. Temporal factor T(¥) to be applied to
Telative excess risk for cancere other than leukenta
or bone sarcoma.

-~70-



Tabla PC-f-C-40. Leukemia Excluding CLL Following Exposure
at Age 40, by Age A, at Diagnosis, Sax, and Dose in Rad
of Lom-LET Radiation. PC in Percent, to Two Significant
Digits or Three Decimal Places.

Ae $e
Male Fomale
“4
Dose

i 7 19 Too t 10 50
$2 44 4.6 45. 134 3.6 3
43 1.2 12, $9, 293 9.2 6
44 1.6 15, 75, 1.2 12. ?
45 1.8 17, 7?. 1.4 1%, 7
46 1.3 18. 79, 1.5 ¥4. 7
4? 2.0 18. 79. 1.6 15. ?
48 2.0 18. 79. 1.6 8. z
49 1.9 17, 78. 1.6 15. 7
30 1.8 16. 27, 1.5 14, 7
$i 1.7 16, 76. 1,5 te. 7
52 1.6 15, 24. 1.4 13 ?
53 1,4 16, 73. 1.3 12, 7
$6 1.3 12, at. 1.2 14, &
$$ 1.2 1t. 68. tf 1f, rs
36 1.0 10, 64, «98 9.6 6
37 +89 8.8 $2. 87 8.7 $2.
$2 +76 7.6 39. 78 7.8 59.
5g 66 © 6.7 55. -69 6.9 56,
60 -57 $.9 $2. +63 6.2 $3.
61 56 $.1 48. 56 5.5 So.
62 44 4.6 45. +48 4.9 47.
&3 +39 4.5 42. 42 4.3 «4,
64 235 3.7 39. -38 3.9 41.
65 «St 3.3 37. 3 $.$ 38.
66 +28 3.0 34. +30 3.1 34.
6? .28 2.7 32. 27 2.8 33.
638 +22 2.3 29. 2¢ 2.5 3h,
69 19 2.8 26. +21 2.2 28.
70 +16 1,7 23. «19 2.0 26.
74 1G 1.8 20. 1? 1.8 24.
72 «12 3.3 18, «15 1.6 22.
73 39 tt 16. 13 1.4 20.
24 +090 +96 44, 12 1.2 18.
75 079 +85 13. 10 wd 4,

- 293 ~


Table PO-$. Esophagus Cancer 10 or More Years After Exposure
to Low-tET Radiation, by Age A, at Exposure, Sex, and
Dose in Rad. PC in Percent, th Two Significant Digits or
Three Decimal Places.

4, Sex
Mate Female
Dose

1 19 100 t 1 T00
20 -2t 2.2 28. 3.8 $1,
2t 19 2.0 26. 5.1 43.
22 17 1.8 23. 4.6 43.
23 215 1.6 2%. 4.t $2.
24 ~33 1.4 20. 3.7 4a.
25 +32 1.3 18. 3.4 37.
26 att 1.2 17. 3.0 3s.
27 +49 tt 16. 2.8 35.
238 2095 98 14, 2.5 31.
29 +084 +90 13. 2.3 29.
3t 078 «83 13. 2.2 28.
3t 072 77 12. 2.0 26,
32 ~067 +72 11, 149 25.
33 +963 $7 te. 1.8 24.
34 059 63 9.8 1.7 23.
35 - 956 69 9.4% 1.6 22.
36 983 37 8.9 1.6 21,
37 056 .54 8.5 1.5 21.
38 048 +52 8.2 t.5 2e.
39 046 49 7.8 t.4 20.
40 0446 47 7.6 1.4 19.
4t O43 6 7.3 1.4 19,
42 a41 44 7.t 3 19,
43 041 44 7.0 1.5 1S.
44 +067 44 7.0 1.4 39,
45 «041 44 7.1 1.4 19.
46 +942 45 7.2 1.4 20.
47 +043 47 7.4 t.3 20.
48 045 148 7.7 1.3 21.
49 047 .30 a.0 1.6 22.
50 +049 52 8.3 1.7 23.
31 051 54 8.6 1.8 24.
$2 +053 -§7 8.9 1.9 24.
33 055 5 9.3 1.9 2s.
34 O58 +62 9.7 2.0 26.
$5 067 +65 1g, 2.1 2).
36 «064 +68 0. 2.2 28.
37 065 71 a, 2.3 23.
33 989 +24 Vt, 2.4 30.
59 47S 277 12. 2.5 31,
69 -076 .8t 12. 2.6 31.

- 306 -

Coin.


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

200 |;

50

20

10

Fig X-1-a-2

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 10

10

15 20 28 30 45

AGE AT DIAGNOSIS Male aan
Female---

- 132 -


at E(21,£)

care
jawed

Exposure 3b:
F(6) = 6 + 62/116 = 6-31

1(21,23) = .0120

0912

1(44,f£) = 2.73

K = E/T = .912/2.73 = 0.334
Rap = Fx Tx K = 6.31 x .0120 x .334 = .0253
Exposures 4, 5, and 6:
F(lal + 0.6 4 0.7) = F(2.4) © 2.4 + 242/116 = 2.45
1(35,9) = .0436
E(35,f) = 1.24
1(44,f) = 2.73

K = E/L = 1.24/2.73 = 0.454

Rys506 = Fx Tx K = 2.45 % .0436 x 0454 = 00485
R = Ry + Ro + Raq + Rap + Ryr506 = -00342 + .00775 + .0123 + 0253 + 0485 = .0973

PC = R/(1+R) = .0973/1.0973 = .0887 = 9%.

ek ok

- 125 -


J

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 Hee Working Group to Develop Radicepidemiological Tables comprised

of scientific experts whose qualifications will insure a thorough, competent,
and timely completion of the task.

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

This Ad Hoc Working Group to Develop Radioepidemiological Tables is governed
by the provisions of Public Law 902-463, which sets forth standards for the
formation and use of advisory committees,

"Function

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 pargaraph (1) and the formulas specified in
patagraph (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 repres-
ent the best available sctentific data and expertise.

“Structure

The Ad Hoc Working Group to Develop Radioepidemiological Tables shall
consist of eight members, including the chairperson, Members and chair-
person shall be selected by the Secretary, or designee, from outstanding
authorities in the fields of endocrinology, radiation biology and pathology,
tadioepidemiology, biostatistics, and radiobiology. Members shall be in-
vited 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 cail of the chairperson
who shall also approve the agenda. A government official shall be present

-3-



90.

91.

92.

93.

94.

9S.

96.

97.

98.

in the Pacific Basin", National Cancer Institute Monograph 62, pp.
207-212. Government Printing Office, Washington, D.C., 1982.

Ishimaru, T., et al., Incidence of Thyroid Cancer among Atomic Bomb
Survivors and Controls, Hiroshima and Nagaskai, 1958-1979; Relation-
ship to Radiation Dose Absorbed by Thyroid Gland. Unpublished
manuscript dated September 20, 1983.

Shore, R. B., Radiation-Induced Thyroid Cancer. In “Radiation
Carcinogenesis: Epidemiology and Biological Significance” (J. D. Boice,
Jr., and J, F, Fraumeni, Jr., Eds.), pp. 131-138. Raven Presa, New
York, 1984,

Ron, E. and Modan, B., Thyroid. In “Cancer Epidemiology and Preven-
tion” (D. Schottenfeld and J. F. Fraumeni, Jr. Eds.-), pp- 837-854.
W. Be Saunders, Philadelphia, 1982.

Matanoski, G. M., Seltser, R., Sartwell, P. E., Diamond, E. L., and
Elliotr, E. A., The Current Mortality Rates of Radiologists and Other
Physician Specialists: Specific Causes of Death. Am. J. Epidemiol.
101: 199-210, (1975). 7

Anderson, R. E., and Ishida, K., Malignant Lymphoma in Atomic Bomb
Survivors, Hiroshima. Ann. Intern. Med. 61: 853-862 (1964).

Anderson, R. E., Nishiyama, H., Ii, Y¥., Ishida, K., and Okabe, N.,
Pathogenesis of Radiation~Related Leukemia and Lymphoma. Lancet 1:
1060-1062 (1972).

Cuzik, J., Radiation~induced Myelomatosis. N. Engl. J. Med. 304:
204-210, (1981).

Miller, R. W., and Beebe, G. W., Leukemia, Lymphoma, and Multiple
Myeloma. In "Radiation Carcinogenesis” (A. C. Upton, R. E. Albert,
F. J. Burns, and R. E. Shore, Eds.}. Elsevier North-Holland, New
York, in press.

Ichimaru, M., Ishimaru, T., Mikami, M., and Matsunaga, M., Multiple
Myeloma among Atomic Bomb Survivors, 1950-1976: Relationship to
Radiation Dose Absorbed by Marrow. J. Natl. Cancer Inst. 69:
323-328 (1982).

= 270 -

Weed


probably should be used for such cases in preference to the all-types
coefficients in the PC calculation. Death certificates may not specify
histologic type, but are generally reliable for leukemia. The present
report also differs from the BEIR report in its use of a “wave” function
to distribute the radiogenic leukemta over time, the BEIR report having
employed a plateau.

Data from the A-bomb survivor series (1) and the British ankylosing
spondylitis series (3) were used to derive lognormal time~to-response models
(see Chapter V-C). Time from exposure to response was assumed to be log-
normally distributed with a two-year minimum. For chronic granulocytic
leukemia (CGL) the ficted distribution of log(time in years - 2} was
independent of age at exposure and sex, with mean 2.68 and variance }.51,
while for acute leukemia the variance was 0.65 and the mean 1.61 + -O15A, +
+0005A,“°, where A; denotes age at exposure.

The age-specific linear-quadratic risk. coefficients in the BEIR III
report for all types of leukemia except chronic lymphocytic leukemia
(CLL) in fact pertained to only AL plus CGL. These were made specific to
AL and CGL in the ratio 68:32, based on a reanalysis of the A-bomb survivor
data (1). Coefficients for single years of age at exposure were derived
by the procedure described in Chapter V-D.

Several studies (6,7) have reported excess childhood leukemias follow=
ing fetal irradiation. Given the well-established association of leukemia
with childhood exposure, the causality is less in doubt than the magnitude
of the effect. The Working Group has made no distinction between fetal
exposure and exposure during the first year of life.

The SEER data on the incidence of leukemia for the period 1973~1981
have been used as the source of age-, sex-, and type-specific incidence
of leukemia in the general United States population (see Chapter VII-C).
The ICDA-8 code equivalents used were:

chronic granulocytic - 205.1
acute - 204.0, 204.9, 205.0, 205.9, 206.0
206.9, 207.0, 207.2, 207.9
all except CLL - 204.0. 204.9, 205.1, 205.9, 206.0,
206.1, 206.9, 207.0, 207.2, 207.9

The reporting areas for the SEER program (8) are relatively homogeneous
as to their incidence of leukemia (see Tables VII-1, and VII-2).

Although the leukemogenic potential of a variety of chemicals is
much discussed, it is only for benzene that reasonably cogent evidence is
in hand (9). Thus, it is not often that risk factors other than radiation
will be identified and appear to compete with radiation. The influence
of risk factors other than ionizing radiation is discussed in Chapter IV,
Sections E to G and in Chapter IX.

- 127 -



3
4
q
+

ue

is proportional to dose and that, for a single exposure to low-LET radia-
tion at age 15, the relative excess for a typical American woman is »O107
times dose in rad, at any time wore than 10 years after exposure (Table
X-10). If a cancer should be diagnosed at age 37, for example, following
exposute at age 15 to 30 rad, the relative excess would be R( breast cancer,
30 rad;age 15, 22 years) = (30)(.0197) = 9.321, and the PC would be
O.321/1.321 = .243 or 24%.

E, Cases in which US Baseline Incidence Does not Apply

PC calculations based on SEER values for baseline c. :cer incidence
Tequire the assumption that the individual in whom cance: s diagnosed
following a documented radiation exposure would have been, in the absence
of that exposure, “typical” of the US population for his or her age and
sex with respect to cancer risk. But the subject may have had an atypical
history of exposure (or nonexposure) to known carcinogens or may have ex-
perienced other life events associated with a higher or lower cancer risk
than average. Or the subject may be a member, perhaps even a “typical”
member, of an ethnic, religious, or other population subgroup known to
have cancer rates higher or lower than the U.S. population as a whole.
Should the PC calculations be modified in such cases, and if so, how?

Having introduced the problem, we shovld also make it clear that it
is a problem about which very little is known. Although experimental
studies have demonstrated that levels of carcinogenic response to ionizing
radiation can be modified drastically through the use of certain so-called
“promoters”, agents that do not in themselves appear to initiate the car-
cinogenic process, we do not know whether or not similar agents contri-~
bute to human cancer risk associated with radiation. It is by no means
clear, at this time, whether people who are at high risk of cancer in the
absence of radiation exposure are more sensitive than other people to the
carcinogenic effects of radiation. Epidemiological research in the area
of combined effects of different risk factors is difficult because combin-
ations that might be of interest are relatively rare, and in the case of
radiation and other factors, such epidemiological study is just beginning,

The estimates of cancer risk from radiation exposure presented by
the BELR Lil Committee were based on syntheses of data from various ex-
posed populations, some of which, like the Japanese A-bomb survivors,
have cancer incidence levels for certain cancer sites that are very
different from U.S. rates. Making the estimates involved the implicit
assumption that the carcinogenic effects of radiation are additive with
respect to whatever factors are responsible for differences between
population cancer rates. This assumption appears to hold for breast
cancer in the case of Japanese and American women (3), for whom population
rates differ by a factor of 4 or 5, and it is not inconsistent with data
on vadiation-induced stomach cancer in A-bomb survivors and British
patients treated with X radiation for ankylosing spondylitis (4). There
may be other sites for which the assumption does not hold, but we have no
way of knowing at present.

Clearly, the problem of calculating PC values in the presence of dif-
ferences in total cancer incidence because of exposure to other carcinogenic

- 4&5 -



APPENDIX It

APPENDIX IL:

APPENDIX IIL:

4s
Se
6.
7.
8.
9.
10.
ll.
12.
13.

Esophageal Cancer
Stomach Cancer . . «
Colon Cancer «. «
Cancer of the Liver
Cancer of the Pancreas
Lung Cancer

ILLUSTRATIVE PC TABLES

Cancer of the Female Breast
Cancer of Kidney or Bladder
Thyroid Cancer .
Excluded Sites ..

ewes

Page

+ 199
+ 205
» 211
» 218
+ 225
+ 232
« 242
« 249
+» 255
+ 262
+ + 271

STATUS OF FINAL REPORT OF THE WORKING GROUP IN RELATION TO THE
RECOMMENDATIONS OF TRE NATIONAL ACADEMY OF SCIENCES (NAS)
OVERSIGHT COMMITTEE ON AN EARLIER DRAFT (JULY, 1984)

GLOSS ARY

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~ 164 -


BONE AND JOINT CANCER*

Fig X=2-6

EXPOSURE AGE 50

19090

50

20

10

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

50

SS

60

AGE AT DIAGNOSIS

*Alpha radiation from radium-224 only

- 188 -

60 35

Male ——
Female---



alee

mi

6. Colon Cancer (153 in ICDA-8)

The colon has long been considered an organ of apparent, but uncer-
tain, sensitivity to radiation carcinogenesis, based on studies of patient
populations irradiated for benign or malignant pelvic disease and the
British series of patients treated with radiation for ankylosing spondylitis.
The uncertainty arose because, although remarkable excess risks were seen
in some studies (35,36), there was none in others with comparable levels
of exposure (37,38). Moreover, the excess risk seen among spondylitis
patients treated with X rays was discounted because of known associations
among spondylitis, ulcerative colitis, and colon cancer (3,26). In fact,
an excess risk was seen soon after treatment began, well before the ex-
piration of a 10-, or even S«year, minimum induction period for radiation-
induced cancer.

More recently, excess colon cancer has been observed in mortality data
for survivors of the Hiroshima A-bomb (28) and in tumor-registry data for
survivors of the Nagasaki bomb (29). At about the same time, however, in
a large international series of women in Europe and North America treated
by irradiation for cervical cancer, no excess mortality was seen for colon
cancer despite an average dose of about 500 rad to the colon, possibly
because average follow-up is only 7.6 years (5).

At the present time the evidence for excess colon cancer associated
with radiation exposure rests mainly upon the A-bomb survivor data,
perhaps because colon cancer normally is rare in Japan in comparison with
the United States, and a modest excess may therefore be easier to detect.
The most recent A-bomb survivor data are consistent with the risk estimates
given in the 1980 BEIR report (4,23) except that the data do not appear
adequate to support a risk estimate for exposures before age 20 (see
Chapter VII-F). The BEIR ILI coefficients for ages 20+, adjusted to the
period 11-30 years after exposure, are the basic risk estimates used by
the Working Group.

There has been no analysis of colon cancer to establish the most
appropriate dose-response function or to determine whether the relative
tisk model is superior to the absolute risk model for distributing radio-=
genic cases over time. The Working Group has assumed that the preferred
linear-quadratic dose-response model of the BEIR LIL committee and the
constant relative risk time-response model would provide a suitable basis
for the calculation of PC values for this stte. These general assumptions
are discussed in Chapter V.

The normal incidence of colon cancer in the U.S. is best represented
by the SEER data of the National Cancer Institute which, however, are
subject to some variation among reporting areas (8). (See Chapter VII-C
and Tables VII-] and ViI-2.) The base-line rates employed here are those
for all races combined and for all areas combined except for Puerto Rico,
and are age- and sex-specific. They are taken from computer tapes for
the period 1973-1981.

Migrant studies have underscored the role environmental factors, in-

cluding nutrition, must play in the etiology of colon cancer, especially
the dietary intake of meat and animal fat. Epidemiologic studies have

- 211 -



Fig X-1-C-7

LEUKEMIA: ALL TYPES EXCEPT CLL
EXPOSURE AGE 60

100
me
Zz
ne Wy fos Ba
10S RAD ——
* & 50 -
iow /
Zz
oO
i
§ 2%
7
jem
s)
= ne
© 10 #
>» TO RAD
-
2 -
$
E i
fd
a
Q
=a
<
=
=
” oz
Woy Za.
60 65

70 75 eo ss 90 $s

Male ——

AGE AT DIAGNOSIS Femate--~

- 153 -



lL

3.

10.

ll.

12.

REFERENCES - Chapter V

National Cancer Institute, “Surveillance, Epidemlology, and End
Results. Incidence and Mortality Data: 1973-1977." NCI Monogr.
57, U.S. Goverament Printing Office, Washington, D.C., 1981.

Committee on the Biological Effects of Tonizing Radiation, “The
Effects on Populations of Exposure to Low Levels of Tonizing
Radiation 1980." National Academy Press, Washington, D.C., 1980.

Larrew

whee

Ichimaru, M., Ishimaru, T. and Belsky, J. L., Incidence of Leukemia
in Atomic Bomb Survivors Selonging to a Fixed Cohort in Hiroshima
and Nagasaki, 1950-71. J. Radiat. Res. 19: 262-282 (1978).

Kato, H. and Schull, W. J., Studies of the Mortality of A-Bomb
Survivors. 7. Mortality, 1950-1978: Part 1. Cancer Mortality,
Radiat. Res. 90: 395-432 (1982).

Ishimaru, T., ec al., Incidence of Thytoid Cancer among Atomic
Bomb Survivors and Controls, Hiroshima and Nagasaki, 1958-1979:
Relationship to Radiation Dose Absorbed by Thyroid Gland. Unpub-
lished manuscript dared September 20, 1983,

Tokunaga, M., Land, C. E., Yamamoto, T., Asano, M., Tokuoka, S.,
Ezaki, E. and Nishimori, I., Incidence of Female Breast Cancer

Among Atomic Bomb Survivors, Hiroshima and Nagasaki, 1950-1980.
RERF Technical Report (in press).

Land, C. E., Cancers of the Digestive Tract and Accessory Organs,
In “Radiation Carcinogenesis” (A. C. Upton, R. E. Shore and
R, E.-Albert, Eds.), in press. Elsevier North-Holland, New York, 1994.

Brown, J. M., The Shape of the Dose-Response Curve for Radiation
Carcinogenesis: Extrapolation to Low Doses. Radiat. Res. 71:
34-50 (1977).

Land, C. E., Estimating Cancer Risks from Low Doses of Lonizing
Radiation. Science 209: 1197~1203 (1980).

Mays, C. W. and Spiess, H., Epidemiological Studies of German
Patients with Ra-224. In “Epidemiology Applied to Health Physics”
(Proceedings of the Sixteenth Midyear Topical Meetings, Health
Physics Society, Albuquerque, NM. January 9-13, 1983), pp. 159-166.
National Technical Information Service CONF-830101.

Ichimaru, M., Ishimaru, T., Mikami, M., Yamada, Y., and Ohkita, T.
Incidence of Leukemia in a Fixed Cohort of Atomic Bomb Survivors and
Controls, Hiroshima and Nagasaki, October 19$0—December 1978. Technical
Report 13-81, Riroshima, Radiation Effects Research Foundation, 1981.

Court Brown, W. M. and Doll, R., Mortality from Cancer and other

Causes after Radiotherapy for Ankylosing Spondylitis, Br. Med. 3.
= 1327-1332 (1965).

- 62 -

ae

=)


7
a

ious associations can arise by chance between cancer risk and
practically anything, or exposure can be fortuitously related
to a true risk factor, Burt such spurious associations are very
unlikely to arise in many different populations, exposed under
different circumstances. -We therefore tend to place most
credence in associations chat turn up frequently and under
diverse circumstances of exposure, while distrusting isolated
Teports not verified by other experience.

E. Quantification of Risk

Partly because we cannot tell for certain whether or not a person
will develop cancer, even when we have the most detailed information
possible about that person's physical condition, genetic background and
life experiences, and partly because, in our present state of knowledge,
carcinogenesis seems to be largely a random process, it is useful to
think in terms of probabilities. In other words, whether or not a person
develops cancer, and the time when that cancer becomes detectable, are
matters of chance. Most of what we know about cause-effect relationships
anc cancer rates in different population subgroups is useful to the extent
that it tells us how the probability of cancer diagnosis in a given person
at a given time depends upon certain observable facts. Thus, information
that ionizing radiation is associated with a particular type of cancer
should, if it is to be of any help to us, lead to improved estimates of
the probability that cancer will occur following radiation exposure.

It is not possible to tell whether or not a particular cancer
observed in a given individual following exposure to ionizing radiation
was caused by that exposure. Cancers occur in nonexposed people and are
in general indistinguishable from radiation-induced cancers. We often
can tell, however, if the number of cancers observed in a group of exposed
people is greater than the number that would have been observed in the
absence of exposure and, if so, we can estimate roughly how many of the
observed cancers were induced by radiation. Thus we can estimate the
excess risk, in an average sense, that pertains to any similar group of
exposed people. Such an estimate pertains to a single individual only to
the extent that that person can be considered “typical” of the group from
which the estimate was obtained. In a particular case of radiation ex-
posure, one must consider a number of relevant factors, including radia~
tion dose; sex; age at exposure; time following exposure; and additional
risk factors or modifiers.

F. Sex

For some organ sites, baseline cancer rates vary markedly by sex,
while for others there is no real difference. Sensitivity to the carcino-
genic effects of ionizing radiation also varies by sex and not always
according to the pattern of natural rates. Sex differences in sensitivity
seem to mirror differences in natural rates for leukemia and for thyroid
and breast cancer. For cancers that vary between sexes because of differing
exposures to carcinogens other than ionizing radiation (e.e., cigarette
smoking in the case of lung cancer) sex differences in sensitivity to
tadiation otherwise may be small or nonexistent (4). Although many

-~17-


30-35 years. Use of the constant relative risk model of time-response

for most solid cumors makes the dependence on the present PC tables for
estimates beyond this interval less hazardous than would be the case if

the constant risk model were to have been used. This fs because absolute
tisks within each age-at-exposure cohort of A-bomb survivors have continued
to rise steadily, tracking baseline mortality, well beyond the 1974 cut-off
that was the basis for many of the BEIR coefficients. ‘The constant rela-
tive risks resulting from these observations have been published through
1978 (4) and are seen in preliminary drafts of the current analysis that
extend through 1982. For leukemia and bone cancer, the wave-like functions
fall so precipitously after attaining their respective peaks that the Work-
ing Group has extended the tables beyond the period of observation to 49
years.

D. Age at Exposure

A rule that appears to hold for all radiation-induced cancers as a
group, and for many cancer sites individually, is that excess risk declines
relative to baseline risk with increasing age at exposure. Also, however,
because excess risk tends to increase over time proportionally with
baseline risk and because available data are limited to che period 30
yeats or so after exposure, absolute measures of risk rend to increase
with increasing age at exposure. For cancers of the lung, digestive
tract, and urinary system, which comprise a large part of both the excess
and baseline cancer risk in exposed populations, this increase appears to
be smooth (2,4), For some cancer sites, like the liver, bone, and, until
recently, the thyroid gland, there was insufficient evidence on which to
base estimates of variation by exposure age, and the BEIR age-specific
risk coefficients for these sites are flat. Three important sites,
however, are exceptions to the general rule.

A recent study of thyroid cancer incidence among A-bomb survivors
indicates strongly that absolute, as well as relative, measures of risk
are warkedly reduced for adult compared to childhood exposures (5).

Breast cancer, however, for which the existence of a tisk following
exposure during the First decade of life was only recently established
(14,15), shows an increase in absolute risk with increasing age at exposure
over the first two decades of life, but a marked decrease thereafter
(6,16,17). To the 1980 BEIR Committee, which relied mainly on Japanese
A-bowb survivor data for exposures after the age of 40, it seemed possible
that the apparent absence of an excess might reflect a hormonal influence
due to ovarian irradiation, or perhaps a difference between Japanese and
western populations (2). More recently, however, a large survey of

breast cancer mortality among Canadian women given multiple chest fluoros-
copies during treatment for tuberculosis revealed the same pattern of
greatly teduced risk for exposure after age 40 (17). Accordingly, the
Working Group computed new age-specific breast cancer risk estimates from
the most recent A-bomb survivor data (6), relying on a Study of Swedish
women given therapeutic X radiation for benign breast disease (16) to
provide a smooth downward transition in risk from age 40 down to 75, at
which age a zero excess was assumed.

- 60 -



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

ice

$0

20

o
ray

Fig X-l+a~6

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 50

70 to

Male ——
AGE AT DIAGNOSIS Female---

- 136 -


2.

7s

.

REFERENCES - Chapter iV

Oversight Committee on Radioepidemiological Tables, “Assigned Share
for Radiation as a Cause of Cancer, Review of Radioepidemiolgic Tables
Assigning Probabilities of Causation” (Final Report). National
Academy Press, Washington, D.C., 1984.

Young, J. Li, Jre, Percy, C. L., and Asire, A. J. (Eds.), "Surveillance,
Epidemiology, and End Results: Incidence and Mortality Data, 1973-1977."
National Cancer Institute Monograph 57. NIH Publ. No. 61-2330. U.S.
Government Printing Office, Washington, D.C., 1981.

Land, C. £., Boice, J. D., Jr., Shore, R. E., Norman, J. E., and
Tokunaga, Me, Breast Cancer Risk from Low-dose Exposures to Ionizing
Radiation: Results of Parallel Analysis of Three Exposed Populations
of Women, J. Natl. Cancer Inst. 65: 353-376 (1980).

Smith, P. G. and Doll, R-, Mortality among Patients with Ankylosing
Spondylitis after a Single Treatment Course with X Ray. Br. Med. J.
284: 449-460 (1982).

Whittemore, A. S. and McMillan, A., Lung Cancer Mortality among U.S.
Uranium Miners. J. Nati. Cancer Inst. 71: 489-499 (1983).

Prentice, R. Le, Yoshimoto, Y. and Mason, M. W., Relationship of
Cigarette Smoking and Radiation Exposure to Cancer Mortality in
Hiroshima and Nagasaki. J. Natl. Cancer Inst. 70: 611-621 (1983).

Blot, W. J., Akiba, S. and Kato, H., Ionizing Radiation and Lung
Cancer: A Review Including Preliminary Results from a Case-Control
Study among A-Boub Survivors. In “Atomic Bomb Survivor Data:
Utilization and Analysis” (R. L. Prentice and D. J. Thompson,
Eds.), pp» 235-248, SIAM (Soctety for Industrial and Applied
Mathematics), Philadelphia, 1984.

Kahn. H. As, The Dorn Study of Smoking and Mortality among U.S.

In: “Epidemiological Approaches to the Study of Cancer and other
Chronic Diseases” (W, Haenszel, Ed-), pps 1-125. Natl. Cancer
Inst. Monograph No. 19, U.S. Government Printing Office, Washington,
D.C., 1966.

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.

Rogot, E. and Murray, J. L., Smoking and Causes of Death among U.S.

Veterans: 16 Years of Observation. Public Health Rep. 95: 213-222
(1980).

-53-



Table PC-9-D. Lung Cancer 19 of More Yaars Aftar Exposure to
Low-LET Radiation, by Age ne at Exposure, Sex, and Dose
in Rad, for Present Ci geret @ Smokars, All. PC in Percent,
to Two Significant Digtts er Three Decimal Places.

4 Sex
Male Female
Cose

1 19 00 t i) 1900
10 224 2.3 34. +23 2.4 30.
tt -21 2.2 28. +20 2.2 28.
12 .f3 2.0 26. oh 2.0 26,
13 17 1.8 24. 183 1.9 24,
14 215 1.6 21. rary 1,7 23.
15 o'3 4.4 19, «14 1.8 21,
16 212 1.2 18. «13 4.4 20.
17 +18 tt 16. +12 1.3 18,
18 -092 98 15. ott t.2 17,
19 +083 «88 13. 19 td 16.
20 1374 73 12, +095 1.0 15.
25 +068 272 1h, 089 «95 14,
22 «061 ~68 10. -933 83 13.
23 «056 +60 9.4 2077 +83 2.
26 +052 $5 8.7 7272 77 12.
2s - 048 51 8.4 2068 +72 4,
26 2944 4? 7.8 +964 «63 un,
2? 041 44 7.4 060 64 mo.
28 -938 40 6.5 .057 -61 9.6
29 »O35 38 6.4 +056 58 9.4
HM -033 3.7 052 $6 8.8
3t -031 $5.4 aso 53 8.4
32 +029 5.0 a4s 33 8.1
33 027 4.8 O45 49 7.8
34 026 4.5 2046 48 7.4
3s 324 4.3 063 +46 7.4
36 1023 4.3 +942 45 7.3
37 022 3.9 04! 144 7.1
38 +021 3.7 2041 144 7.49
a$ 020 3.6 +040 643 6.9
43 .Ot9 3.8 +090 43 6.8
41 .0tF 3.3 033 +42 6.8
$2 2018 3.2 +039 242 6.8
43 -018 3.1 .039 +42 6.7
44 .O17 3.4 2039 $2 6.7
45 O17 3.0 +039 +42 6.8
46 O16 2.9 .039 «42 6.8
47 O16 2.9 «0460 «43 6.9
4s +916 2.8 2040 +43 6.9
49 2016 2.8 .041 146 7.0
54 045 2.8 +942 345 7.1

~ 322 -

Eade a

tata


Although epidemiology has not focused to any great extent on inter-
active effects between suspected or known carcinogenic risk factors,
there are a few well-known examples of such phenomena. It has already
been noted that alcohol consumption is generally regarded as a co-factor
that combines with cigarette smoking to elevate the risk of esophageal .
cancer. Similarly, the joint action of infeccion with hepatitis B virus
and dietary intake of aflatoxin has been cited as a cause of liver cancer
in certain African and Far Eastern populations. Dietary zinc deficiency
may also interact with alcohol consumption to increase the likelihood of
developing esophageal cancer (4), Furthermore, some investigators have
Suggested that air pollutants combine with carcinogens in cigarette smoke
to enhance the production of lung cancer (4). However, the most striking
example of an enhanced response resulting from the joint action of two
environmental carcinogens is the combined effect of asbestos and cigarettes.
The mortality ratios for workers exposed to either asbestos or cigarettes
individually were observed in one industrial study te be approximately 5-
and 10-fold, respectively, whereas the corresponding ratio for workers
exposed to both (i.e., asbestos-exposed workers who smoked) was in excess
of 50-fold (4). Cigarette smoking also appears capable of altering the
carcinogenic effects of ionizing radiation in certain circumstances, as
is discussed ia a later section of this report (Chapcer IV-H).

Caen

1

-~10-


man when delivered to the whole body. Moreover, the A-bomb survivor data
gave no clear evidence of a high-dose downturn in the carcinogenic response.
Finally, the BELR Committee was concerned mainly with applications to low-
dose exposures, for which the competing effect of cell inactivation is

not a serious consideration. Nevertheless, cell inactivation at high

dose levels is a likely explanation for increases in leukemia risk that
have been lower than would be predicted among patient populations piven
partial-body exposures, and partial-organ exposures in terms of active

bone marrow, at therapeutic dose levels for the treatment of ankylosing
spondylitis (76) and cervical cancer (77).

J. Modifying Effects of Other Exposures

The literature of experimental carcinogenesis abounds with examples
in which a co-carcinogen or promoting agent has been found to modify the
level of effect, or even the shape of the dose-response curve, for radiation
carcinogenesis. Examples in the epidemiological literature are rare, but
net unknown. Increased skin cancer risk was found among persons given
epilating doses of X rays as children for treatment of cinea capitis, but
the cancers occurred more commonly in those irradiated areas with high
levels of exposure to sunlight, did not occur in blacks, and among whites
occurred preferentially in persons with light complexions (78). Smoking
and radon exposure were found to interact multiplicatively among U.S.
uranium miners in the causation of lung cancer (79); that is, increased
risk per unit radiation dose was many times higher among smokers than
among nonsmokers. On the other hand, an additive rather than multiplica~
tive interaction was found among Swedish iron miners (80) and Japanese
A-bowd survivors (81). The similar excess breast cancer risks among
Japanese A-bomb survivors and medically irradiated U.S. women (50) suggest
that whatever causes American women to have about 5 times the lifetime
breast cancer risk of Japanese women does not interact synergistically
with fonizing radiation.

In summary, little is known about the influence of other physical
and chewical agents on radiation-induced cancer risk in man, and what
Little is known is generaliy consistent with additive interactions, at
least for low-LET radiation. The experimental literature suggests that
synergistic relationships exist, but they are yet to be discovered in
humans, and we do not know how important they are relative to other
determinants of risk.

XM. Extrapolation from One Population to Another

As mentioned above, epidemiological data relating cancer risk to
radiation exposure come from a variety of exposed populations but predom
inantly from patients given diagnostic or therapeutic X radiation and the
Japanese A-bomb survivors whose exposures were chiefly to hard gamma
radiation. Basing risk estimates on these data requires assumptions
about the comparability of the irradiated populations on which the esti-
mates were based with the population to which the estimates are to be
applied.

~27-



3

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

20

10

Fig X-1-C-1

LEUKEMJA: ALL TYPES EXCEPT CLL

EXPOSURE AGE 0

10

a5 20

AGE AT DIAGNOSIS

~ 167 -

30 3s

Male
Female ----



the U.S. data for exposures before 1961 are included in the weighted

average calculated by Jacobi, there is also reason to use a higher risk’
factor, such as the value 1.5 percent per WLM calculated from Czech and
Canadian data (60), for later exposures. The Working Group wishes to empha-
size, however, that the range of published risk estimates is somewhat greater
than from 0.7 to 1.5 percent per WLM, and that reviews by expert committees
may provide us with different estimates within the next year or so.

One marked difference between the above algorithm and that recommended
below for low-LET radiation is that in the above expression relative excess
does not depend upon age at exposure. In fact, age at exposure is difficult
to study in mining populations because exposure tends to be spread out
over many years. Moreover, given the uncertainty of age-specific risk
coefficients derived from the A~bomb survivor data, it is entirely possible
that, over the age ranges at which most mining exposures are received,
there is litcle variation in susceptibility by age at exposure. me

Another difference is that, for alpha radiation from imhaled radon
daughter products, a multiplicative interaction is assumed to hold with
tTespect to smoking. Thus, unlike the algorithm for external, low-LET
radiation, the relative excess is invariant under differences in swoking
level.

Estimates for low-LET radiation

Estimates based on the A-bomb survivor series and the British
spondylitis series are in good agreement (67). Accordingly, new risk
coefficients were calculated for low-LET radiation, based on the A-bomb
survivor lung cancer mortality data for-1955-1978 (28). Regression
coefficients calculated separately for exposure ages 10-19, 20-34, 35-49,
aod 50+ conformed to a roughly linear pattern of dependence on exposure
age; the absolute risk coefficients in Table VI-1, and the coefficients
for telative excess in Table X-9-A therefore incorporate a linear
dependence cn age at exposure, plus a correction for an estimated 30
percent underascertainment from death certificates. This correction allows
for some improvement in ascertainment effictency since the report of
Steer et al., which was largely based on autopsy and death certificate
data from the 1960s (68).

Lung cancer is not one of the cancers reliably identified by those
who fill out death certificates, but the errors are mostly in the
direction of under-reporting primary cancer of the lung and bronchus.

The NCI SEER data on the incidence of lung cancer in the US by age
and sex, for the years 1973+1981, are used for the normal risk of lung
cancer in calculating PC values for low-LET radiation. As way be seen in
Tables VII~1 and VII-2, the SEER reporting areas differ considerably in
their reported baseline levels of incidence (che range is 42 to 113 for
males) (8). Although the main risk factor for lung cancer is smoking,
for which adjustments can be made as discussed in Chapter IV, Section H,
and in Chapter IX, there are other important etiologic agents that may
pose difficulties, notably asbestos, polycyclic hydrocarbons, chloromethyl
ethers, chromium, nickel, and fnorganic arsenic (69). As noted in Chapter
IV-G and in Chapter IX, risk co-factors other than smoking may be taken

- 234 ~



among which are included other carcinogenic exposures, but it may vary
depending on the presence (or absence) of exposure to other carcinogens.

It is not possible to modify the PC formula to account for every
possible exposure that can be listed. For example, prolonged exposure to
inhaled asbestos fibers is a risk factor for lung cancer and for mesothe-
lioma. Although mesothelioma has not been shown definitely to be induced
by ionizing radiation, lung cancer has. If possible, therefore, it would
be desirable to ¢ike explicit account of the possible role of asbestos
exposure in the causation of a lung cancer in, for example, a shipyard
worker who had radiation exposures while working as a radiographer examin-
ing welds, who also had spent several vears installing asbestos insulation,
and who smoked two packs of cigarettes daily. It is impossible to undertake
so complete an analysis at this time, because data concerning such combined
exposures are not available, and further because we are not yet able to
classify asbestos exposures adequately with respect to lung cancer risk
in relation to duration and intensity of exposure or exact type or fiber
size of mineral.

Models

The way in which exposure to another carcinogen affects the PC
depends upon the magnitude of the carcinogenic effect of that factor in
the presence or absence of radiation. Although the interaction between
the two factors might, theoretically, be extremely complex (even anta-
gonism might occur), two interaction modes are especially simple and
natural, ane we confine our further attention to them. Those modes are
the multiplicative and the additive. We avoid using the term “synergism”
because it has been used by different writers with somewhat different
meanings, alchough some have defined it to mean what we call multiplicative
interaction and others as more than additive interaction,

(1) The Additive Interaction Model (AIM)

If the total excess risk from a radiation exposure and from another
risk factor is assumed to be the sum of the excess risks fram each of the
two taken separately, we say that thev interact additively. This is what
was assumed (on the basis of extensive information) for two vadiation
exposures in section F above. As in that section, if R(D) denotes the
relative excess for radiation at dose D and R(Z), the relative excess for
another factor at level Z, the relative excess for both factors combined
is

R(D,Z) = RCD) + RCZ).

Defining, in continuing analogy with section F, the altered baseline due
to 2 as

Lt = ¥ x (1+#R(Z)) = I/W(2),
the relative excess for radiation given the other factor is

R(D;Z) = (E(D,Z)~E(Z))/I' = (R(D,Z)-R(Z)) x W(Z) = RCD) x W(Z). — (iV-3)

-47 -



tose

Ban!

tadon daughter products are remarkable for the diversity of risk estimates
produced. Estimates based on reasonably large mining populations range
from 0.3 percent relative excess per WLM for U.S. uranium miners (59) to
3 percent or more in Swedish metal miners and Canadian uranium miners
(55). Reviews of the wining population data have tended to differ in the
amount of weight given to the various studies. In a recent proportional
hazard model analysis of data from Czech, U.S., and Canadian uranium
miners, Jacobi et al. obtained estimates of, respectiv .y, 1.5, 047 and
(about) 1.5 percent relative excess risk per WLM with . weighted average
of 1.2 percent per WLM (60). Another review, by Thomas and McNeill,
placed less weight on the U.S. uranium miner data and, using a different
analytical approach, obtained an overall estimate of 2.3 percent per WLM
(55).

Another source of variability in studies and reviews by expert
committees is the assumed distribution of excess risk over time following
exposute. Lundin et al. (61) postulated a lognormal model for time to
response in their analysis of U.S. uranium miner data, while Whittemore
and McMillan assumed a constant relative risk model in their analysis of
substantially the same data (59). The authors of NCRP Report No. 78 (62)
assumed a decreasing absolute risk model with a 20-year half-life for stem
cells transformed by alpha radiation (63). Recently, Jacobi et al.
introduced a ptoportional hazards model, incorporating the constant
relative risk model (60). Previously, Jacobi and the ICRP had employed
the constant absolute risk model (64,65). Ellect and Nelson (66) have
used lung cancer data from smoking and non-smoking iron miners in
Sweden to test various time-to-response models for lung cancer induced by
exposure to radon-daughters. Their analysis found that the constant
telative risk model gave a reasonably good fit to the observed age-at-
diagnosis data, whereas the BEIR model gave a marginally unsatisfactory
fit; the constant absolute risk model and the decreasing absolute risk
model of NCRP Report No. 78, on the other hand, deviated markedly from
these data.

Expert committees of the ICRP and the U.S. National Academy of
Sciences are now preparing, or will soon prepare, assessments of lung
cancer risk associated with exposure to radon daughters. In the meantime,
there is no one “official” estimate that appears to take precedence over
ail others. The estimate most nearly consistent with the approach of
the present Working Group {ts that calculated by Jacobi et al. (60);
according to that estimate, the relative excess risk R associated with a
single exposure of reasonably short duration, measured in WLM, might be
calculated as

R= Ux T(Y) x 1.2 percent per WLM

where U is the exposure in WLM, and the temporal factor T(Y) is defined
in the same way as for lung cancer following external, low-LET radiation.
The method of estimating exposure for U.S. uranium miners prior to :3$1
appears to have been different from that used after that date and those
used in other countries, and is considered on the whole to have over-
estimated exposure (55,61). There is, therefore, some justification for
using a difference risk factor for U.S. miner exposures before 1961, such
as the value of 0.7% per WLM estimated by Jacobi et al. (60). Because

~ 233 -



t
Lean

and

fia.

soced

Chapter III: RADIATION AS A CAUSE OF CANCER

4. Introduction

Although ionizing radiation has been a part of the natural environ-
ment since the world began, only within the past century has man begun
to study and use radiation as a tool in industry, biology, medicine, and
warfare. The study of ionizing radiation as a cause of cancer has been
particularly productive, with the result that we probably know more about
its carcinogenic effects than about those of any other environmental
carcinogen (1). This knowledge has been gained because it has been
possible to identify study populations with documented exposures to
fairly high radiation levels, and because ionizing radiation has proved
to be a precisely controllable means of inducing cancer experimentally in
laboratory animals. As a public health problem, ionizing radiation ranks
well down the list of carcinogens: less than 3% of the U.S. cancer burden
can be plausibly attributed to ionizing radiation from natural sources
and human activities (2), compared to around 30% for tobacco smoking (3).
We also know, however, that large doses of ionizing radiation can notice-
ably increase the cancer risk, and we are able to quantify these effects
with some confidence (4). For example, among 6,035 atom bomb survivors
in the Life Span Sample who were exposed to 100 or more rad, there were
498 deaths from cancer in the period 1950-1978, when only 323 such deaths
would have been expected on the basis of the experience of survivors ex-
posed to less than one rad, an increase of 54 per cent (5). Among the
23,073 exposed to 1-9 rad, however, the observed 1,248 cancer deaths are
no higher (even slightly less) than expected on the same basis.

B. Characteristics of Tonizing Radiation

Tonizing radiation includes electromagnetic radiation (such as X
Yays and gamma rays), and energetic subatomic particles (such as protons,
neutrons and alpha particles}. These radiations have the capacity to
Produce ions from atoms or molecules in their paths by adding or removing
electrons. A mechanism by which ionizing radiation induces cancer is
thought to begin with the absorption of energy within cells, leading to
alterations in che genome of the cell (1; see also Chapter If). Some
other forms of radiant energy, like ultraviolet light, can affect cellular
DNA directly and induce cancer, but not by fonization.

The energy absorbed per unit mass from the radiation traversing a
tissue is termed the absorbed dose. Absorbed dose (or, for simplicity,
dose) is measured in rad (1 rad = 100 erg per gram) or gray (1 gray (Gy)
= 1 joule per kg = 100 rad). Im general, the greater the dose, the
Breater the likelihood of an observable biological effect. Different
biological effects can interfere with one another, however; e.g., it is
Possible for the likelihood of cancer to decrease with increasing dose
at very high dose levels if cells that might otherwise give rise to
ue are so severely damaged that they lose the abilicy co multiply

2,4,6),

-13-



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

1090

30

20

19

Fig X-leAa

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 30

30

35 40 4s 30 $s 60 65

le ——
AGE AT DIAGNOSIS Fensleno-

~ 136 -


sites and cell-types, the empirical evidence is simply inadequate to
establish or deny carcinogenicity, and for some, e.g-, multiple myeloma,
the evidence seems rather controversial (see Chapter X, Section 13).
Authoritative lists of cancers considered to be radiogenic (1-4) are

based on judgment as to the sufficiency of the human data available and

the cogency of the evidence involving radiation as a cause. As a practical
matter, however, even if a particular tissue 1s considered to be sensitive
to the carcinogenic force of fonizing radiation, useful PC tables cannot

be calculated in the absence of reasonably good estimates of risk coeffici-
ents. It is this requirement, for example, that limits the preparation

of tables by cell-type to the leukemias. There are recent reports, for
example, linking brain cancer with exposure to lonizing radiation (5,6)

but none provides the kind of information that would be required for PC
calculations. Further, as has been noted for the various types of leukemia,
it remains possible that differentials may ultimately be established for the
risks of certain cell-types among the solid tumors. If there are large
probabilities of causation that involve sites of cancer other than those
selected for the PC tables, those cancer sites must be quite rare.

The Working Group accepted the BEIR III list of radiogenic cancers
with the following modifications: (a) lymphomas (including multiple
myeloma) were deleted; (b) salivary gland cancers were added; and
(c) “other” sites, needed by the BEIR III Committee in order to estimate
the totality of radiogenic cancer, and for which no real data exist, were
excluded. Of these changes, the first is discussed in Chapter X, Sec. 13,
the second in Chapter X, Sec. 3, Sites of cancer for which PC estimates
can be made, but for which the quantitative data are least reliable, are
salivary glands, esophagus, pancreas, liver, urinary bladder and kidney.

C. Source Tables of Cancer Incidence in the U.S. Population

Age- and sex-specific SEER rates for the U.S.A are averages for the
period 1973-1981 and for 10 areas containing about 10 percent of the U.S
population. Although the SEER sample is not a probability sample, it is
reasonably representative of the U.S population as judged by mortality
rates. The quality of the data is very high, only 1.4 percent of reported
cases depending on death certificates alone, and 92 percent being micro-
scopically confirmed (7). Geographic and ethnic variations are very real,
of course, especially for certain anatomical sites (7). In addition, over
the period of interest there have been important changes in the incidence
of cancer for certain sires, especially stomach and lung (7-9). Although
incidence data are not available systematically over time in the U.S.,
there are bench-mark data for 1947 and 1969-1971, and for some sites,
especially lung and stomach, mortality data adequately reflect incidence.
Incidence and mortality from stomach cancer have been moving down steadily
for some time. For example, the death rate for white males that was 16 per
100,000 per year in 1960 had fallen to 8.2 by 1977. Conversely, death
rates for lung cancer have been increasing rapidly over this period, the
comparable rates for white males being 38 in 1960 and 68 in 197?. Changes
in rates for other sites are less dramatic or seem less certain at the level
of incidence. For example, mortality from thyroid cancer has been falling
but there are indications of a 10 percent increase in incidence from 1970 to
the average for 1973-1981. There are also some changes for non-whites of

~- 80 -

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- 310 -



Tab

le PO-!-A-0. Chronic Granulocytic Leukemia Following

Exposure at Age 0, by Aga A, at Diagnesis, Sex. and Dose
in Rad of Low-L&T Radiation? PC in Percent, to Two
Significant Digits or Three Decimal Places.

A, Sex
Male Female
Dese

1 1g 100 1 10 100
2 29 a2. 34. 8s. 99.
3 52. $2. 5é. 93. 24.
6 $6, $3. 56. 93. 99.
s 7, $3. 52. 92. 99,
6 56. 93 47. ot. 99.
7 55. 33 $3. 83. 99.
& 53. 92. a1, 88 99.
% 34, 92. 40. & 99.
12 ay, 91 39. 8 $9.
14 47. 95 37. 8 99.
12 4S. 9B. 35. & 99.
3 42. as. 39. 8 99.
14 7. a6. 26. 7 98.
15 34, a3. 21. 74, 98.
1$ 27. ea. 18, 70. 93.
17 23. 76, 16. 6?. 92,
18 19. 72. ts. 65. 97.
19 16. 68. 15. $5. a7.
20 14, $3. 15. 65. 92.
ral ta, 53. 14, 64. 97.
22 9.7 54, 12. 5S. 96.
23 7.8 43. 9.7 54. 95.
24 6.0 41. 8.0 43. 94,
2s 4.8 35. 6.7 a6, $3.
26 3.9 31. $.? 39. $2,
27 3.5 28. 4.9 36. 96,
28 3.2 27. 4.2 32. 89.
29 3-2 26. 3.7 29. 88.
30 3.2 2$. 3.3 27. a6.
31 3.2 26. 2.9 24. 85.
32 3.8 25. 2.% 22. $3.
33 2.8 23. 2.3 20. ei.
4 2.5 22. 2.5 19. ao.
35 2.3 20. 1.9 17, 78.

- 273 -



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- 162 -


41.

42.

43.

45.

46.

50.

53,

54,

National Cancer Institute, "Surveillance, Epidemiology, and End
Results. Incidence and Mortality Data: 1973-1977." NCI Monogr. 57,
U. S, Govt. Printing Office, Washington, D.C., 1981.

The Distribution of Incubation
+ Epidemiol. 99: 92-100 (1974).

Armenian, K. H. and Lilienfeld, A. M
Periods of Neoplastic Diseases. Am.

Raventos, A. and Winship, T., The Latent Interval for Thyroid Cancer
Following Irradiation. Radiology 83: 501-508 (1944),

Mayneord, W. V. The Time Factor in Carcinogenesis: The 1977 Sievert
Lecture. Health Phys. 34: 297-309 (1978).

Sartwell, P. E., The Distribution of Incubation Periods of Infectious
Disease. Am. J. Hyg. 51: 310-318 (1950).

Mays, €. W. and Spiess, H., Epidemiological Studies of German
Patients with Ra-224. In: "Epidemiology Applied to Health Physics”
(Proceedings of the Sixteenth Midyear Topical Meeting, Health
Physics Society, Albuquerque, NM. January 9-13, 1983), pp. 159-166.
National Technical Information Service CONF-830101.

Ichimaru, M. and Tshimaru, T, Leukemia and Related Disorders.
J. Radiat. Res. 16 (Supplement): 89-96 (1975).

Land, C. E. and Norman, J, E., Latent Periods of Radiogenic Cancers
Oeeurring among Japanese A-bomb Survivors. In: “Late Biological
Effects of Lonizing Radiation”, Vol. 1, pp. 29-47. International
Atomic Energy Agency, Vienna, 1978,

and, C. E. and Tokunaga, M., Induction Period. In “Radiation
Carcinogenesis: Epidemiology and Biological Significance"

(J. 0. Boice, Jr. and J. Fraumeni, Jr., Eds.), pp. 421-436."
Raven Press, New York, L984.

Land, C. E., Boice, J. D., Ire, Shore, R. E., Norman, J. E. and
Tokunaga, Breast Cancer Risk from Low~Dose Exposures to Ionizing
Radiations: Results of Parallel Analysis of Three Exposed Populations
of Women. J. Natl. Cancer Inst. 65: 353-376 (1980).

Land, C. E., personal communication.
Land, C. £., Extrapolation from Large-scale Radiation Exposure.
In: “Assessment of Risk from Low-level Exposure to Radiation and

Chemicals: A Critical Overview", in press.

Gofman, J. W., “Radiation and Human Health.” Sierra Club Books,
San Francisco, 1981.

Steel, G. G. “Growth Kinetics of Tumours." Clarendon Press, Oxford,
1977.

~34-


REFERENCES = Chapter VI

Ichimaru, M., Ishimaru, T., and Belsky, J. L., Incidence of Leukemia !
in Atomic Bomb Survivors Belonging to a Fixed Cohort in Hiroshima and i
Nagasaki, 1950-71. J, Radiat. Res. 19: 262-282 (1978).

"U.S. Decennial Life Tables for 1969-71," Vol. 1, No. 1, DHEW
Publication No. (HRA) 75-3150, U.S. Department of Health,
Education, and Welfare, Public Health Service, Health Resources
Administration, National Center for Health Statistics, Rockville,
Maryland (May 1975),

Akima, H., A New Method of Interpolation and Smooth Curve Fitting
Based on Local Procedures, J. Assoc. Comput. Mach. 17: 589-602
(1970).

Committee on the Biological Effects of Ionizing Radiation, “The
Effects on Populations of Exposure to Low Levels of Ionizing
Radiation: 1980." National Academy Press, Washington, D.C., 1980.

Jacobi, W., Paretzke, He G., and Schindel, F., Lung Cancer Risk
Assessment of Radon-Exposed Miners on the Basis of a Proportional
Hazards Model. In “Proceedings of the International Conference
on Occupational Radiation Safety in Mining”, Oct. 14-18, 1984,
Toronto, Canada, in press.

-75 ~


PC = R/(1 + R)
is found as the product of three functions, i.e.,
R= FD) x T(¥) x R(Aq)
where F(D) represents the influence of the low-LET tissue dose (Dp), TY)
Tepresents the variation in R aver time in years (¥) after exposure, and

K(A,) represents the relative excess risk of breast cancer for a woman of
age A} at exposure, when both F and T = 1.

Under the linear model assumed for breast cancer, F = D for low-LET
radiation.

For breast cancer the influence of time (T) on the relative risk does
not vary by age at exposure but does depend on years from exposure to
diagnosis (Y) in che following fashion:

Y 0-4 5 6 7 8 9 10+
T 0 +074 «259 +500 2741 2926 L
The standardized relative risk of excess breast cancer, K, is given
in the accompanying Table X-10 for low+LET radfation and fot each completed
year of age from birth to 75.

A few examples should illustrate how the PC values are to be obtained
in individual cases.

Example 1 A typical female, aged 10 when exposed to 10 rad of low-LET
tadtation to breast tissue, with a diagnosis of breast cancer at age 35,
That ts, D = 10, Ay = 10, and ¥ = 25.

F(D)

10

MY) = 1(25) = 1

k(A),S) = K(10) = .0144
then R= 10 x 1 x 0144 = 1144

and PC = R/(1 + R) = .144/2.144 = .126 or 13%.

Example 2 A breast cancer was diagnosed at age 44 in a woman following i
several exposures to low-LET radiation at various ages. The first, of 7
one rad to the breast in which cancer was later diagnosed, occurred at

age 20, 24 years and 2 months before diagnosis (Y = 24). The second, to 2
rad, occurred 4 months later, at che same age (A) =20) but 23 years and

10 months before diagnosis (¥ = 23). At age 21, 23 years and 3 months
before diagnosis, a 9-rad total dose was received over a 36-hour period at
the continuous rate of 250 millirad per hour (Y = 23}. Finally, at age 35,
three exposures, to 1.1, 0.6, and 0.7 rad, respectively, were received on
consecutive days, 9 years and 2 months prior to diagnosis (Y¥ = 9).

= 244 ~


Table PC-6 (Continued). Colon Cancer 19 or Mora Years After
Exposure to Low-LET Radiation, by Age A, at Exposure, Sex,
and Dosa in Rad. PC in Percent, to Two Significant Digits
or Threa Decimal Places.

4a, . Sex
Male Female

Dese
t 10 100 1 10 149
63 -833 +35 3.7 038 «45 6.6
ee +033 -38 5.8 038 41 6.6
63 -O33 «36 5.8 939 82 6.7
64 .933 «36 3.3 039 +42 6.8
$5 +034 036 §.8 +040 -43 6.8
66 +034 «36 5.9 049 43 6.9
67 034 36 5.9 2043 43 7.0
63 034 38 3.5 ~94t 44 7.8
63 a34 +36 5.9 04% 344 7.1
70 034 36 5.9 +042 245 7.2
75 634 36 3.9 062 45 7.2
72 +036 «36 5.3 062 645 7.2
73 +934 38 5.9 +042 346 7.3
74 - O34 236 5.8 043 46 7.3
75 +033 36 5.8 063 46 7.3

mi

- 311 -


Table PC~1-A-10. Chronie Granulocytic Leukemia following
Exposure at Age 10, by Ace A, at Disanosis, Sex, and Dose
in Rad of Low-LET Radiation.© PC in Percent, to Two
Significant Digits or Three Decimal Places,

4, Sex

Hale Female I

Dose ry

T 70 Tae T 10 TO u
12 16 $7. 97, tt. 96.
13 32 BG. 99 22 98.
16 33 84, $9 23. 98.
15 30 82. 39. 20. $8.
16 26 79. 98, 17. 98.
1? 22. 75. 93. iS. 97.
18 19. Tt. 98, 54, 97.
19 16, 87. 97. 14, 97,
20 13. 62. 96. 14. 97.
21 wt. 57. 38. 13. 97.
22 9.9 54. 38, i 98.
23 7.1 45. 33. 8.9 95.
24 5.4 38. ot. 7.2 93.
25 4.2 32. 83, 6.0 92.
26 28. 87. 5.9 ot.
2? 3.0 25. 85. 4.2 a3.
28 2.8 23. Ba. 3.6 87.
29 2.7 23. 35. 3.1 gs,
39 2.7 23. a3. 2.7 34.
3 2.6 22. 33. 2.4 82.
32 2.5 21, 82. 2.4 : aa.
33 2.2 20. gi. 1.9 : 7a.
34 2.0 18, 79, 17 : 76.
35 1.8 16. 77. 1.5 : 74,
36 1.6 15. 75. 1.3 . 71,
37 1.5 13. 74. 1.2 : 69.
33 1.4 13. 72. 15 . 67.
39 13 12, 74, -98 8.7 65.
49 1.2 42. 69. -83 4.9 62.
41 wt ic 68. $2 8.1 6a.
42 it 10. 6S. 78 7.5 58
43 +99 3.7 65. +70 7a $?.
45 +93 9.2 63. +70 cee 57.
43 .8? 3.6 62. -76 v4 57

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- 274 -


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- 166 -


Exposure 3a:

F(3) = 3 + 32/116 = 3.08
T(23) = 1
K(21,£) = .00497

R3q = Fx Tx K = 3,08 x 1 x £00497 = .0153

Exposure 3b:

F(6) = 6 + 62/116 = 6.31
(23) =1
K(21,£) = .00497

Ray = F x Tx K = 6.31 x 1 x 400497 = .0314
Exposures 4, 5, and 6:

FCLel + 0.6 + 0.7) = F(2.4) = 2.4 + 2.42/116 = 2.45

T(9) = 6926

K(35,£) = .00153

Ras5o6 = F x Tx K = 2.45 x .926 x .00153 = .0035

R= Ry + Ro + Rag + Ray + Ras5.6 = +0057

+ .01146 + .O153 + .0314 + .0035 = .0673

PC = R/(1+R) = .0673/1.0673 = .063 = 6%.

The uncertainty surrounding PC estimates is discussed in Chapter VII,
and Section VII-O includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig X~4 has been drawn
for tissue doses of 10 and 100 rad of low-LET radiation, and PC values
plotted by age at exposure, for both males and females, and on the assumption
that the minimal latent period has been satisfied. The vertical scale is

logarithmic and curves are presented for only two radiation dose levels. wl
For these and other reasons interpolation is to be discouraged.

- 202 -


Promoter —

risk at different levels of some factor such as dose, time after
exposure, or baseline level of risk, in terms of a parametric function
of that factor. Ic becomes a projection model when data in a particular
range of factor values are used to assign values to the parameters in
order to estimate (or project) excess risk for factor values outside
that range.

Qe

an agent which is not by itself carcinogenic, but which can amplify
the effect of a true carcinogen by increasing the probability of
late-stage cellular changes needed to complete the carcinogenic process.

aed

Protraction -

PY

the spreading out of a radiation dose over time by continuous delivery ~~.
at a lower dose rate. '

person-years —

a unit used in epidemiological analyses, obtained by adding the
numbers of years of observation for all members of the group studied.
The number of PY may be used to predict the number of baseline cancers
expected in the population group studied.

Quality factor -

also QF or Q, the LET-dependent factor by which absorbed doses are
multiplied to obtain (for radiation protection purposes) a quantity
that expresses the effectiveness of an absorbed dose on a common
scale for all kinds of tonizing radiations. X rays at 250 kVp are
usually used as reference radiation (Q = 1).

Rad -

unit of absorbed dose of ionizing radiation = 100 erg/g mass; a newer
unit of absorbed radiation dose is the gray (Gy): 1 gray = 1 joule
absorbed energy per kg mass; thus 1 gray = 100 rad. (Average background
radiation in the U.S. is on the order of 0.1 - 0.2 rad annually.)

Radiation qualicy -

a general term referring to the spatial distribution of absorbed dose

in extremely small volumes of target tissue. For example, an exposure ui
to neutron radiation may be quantitatively the same as an exposure to ty
gamma ray, in the sense that, for volumes of tissue on the order of

one cubic centimeter, the absorbed enetgy is the same. Yet at resolu- Pal
tions of a few microns the ionizing events will be more uniformly :
dispersed for the gamma ray radiation then for the neutron radiation

(see LET), producing quantitatively different biological effects (see

CRBE).

- 352 +


Risk Coafficiant

Bone and Joint Cancer:
ECA, 8) by Exposure Age A, and Sex $

Table X-2-3,

Sax

A

Sex

A

Famale

Male

Fenala

Male

RR ee EOI BAN CoMonnscemennannwsmoes
RIMM Coe coe ennMnaMes sa sMMMNAT HT OOR RE ROO

NA NON ANNAN NNN NNN ON NNN ee ee

BoB R RRR Seer NNER s- weMenduonan onone
SOOO TE MMMM HH — COORD HOW DO

NNNAN NNN NUNN NNN ANNU NNN Ome eee

BREST NM SN ON WOOK NM Ee NOR MOO NEN
er DANO DG OOO COO ODOR RANE

SO OOO TAA O ROMO RN CONE EMH OWn

ROW OR OOR RE RANA RRR REAR RRR RRR RNR Oe

- 192 ~


SEER program —

Surveillance, Epidemiology and End Results, a nationwide system of
population-based cancer registries supported by the National Cancer
Institute to provide systematic cancer incidence data for the U.S.
Approximately 10 percent of the U.S. population is covered; data
for 1973-1977 are published, data are otherwise available through
1981. (The Working Group has used SEER data for base-line cancer
incidence rates in the present report.)

Stochastic -
a stochastic process is one in which the system incorporates an
element of randomness, as opposed to a deterministic system. As
used in this report (following ICRP), stochastic effects are those
in which the probability of an effect occurring rather than its
severity is a function of dose, without threshold.

Thorotrast -

a contrast agent used earlfer (1928-1955) for X ray diagnostic
procedures; Thorotrast contains radioactive thorium-232 dioxide.

Threshold (dose) -

a specified level of dose below which, it is assumed, no radiation
injury of a specified type occurs.

Time-response model ~
@ mathematical model expressing the conditional probability
distribution of the time from exposure to a carcinogen until
diagnosis of a cancer caused by that exposure.

Tinea capitis -
vingworm of the scalp.

UNSCEAR ~

United Nations Scientific Committee on the Effects of Atomic Radiation;
publishes periodic reports on sources and effects of ionizing radiation,

WL = Working Level -
any coubination of short-lived radon daughters in one liter of air
that will result {n the ultimate emission of 1.3 x 105 MeV of potential
alpha particle energy.

WLM = Working Level Month
exposure resulting from the inhalation of air with a concentration of

1 Wi of radon daughter for 170 working hours. One WLM corresponds to
a dose of approximately 6 rem.

- 354 ~



Puerto Rico. Presumably, these differencés are due to differential
exposures, and an individual case probably should be evaluated in terms
of that individual's exposure history rather than in terms of regional or
ethnic classification. For example, male lung cancer rates in Utah are
about half as high as those in the United States as a whole, but this is
ascribable to che fact that the proportion of smokers in Utah is smaller
than that in the rest of the country, due to the predominance of the
Mormon Church, which proscribes tobacco use among its members. As we
have seen above, nonsmokers have less than one sixth the lung cancer rate
among males generally. Clearly, for lung cancer, information about
smoking is more useful than information about area of residence and,
presumably, about other factors as well (i.e., a member of the Mormon
Church who suokes is unlikely to have a Lung cancer risk much different
from that of a non-Mormon with the same suoking history).

As a purely calculational exercise, it is a simple matter to define
a factor W for membership in a certain subpopulation, as the ratio of the
appropriate SEER rate to the corresponding subpopulation rate. Whether
this should, or can, be done, however, is another matter. Differences
between subpopulations with respect to cancer rates may depend mainly
upon differences in exposure histories, and except for exposure to tobacco
smoke, in the case of lung cancer, and radiation exposures other than the
one(s) of interest, there appears to be uo basis for a model by which
other exposures may interact with a radiation exposure of interest.
Siwply ignoring information about a possibly altered cancer rate, on the
other hand, amounts to treating the factors responsible as if they were
known to interact multiplicatively with radiation.

Although in the abstract it would be destrable to take account of
factors that interact additively in the appropriate way, we are ignorant
of the nature of interactions except for smoking and lung cancer. More=-
over, even if one wished to take account of a particular interaction as
if it were additive, the necessary data that would enable the calcula~
tions are not available. However, the relative risk time-response model
for radiation is consistent with existing data, and also with che idea
that many, if not all, other risk factors do interact multiplicatively
with radiation. It should be recognized, however, that to use the tables
ignoring the influence of any particular other factor, is equivalent to

treating that factor as one that interacts oultiplicatively with radiation.

- 52 -

5
3
a


27.

28.

29,

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

Beebe, G. W., Kato, H., and Land, C. E., Studies of the Mortality of
A-bomd Survivors. 6. Mortality and Radiation Dose, 1950-1974.
Radiat. Res. 75: 138-201 (1978).

Kato, H., and Schull, W. J., Studies of the Mortality of A-bomb Sur-
vivors. 7. Mortality, 1950-1978. Part I. Cancer Mortality.
Radiat. Res. 90: 395-432 (1982).

Wakabayashi, T., Kato, H., Ikeda, T., and Schull, W. T., Studies of
the Mortality of A-bomb Survivors. 7. Mortality, 1950-1978. Part
IfI. Incidence of Cancer tn 1959-1978, Based on the Tumor Registry,
Nagasaki. Radiat. Res. 93: 112-146 (1983).

Kato, He, et al., In preparation.

Day, Ne Ee, and Munoz, N.», Esophagus. In “Cancer Epidemiology and
Prevention” (D. Schottenfeld and J. F. Fraumeni, Jr., Eds.), pp-
596-623. W. B. Saunders, Philadelphia, 1982.

Tuyns, A. J., Pequignot, G., and Jensen, 0. M., Les Cancers de
l1'Oesophage en Ille~et-Villaine en Fonction des Niveaux de Consommation
da'Alcool et de Tabac. Des Risques Qui Se Multipltent. Bull. Cancer
(Paris) 64: 45-60 (1977).

Land, ©. Es, and Tokunaga, M., Induction Period. In “Radiation
Carcinogenesis: Epidemiology and Biological Significance” (J. D. Boice,
and J. F. Frauweni, Jr., Eds»), pp. 421-436. Raven Press, New York,
1984,

Nomura, A», Stomach. In “Cancer Epidemiology and Prevention”.
{D. Schottenfeld and J. Fe Fraumeni, Jr., Eds.), pp» 624-637.
W. B. Saunders, Philadelphia, 1982.

Brinkley, D., and Haybittle, J. L., The Late Effects of Artificial
Menopause by X-radiation. Br. J. Radiol. 42: 519-521 (1969).

Smith, P. G., and Doll, R., Late Effects of X-irradiation in Patients
Treated for Metropathia Haemorrhagica. Br. J. Radiol. 49: 224-232
(1976).

Dickson, R. J., The Late Results of Radium Treatment for Benign Uterine
Haemorrhage. Br. J. Radiol. 42: 582-594 (1969).

Wagoner, J. K., Leukemia and Other Malignancies Following Radiation
Therapy for Gynecological Disorders. In “Radiation Carcinogenesis:
Epidemiology and Biological Significance” (J. D. Boice, Jr. and

J. F. Fraumeni, Jr., Eds»), pp. 153-160. Raven Press, New York, 1984.

Schottenfeld, D. and Winawer, S$. J.: Large Intestine. In “Cancer

Epidemiology and Prevention” (D. Schottenfeld and J. F. Fraumeni, Jr.
Eds.), pp. 703-727. W. B. Saunders, Philadelphia, 1982.

- 265 -


Table VIi-I-A. Absolute Risk Coefficlente: Absolute Excess Cancer Incidence
per 100,000 Persona per Year per Rad (Organ Dose) at Low Levels of Low-LET
Radiation, by Site, Sex, and and Exposure Age, Averaged over the
Specified Follow-up Period

Site Exposure Yeate= Dose-response Model Sex,
Age Follow-up Ea F
Leukemia? 0-9 5-26 Linear-Quadratic +173 210
Call types 10419 5-26 «0854 «0543
except CLL) 20-34 5-26 0846 +0538
35-49 5-26 +105 +0670
50+ 5-26 +156 0990
Salivary? 0-14 19-30 Linesr—Quadratic 00104 200104
Esophagus? 20-34 10-30 Linear-Quadratic 20052 20052
35-39 10-30 0084 60084
50+ 10-30 20224 20224
Stomach} 10-19 10-30 Linear-Quadratic «0160 20160
20-34 10-30 +0308 +0308
35-49 10-30 +0508 «0508
50+ 10-30 134 +136
Colon? 20-34 10-30, Linear-Quadratic +0208 +0208
35-49 10-30 +0336 +0336
SO+ 10-30 20892 0892
Liver3 20-34 10-30 Linear-Quadratic +028 028
35-49 10-30 028 +028
50+ 10-30 +028 028
Pancreas? 20-34 10-30 Linear-Quadratic 018 +018
35-49 10-30 +030 +030
50+ 10+30 +0788 +0788
Lung? 10-19 10-33 linear~Quadratic 030 +030
20-34 10-33 056 +056
35-49 20-33 086 086
50+ 10-33 «120 2320
Breast? 0-9 10-35 Linear - +38
10-19 10~35 - +76
20-29 10-35 - +49
30-39 10-35 - 89
40-49 10-35 - “33
50+ 10-35 - 08
Urinary3 20-34 10-30 Linear-Quadratic -0200 +0200
35-49 10-30 0368 -0368
50+ 10-30 20648 0648
Tayrotd2 og 10-34 Linear «5 50
10-19 10-34 | lS =50
20-34 10-34 205 15
35-49 10-34 +05 «15
50+ 10-34 205 +35

~ 76 -

en

anda



Tabla PC-t-4-70. Chronic Granulocytic Leukemia Following
Exposure at Age 70, by Age A, at Diagnosis, Sex, and Dose
in Rad of Low-LET Radiation.” PC in Percent, to Two
Significant Digits or Three Decimal Places.

as Sex
Male Femaie
Dese

1 ¥@ 190 t +0 100
72 +37 3.9 53 5.4 30.
73 +90 8.9 1.2 t2. 70.
74 =98 9.6 1.3 tS, 71.
75 «9S 9.0 1.2 12, 79.
76 89 8.0 i.t 10. 67.
77 +69 7.9 192 9.1 63.
78 58 3.9 79 7.9 59.
73 47 4.9 «67 6.8 35.
ao ~40 4.1 $8 5.9 52.
81 «34 3.6 +50 s.3 $8,
82 +31 3.3 +43 4.8 43.
&3 229 3.0 +38 4.0 41.
84 +27 2.8 34 3.5 38.
8&5 +28 2.6 +30 3.2 36.
8s «23 2.5 +28 3.0 34,
3? +22 2.3 +26 2.8 33.
83 221 2.2 +25 2.6 3t.
8s 19 2.0 «23 2.4 30.
$9 18 1.F +22 2.3 29.
1 .v 1,8 20 2.2 27.
92 «16 1,7 Pak 2.0 26.
93 5 1.6 18 1.9 25.
9¢ 16 1.5 <5? 1.8 24.
$5 AS 1.4 ts 1,7 23.
96 43 1.4 15 1.6 22.
37 212 1.3 15 1.5 2t.
98 oft 1.2 +14 1.5 20.
99 4d 1,2 13 1.4 19,
10g +10 11 12 1.3 19.
it 098 1.9 ~12 1.3 18,
492 +093 to att 1.2 17,
183 085 +95 aft Wt 17,
104 085 .9t +10 1.3 16,
105 681 87 098 1.0 tS.

~ 280 -

uy
fq
ud

ta

Win anit


a After Exposure te
at Exposure, Sex, and Dose ia

to Two Significant Digits or Thr

Liver Cancer %0 or More Year
a y Aga A
PC in Parcant,

Low-LET Radiation, b

Rad,
Decimal Places.

Table PC-7.

Fesale

Mala

Dose

104

192

BIEN OD INE HH OE NORRIE UR OM OEM ORK
9099 00 9090 BROT OOOO AOINMMAMNMOAS Cree eee

90
90
89

MMNOM BENT OMAN NE
MAMMNANNN OT He ee

LIgteNenecon enaran-conns

WAM EK NOE NEAN ONE ONH ONO ROMO DOTNO WRATH
LAINIE ER OE Set POG DOAMNHNS Se TMM
PEM EO NN et
INCOWOS FEE HON DOEENONONNYN- TON wNY eMNUNe oS
RON SE OOO ONO TEE SOM MMMM NUNN NA NNN ANON
ote ee ko 8 EMO NN NOS OR ING INE NT BOON COIN
MOHORGEMEO ee te tt ee to twed et eet eee
NNT RK RE RK KOON CONT + FNM MNANNNNNR OOo Sheetal

QE KARIN FS OOK Om BNE OM On
tO eons FAMOMNNN
Nee ee TT te

124
22
21
2¢

SNiaseadd dak, Lake

- 312 -


Epidemiology —
the study of the determinants of the frequency of disease in man. The
two main types of epidemiological studies of chronic disease are cohort
{or follow-up) studies and case-control (or tetrospective) studies.

Etiology ~
the science or description of cause(s) of disease.

Fallout ~

vadioactive debris from a nuclear detonation or other source, usually
deposited from air—borne particulates.

Fluoroscopy -

a method of visualizing internal structures by directing X rays through
an object (e.g., part of the body) onto a fluorescent screen.

Fractionation -

the delivery of a given total dose of radiation as several smaller
doses, separated by intervals of time.

Gamma radiation =
also gamma rays; short wavelength electromagnetic radiation of nuclear
origin, similar to X rays but usually of higher energy (10 ke¥ to
9 MeV).
Geometric mean <
the geometric mean of a set of positive numbers is the exponential
of the arithmetic mean of their logarithms. The geometric mean of a
lognormal distribution is the exponential of the mean of the associated
normal distribution,
Geometric standard deviation (GSD) -
the geometric standard deviation of a lognormal distribution ts the
exponential of the standard deviation of the associated normal
distribution. The geometric standard deviation is not standard
for statistical terminology but is more commonly used by physicists.
Half-life -

(physical); the tine required for a radioactive element to lose
50% of its activity by decay. .

High-LET radiation -
radiation producing high jonization density along its track; includes

neutrons, protons, alpha particles, and the charged nuclei of higher
atomic-weight elements (see LET).

- 348 -

hot

“eat


Table VII-6 (continued)

Source of Uncertainty

Resolution by the
Working Group

Practical Effect on
PC Calculations

Other risk factors

No adjustment made,
except for smoking

than if based on the
constant absolute

tisk model; after the
period of observation
PC's will be generally
higher. Relative risk
models incorporating
Some variation over time
might increase or de-
crease particular PC
estimates

Unknown, and depending
on any interaction with
radiation.

~ ill -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100 +

$0

20

19

Fig X-2-3

BONE AND JOINT CANCER *
EXPOSURE AGE 20

20 25 30 3s 40 ery $0 35
Male ——
AGE AT DIAGNOSIS Female--<

*Alpha radiation from radium-224 only

- 185 -


Table VIi-9

Limits €or 90 Percent Credibility Intervals on Probabilities of Causation

(A) Lower Limits (95 percent)

Factor PC = 5% 10% 20% 30% 30%
Percent
0.2 1 2 5 8 17
0.3 2 3 7 1 23
0.4 2 4 9 15 29
0.5 3 5 ll 18 33
0.6 3 6 13 20 38
0.7 4 7- 15 23 41
0.8 4 8 17 26 44
0.9 5 9 18 28 47

(B) Upper Limits (95 percent)

Factor PC = 2% 5% 10% 202% 30%
Percent
1.4 3 7 13 26 38
1.6 3 8 1s 29 41
1.8 4 9 17 31 44
2.0 4 10 18 33 46
2.2 4 10 20 35 49
2.4 5 11 21 38 51
2.6 5 12 22 39 53
2.8 5 13 24 41 55
3.0 6 14 25 43 56
342 6 14 26 44 58
3.4 6 15 27 46 59
3.6 7 16 29 47 61
3.8 7 17 30 49 62

wah


fdoe

al
=

Loo

is the length of the follow-up period on which the risk estimates were
based, the models differ with respect to the likelihood that a radfation-
induced cancer will occur in any given year. For example, the 1980 BEIR
report estimated that, for a 100-rad exposure at age 15, the average ex~
cess breast cancer risk during years 11-30 following exposure (i-e., from
age 25 through age 44) is 730 cancers per year per million women exposed
(4, page 198). Ignoring intercurrent mortality, about 14,600 extra

breast cancers would be predicted during this period under either pro-
jection model, compared to about 10,000 which would be expected according
to population rates. But the distribution of the excess cases differs
markedly by model. The U.S. incidence of breast cancer per million women
(i.e., the number expected to develop breast cancer at a given age) is
about 64 at age 26, 435 at age 35, and 1,314 at age 44 (41). The absolute
risk model would predict 730 excess cancers at each of these ages following
a 109-rad exposure at age 15, while the relative risk model would predict
93 at age 26, 635 at age 35, and 1918 at age 44. Looked at in another way,
in a population exposed co 100 rad to breast tissue, 92% of the total
breast cancer risk at age 26, or 730 out of 794 cases predicted according
to the absolute risk model, would be radiation-related compared to 63% of
those at age 35 and 36% of those at age 44, while according to the relative
risk model, 59% of all breast cancers observed at each. of these ages would
be considered radiation-related.

Probability of causation calculations, which pertain to a particular
cancer diagnosed at a particular time following a particular radiation ex-
posure, clearly require an approach to response time that is more refined,
and less ambiguous, than that of the BEIR Committee. A number of authors
(42-44) have suggested that the lognormal model applied hy Sartwell (45)
to the incubation period for infectious disease may be appropriate for
radiation-induced cancer. This suggestion seems reasonable for those
cancers, like bone cancer (46) and leukemia (47), that have been observed
to follow a wave-like pattern of an increase in risk followed by a decline;
it seems less plausible, or less practicable, for cancers of sites like the
lung, female breast, and digestive tract, for which radiation-related ex~
cess risks were slow to become apparent and showed no signs of declining at
last follow-up (5).

Epidemiological data permit response-time analyses for only a few
cancer sites; the crucial considerations are (a) a high excess relative
to background, i-e., so high that most of the cancers diagnosed following
exposure can be assumed to be radiation-related; (b) an exposure of brief
duration; and (c) a lengthy follow-up period. These criteria are satisfied
best for bone cancer data from a German population given therapeutic ita-
jections of radium-224, a bone seeker with a half-life of 3.6 days.
Fifcy-three bone sarcomas were observed compared with only 9.2 expected,
so chat essentially all the cases can be considered to be radiation-induced,
and treatments lasted less than one year (46). Less pute, but nevertheless
useful, data pertain to leukemia (21) and breast cancer (48,49) among A-bomb
survivors. The criteria are satisfied to a lesser extent by lung cancer
mortality among A-bomb survivors (5,49} and breast cancer incidence in
patients treated by X rays for acute postpartum mastitis and in tubercu-
losis patients given multiple chest fluoroscopies (50), and marginally by
stomach cancer among A-bomb survivors (5,51). Thyroid cancer presents
special difficulties because it is usually an indolent disease which may

-21-


Table PC-9-E, Lung Cancer 10 or More Years After Exposure to
Gow-tET Radiation, by Age Ay at Exposure, Sex, and Doss
in Rad, for Presant Ci Sette Smokers, Under 19 per Day.
PC in Percents to Two Significant Digits or Threa Decimal

Places.
Ay Sex
Male Female
Dose

0 109 7 rT Ta9
19 -68 6.9 56. 66 6.7 38.
Bi bt 6.2 53. 61 6.2 33.
12 -55 3.6 50. 58 $.? St.
13 48 5.0 47. ~54 5.2 48.
14 +43 4.4 44, 46 4.7 46.
1§ +38 3.9 41. 142 4.3 44.
6 «33 3.5 38. +38 3.9 41.
17 +30 3.1 36. 35 3.6 39.
13 «27 2.8 33. +32 3.4 37.
+9 124 2.8 Bi. Mw 3.1 35.
20 +21 2.3 28. +28 2.9 34.
21 +20 2.1 27. +26 2.7 32.
22 ~18 1.9 25. 24 2.5 at.
23 216 1.7 23. +22 2.3 23.
24 15 1.6 22 -21 2.2 28.
25 14 1.5 20. -29 2.1 27,
26 +33 1.4 19. +8 2.0 2s.
27 t 1.3 18. .17 1.8 24.
23 alt 1.2 17, tT 1.8 23.
23 10 res 16, . 16 1.7 22.
30 095 1.9 15. 21S 1.6 22.
3t 2389 +95 1h, ary 1.5 21,
32 083 89 3. 214 1.5 20.
33 -078 84 43, 33 1.4 20,
34 074 +79 $2. 213 1.4 19,
35 2079 78 tt, .12 1.3 19,
36 - 066 71 14, +2 1.3 18.
3? ~063 -68 10, ~12 1.3 18,
34 -064 -65 10. .t2 1.3 8.
33 058 -62 9.7 +12 1.2 18.
4a +056 60 9.4 "1 1.2 17,
os -054 $8 aT aff 4.2 7.
42 +952 +56 8.8 1% 1.2 7,
43 O81 54 8.6 wif 1.2 17,
44 20469 .53 8.4 aff 1.2 17,
45 848 +52 8.2 -it tg 17,
46 647 -$1 8.0 wit 1.2 17,
47 -046 59 7.9 -1t 1.2 18.
48 +046 +49 7.8 +12 1.2 18,
49 2055 48 77 232 1,3 18.

- 324 -

svemg

canted


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

160

$o

20

10

Fig X-1~B-8

ACUTE LEUKEMIA
EXPOSURE AGE 70

70

7s

to
AGE AT DIAGNOSIS

- 146 -

100 ics

Male -—————
Female ----


gseee
soe
visto
414aa"
riety
44100
40z09

~ 169 +

arn enenae

: Uy aby ye sansodu3
SPUAY A 40RA Aa CAS VDL VOLENGT ANOLE Tesodwe, 1919 4¢NdKD Meda TEV -wLOUNROT “D-F-K PIREL

4 . oer


dose of radiation increases the probability of developing cancer by a
constant fraction of the baseline risk. Available data, particularly on
breast and leng cancer in Japanese atomic bomb survivors, which have
appeared since the preparation of the BEIR ZII report, support the relative
risk time-projection model more convincingly. Therefore, the Ad Hoc Group
has adopted this model, as discussed in Chapter III.

There is a substantial body of data on the risk of developing leukemia
{both acute leukemia and chronic granulocytic leukemia) after radiation.
Hence, it is possible to dvelop a model that accurately follows the observed
data. This model is basically wave-like in form, following neither the con-
stant absolute risk nor the constant relative risk time-projection model.
Accordingly, we have used the wave-like model to describe che risk of
developing leukemia as a function of time after radiation.

V. A problem awaiting resolution is the relative carcinogenicity of
high-LET radiation. This is the type of radiation delivered by large,
highly energetic particies such as neutrons or alpha particles. For the
same absorbed dose this kind of radiation appears to be more effective in
causing cancers than low-LET radiation, such as that delivered by X rays
or gawma rays. All the tables except for bone cancer, and for lung cancer
after exposure to radon (which occurs principally in uranium miners), deal
“with the more commonly occurring low-LET radiation. Several committees
are currently investigating the carcinogenic effects of high-LET radiation.
Pending their conclusions, it is not possible to use these tables relevant
to low-LET radiation for the calculation of PC estimates for high-LET
Tadiation unless a biologically equivalent dose can be determined for the
individual case.

Other estimates of probability of causation, or their equivalent,
have been prepared by British Nuclear Fuels, Limited (BNFL), by Gofman
(11), and by Stewart (12). ‘The BNFL procedure is not available to the
public, and certain objections have been raised to the Gofman calculations
(13). Stewart's analysis was based on data from the Hanford workers (14),
which are much too limited to provide any basis for a compensation system
(15,16). The present report represents a consensus of the Working Group,
aided by its interaction with the Oversight Committee of the National
Academy of Sciences and the Science Panel of the Committee on Interagency
Radiation Research and Policy Coordination,

Chapter I of the report outlines the Congressional actions that
mandated its preparation; Chapter I1 describes briefly what is known
about human cancer. Chapter III describes relations between radiation

a and cancer, including a listing of those cancers which may be caused by
radiation and for which adequate data are available to calculate PC, and
those for which an association with radiation is not proved. Chapter IV
a3 describes concepts involved in calculating the probability that any given
amount of radiation was the cause of any particular cancer. Chapter V
lists data sources and assumptions that are required for calculations of
PC values and justifies these choices. Chapter VI describes how the cal-
culations have been performed. Uncertainties in the basic data and
assumptions which are necessary ingredients in the calculation of proba-
bilities of causation are reflected in uncertainties in the final PC
values themselves. An attempt has been made in Chapter VII to identify



Radiogenic -

caused by radiation.

Radionuclide -

a radicactive atomic species.

Radon daughters —

(radioactive) decay products from the radioactive gas, radon (itself
a decay product from radium).

RBE = relative biologic effectiveness -

a factor used in comparing fonizing radiation of different types,
generally by measuring the effectiveness relative to 250 kVp X radiation.
For a given dose of given type of radiation, the RBE is the ratio of the
dose of 250-kVp X rays to the dose of the given radiation that will pro-
duce the same biological effect. For a given type of radiation, RBE
varies with the energy, the ; mgnitude of the dose, and with the end
point studied.

Relative risk -

an expression of excess risk relative to the underlying (baseline)
risk; if the excess equals the baseline risk the relative risk is 2.

Rew -

RERF

Risk

Sarcoma -

(rad equivalent, man); unit of dose equivalent. The dose equivalent
in “rem” is numerically equal to the absorbed dose in “rad“ multiplied
by the “quality factor” (see this), the distribution factor and any

other necessary modifying factor.

Radiation Effects Research Foundation; a Japanese foundation chartered
dy the Japanese Welfare Ministry under an agreement between the U.S.A
and Japan. The RERF is the successor to the ABCC (Atomic Bomb Casualty
Commission).

coefficient -

a fitted constant in an equation that describes how an effect depends
on dose.

a malignant growth arising in tissue of mesodermal origin (connective
tissue, bone, cartilage or striated mscle).

- 353 -



Example #3 A typical male, aged 7 at first exposure to 6 cad of low-LET
radiation to the salivary glands, and aged 12 at the second exposure to 5
rad of low-LET radiation, with diagnosis at age 20, 8.3 years after the
second exposure and more than 10 years after the first. This example
requires that two estimates of R be made, one for each exposure.

Exposure at age 7, when D = 6, Ay = 7, and Y = 13

F(6) = 6 + 62/116 = 6.31

T0113) = 1

K(7,m) = 0311
and R(7) = Fx Tx K = 6.31 x1 x .0311 = +196
Exposure at age 12, when D = 53, A, = 12, and ¥ = 8

F(5) = 5 + 52/116 = 5.22

T (8) = .741

K (12,0) = 0214

R12} = 5.22 x .741 x .0214 = .0828

then R = R(7) + R(12) = .196 + .083 = 279

and PC = R/(L + R) = .279/1.279 = .22 or 22%.

The uncertainty surrounding PC estimates is discussed in Chapter VII
and Section VEI-0 includes a derivation of approximate 90 percent credibility
intervais for PC estimates.

To provide some orientation to the general magnitude of the PC values
resulting From the procedures described here for the salivary glands, Fig
X-3 has been drawn for tissue doses of 1, 10, and 100 rad to show the PC
values by age at exposure and sex. The calculations were performed with
TCY) = 1, i.e., on the assumption that the interval from exposure to
diagnosis was 10 or more years. The vertical scale is logarithmic and

curves are presented for only three radfation dose levels. For these and
other reasons interpolation is to be discouraged.

- 196 -


A

The constant relative risk model for time to response does not hold
for leukemia, which appears to follow a “wave” function. The factor T is
the probability that a cancer caused by an exposure to radiation at age
A; will be diagnosed Y years later, T depends only on ¥ for CGL, but on
both Y and A) for AL and for all types considered as a group.

Several examples are provided to illustrate the procedures for calcula-
ting individual PC values:

Example #1 A typical female aged 5 at exposure to 5 rad of low-LET radia-
tion to the bone marrow, with a diagnosis of acute leukemia at age 9, 4.2
years after exposure. Here, D= 5, Ay = 5, Ap = 9, and Y = 4.

F(D) = 5 + 52/116 = 5.22;

T(Ay,¥)

T(S,4) «122, Table X-1-D;
E(A],S} = E(5,f) = 2.04, Table X-1-E;
I(A2,S) = 1(9,f) = 2.22, Table X-1-F;
R(A],A7,8) = K(5,9,£) = E/T = 2.04/2.22 = 919;
then R= Fx Tx K = 5,22 x .122 x .919 ='.585;
and, finally, PC = R/(1 + R) = .369 or 37%.
Example #2 A typical female, exposed at age 45 to 5 rad of low-LET radia~
tion to the warrow, with a diagnosis of leukemia at age 53, 8 years after
exposure, the leukemia not being well-established as to chronicity. In
this case, one would use the acute leukemia tables: D = 5, Ay = 45,
Az = 53, and ¥ = 8;
F(D) = 5 + 52/116 = 5.223

T(Ay) = T(45,8) = .0159, Table X-1-G;

E(A],S) = E(45,f) = 2.37, Table X-I-H;
1(Az,$) = 1(53,f) = 4.21, Table X-l+1;
and K = B/I = 2.37/4.21 = .563

then R= Fx Tx K = 5.22 x -0159 x .563 = .0467

and PC = R/(L + R) = .0446 or 4%, . -

'

Exauple #3 A typical male, exposed at age 35 to 10 rad of low-LET radia~
tion, with a diagnosis of CLL at age 60. In this case, no calculation
would be made as CLL is not an eligible diagnosis.

The uncertainty surrounding PC estimates is discussed in Chapter VII,

and Section VII-0 includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

-~ 4129 -


Table PC-1-B-20. Acute Leukemia Following Exposure at Age 20,
by Age A, at Diagnosis, x, and Dose in Rad of Low-LET
Radiation, PC im Percent, to Two Significant Digits or
Three Decimal Places.

Aa . Sex
Male Female
Bese

1 10 449 1 40 190
22 .35 3.7 $0 : 3.0 35.
25 2.7 23. Bs 2 20, ei,
24 4.8 38. 99 4 32. a9.
25 3.7 39. 92. . 36. gi.
26 5.7 40. 92. 5.2 37. $i.
2? $5.4 38. 91 5.9 36. Bi.
28 4.9 36. 30. 4.6 M. $0.
29 4.3 33. 389. 4.1 32. 89.
30 3.8 3o. 83. 3.7 29. ab.
34 3.3 27. BS. 3.2 26. Bb.
32 2.9 24. 8s 2.7 23. B4¢.
35 2.5 22. ge 2.3 20, as.
34 2.1 19, 30 1.9 7. 78.
35 1.¢ 17. 78 1.6 15. 75.
36 1.6 1$. 75. 1.3 13, 71,
37 1.4 13, 72. t.1 14, 68.
38 4.2 12, 69. 96 9.¢ 64,
33 1.0 10. 66. +8t g.t 60.
40 +90 9.0 63. -69 7.4 56.
41 +76 + 7.6 39. +359 6.6 52.
42 -63 6.46 34, “53 5.2 49.
43 51 3.3 49. 42 4.4 44.
44 942 4.3 44, 234 3.6 39.
45 +34 3.6 39. +27 2.9 34,
46 +28 3.2 33. ~%2 2.3 29
47 +24 2.5 at. ty 2.9 2
48 220 2.% 27. +16 3.7 2
49 17 3.8 24. 214 re) 2
56 18 4.6 2i, o13B 4.4 1
51 Vd 1.3 19. 1! 1.2 1
52 ott 1.2 17. ~10 14 1
$$ 2093 1.0 15. 086 692 1
546 +080 86 13. 074 79 12.
35 068 73 Wd. 063 68 t

- 283 -



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

i100

sO

20

19

Fig X-1-A-7

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 60

T
G s wee
y ~~ wee
10 RAD Sy
y
i
¢ _
i x
' .
pen
j Nor ~.
~ “ee
60 65 90 98
Male ———

AGE AT DIAGNOSIS

Female---


4

Faery

into consideration in interpreting the PC values derived by the procedures
presented here. If it is believed that some other risk factot operates
additively with radiation, and the individual is thought to have been
exposed to that risk factor to an extent greater than the average for the
population generally, then the PC obtained from the present procedures
may be somewhat excessive. But if it 1s believed that the second risk
factor may combine with radiation to enhance risk in multiplicative
fashion, the PC estimates based on these procedures should be unbiassed.

For lung cancer, the relative excess, R, in the basic equation
PC = R/{1 + R)
is found as the product of three functions, f.e.,
R = FCD) x TCY) x K(A],5)

where F(D) represents the contribution of the low-LET tissue dose (D) in
rad, T(¥) represents the variation in R over time in years (Y) after
exposure, and K(A,,S) represents the relative excess risk of lung cancer
for a person of sex S and age Ay at exposute, when both F and T= 1.

Under the linear~quadratic model assumed for the lung when exposure
is to low-LET radiation,

F= D+ D2/116.

For the lung, the influence of time (T) on the relative risk depends
only on years from exposure to diagnosis (Y).

Y a-4 5 6 ? 8 9 10+
T 0 2074 +259 +500 2741 +926 1

The standardized relative risk of excess lung cancer, K, is given in
the accompanying Table X-9~A for low-LET radiation and for each sex and
completed year of age at exposure from 10 to 75.

Because cigarette smoking dominates the risk of lung cancer in the
general population, the PC estimate should, 1f possible, take smoking
history into account. As explained in Chapter IV, the multiplicative
interaction model would require no adjustment for smoking history, but
the additive interaction model seems more appropriate for lung cancer, at
least for low-LET radiation. This requires that the influence of smoking
history be incorporated into the expression for R when calculating PC's.
This results in a multiplier for R, calculated as the average population
risk divided by the average risk in the relevant smoking category. This
ratio is Win the Chapter IV discussion, and the values developed there
are repeated in Table X-9-B. Then the value of R, modified to show the
influence of smoking status, becomes

R=FxTxKx We

- 235 -



Exposure at

and Dose in Rad of

er Followin

F-
Sex,
arcent, to Two Significant Digits

Nesis,

Bone and Joint Can,
PC in

ty Age Ay at pag

Raciatien.
hree Secimal Places.

Age 79.
Alpha

Table Po-2-70.
or

Sex

el

Famaia

Male

Dosa

190

19

10

o
MN ee eee er toto r)

DOH NOW MT HR NANO RMN

MMF NONE EEE MONE TH Ee eR ONO

ad

SM COT COT ENHOONR FOUNMNOM ORD MONK OTN
OR et tt eee tee OR OMNES IM

AF HOO ON OS eT IN ee weeteee

WO ANS FE EE MONE ON TINO OU N ON INNOWh
FITS 10 90 000900 00D OR OO OINUIE S FIMMONANNN
”

Se ee ee RAY ONO ONIN 0
SUNN Ns HUM men TORINO OA ONO NG

OL MRRNOT m ROROIN  mMN OE

TNE RON OR OT NO TNUR MEOH NMS NR WHO H NIN
ARR RE RRR OOOO DONO TORE E ROARS MOGOOOR

~ 304 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT }

100

“50

20

40

Fig X-1-B-5

ACUTE LEUKEMIA
EXPOSURE AGE 40

(7

AGE AT DIAGNOSIS

- 143 -



Table PC-9-A (Continued). tung Cancer 10 of More Years After
Exposura to Low-LET Radiation, by Aga A, at Exposure, Sex,
and Dosa in Rad, Given No Information of Smoking, PC in
Parcent, to Two Significant Digits or There Decimal Places.

: ay Sex
Male Female
Desa

7 io 166 7 Te 100
st +925 «27 4.5 10 16.
s2 «025 +27 4.5 «10 16.
53 +025 «27 4.4 att 16.
34 +025 +27 4.4 ait 17,
55 025 «2? 4.5 all 17,
se 2025 -2? 4.5 pars 18,
3? +926 «27 4.5 Pard 18,
58 026 -28 4.5 12 18.
39 026 +28 &.6 wt} 19,
60 -026 «28 4.6 wid $9.
61 027 «23 4.7 3 2c.
62 «027 +29 t& 20.
63 28 +30 14 ron
64 +028 38 218 21.
65 ra) +31 td 22.
66 30 -32 18 23.
47 3) +33 16 23.
68 .032 -35 Pars 24.
69 .033 36 38 24.
79 ~O35 «3? 18 25.
7) «036 3% 219 26.
72 40 td 26.
73 242 219 26.
74 -§3 20 27.
75 244 7.4 +20 27.

- 31? -


69.

70.

Vl.

72.

734

74,

755

76.

776

78.

79.

80.

$i.

Peto, R., Carecinogenic Effects of Chronic Exposure to Very ‘Low Levels
of Toxic Substances. Environ. Health Perspect. 22: 155~159 (1978).

Van Ryzin, J., The Assessment of Low-Dose Carcinogenicity. Biometrics
(Suppl.): “Current Topics in Biostatistics and Epidemiology”,
130-139 (21982),

Land, C. E., Estimating Cancer Risks from Low Doses of Tonizing
Radiation. Science 209: 1197-1203 (1980).

Tokunaga, M., Land, C, E., Yamamoto, T., Asano, Ms, Tokuoka, S.,
Ezaki, E. and Nishimori, I., Incidence of Female Breast Cancer Among
Atomic Bomb Survivors, Hiroshima and Nagasaki, 1950-1980. RERF
Technical Resport (in press).

Modan, B., Ron. E. and Werner, A., Thyroid Cancer Following Scalp
Irradiation, Radiology 123: +741-744 (1977).

Brown, J. M., The Shape of the Dose-Response Curve for Radiation
Carcinogenesis: Extrapolation to Low Doses. Radiat. Res. 71:
34-50 (1977).

Baverstock, K. F., Papworth, D. and Vannart, J., Risks of Radiation
at Low Dose Rates. Lancet i: 430-433 (1981).

Smith, P. G. and Doll, R., Mortality among Patients with Ankylosing
Spondylitis after a Single Treatment Course with X-Rays. Br. Med. J.
284: 449-460 (1982).

Boice, J. D., Day, Ns Ee, Anderson, A et al., Cancer Risk Following
Radiotherapy of Cervical Cancer. In diation Carcinogenesis:
Epidemiology and Biological Significance” (J. De Boice and J. Fs
Praumeni, Jr-, Eds.), pp. 161-180. Raven Press, New York, 1983.

Shore, R. E., Albert, R. E. and Pasternack, B. S., Follow-up Study
of Patients Treated by X-ray Epilation for Tinea Capitis: Resurvey
of Post-treatment Illness and Mortality Experience, Arch. Environ.
Health 31: 17-24 (1976).

Whittemore, A. S. and McMillan, A., Lung Cancer Mortality among
U.S. Uranium Miners: A Reappraisal. J. Nati. Cancer Insc. 71:
489-493 (1983).

Radford, E. P., and St. Clair Renard, K. G., Lung Cancer in Swedish
Tron Miners Exposed to Low Doses of Radon Daughters. New Engl. iJ. Med.
310: 1485-1494 (1984).

Blot, W. J., Akiba, $. and Kato, H., Tonizing Radfacion and Lung
Cancer: A Review Including Preliminary Results from a Case-control
Study among A-Bomb Survivors. In “Atowic Bomb Sutvivor Data:
Utilization and Analysis” (R. L. Prentice and D. J. Thompson, Eds.),
pp. 235-248. SIAM (Society for Industrial and Applied Mathematics),
Philadelphia, 1984,

-3-

meat)

i


ry

Lone

7(23) = 1

K(20,f) = .00230

Ro - Fx Tx Kx W = 2.03 x 1 x .00230 x 4.64 = .0217
Exposure 3a:

F(3) = 3 + 32/116 = 3.08

T(23) = 1

«00224

K(21,f)

Rgg =F x Tx K x W= 3.08 x 1 x 200214 x 4.64 = .0306
Exposure 3b:

F(6) = 6 + 62/116 = 6.31

T(23) = 1

K(21,£) = .00214

Rap = FX Tx Kx We 6.31 x 1 x .00214 x 4.64 = .0627
Exposures 4, 5 and 6:

F(1.2 + 066 + 067) = F(2.4) = 2.4 + 2.42/116 = 2.45

T(9) = .926

k(35,f) = .09104

R4o556 = Px Tx K x W = 2.45 x 926 x 00104 x 4.64 = .0109

R= Ry + Ro + Rag + Rap + Ras5s6 =

+ .0108 + .0217 + .0306 + .0627 + .0109 = .1367

PC = R/{1 + R) = .1367/1.2367 = .120 or 12%.
Example 3 A lung cancer was diagnosed in a man whose only known radiation
exposure was to inhaled radon and radon daughters while employed as a
uranium miner during the period 1950-1968. The most recent exposure
occurred more than 10 years before diagnosis. Total recorded exposure
was to 140 WLM, of which 100 WLM was before 1961 and 40 WLM afterward.
If the risk factor .012 per WLM is applied to the total exposure, the
calculated relative excess is

R= 140 x .012 = 1.68

and the PC is

~ 237 -



Table X-3. Salivary Gland Cancer: Relative Excess
KOA, »S) by Exposure Age Ay and Sex §

A, Sex A Sex
Male Female Male Female

¢ «0509 9446 8 +0290 - 0237
1 -0467 +0412 9 8270 0221
2 20433 330 19 ~0250 +0206
3 60405 +G35¢ "1 .0234 0194
4 9379 0325 12 0216 0183
3 0358 0300 13 20198 20474
é 9332 0277 14 20184 «0165
? 20381 0256

- 198 -



Fig. X-6

COLON CANCER

7

s
wa *S

100

a 2 Q
wn a - w _ “

(1N3943d)} NOLLUSAWD 40 ALITIGyaOud GALuWILS3

so £0 70
fale oe
female --=-

40

30
AGE AT EXPOSURE

20

10

°

~ 216 -


Some environmental and occupational doses are quite small, on the
order of those resulting from natural background radiation to which we
are all exposed (about 0.08 to 0.2 rem per year in the United States).

It might be supposed, therefore, that studies of populations living in
Tegions where background levels vary greatly would yield estimates of
carcinogenic risks associated with such differences. Several such studies
have been attempted, but the risks are so low that any effect of variation
in background radiation is overshadowed by the natural variations in
cancer incidence (1,7-9). At the present time, estimations of effects at
low doses are based upon assumptions as to the mathematical form governing
the dependence of effect upon dose, since we must extrapolate from the
dose region where we have evidence of effects, to lower doses where
effects have not been observed or may not be large enough to be detectible.

In general, the Working Group has sought to use the dose-effect
model for each cancer which is most consistent with both the huwan epi-
demiologic data and the radfobiological data. For leukemta, the data are
consistent with a so-calied Linear-quadratic model; hence this model is
the basis for the PC tables calculated for leukemia. This model utilizes
two constants and, in general, predicts that small doses of radiation
have a lesser effect per rad than do higher doses. There are tadiobiolog-
ical reasons for assuming that a linear-quadratic dose-effect modet is
generally applicable to other cancers, which are discussed both in the REIR
IIL report and in Chapter IIL of the present report. Accordingly, we
have used this approach for ali cancers except those of the thyroid and
breast. For carcinoma of the breast and thyroid, the data appear to be
best described by a simple linear relationship in which the carcinogenic
effect of radiation is directly proportional to the dose; again, the
tables are based on this interpretation.

Tl. The Working Group also had to consider the relative effective-
ness of radiation delivered at different dose rates. Although there are
no conclusive human data on the carcinogenic effect of radfation delivered
at a very low dose rate relative to that delivered at a high dose rate
{atom bomb survivors, therapeutic radiatior), several national and inter-
national bories have suggested that radiation of low linear energy transfer
(low LET) is considerably less carcinogenic at a low dose rate than at a
high dose rate (6,7,10). I€ a linear-quadratic model is used, no separate
dose-rate correction is necessary for protracted radiation exposures, given
a certain partitioning of the dose (see Chapters III-I and V=-B). In the
case of carcinoma of the breast and thyroid, the use of the linear dose-
effect model implies chat there should be no dose-rate effect; data
available for both of these cancers are consistent with this prediction.

I¥, An additional assumption required for calculation of PC values
concerns the relationship between the number of cancers produced at any
given time after radiation and the number normally occurring in a similar
population of the same age and sex not exposed to radiation. The BEIR
IIT report utilized both a relative risk time projection model and an
absolute risk time-independent model. The absolute risk model assumes
that the radiation-induced risk of developing cancer is constant after a
suitable latent period following irradiation. ‘The relative risk time
projection model states that, at any time after a latent period, a given

-iv-


Fig. X-8

PANCREAS CANCER

iJ
.

10

100

o
n

9 c=)
” 7 “ n “

CLNZ283d) NOLLYSAWD JO ALITI@UEOUd CALYWILSa

male
Female aos

AGE AT EXPOSURE

- 230 -


with models for low-dose extrapolation of risk, the unresolved issues for

extrapolation from one population to another involve questions fundamental
to the nature of carcinogenesis.

- 30 -

toe



Tabla PC-9-A. Lung Cancer {0 or More Years After Exposure to
Low-LET Radiation, by Age a, at Exposure, Sex, and Dose
in Rad, Given No Information on Smoking. PC in Percent,
to Two Significant Digits or Three Decimal Places.

Ay Sex

Male Female

Teen

i

a
2
o|
2
3
al

18 39 4.0 42. 3.7 51.
41 +35 3.7 39. 5.2 49.
12 +31 3.3 37. 4.8 46.
13 +28 2.9 34. 6.4 $4.
14 +24 2.6 si. 4.0 42.
15 +22 2.3 28, 3.7 39.
16 19 2.0 26. 3.3 37.
17 a1? 1.8 24. 3.1 33.
8 15 1.6 22. 2.8 33.
19 114 1.3 26. 2.6 32.
20 rd 1.3 19. 2.4 3a.
21 ~1t 1.2 17, +22 2.3 23.
22 259 wd 16. -24 2.4 2?.
23 +093 -99 15. 3 2.0 26.
24 «086 91 14, 18 Fo 26.
2s 2379 +84 13. = 16 t.? 23.
26 +073 78 12, 16 t.6 22.
27 - 067 +72 M4. 15 1.6 at.
28 «062 67 19. IG 1.5 20.
23 .088 +62 9.7 13 $.4 20.
39 - 054 +58 9.9 713 1.3 19,
31 051 ~34 8.6 rar4 t.3 18.
32 ~ 048 3? 8.1 +12 1.2 18.
33 +945 48 7.6 ott t.2 17,
coy +042 43 7.2 wad t.t 17,
35 +049 ~43 6.9 ~i0 tad 16.
36 +038 $3 6.6 ~10 1d 16,
3? +036 +33 6.3 +40 1 te.
33 +035 3 6.9 099 tt $$.
39 033 36 3.8 098 1.0 15.
$0 +932 «34 3.6 -996 1.0 15.
41 «O31 -33 3.4 «096 1.9 t$.
42 038 .32 $.2 - 095 1.8 5.
43 +029 34 $.t 1995 1.0 3.
44 023 -30 3.90 -095 1.9 1S.
45 +928 -36 4.9 +095 1.8 3,
46 +927 +29 4.8 +096 1.8 tS,
47 ~92? +28 4.7 +097 1.8 15.
48 -026 «28 4.6 O98 1,8 13.
43 026 -28 4.6 +099 t.4 15,
34 026 +28 4.5 +10 Wa 16.

~ 316 -


Table VII-6 (continued)

Source of Uncertainty

Resolution by the
Working Group

Practical Effect on
PC Calculations

Dose-response
function

Dose-rate

Time-response model

Linear-quadratic (LQ)
model assumed for low~
LET exposure, linear
{L) for thyroid and
breast

Fractionated or con~-
tinuous exposures with-
in a 24-hour period
are treated as single
exposures. Other ex-
posures separated in
time are treated in-
dividually, not summed.
Accumulations over
longer periods are
treated as separate
exposures occurring on
different days

Constant relative risk
model for solid tumors
except bone; wave func-
tion for leukemia and
bone

- 110 -

The true PC may be
greater or less, depen-
ding on the actual form
of the dose-response
function. PC's calcu~
lated at less than 2%
may be too large or too
small by not more than
a factor of 2.5, PC’s
of 5-20%, by not more
than a factor of 2,

and larger PC's, by
lesser amounts

Ignoring fractionation
within a 24-hour period
probably overestimates
tisk by an amount no
greater than the quad-
ratic coefficient mul-
tiplied by dose~squared.
Under the linear model
fractionation does not
affect estimated risk

For leukemia and bone
cancer, for which a
wave function is clearly
indicated, any uncertain-
ty relates not to the
choice of the model but
to its precise forn.
For other tumors the
effect on PC values
depends on the interval
between exposure and
diagnosis and whether
it falls outside the
period of observation.
Within the period of
observation PC's will
be lower toward the
beginning of expression,
and higher thereafter,

(continued)



Table X-4. Esophagus Cancer: Relative Excass K(A;,5)
by Exposure Age 4, and Sex §

4, Sex 4, Sex

Male Female Male Female

—————______ ———
20 -00207 00562 48 090466 «00146
21 709184 09497 ag «000464 .O0155
22 00164 19442 30 -000483 090188
23 -00147 00396 $i 000504 00166
24 «06132 «00388 52 000527 00174
25 700129 90320 53 -G0055$ +00183
26 200169 00289 54 ~ 000576 700192
2? + 600992 «90262 535 000603 00201
28 000908 90239 36 000630 00219
29 -009835 +00220 37 000653 ~G0219
30 «009771 - 09206 53 000588 ~20228
31 900716 00190 34 000789 «00237
32 «9006467 0O17F 60 -9G9752 200245
33 «000624 +00169 61 -000785 90253
34 090586 00160 $2 - 990822 00259
35 000556 00153 $3 + 000857 00265
36 600525 «00146 64 000891 00270
7 ~000499 00460 65 - 020924 00276
38 +000477 06136 66 .000955 20279
ey) «000457 00132 67 «090982 «00282
40 906939 00128 63 00501 ~ 00285
4i «009923 200126 69 08103 00287
42 000611 00525 7¢ + 00105 00288
43 0004665 «00124 71 ~00196 00288
a 000405 00126 72 +90 107 - 00287
45 +000419 200129 73 0007 902846
4% .000619 209533 74 09108 00281
47 600431 00438 75 01g? 96278

- 204 -


el

6. Medical therapy and diagnosis

Some agents used in the past to diagnose or treat various diseases
have subsequently been shown to increase the risk of cancer, and their
their use has been curtailed. Examples include inorganic trivalent
arsenic (skin cancer), chloronaphazine (bladder cancer), the radioactive
contrast agent, thorotrast (cancer at the organ of concentration), and
diethylstilbestrol (vaginal adenocarcinoma) (4). Ionizing radiatfon and
some of the drugs that have been found to possess carcinogenic potential,
such as certain alkylating agents used to treat different types of cancer
and various immunosuppressive drugs employed in organ transplantation,
continue to be used with discretion, insofar as their expected benefits
ate considered to outweigh their known risks.

7. Sexual development and behavior

Hormonal stimulation associated with normal sexual development
influences the risk of cancer in humans. For example, the risk of breast
cancer in women is affected by age at menarche, age at first childbirth,
and age at menopause. The incidence of testicular cancer is elevated in
men born with cryptorchidism or undescended testes. The likelihood of
developing cancer of the uterine cervix increases with the number of
different sexual partners that a woman has had (4).

8. Viral infections

Viral, infections are a known cause of various cancers in animal

species and have been regarded as potential-risk factors in the development

of human tumors. The Epstein-Barr virus is thought to act as a causative
cofactor in the onset of Burkitt's lymphoma (in Central Africa and New
Guinea) and nasopharyngeal carcinoma (in the Far East, especially South
China). Hepatitis B virus evidently plays a role in the development of
hepatocellular carcinoma, particularly in Asia and Africa (3,4).

Other viruses of possible importance in human reproductive tract
cancer development include herpes simplex virus (4) and cytomegalovirus
(4). Human T-cell leukemia virus (18) has been isolated and sequenced
and is clearly the etiologic agent in this type of leukemia. At the
present time, the role of retroviruses or oncogenes in other cancers is
unclear, but it could well be that activation or mutation of oncogenes
are importent factors in the genesis of many cancers.

9. Interactive effects

The preceding discussion of carcinogenic risk factors concerned
primarily the effects of individual agents, whereas humans are ordinarily
exposed to a variety of agents. The potential for interactions among the
effects of different risk factors should also thus be considered. The
interaction of two factors can be expressed in a variety of ways. For
example, one may act as a vector that carries the other to a critical
target site; the first may promote or enhance the carcinogenic activity
of the second; the two may act independently; or they may produce a joint
effect which markedly exceeds the sum of their separate effects.

-9-



at Exoosure,

y Age A,
PC in Percent, to Two Significant

Kidney and Bladder Cancer 10 or More Years After
Digits or Three Decimal Places.

Exposure to Low-LET Radiation, b

Sex, and Dose in Rad.

Table PC-11,

Sex

Female

Male

Dose

190

19

100

10

MMNNNNANNN OOO eee enn eee errr tee

wonins
COR OOS NTH BAO BONE FMAANT HH ODOT RED GRARGA DRANG
veeere eoeo

POMONA RK KO te tt et yt nen ed ee
el neal ee ee eo eo

NNR BNOMMME ONE OM H OR MINR OF DNEMNNT HOODOO RANT
Se OO dO SOE FE ET AAO MMA

AD AN = HON ONO ON OF IMINY HT OOM HOON
OLDS HO 10 FO DAA FT SONA AMET HS OHI OH OIE
Se HBB OSOOOSODOCOOESOCODS SOD SBVOOGOOSCSODOCe

- 335 -


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.

snd

“Annual Cost Estimate

Estimated annual cost for operating the Ad Hoc Working Group, including
compensation and travel expenses for members but excluding staff support,
is $36,700. Estimated annual man years of staff support required is one
at an estimated annual cost of $49,213.

“Reports

Section 7(b) of Public Law 97-414 directs that within one year after the
date of enactmenc 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



a

EXECUTIVE SUMMARY

Public Law 97-414, the Orphan Drug Act, passed by the Congress and
enacted on January 4, 1983, directed the Secretary of Health and Human
Services to construct radicepidemiological tables showing the probability
that certain cancers could result from prior exposure to radiation,

To ensure as far as possible thar the radioepidemiological tables
would represent the best possible scientific judgment, the Secretary of
Health and Human Services established the NIH Ad Hoc Working Group to
Develop Radioepidemiological Tables. To assist the Working Group, the
NIH and the Assistant Secretary for Health requested the National Academy
of Setences to form an advisory committee (the National Academy of Sciences
Oversight Committee on Radioepidemiologic Tables), The Working Group would
like to thank Dr. C. Frederick Mosteller and the other members of the
Oversight Committee for their constructive criticisms, which have been of
great benefit during the preparation of the report. The Working Group
also benefited greatly from the groundwork laid by the National Council
on Radiation Protection and Measurements (NCRP) Committee No. 71, which
already was addressing the question of probability of causation (PC) for
radiogenic cancers. Finally, the Working Group has had an opportunity to
interact with the Science Panel of the Committee on interagency Radiation
Research and Policy Coordination, Office of Science and Technology Policy,
Executive Office of the President, during the course of the Panel's
evaluation of the tables, and has its report dated November, 1984.

In constructing the tables, the NIH Working Group and the Oversight
Committee identified the same set of problems involved in the calculation
of probability of causation for cancer following exposure to Lonizing
radiation. Additionally, the Oversight Committee has made several important
suggestions that a future committee, whose task is to update this report,
should find useful.

The Working Group determined that it could not attempt a new analysis
of the epidemiologic data but should base many of its calculations on the
teport issued in 1980 by the National Academy of Sciences Committee on the
Biological Effects of Ionizing Radiation (BEIR IIL) (1) that itself had
required more than three years to complete. The Working Group, however,
did depart from the BELR IL} report in several important details because
of the availability of new data. These include adoption of a new “wave
function” time-response model for leukemia and bone cancer, different co-
efficients for leukemia and cancers of the lung, thyroid and breast,
addition of cancer of the salivary gland, omission of lymphoma as a
radiation-induced cancer, and avoidance of PC calculations for certain
cancers following exposure at younger ages. Overall, of the 78 age-,
sex~, and site-specific risk coefficients employed in the present report,
40 were taken directly from the BEIR III report and 38 were obtained from
more recent sources.

The problems recognized by both groups can be resolved more accurately
in the future through the accumulation of more human data, and especially
by new insights into the mechanisms of carcinogenesis, and perhaps, rather
less by mathematical ingenuity or further in-depth analysis of existing



For the second, ignoring the first,
F(D) = F(3Q) = 30
TY) = 1(8) = .741
K(A,S) = K(17,m) = .0397 (Table X-12)
R(2) = Fx Tx K = 30 x «741 x .0397 = .883 ld

The relative excess R and the PC for the combined exposures are

R= R(1) + R(2) = 10.6 + .883 = 11.5
PC = R/(L + R) = 12.5 / 12,45 = .920 = 92%

* * *

Wilms’ cumor is nearly always fatal unless treated, and it is highly
likely that in the preceding example the high-voltage X ray therapy saved
the patient's life. Thus the calculation of greatest interest might well
concern the extent to which the patient's cancer is attributable to his
second exposure alone. Simply ignoring the first exposure gives R = R(2)
and

PC(2) = R(2)/(1 + R(2)) = .883/1.883 = 0.468 = 47%, .

This calculation treats the patient as if he were a member of the general
population; it is clear, however, that he ig not. The tadtation that saved
the subject's life from Wilms’ tumor also, as a side effect, increased his
chances of getting thyroid later in life. Therefore he is a member of a
subpopulation with a baseline rate that is different from the general
population. As a group, men given a 100-rad thyroid dose in infancy have
a thyroid cancer risk, in the absence of other exposure, 1 +° R(1) times

as large as that of the general population. Therefore the relative
excess, in the context of that subpopulation, is

R'(2) = R(2)/(1 + RCL)) = -883/12.6 = .0761.
The PC calculated from R'(2) is
Po'(2) = R'C2)/(1L + R'C2)) = .0761/1.0762 = .0707 = 7%.

The Ad Hoc Working Group considers the last calculation the most appropriate
in this case.

In Chapter I¥-F the quantity Wis introduced as the ratio of base-
Line rates in the general population and the subpopulation. In the above
example W = 1/( + R(1)), and R'(2) = R(2) x W. This method allows the
computation of a PC for a member of a population having a baseline risk
different from the general population by méans of the formula
R= FxeTxkxwW,

provided that the factors causing the subpopulation to have a baseline risk

- 122 -


Tabla PC-9-D (Continued). Lung Cancer 10 or More Years After
Expasure to Low-LET Radiation, by Age A, at Exposure, Sex,
and Dose in Rad. for Present Cigarette dnokers, ALL.” PC in
Percent, to Two Significant Digits or Thraa Dacimal Places.

Ay "Sex
Male Female
Dose

t 19 400 t 10 seo
5t 018 2.8 ~ 042 45 7.3
52 +015 2.7 o4s 46 7.4
$3 +615 2.7 1044 4? 2.5
54 O55 2.7 +645 +49 7.7
$5 +615 2.7 ~ 0467 +50 7.9
56 2018 2.8 +048 -51 gt
5? 085 2.8 049 -53 8.3
58 ary 2.8 +051 34 8.6
39 +046 2.8 -952 ~56 3.8
63 «016 2.9 2054 «57 9.0
$1 O16 2.3 -055 59 9.3
62 -046 2.9 +057 65 9.5
63 O17 3.9 -089 63 9.8
64 017 3.1 +064 65 10.
65 018 3.1 063 .67 tO,
66 2098 3.2 «065 69 ti.
6? +015 3.3 067 +72 vy
6s 2018 3.5 079 75 We
$3 «020 3.6 +072 +27 12.
70 24 3.7 07S +79 12.
7+ 022 3.9 076 +82 12.
72 -025 4.0 +078 83 13,
73 023 45 1679 185 13.
4 6026 4.3 081 -86 13.
75 025 4.4 082 8? 13.

é

- 323 -


Tabla PC~t-B-30, Acute Leukemia Following Exposure at Age 30,
by Age Agat Diagnosis, Sex, and Dose in Rad of Low-teT

Radiatio: PC in Parcent, to Tue Significant Digits or
Three Decimal Places.
A, Sex
Male Female H
id
Dose
1 10 100 1 10 120
32 +979 374 11, 065 .79 11,
33 -82 8.2 6a +24 7.5 58. !
34 2.9 ta. 79 1,7 1%. 2?.
35 2.9 24. 85 2.5 21. $2,
36 3.4 28, 87 2.8 26. 84,
37 3.6 29. a? 2.9 25. 85.
38 3.6 29. a7, 2.9 24. 85.
39 3.5 28. 87. 2.7 23. 84.
49 3.3 27. 86. 2.5 22. 83.
41 2.9 25. as. 2.3 2a. S11.
42 2.6 22. $3. 2.1 19. st.
43 2.2 49, gt. 14.8 17, 77.
44 1,9 17, 73. 1.5 14, 74.
43 1,6 1s. 75. 1.2 42. 70.
4% 1.3 13. 7h. 4.9 TO. 66. :
47 Vwi uw, $3. 84 8.9 $2.
48 -98 9.6 65. 79 7.4% ge.
49 «85 8.4 61. 272 7.2 57. ‘
50 74 7.4 38. 65 6.6 $5.
31 64 6.5 54. +59 6.0 $2.
52 -56 5.7 $1, $2 5.3 49,
53 149 5.90 43 +45 4.7 46.
$¢ «43 4.4 454. +39 6.3 42.
55 37 3.8 40. +34 3.$ 39,
54 «3t 3.2 37. «29 3.6 35.
37 -2$ 2.7 32. 24 2.6 3t.
$3 +21 2.3 28. +20 2.2 27.
59 18 1.9 2s. a1? 1.8 24.
60 215 1.6 2t. ats 1.6 23.
$1 12 1.3 19. «3 §.3 $9,
62 i 1,9 16. ait $.2 17,
$3 O93 98 16, 095 1.0 15.
64 o80 86 13. 083 189 13. .
65 070 +75 19, -073 -78 12, ;

- 284 -


13. Jablon, S. and Kato, H., Childhood Cancer in Relation to Prenatal
Exposure to Atomic-bomb Radiation. Lancet 2: 1000~1003 (1970).

14, Baum, J. We, Population Heterogeneity Hypothesis on Radiation Induced
Cancer. Health Phys. 25: 97-104 (1973).

15. Beebe, G. W., Kato, H., and Land, C. E., Studies of the Mortality of
A-bomb Survivors. 6. Mortality and Radiation Dose, 1950-1974,
Radiat. Res. 75: 138-201 (1978).

16. Bolce, J. D., Rosenstein, M., and Trout, E. D., Estimatton of Breast
Doses and Breast Cancer Risk Associated with Fluoroscopic Chest
Examinations of Women with Tuberculosis. Radiat. Res. 73: 373-390
(1978),

17. Bond, ¥. P. and Thiessen, J. W. (Eds.), "Re-evaluations of Dosimetric
Factors, Hiroshima and Nagasaki," Department of Energy Symposium
Series No. 55, (CONF-810928). U.S. Govt. Preg. Off., Washington,
DeC., 1982.

18. Sinclair, W. K., Revisfons in the Dosimetry of the Atomic Bomb Survivors.
In “Radfation Research, Reviews and Summaries on Chemistry, Physics,
Biology and Medicine,” Proceedings of the Seventh International Congress
of Radiation Research, July, 1983, (4. J. Broerse, G. W. Barendsen,

H. B. Kal, and A. J. van der Kogel, Eds.) pp. 63-73. Martinus Nijhoff
Publishers, Amsterdam, 1983.

19. Dobson, R. L. and Straume, T., Estimated Cancer Risks and Neutron RBE's
from Revised Hiroshima and Nagasaki Dosimetry. Bre J« Radiol. 55:
788-795 (1982),

20. Fujita, S., Awa, A. As, Pierce, H., Kato, He, and Shimizu, Y., Re-
evaluation of the Biological Effects of Atomic Bomb Radiation by
Changes of Estimated Dose. In “Biological Effects of Low-Level
Radiation,” Proceedings of a Symposium, Venice, April 11-15, 1983,
pp- 55-60. International Atomic Energy Agency, Vienna, 1983.

21. Sinclair, W. K. and Failla, P., Dosimetry of Atomic Bomb Survivors,
Radiat. Res. 88: 437-447 C1981).

22. Charles, M. W., Lindop, P. J., and Mill, A. J., Pragmatic Evaluatton
of Repercussions for Radiological Protection of Recent Revision in
Japanese Abomb Dosimetry. In “Biological Effects of Low-Level Radiation,”
Proceedings of a Symposium, Venice, April 11-15, 1983, pp. 66-75.
International Atomic Energy Agency, Vienna, 1983,

23. Smith, P. G., and Doll, R-, Mortality among Patients with Ankylosing
Spondylitis after a Single Treatment Course with X-rays. Br. Med. J.
284: 449-460 (1982).

24, Ron, E. and Modan, B., Benign and Malignant Thyroid Neoplasms after

Childhood Irradiation for Tinea Capitis. J. Natl. Cancer Inst. 65:
7-11 (1980).

~ 100 -



For leukemia and bone cancer the temporal distributions of risk
imply that the plausibility of a causal connection between a particular
cancer and a prior radiation exposure may depend strongly upon the length
of the intervening time interval. For example, according to the time-to~
response model described above, a radfation-induced bone cancer is about
6 times more likely to be diagnosed 5 years after exposure than 20 years
after exposure; therefore, all other things being equal, the plausibility
of a causal connection between a diagnosed bone cancer and a prior radiation
exposure is greater for a 5-year interval from exposure to diagnosis than
for a 20-year interval.

For cancers other than leukemia and bone cancer, the estimated
probability of causation is independent of time from radiation exposure
until cancer diagnosis, if that time is greater than 10 years. This ‘s a
consequence of the constant relative risk model for time to respons:
which the Working Group adopted on the basis of published studies ¢ —-ussed
in Chapter ILI-H. Because these studies pertained mainly to breas” a
lung cancer, the Working Group carried ou: + comparable analysis ¢
stomach cancer among high-dose A-bomb suri-vors, and obtained resui.:
similar to those obtained for breast cancer and lung cancer.

The constent relative risk model applies only after some initial
period, which the BEIR Ii Committee fixed at 10 years. The Working
Group felt that this value was consistent with epidemiological findings
for persons exposed at ages at which baseline incidence was already high
enough for an appreciable number of excess cancers to be expected under
the model, and that for younger exposure ages the practical {wportance of
the initial period was small because few cancers, radiation-induced or
otherwise, would be expected until much later than 10 ye:rs after exposure.
On the other hand, the radiation-related excess risk is sero at the time
of exposure, and assumes its eventual full value relative to baseline
incidence after about 10 years. The Working Group felt that not enough
is known about tumor growth kinetics to justify a distributional model '
for the time required for a single transformed cell to develop into a
clinically detectable tumor; what is known, however, suggests that the
risk of radiation-induced cancer (other than bone cancer and leukemia) is
negligible for the first 5 years after exposure (see Chapter III-H). A
discontinvity is biologically unlikely, and the Working Group therefore
decided upon a cubic function of time to provide a smooth -ansition from
an assumed zero excess for the first 5 years after expos to the ev ual
constant relative excess after 10 years (Figure V-5), to applied ¢
the basis of time in whole numbers of years. In the table below, Y r-
resents the integer part of time in years from exposure until diagnosi
(e.g., 11 years, 10 months corresponds to ¥ = 11) and T(¥) is the corre: —
ponding proportion of the eventual relative excess applying at time Ye

Yr 0-4 5 6 7 8 9 10+
TCY): O 074 .259 .500 «741 .926 1.000
PC estimates are most reliable, of course, when they are based
altogether on observational data. Unfortunately, there are no series

that provide followup data beyond 40 years after exposure, and most of
the available longterm data pertain to the interval from exposure to

- 59 -



oan

ESTIMATED PROBABILITY OF CAUSATION (PERCENT?

CES

100

$o

20

a0

Fig, X-3

SALIVARY GLAND CANCER

=,

0 BAD

T

zo 30 40 $0
AGE AT EXPOSURE

~ 197 -

7

‘oe ——
Taleo



Different types of ionizing radiation have been compared experi-
mentally with respect to various biological effects, including cell
killing, munagenesis, and carcinogenesis (6). In general, the relative
biological effectiveness (RBE) of a given absorbed dose of charged part-
icle radiation depends on the spatial density of che ionizations (linear
energy transfer, or LET) produced along the tracks of the radiation, the
heavy particle radiations tending to produce very closely spaced ioniza-
tions (high LET), while electrons, X rays and gamma rays tend to have
fewer jonizations per unit length of track (low LET). In dealing with
different types of radiation, the practice in radiation protection has
been to relate the doses and effects of a given high-LET radiation to
those of 250 kVp X rays as a standard, by introducing the quantity “dose
equivalent.” For a given end point, e.g-, 50% acute mortality, the RBE
of a certain type of radiation, say, neutron radiation of a given energy,
is defined as the ratio of the required dose of X rays to the required
dose of neutrons for that end point. For other end points, for different
energies and for different dose rates or total doses, the RBE will have
different values. A variable RBE is difficult to use for radiation pro-

. tection purposes, and therefore practical reliance for assessing the
impact of occupational or environmental exposures to high-LET radiation
has been placed on a “quality factor”, Q, which varies in relation to LET
and is assumed to remain constant in the low-dose range (7,8). By multi-
plying the absorbed dose (in rad) by the quality factor (Q) for a given
radiation, one obtains the “dose equivalent” for that type of radiation
(expressed in rem = “rad equivalent in man"). The use of the Q factor is
unsatisfactory, however, for the purpose of estimating cancer risk from
high-LET radiation, in view of the aforementioned variations in RBE. In
general, data are not available for estimating the site-specific RBE for
each pacticular set of circumstances; the necessary information includes
the LET of the radiation at the target tissues. For internal emitters
(deposited radioauclides), knowledge of the spatial and cemporal distribu-
tion within the target tissue will also be required. These are factors
that must be determined on a case-by-case basis. For this reason, the
Working Group has refrained from making tables for high-LET radiation
except in the limited case of alpha particle radiation from radium-224 in
bone and exposure to radon daughters in the case of lung, for which
epidemiological data exist from direct observations.

Cc. Sources of Radiation Exposure

Each of us is continually exposed to ionizing radiation from cosmic
rays, disintegrating radioactive elements in the earth, and radioactive
elements occurring naturally in our bodies (4). People living at sea
level in the United States receive about 80 millirem (1,000 millirem = 1
rem) average dose (strictly speaking, average dose equivalent) to their
internal organs per year (Fig. III-1); but at higher elevations, where
cosmic rays are more intense, or in regions where the natural radio-
activity of the soil is fairly high, the dose can be twice that size, or
greater. Vatural background radiation is increased by building materials

'The NCRP and ICRP=ICRU currently have task groups working on high-LET
radiation,

-14-

hone



wh

X radiation -

also X rays; penetrating electromagnetic radiation, usually produced
by bombarding a metallic target with fast electrons in a high vacuum.

Xeroderma pigmentosum (XP) -
an inherited disease in which skin cells are highly susceptible
to sun-induced cancer; XP cells have 2 defect in DNA repair after

ultraviolet {rradiation which apparently accounts for the propensity
for this neoplasm.

U.S. COVERIOES? PRINTING OFFICE: 1985-46i-3202496)

~ 355 ~



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

300

$9

20

10

Fig X-1-a-3

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 20

20

AGE AT DIAGNOSIS

- 133 -

Male ——
Femate---


Exposures 4, 5, and 6:
F(1.1 + 0.6 + 067) = F(2.4) = 2.4 + 2.42/116 = 2.45
T(9) = .926
K(35,f) = .00184
Rao506 > Fx Tx K = 2.45 = 926 x 00284 = .00417
R= Ry + Ro + R3q + R3p + Rasgeg = 00746
+ 60150 + .0204 + .0419 + .00417 = .089
C = R/(1 + R) = .089/1.089 = .082 = 8%.

The uncertainty surrounding PC estimates is discussed in Chapter VII,
and Section VII-O includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

To provide a general orientation to the magnitude of the PC values that
result from the procedures described here, Fig. X-8 has been prepared for
pancreatic cancer. It gives PC values for 1, 10, and 100 rad of low-LET
tadiation to pancreatic tissue by age at diagnosis, separately for males and
females. The vertical scate is logarithmic and curves are presented for only

two radiation dose levels, For these and other reasons interpolation is to
be discouraged.

- 229 -


14,

is.

16.

17.

Mancuso, T. F., Stewart, A., and Kneale, G., Radiation Exposures of
Hanford Workers Dying from Cancer and Other Causes. Health Phys.
33: 369-385 (1977).

Anderson, T. W., Radiation Exposures of Harford Workers: A critique
of the Mancuso, Stewart and Kneale report. Health Phys. 35: 743-750
(1978). —

Hutchison, G. B., MacMahon, B., Jablon, $. and Land, C. E., Review
of a Report by Mancuso, Stewart and Kneale of Radiation Exposure of
Hanford Workers, Health Phys. 37: 207-220 (1979).

Oversight Committee on Radioepidemiological Tables, “Assigned Share
for Radiation as a Cause of Cancer - Review of Radioepidemiological
Tables Assigning Probabilities of Causation” (Final Report).
National Academy Press, Washington, D.C., 1984.

~ viii -

aa
aad

etme


ESTIMATED PROBABILITY OF CAUSATION {PERCENT}

160

50

20

10

Fig X-i-a-1

CHRONIC GRANULOCYTIC LEUKEMIA
EXPOSURE AGE 0

5 10 15 20 25 30 35
Male ame
AGE AT DIAGNOSIS Female-o-

- 731 -


ICDA -
the International Classification of Diseases Adapted for use in the
U.S. The ICD ts periodically revised by the World Health Organization;
the 8th ICDA is adapted from the 8th ICD and was issued in 1972.
ICRP -
Anternational Commission on Radiological Protection.
Incidence —
or incidence rate; the rate of occurrence of a disease within a
specified period of time, often expressed as number of cases per
100,000 individuals per year.
In utero -
in the womb, i-e., before birth.

In vitro -

(literally, in glass), in culture or in the test~-tube (as opposed to
in vive, in the living individual).

In vivo ~
in the living individual,
Ionizing radiation ~

radiation sufficiently energetic to dislodge electrons from an atom.
Ionizing radiation includes X and Zamma radiation, electrons (beta
radfation), alpha particles (helium nuclei), and heavier charged
atomic nuclei. Neutrons ionize indirectly by colliding with atomic
nuclei.

Kerma —-
Kinetic Energy Released in Material. A unit of exposure, expressed
in rad, that represents the kinetic energy transferred to charged
particles per unit mass of irradiated medium when indirectly fonizing
(uncharged) particles, such as photons or neutrons, traverse the medium.

kVp -

“kilovolt peak”, a measure of the energy of the X-ray tube-voltage and
hence of the maximum energy of the X-ray photons produced.

Latent period -
also time ta response, induction period; the period of seeming
inactivity between the time of exposure of a tissue to an injurious

agent (e-g., radiation) and observed response (e.g., diagnosis of
cancer).

~ 349 -

-


198

Exposure to
and Dose

10

21 to 39 per Day.
Female

at Exposure, Sex,
ke Smokers,
ignificant Digits or Three Decimal
Sax
Dosa

jarat
100

on, by Age &.
3

esent Ci
to Two

tung Cancer 16 or More Years After
Male
10

for Pr

Low-LET Radiati

in Rad;
PC in Percent,

Tabla PC-$-G.
Places.

a

et ew ew 8 OMT OM FH OOK OR MORE NOOR RE Oe
TONE OT Oe tee ee ET ME ODEN OO
NOR RR Ree RR Me ORR COMMS EEE ETE SES

64

aareterant ramen

VON ES CONE LMH BRINE NT OFFA RRND Ow
DIONE SOON DO ONS 99 SMM MMMM NAO CD OE
Re KKM OCOSCeooOCEDRSGCEEOD

26
027
027
427
628

SRP Ae RAs OmMn ONY eONNANAN
SMMONNNNOANR Hee ee wee rere

VWNSYAN ORIN TNH On CONS EMME HO
VEOH CON COONS ENMMMONNANARH HO weoce ree papers
350

eK Ms NOR Oe

weesessy

41

~ 328 -


$ex,
Toa

10 to 20
Significant Digits or Three

at Exposure,
19

lung Cancer 10 or More Years After
y Age 4)
garette Smokers,
Sex
~ Female
Dose
100

for Present Ci

10

PC im Percent, to Tre
Male

Decimal Places.

Day.

Exposure to Low-LET Radiation, 6

and Dose in Rad,

Tadle PC-9-F (Continued),

DODO DORAN OOO R AAR «>

52
33
34
$5
3?

ROK TOR EH MOR OKMOTNAE OM Mw
Ke alabatutaralalatete a tS teen ee Tt tt eee
SEVOOGOCOCDBCe CeCe GOCCCOEDD

NANNIES EHO ORONMNMHOHWEH

ROKK UME Nan QrOK MEH
WAND OOOO OOO RR

3
5
$
$
3
3
56

- 327 -


APPENDIX IL - STATUS OF FINAL REPORT OF THE WORKING GROUP IN RELATION
TO THE RECOMMENDATIONS OF THE NATIONAL ACADEMY OF SCIENCES (NAS)

OVERSIGHT COMMITTEE ON AN EARLIER DRAFT (JULY, 1984)

The NIH Working Group has been in close communication with the NAS Over-
sight Committee throughout the period during which the Radioepidemiological
Tables have been in preparation. In consequence, many of the recommendations
made by the Oversight Committee on the July draft have been followed in the
preparation of the final draft. Others, of course, look to the future
and counsel any future group that may have the task of preparing revisions.
In what follows, the NAS recommendations are first reproduced individually
and a statement is provided to show how that topic has been handled in
the final report.

le “The Oversight Committee recommends that the Working Group prominently
indicate that the doses used in the tables are absorbed doses in organs
and that use of other radiation measures, such as kerma or instrument
readings, in calculating assigned shares will results in errors.”

The final report should make it clear that the dose to de used

for each site is the absorbed dose.’ Chapters IV, ¥, Vi, and IX,

in which the methodology is outlined, all refer to dose as “absorbed”,
“tissue”, or “organ” dose, and in Chapter X the PC calculation for
each site is given in terms of absorbed dose.

2. “The Oversight Committee recommends that the Working Group consider
other ways of defining the category of “leukemia excluding CLL” (chronic
lymphocytic leukemia)-- for example, ways that would exclude cases that
should be diagnosed as CLL but are not.”

The Working Group's definition of a disease that included all
types of leukemia other than chronic lymphocytic leukemia (CLL)
was based on the previous use of this definition by the BEIR TIT
Committee and on the fact that CLL is the only major type of
leukemia that has not been observed to increase in incidence in
irradiated human populations. It is true, as stated by the Over-
sight Committee, that this definition can result in the inclusion
of cases of CLL that are not diagnosed as suche However, no
classification can protect entirely against misdiagnosis. To
define che category by inclusion rather than exclusion based on
current diagnostic criteria would require re-analysis of all the
leukemia case material from the A-bomb survivors, ankylosing
spondylitics, Thorotrast patients and other series, which is
probably not feasible.

3. “The Oversight Committee recommends that the decision of whether to
include specific sites of cancer in the radioepidemiologic tables be
based, to the extent possible, on an evaluation of the reliability of the
estimates of assigned share, rather than on a subjective judgment preceding
the data analysis.”

- 339 -



coe rn nancnnosnee—e re
RRTSSASSSTLASE RAS

reste:
etcee"
4ycae:
sacae:
bese”

zs

Aq cat an woygnaysasia [esodmey 1119 Yetwony wOddy TTY “e (Henney

‘X‘

ly aoy ye ernsodng sezsy 4 ae,
(pRnuE uaa) G-1-X Slay

- 174



Table PC-9-B (Continued). Lung Cancer 16 or More Years After
Exposu to Low=LET Radiation, by Age AL at Exposure, Sex,
and Dose in Rad, for Nonsmokers, PC in Percent, to Two
Significant Digits or Three Decimal Places.

ay Sex
Male Famaie
Dose

1 10 100 t 10 129
$1 27 24, 48 4.9 47.
‘r4 -t? 24. +43 5.0 47,
$3 «UV? 24. 49 $.1 43.
54 17 24, 51 5.2 49,
$s +t? 24. «52 5.3 “5.
56 217 24. $4 5.5 53.
$? 37 24, +55 5.6 50.
58 wt? 24. 37 5.8 St.
$9 38 25. 58 5.9 52.
0 +18 2s. +60 6.4 33.
61 18 2s. 62 6.3 33.
62 «38 25. 264 €.5 54,
63 mah) 26. -66 6.7 55.
64 -19 26. +68 6.9 56.
65 +20 27. +70 ?.1 5?
66 «20 27. =72 7.3 5
6? 221 28. 75 7.5 5
68 22 29. 78 7.8 $
ao +23 36. 3! g.4 &
79 +24 30, 83 8.3 ei.
7t +26 31, 35 8.5 i,
72 .25 32. 87 8.7 62.
73 +26 33. ~89 4.8 62.
74 2 34. 90 3.3 $3,
75 «28 34, 95 9.0 63,

- 319 -



tee

Although an association appears to be well established between
prenatal X irradiation and childhood cancer, the extent to which the
association may be causal is highly controversial (4,27-29). More pre-
cisely, ic is difficult to reconcile an order-of-magnitude difference
between risk estimates derived from studies of the frequency of X-ray
pelvimetry, usually carried out shortly before birth (4, page 452) and
estimates derived from studies of patients given therapeutic X-radiation
during infancy (30), or A-bomb survivors exposed in utero (31) or in
early childhood (5). It is not readily apparent that the association is
explainable in terms of a medical indication for pelvimetry that itself
confers an increased risk of childhood cancer; analyses adjusting for
variables such as birth weight, maternal age, and a few others, have not
greatly affected risk estimates (29,32). Furthermore, analy:«s restricted
to twin births, for which medical indication for pelvimetry should be less
important, have yielded estiwates similar to those not restricted to twins
(33,34).

Experimental studies do not support a greater cancer risk from pre-
natal as opposed to postnatal exposure to ionizing radiation (4,35,36).
A particularly thorough experimental investigation of the influence of
age at exposure on cancer risk has been carried out by Sasaki et al. at
the National Institute of Radiological Sciences in Japan (37-40). These
studies indicate that mice irradiated with X or gamma rays at fetal, peri-
natal, neonatal, pubertal, and young adult stages of development vary
with respect to the type and frequency of tumors developing after irradia-
tion. The observed differences suggest, however, a smooth variation by
exposure age and, in particular, little if any difference between exposure
at the late fetal, neonatal, and suckling stages. Irradiation during the
middle intrauterine stage, on the other hand, was followed by significantly
lower cancer risk than that observed among non-irradiated controls, es-
pecially for tumors. of lymphoreticular tissue, the lung, and, in females,
the uterus (38). °

H. Time to Response

The plausibility of a causal association between a cancer and a
prior exposure of the patient to ionizing radiation depends partly upon
the length of time by which diagnosis follows exposure. Detection is
unlikely until hundreds of millions of cancer cells have been replicated
from what probably begins as a single transformed cell. Moreover, for
many, but not all, types of cancer the epidemiological evidence suggests
that events subsequent to irradiation may be required before any cellular
changes initiated by ionization can result in a transformed cell capable
of uncontrolled proliferation. Thus, for example, in irradiated popula-
tions no excess risk of breast cancer or lung cancer has been seen ontil]
the exposed individuals have reached ages at which these cancers usually
are observed in non-irradiated populations, which suggests that cancers
of these sites require other time-dependent etiologic factors whether or
not exposure to ionizing radiation plays a role in their causation. Bone
cancer and leukemia, on the other hand, have appeared in excess within a
very few years after exposure in heavily irradiated populations, suggesting
that subsequent events follow rapidly, or may not be required to complete

~ 19 =



Risk

Chronic Granulocytic Leukemia:
Coefficiant £CA,,S) by Exposure Age A, and Sex $

Table X-t-B.

Sex

A

Sax

Y

A

Famale

Male

Female

Male

NI RENE RE KOREN TK KO MMR OE N SORT ONMMNORWKO=
LOL RET NY SE ST ORS ESCORT KHER ANNAN NNN

DANE TK MN ON MOH MO NNET ROMO FOR SOOT MRO
TAIT NENNA NNN S oo THN ODOR ERR ONNYNTENOOOS

BREE ERE ONT ONM ET OR
ROOTING K EAS ORO ST MAN TH HK NN S NOOR ODOM
Rewer.

OR KANE OM K KONA OOH NNOH TORR TANNER ORK
RWI Nw FOONENNT COOOOTON RR ER WERE BOONES OF HH
vente ett eet wt ee tte ARO RAROARA eet eee
NUNN RK Kee eee ee ceeded re

wererreses an

- 156 -


43.

17.

18,

19.

20.

21.

22.

23.

24,

25.

26.

Land, C. E., Personal communication.

Fraumeni, J. F., Jr. and Boice, J. Ds Jre: Bone. In "Cancer Epidemio—
logy and Prevention” (D. Schottenfeld and J. F. Fraumeni, Jr., Eds.),
pp-+ 814-826, W. B. Saunders, Philadelphia, 1982.

Mulvihill, J. J., Miller, R. W., and Fraumeni, J. Fe, Jre, Genetics
of Human Cancer. Raven Press, New York, 1977.

Saenger, E. L., Silverman, F. N., Sterling, T. D., and Turner, M. E.,
Neoplasia Following Therapeutic Irradiation for Benign Conditions in
Childhood. Radfology 74: 889-904 (1960).

Janower, Me L. and Miettinen, 0. $., Neoplasms after Childhood Irradi~
ation of the Thymus Gland. J. Am. Med. Assoc. 215: 753-756 (1971).

‘Modan, B., Baidate, D., Mart, H., Sreinitz, R., and Levin, S. Ge,

Radiation-Induced Head and Neck Tumours. Lancet 1: 277-279 (1974).

Hempelmann, L. H., Hall, W. J., Phillips, M., Cooper, R. A., and Ames,
W. R., Neoplasms in Persons Treated with X-rays in Infancy: Fourth
Survey in 20 Years, J, Natl. Cancer Inst. 55: 519-530 (1975).

Shore, R- E«, Albert, R. E., and Pasternack, B. S., Follow-up Study of
Patients Treated by X-ray Epilation for Tinea Capitis: Resurvey of
Post-treatuent Illness and Mortality Experience. Arch. Environ. Health
31: 21-28 (1976).

Schneider, A. B-, Vavus, M. J., Stachura, M. E., Arnold, M. J., and
Frohman, L. A., Salivary Gland Neoplasms as a Late Consequence of Head
and Neck Irradiation. Ann. Intern. Med. 87: 160-164 (1978).

Maxon, He R., Saenger, E. L., Buncher, C. R., Kereiakes, J. G., Thomas,
S. R., Shafer, M. L., and McLaughlin, C. A., Radiation~associated
Carcinoma of the Salivary Glands. A Controlled Study. Ann. Otol.
Rhinol. Laryngol. 90: 107-108 (1981).

Land, C. E., Carcinogenic Effects of Radiation on the Human Digestive
Tract and Other Organs. In “Radiation Careinogenesis” (A. C. Upton,

R. E. Albert, F. J. Burns, and R. E. Shore, Eds.), 1985, Elsevier North-
Holland, New York, in press.

Belsky, J. L., Takeichi, N., Yamamoto, T., Cihak, R. W., Hirose, Fe,
Ezaki, H.«, Inoue, S., and Blot, W. J., Salivary Gland Neoplasms
Following Atomic Radiation: Additional Cases and Reanalysis of
Combined Data in the Fixed Population, 1957-1970. Cancer 35:
555-559 (1975).

Takeichi, N., Horise, F., and Yamomoto, H., Salivary Gland Tumors in|
Atomic Bomb Survivors, Hiroshima, Japan. I. Epidemiologic Observations.
Cancer 38: 2462-2468 (1976).

Court=Brown W. M., and Doll, R., Mortality from Cancer and Other Causes
after Radiotherapy for Ankylosing Spondylitis. Bre Med. Jo 2: 1327-
1332 (1965).

- 264 -

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- 176



@ Years
at Exposure,
gnificant

by Age &,
in Percent, to Ye Si
aces.

Thyroid Cancer 10 of Mor.

H-LET Radiation
PC

@ to Lo
n Rad,
Decimal Pl

3

t2 (Continved),
Digits or Threa

after Exposur

Sex, and Dose

Table PC-

att

Sex

Tale”

“Female

Dose

19

100

19

64,
6
6
6
6
ry
é
6
6
6
4
$
é
6
6
ry
6
6
4
6
6
6
$
6
6
6
6
6
6
6

F010 1 WOR ER RRR ERRNO OOOOODOOOO ONE

VOR SOT Mer NK Brn Hen ENR om eH
ONS TO OF 890000 0090 HO NR Eee

SUI Mer WTO NM NT OR O- VME MER MOOK AME IA
FEE EET TOMI 0 OOOO DO Om Ree

Baa)

- 338 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT }

Fig. X-12

a9

zo

30 40 so
AGE AT EXPOSURE

- 260 -

70

male
Fema le--—

Pres

Mola!


F(D) = S
TCY) = T(3) = 926
K(A1,8) = K(10,f) = .0594
then R@ Fx TxK = 5 x .926 x .0594 = .275
and PC = R/(1 + R) = .275/1.275 = «216 or 22%.
Example 2 A female exposed twice to low-LET radiation to thyroid tiesue,
5 rad at age 10 and 2 rad at age 15, with diagnosis of thyroid cancer
at age 25, 9.8 years after the latter exposure. Again, it is assumed
that she is representative of her age and sex with respect to the normal
risk of thyroid cancer. We must combine two values of R, one for each
exposure.
Exposure 1, at age 10, when D = 5, Ay = 10, and ¥ = 15
F(D) = 5
TUS) = 1
K(10, f) = .0594
then R} = Fx Tx K= 5x1 x .0594 = .297
Exposure 2, at age 15, when D= 2, Ay = 15, and Y= 9
F(D) = 2
(9) = .926
RCIS, £) = .0535
then Ro = Fx Tx K* 2 x .926 x .0535 = .0991
the total R = Ry + Ro = .297 + .099 = .396
and PC = R/(1 + R) # .396/1.396 = .284, or 28%.
Example 3 A thyroid cancer was diagnosed at age 44 in a woman following
several exposures to low-LET radiation at various ages. The first, of one
rad to the thyroid, occurred at age 20, 24 years and 2 months: before
diagnosis (Y = 24). The second, to 2 rad, occurred 4 months later, at the
same age (A) = 20) but 23 years and 10 months before diagnosis (Y = 23).
At age 21, 23 years and 3 months before diagnosis, a 9-rad total dose was
received over a 36-hour period at the continuous rate of 250 millirad per
hour (¥ = 23). Finally, at age 35, three exposures, to 1.1, 0.6, and 0.7
rad, respectively, were received on consecutive days, 9 years and 2
months prior to diagnosis (Y = 9%). The first, second, and third exposures
should be considered separately, because exposures 1 and 2 correspond to

different values of Y, and exposures 2 and 3 to different exposure ages.
The 9-rad continuous exposure delivered over 36 hours can be treated as a

- 257 ~


Finally, @ question has been raised as to the source of the BEIR LII
coefficients, especially their considerable dependence upon the experfence
of the Japanese A-bomb survivors and their applicability to the w.S.
population, The only available test here is one of consistency among
sources, and in general the absolute risk coefficients obtained in japan
are very much like those obtained in the U.S. and U.K. except chat their
variances are smaller because the experience is larger. This subject ts
discussed more fully in Chapter I1I-K.

J. Dose Rate

The linear~quadratic model used for the risk estimates with low~LET
radiation for all cancer other than breast and thyroid, having a “cross-
over" point at 116 rad, is based on acute (f.e., fairly high dose rare)
exposures to radiation. As has already been discussed in Chapter III, at
low dose rates the quadratic term becomes less important, and at very low
dose rates it is assumed that the dose-response function is reduced to
the linear term only. The exact dose Tate below which the quadratic term
can be ignored is not precisely determined, but experimental studies
indicate that it might be on the order of 0.001 tad/min or 1 rad/day, or
perhaps somewhat greater (see Chapter III-1). For acute exposures below
5 rad, the contribution of the quadratic term is on the order of 4 percent
or less of that of the linear term alone. The approach being suggested
for the calculation of protracted or fractionated radiation (see Chapter
V) will reduce any dose-rate effect to well within these limits of error.
For thyroid and female breast the available date suggest a linear dose—
Tesponse model which implies that there should be no influence from vari-
ation in dose rate. The latter inference is borne out in the case of the
breast.

In human cells in vitro the greatest change in effect (cell inactiva~
tion) with dose rate occurs in rhe range 100 rad/min to 10 rad/hr (26);
one may, therefore, as a first approximation, assume no variation in
effect with dose rates In the LQ model at dose rates greater than 100
tad/min. For dose rates in the transition range (10 rad/hr to 100 rad/min),
if one were to treat large exposures as acute doses, the margin of error
would be the contribution of the quadratic term of the linear-quadratic
model. Below the cross-over point (116 rad) that would imply a factor
less than 2.0. It is reasonable to assume that not many exposures will
fall in this dose-rate range, but such exposures should be treated on an
ad hoc basis.

The uncertainty associated with the dose rate is essentially incorpor-
ated in the factor estimated for the choice of dose-response model,
especially when account is taken of the uncertainty in the crossover dose.

K. Time-Response Models

Risk coefficients are either absolute, i-e., calculated as an excess
over and above baseline incidence, or relative, i.e., expressed in cultiples
of the natural incidence. Absolute risks are frequently expressed as
excess cases per million persons per year and per rad (or rem), whereas a

~ 88 -

Pownce


To provide a general orientation to the magnitude of the PC values
that result from the Procedures described here, Fig. X~l-A, B, and C have
been prepared for CGL, acute forws, and ali forms respectively. They
give PC values for 1, 10, and 100 rad of low-LET radiation to the bone
marrow by age at diagnosis, separately for males and females, and each
has 8 parts corresponding to ages 0, 10, 20, 30, 40, 50, 60, and 70
at exposure. ‘The vertical scale is. logarithmic and curves are presented
for only three radiation dose levels. For these and othet reasons inter~
polation is to be discouraged.

- 130 -


Table PC~!-B-0,

Acute Leukemia Following Exposure at Age 6,

by Aga A> at Diagnosis, Sex, and Dosa in Rad ef Low-LET

Radiation,

PC_in Percent, to Two Significant Digits or

Three Decimal Places.

Ay Sex
Male Female
Dose

t WwW TOO 1 19 106
2 1.5 14, 74. 1.2 69,
3 6.9 $5. 93. 5.4 9%.
* 9.9 54. 95 7.8 94.
5 14. 38. 96 a8 95.
7 12. 59. 96 9.3 95.
? 12, $8. 96 3.0 95.
& 10, $5. 95 8.1 94.
3 9.0 $2. 95 7.2 94.
40 7.9 48. 94 4.5 93.
14 a, 33 5.38 $2.
12 39. 92 5.1 $1.
13 35. 50. 4.6 $0.
14 30. 8s. 4.4 89.
15 26. Be. 3.7 gs.
1$ 22. 83. 3.3 86.
17 19, #5. 2.9 gs.
8 17, 78. 2.6 82.
19 16. 27. 1.9 73,
20 ts. 76. 1.6 75.
2? 14. 74. 1.3 24.
22 3, 71, 1.4 §?.
23 at. 68. -95 $4.
24 9.4 $4. 82 60.
25 8.0 60. 71 57.
26 6.9 56. +61 $3.
27 6.0 52. $3 50.
238 5.1 48. +47 46.
29 4.4 44, Gt 43.
39 3.9 Gt, ~36 4c.
iM 3.3 3. +3t 36.
32 2.9 34. +26 32.
33 2.5 31, +22 29.
34 2.2 28. +18 2s.
35 1,9 2s. 16 22.

~ 281 ~



which the most significant is for the esophagus: the mortality rate i.r
non-white males that was 10 in 1960 had risen to 14 by 1977.

Among the ten SEER regions, there is a fair amount of variabilicy
for some cancer sites (Table VII-1). For example, the incidence of lung
cancer may vaty by as much as a factor of three between the SEER regions
with the lowest and highest rates. Table VII-2 exhibits for each kind of
cancer the largest and smallest ratios for any area to the All Areas
incidence rate. Although a few of the extreme rv° “s are based on small
numbers of incident cases, and hence are subjec: large sampling varia-
bility (e.g., the ratio of 0.26 for esophageal er in females in Utah
is based on only nine cases) most of the ratios are fairly stable with
respect to sampling variability: the very high ratio of 2.14 for stomach
cancer in Hawaii males is based upon 442 cases. Most of the variability
exemplified in Table VII-2 must be considered real.

Explanations for some of the variation come readily to mind: Hawaii
has a very diverse ethnic mix, and the high ratios for thyroid and stomach
cancer, and the low ratio for breast cancer, result from that fact, as an
examination of ethnicity-specific rates in Hawaii makes clear (7). The
low ratios in Utah for cancers of the Lung and bronchus, esophagus, and
colon presumably result from the well-known differences in life style of
the Mormon populations of that state. To the extent that the low ratios
for lung and bronchus reflect a high proportion of non-smokers, that
effect will be accounted for if smoking history is considered by the method
explained in Chapters IV and IX.

D. Minimal Latent Period

Time to tumor recognition is approximated by the interval from expo-
sure to date of diagnosis. This approximation may be subject to “error,”
in that diagnosis may be delayed beyond the time when it might have been
made, but it would be unusual if the delay were more than a year or two,
except in the case of thyroid cancer. Most incidence rates for cancer do
not change rapidly over such short age intervals. An “error” of this kind
could be significant only if it affected whether or where the interval from
exposure to tumor detection fell within the period over which the minimum
latent period is smoothed as described in Chapter V-C; e.g., 5.0-9.9
years for most solid tumors.

The minimum latent period assumed in the calculation of PC tables is
empirically based, but can be only ronghly estimated for solid tunors.
The BEIR III report (1) gives a minimal latent period of 2-4 years between
exposure and tumor detection for leukemia and bone cancer, and this range
seems well established. The BEIR III value of 10 years given as the
minimal latent period for solid tumors is very approximate, as it is not
sice-specific and all indications are that the interval varies greatly
with age at exposure, being longer for younger than for older individuals.
For younger individuals especially, the uncertainties are appreciable,
but of little’ practical effect when the constant relative risk model of
time-response is used.

Although the Working Group starts from the assumption of minimum

- 81 -



Table PC-3. Salivary Gland Cancer 10 of More Years After
Exposure to Low Ler Radiation, by Age A at Exposure,
Sex, and Dose in Rad. PC in Percent, to Two Significant
Bigits or Three Decimal Places.

ay Sex

Fale Female

2
2
=
o
2

mR RENNIN
NO BS a HUAN ON AO
OVOWeNUUnwn eNeUw
nN
nw
‘Sd 42 “4.08 08 08 00 09 00 08 00 08 8
ROSEN DUM UO Oe

BUN (Owe eOMeUNnse
ARRAN UU ee
RO UU ONUY ON
‘MA4.00 08 OF Co 08 08.00 8 08 08 OF 2
MRO=NU SUSIE ORO

ae RNIN Ue

w
~
w

~ 305 -



to.

a

ta,

ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

Fig. X-5

STOMACH CANCER

60 T

$0

20

20

.
-
el
wee

m a.

° 40 20 30 40 $0 6o vo
¢
AGE AT EXPOSURE Finite

~ 209 -


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

200

$0

20

+0

Fig X-2-1

BONE AND JOINT CANCER *
EXPOSURE AGE ©

s 310 5 20 28 30 35
GE AT DIAGNOSIS Hale

*Alpha radiation from radium-224 only

- 183 -



done; the discussion by the Working Group reflects
the fact that these approaches seldom are successful.

10, “The Oversight Committee recommends that the assumption of constant
relative risks be veassessed as new data and new methods of analysis appear.”

This is for the future, but the Working Group endorses the 4
recommendation. a

ll. “The Oversight Committee recommends that the method for projecting
relative risk estimates among populations be reconsidered when the
tables are next revised.”

This 1s for the future, but the Working Group endorses the
recommendation.

12. “The Oversight Committee recommends that each revision of the tables
include a fresh appraisal of the relationship between cancer risks and
radiation dose and dose rate, allowing different responses under different
conditions for differeat tumor types."

Tnis also is for the future, but scarcity of human data may always
force reliance on experimental results with animal models,

13. “The Oversight Committee recommends chat the Working Group further
justify its decision on how to apply quality factors in calculating
assigned shares for various high-LET radiations."

(See comment following 14 below.)

14. “The Oversight Committee recommends that a method for estimating
assigned shares for persons exposed co high-LET radiation be developed
that does not depend so heavily on the estimates for low-LET radiation.”

In the final report, the Working Group has abandoned the use of
quality factors (Q) for estimating the cancer risk from high-LET
radiation. In the narrowest sense, Q for a given type of radia-
tion may be viewed as a somewhat arbitrarily selected constant
“relative biological effectiveness” (RBE) factor. The use of Q
makes sense from a radiation protection standpoint, in that it
enables one to express doses of radiation of different qualities
on a common scale (dose equivalent in rem). In reality, the RBE
of a given radiation varies with the end point studied, the
energy (and hence the LET) of the radiation at the target site,
the total dose and in many cases the dose rate. Therefore, it
fs not possible to assign a single RBE value for a given type of
high-LET radiation, say, fast neutrons. For internal epitters
(deposited radionuclides), dosimetry is further complicated by
variations in spatial and temporal distributions of the radiation ae
sources within the target tissues. For these reasons, the

Working Group has limited its consideration of high-LET radiation

to cases where data from direct observations exist, i.e., exposures

of bone to radium-224 (in which case the alpha-radiation dose is

measuted in rad) and exposure of lung to radon daughters (radiation

exposure in working level months, WLM).

- 342 -


Bal.

4
iad

Chapter I: LEGISLATIVE AUTHORITY

A. Background

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
Pood, Drug and Cosmetic Act to facilitate the development of drugs for
rare diseases and conditions, and for other purposes. This legislation
inelodes a provision (Section 7 (b) of the bill) directing the Secretary
of Health and Human Services 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 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 included in section B of this chapter.

On February 25, Dr. Edward N. Brandt, Jr-, Assistant Secretary for ei
Bealth, Department of Health and Human Services, assigned lead respons- i
ibility for the implementation of this charge to the National Institutes j
of Health. An Ad Hoc Working Group, chaired by Dr. J. E. Rall, Deputy
Director for Intramural Research, NIH, was established; this group has
met regularly since April 5, 1983. Subsequently (Auguse 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 section C.

It may be noted that the section of P.-L. 97-414 pertaining to the i
development of radioepidemiological tables originally was introduced by
Senator Orrin Hatch (Utah) as a part of Senate bill S 1483: “Radiation i
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. On March 23, 1983,
Senator Hatch introduced the “Radiogenic Cancer Compensation Act” which
intends to use as the basis for award of compensation the tables of
probability of causation of cancer from radiation exposures, prepared in
response to the requirements of the “Orphan Drug Act.”

B. Public Law 97-414 - January 4, 1983

"7(b)(1) Within one year after the date of enacrment of this Act, the
Secretary of Health and Human Services shall devise and publish radio-—
epidemiological tables that estimate the Jikelihood 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 shall 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,

-l1-


shape of the dese~response curve, but even a careful reconstruction with
phantog simulation may not take full account of the influence of movement
on the part of the patient during the therapeutic procedure, movement

that might have led to higher doses to the thyroid than those estimated,

I. Coefficients Describing the Dependence of Risk on Dose

Although the risk coefficients are the most complex element in the
PC calculation, it is doubtful whether they are subject to errors as large
as those of most dose estimates for persons exposed to fallout, for
example. Standard statistical measures of uncertainty calculated for
specific data sets are meaningful when data are reasonably numerous, as
is true for some sites in the case of A-bomb survivors, but such instances
are few, and sampling varfation is only one part of the uncertainty
surrounding risk coefficients. As an example, Table VII-3 reproduces the
linear regression estimates and 90 percent confidence intervals for many
types of cancer mortality associated with ionizing radiation among A-bomb
survivors (25). Only for leukemia, lung cancer, and breast cancer do the
90 percent limits differ from the mean by a factor less than Zz. These
coefficients are for all ages at exposure. When one confronts the task
of calculating PC tables over the entire age range, one finds that it is
only for leukemia, and cancers of the breast, bone, salivary glands, and
thyroid, that there is enough experience upon which to base risk coeffic-
dents for those exposed under age 10. Most recorded series pertain to
exposure during adult life, and even the A-bomb survivors exposed before
age 10 provide very lictle information on thé risk of radfogenic cancers
of gastrointestinal, urinary, and respiratory organs. This is discussed
more fully above in Section F.

It should be borne in mind that the site-specific risk coefficients
for cancer incidence in the BEIR III report are, except for leukemia and
bone cancer, linear coefficients. They were derived by the BEIR III
coumittee as an adjunct to the mortality estimates, and represent the
Committee’s summary of the evidence from the medical and the environmental
exposures reported in the literature as of 1979. In some instances
incidence risk estimates were obtained by transforming mortality risk
estimates as explained in the BEIR report (1). The technique employed
the lifetime expectations of (a) developing, and (b) dying of, cancer of
a specific site.

The conversion of BEIR linear-model risk coefficients to coefficients
for the BEIR linear~quadratic model, in which the excess risk from an ex-
posure to D rad is proportional to D + D2/116, was accomplished by dividing
the linear coefficients by 2.5 (see Chapter V-B). The results obtained by
this procedure are not necessarily identical to those that would have been
obtained by reanalyses of the original data using the new model,’ but this
source of uncertainty is unimportant relative to that involved in the choice
of the crossover dose of 116 rad. The statistical uncertainties underlying
this procedure are appreciable. The reliability of the crossover valve
depends more on its agreement with experimental results obtained over a
wide range of biologic systems than on its statistical stability (See
Chapter V-B).

~ BF -





$2a0°
evy00" 9400
i
ry
se ve fe ae

40 CAS ODA wOgangysze rd Tesedwel 1179 y40OKD eds, TIE

ernnemen ee.

a

Vy ety ye eunsoduy seygy 4 s90,

fe leeyney

“£8enG}}U0D) D-4-x OF

- 177 -


The excess relative risks are considered to be subject to uncertainties
that have lognormal distributions. The logarithms of the “best estimates”
which are tabulated then correspond to the mean values of normal distribu-
tions.

A normal distribution is symmetric about its mean, and deviations from
that mean are expressible in standard form as wultiples of the standard
deviation of the distribution. Thus, for example, 95% of a norma] distri- 4
bution with mean yp and standard deviation o lies between p - 1.963 and y +
1.960. A lognormal distribution also is symmetric about its geometric
mean G, but in a aultiplicative sense. ¢ 1s the exponential of the arith- ry
metic mean on the logarithmic scale. Defining the “geometric standard de- ‘
viationTM (G.S.D.), §, as the exponential of the standard deviation on the
logarithmic scale, it follows, for example, that 95% of the distribution
lies between

G x $71-596 = exp (1nG - 1.96 Ins)

ao
"

and

U=G x $1-%6 = exp (inG + 1.96 inS).

In the above formulation, if G and § are estimated, then the interval
{L,U) corresponds approximately to a 95% confidence interval for the true
geometric mean. In some applications no value of S may be obtainable
directly from data, but if a 95% “credibility interval" of the form (L,U)
can be constructed for the true geometric mean, a subjective estimate for
S can be calculated by solving the relationship

L/u = 53-92,

The G.S.D. for a lognormally distributed estimate G, which is itself the

product of K independent estimates, each with 6.5.D. S4, can be calculated as

1n25 = in’s, teen t in’sy,

and a credibility interval for the true value can be calculated in terms of
G and S.

Where G.S.«D.s could be calculated from available data, as for variation
in baseline rates, the values S{ were estimated as the exponentials of the
standard deviations of the logarithms of the rates. In other instances the
values of S; were estimated as described above, relying on estimates of U and Ls

The uncertainties are of two kinds: Those which may equally well be in .
either direction and those, like that which derives from the reassessment of wd
the A-bomb dosimetry, which are considered more likely to be in one direction
than the other. We refer to them briefly as unbiassed and biassed uncertainties. i
1. Unbiassed uncertainties

a Thnassed wacertainties

o Baseline values. The All Areas SEER incidence rates are
appropriate for an average member of the population of the United

- 92 =


my

‘exposure. Then D = 5, Ay = 45, and Y = 3.
F(5) = 5 + 52/116 = 5.22
T(3) = 0
K(45,£) = .000340
then R= Fx TxkK =O
and PC = 0 also.
Example 2 A typical male exposed to an acute dose of 2 rad of low-LET
radiation to the colon at age 36, and with a diagnosis of colon cancer at
age 55. Then D = 2, Aj = 36, and ¥ = 19. .

F(2) = 2 + 22/116 = 2.03

19) = 1

K(36,m) = .000493

then R= F x Tx K = 2.03 x 1 x .000493 = .0010
and PC = R/{1 + R) = .0010/1,0010 = .001 = 0.2%

Example 3 A colon cancer was diagnosed at age 44 in a woman following
several exposures to low~LET radiation at various ages. The first, of
one rad to the colon, occurred at age 20, 24 years and 2 wonths before
diagnosis (Y = 24), The second, to 2 rad, occurred 4 months later, at the
same age (A) = 20) but 23 years and 10 months before diagnosis (¥ = 23).
At age 21, 23 years and 3 months before diagnosis, a 9-rad total dose was
received over a 36-hour period at the continuous rate of 250 millirad per
hour (Y=23). Finally, at age 35, three exposures, to 1.1, 0.6, and 0.7
tad, respectively, were received on consecutive days, 9 years and 2
months prior to diagnosis (Y¥ = 9),

The first, second, and third exposutes should be considered separate-
ly, because exposures 1 and 2 correspond to different values of Y, and
exposures 2 and 3 to different exposure ages. The 9-rad continuous
exposure delivered over 36 hours should be treated as 2 exposures because
it required more than one day, but less than two. The partition giving
the maximum risk estimate assigns a 3-rad exposure to one 24-hour period
and 6 rad to another. The three exposures at age 35 can be treated as
one because they correspond to the same values of A, and Y, and because
the total dose is less than 5 rad.

Exposure |:
F(1) = 1 + 12/116 = 1.02
1(24) = 1
K(20,£) = 00153
Rl = Fx Tx K = 1.01 x 1 x .00153 = .00155

- 213 -



Table PC~2-30. Bone and Joint Cancer Following Exposure at
Age 30, by Ace at Diagnosis, Sax, and Dose in Rad of
Alpha Radiation.” PC in Parcant, to Two Significant Digits
or Three Decimal Places.

Ay Sex
Male Fomale
Dose

t ZX) 190 1 te 160
3s - 607 672 «72 013 -43 1.3
32 2.4 ee. 7h, 4.2 30. St.
a3 12. 38. 93. 20. 72. $6
4 22. 73. 9?. 36. 85. 98
35 28. 79. 97 48. 30. 99
36 31. a2. 98 33. s2. 99
3? 32. a2. 98 54. 92. 99.
38 32. $2. $3. $2. 92. 9
33 34, 8&2, 38 48. 94. 39
$9 34, Bi. 93 42. 83. 99
41 28. 79. 97 36 85. 98
42 25. 77. 97. FBI 82. 98.
43 28. 72. 96. 26. 78. 97
44 1$, 6S. $5. 2) 73. $6.
45 12. 37. 93. 7, 6?. $$.
46 o.4 So. bal 14 62. 94.
47 7.3 44, a9 ti. $6. 93.
43 $.1 39. 37. 9.8 $2. 92
49 §.1 35. 84. 8.9 49, 91,
39 4.3 3i. 82. 8.1 47. 90.
53 3.6 27. 79, 7.2 44. 89.
52 3.0 24. 76. 5.9 38. 86.
33 2.5 21, 72. 4.6 33. 83.
34 2.4 18. 68, 3.7 28. 79.
55 wa $$. 65. 3.0 23. 75.
36 1.5 13. ei. 2-4 2a, 7h,
57 3 12. 57 2.0 17, 67,
58 tod 10. $3. 1.6 14, $2,
39 1.0 9.2 50. 1.3 12. $7.
69 91 8.4 43. it td. $3.
$1 “8! 7.6 4S. 292 8.5 48.
62 70 6.6 41. 77 7.2 44,
63 58 5.5 37, 67 6.3 40.
&4 48 4.6 32. +61 5.3 38.
65 39 3.8 28. +38 $.5 37.

- 300 -

pers

snag

dea antl

Bate


Table FC-1-C-10, Laukemia Excluding CLL Following Exposure
at Age 10, by Age A, at Diagnosis, Sex, and Dose in Rad
of Lou-LET Radiatiod. PC in Percent, to Two Significant
Digits or Three Decimal Places.

a; Sex
Male Female
Dese

¥ 0 100 7 19 100
12 1,7 16, 76. 1,5 14, 74
13 7.3 46. 34 7.0 45. $3
14 TO, 54. 9s 10. 56. 96
15 10 55. 95 12 5a, 96
16 9.3 53. 98 tt, 58. 96.
17 8.3 49. 94 10. 53. 95.
18 7.5 $6. 94 8.6 Se. 95
19 6.8 44. $3. 7.3 46. 94
29 6.3 42. $3. $.2 42. $2.
Qt 5.7 39. 92. 5.2 37. 91
22 $.0 3é. 91 4.4 33. 90
23 4.2 32. as 3.8 30, Bg.
24 3.4 28. 87, 3.2 26. 86,
25 2.8 29. &4 2.8 23. 84
26 2.3 20. gi, 2.4 21. 82
27 2.0 Ww. 79 2.0 18, 73,
28 5.7 te. 77 1.8 16. 77.
29 1.6 15, 74. 1.6 15. 74.
30 1.4 13 72, 3.4 13. 72,
31 1.2 12 74, 1.2 WH, 6%.
32 tA 1 47. 1.0 9.9 65.
33 -98 9.6 65. 87 8.8 42.
34 +87 8.6 62. 75 7.5 58.
35 +77 7.7 53, 65 6.6 35.
36 +69 7.0 56. $7 §.8 $1,
BP -62 6.3 53. 50 $.1 48.
38 35 $.7 $1, S¢ 4.5 45-
a9 +59 5.1 48. 39 4.0 42.
40 45 4.6 45. 35 3.4 39.
4s -40 4.1 43. 3 3.2 36.
42 236 3.7 49, 28 2.9 34.
43 -32 3.3 37. 25 2-6 Bie
o6 +28 2.5 34. 22 2.3 25.
45 +24 2.5 3s. 19 2.0 26.

- 290 -


y Year Y¥

Bone and Joint Cancer:
Temporal Distribution TCY) b&b
After Exposure

Table X-2-a,

TeY)

Y

TOY?

Onn ROTONOEMONNT OTH OOTMCOTe
WOR OF TSAR HK ORAMNT OROR DOME
ROMO MMMNONT HT eon0900
Serco eeoCoM ODM FOCUS DDE Coe DS
SOSCOGEEEDBOCOONAOELODGODS

rs

oO +0
CONOR TR OCRANENAENOMNDOMAN
COBH REAM OT MON O—
COM OWOMRR ONS FMMNNNE Heo
PoeeccoconcCoveeT COC OVeBOD

OT NN THOR AMO“ AMITMOR MRO“ NM
wereres ree nene

- 191 -


The constant relative risk model for time to response was not assumed
to hold for bone cancer, which appears to follow a “wave” function, and
therefore the factor T is the probability that a cancer caused by an
exposure at age A; will be diagnosed Y years later,

A few examples are given below to illustrate the use of the tables in
deriving the PC values.

Example #1 A typical male, exposed to 50 rad of brief alpha radiation
to endosteal tissue at age 10, with a diagnosis of bone cancer 6.5 years
later, at age 16. Then A) = 10, Ap = 16, ¥ = 6, and D = 50

F(D) = 50

T(Y) = T(6) = .0874

E(A),S) = E(10,m) = 2.79
I(A2,8) = 1Ci6,m) = 1.54
K = E/T = 2.79/1.54 = 1.812

then R= Fx Tx K = 50 x .0874 x 1,812 = 7.91

and PC

R/(1 + R) = 7,91/8.91 = .89 or 89%.

Example #2 A typical female exposed to 100 rad of brief alpha radiation
to endosteal tissue at age 7, with a diagnosis of bone cancer at age 20,
12.5 years after exposure. Then A, = 7, Az = 20, Y = $2, and D = 100.

F(D) = 100

T(12) = .0485

E(7,£) = 2.81

1(20,f) = .782

K = E/T = 2.81/.781 = 3.60

i

then R= Fx Tx K = 100 x .0485 x 3.60 = 17.5
and PC = R/(1+R) = 17.5/28.5 = .946 or 952,

The uncertainty surrounding PC estimates is discussed in Chapter VII,
and Section VII-0 includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

To provide some orientation to the general magnitude of the PC values
resulting from the procedures described here for bone cancer, Fig. X-2 has
been drawn for endosteal doses of 1, 10, and 100 rad to show the PC
values by age at exposure and sex. The figure is in 8 parts corresponding
Co ages 0, 10, 20, 30, 40, 50, 60, and 70 at exposure. The vertical scale is
logarithmic and curves are presented for only three rad{ation dose levels.
For these and other reasons interpolation is to be discouraged.

~ 182 -



Table VII-5
Numbers of Deaths from Cancers of Various Organ Systems, 1950-

1974, in A-bomb Survivors Aged 10-19 in 1945.

Number of Deaths
Total With 10+ Rad

All malignant neoplasms except leukemia 128 45
Digestive organs and peritoneum 70 21
Stomach 44 ML
Colon 3 2
Esophagus, rectum and pancreas 7 3
Other digestive organs 16 5
Trachea, bronchus and lung 5 2
Breast 4% 11
Lymphatic and hematopoietic 7 3
All other combined 32 8

- 108 -


incidence among A-bomb survivors (5,6) provided new information on the
dependence of risk on age at exposure, an issue that had not been resolved
satisfactorily by the BEIR LIf Committee (see Section D). A recent

review of studies of salivary gland cancer following childhood irradiation
(7) provided a numerical risk estimate for exposure ages 0-14, and the
gite was included in the calculations. Finally, BEIR estimates for

ta certain sites and exposure ages were evaluated and rejected as uncertain,
and corresponding PC calculations were not performed. Of the 78 age,

sex, and site-specific risk coefficients employee in the present report,
40 were taken directly from the BEIR report and 38 were taken from more
recent sources; also other coefficients presented in the BEIR report for
the lyr :mas and “miscellaneous other” sites were not used (see Chapter
VU-F).

B. Dose-Response and Dose-Rate-Effect Models

As discussed in Chapter ITI-H, the weight of radiobiological evidence
favors a linear-quadratic dose response to low-LET radiation for most
cancers, with a “crossover” dose, at which the components of risk propor~
tional to dose and dose-squared are equal, somewhere between 50 and 200
tad (8). In general, the epidemiological evidence discriminates poorly
among competing dose-response models (9). Thyroid cancer and female
breast cancer are exceptional in that the epidemiological data strongly
favor linearity (2,5,6). Accordingly, the Working Group has adopted
linearity for breast and thyroid cancer and the BEIR III linear~quadratic
model for all other sites, for PC calculations involving exposure to
low-LET radiation. The BEIR ITI linear-quadratic model estimates excess
cancer risk, following a radiation exposure of short duration, as

Excess = 21g * (Dp + p7/216),

where epg is a site-specific coefficient depending upon age at exposure and
sex, and D 1s radiation dose in rad (see Chapter I1I-H). The linear model,
of Course, expresses excess risk as

Excess = ey x De

The so-catled crossover dose of 116 rad in the formulation of the BEIR
Vinear=quadratic model, which specifies the degree of curvature in the
Braph of risk as a function of dose, was originally determined from the
Japanese leukemia data (2,3), but is also consistent with a number of
Other Tadiobiologic end points (see Chapter III-I). Since no other human
cancer data are adequate for calculating crossover doses for individual
Sites other than the thyroid gland and female breast, the value of 116
ae has been assumed to apply to all sites for which a linear-quadratic
loSe-response model for low-LET radiation is considered appropriate for

low-LET radiation (ive., all cancers other than those of the thyroid and
female breast).

ent. Alchough the BELR Committee’s site-specific incidence risk coeffici-
nodal except for leukemia, corresponded to the linear dose-response
el, the Committee provided numerical coefficients for both linear and

- 55 -



9. Lung Cancer (162.1 in ICDA-8)
Introduction

The association between fonizing radiation and cancer of the lung
and bronchus has been mast clearly evident in various studies of underground
ainets who are exposed to radon and its daughter products (48-50). The i:
Tesults of the studies on miners are broadly consistent with other studies ae)
of the relation of X rays and gamma rays to respiratory cancer, notably
those of the Japanese A-bomb survivors (28) and the British ankylosing
spondylitis patients who were treated with X rays (3).

The BEIR IlI assessment of lung cancer risk following exposure to
ionizing radiation was a synthesis of epidemiologic data from a number of
studies of mining: populations with occupational exposure to alpha radiation
from tnhaled radon daughters, and from the Japanese A-bomb survivor
studies and the British series of patients given X-ray therapy for
ankylosing spondylitis, both representing exposure to external, mainly low
LET, radiation, In that assessment it was concluded that, among miners,
excess lung cancer risk was proportional to cumulative exposure to radon
daughters, measured in “working level months” (WLM), and that excess risk
was proportional to cumulative dose from low-LET radiation, with approximate
equivalance of effect between one WLM and 6 rad low-LET dose to che
bronchial epithelium. (One “working level" (WL) is defined as the activity
in air chat gives 13,000 MeV of alpha radiation per liter from ultimate
decay of the short~lived daughters; one WLM is defined as exposure to 1
WL for 170 hours.) In the BEIR assessment, age at observation was a far
more important determinant of excess risk than age at exposure. For a
given cumulative exposure, and after a minimum latent period, estimated
risk increased approximately linearly with age at observation, from zero
before age 35 to a maximal value at about age 70 and older (4, pp. 198,
325-327).

The Working Group found the BEIR analysis difficult to use, partly
because the formula of a linear increase in excess risk with increasing
age at observation is inconsistent with the constant relative risk model
for time from exposure to diagnosis, a model that the A-bomb survivor
lung cancer mortality data for 1950-1978 appear to support (28,33).
Also, there is some evidence that the two kinds of radiation may differ
in their carcinogenic effects. The shape of the dose-response relationship
is probably different for the two types of radiation (see Chapters III-1
and V-B). Moreover, the A-bomb survivor data strongly suggest an additive
Telationship between exposure to low-LET radiation and smoking in the
causation of Lung cancer (51), whereas the relevant data for radon daughter
exposure and smoking, while mixed (52-54), tend, on the whole, ro suggest
a multiplicative interaction model (49,55-59). It was also noted that
there is no real necessity to base risk estimates on the combined data
from the two kinds of exposure; there are sufficient data to support
separate lung cancer risk analyses for external, Low-LET radiation and
exposure to inhaled radon daughter products.

Estimates for high-LET radiation

The many studies of lung cancer risk in mining populations exposed to

- 232 -


For leukemia, there is a high absolute excess risk for exposures
during the first decade of life, with a much lower excess for exposure
at ages 10-19, and a steady increase for exposures at older ages (4).

The BEIR report estimates, which were based on A-bomb survivor incidence
data (3), do not vary smoothly with age, in that the coefficient for
exposure ages 20-34 is higher than those for ages 10-19 and 35-49. The
difference is far from significant statistically, however, and a similar
pattern is not seen in data based on the British spondylitis series (18).
Accordingly, the Working Group replaced the BEIR coefficients for exposure
age intervals 10-19, 20-34, 35-49, and 50+ by values corresponding to a
quadratic function of age, fitted by least squares using weights based on
the variances of the BEIR estimates. No adjustment was made to the BEIR
coefficient for exposure ages 0-9, about which the spondylitis data are
uninformative.

Epidemiological data linking fetal radiation exposure to increased
cancer risk largely pertain to exposure from pelvimetry examinations
shortly before birth. The 1980 BEIR report presented an estimate of this
risk based on the results of the Oxford Survey (19), as 25 excess leukemia
deaths and 28 excess deaths from other cancers per million persons per
year per rad for the first 12 and 30 years of life, respectively. The
Committee did not, however, explicitly include these estimates in its
tabulated estimates of lifetime risk following acute and chronic exposures
to radiation. Even after allowing for the difference in follow-up (5-26
years for the A-bomb survivors vs. 0-12 years for the Oxford Survey) in
the light of the calculated lognormal time-to-diagnosis distribution for
exposure at age 0 (Table X.1.H), and allowing, with Stewart (20), for the
possibility chat estimated radiation doses in the Oxford Survey may have
been too small by a factor of 2, the above estimate for leukemia is three
times as high as an extrapolated estimate based on the leukemia coefficients
used for the present report (Table VI-1). Experimental studies, in fact,
suggest that there is little or no cancer risk associated with exposure
during the middle uterine period, and that exposure during the late
uterine stage is comparable in effect to exposure during infancy and
early childhood (21-24). Given the uncertainties that remain about the
magnitude of radiogenic risk of leukemia and other childhood cancers
following feral irradiation (see Chapter I1I-G), the Working Group is
unpersuaded that cancer risk depends strongly upon whether or not the
exposed person was in utero or postnatal, and suggests that in-utero

exposures be treated no differently than postnatal exposures at age 0.

-61-



ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

50

20

10

Fig X+2-8

BONE AND JOINT CANCER*
EXPOSURE AGE 70

70 ao 300 105

AGE AT DIAGNOSIS tale

*Alpha radiation from radium-224 only

~ 190 -



Table PC=t-C-60. Leukemia Excluding CLL Following Exposure
at Aga 60, by Ace A, at Diagnosis, Sex, and Dose in Rad
of Low-LET Radiation. PC in Percent, to Two Significant
Digits or Three Decimal Places.

Ay Sex
Male Female
Dosa

1 10 +00 1 19 toc
62 37 3.8 4a, «39 q.1 42.
63 ot $.0 63. 195 9.4 $4.
64 1.9 10, 66. Wd WW. 67.
65 1.0 Fa $5. 1.0 19, 66.
66 +92 9.0 $3. .95 9.4 64,
&7 -83 8.3 61. 86 8.6 62.
68 +73 7.3 58. 77 7.7 39.
69 +63 6.4 34, +69 6.9 56.
70 54 5.5 5a. -6t 6.2 $3
74 246 4.8 46. +55 $.6 31
72 40 4.2 43. +50 S41 48.
73 +36 3.7 40. «45 4.6 46.
74 232 3.3 3?. 43 4.2 43.
75 +29 3.0 38. .37 3.8 4S.
76 12S 2.8 33. 34 3.5 38.
77 +24 2.6 31. «31 3.2 38,
78 +22 2.4 29. -28 2.9 34.
79 62) 2.2 28. «25 2.7 32.
20 219 2.0 26, +23 2.4 30.
a1 218 1.9 es. 21 2.2 28.
82 -1? 1.8 26. +20 2.1 27,
33 16 1.7 23. 39 2.9 2s.
ae «16 1,7 23. 19 2.0 26.
a5 +16 1.6 22. «18 1.9 25,
86 «18 1.6 22. =18 1.9 25.
&7 21S 1.6 22. 38 1.9 25.
as 215 1.6 22. 38 1.9 25.
39 15 1.6 22. +48 1.9 25.
30 +15 1.6 22. 18 te 25.
oy ar 1.6 22. 18 1.9 24.
92 oth 1.6 21. iv? 1.8 24.
93 oth 1.6 21, 17 1.8 24.
a4 ~15 1.5 21. 37 1.8 24
$5 154 1.5 21, WZ 1.8 24

- 295 -


Sex,

tin Percent, to Two

at Exposure,

é

Pp
Significant Digits or Three Decimal Places.

Lung Cancer 10 or More Years After
by Age &

Exposure to Low-LET Radiation,
and Dose in Rad, for Formam Smokers.

Tabla PC-5-C (Continued).

Sex

Female

fate

Dose

190

19

100

#¢

ROT ROVS——ANM ENINORR WET ROS
ST NNN NINA AN RIEU FRO

MANS STON OOM ONAN INNING Ft

eres ee een tee POT NENT ATA)

RRR RRR RRR RRR QO QOR EDR HHH
RR OOWON NN OMKO~ MINN D-Mown Me
FEST F ITT TT ONNAN OO DORE

St NOR OREM Hor OKOT ME
PEA IAD AR ODO OOOO DORE RI

- 321 -


Although much of the research on carcinogenesis has been Focused
on the initiation phase, promotion may ultimately be of greater importance
in detetmining the incidence of cancer (3). It is noteworthy moreover,
that the distinction between initiating and promoting agents is not
always clear-cut (2). Radiation and certain chemicals appear to be
capable of acting both as initiators and promoters; i.e., as complete
carcinogens (4).

Genetic effects leading to cancer may involve germ cells as well as
somatic cells. Evidence for the influence of germ cell mutations oa
human carcinogenesis comes primarily from studies of single-gene defects
assocLated with cancer, family aggregations of neoplasia, and cytogenetic
studies showing some cancers to be associated with inherited chromosomal
abnormalities, Every form of cancer probably has a heritable component
of some magnitude. For some forms it can be large.

It is difficult to estimate the carcinogenic risks of radiation by
extrapolation without further knowledge of the precise mechanisms involved
in radiation carcinogenesis. Advances in the molecular biology of cancer
should eventually lead to new understanding of how radiation induces
malignancy and to refinement in our approaches to risk assessment.
Significant advances in cancer biology have already come from studies of
the genes involved in malignant transformation, some of which are called
“oncogenes” (5). Oncogenes discovered originally in tumor viruses have
since been found to have homologues in normal cells (6), where they can
be “activated” to produce malignant transformation by (a) linking them to
powerful retroviral promoters, (b) mutations which may be produced by
chemical carcinogens like aitrosomethylurea (7,8), or (ce) chromosomal
translocations (6-9). Since ionizing radiation is known to cause both
point mutations and chromosomal aberrations, it ts conceivable that
radiatton carcinogenesis nay, in some instances at least, involve activa-
tion of cellular oncogenes. Recently, direct evidence for activation of
the c-K-ras oncogene by gamma radiation, through a single base mutation,
has been reported (10).

Recent studies of aalignant transformation by viral oncogenes and
activated cellular oncogenes suggest chat the transformation of cells to
malignancy may require activation of more than one cellular oncogene. It
is thus possible that the long “latent” period that characteristically
elapses between radiation and the clinical appearance of a cancer may
result from the need for successive oncogenes to be activated or for
other types of sequential changes to take place.

€. Environmental and Life Style Risk Factors Y

Ic has been inferred that as much as 75-80% (3) of fatal cancers in
the United States results from the influence of life style and other non-
heceditary, or environmental, factors. Epidemiological studies imply that
the largest effects are related to smoking, alcohol consumption, diet and
other factors related to life style. Occupational exposures and the effects
of radiation, chemical pollution, medical therapy, sexual activity, and
infections ate thought to contribute to a lesser extent. In some instances,
heredity may render an individual more vulnerable to the effects of an

-6-


ESTIMATED PROBABILITY OF. CAUSATION {PERCENT}

100

bs)

20

19

Fig R-1-C-4

LEUKEMIA: ALL TYPES EXCEPT CLL
EXPOSURE AGE 30

ae *s.

AGE AT DIAGNOSIS Male ———-
Female -~--

- 150 -

ca


Exposures 4, 5, and 6:

The uncertainty surroundin:
and Section VII

F(Ie1 + 0.6 + 0.7) = F(2.4) = 2.4 + 2.42/116 = 2245

T(9) = .926

K(35,£) = .0139

R4s556 = Fx Tx K = 2.45 x 2926

R= Ry + Ro + Ryg + Rap + Rassig
+ -143 + .292 + .0315 = .619

+382

aw

PC = R/(1+R) = .619/1.619

intervals for PC estimates.

x

+0139 = .0315

+0508 + .102

38%

zg PC estimates is discussed in Chapter VII,
-0 includes a derivation of approximate 90 percent credibili.

To provide an ortentation to che general magnitude of the PC values
that result from the procedures described here, Fig X-7 has been drawn
for tissue doses of 1, 10, and 100 rad of low-LET radiation, and PC
values plotted by age at exposute, for both males and females, and on the

assumption that the minimal latent period has been satisfied.
scale is logarithmic and curves are

levels.

The vertical

presented for only three radiation dose

For these and other reasons interpolation is to be discouraged.

~ 222 -

~~

ty


More Years After Exposure
Sex, and
Two Significant Digits or

at Exposure,

Thyroid Cancer tO or
to Low-LET Radiation, by Age &
PC in Parcent, ¢

Dose in Rad.
Three Decimal Placas.

Table PC-12.

Sex

Fenaia

Male

vi

100

10

106

19

HK COGAN COOMA ES ENN KOR Ss KON NNN MMMM SEE
OO O00 8 00 02 00 00 00 80 90 00 40 09 00 A ED ASO IG OOD DOOD ODO ODDD
BOR INE NH OR ODN TH ORIN OME rr INNA
ASS EF SE ENON MMMM MUNNNNT Hm RE Ree ee

HK Se NS ORE EAN T OWS HOH MENNS FEMA KOS

EL Pr er a a ee Le ars)
KH RRM NOr WOME FONT COME NOMEN HOTT TOO se
DE EIN BME FE RR RED RDA DOD

HNN NOR WARE HK NM EHOR OD OK NMS NOR ORO NMS NON OTS
RT NNN NINA

ca

~ 337 -


relative risk estimate way be some (generally constant) fraction of the
baseline incidence corresponding to the effect of a fixed dose, e.g-, a
rad (or rem}. Wher a constant absolute risk is used as a time-response
model it suggests that the risk of radiogenic cancer is viewed as independent
of the underlying baseline risk. A constant relative risk model for time-
Tesponse is suggestive of mechanisms by which radiation interacts with
other causes to multiply che baseline risk by some constant (see Charter
IV-H}. These models, and the measures they generate, have very differe +t
implications for the calculation of excess cancers following exposure to
radiation. Under the constant absolute risk model for distributing
radiogenic cancers over time, once expression has been established, the
excess per unit of population, dose, and time, 1s constant. Under the
constant :elative risk time-response model, the number of excess cases
during the period ¢ expression is a fixed multiple of baseline incidence
and, therefore, for ©:st solid tumors, increases with av:. For the
interval observation -rom which the risk estimates ate .-nerated, both
measutes must, of course, yield the same rotal excess, pat the ex.75s
will be distributed differently over time. For the period beyond -%e
interval of observation, the predicted excess will frequently be very
different for the two measures and greater with the relative risk model
since baseline rates of cancer generally increase markedly with age.

Although the absolute risk time-response model has dominated the
literature and has been the choice of such groups as the ICRP (4) and
UNSCEAR (2), in the NAS BEIR I (27) and BEIR IIT (}} reports it has been
used in parallel with the constant relative risk time-response nodel.
Recent data on the experience of the A-bomb survivors (25,28) have
provided a strong basis for employing the relative risk model in preference
to the absolute risk model, especially for breast cancer and lung cancer,
and the working group has adopted the relative risk approach in calculating
this first edition of the PC tables (see Chapter V-C). The use that is
made of the constant relative risk approach, however, is not based on the
assumption that the relative excess per rad is invariant with respect to
age, sex, tumor site, geographic or cultural region, etc. Rather, it is
limited to the assumption of a relative risk that is constant over the
period 10-35 years after exposure for a particular tumor, a particular
age-group at exposure, a particular sex, and a particular population
level of baseline incidence.

Within the period of observation, generally up to 35 years after ex-
posure, the uncertainty introduced by the choice between the two models is
not large, but it does increase thereafter. In the life-time projections
of the BELR Ill report, where risks are extrapolated beyond the present
range of the available human data, constant relative risk estimates of
the total burden of radiogenic cancer from a continuous exposure of
1 rad/year beginning at birth are about 3 times those based on constant
absolute risk estimates (1). With continuous exposure beginning at age
20, however, the differential in risk is only about two-fold.

The constant relative risk model is definitely superior to the constant
absolute risk model which simply does not fit the data. But with additional
observations, beyond the 35~year interval for which data are presently avail-
able, the constant relative risk model may fit less well than it does for the
earlier period. For example, the multiple of baseline incidence may decline

- 89 -


4.

10.

ll.

12.

13.

14.

15.

16.

REFERENCES - Chapter IT

Weinstein, I. B-, Current Concepts and Controversies in Chemical
Carcinogenesis. J. Supramol. Struct. Cell. Biochem. 17: 99-120 (1981).

Weinstein, 1. B., Carcinogen Policy at EPA (letter to the Editor).
Science 219: 794-796 (1983).

Doll, Re and Peto, R. The Causes of Cancer: Quantitative Estimates of
Avoidable Risks of Cancer in the United States Today. J. Natl. Cancer
Inst. 66: 1191-1308 (1981).

Office of Technology Assessment, “Assessment of Technologies for
Determining Cancer Risks from the Environment.” U.S. Government Printing
Office, Washington, D.C., 1981.

Marx, J. L., What.Do Oncogenes Do? Science 223: 673-676 (1981)
Bishop, J. M., Cancer Genes Come of Age. Cell 32: 1018-1020 (1983).

Sukumar, $., Notario, Ve, Martin-Zanca, D. and Barbacid, M-, Induction
of Mammary, Carcinomas in Rats by Nitrosomethylurea Involves Malignant
Activation of H-ras~1 by Single Point Mutations. Nature 305: 658 (1983).

Sukumar, S-, Pulciani, S-, et ale, A Transforming ras Gene in Tumori-
genic Guinea Pig Cell Lines Initiated by Diverse Chemical Carcinogens.
Science 223: 1197~1199 (1984).

Rowley, J. D., Oncogent Human Oncogene Locations and Chromosome
Aberrations, News and Views. Nature 301: 290-291 (1983).

Guerrero, I., Villasante, A., Corces, V. and Pellicer, A., Activation
of a c-K-ras Oncogene by Somatic Mutation in Mouse Lymphomas Induced
by Gamma Radiation. Science 225: 1159-1162 (1984).

Jett, J. Re, Corcese, D. A. and Fontana, R. S., Lung Cancer: Current
Concepts and Prospects. Ca ~ A Cancer Journal for Clinicians 33:
74-86 (1983).

U.S. Department of Health and Human Services, “Cancer: The Health
Consequences of Smoking: A Report of the Surgeon General.” US.
Government Printing Office, Washington, DeC., 1982.

Hirayama, T., Non-smoking Wives of Heavy Smokers have a Higher Risk
of Lung Cancer: A Study in Japan. Br. Med. J. 282: 182-185 (1981).

Trichopolous, D., Kalandidi, A., Sparros, L. and MacMahon, B., Lung
Cancer and Passive Smoking. Int. J. Cancer 27: 1-4 (2981).

Correa, P., Pickle, L. W., Fontham, E., Lin, Y. and Haenszel, W-,
Passive Smoking and Lung Cancer. Lancet 2: §95-597 (1983).

Ames, B. M., Dietary Carcinogens and Anticarcinogens- Science
221: 1256-1264 (1983).

-ill-


20 Teo% Confidence Limits)
18
16
14
B42 T
c aa ~-
£ 10 |
= ak
o
= I I
2 + tL a
i caneecaeneeeeeceetar

SsHBeeFRaSB
Seeeeeehess

Age At Time Of Bomb

Figure III-3. Relative risk of breast cancer among female Japanese
A~bomb survivors, incidence 1950-1980, 504 rad versus 0-9 rad and

non-exposed, by age at the time of the bombings, both cities combined,

[Land, C. E., unpublished data.]

~ 40 -


handled as described in Chapter V-D, by a method that seems reasonable
and satisfactory to the Working Groupe. It must be admitted, however,
that other plausible approaches might have yielded different estimates
for very young and very old exposure ages.

G. Sex

Sex differences in the absolute risk of radiogenic cancer are
apparently smal] (1), except for breast cancer, thyroid cancer, and
leukemia, but the topic is not fully developed in the radiation literature.
In the BEIR ILI report the age-specific absolute risk coefficients are
identical for the two sexes, except for the 3 sites named, but when, as
here, these coefficients are employed to derive relative risk factors
by sex, such factors differ considerably between the sexes, most notably
for lung cancer, but also for major gastrointestinal and urinary organs
for which SEER baseline rates for males are well in excess of those for
females. There is uncertainty here, but it cannot be quantified.

HK. Dosimetry

The organ dose from external low-LET radiation can usually be esti-
mated within a factor of 2 in individuals who wear film badges or other
quantitative detection devices or who work in carefully monitored
areas. The absorbed radiation dose is even more uncertain for any
unbadged individual whose dose estimate depends on an environmental
reading that may not be in his immediate vicinity, and is subject to
attenuation by environmental shielding as well as body shielding and
thus may vary over time. Exposure from ingestion or from sources
absorbed within the body, such as iodine-131, thorotrast, radium, and
radon daughters, is characterized not only by uncertainties as to level
of dose, but also by the lack of precise information on their relative
biological effectiveness. If the absorbed radioisotope 1s long-lived
and can be measured in an individual and in specific organs, dose
estimation may be much more accurate. The determination of iodine-]31
doses to the thyroid after the fact, e.g-, from weapons tests, will
always be difficult in view of the indirectness of the exposure through
the food chain and the physiological variables affecting the uptake of
the radioisotope by the gland. A major effort, also mandated by PL
97-414, is currently in progress to address the radfoiodine problem. The
Working Group early determined that it should extend its PC estimation
to internal emitters only where adequate epidemiological data were
available, i.e., for radium-224 in relation to bone cancers

The absorbed dose to the relevant tissue, generally an average over
the target organ in the case of external radiation, is the quantity em-
ployed in these tables because this is the form in which BEIR III
presented its risk estimates. These, in turn, were based on reports on
the effects of diagnostic and therapeutic irradiation that generally
State dose-specific risk estimates in terms of the tissue dose, and on
Teports on the A-bomb survivors whose external (kerma) doses were
converted to tissue doses by means of Kerr's table (1). The relevant
dose to a particular organ will, however, in many instances be difficult

- 8 -



The first, second, and third exposures should be considered separate-
ly, because exposures 1 and 2 correspond to different values of Y, and
exposures 2 and 3 to different exposute ages. The 9-rad continuous
exposure delivered over 36 hours should be treated as 2 exposures becavse
it required more than one day, but less than two. The suggested partition
assigns a 3-rad exposure to one 24-hour period and 6 rad to another. The
three exposures at age 35 can be treated as one because they correspond
to the same values of Ay and Y, and because rhe total dose is less than 5
rad,

Exposure L:
F(D) = 1 + 12/116 = 1.02
TY) = 1(24) =1
K(20,f) = 200739
R, = Fx Tx K = 1.01 x 1 x .00739 = .00746
Exposure 2:
F(2) = 2 + 22/116 = 2.03
(23) = 1
K(20,£) = .00739
Rp = Fx Tx K = 2.03 x 1 x .00739 = .0150

Exposure 3a:

F(3) = 3 + 32/116 = 3.08
(23) = 1
K(21,£) = .00664

R3q = Fx Tx K = 3.08 x 1 x 100664 = .0204

Exposure 3b:

F(6) = 6 + 62/116 = 6.31
T(23) = 1
K(21,f) = .00664

R3p = Fx Tx K = 6.31 x 1 x .00664 = .0419

= 228 -


The hypothesis is inconsistent with avatlable data within 35 years after
exposure, and beyond that point there are no data with which to test ir.
When age-specific analyses are done on the data used by Gofman to support
his model, no increase in relative risk with increasing follow-up is
found (5,49,50). .

Finally, minimal response time is an essential element of temporal
distribution of risk, and one that is extremely difficult to estimate.
If cancers are of monoclonal origin, as seems likely, the development of
a radiation-induced cancer can be considered sequentially in terms of the
transformation of an affected cell which then becomes capable of unres-
trained proliferation, followed by a growth period involving 30 of so
generations of replication resulting in hundreds of millions of cancer
cells, at which point detection becomes likely (54). Observed doubling
times for cadlographically-monitored primary and metastatic tumors of
various sites in human patients appear to he lognormally distributed,
with considerable variation by type (metastatic vs. primary) and site
(54). These observations, especially those of primary tumors, necessarily
occurred after many generations of replication had already taken place,
and it does not necessarily follow that the time reauired for the eatire
growth phase can be determined by extrapolation. Doubling time may well
depend upon attained tumor size, the degree of vascularization, or upon
variable factors not influenced by the existence of a tumor. Also,
lognormalicy of the doubling time at any stage of tumor growth does not
necessarily imply lognormality for the total time necessary for growth;
for example, if the process were characterized by some degree of statistical
independence between growth rates at different times, a more nearly symmetric
temporal distribution would result.

‘tumor doubling-time data are intriguing in their implications for
radiation carcinogenesis as a multi-stage process. Tf tumor growth tended
to begin quite soon after irradiation, a wave-like temporal pattern of
excess risk might be expected on the basis of growth kinetics alone. If,
on the other hand, the beginnings of tumor growth were distributed over
time in such a way as to produce a constant ratio between excess and back-
ground risk, there should be an initial period of several years during
which, due to growth kinetics, the relative excess slowly increases from
an initial value of zero to its eventual value.

1. Models for Dose Response and Dose Rate

To predict the risk of cancer at a given tadiation dose from empirical
observations of effects at other doses, one must use a mathematical model
relating cancer incidence to dose. Various mathematical models have been
proposed for the purpose (4,6,55); however, the empirical data are so
imprecise in most instances as to be compatible with any of the available
theoretical models. Hence, the choice of the most appropriate model is a
matter of expert judgement.

For carcinogenesis, in general, and radiation carcinogenesis in
particular, there are strong grounds for questioning the assumption that
the dose-response relationship has a threshold (4,6,56-59)- The evidence
that many, if not most, cancers arise from a single cell (66), the putative

-23-


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a
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~ 158 -


Confidence interval -

an interval estimate of a statistical parameter, obtained as a
particular function of observed values of one or more random
variables whose joint distribution depends upon that parameter.
The interval-valued function is so defined that, in an infinitely
increasing number of independent replications of the experinent
yielding the observed values of the random variables, the propor-
tion of times that the interval contains the (unknown) parameter
value converges to a number at least as large as some preset value,
called the confidence level of the interval.

Credibility interval -
an analogue of confidence interval, in cerms of subjective probability.
If one's information about the true value of an unknown parameter can
be summarized by a probability distribution for that value, a credi-
bility interval of a given probability level for the parameter is an
interval such that the subjective probability distribution, integrated
over the interval, is not less than the given probability level.

Crossover dose -
that value of the radiation dose for which the contributions of the linear
and quadratic components of the linear-quadratic dose-response function
are equal. A crossover dose of zero corresponds to a pure quadratic
dose-effect function, and an infinite crossover dose corresponds to 4
pure linear dose-effect function.

DNA -
deoxyribonucleic acid; the genetic material of cells,

Dose = absorbed radiation dose -
see: rad.

Dose-effect (dose-response) model -

a mathematical formulation of the way in which the effect, or
response, depends on dose.

Dose equivalent -
@ quantity that expresses all radiations on a common scale for cal-
culating the effective absorbed dose. Dose equivalent is defined as
the product of the absorbed dose in rad and certain modifying factors
{the most important being the so-called quality factor, Q) and is expressed
in units of “rem” (see this).

Dose rate -

the quantity of absorbed dose delivered per unit time.

- 347 -



different from that of the general population are additive in effect with
respect to radiation exposute, .

Example 4 (Lung Cancer):

A lung cancer has been diagnosed in a 55-year-old man who was exposed
to gamma rays at age 28 resulting in a 40-rad dose to the bronchial ares
of the lungs. He is a lifelong nonsmoker. If the PC calculation were
carried out without regard to smoking history, it would be as follows:

F(D) = F(40) = 40 + 40/116 = 53.8
T(Y) = 1(27) = 1
K(A,,S) = K(28,m) = .000619 (Table X-9-A) ;
R= FxTxX K = 53.8 x 1 x .000619 = 0333
PC = R/CItR) = .0333/1.0333 = .0322 = 3%.

From Table X-9-A, however, the lung cancer rate of male nonsmokers is
smaller than that of the general population by a factor of 6.81, and it
appears that smoking and radiation interact additively in the causation

of lung cancer (see Chapter IV-H). Thus W = 6-81, and the revised relative
excess is

R=FxTx Kx W= 53.8 x 1x .900619 x 6.81 = «206,
from which

PC = R/C14R) = .206/1.206 = «171 = 17%.

x x

Age at exposure, age at diagnosis, and time from exposure to diag~
nosis are tabulated in annual.increments. For multiple, fractionated, or
protracted exposures taking place at a single year of age A, and corre-
ponding to the same value of Y, the doses can be summed provided that a
linear dose-response model is appropriate for each exposure. If the
linear-quadratic model applies, however, doses should be given for discrete
24-hour periods and treated as pertaining to separate exposures. In
practice, however, there is little purpose to subdivide accumulated doses
of less than 5 rad.

Example 5 (Acttte Leukemia):

An acute leukemia was diagnosed at age 44 in a woman following several
exposures to low-LET radiation at various ages. The first, to one rad
average bone-marrow dose, occurred at age 20, 24 years and 2 months before
diagnosis (Y=24). The second, to 2 rad, occurred 4 months later, at the
same age (A=20) but 23 years and 10 months before diagnosis (Y¥=23). At
age 21, 23 years and 3 months before diagnosis, 9 rad total dose was
received over a 36-hour period at the continuous tate of 250 millirad per
hour. Finally, at age 35, three exposures, to 1.1, 0.6, and 0.7 rad,

~ 123 -



weal

environmental carcinogen, as is illustrated by the heightened suscepti-
bility of individuals suffering from xeroderma pigmentosum to the develop-
ment of skin cancer as a result of exposure to the ultraviolet radiation
in sunlight. In evaluating the importance of the various environmental
risk factors, one should consider the potential influence of host-related
characteristics as well as the possibility that a cancer may have multiple
causes.

i. Smoking

Smoking of tobacco, particularly in the form of cigarettes, is
generally recognized as the single most important external risk factor
for human cancer, being estimated to cause 25-40% of all cancer deaths in
the U.S. (3,11,12). It is the primary cause of lung cancer in both men
and women, and is also associated with an increased risk of cancer of the
larynx, oral cavity, esophagus, bladder, kidney, and pancreas. Although
the percentage of the smokers in the population has declined from 42% in
1965 to a current level of approximately 33%, the number of active smokers
in the United States is estimated to be about 53 million (12), and there
ig concern about the potential risks from “passiye“ smoking in non-smokers
(13-15). Although the specific mechanism(s) by which tobacco smoke
contributes to an increased risk of various types of cancer is not yet
known, a variety of carcinogenic chemicals are known to be components of
tobacco smoke (12).

2. Alcohol consumption

Alcohol consumption is thought to play a role in the onset of
cancer at a variety of sites, including the mouth, pharynx, larynx,
esophagus, liver, and lung; and some investigators have associated 3-5%
of all cancer deaths with the drinking of alcoholic beverages (3). Al-
though approximately one-third of the adult U.S. population drinks alcoho~
lic beverages at least once a week, and about 10 million members of the
population are estimated to be problem drinkers (4), the specific impact
of alcohol per se on human cancer risk is difficult to assess since,
among the complexities, reliable quantitative date on consumption are
difficult to obtain, Furthermore, many investigators believe that alcohol
acts chiefly by enhancing the effects of other primary carcinogens such
as those in tobacco smoke (4),

3. Diet

Although there is a growing recognition that diet can influence the
risks of specific types of cancer, the mechanisms and magnitudes of
dietary effects are poorly understood. Doll and Peto infer that diet may
be involved in 10-70% of all cancers in this country {3}. Humans are
exposed to a multitude of agents that can enhance or inhibit the onset of
cancer, through the dietary intake of meats and fats, fibers, vitemins,
and naturally occurring carcinogens and their precursors (16). Carcinogens
in the diet also arise as by-products of food preparation (polycyclic
aromatic hydrocarbons), or may be introduced as natural contaminants

-7-



rece

Table Po~'-8-40. Acute Levkemia Following Exposure at Age 46,
by Age A» at Diagnosis, Sex, and Dose in Rad of Low-LET
Radiation, PC in Percent, to Two Significant Digits or
Three Dacimal Places.

as Sex
Male Female
Dose

t 10 100 1 10 100
42 008 889 1.5 006 072 1.2
63 «18 $.6 22. +13 1.4 19,
46 «59 5.3 43. 4) 4.2 43.
45 88 8.7 62. -63 7.0 56.
46 1.2 ti, 63. 92 9.1 63.
47 1.4 3. 72. 1.3 1h, 67,
68 1.5 14, 74. 1.2 12. 69,
49 1.6 15, 2%. 1.3 12, 71.
30 1.6 15. 74. 1.4 13. 72.
eal 1.5 t4, 74. 1.4 13. 72.
$2 1.5 i4, 73. t.4@ 13. 72.
53 1.4 3. 72. 1.3 12. 74,
5a 1.3 32. Wi. 1.2 i, 69.
§5 1.2 th, $9. 1t 14, 67,
56 14 10. 66. 98 9.6 6S.
3? «93 9.2 3. 87 8.6 62.
53 80 8.9 $0. 276 7.6 59,
59 +69 7.0 3$. 67 6.8 36.
$0 .6¢ $3 53. .$9 6.0 $2,
6! 52 $.3 49. +33 5.4 49.
62 245 4.7 4b. +4? 4.8 47,
63 4 4.2 3. 142 4.3 44.
4 -36 3.8 40. 38 3.9 qt.
65 «33 3.4 38. -34 3.5 38.
66 129 3.1 35. +39 3.2 36.
$7 126 2.7 32. -27 2.3 33.
3 +22 2.3 29. +24 2.5 3.
$9 wig 2.0 26. s2t 2.2 28.
70 «16 1,7 23. 18 1g 25.
74 -13 16 20. -16 1,7 23.
72 12 t.2 ta. 16 +5 2s.
73 1g wd 16. oN2 '.3 19,
74 088 94 14, at 1.2 12,
75 07? 83 13. 098 $.0 18.

- 285 -



From equacion IV-7 we obtain:
Males 12982 + 3.97 x .1923 + 11.28 x .5095 = 1/(1+R(0)}
Females «5901 + 3.97 x .0781 + 11.28 x 3318 = 1/(1+R(0))

so that

tee

“ Males wed)

1/0.1469
e Females W(0) = 1/0.2154,

whence, from equation IV-8 we obtain the values of W(s).

Values of W(s) - Lung Cancer

Smoking Category Males Females
Total 1.00 1.00
Nonsmokers 6.81 4.64
Former smokers 1.71 led?
Present cigarette smokers - all 0.604 0.411
<10/day 1.75 1.19
10-20/day +707 482
21-39/day «408 «278
40+/day +287 +196

{2) Probability of Causation for Lung Cancer ~ Additive
Interaction Model.

Referring back to equation IV-2, it is evident that the smoking
characteristic can be accounted for in calculating the PC merely by
id multiplying R(D) by the appropriate value of W(s). This process is
exemplified, and illustrative examples are given, in Chapter X-9.

I. Subpopulations with Non-standard Cancer Risks

From a reading of SEER rates for the different reporting areas, it
is easy to select examples in which cancer incidence for a particular
reporting region, and especially a particular ethnic group within a
particular reporting region, is markedly higher or lower than the rates
used for this report, which were based on all reporting regions except

-51-


ul

ivan)

‘Example 2 A stomach cancer was diagnosed at age 44 in a woman following

several exposures to low-LET radiation at various ages. The first, of
one rad to the stomach, occurred at age 20, 24 years and 2 months before
diagnosis (Y = 24). The second, to 2 rad, occurred 4 months later, at the
same age (A)=20) but 23 years and 10 months before diagnosis (Y = 223. At
age 21, 23 years and 3 months before diagnosis, a 9-rad ctotel dose was
received over a 36-hour period at the continuous rate of 250 millirad per
hour (Y = 23). Finally, at age 35, three exposures, to 1.3, 0.6, and 0.7
vad, respectively, were received on consecutive days, 9 years and 2 months
prior to diagnosis {Y = 9).

The first, second, and third exposures should he considered separate~
ly, because exp:sures ] and 2 correspond to different values of Y, and
exposures 2 an? 3 to different exposure ages. The 9-rad continuous ex-
posure delivered over 36 hours should be treated as 2 exposures because
it: required more than one day, but less than two. The suggested partition
assigns a 3-rad exposure to one 24-hour period and 6 rad to another. The
three exposures at age 35 can be treated as one because they correspond
to the same values of A, and Y, and because the total dose is less than
5 rad.

Exposure |:

POL) = 1 + 12/116 = 1.01

T(24) = 1

K(20,f) = .G100

Rp = FxTtx K= 1.01 x 1x .0100 = .0101
Exposure 2:

F(2) = 2 + 22/116 = 2.03

T(23) = 1

K(20,f) = .0100

Ro = Fx Tx K = 2.03 x 1 x .0100 = .0203
Exposure 3a:

P(3) = 3 + 32/116 = 3.08

T(23) = 1

K(21,f) = .00959

R3g = Fx Tx K = 3.08 x I x .00959 = .0295

- 207 -



It must be emphasized here, following the discussion in Chapter IV-£
to G, that the use of the SEER values for baseline incidence presupposes
that the calculation is being made for an individual who, apart from the
particular radiation exposure of interest, is “typical” of the US population
for his age and sex with Tespect to cancer risk. The only exceptions that
are made here pertain to the smoking history of an individual with lung
cancer (see Chapter LV-H) and to prior and unrelated exposure to tonizing
radiation itself (see Chapter IV-E). It has not been possible to take into
account atypical exposure to other carcinogens such as asbestos, for example,
for which quantitative data adequate for the present purpose do not exist.
Given an atypically high exposure to a known carcinogen other than fonizing
tadiation ot cigarette smoking (in the case of lung cancer), which interacts
additively with radiation exposure, it is clear that the bias in the calcula-
ted PC value would be upward. That is, if it were possible to take into
account the influence of the other carcinogen, as 1s done for smoking in the
case of lung cancer, the adjustment would increase the baseline incidence
above the average SEER rate and thus reduce the PC value below that found by
means of the tables presented in this report. The opposite would be true
for an atypically low exposure. On the other hand, the other carcinogen
might well interact multiplicatively with vadiation, for example if the
other agent acted by promotion, that is, by increasing the likelihood that
a radiation-induced cancer would develop. In that case the PC would have
no bias (see Chapter IV-G). Conceivably, other interaction models might
also apply, which would affect bias differently.

Example } (Breast Cancer):

A woman diagnosed with a breast cancer at age 45, 19.7 years after an X-ray
exposure at age 25 that delivered 10 rad to breast tissue.

F(D) = FC(10) = 10

TCX) = T(19) = 1
K(A,,5) = K(25,f) = .00329 (Table X-10)
R=FxTxK= 10x 1 x .00329 = .0329

PC = R/C14R) = .0329/1.0329 = .0319 = 3%.

* x

Example 2 (Bone Cancer):

A man diagnosed with bone cancer at age 20, 5.4 years after an exposure of
70 cad dose to the endosteal layer from alpha particle radiation at age 15.

- 120 -


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- 104 -


The procedures for calculating PC values for cancers of the kidney
and bladder are based on the assumptions and principles discusced in
Chapter V and the procedures of Chapter VI and IX. As with most sites,
for cancers of the kidney and bladder the relative excess, R, in the
basic equation

PC = R/(1 + R)

is found as the product of three functions, i.e.,

R= F(D) x T(Y) x K(A),S)
where F(D) represents the influence of the low-LET tissue dose {B), TCY)
reptesents variation in R over time in years (Y) after exposure, while
K(A),S) represents the relative excess risk of cancer of the kidney or
bladder for a person of age at exposure Ay and sex S$, when both F and T=l.

Under the linear-quadratic model assumed for cancers of the kidney
and bladder, when exposure is to low-LET radtatton

Fep+ v/i16,

For cancers of the kidney and bladder the influence of time (T) on
the relative risk depends entirely on years from exposure to diagnosis
(¥). The function T is tabled below:

Y 0-4 5 6 7 8 9 10+
Tt. is] +074 +259 +500 74h «926 1.

The standardized relative excess risk for cancer of the kidney or

bladder, K, is given in the accompanying Table X=-1! for low-LET radiation

and for each sex and year of age (completed yeare) from 20 to 75,

A few examples should clarify the actual computational Procedures for
cancers of the kidney and bladder following exposure to fonizing radiation.

Example 1 A typical female, aged 35 when exposed to 10 rad of low-LET
radiation to bladder tissue with diagnos{s at age 55, 20 years after exposure,
Then D = 10, Ay = 35, and ¥ = 20

F(D) = 10 + 102/116 = 10.86

T(Y) = T(20) = 1 ey

K(AL,S) = KC35, £) = .00142

R= Fx Tx K = 10.86 x 1 x .00142 = 01542

and PC = .0154/1.0154 = .015 or 2%.

- 250 -


radiation acts at an early stage, and on analyses of data for
breast, lung, and stomach cancer. For those sites, the constant
relative risk model fits well. The extension of the model to
other sites receives support from analyses by Kato and Schull
(4, Chapter V) showing that the relative risk for all cancers
other than leukemia, considered as a group, varies little over
time, within age-at-exposure cohorts. Also, Darby's analyses in
parallel of mortaliry data from the A-bomb survivor and British
spondylitic series (18, Chapter V) indicates that the model
holds for the group of sites heavily irradiated in the latter
seties. Only for thyroid cancer is there reason to believe that
relative risk may vary over time; this variation may, however,
merely reflect unusually thorough ascertainment in irradiated
populations thought to be at elevated risk.

7. "The Oversight Committee recommends that the Working Group provide
explicit guidance on projecting risks beyond the period of observed data--
e.g., how to estimate an assigned share for a person whose cancer occurs more
than 35 years after exposure--or else provide an explicit statement that it
cannot now be done.”

The tables for leukemta and bone cancer have been carried out
to 49 years, but for other sites, where the relative risk time
distribution model is employed, the tables permit PC's to

be estimated for any period following exposure. The user is
informed as to the specific period of observation on which
the underlying data for other sites are based and alerted

to the additional uncertainty attending PC estimates for
longer periods.

8. “The Oversight Committee recommends that full consideration be given
to the possibility of reanalyzing the available statistics on excess
cancer to model their time dependence without any specific assumptions
about period of latency, rather than assuming a fixed minimal latent
period and a prescribed form for the hazard function.”

(See comment following 9 below.)

3. “The Oversight Committee recommends that, if analyses like those
sescribed in Recommendation 8 prove ineffective, consideration be given
to allowing different minimal latency periods and different periods during
which relative risks increase, for each specific type of cancer and age at
exposure.”

Minimal latent period is very difficult to investigate
except when the relative excess risk is extremely high,
as for bone sarcoma in patients exposed to radium-224.
Another complication is that, for example in the case
of breast cancer among women exposed at young ages,

it would be possible for the true relative risk to be
fairly high at ages of very low baseline risk, without
any cancers being observed even in a large sample.

The approaches recommended by the Oversight Committee
are in fact no different from what actually has been

- 341 +



send

APPENDIX I
ILLUSTRATIVE PC TABLES

The complexity of the algorithms of the PC calculation is such that
systematic tables of the extent.called for in the Orphan Drug Act would
prove unwieldy in practice and might invite more error than the alternative
procedure of ad hoc calculation based on a few reference tables for each
site. In adopting the latter route in its presentation, the Working Group
nevertheless was persuaded that some illustrative PC tables would usefully
supplement the graphic summaries of Chapter X.

PC tables have been prepared for tissue doses of 1, 10 and 100 rad,
and, for lung cancer (Table PC~9-1), for increments of cumulative exposure,
in WLM, to inhaled radon and radon daughter products. For the latter table
only, alternative PC values are presented, reflecting various choices of
risk coefficients as discussed in Chapter X-9. All other tables, with the
exception of the tables for bone cancer associated with exposure to alpha
particle radiation from radium-224, pertain only to low-LET radiation and
may not be used for exposure to highsLET radiation. Except for leukemia
and bone cancer, the tabulated coefficients from which the PC values are
ealculated do not depend upon age at diagnosis. With the same exceptions,
dependence on time after exposure is restricted to multiplication of the
relative excess risk by a factor T(Y¥) which increases from zero during
years Y = 0-4 to one for Y > 10. Thus it is sufficient to tabulate PC
values by radiation dose, sex, and age at exposure, for Y > 10. For
leukemia and bone cancer, on the other hand, the PC depends upon age at
diagnosis as well, and in the interests of brevity, separate tables of
PC, tabulated by sex, dose, and age at diagnosis, are presented only for
exposure ages 0 to 70 in steps of 10.

Interpolation on exposure age is not recommended for leukemia or
bone cancer because of the added complexity of dependence upon age at
diagnosis, and is unnecessary for other cancer sites. Interpolation on
dose is impracticable, except for interpolation on WLM in Table PC-9-1,
because PC values are given for only three dose values. It is, in any {
case, easy to calculate PC values from the relevant tables in Chapter X.

A simple mathematical relationship holds between the PC values
corresponding to any two dose values, for any site, provided that all
other factors, like age at exposure, time from exposure to cancer diagnosis,
and sex, are the same. Let PC; denote the tabulated PC value for dose
Dy, and let PCz denote the (untabulated) value for dose D2. Then

1, 1-PC, FD)
PC, PC) FO)

where P(D) = D for breast or thyroid cancer following exposure to lLow-LET
radiation or for bone cancer following exposure to radium-224, and F(D) =

D+ pe 4116 for other cancers following exposure to low-LET radiation. The
above relationship is not recommended for routine use because the tabulated
PC values are given to a lower degree of precision than the risk coefficients
in Chapter X.

- 271 -



Table VII-3

Absolute Risk Coefficients for Fatal Radiogenic Cancers
Among A-Bomb Survivors by Site or Type of Cancer

Site or Type of Cancer Risk Coeffictent#
Leukemia 1.72 (1.57, 1.87)
Esophagus 0.16 (0.02, 0.30)
Stomach 0.79 (0.34, 1.24)
Colon 0.30 (0.16, 0.43)
Lung 0.61 (0.37, 0.86)
Breast? 0.50 (0.29, 0.72)
Urinary tract 0.15 (0.04, 026)

aExcess deaths/106 person-year-rad; linear coefficients
with 90% confidence intervals.

bremales only

From Kato and Schull, 1982 (25)

~ 106 -


78.

79.

80.

81.

92.

83.

84.

85.

86.

87.

88.

89.

Tokunaga, M., Land, C. Z., Yamamoto, T., Asano, M., Tokuoka, S.,
Ezaki, #., and Nishimori, I., Breast Cancer Among Atomic Bomb Survi-
vors. In “Radfatton Carcinogenesis: Epidemiology and Biological
Significance” (J. D. Boice, Jr. and J. F. Fraument, Jr., ¥ds.),

pp. 45-56. Raven Press, New York, 1984.

Hildreth, N. G., Shore, R» E., and Hempelmann, .L. H., Risk of Breast
Cancer among Women Receiving Radiation Treatment in Infancy for
Thymic Enlargement. Lancet 2: 273 (3983).

Howe, G. R., The Epidemiology of Radiogenic Breast Cancer. In
“Radiation Carcinogenesis: Epidemiology and Biological Significance”
(J. D. Boice, Jr. and J. F. Fraumeni, Ir., Eds.), pp. 119-129. Raven
Press, New York, 1984,

NCRP Report No. 64, “Influence of Dose and Its Distribution in Time
on Dose~Response Relationships for Low-LET Radiation.” National
Council on Radiation Protection and Measurements, Washington, D.C.,
1980.

Mackenzie, I., Breast Cancer Following Multiple Fluoroscoptes.
Br. J. Cancer 19: 1-8 (1965).

Advisory Committee on the Biological Effects of Ionizing Radiation,
“The Effects on Populations of Exposure to Low Levels of Ionizing
Radiation.” National Academy of Sciences, Washington, D.C., 1972.

Petrakis, N. L., Ernster, V. L., and King, M.-C., Breast. In "Cancer
Epidemiology and Prevention” (D. Schottenfeld and J. F. Fraumeni, Jrs,
Eds.), pp. 855-870. W. B. Saunders, Philadelphia, 19862.

Morrison, A. S., and Cole, P., Urinary Tract. In “Cancer Epidemiology
and Prevention” (D. Schottenfeld and J. F. Fraumeni, Jr., Eds.), pp.
925-937. W. B. Saunders, Philadeiphia, 1982.

Cole, P., et al, Occupation and Cancer of the Lower Urinary Tract.

Cancer 29: 1250-1260 (1972).

Parker, L. Ne, Belsky, J. L., Yamamoto, T., Kawamoto, S., and Keehn,
R.« Je, 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 Founda~
tion, Hiroshima, 1973.

Ron, E-, and Modan, B., Thyroid and Other Neoplasms Following Child-
hood Scalp Irradiation. In “Radiation Carcinogenesis: Epidemiology
and Biological Significance” (J. D. Boice, Jr. and J. F. Fraumeni, Jr.,
Eds.), pp» 139-151. Raven Press, New York, 1984,

Prentice, R. L., Kato, H., Yoshimoto, K., and Mason, M., Radiation

Exposures and Thyroid Cancer Incidence Among Hiroshima and Nagasaki
Residents. In “Third Symposium on Epidemiology and Cancer Registries

~- 269 -



PC = R/(1 + 2) = 1,68/2.68 = .626 = 63%.

The same result {is obtained by looking up in Table PC-9-I (Appendix 1)
the PC for 140 WLM with an assumed excess risk of 1.2%. However, it may
be desirable to use different relative excess risks because of employment
as a miner both before and after 1961. In this case, Table PC-9-I cannot
be used and calculations are as follows:

If the factor .007 is applied to exposures before 1961 and the factor
+015 to exposures afterward, the relative excess is

R= 100 x .007 + 40 x .015 = 1.30,
and the PC is
PC = 1.30/2.30 = .565 = 57%.

The uncertainty surrounding PC estimates is discussed in Chapter VII,
and Section VII~O includes a derivation of approximate 90 percent credibility
intervals for PC estimates.

To provide an orientation to the general magnitude of the PC values
that result from the procedures described here, Fig X-9 has been drawn
for tissue doses of 1, 10, and 100 rad of low-LET radiation, and PC values
plotted by age at exposure, for both males and females, on the assumption
that the minimal latent period has been satisfied and with no information
with respect to smoking history. The vertical scale is logarithmic and
curves are presented for only three radiation dose levels. For these and
other reasons interpolation is to be discouraged.

~ 238 -


Table PC-2-0. Bone and Joint Cancar Follewing Expesure at
Age 0, by Age Az at Diagnosis, Sax, and Dese in Rad of
Alpha Radiation. PC in Percent, te Two Significant Digits
or Three Decimal Places.

Ae Sex

Male Female
Bese

1 10 106 1 +0 100
t 953 -53 5.1 953 <3 3.t
2 18. 64 95. 15, 64, 95.
3 46. 99 99. 48, 89. 99,
4 $7, 93 99, 52. 92. 99.
$ 56. 93 99. 49, oi, 39.
6 St. 91 99. 44, gt. 99.
? 44, 39 99. 38. 86. 98.
8 34. 84. $8. 30. ei, 93,
$ 24. 76 $7. 22. 74. 97.
19 87, $?. 95. 46, 66. 95.
Ww t2. 38. 93. 3. 39. 96,
$2 3.5 $1, gi. 10, 53. 92.
13 7,7 45. ay. 8.7 49. oo,
14 6.4% $0. a7. 7.5 45. &9.
1$ 5.4 36. 85. 6.7 42. 38.
16 4.7 33. &3. 6.1 39. 87,
17 4.1 30. gi. 5.6 37. 8s.
18 3.8 29. ao. $.3 36. 85.
19 3.2 28. 79, 5.2 33. 84.
20 3.6 27. 79. $.t 35. 84.
2) 3.6 27. 79. 5.4 35. 84,
22 3.4 26. 78. 3.0 35. 84.
23 3.2 25. 77. 4.8 34. Bs.
2¢ 2.9 23. 73. 4.7 33. 83.
25 2.7 22. 74, 4.4 32. 82.
2s 2.5 20. 72. 4.2 3e. et.
2? 2.3 19, 7G, 3.9 29. zo.
28 2.0 17, 67. 3.5 27. 78,
29 1,7 18, 64, 3.1 24. 76.
30 1.5 13. 64. 2.7 22. 73.
31 3 32, 58. 2.3 13, an
32 1.2 a1, $5. 2.7 38. eg.
33 tt tO. $3. 2.0 17. 68.
34 tt 9.8 52. z.t 18. 68.
35 1.9 9.4 St. 2.3 19, 79.

- 297 -



data, although more refined analysis of newer data will be useful. The
Working Group interpreted its mandate from the Orphan Drug Act as requiring
assessment of currently available data and the exercise of its best
judyment regarding the handling of the scientific uncertainties that are

at ptesent unresolved. .

Historically, not long after fonizing radiation was discovered tn 1895
and methods for producing and utilizing various types of radiation hecame
available, it was demonstrated that such radiation could he seriously
damaging. first came the tecognition that radiation to the skin could
cause a serious, sunburnlike effect. By 1904 it was learned that radiation
could cause skin cancers, and somewhat later (1911) it was shown that the
incidence of leukemia was elevated in radiolopists.

In 1928 the International Congress of Radiology adopted the first
international recommendation for radiation protection, At that time, it
was believed that there was a threshold for the deleterious effects of
radiation, that is, a dose below which there would be no damage. Work on
the genetic effects of radiation in the 1930's suggested that any dose of
radiation had a certain likelihood of producing a damaging effect on germ
cells. Concern over the genetic effects of radiation (2), so prevalent in
the 1950's, has lessened in the last two decades, whereas the carcinogenic
effects of radiation have become much more evident.

Radiation acts to cause cancers ia a largely random manner. In a
sicuation in which a large number of people have received a moderate-to-
large amount of radiation, the numbers of cancers of specific sites (e.g.,
breast cancer, leukemia, etc.) produced by that amount of radiation can
be estimated. Ye cannot, however, predict which individuals will develop
cancer. Even after the cancer has developed, we cannot state with certainty
whether it was caused by radiation, since it is usually impossible to
differentiate cancers induced by irradiation from those which occur
“normally” in the population.

Cancers appear to be associated with a large aumber of environmental
factors and genetic susceptibilities although, in any individual case, it
is usually not possible to be sure o€ the exact cause of the cancer. The
events that may cause or predispose to cancer interact in several ways,
but only a few of these interactions are known and understood. Moreover,
different individuals are exposed differently, and to a greater or lesser
extent, to various carcinogenic factors as the result of cigarette smoking,
alcohol consumption, viral infection, dietary habits, occupation, heredity,
etc. If detailed knowledge were available about the effects of all these
exposures and interactions, it would be possible theoretically to classify
individuals into a large number of groups among which the probability of
causation of a particular cancer by a given agent could be calculated
mote accurately, For any carcinogen, however, including radtation, che
Aumber of such groups is severely limited at present; i.e., from available
data we can, with some assurance, partition populations into categories
based only on a few factors, including age at diagnosis, sex, smoking
history and age at exposure to radiation. Except for these subdivisions
we calculate probabilities of causation only for aggregate groups in which
unknown variations among individuals may be appreciable. However, probabil-
tries of causation based on even the most minimal partitioning are valid
probabiltties for these groups.

-di-

sate


2.8, 6.94, and 0.074. The linear model is generally considered to over-
estimate the risk in the low dose range, although it is possible to post~
ulate a distribution of susceptible individuals in the population such
that a power curve might better describe the dose-response relationship
(14), In this latter case, low-dose risk estimates might exceed those
based on the linear model, but the applicability of such estimates to the
calculation of PC values would be questionable.

Animal experiments in which a wide range of dose is employed often
show a turn-down in the dose-effect curve at high doses, an observation
attributed to cell-inactivation. The BEIR II1 committee did not employ a
model with a term that brings down the curve at high doses since it vas
concerned with low dose estimation and, since the LDsg for acute whole-
body doses to man is in the range of 350-450 rad, the turn-down is not as
definite in the data on the A-bomb survivors. But for partial-body
irradiation this aspect of dose-response may have considerable importance
when organ doses are very high, as is suggested by the low incidence of
second cancers in patients treated with therapeutic doses of radium and X
radiation for cervical cancer. Failure or inability to correct for this
phenomenon has the effect of over-estimating the PC values at very high
doses.

As indicated in Chapter V-B, for exposure to low-LET radiation the
Working Group has chosen the linear-quadratic dose-response model for all
forms of cancer except cancers of the breast and thyroid. Since the co-
efficient of the linear term of the linear-quadratic dose-response function
was generally derived from the corresponding coefficient of the linear
function employed in the BEIR report for cancer incidence, and the procedure
was merely to divide the latter by 2.5 to create the coefficients used
here, this factor provides one measure of the uncertainty associated with
the choice of the dose-response function, at least in the range of 20 rad
or less. Above 20 rad the p2/116 term becomes increasingly important;
the risk on the linear model would be less than 2.13 times that on the
linear-quadratic model, not 2.5. In addition, there is an uncertainty in
the factor 2.5 that rests on the choice of the cross-over dose, estimated
in Section VII~O below to range from about 1.0 to 6.3,

F. Influence of Age at Exposure

Although the BEIR III risk estimates (1) in Table VI-I here represen-
ted a consensus of informed scientific opinion at the time, there were
few human data to substantiate some of the risk estimates for exposures
below age 10 or, in some cases, below age 20, Although for a few cancers
(thyroid, breast, lung, leukemia) the Working Group has modified the BEIR
1980 risk values on the basis of later data not available to the BEIR
Committee, for most of the cancer types the BEIR risk estimates have been
adopted.

The accuracy of a risk estimate is limited by the number of cases of
a particular cancer observed among persons whose doses were at least 10
tad. Even when that number is reasonably large, the risk estimate may be
subject to considerable uncertainty but, when the number is small, the
uncertainty may be so large that che risk estimate is unusable for the

- 63-


For example, the population rates not influenced by radiation
exposure among the Japanese A-bomb survivors and their non~exposed, local
comparison group are similar to the USA population rates for leukemia but
far lower for breast cancer and far higher for stomach cancer (82). The
question arises: Should the absolute excess risk attributable to radiation
exposure, that is, the difference between total risk and that expected
according to population rates, be assumed to be the same for an trradiated
USA population as for a similarly exposed group of Japanese A-bomb survivors,
or should the excess be scaled Proportionally to the underlying population
rates? Both these extrapolation rules are very simple, even crude, and
there is little information to support more complicated rules. .

In general, absolute excess leukemia risk appears comparable between
Japanese A-bomb survivors and medically irradiated Western populations
with similar doses at similar ages (4). Comparisons between the A-bomb
survivors and two medically irradiated USA poptlations with respect to
breast cancer risk suggest that the absolute excess risk is about the same
in all three populations, for similar ages at exposure, in spite of a
five-fold difference in the underlying population rates (50). At high
dose levels, the excess stomach cancer risk among British patients given
X ray therapy for ankylosing spondylitis was not much different from that
in A-bomb survivors of similar ages at exposure (5,83,84).

Radiation is believed ro affect an early stage of the multi-stage
process that results in cancer at least for breast cancer and perhaps for
other cancers as well. If that is so, then the effect of other agents
which act at an early stage would be simply to add to the effect which
results from radfation. That the causes of excess stomach cancer in
Japan act on early stages is implied by the fact that among Japanese
migrants to the United States, although stomach cancer rates do decline
from the Japanese levels to those which characterize the host country,
they do so only after a very long delay--several decades (85). The
implication is that the initial events had already occurred before the
wigrane left Japan,

A possible contradiction between the constant relative risk model
for time to response and the absolute risk model for projection from one
population to another has been pointed out by Land et al. (50) and by the
National Academy of Sciences Oversight Committee on Radioepidemiologic
Tables (86). Briefly, if the ratios of baseline rates in the two popula-
tions vary watkedly by age at diagnosis, it seems unlikely that both
models can hold. In the case of breast cancer, baseline risk is about 4
times higher in the United States than in Japan, based on age-adjusted
rates from the Connecticut, Miyagi Prefecture, and Nagasaki City tumor
registries (82). On an age-specific basis, however, this ratio varies
from less than 3 at ages under 50 to more than 6 at ages over 70. Thus,
1f the variation of baseline risk over time following some event, like a
tadtation exposure, is truly represented in both populations by the
published population rates, and if within both populations the constant
relative risk model holds, then, for an exposure at age 20 (say), escimates
of average yearly absolute excess risk should not agree between Japanese ‘
and Americans both for the period 10-30 years after exposure and the
period 40-60 years after exposure. Conversely, if measures of absolute
risk agreed between the two populations for any similar follow-up period,

~ 28 -

hee


ESTIMATED PROBABILITY OF CAUSATION (PERCENT)

100

59

20

io

w

v

oy

Fig X-1+C-2

LEUKEMIA: ALL TYPES EXCEPT CLL
EXPOSURE. AGE 10

f r00 RAD

10

as 20 25 35 40 45

AGE AT DIAGNOSIS

30

Male —emee
Female ----

~ 148 -



Table VII~10
Values of the PC for which a 95 Percent

Lower Credibility Limit is 50 Percent

PC for which 50% is the Lower Limit

Factor for Lower Limit Percent
0.2 83
0.3 77
0.4 71
0.5 67
0.6 62
0.7 59
0.8 56
0.9 53

- 115 -



The tables appearing below are:

PC-1-A Chronic granulocytic leukemia

i PC-I-B Acute leukemia

PC-1-C All leukemia except CLL

PC-2

PC-3
PC-4
PC~5
PC-6
PC-7
PC-8
PC-9
PC-10
Pe-1L

PC=12

Bone cancer following exposure to rad{um-224
Salivary gland cancer

Esophageal cancer

Stomach cancer

Colon cancer

Liver cancer

Pancreatic cancer

Lung cancer

Cancer of the female breast

Kidney or bladder cancer

Thyroid cancer.

- 272 -



after 40 or 50 years. Thus, PC estimates calculated for intervals of more
than about 35 years after exposure have an additional element of uncertainty.

L. Interaction with Other Carcinogens

The prevalence of carcinogenic influences in one's environment and
life-style suggests that any individual with cancer following exposure to
ionizing radiation will also have been exposed to other carcinogens. The
only competing risk factor for which the Working Group has been able to
find adequately quantitative data is smoking in relation to lung cancer.
Smoking is a very potent risk factor for lung cancer. The relative risk
of lung cancer for heavy smokers versus non-smokers, about 24, is exceeded
for very few tisk factors. Unfortunately the literature is unclear as to
the nature of the interaction between smoking and ionizing radiation in
this case: a recent analysis of the experience of the U.S. uranium
miners suggests a multiplicative relationship (29), another on Swedish
iron miners suggests an additive relationship (30), and finally, the data
on the A-bomb survivors suggest additivity (31). In the present report,
additivity has been assumed for low-LET radiation and a multiplicative
relationship for exposures to radon daughters. The range of uncertainty
surrounding the choice of model in this case is toughly indicated by the
values of “W" in Chapter IV~H that vary from 6.8 for nou-smoking males to
0.29 for males with a two-pack-a-day habit. That is, these are the
multipliers that are considered appropriate for the additive model, while
under the multiplicative model "W" is one.

For many sites of cancer there are factors that seem able to increase
the risk of cancer by a factor of two or mote, and for all of these it
has been assuned that the multiplicative model is more appropriate. This
assumption, it should be noted, is not based, as ig the choice of model for
smoking, on empirical studies of radiation and other specific carcinogens,
but on the fact that, in the few series with relevant observations, the
distribution of the radiogenic excess over time appears to be proportional
to baseline incidence. If another carcinogenic factor is present in
addition to the radiation, and to a degree greater than average for the
baseline population, and the two factors are additive in effact, the
normal cancer incidence assumed for the PC calculation is too low and the
resulting PC value, too high. If, on the other hand, they interact
multiplicatively, no adjustment is required. The problem is discussed
further in Chapter IV.

M. Other Sources of Uncertainty

In addition to the above sources of uncertainty, for which there is
some information, others can be named for which information is completely
lacking: hormonal Status, genetic or other differences in DNA repair
capability, and other host factors, particularly immune status. It is
extremely difficult to establish the etiology of an individual tumor, bet
epidemiologic and toxicologic studies have identiffed a number of specific
carcinogens for man, and any instance of a cancer following exposure to
ionizing radiation should ideally be reviewed in the context of exposures
to other carcinogens that may, in fact, have been responsible for initiating

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6.

10.

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12.

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14,

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