3.4 Calculation of Doubling Doses for Various Cancer Sites, Considering the
Age Distribution of the Exposures

3.4.1 The Implications of the “Preponderance of the Evidence” Test for
Causation, Applied on an Individual Basis
Over the years various national and international expert committees have assessed the

epidemiological evidence relating specific kinds and amounts of ionizing radiation exposure to the
excess risk of various kinds of cancer in people exposed at various ages. The National Council on
Radiation Protection and Measurements (NCRP)?8 has provided a simple and convenient formula
that utilizes these relationships to calculate the probability that a specific cancer was caused bya
specific radiation exposure:

pc = —AP_ x 100
B+ AD @

where PC is the probability of causation in percent, “A is the lifetime radiation risk coefficient for
the individual (taking account of age, sex, time since exposure, etc.), B is the appropriate baseline
lifetime malignancy rate for the individual, and D is the radiation dose®9 received by the
individual.”

The usual standard of proof for causation/work-relatedness in tort law and workers’
compensation is a “preponderance of the evidence”. In this context, therefore, “proof” means that
it must be just barely “more likely than not” that the worker’s cancer was caused by his or her
exposure. This translates into a Probability of Causation (PC in the above formula) of just over
50%. Based on the formula clearly in order for PC to exceed 50%, AD must be larger than B—or
in other words the dose D received by the worker must exceed the “doubling dose” (the dose that
just doubles the background risk) given by B/A.

3.4.2 “Doubling Doses” for Induction of Various Cancers by Tonizing
Radiation Delivered at Various Ages
Table 15 shows calculated “doubling doses” as defined in the previous section, based on
the age specific EPA risk coefficients discussed earlier for sites where EPA has used relative risk

38National Council on Radiation Protection and Measurements, “The Probability Thar a Particular Malignancy May
Have Been Caused by a Specified Irradiation,” NCRP Statement No. 7, Issued September 30. 1992, 4 pp.

39Or doses, if the individual has been exposed more than once or continuously over some period such as a working
lifetime.

38


2. Magnitude and Distribution of Past Radiation Dosage in DOE and ;
Contractor Employees

2.1 The Distribution of Cumulative Career Total Dosage in Recent Retirees
from Hanford, Los Alamos, and Savannah River

The distribution of career total dosage among workers is a key determinant of the efficiency
of any system for discriminating between cancers that are and are not likely to have been caused in
part by occupational radiation. Other things being equal, if a large fraction of all dosage (and
resulting risk) is concentrated among a relatively few workers, then both assessment and
Compensation resources can be targeted toward those few with relatively high chances of
Occupational causation, with relatively litle loss of “sensitivity” in addressing the needs of rare
individuals who by bad luck developed cancer attributable to relatively low-dose occupational
exposures. On the other hand, if the aggregate past dosage is widely dispersed among a large
population, then in order to deal appropriately with a meaningful percentage of the “true positive”
cases, more substantial costs will need to be incurred in evaluating and compensating larger
numbers of cancers of non occupational origin that are indistinguishable from those whose causal
pathway includes a contribution from occupational radiation exposures.

Through the good offices of Steve Zobel of the DOE we were able to obtain detailed data
on the recorded career total radiation dosage!0 of workers retiring from three major facilities over
the period from 1990-1994. These facilities were chosen because they represent DOE offices and
States with relatively higher concentrations of past radiation dosage, and therefore are likely to have
a significant percentage of eventual compensation cases (Table 1). Overall, the three DOE field
offices that include the covered facilities report over half of the total collective radiation dose
delivered to DOE and contractor employees between 1982 and 1992. Originally, we had also
sought data for Rocky Flats, but because of needs to process data for large numbers of recent
personnel changes, the Rocky Flats facility was unable to supply the requested data in time for this
report.

10The request was for dosage in terms of the current DOE standard for expressing career dose~the lifetime committed
dose. In theory this involves a different treatment of dosage from internal emissions from radionuclides than earlier
standard forms for expressing dosage. The new “committed” doses are defined as the entire dosage that is expected to
be delivered from work in a given year Over the subsequent 50 years, if the worker survives for that period. My
impression is that earlier conventions for expressing dose recorded only the external dose plus the portion of the
internal dose that was expected to be delivered within a particular year. It is not completely clear how much
recalculation of career committed doses from long past radionuclide exposures.is reflected in the data we received.
‘The responsible person from one facility (Los Alamos) was unable to supply us fully recalculated information from
all retirees; but was able to supply these data for participants in their Voluntary Early Retirement program, and these
are the dara reflected in our tables. We expect to receive a limited representative sample of dara for 100 retirees from
this faciliry in the fumre.


Law Offices of
Tom H. Foulds and Associated Counsel

703 Sixth Avenue North Telephone: (206): 285-8390
Seattle, Washington 98109 Facsimile: (206) 285-8494
e-mail <{foulds@home.com> Toll Free: (800) 628-3147

December 13, 2000
Secretary Bill Richardson
Department of Energy
Washington, D.C.

Dear Secretary Richardson,

As a matter of full disclosure, I am counsel for the major group of Hanford
down-winders in the litigation against contractors indemnified by the DOE, and I am
also counsel for plaintiff in a Citizen’s Suit to force the DOE to fund a medical
monitoring program proposed by the Agency for Toxic Substances and Disease
Registry. But, since neither of these legal actions involve claims for worker
compensation, I believe I have the liberty to contact you directly conceming DOE
worker compensation programs.

Specifically, I write in regard to the legislation passed into law by Congress
October 8", 2000 under H.R. 4205 (adopting H.R. 5408) as the “Energy Employees
Occupational Illness Compensation Program”. This legislation was in response to
the admirable program initiatives from your office earlier this year, as outlined in the
DOE press release of April 12, 2000, which included provisions to provide fump
sum benefits to former DOE workers for radiation-related cancers.

However, as you know, the DOE proposals, as reflected in the Senate version
of the legislation, were drastically altered in the House version that was eventually
adopted. The initiatives from your offices had been based upon studies from the
National Economic Council (NEC) that had found significantly higher rates of
cancer among former workers, notwithstanding the historical DOE dose records
showing that virtually all of the individual exposures were far below the levels of
radiation exposure at which increased cancer rates have been detected in other
epidemiological studies. Serious questions have been raised as to the reliability of

Page 1 of 3


47

career doses of at least 5-10 rem.43 Unfortunately, it is difficult to see how these
techniques by themselves will be very helpful in improving the fairness of workers
compensation results in the light of the calculations in Section 2. The status of the
affected workers’ legal cases would only improve if the new procedures revealed that
they had received career total accumulated dosage that exceeded the levels in Tables
15-18 (or Appendix Tables Al-A4). Unless there is a substantial amount of
historically unrecorded dosage due to poorly monitored neutron exposures, etc., this
seems likely only in a vanishingly small proportion of cases.

¢ Category 3 innovations are improvements in the assessment of differences in
individual susceptibility to cancer risk from different types of agents. The recent
literature contains a great deal of information on the variability in genetic and non-
genetic factors that are likely to alter susceptibility to different classes of
carcinogens. If person were known to have a special sensitivity to radiation-induced
cancers (say, because of less efficient repair of radiation-induced DNA damage), it is
possible that their effective doubling dose for the resulting radiation-induced cancers
would be reduced. The recent publication of data on the gene responsible for Ataxia
Telangiectasia is a further case in point.45 This gene is important in detecting radiation
induced damage to DNA and inhibiting cell replication until repair enzymes can remove
the damage, and impaired forms of the gene are relatively common. One copy of a
mutant form of this gene is carried by about 1% of all people. These heterozygotes are
more sensitive to radiation-induced cell killing and mutagenesis. Current preliminary
epidemiology studies suggest that the heterozygotes have a threefold increase in their
telative risk of cancer in general, and a five-fold increased risk of breast cancer (the
breast is a relatively radiosensitive site in humans).*6 If these findings are confirmed,
they would suggest larger relative increases in the risk due to specific identifiable
causes (such as radiation) and correspondingly lower doubling doses, because the
overall increases in incidence are relative to a background incidence thar is related to
multiple carcinogenic agents.

* Category 4 innovations represent improvements in the recognition of non-agent-
specific individual differences in susceptibility to carcinogenesis—such as germ line
mutations in genes that contribute to the genetic pathway to cancer in specific tissues
(e.g., the retinoblastoma gene.) Although such mutations could be expected to
increase the absolute risk due to both radiation and other exposures in affected people,

43Straume, T., and Lucas, J. N. “Validation Studies for Monitoring of Workers Using Molecular Cytogenetics.” in
i i 2 ives, Mortimer L. Mendeisobn, John P. Peeters, and
Mary J. Normandy, eds., Joseph Henry Press, Washington, DC, 1995, pp. 174-193. These authors report that
“many Department of Energy (DOE) radiation workers were exposed to neutrons during the 1940s through the 1960s
when neutron dosimetry was in its infancy. Asio, many individuals have received substantial radiation exposures in
Connection with accidents, nuclear weapons testing, human experimentation. the atom bombs dropped on Hiroshima
and Nagasaki, and various medical radiological procedures.”
44Hanis, D., and Barlow, K. “New Estimates Of ‘Variability In Parameters Putatively Related To Individual Cancer
Risk” Report to the Ministry of Health, Government of Canada, by the Center for Technology, Environment, and
Development, Clark University, March, 1995.
or R,, “Discovery of AT Gene Sparks Biomedical Research Bonanza.” Science 268:1700-1701, (June 23.
5).
46Savitsky, K., Bar-Shira, A., Gilad, S., Roman, G., Ziv, ¥. Vanagaite,; L., Tagle, D. A., Smith, S., Uziel, T.
Sfez, S., Ashkenazi, M., Pecker, L, Frydman, M., Harnik, R., Patanjali, $. R., Simmons, A.. Clines. G. A..
Sartiel, A., Gani, R. A., Chessa, L., Sanal, O., Lavin, M. F., Jaspers, N. G. J., Taylor. A. M. R. Ariett. C. F.,
Miki, T., Weissman, S. M., Lovert. M., Collins. F. S., and Shiloh. Y. “A Single Ataxia Telangiectasia Gene with
a Product Similar to P{-3 Kinase.” Science 268:1749-1753 (June. 23. 1995).


58

Table 25, Continued
Frequency of Deletions and Other Selected Mutation Types Observed in P53
Genes in Human Cancers and Cell Lines Derived from Human Cancers

Type of Tumor % of Tumors with | Number of % Deletions % Deletions + % CpG

P53 Mutations Mutations Studied Insertions ‘Transitions
Miscellaneous 388 9.3 12.4 20.1
Adrenal cortex 23 4 0.0 0.0 25.0
Angiosarcoma 2 0.0 0.0 0.0
Bladder 34 109 4.6 73 17.4
Buccal cavity & 143 13.3 18.2 14.0
Pharynx ("Head and
Neck” - Larynx)

Carcinoid u 1 0.0 0.0 0.0
Cholangio 3 0.0 0.0 53.8
Endomesial 22 1 0.0 100.0 0.0

Eye (melanoma) 2 0.0 0.0 0.0
Kidney—Wilms’ 2 0.0 0.0 0.0
Mesothelioma 2 4 0.0 0.0 50.0
Parathyroid 8 1 0.0 0.0 0.0
Prostate 30 29 13.8 13.8 31.0
Renal 19 9 22.2 22.2 222
Testis 0 2 50.0 50.0 0.0

Thyroid 13 48 8.3 10.4 33.3
Unknown— 8 12.5 125 0.0
metastases
Urothelial 10 0.0 0.0 20.0


11

These estimates do-not include allowances for brain cancers and multiple myelomas. If
brain cancers were to be as susceptible to induction by intemal radiation exposure as estimated by -
_ ‘one researcher~a doubling dose of 25 rem-then 35% of induced brain cancers wouldbe 77 =."
' “Gompensable under a1 doubling dose requirement, and 62% would be compensable under a 1/2’. -
/ doubling dose Tequirement. If the threshold for Tecovery were one tenth of a doubling dose, 87%

would be compensable. - : . : , _

_ Potential Effects: of New Molecular Biological. Techniques on the’
"-Compensability of Radiogenic. Cancers Ts

The last two decades have seen dramatic advances in the molecular biological tools
available for (1) analysis of changes in genetic information and (2) understanding the significance _
of specific changes in particular genes for carcinogenesis. Specifically, these advances in :

- molecular biology have yielded information of four kinds that conceivably could have a bearing on ._

the dilemma described above:
*. Category 1 innovations essentially have the potential to make possible much mofe fine *

scale radiation cancer epidemiology by subdividing tumors-observed at particular :

anatomical sites (and histological types) into categories of molecular pathology. By

molecular pathology I mean (A) the specific series of genes that have been altered or

impaired to produce a particular cancer and (B) the specific changes in DNA sequence

that have occurred in those genes, or the changes in the location of specific sequences

in the genome that has altered the activity of the cancer genes. This category of

innovations has the potential to effectively lower the doubling dose for types of genetic.

_ changes that are established to be preferentially produced by specific kinds of ~<." wo
radiation/radionuclide exposure: P53 in.particular is an important gene on the pathway.
to many cancers that has been the subject of a large amount of DNA sequence analysis.
in individual tumors. About 37% of all tumors carry a defined change in this gene.

The specific type of change that has occurred in individual tumors may provide a clue
to causation.

* Category 2 innovations are techniques to improve radiation dosimetry for past .
exposures (e.g., “FISH”/’Chromosome painting”). These techniques are likely to be
useful in disclosing risks to individual workers who for one reason or another were
not adequately monitored, and who received total career doses of at least 5-10 rem.
Unfortunately, it is difficult to see how these techniques by themselves will be very
helpful in improving the faimess of workers compensation results in the. light of the
calculations in Section 2. The status of the affected workers’ legal cases would only
improve if the new procedures revealed that they had received career total accumulated
dosage that exceeded the levels in Tables 15-18 (or Appendix Tables A1-A4). Unless
there is a substantial amount of historically unrecorded dosage due to poorly monitored
neutron exposures, etc., this seems likely only in a vanishingly small proportion of
cases.

* Category 3 innovations are improvements in the assessment of differences in
individual susceptibility to cancer risk from different types of agents. The recent
literature contains a great deal of information on the variability in genetic and non-


Table 22
HPRT Mutations Studied by Jostes et al. (1994)53 in CHO (Chinese Hamster
Ovary) Cells: (percentages in parentheses)

Agent Whole Gene “Alterations’TM* No Detected Total Relative
Deletions Change Enrichment of
Whole Gene
Deletions
None 5 (16%) 3 (10%) 23 (74%) 31 1.0 (defined)
(Spontaneous)
25-3 Gy radon 14 (52%) 4 (15%) 9 (33%) 27 3.2
-76 Gy radon 11 (44%) 8 (32%) 6 (24%) 25. 2.7
3.0 Gy x-rays 16 (47%) 7 (21%) 11 (32%) 34 2.9
sation aos 41 (48%) 19 (22%) 26 (30%) 86 3.0
Table 23

APRT Mutations Reported by Lehman et al. (1994)54 in CHO (Chinese Hamster
Ovary) Cells (Percentages in Parentheses)

Agent Transitions and Deletions Insertions Total Relative
Transversions Enrichment of
Deletions
None (Spontaneous) 28 (93%) 2 (7%) 0 30 1.0 (defined)
Ultraviolet Light 32 (94%) 1(2%) 1(2%) 34 0.9
Jonizing Radiation 11 (69%) 5 (31%) 0 16 4.7
Benzopyrene Diol 19 (90%) 1(5%) 1(5%) 21 0.7
Epoxide

S3Jones. R. F., Fleck, E. W., Morgan. T. L., Stiegier, G. L., and Cross, F. T. “Southem Blot and Polymerase
Chain Reaction Exon Analyses of HPRT~ Mutations Induced by Radon and Radon Progeny,” Muration Research,
Vol 137, pp. 271-379, 1994. :

. According to the authors, these are “rearrangements within the gene or loss of fewer than 8 exons.”

54Lehman, T. A., Greenblar, M., Bennert, W. P., and Harris, C.C. “Mutational Spectrum of the p53 Tumor

Suppressor Gene: Clues to Cancer Etiology and Molecular Pathogenesis.” Drug Metabolism Reviews, VoL 26. pp.
221-235. 1994.

wu

iv)


Log(rem dose)

Log(rem dose)

Figure 4

= - 0.56544 + 0.41759x} RaQ = 0.953

00+
1 2 3 4 5
1965 Z-Score
Figure 5

1968--Lognormal Plot of Penetrating Tonizing Radiation
Exposures for DOE and Contractor Employees

0.8

0.6

0.4

0.2
Y= - 0.292774 0.26233x RQ = 0.873;

0.0

1968 Z-Score


Table Al
Doubling Doses for Breast Cancer Mortality and Total Breast Cancer Incidence in

Women
Age at Exposure Time After GSD Excess Implied Doubling Implied Doubling Dose
Exposure Relative Dose (Rem) Without (Rem) With Lognormal
(Years) Risk Per 10 Lognormal Correction Correction
Rem
Beast Cancer Mortality

5 15 19 0.418 24 19
25 1.6 0.427 23 21

35 1.57 0.23 43 39

45 1.89 0.105 95 78

15 15 19 0.418 24 19
25 1.6 0.427 23 21

35 1.57 0.23 43 39

45 1,89 0.105 95 78

25 15 L77 0.056 179 152
25 1.54 0.057 * 175 160

35 1.6 0.031 323 289

45 1.99 0.04 250 197

35 15 19 0.03 333 271
25 1.76 0.03 333 284

35 1.85 0.016 625 317

45 15 231 0.016 625 440
25 225 0.016 625 450

55 15 2.99 0.008 1250 686

Breast Cancer Incidence

<20 15 1.45 0.52 19 18
25 1.24 0.27 37 36

35 13 0.18 36 54

45 1.44 0.13 77 72

20-39 15 1.35 0.12 83 80
2s 1.26 0.06 167 162
35 1.4 0.04 250 236

45 1.57 0.03 333 301
240 15 29 0.05 200 113
25 2.88 0.02 500 286

35 2.99 0.02 500 274


Table 7

Annual Recorded Dosage Delivered to Hanford Workers, 1944-1989

Year
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1987
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Total

Workers Monitored
3495
5826
4195
5349
6923
6665
6499
8090
8457
8108
8337
9055
9406
9463
8848
8115
8308
8398
8404
8669
8969
8878
8660
8731
8634
8315
7967
7618
6981
7000
7919
8432
9577
10778
11818
10775
9666
8934
8446
8175
7972
7699
7387
6983
6406
5700

369030

Total Dose (person-rem)
207.2
1309.8
583.8
420.1
329.1
436.2
584
770.4
1193.5
1772.9
1566.4
1918.3
1943.5
1951.2
2613.3
2211.3
2629.9
3204.8
4098.9
3948.8
4605.8
6182.4
4062
3556.7
3629.4
2961
2496.8
2293.3
2579.7
2120.9
2317.2
2487.1
2082.5
2254.3
1828.8
1657.9
1254.1
873.9
1030.7
771
685.4
642.7
530.1
533.2
169.1
222.6
87,522

% Total Dose in Year
0.24
1.50
0.67
0.48
0.38
0.50
0.67
0.88
1.36
2.03
1.79
2.19
2.22
2.23
2.99
2.53
3.00
3.66
4.68
4.51
5.26
7.06
4.64
4.06
4.15
3.38
2.85
2.62
2.95
2.42
2.65
2.84
2.38
2.58
2.09
1.89
1.43
1.00
1.18
0.88
0.78
0.73
0.61
0.61
0.19
0.25

18


4. Prospects for Individual “Proof” of Causation for Radiation-
Induced Cancers in the Population of Former DOE/Contractor
Workers :

4.1 Fraction of Cancers that Could be Compensable Under the Usual “More
Likely Than Not” Test

Given the estimates of doubling doses in Tables 17 and 18 in the previous section, the
estimated distribution of cumulative dosage in workers surviving to 1995 and various years in the
future (Tables 4 and 9 of Section 2), what percentage of DOE and contractor employees who might
be expected to develop cancer as the result of their DOE exposures will be in a position to “prove”
causation on the basis of their own personal documented dosages? Table 19A shows the
proportions of affected workers who would be expected to exceed the doubling doses for the
tumors in question, and the overall percentage of radiogenic cancers expected to appear in various
Periods that would be expected to be compensable. Table 19B shows a similar treatment under the -
assumption that the threshold of compensation might be set at half of the doubling dose (omitting
the effect of the DDREF). 20A and 20B are similar except that for this table the analysis is
confined to fatal cancers only.

Itcan be readily seen that very few workers with radiogenic cancers could be expected to
be compensated under the 1 doubling dose standard, if the doubling doses are as high as those
calculated using a DDREF of 2—about 1 % of total cases and 1.4% of total deaths would be
compensated. 1% of total cases, of course, represents about 4 people out of the 360 cases in the
lower bound of our range of estimates of radiogenic cancers in DOE and contractor employees.

The outcome is markedly better, but still quite discouraging at half the calculated doubling
doses (corresponding to a case in which the DDREF is set at 1). Under this assumption, about
4.2% of all cases and 5.4% of total fatal cases of the enumerated types could be eligible for
compensation. 5.4% of all cases represents about 54 compensable cancers out of the 1,000 in our
upper bound estimate of all occupationally caused radiogenic cancers in the DOE/contractor
workers.

These tables do not include allowances for brain cancers and multiple myelomas. If brain
cancers were to be as susceptible to induction as estimated by Alexander (see above)—a doubling
dose of 25 rem—then 35% of induced brain cancers would be compensable under a 1 doubling
dose requirement, and 62% would be compensable under a 1/2 doubling dose requirement.”

* Under progressively less demanding thresholds. the fractions compensable under .2. .1, and .075 doubling dose
thresholds would be about 80%, 87%, and 90%, respectively.


Log(rem dose)

Log(rem dose)

Figure 10

1983--Lognormal Plot of Penetrating Ionizing Radiation
Exposures for DOE and Contractor Employees

0.8
0.65
0.45
icf

0.24

| y= - 0.92479 +0.45255x R42 = 0.997
0.0 T

2 3 4

1983 Z-Score

Figure 11

1986--Lognormal Plot of Penetrating Ionizing Radiation
Exposures for DOE and Contractor Employees

0.8
0.6 4
0.44
024
y= - 0.6248 +0.3233x R*2 =0.967
0.0 +a t 7
2 3 4 * 5

1986 Z-Score


In the section immediately below, we will consider possible “technical fixes” for this
problem—possible new molecular biological technology on the horizon that could help better
quantify past dosage and distinguish cancers that are more vs less likely to have been caused by
ionizing radiation. .

4.2 Analysis of Recent Innovations in the Molecular Biology of Cancer, and
Potential Implications for the Legal Determination of Cancer Causation

4.2.1 Four Categories of Improved Information Resulting from Recent
Scientific and Technical Advances
The last two decades have seen dramatic advances in the molecular biological tools
available for (1) analysis of changes in genetic information*2 and (2) understanding the
significance of specific changes in particular genes for carcinogenesis. Specifically, these
advances in molecular biology have yielded information of four kinds that conceivably could have
a bearing on the dilemma described in the previous section:

* Category | innovations essentially have the potential to make possible much more fine
scale radiation cancer epidemiology by subdividing tumors observed at particular
anatomical sites (and histological types) into categories of molecular pathology. By
molecular pathology I mean (A) the specific series of genes that have been altered or
impaired to produce a particular cancer and (B) the specific changes in DNA sequence
that have occurred in those genes, or the changes in the location of specific sequences
in the genome that has altered the activity of the cancer genes. This category of
innovations has the potential to effectively lower the doubling dose for types of genetic
changes that are established to be preferentially produced by specific kinds of
radiation/radionuclide exposure.

* Category 2 innovations are techniques to improve radiation dosimetry for past
exposures (e.g., “FISH’/’Chromosome painting”~see note 42 above for citations).
These techniques are likely to be useful in disclosing risks to individual workers who
for one reason or another were not adequately monitored, and who received total

42Such changes include both “point mutations” (changes at particular places in the DNA code) and rearrangements of
information represented by the transfer of large sections of chromosomes in recombination events. Point mutations
have been studied by extracting specific genes from tumors and other cells. copying the genes many times. and
determining the detailed sequence of DNA bases in those genes. One specific cancer related gene that has been
extensively studied in this way is p53 (Greenblatt. M. S., Bennen, W. P., Hollstein, M., and Harris. C. C.
“Mutations in the p53 Tumor Suppressor Gene: Clues to Cancer Etiology and Molecular Pathogenesis,” Cancer
Research 54:4855-4878, 1994.) Persistent chromosome rearrangements suitable for assessment of past radiation
doses have been studied by both conventional cytogenetic and chromosome banding studies, and newer techniques
that are referred to under the “Fluorescence In Sim Hybridization (FISH)” or “Chromosome Painting” rubrics
@renner, DJ. and Sachs, R.K. “Chromosomal ‘Fingerprints’ of Prior Exposure to Densely Ionizing Radiation.”
Radiation Research 140:134-142, 1994; Tucker, J. D., Ramsey, M. J., Lee, D. A., and Minkler, J. L. “Validation of
Chromosome Painting as a Biodosimeter in Human Peripheral Lymphocytes Following Acute Exposure to Ionizing
Radiation In Vitro,” International Journal of Radiation Biology 64(1):27-37, 1993; Lucas. J. N.. Poggensee. M.. and
Straume, T. “The Persistence of Chromosome Translocations in a Radiation Worker Accideatally Exposed to
Tritium.” Cytogenetics & Cell Genetics 60(3-4):255-256, 1992.)

46


83 -

Table A2
Doubling Doses for Cancer Mortality for Sites Other Than the Breast
Age at Exposure Time After GSD Excess Implied Doubling ‘Implied Doubling
Exposure Relative Risk Dose (Rem) Without Dose (Rem) With
(Years) for 10rem Lognormal Correction Lognormal Correction
Dose
Respiratory Cancer Mortality--Males
All Ages 15 1.59 0.096 . 104 94
25 2.03 0.046 217 169
35 2.63 0.028 357 224
45 3.23 0.02 500 251
Respiratory Cancer Mortality--Females
All Ages 15 1.47 0.196 31 a7
25 1.76 0.094 106 OL
35 2.27 0.058 172 123
45 2.8 0.04 250 147
Digestive Cancer Mortality
Males, All Ages amames> 15 0.081 123 4
Females, All Ages All times > 133 ot 1 68

Leukemia Mortality (Males and Females)

<20 <i5 28 3.637 27 1.6
16025 253 291 34 2
2260332 0.027 370 180
221 25 1830287 35 29
261030 252 0.139 n 47
2310332 (0.027 370 180
Other Cancer Mortality ;
5 ams? ss 0.123 81 74
15 140.097 103 97
25 131 0.061 164 158
35 145 (0.038 263 246
45 L75—(0.024 417 356
55 217 0.015 667 494

65 271 0.009 IL 676


Table 8, Continued

Age Non-Smoker Mortality Risk Per Year % of Starting Population Alive at End of Year
73 0.0338 63.302
14 0.0353 61.065
75 0.0368 58.818
16 0.0411 56.400
77 0.0454 53.839
78 0.0495 SL.A71L
79 0.0537 48.425
80 0.0578 45.626

8i* 0.222 35.499
82 0.387 21.768
83 0.556 9.653
84 0.728 2.624
85 0.98 0.053

*Data for ages over 80 were adjusted upward to produce complete essentially mortality by age 86.

Table 9
Expected Changes in the “Inventory” of Collective Radiation Dosage in Surviving
Workers, 1970-2025

Dose Surviving to Year % Dose Surviving

Total Delivered 1944-1992 640,000 100

1970 400,000 62

1975 460,000 2

1980 500,000 78

1985 500.000 78

1990 480,000 75

1995 420,000 66

2000 360,000 56
. 2005" 290,000 45 .
7 2010 220.000 34

2015 160.000 24

2020 100,000 16

2025 63,000 10


66

Table 29
Percentage of Total Radiogenic Cancer Cases Occurring in Different Time Periods
That Would Be Eligible for Compensation

A. Requirement for 20% of the Doubling Dose--% Cases Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, All Times
Leukemia 2.83 1315 1.176 0.000 5.32
Liver 0.45 0.332 0.297 0.298 “137
Bladder 117 0.870 0.785 0.794 3.61
Ovary 0.06 0.046 0.045 0.048 0.20
Stomach 0.46 0.341 0.574 0.812 2.18 - a
Kidney 0.04 0.028 0.025 0.025 O12 |
Colon/intestine 0.09 0.067 0.185 0.287 0.63
Esophagus 0.02 0.013 0.011 0.009 0.05
Breast 0.00 0.000 0.005 0.008 0.01
Remainder 0.00 0.000 0.000 0.000 0.00
Lung 0.00 0.000 0.000 0.000 0.00
Total 3.1L 3.01 3.10 2.28 13.5

B. Requirement for 10% of the Doubling Dose--% Cases Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, All Times
Leukemia 3.21 1.487 - 1.344 0.000 6.04
Liver 0.57 0.427 0.382 0.382 1.76
Bladder. 1.68 1.253 1.125 1.131 5.19
Ovary 0.12 0.089 0.082 0.084 0.37
Stomach 124 0.923 1.005 1.134 430
Kidney 0.14 0.105 0.094 0.094 0.44
Colon/Intestine 0.90 0.673 1.103 1.379 4.06
Esophagus 0.10 0.073 0.062 0.055 0.29
Breast 0.04 0.028 0.038 0.050 0.15
Remainder 0.80 0.598 0521 0.511 2.43
Lung 0.12 0.092 0.036 0.000 0.25

Total 8.91 5.75 5.79 4.82 25.27


Figure ES-1

Total Cumulative Person-Rem in
Hanford Retirees by Year of Age

1200 +

1000 4 _—

68% of Total Population Dose in
800 + Retirees Between 55 and 66 Years Old

Total Person-Rem

600 +
400 +
200 +
04
15
Age
Figure ES-2

Collective Dose Delivered In Various Years to 37,009
Exposed Hanford Workers Who Were First Employed
Between 1944 and 1978--Data of Buschbom and Gilbert, 1993

7000

6000 4
5000 4
4000 3

3000 ~

Total Dose (Pdison-iem)

2000 +

1000 +

Qo T T T T
1940 1950 1960 1970 1980 1990

Year


Radiation-Induced Cancers in DOE and Contractor
Employees--Prospects for the Individual Ascertainment
of Causation

Dale Hattis, Ph.D.

. Research Associate Professor
Center for Technology, Environment,-and Development (CENTED)
George Perkins Marsh Instimte, Clark University
950 Main Street
Worcester, Mass 01610

October 1995


2.2.3 Estimates of Aggregate Radiation Doses Delivered for DOE and
Contractor Employees as a Whole, By Year and Age, 1944-1992
Assuming that the dose delivered in the studied Hanford population has been a roughly
consistent fraction of overall DOE exposures over the years, the Hanford data can be used to make
an approximate projection of the overall DOE-wide collective dose delivered between 1944 and
1992. We first note that between 1965 and 1989, the studied Hanford workers received about
14% of the total DOE-wide collective dose:
Hanford 1965-1989 DOE 1965-1989 %Hanford/DOE
person-rem person-rem.
49,200 355,000 13.9

The result is similar if the analysis is restricted to the period between 1965-1978, when all eligible
Hanford hires should be included in the study group:
Hanford 1965-1978 DOE 1965-1978 %Hanford/DOE
person-rem person-rem
40,900 265,000 15.4

If we assume this same relationship holds approximately for the 1944-1964 period, we project
Recorded Hanford 1944-1964 Estimated DOE 1944-1964 person-
person-rem rem
38,300 276,000

This leads to a projection that DOE and contractor workers as a whole probably received about
640,000 person-rem between 1944 and 1992.

2.3 Expected Loss of the Inventory of Cumulative 1944-1992 Dose with Past
and Expected Future Mortality, 1970-2025

As a prelude to the calculation of the times of appearance of the cancers resulting from.
radiation exposure, it is of interest to know how the “inventory” of overall accumulated radiation
dosage changes over the years. Inventory accumulates as more dosage is received by the worker
population, but it is also lost as the workers who received some of the radiation die. (The mortality
is of course from all causes, not just the small number of radiation-induced cancers).

General mortality is a strong function of age. Therefore, using the age-at exposure
information from the Hanford study (Figure 14) I created a year-of-exposure by age-at-exposure
matrix. For single years in each dimension I then applied the general mortality rates listed in Table


Us
vn

well-controlled epidemiological studies have found that people exposed to a dose of radiation d
have a lifetime risk of those cancers of R(D), where

R(D) = + qD ; (3)

The doubling dose defined earlier, D2,, where the probability of radiation-induced causation is at
the borderline of the conventional more-likely-than-not (“preponderance of the evidence”) criterion
of tort law and most workers’ compensation system, is of course given by

D,, =" “)

so

Now let us suppose that radiation is much better at causing one kind of DNA change (e.g.,
deletions) than another (e.g., point mutations). We can break down the total cancer risk, R(D) into
these two components:

RD) rorat = RD) getedons + R(D) point mataons

5
= Roactground deletions + Qt ictaced deteioos + Rrnctsrount point mations + ind poise ucaions]) 6)
Because, by hypothesis, radiation is better at inducing deletions than point mutations, the q) for
deletions must be larger in relation to the corresponding background for deletions than the q; for
point mutations is in relation to the background for point mutations. Therefore, in terms of the
doubling doses for cancers with each type of genetic change,

Roackzround deletions

Roeackground point murations
Da. cancers with deletions = <D,, ‘with point mutstions =
1 inctuced deletions 1 induced point mutations

(6)

‘The magnitude of the reduction of the doubling dose for the cancers with deletions (or any other
type of mutation) depends on just how much enrichment there is of the deletions in the radiation-
induced cancers/mutations relative to the background cancers/mutations. If we believe the Taylor
et al. (1994) observations reported earlier (see equation 2 above), this enrichment could be as much
as a couple of hundred fold in favorable cases. Below we will examine the less favorable case of
deletion mutations based on available information from a number of different sources.

Tables 22-24 show data from three in vitro (cell culture) system on the enrichment of
deletions in radiation-exposed cells with specific selectable mutations relative to similar mutations
arising spontaneously or in cultures exposed to other mutagenic agents. Each of these dara sets is


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Department of Energy - :
Washington, DC 20585 ian’ ares ne

January 19, 2001 C BY
Mr. Tom H. Foulds

Law Offices of Tom H. Foulds Ted here.
and Associated Counsel . Kethy 14

703 Sixth Avenue North

Seattle, Washington 98109

Dear Mr. Foulds:

In response to your letter to Secretary Bill Richardson of December 13, 2000, I am
enclosing a copy of the “Energy Employees Occupational Illness Compensation
Amendments of 2001” that was announced on January 11, 2001, as well as the Executive
Order 13179 that. was signed by the President on December 7, 2000.

I have also taken the liberty of forwarding your concerns to the Department of Health and
Human Services (HHS). HHS is the agency that has been assigned the responsibility of
promulgating the guidelines “to assess the likelihood that an individual with cancer
sustained the cancer in the performance of duty” and of developing methods for estimating
radiation doses.

Sincerely, .

L- _

David Michaels, PhD, MPH

Assistant Secretary

Environment, Safety and Health
2 Enclosures

cc w/o enclosures:
ir. Larry Fine, NIOSH, w/incoming

@ Printed with soy ink on recycled paper


concept (a PC of 50% or more), will compensate only 1% of the radiogenic
cancers, and even using the PC upper 99% confidence interval, the percentage of
workers compensated would still not be increased beyond 6%. (See: Radiation
Induced Cancers in DOE and Contractor Employees~Prospects for the Individual
Ascertainment of Causation, October 1995, Dale Hattis, Ph.D., copy enclosed)

In other words, the proposals of the DOE to do the right thing for the former
workers with radiogenic cancers have been completely thwarted by the legislation
as finally written. In the hopes you can turn this problem over to DOE staff who will
be assisting the next administration and noting that the legislation itself provides for
corrective proposals being needed and made to Congress before a March 15, 2001
deadline, I am respectfully suggesting that before you leave office you initiate the
staff development of such corrective proposals to begin as soon as possible to meet
the deadline. Without changes, the present program offers only chimerical benefits
instead of the deserved compensation contemplated by your proposals.

Yours truly,
Tia ber
“Tom H. Foulds
~ cc Senator Patty Murray
cc Senator Maria Cantwell

Page 3 of 3


End

Employment

1990-1994
1990
1991
1992
1993
1994

Average rem/person

Aveage Ave age of workers Total person- Total N
with dose rem .
38.6 46.3 10964 10709
36.7 42.1 T31 1109
37.8 432 1425 1361
37.1 43.5 1261 1470
37.6 44.3 1804 2359
40.3 50.0 5744 4410
Figure 3

Table 5

Hanford Summary by Year of Retirement

N with non-
zero dose

4883
282
758
660
1120
2063

Rate of Increase in Average Career Rem/Person
in Older Age Groups--Hanford Retirees

12
y= -14.0+0302x R‘2=0.815 .
104
(Line based on points from 50+ age
8 groups only.)
64
a4
24
1-3
8 ict
0 +e —-S_, 7 7 +
20 30 40 50 60 70 80

Age (5 yr groups)

% with non-zero
dose

45.6
25.4
55.7
449
475

46.8


Table 30
Percentage of Total Radiogenic Cancer Deaths Occurring in Different Time
Periods That Would Be Eligible for Compensation

A. Requirement for 20% of the Doubling Dose--% Deaths Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, All Times
Leukemia 3.99 1.885 1.686 0.000 7.56
Liver 0.60 0.457 0.409 0.409 1.87
Bladder 0.83 0.631 0.569 0.576 2.60
Ovary 0.06 0.048 0.047 0.050 0.21
Stomach 0.58 0.445 0.748 1.059 2.84
Kidney 0.03 0.027 0.024 0.024 0.11
Colon/Intestine 0.07 0.054 0.148 0.229 0.50
Esophagus 0.02 0.018 0.015 0.012 0.07
Breast 0.00 0.000 0.003 0.006 0.01
Remainder 0.00 0.000 0.000 0.000 0.00
Lung 0.00 0.000 0.000 0.000 0.00
Total 6.19 3.56 3.65 2.37 15.8

B. Requirement for 10% of the Doubling Dose--% Deaths Compensable

Before 1991 1991-2000 2001-2010 «2011-2035 Total, All Times
Leukemia 4.52 2132 1.927 0.000 8.58
Liver 0.77 0.587 0.525 0.526 * 241
Bladder L19 0.909 0.816 0.820 3.74
Ovary 0.12 0.093 0.086 0.088 0.39
Stomach 1.58 1.203 1310 1.479 5.57
Kidney 0.13 0.100 0.089 0.089 0.41
Colon/Intestine 0.70 0.536 0.879 1.099 3.22
Esophagus 0.13 0.100 0.084 0.076 39
Breast 0.03 0.021 0.028 0.037 O.1L
Remainder 0.70 0534 0.465 0.526 22
Lung 0.17 0.126 0.050 0.000 0.34

Total 10.03 6.35 6.26 4.74 274


distinguishing mutations induced by background and medical sources of radiation from mutations
induced by occupational radiation sources. Background and medical radiation exposures can be
appreciable in the context of lifetime cumulative dose. Official estimates of national average
background radiation exposure are about 100 rem/year (1 mSw/year). Medical exposures to
diagnostic x-rays—which are likely to be highly variable from person to person~are said to average
an effective dose equivalent of 39 mrem/year based on early 1980's technology.57 Over a 50 year
period, the mean from these two non-Occupational sources would add up to about 7 rem—
considerably greater than the mean career dose of a litle more than 2 rem in recent retirees from
selected DOE facilities.

Co nclusions--The Trajectory of Furure Technical Developments

The foregoing should be sufficient to indicate that, marvelous as the new technology is for
understanding the molecular basis for some tumors, there is no near term prospect that, by itself, ic
will solve the problem of under compensation of radiation-induced tumors. Nevertheless, there is
some hope that further basic research, with the cooperation of DOE and its former
contractors/workers, could eventually lead to better results. A systematic program of sequencing
the p53 genes and other cancer related genes (as techniques become available) in former workers
with known relatively high accumulated lifetime exposures (say, over 5 rem), and concurrent
controls with lower known exposures, could eventually yield the kind of spectacular enrichment of
specific mutations at specific places by specific kinds of radiation that we saw in the radon
example. (The radon example itself, of course, requires confirmation in further studies), With
such observations, radiation cancer epidemiology could be enhanced; dose-time-response
relationships could be better defined at low dose rates, and possibly some additional rumors could
be more definitively linked to their causes.

4.3 The Prospect of Bayesian Modification of Individual Doubling Doses for
Cancer Cases in the Light of Uncertainties in the Individual Estimation of
Dosage
There is one other possible “technical fix” that may be useful in securing compensation for
some workers without changing the current rules. This has been suggested informally by Robert
Goble (a physicist in the Environmental Science and Policy Program at Clark University). The
extent of its potential applicability is difficult to assess at this time.

37National Council on Radiation Protection and Measurements (NCRP), “Ionizing Radiation Exposure of the
Population of the United States,” Report 93, Bethesda. Md. (1987) quoted by Menter. F. A. and Upton. A C.
izing Radiation, Second Edition, W. B. Saunders Company, Philadeiphia. 1995. p. 31.


Therefore the use of stationary 1980 population distribution and death statistics is
likely to understate future life expectancy and the numbers of people who will survive
to older ages where there is a relatively high incidence of cancer. Additionally,
improvements in the effectiveness of cancer treatment may well prolong the survival of
patients with cancer and shift some cases from the “fatal” to “non-fatal” categories
(hence I have broadened the range of “total cases” to three-fold, in comparison to the
two-fold range applied to the base estimate of “cancer deaths”).

Figure ES~4 presents the resulting time pattern of overall cancers (other than leukemia)
expected to result from dosage delivered to DOE workers between 1944 and 1992; Figure ES-5
presents the same data projected in the form of a cumulative distribution for cancers occurring
between 1965 and 2030. The peak year for the radiogenic cancers other than leukemia appears to
be about 1995 or the next couple of years in the future. About 32% of the total cancers are
expected to have occurred prior to 1990; about 44% will have occurred by the end of 1995; and
two thirds are expected to happen by 2005.

Prospects For Individual “Proof” Of Causation Of The Radiation-
Induced Cancers

Expected Compensation Under the Current “One Doubling Dose” Threshold
for Recovery

In general a worker must show past exposure that exceeds the relevant cancer “doubling
dose” in order to satisfy the usual “preponderance of evidence” test for legal causation. Figure ES-
6 shows the estimated distribution of worker exposure in relation to the doubling doses for the
most radiation sensitive cancer sites covered in the EPA radiation cancer potency estimates. It can
be readily seen that although the past worker exposures may well have induced several hundred
cancers, the numbers of workers who have past accumulated doses in excess of the officially
recognized doubling doses are very small.

More detailed calculations indicate that if the doubling doses are as high as those calculated
using a DDREF of 2--only about 1 % of total cases and 1.4% of total deaths would be
compensated. 1% of total cases, of course, represents about 4 people out of the 360 cases in the
lower bound of our range of estimates of radiogenic cancers in DOE and contractor employees.
The outcome is markedly better, but still quite discouraging at half the calculated doubling doses
(corresponding to a case in which the DDREF is set at 1). Under this assumption, about 4.2% of
all cases and 5.4% of total fatal cases of the enumerated types could be eligible for compensation.
5.4% of all cases represents about 54 compensable cancers out of the 1,000 in our upper bound
estimate of all occupationally caused radiogenic cancers in the DOE/contractor workers.


* — Ttis far from obvious that the two-fold Dose and Dose Rate Effectiveness Factor is
appropriate (and uniform in magnitude) as applied to all cancers other than breast and

leukemia. Surely if DNA repair saturation is the underlying mechanism, there is likely

to be a different amount of high dose saturation (and therefore high-to-low dose
change in dose response slope) for different tissues. The very fact that a uniform
factor is applied indicates that specific data relevant for different cancer sites are
probably not available, and the overall two-fold reduction in potency due to this factor
carries considerable uncertainty.

* Competing sources of mortality (in particular, cardiovascular diseases) have been
declining in recent decades, increasing the proportion of deaths due to cancer.
Therefore the use of stationary 1980 population distribution and death statistics is
likely to understate future life expectancy and the numbers of people who will survive
to older ages where there is a relatively high incidence of cancer. Additionally,
improvements in the effectiveness of cancer treatment may well prolong the survival of
patients with cancer and shift some cases from the “fatal” to “non-fatal” categories
(hence I have broadened the range of “total cases” to three-fold, in comparison to the
two-fold range applied to the base estimate of “cancer deaths”).

3.3 How Many Radiation-Induced Cancers of Various Types Should Be
Expected When?

For most cancer sites other than leukemia, the EPA assumes that there will be a constant
increase in relative risk over baseline after a 10 year lag period. [For the relevant leukemias, the
time pattern is more complex—depending on both age at exposure and time after exposure (Figure
15).]

To calculate the expected time pattern for the occurrence of cancers other than leukemia for
the DOE and contractor workers I started with a generic baseline relative risk assumption derived

For example, although the most recent analysis of worker mortality does not show an overall excess of cancer in
relation to 10-year lagged dose when leukemias are separated out, there is a trend in the data toward more positive
results with longer lag periods:

Lags for dose (years) All Cancers Excluding Leukemia~Excess 90% Confidence

Relative Risk/100 Rem Limits
0 021 . (0.4.0.1)
5 O13 (-0.4,0.2)
10 0.07 (-0.3,0.3)
15 0.04 (05.05)
20 40.14 (0.5.0.9)

Source: Cardis, E., Gilbert, E. S., Carpenter, L.. Howe, G., Kato, L, Armstrong, B. K., Beral. V., Cowper, G..
Douglas. A, Fix. J., Fry, S. A. Kaldor. J., Lave, C., Salmon. L., Smith. P. G., Voelz. G. L. and Wi .
“Effects of Low Doses and Low Dose Rates of External Ionizing Radiation: Cancer Mortaliry Among »
Industry Workers in Three Countries,” Radiat. Res. 142:117-132 (1995).

uw
tes)


75

: — Table 33
Ratios of Total Compensated Cases/’True” Radiogenic Cancer Deaths for Various
Thresholds for Compensation

A. Requirement for One Doubling Dose
Ratio of Total Compensated/’True” Radiogenic Deaths

Total % Radiogenic Cancers 1991-2000 2001-2010 = 2011-2035 = Total, All Times

Compensated 1991+ of all
Caused by 1944-1992 Exposures

Leukemia 0.610 L718 1.694 1.706
Liver 0.057 1.858 1.858 1.858 1.858
Bladder 0.031 1.914 1.909 1.903 1.909
Ovary 0.000

Stomach 0.023 1.887 1.887
Kidney 0.000

Colon/Intestine 0.000

Esophagus 0.000

Breast 0.000

Remainder 0.000

Lung 0.000 .

Total 0.721 1.733 1.709 1.880 1.732

B. Requirement for 50% of the Doubling Dose
Ratio of Total Compensated/”True” Radiogenic Deaths
Total % Radiogenic Cancers 1991-2000 2001-2010 2011-2035 Total. All Times

Compensated 1991+ of all
Caused by 1944-1992 Exposures

Leukemia 1.90 2.28 222 2.25
Liver 0.47 2.43 2.43 2.43 2.43
Bladder 0.36 2.48 2.48 2.46 2.47
Ovary 0.02 2.68 2.65 2.62 2.66
Stomach 0.33 2.74 2.63 2.45 254
Kidney 0.00
Colon/Intestine 0.00
Esophagus 0.00
Breast 0.00
Remainder 0.00
Lung 0.00
Total 3.08 2.34 2.30 2.44 2.35


Table 24
HPRT Mutations Studied by Nelson et al. (1994)55 in TK6 cells (Human B-
Lymphoblastoid Cell Line)

Agent Complete Gene OtherDeletions Total, All Total Mutants Relative
Deletions Deletions Studied — Enrichment of
Complete
Deletions
None
(Spontaneous) 7 (9%) 41 (53%) 48 (62%) 78
X-Rays (200 41 (35%) 45 (39%) 86 (74%) 116 “3.9
cGy)

based on a limited sample size, and the results vary depending in part on the kinds of deletions and’
other mutations that are effectively detected in the various authors’ assay system, the background
frequencies of different mutations in the different systems, etc. Overall, however, it can be said
that complete gene deletions often seem to be enhanced in radiation-exposed cultures, and there is
some evidence that smaller deletions are enhanced relative to other mutations in some cases. The
most favorable case for the latter conclusion is seen in Table 23, where (based on a very limited
sample) deletion mutations are enhanced nearly 5-fold relative to spontaneous mutations and
mutations induced by other agents.

Table 25 is a large compilation of data from over 2800 P53 mutations found in human
tumors and cell lines derived from human tumors. The first column of data~the % of tumors of
various types that have been found to contain p53 mutations—comes from Table 2 of Greenblatt et
al.48 The other information was extracted from the latest available version of a data base (last
updated June, 1994) available from the European Molecular Biology Laboratory over the
internet.°6 Table 26 analyzes the subset of this information that involves lung cancers~—comparing
the frequency of deletions and insertions in lung cancers that were and were not associated with
tadon. It can be seen that if all the lung cancers are included (Table 26A) there appears to be about
a 3-fold enrichment of deletions and insertions in radon-associated lung cancers compared to other

55Nelson, S. L., Giver, C. R., and Grosovsky, A. J. “Spectrum of X-ray-induced Mutations in the Human HPRT
Gene,” Carcinogenesis, Vol. 15, pp. 495-502, 1994.
S6Hollstein, M., Rice, K., Greenblatt, M. S., Soussi, T., Fuchs, R.. Sorlie, T., Hovig, E., Smith-Sorensen. B..
Montesano, R., and Harris, C. C. “Database of P53 Gene Somatic Mutations in Human Tumors and Cell Lines.”

ic Aci Vol. 22. pp. 3551-3555, 1994. The database can be obtained by sending an Email message
to NetServ@EBLAC.UK and including the line Get P53:(filename). A list of the filenames can be obtained by
sending the message “help p53”.

54


Figure 12

1992--Lognormal Plot of Total Equivalent
Exposures for DOE and Contractor Employees

1
3
cs
ra}
]
2
3 4
2 Q
S
3
s
i=
& -1-
2
S y = - 2.1797 +0.73464x R*2 = 0.998
a

-2 T T T

1 2 3 4 5

Z-Score

Figures 4-12 indicate that for these data sets, with the possible exception of 1992, the fit is
reasonable, but there are systematic tendencies to depart from the expected lognormal distribution
in particular ways. For all of the graphs through 1986 the slope of a line drawn between the first
two points (corresponding to 1 rem and 2 rem) is steeper than the line for the overall population
distribution. A steeper line corresponds to more variability. This is an indication that if one were
to use the simple regression lines in these figures to estimate the full distribution of worker
exposures, that would very likely overestimate the exposures experienced by lower- exposed
workers (below 1 rem per year). To reduce this problem, I have estimated exposures in the below
I rem region by using the steeper lines drawn between the 1 and 2 rem data points. For the region
above 2 rem, I have further pruned the data used by eliminating data points based on fewer than 10
workers in any one year (out of approximately 100,000 per year total monitored).!4

Table 6 summarizes estimates of total collective person-rem delivered for 1965-1992. For
the years 1982-1992 I have taken the collective dose estimates directly from data summarized in

14This does not mean that I have eliminated the exposures accrued by the highest exposed workers. Only that in
determining the overail slope and intercept of the lognormal regression line I have not given equal weight to the
Telatively unreliable data based on very small numbers of workers at the highest end of the distribution of exposures.

15


iS
sl

3.2 Estimates of the Potency of Low Dose Rate Radiation Exposures for
Inducing Cancers of Various Types

A variety of national and international expert committees have used the latest estimates of
dose and cancer incidence for the Japanese atomic bomb survivors and various medical radiation
treatments to arrive at consensus estimates of the potency of different forms of ionizing radiation
for causing different cancers. The results differ somewhat depending on:

¢ Risk modeling approaches-"absolute” vs “relative” risk models;** assumptions about

minimal latency periods for different cancers, and approaches for analyzing the

distribution of cancer occurrence as a function of the age at exposure; and the elapsed
time since exposure occurred.

* Conventions for aggregating cancer sites—for example data can be analyzed as all
digestive system cancers (e.g, BEIR V) or by esophagus, stomach, intestine, colon,
etc,

* The choice of whether to incorporate a “dose and dose rate effectiveness factor”
(DDREF)~a reduction of the potency estimated from studies done after exposure at
high dose rates (e.g., atomic bomb survivors) to reflect a greater efficiency of DNA
repair, etc. when dose is administered over a prolonged period, as is typically expected
for long term cumulative worker exposures. Conventionally, this is given a value of
2, applied uniformly to all sites except those (such has breast) where the primary data
come from populations exposed to relatively low doses or dose rates (acute exposures
below about 10 rem).

Table 10 shows the most recent official EPA conclusions for ionizing radiation cancer
potencies for exposure of the general population at low dose rates.25 The EPA mortality estimates
were derived by taking the geometric mean of potency estimates from previous ICRP, NIH, and
NRC risk models? applied to a stationary population with 1980 vital statistics, and then applying a
downward adjustment of two-fold for sites other than the breast. The morbidity estimates
(numbers of cases, rather than deaths) were derived by dividing the mortality rates by the lethality
fractions shown in Table 11 for various sites. For background, Table 12 compares the indicated
distribution of radiogenic cancers among cancer sites with the general population distribution of
cancer morbidity and mortality among sites.27

24 absolute risk models analyze results in terms of the raw numbers of excess cancers that occur as a function of
exposure level; relative risk models analyze the multiplicative increase in some baseline risk as a function of
exposure.

25Puskin, J. S., and Nelson, C. B, "Estimates of Radiogenic Cancer Risks” Health Physics 69:93-101 (July, 1995).
26National Institutes of Health, “Report of the National Instinutes of Health Ad Hoc Working Group to Develop
Radicepidemiolgical Tables.” Washington. D.C.: U.S. Government Printing Office; NIH Publication 85-2748:,
(1995); International Commission on Radiological Protection, 1990. “Recommendations of the International
Commission on Radiological Protection.” Oxford: Pergamon Press; ICRP Publication 60; Ann. ICRP 21 (1991).
27The general population mortality data for various sites are from 1990 and 1991 U.S. vital statistics compilations.
Morbidity estimates are for 1995 from the American Cancer Society, “Cancer Facts and Figures~1995”, American
Cancer Society, Inc., Atlanta, 1995.


uw
Nn:

In my opinion a prudent policy planner will want to consider these estimates as the lower
bounds of an approximately 2-3 fold credible central range of likely overall cancer risk (250-500
cancer deaths; 360-1000 total cancer cases). This is because:

* With the possible exception of tritium exposures, long term exposures from absorbed
radionuclides appear to be reflected incompletely in the past records of “penetrating”
doses. DOE policies appear to have been changed to require reporting of “total
effective dose equivalents” (including an estimate of internal dose for the current year)
only since 1990. Most recently, the reporting definition has been changed again to
“committed effective dose equivalents” which evidently include an estimate of the total
dose that is expected to be delivered to workers over the next 50 years (if they survive)
from radionuclide dosage absorbed in the current year. The pre-1990 data which
comprise the great bulk of the cumulative dose delivered to workers, do not reflect
these expanded definitions.

* Older methods of measuring even the penetrating dose were not sensitive to some
forms of radiation (e.g., neutrons before 1972; low energy gamma radiation before
1957 at Hanford), although measurement of the predominant form of ionizing
radiation—high energy gamma~was evidently fairly complete.3! Additionally, the
monitoring was done primarily for compliance purposes and some workers who were
thought to have relatively small exposures were not monitored. A study of 1943-1956
measurements of external dosage at Oak Ridge National Laboratory resulted in a 50%
upward adjustment in the estimate of total collective dose for over 7000 workers at that
facility during that time period (from a mean of 1.08 to 1.63 rem/worker). A similar
analysis of dosage for nearly 8500 workers at the nearby Y-12 facility from 1947-
1960 led to an overall 80% upward revision of their collective dose (from a mean of
0.5 to 0.9 rem/worker).32 On the other hand, a paper in press by Gilbert et al.33
points out that total penetrating dose as reported may tend to overstate the dosage
delivered to various organs, depending on the geometry of the placement of the
dosimeter and other factors. The overall upward bias was estimated at 1-27% for
“deep dose”, 41-75% for red bone marrow dose, and 6-33% for lung dose in various
time periods between 1944 and 1989.

* — Classical epidemiological methods have a bias toward underestimation of the slopes of
dose response relationships where there is uncertainty in the estimation of individual
dose.3435_ If estimates of these uncertainties are made, it is possible to correct for this
bias, but such corrections are very unusual in epidemiology, and the international
consensus estimates of radiation potency do not include an allowance for this effect36

Gilbert, E. S., and Fix, J.J. “Accounting for Bias in Dose Estimates in Analyses of Data from Nuclear Worker
Mortality Studies.” Health Physics 68: 650-660 (1995).

32Warkins, J. P., Cragle, D. L., Frome. E. L., West. C. M., Crawford-Brown, D. J., and Tankersiey, W. G.
“Adjusting External Doses from the ORNL and Y-12 Facilities for the Oak Ridge Nuclear Facilities Mortality
Study,” Oak Ridge Instirute for Science and Education, Report No. ORISE 94/G-34, 1994,

33Gilbert, E. S., Fix, J. J., and Baumgarmer, W. V. “An Approach to Evaluating Bias and Uncertainty in Estimates
of External Dose from Personal Dosimeters” Health Physics, 1995 in press.

34Copeland, KT., Checkoway, H., McMichael, A. J., and Holbrook. R. H. “Bias due to misclassification in the
estimation of relative risk. Akm . J. Epidemiol, 105:488-495 (1987).

35Shy, C. M., Kleinbaum, D. G., and Morgenstern, H. “The effect of misclassification of exposure stamus in
epidemiological studies of air pollution health effects. Bull. N.Y. Acad Med. 54:1155-1165 (1978).

38 Additionally, there is some suggestion in the literarure that the epidemiological results may tend to become more
Positive as additional time passes and longer lag periods are allowed in epidemiological analyses of relative risks.


Table 10
Official EPA Estimates of Low Dose Rate Cancer Risks for Ionizing Radiation
Exposure to the General Population (Puskin and Nelson, 1995)

Mortality (10+ Morbidity (10+ % Radiogenic % Radiogenic

per Gy) per Gy) Ca Deaths Cancer Cases
Colon/Intestine 98.2 178.5 19.3 23.5
Lung 71.6 75.4 14.1 9.9
Leukemia (Acute and Non-Lymphocytic— - 49.6 50.1 9.7 6.6
approx. 2/3 of all leukemias) .
Breast 46.2 92.5 9.1 12.2
Stomach 44.4 49.3 8.7 6.5
Bladder 24.9 49.7 4.9 6.5
Ovary 16.6 23.7 3.3 3.1
Liver 15.0 15.8 2.9 2.1
Esophagus 9.0 9.5 1.8 12
Kidney 3.5 8.4 Ll : Ll
Thyroid 3.2 32.1 0.6 4.2
Skin (presumably based on fatal cancers only, 1.0 10 0.2 0.1
overall morbidity for nonfatal cancers would
be about 500 times greater)
Bone 0.9 13 0.2 0.2 7
Remainder 123.1 173.4 24.2 22.8
Toul , 509.1* 760.6" 100.0 100.0

* These overail estimates are for the general population (all ages included). For occupational exposures (assumed to
be delivered at a uniform rate between age 18 and 65 years) the mortality and morbidity incidence rates are given as
394 and 567 X 10+. per Gray respectiveiy.


” Table 25, Continued
Frequency of Deletions and Other Selected Mutation Types Observed in P53
Genes in Human Cancers and Cell Lines Derived from Human Cancers

Type ofTumor % of Tumors with Number of % Deletions % Deletions + % CpG
P53 Mutations Mutations Studied Insertions Transitions
All Other 1028 8.7 11.7 25.3
Tumors
All Nervous 170 8.8 12.9 33.9
System
Brain astrocytoma 25 (all brain) 53 9.4 15.1 37.7
Brain—glial cell 25 (all brain) 96 8.3 115 37.5
(glioma,
glioblastoma)
Brain—other or not 25 (all brain) 17 11.8 11.8 29.4
stated
Neuroblastoma 1 3 0.0 0.0 0.0
Neuroepithelioma 1 0.0 100.0 0.0
All Female 257 8.9 10.5 26.8
Reproductive
System (Except
Breast)
Cervix 7 25 12.0 12.0 28.0
Ovary 44 170 . 8.2 9+ 23.5
Uterine 56 10.7 14.3 37.5
Vulva 6 0.0 0.0 16.7
All Sarcomas 31 90 10.0 14.4 24.4
Chondrosarcoma 2 0.0 0.0 50.0
Leiomyosarcoma 2 0.0 0.0 50.0
Ewing's Sarcoma 21 9.5 14.3 23.8
Liposarcoma 4 0.0 0.0 0.0
Sarcoma—MFH 5 0.0 0.0 40.0
NFS 1 0.0 0.0 100.0
Osteosarcoma oo 33 15.2 24.2 18.2
Rhabdosarcoma 3 33.3 33.3 0.0
Soft tissue sarcoma 1 0.0 0.0 0.0
Sarcoma—nos 18 5.6 5.6 33.3
All Skin 44 123 4.9 8.1 24.4
Basal 55 18 7.3 27.3
Bowens 8 0.0 0.0 12.5
Melanoma 9 6 0.0 0.0 16.7
Squamous Cell 17 11.8 1L.8 3.9
Carcinoma
Xeroderma 27 00 |. 3.7 40.7
Pigmentosum

Skin, NOS 10 30.0 30.0 10.0


Table 29, Continued
Percentage of Total Radiogenic Cancer Cases Occurring in Different Time Periods
That Would Be Eligible for Compensation

C. Requirement for 7.5% of the Doubling Dose--% Cases Compensable

Before 1991 1991-2000 2001-2010 2011-2035 oral, All Times
Leukemia 3.41 154 1.40 0.00 6.35
Liver 0.59 0.45 0.41 0.41 1.86
Bladder 1.76 1.35 1.21 1.21 5.53
Ovary 0.13 0.10 0.09 0.09 0.42
Stomach 1.43 1.09 113 1.21 4.86
Kidney 0.20 0.15 0.13 “03 0.61
Colon/Iatestine 1.72 131 1.90 2.16 7.09
Esophagus 0.16 0.12 0.10 0.10 0.48
Breast 0.06 0.05 0.07 0.08 0.27
Remainder 1.32 LOL 0.85 0.86 4.05
Lung 0.31 0.24 0.13 0.05 0.73

Total 11.09 741 7.43 6.31 32.2


Nn:
vn

8.17 These mortality rates were derived from non-smoker data for the mid-1960’s. I chose to
apply non-smoker mortality rates as a very approximate recognition of the fact that worker
populations have lower mortality than the general population.

Given these assumptions, Table 9 shows the expected changes in the “inventory” of
cumulative radiation exposure in surviving current and former workers over time through the year
2025. (The data for 1970 through 1990 in this table reflect the net effects of both accumulation and
loss of exposure with mortality.) It can be seen that as of now (1995) about two thirds of all the
dosage delivered in the 1944-1992 period is expected to occur in the population of surviving
workers. Within 15 years from now (2010), however, only half of that remaining fraction (34%
of the original dose delivered) will still be carried by living people. Ten years after that (2020),
only 16% will remain, and by 2025 only 10% will remain. Clearly any policy measures that are
considered necessary to deal with the effects of these exposures will need to be put into place in the
immediate future in order to be effective.

17Most of the data come originally from Lew, E. A., and Garfinkel, L. “Differences in mortality and longeviry by
sex, smoking habits and health status.” Trans. Soc. Actuaries 39: 107-120 (1987). The data were extended to
additional ages and otherwise adapted in Silver, K., Hattis, D., and Anfield. ML “Methodology for Quantitative
Assessment of Risks From Chronic Respiratory Damage: Lung Function Decline and Associated Mormiiry from
Coal Dust.” M. L T. Center for Technology, Policy and Industrial Development, Report No. CTPID 90-9, (1991).


these individual worker doses indicated by the film badges and pencil monitors
wom by the workers on which the DOE dose records are based, which may partially

explain the contradiction between very low recorded doses and the excess rates of
cancer.

However, despite the intentions of the DOE in regard to providing a fair
program to equitably compensate former workers for radiation caused cancers, the
program as adopted into law will not serve that purpose, and it effectively takes the
possibility of compensation back to the near zero basis that existed before the DOE
initiatives. This is because eligibility for compensation under the new law requires
that the specified cancer be “at least as likely as not” related to the DOE facility
employment, as based upon a radiation dose at the upper 99% confidence interval
of the “probability of causation” in the published radioepidemiological tables. [See
‘sections 3623(b) and 3623(c)(3)(A)]

For the probability of causation (PC) to equal 50% (which supposedly meets
the requirement of “as likely as not”), the dose received by the worker must equal
the doubling dose, which is the dose that just doubles the background risk. Herein
lies the problem. Only a minute fraction of the former workers have total individual
doses, as recorded historically in the DOE database, that would equal or exceed the
doubling dose for any cancer so as to provide a probability of causation equal to
50%, even at the upper end of the confidence interval.

The problem is best illustrated in the attached Table lof Appendix 2 to the
National Economic Council report on which your initiatives were based. This table
shows that out of 2,015,794 worker monitoring yearly totals at the various DOE
sites from 1947 to 1974, only 45 workers were measured as having a dose over 15
rem. Compare this to the over 300 rem doubling dose needed for cancers of the
esophagus, colon, lung, and breast, and the over 100 rem doubling dose needed for
cancers of the bladder, stomach and liver. (Only thyroid and brain cancers would
have a doubling dose threshold low enough to qualify some of the tiny group of 45
workers with doses in the 15+ rem range). This is why a PC of 50%, or more, will
practically never be found. Yet this is what the new law sets forth as the guideline to
determine if the cancers are radiation related.

A comprehensive study of this very same problem was done five years ago
under a DOE contract which clearly establishes that using the doubling dose

Page 2 of 3


Table A4
Overall Estimated Average Working Lifetime Doubling Doses for Mortality By
Cancer Site and Gender

Cancer Site and Gender ° Approximate % Total Approximate Average
Tumors Induced in Each Doubling Dose
Gender
Female breast cancers 4 184
Female respiratory cancer 21 178
Female digestive cancer 47 71
Female leukemia 8 . 69
Female—other tumors 10 463
Total 100
Male respiratory cancer 23 361
Male digestive cancer 44 123
Male leukemia 13 69
Male—other tumors 20 463

Total 100

rem of radiation exposure decline with age (See Tables Al-A2). The third column of Table A4
Provides some crude overall estimates of doubling doses for cancers occurring by age 70, based on
a uniform assumption that mortality rates for all the cancers increase with the fifth power of age,
and an assumption that radiation exposure occurs relatively evenly between ages 25 and 55. The
second column of this same table gives an approximare percentage distribution for ionizing
Tadiation induced cancer mortality by site, based on the relative risk data in Tables Al-A2 and the
1995 estimated relative frequencies of mortality from cancers at various sites.61

‘These estimates would of course require adaptation to the specific exposure patterns
experienced by individual workers. However, the generic estimates in Table 4 indicate that in most
cases, for the more sensitive cancer sites, workers will need to show about 70-120 rem of
accumulated working lifetime exposure in order to satisfy a “more likely than not” test of cancer
Causation. For the cancer sites thar are less sensitive to radiation than average, the requirement will
be for doses in the low hundreds of rem.

5 Americas Cancer Society, “Cancer Facts & Figures~1995” American Cancer Sociery. Inc., Adlanra. GA. 1995. p.

85


Table 20
Percentage of Total Radiogenic Cancer Deaths Occurring in Different Time
Periods That Would Be Eligible for Compensation

A. Requirement for 1 Doubling Dose--% Deaths Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, All Times

Leukemia 0.639 0.301 0.309 0.000 1.25

Liver 0.027 0.020 0.018 0.018 0.083
Bladder 0.014 0.011 0.010 0.011 0.045
Ovary 0.000 0.000 0.000 =. ~—0.000 0.000
Stomach 0.000 0.000 0.000 0.023 0.023
Kidney 0.000 0.000 0.000 0.000 0.000
Colon/Intestine 0.000 0.000 0.000 0.000 0.000
Esophagus 0.000 0.000 0.000 0.000 0.000
Breast 0.000 0.000 0.000 0.000 0.000
Remainder 0.000 0.000 0.000 0.000 0.000
Lung 0.000 0.000” 0.000 0.000 0.000
Total 0.68 0.33 0.34 0.052 1.40

B. Requirement for 1/2 Doubling Dose--% Deaths Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, All Times
Leukemia 1.81 0.855 1.044 0.000 _ 3.71
Liver 0.24 0.187 0.120 0.167 0.72
Bladder 0.17 0.130 0.119 0.110 0.53
Ovary 0.01 0.006 0.007 0.003 0.02
Stomach 0.03 0.026 0.122 0.182 0.36
Kidney 0.00 0.000 0.000 0.000 0.00
Colon/Intestine 0.00 0.000 0.000 0.000 0.00
Esophagus 0.00 0.000 0.000 0.000 0.00
Breast 0.00. 0.000 0.000 0.000 0.00
Remainder 0.00 0.000 0.000 0.000 0.00
Lung 0.00 0.000 0.000 0.000 0.00

Total 2.27 1.20 141 - 0.46 5.35


Overall, radiation exposures are expected to be more potent in inducing cancers in younger
people than in older people. Table 13 shows EPA relative risk coefficients (per Gray) for
exposures in various occupational age ranges for the sites where they have used relative risk
models (for some other sites, absolute risk models were used).

EPA Relative Risk Coefficients2? (Per Gray = 100 Rad) for Exposure at Various

Table 13
Ages
20-29
Esophagus 0.252
Stomach 1.905
Colon 0.281
Liver 1.345
Lung 0.045
Leukemia (Ave 3-20 yrs 3.268
after exposure)
Bladder 1.074
Kidney 0.391
” Residual 0.174

30-39
0.289

1.288
0.428
1.345
0.134

2.341

1.054
0.391

0.175

0.179

1.458

0.964
0.391

0.185

As noted in the foomote to Table 10, the general observation of lower potency at older ages
at exposure for most sites (but not all sites—see, for example, lung) reduces the expected number
of total cancers per unit of low dose occupational exposure, relative to general population
exposure, by about 20% —from about 510 deaths and 760 cases per million person rem for the
general population to 390 deaths and 570 cancer cases per million person rem for workers.30
Combining these overall potency estimates with our earlier overall cumulative dose estimate of
640,000 person-rem, we arrive at an expectation that there will evenmually be about 250 cancer
deaths and 360 total cancer cases (the 250 fatalities plus 100 cancer cases who survive) as the
result of the occupational exposure of DOE and contractor employees to penetrating radiation.

29F or example, exposure of 20-29

year olds to 1 Gray is expected to increase their relative risk (after a 10 year lag)

by 25% for cancer of the esophagus, by 190% over baseline (to nearly 3 times the basal level) for cancer of the
stomach.

30Merler and Upton give similar worker

Tisk estimates of 400 fatal cancers and 480 total cancers per million person-

rem based on reference 28 above (Mettler. F. A., and Upton, A. C. “Medical Effects of Ionizing Radiation” 2nd

Edition,

Philadelphia: W.B. Saunders Company, 1995, p. 85.

31


Table 35
Central Projections of Absolute Numbers of Cases and Deaths That Would Be
Eligible for Compensation Under Different Scenarios

A. Conclusions Based on Total Cancer Cases

Threshold for Compensation 1991-2000 2001-2010 2011-2035 Total 1991+"
(Fraction of a Doubling Dose)
1 2.8 2.8 0.6 6
(1-5-4.2) (1-5-4.2) (0.3-0.9) G-9)
0.5 15 7 7 39
(8-22) (9-25) (4-10) (21-57)
0.2 74 8 63 210
(39-109) (41-114) (33-92) (113-320)
ee 230 230 210 670
(122-340) 123-340) (111-310) (360-990)
0.075 380 370 340 1080
(200-560) (200-540) (178-490) (570-1600)
B. Conclusions Based on Total Cancer Deaths
Threshold for Compensation 1991-2000 2001-2010 2011-2035 Total 1991+"
(Fraction of a Doubling Dose)
I 22 2.2 0.4 5
(1.42.9) (1.4-2.9) (0.2-0.5) G6)
0.5 i 12 4 27
(7-14) (8-16) (3-6) (18-36)
0.2 47 49 35 131
(31-62) (33-65) (24-47) (87-175)
0.1 135 131 lll 380
(90-180) (88-175) (74-147) (250-500)
0.075 210 200 170 590
(143-280) (135-270) (114+-230) (390-780)

* Totals may not add due to rounding.


Table 1
Summary of Collective Dose Reported by Different DOE Field Organizations

Field Organization Total person-rem, 1982-1992 % All DOE person-rem
Albuquerque (Includes Los 8591 13.4
Alamos)

Chicago 4146 6.5
Idaho 3752 5.9
Nevada 216 03
Oak Ridge 3741 5.8
Pittsburgh 1305 2.0
Richland (Includes Hanford) 16636 26.0
Rocky Flats 11089 17.3
San Francisco 1493 2.3
Savannah River 10978 17.2
Schenectady N.R. Office . 2056 3.2
Total 64003 - 100

Source: Table 4.7 of the DOE overall annual radiation report!

For two of the three facilities (Hanford and Savannah River), extensive data were available
from all retirees. For Los Alamos, the data come from a substantial subset of retirees who
participated in a voluntary early retirement program. Table 2 provides an overview of the ages,
and overall dosage recorded in the three data sets. It can be seen that the only important difference
among the groups is that the Los Alamos voluntary early retirees have a greater average age—in
other respects the data appear very comparable to one another.

The same basic consistency among the data sets is seen in the distributional breakout (Table
3 and Figure 1). In Table 3 I have assessed for each facility (1) the percentages of retirees with
Career total doses above each level, and (2) the percentage of the total population dose that was
received by workers above each dose cutoff. Overall, combining all three populations, about two
thirds of the aggregate dosage is carried by workers who received at least 10 rem (100 mSv) (Table

l1 smith et al, cited earlier as note 6.


18

1. Introduction

From the early 1940’s to the present, hundreds of thousands of workers have participated
in national efforts to develop and use nuclear technology for both military and civilian applications
under the supervision of the Department of Energy and its predecessor agencies. This research
explores the scientific bases for estimating the number of workers who are reasonably likely to
have suffered serious adverse health effects as the result of their contributions to these efforts.

Although DOE and its contractors took extensive precautions to minimize worker radiation
exposures, a significant amount of radiation dosage was received by the worker population as a
whole. Current understanding of radiation biology and carcinogenesis indicates that some cancers
have resulted from these exposures, and that additional cancers will continue to occur in the future.
Unfortunately, with the exception of some worker subgroups,! the precise numbers of induced
cancers have generally been difficult to unequivocally measure directly in the population as a
whole? because of (1) the high background of cancers from other sources, (2) the relatively small
proportion of workers exposed at very high dose levels, and (3) other imperfections in long term
occupational epidemiology, such as the relatively short period of follow-up in some cases, the
“healthy worker effect”,? and difficulties in accurate ascertainment of individual occupational
dose.4 :

ILubin, J. H., Boice, J. D. Jr., Edling, C., Hornung, R. W., Howe, G., Kunz, E., Kusiak, R. A., Morrison, H. L,
Radford, E. P., Samet, J. M., Tirmarche, M., Woodward, A., Xiang, Y. S., and Pierce, D. A.

isk: i Lvsi i ies U. S. Department of Health and Human Services,
NIH Publication No. 94-3644 (1994; Frome, E. L., Cragie, D. L., and McLain, R. W. “Poisson Regression
Analysis of the Mortality Among a Cohort of World War If Nuclear Industry Workers,” Radiation Res.: 123:138-
152 (1990); Wilkinson, G. S., Tietjen, G. L., Wiggs, L. D., Galke, W. A. Acquavella, J. F., Reyes, M., Voelz,
G. L., and Waxweiler, R. J., “Mortality Among Plutonium and Other Radiation Workers at a Plutonium ‘Weapons
Facility,” Am. J. Epidemiol. 125:231-250 (1987); Checkoway, H., Pearce, N., Crawford-Brown, D. J, and Cragle,
D. J. “Radiation Doses and Cause-Specific Mortality Among Workers at a Nuclear Materials Fabrication Plant,” Am
J. Epidemiol. 127:255-266 (1988); Wing, S., Shy, C. M., Wood, J. L., Wolf, S., Cragle, D. L., and Frome, E. L.
“Mortality Among Workers at Oak Ridge National Laboratory,” JAMA 265:1397-1402; Alexander, V., “Brain
Tumor Risk Among United States Nuclear Workers,” Occupational Medicine: State of the Art Reviews 6:695-714
(1991), :
2Cardis, E., Gilbert, E. S., Carpenter, L., Howe, G., Kato, L, Armstrong, B. K., Beral, V., Cowper, G., Douglas,
A., Fix, J., Fry, S. A., Kaldor, J., Lave, C., Salmon, L., Smith, P. G., Voelz, G. L., and Wiggs, L. D. “Effects of
Low Doses and Low Dose Rates of External Ionizing Radiation: Cancer Mortality Among Nuclear Industry Workers
in Three Countries,” Radiat. Res. 142:117-132 (1995); Gilbert, E. S., Fry, S. A., Wiggs, L. D., Voelz, G. L.,
Cragle, D. L., and Petersen, G. R. “Analyses of Combined Mortality Data on Workers at the Hanford Site, Oak
Ridge National Laboratory, and Rocky Flats Nuclear Weapons Plant,” Radiat. Res. 120:19-35 (1989); Dupree, E.
A., Watkins, J. P., Ingle, J. N., Wallace, P. W., West, C. M., and Tankersley, W. G. “Uranium Dust Exposure and.
Lung Cancer Risk in Fur Uranioum Processing Operations, Epidemiology 6:370-375 Quly, 1995).
3Steenland, K., and Stayner, L. “The Importance of Employment Status in Occupational Cohort Mortality Studies,”
Epidemiology 2:418-423 (1991). .
4Gilbert, E. S., Fix, J. J., and Baumgartner, W. V. “An Approach to Evaluating Bias and Uncertainty in Estimates
of External Dose Obtained from Personal Dosimeters,” Health Physics, (1995, in press); Gilbert, E. S., and Fix, J.
J, “Accounting for Bias in Dose Estimates in Analyses of Data from Nuclear Worker Mortality Studies,” Health
Physics 68:650-660 (1995); Watkins, J. P., Cragle, D. L., Frome, E. L., West, C. M., Crawford-Brown, D. J., and


Table A3 :
Doubling Doses for Lung Cancer Mortality From Exposure to Radon Progeny;

Excess Relative Implied Doubling
Risk/WLM Dose (WLM)

Overall Risk from Radon Progeny Observed in 11 0.0049 204

Studies

Never-Smokers 00103 97

Smokers 0034 294
Figure Al

B4

The Skewed Shape of a Simulated Lognormal Distribution With An Arithmetic, ~~

Mean of 1, an Arithmetic Standard Deviation of 1, and a Geometric Standard
Deviation of 2.3

15,243 Trials
04 596
“ Median = 0.71

=> .03 447
= Mean = 1 Zz
= A 3
g 02 b298 S
2 Ss
eo 3
= tad
a 01 . 149

00 +! iit wehanig | g

0.00 1.00 2.00 3.00 4.00



Log(rem dose)

Log(rem dose)

Figure 8

1977--Lognormal Plot of Penetrating Ionizing Radiation
Exposures for DOE and Contractor Employees

1.0

0.8 4

064

0.44

024

0.0

= - 0.76600 + 0.40829x R42 =

va

T

3 4 5

1977 Z-Score
Figure 9

0.958

1980--Lognormal Plot of Penetrating Tonizing Radiation
Exposures for DOE and Contractor Employees

0.5

0.44

0.35

0.25

0.14

= - 0.58863 + 0.

3 4

1980 Z-Score

}0813x R*2 = 0.893

13


Table 14
Expected Age Distribution of Background Cancers and Radiation-Induced Cancers
Other Than Leukemia in Various Years

% Total Cancers in Each Age Group
29-39 40-49 50-59 60-69s70-79Ss BS all
Background Cancers 6.0 158 29.9 37.1 9.5 100.0

Radiation-induced cancers in various years

1985 0.2 3.7 15.9 34.1 36.1 9.9 100.0
1990 0.2 2.6 13.7 32.8 38.2 ‘12.5 100.0
1995 0.1 1.8 ILL 313 40.6 15.0 100.0
2000 0.1 13 8.5 29.2 43.3 17.7 100.0
2005 0.0 0.8 6.2 25.8 46.3 20.8 100.0
2010 0.0 0.4 42 20.8 46.9 27.7 100.0
2015 0.0 0.1 2.9 18.0 49.4 29.6 100.0
2020 0.0 0.0 1.6 15.2 48.7 34.4 100.0
2025 0.0 0.0 1.6 12.5 48.3 37.7 100.0

More complex calculations needed to describe the expected time pattern of the leukemias.
Clearly, a larger proportion of the leukemias should be expected to occur sooner after exposure
than will be the case for the other cancers whose expected time pattern is depicted in Figures 17
and 18. For purposes of the potential compensability calculations in Section 4, [have simply
assumed that (1) essentially all the leukerhias that will result from 1944-1992 exposures occur by _
the year 2010, and (2) the leukemias that might otherwised occur after 2010 (under the time pattern
for other cancers) should be added to the calculated number of leukemias that have already occured
prior to 1991.

Thave also not attempted to separately describe in detail the time patterns of expected
morbidity vs mortality from cancers. The mortality curve will of course be shifted a few years into
the funure relative to the morbidity curve. For planning purposes, and to avoid complications
arising from the changing success of cancer treatment in prolonging life, I recommend thar the time
patterns in Figure 17 and 18 be regarded as morbidity (cases) rather than mortality.

uw
a


Table 25
Frequency of Deletions and Other Selected Mutation Types Observed in P53
Genes in Human Cancers and Cell Lines Derived from Human Cancers

Type of Tumor % of Tumors with  Numberof % Deletions % Deletions + % CpG
PS3 Mutations Mutations Studied Insertions Transitions
All Tumors 37 2847 8.2 10.4 24.5
Breast 22 274 14.6 15.0 22.3
Respiratory 401 6.0 7.2 7.5
system
Larynx 26 17 us 17
All Lung Cancer 56 375 5.9 6.9 7.5
All Non-Radon LC 332 50 5.6 8.0
Adenocarcinoma 40 2.5 75 175
Carcinoid 5 0.0 0.0 0.0
Large cell 12 8.3 16.7 0.0
non-SCLC : 98 5.1 5.1 8.2
SCC or Adeno/SCC 55 16.4 18.2 73
SCLC 92 2.2 3.3 9.8
Metastasis 2 0.0 0.0 50.0
Lung not otherwise 2 4.0 4.0 16.0
Specified.
nonsmoker 8 0.0 0.0 12.5
All Radon LC 38 2 13.4 2.6
radon, not otherwise 29 10.3 17.2 3.4
specified
tadon—CIS 1 0.0 0.0 0.0
radon—non SCLC 3 33.3 33.3 0.0
radon--SCC/SCLC 5 20.0 20.0 0.0
All Digestive 855 7.0 8.8 30.2
System
Esophagus 45 98 N2 13.3 19.4
Stomach 41 107 103 15.0 36.4
Hepatocellular 29 240 79 8.3 8.8
carcinoma .
Pancreas 44 64 47 73 28.1
Colon 50 343 47 6.1 46.6
Anal 3 0.0 0.0 33.3


Figure 1

Probability Plots of the Cumulative Dose
Distribution for All Retiring Workers
(ncluding Those with 0 Dose)

Log(Rem Dose)

%
4

= -133+136x R*2=0.986 & Savannah River Retireees 110 S
= -140+136x R°2=0974 ¢ Los Alamos Vol. Early Retirees

y= -219+1.69x R*2=0.972 8 Hanford|Retirees (1/10 Sample)
4 T T 7 T
-1 0 1 2 3 4

Z-Score

4). (Table 4 also incorporates important information on the overall aggregate population dose
likely to be borne by workers and former workers surviving to 1995. I will show the formal
derivation of these estimates in the subsections below).

The aggregate dose is also substantially concentrated among a relatively narrow range of
ages. Figure 2 indicates that two thirds of the dose is bore by workers retiring near the end of
their normal work lives. The workers with substantial dosage are, by and large, not temporary
employees, but people who have worked for many years directly or indirectly on DOE projects.
Figure 3 shows the growth in average rem/person as a function of age at retirement in the Hanford.
retirees.

Table 5 summarizes the Hanford retiree data broken down by the year that employment
ended. These data indicate that relatively large numbers of older workers with substantial dosage
have retired in the most recent year covered (1994).

&


Table 32, Continued
Ratios of Total Compensated Cases/’True” Radiogenic Cancer Cases for Various
Thresholds for Compensation

C. Requirement for 20% of the Doubling Dose
Ratio of Total Compensated/”’True” Radiogenic Cases

Total % Radiogenic Cancers 1991-2000 = 2001-2010 = 2011-2035 = Total, All Times

Compensated 1991+ of ail
Caused by 1944-1992 Exposures

Leukemia 2.491 2977 2.931 2.96
Liver 0.927 3.584 3.584 3.584 3.58
Bladder 2.449 3.926 3.973 3.922 3.94
Ovary 0.139 4375 4.327 4.239 431
Stomach L727 4583 «4.257 3.878 4.14
Kidney 0.078 4.781 4.781 4.781 4.18
Colon/Intestine 0.540 5.486 5.235 5.131 5.21
Esophagus : 0.033 5.181 5.195 5.247 5.20
Breast 0.012 5.212 5.256 5.24
Remainder 0.000

Lung 0.000

Total 3.40 3.60 3.69 4.04 3.15

D. Requirement for 10% of the Doubling Dose
Ratio of Total Compensated/"True” Radiogenic Cases

Total % Radiogenic Cancers 1991-2000 2001-2010 = 2011-2035 = Toral. All Times
Compensated 1991+ of all

Caused by 1944-1992 Exposures
Leukemia 2.831 3.825 3.624 3.73
Liver 1.192 4.635 4.635 4.635 4.64
Bladder 3.509 5.108 5.061 4.991 5.06
Ovary ” 0.254 6.012 5.862 5.794 5.89
Stomach 3.062 6.606 5.822 4.987 5.75
Kidney 294 1.528 7528 7528 7.53
Colon/Intestine 3.156 8.231 8.176 8.013 8.12
Esophagus 0.190 8.041 8.034 8.168 8.08
Breast 0.115 8.638 7.937 8.183 21
Remainder 1.630 8.754 8.869 . 8.863 8.82
Lung 0.128 9.467 561 9.49

Total 16.36 5.91 5.90 6.37 6.04


Figure ES-3

Age Distribution of % Total Cumulative Dosage
Delivered to Hanford Workers, 1944-1989

3
a
Ss 24
a
3
3
e
S
Ss 14

0 T T 7 T T

10 20 30 40 50 60 70
Age
Table ES-2

Expected Changes in the “Inventory” of Collective Radiation Dosage in Surviving
Workers, 1970-2025

Dose Surviving to Year % Dose Surviving -
Total Delivered 1944-1992 640,000 100
1970 400,000 @
1975 ; 460,000 R
1980 00,000 8
1985 500,000 B
1990 480,000 15
1995 420,000 66
2000 360,000 56
2005 290,000 45
2010 220,000 34
2015 160,000 - 4
2020 100,000 16

2025 63,000 10


Table 25, Continued
Frequency of Deletions and Other Selected Mutation Types Observed in P53
Genes in Human Cancers and Cell Lines Derived from Human Cancers

Type of Tumor %ofTumorswith  Numberof % Deletions % Deletions + % CoG
P53 Mutations Mutations Studied Insertions Transitions
All Leukemia/ 12 289 7.3 11.1 30.8
Lymphoma
Leukemias and 167 9.0 14.4 29.3
Related
Neoplasms
ALCL 1 0.0 0.0 0.0
ALL 24 83 16.7 33.3
B-ALL 7 28.6 28.6 57.1
pre-B 3 0.0 0.0 0.0
B-CLL 16 0.0 . 18.8 12.5
T-ALL 2 0.0 0.0 0.0
T-leukemia 1 0.0 0.0 0.0
T-lymphoma 2 0.0 0.0 50.0
TFL 10 20.0 20.0 20.0
CML 23 8.7 13.0 26.1
CTCL I 0.0 0.0 100.0
PTCL 1 0.0 0.0 0.0
Richter . 3 0.0 0.0 33.3
Eryth 1 0.0 0.0 0.0
FL 3 0.0 0.0 0.0
HCL 1 0.0 100.0 0.0
Myeloid + 18 222 22.2 2.2
myeloprolif
AML 2 45 9.1 40.9
ATL 15 13.3 13.3 40.0
Lymphoid 1 0.0 0.0 100.0
MDS 12 0.0 8.3 33.3
Other Blood and 122 4.9 6.6 32.8
Lymph Tissues
B-Lymphoma 18 1L1 ILL 222
Burkic's Sl 78 9.8 37.3
Lymphoma
Hodgkin's 5 0.0 0.0 40.0
Non-Hodgkins’ 2 0.0 0.0 40.9
Lymphoma
Multiple Myeloma 9 8 0.0 0.0 25.0

Not specified 18 0.0 5.6 22.2


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60

* the distributions of radiation dosage among DOE and contractor workers previously
developed in Section 2 (this includes an allocation of 95% of all dosage to male
employees)

* the doubling doses given in Tables 17 and 18, and

Based on these assumptions, Tables 27 and 28 describe the approximate percentages of
radiation-induced tumors of various kinds that might be able to satisfy a “more likely than not”
criterion of causation, with and without the aid of P53 sequence analyses, based on
deletion/insertion findings. Table 27, in parallel with Table 19A assumes a five-fold effective
reduction in doubling dose from the original EPA doubling dose estimates (incorporating the
DDREF of 2). Table 28 assumes that the 5-fold reduction in doubling dose occurs in combination
with elimination of the DDREF—meaning that the calculations for qualifying tumors in this table are. =
based on a 10-fold reduction in doubling doses from their original values in Tables 17 and 18. .

In order for P53 sequence analysis to push a particular case beyond the preponderance-of- °
evidence threshold, the mmor must:

A) Occur in a person who is between the original doubling dose for the tumor (column 3)

and the revised doubling dose for tumors bearing p53 deletions or insertions (column

4). The expected percentage of each type of radiation induced tumor occurring in this
dose interval is the difference between columns 5 and 6.

B) Carry a p53 mutation (column 7) (The p53 analysis is potentially more helpful for
cancers other than leukemias in part because leukemias rarely carry p53 mutations.)

©) Cary a deletion mutation in p53 (column 9) given the assumed 5 X multiplicative
enrichment of deletions in radiation-induced mutations (limited of course, by the upper
bound of 100%).

As deduced earlier, the bottom lines of column 11 in these tables indicate that only
approximately 1%-4% of the total radiation induced tumors might be compensable under a
preponderance of evidence test without any p53 sequence analysis (with the 4% figure derived
from the elimination of the DDREF in Table 28). With the same baseline assumptions, if there is a
5 fold enrichment of deletion and insertion p53 mutations in radiation-induced tumors, then an
additional 1.6-3.4% of the total radiation-induced tumors might be able to pass the preponderance
of evidence threshold with the p53 sequence analysis. Based on our earlier estimare that a toral of
about 360-1000 extra cancers might have been initiated in DOE and contractor employees by
exposures over the 1944-92 period, then the number of potential beneficiaries from the ps3
technology in this group might be approximarely 5-30, spread out over the next couple of decades.

A further factor that is not included in these calculations is the issue of background
tadiation exposure. Tests such as those described above have some modest promise for
distinguishing radiation-induced mutations from other mutations, but there is little hope of


Table 31
Probability of Causation and Ratio of Total Cases/’True” Radiation-Induced
Cases at Various Fractions of a Doubling Dose

Fraction of Doubling Dose Probability of Causation _Ratio of total cases/true positive cases
2 =

0.667 ‘1.500
1.95 0.661 1513
19 0.655 1.526
1.85 0.649 1541
L8 0.643 1.556
1.75 0.636 1571
7 0.630 1.588
1.65 0.623 1.606
. 16 0.615 1.625
1.55 0.608 1.645
15 0.600 1.667
1.45 0.592 1.690
1.4 0.583 L714
1.35 0.574 L741
13 0.565 1.769
125° 0.556 1.800
1.2 0.545 1.833
11s 0.535 1.870
Ld 0.524 1.909
1.05 0.512 1.952
I 0.500 2.000
0.95 0.487 2.053
0.9 0.474 2
0.85 0.459 2.176
0.8 0.444 2.250
0.75 0.429 2333
0.7 0.412 2.429
0.65 0.394 2538
0.6 0.375 2.667
0.55 0.355 2.818
0.5 0.333 3.000
0.45 ‘0310 3.222
0.4 0.286 3.500
0.35 0.259 3.857
0.3 0.231 4.333
0.25 0.200 5.000
0.2 0.167 6.000
0.15 0.130 7.667
0.1 0.091 11.000
0.075 0.070 14.333

0.05 0.048 21.000


Table 15
Doubling Doses for Selected Cancer Sites for Low Dose Rate Ionizing Radiation
Exposure, Calculated From EPA Age Specific Risk Coefficients Incorporating a
Dose and Dose Rate Effectiveness Factor of 2

Males Risk Coefficients by Age Group (1/Gy) Resulting Doubling Doses (rem) by
Age Group

20-29 30-39 40+ 20-29 30-39 40+
Esophagus 0.2517 0.2892 0.3258 397 346 307
Stomach 1.9051 0.2881 0.2524 52 347 396
Coion 0.2809 0.4275 0.0899 356 24 1112
Liver 1.3449 1.3449 1.3449 14 74 74
Lung 0.0453 0.1342 0.1794. 2208 745 557
Leukemia (Ave 3- 3.2681 2.3407 * 1.4575 31 3 6
20 yrs after
exposure)
Bladder 1.0736 1.0544 0.9639 93 95 104
Kidney 0.3911 0.3911 0.3911 256 256 256

Residual 0.1735 0.1754 0.1847 376 570 S41


35

Figure 16

Power-Law Increase in Cancer Incidence With Age (Based
on Morbidity Data for Larynx, Liver, Kidney, Bladder, and Lung)

, .
= -7.16+4.13x R*2 = 0.982

Log(Relative Cancer
Incidence, 5 Sites)

T 7
1.30°°14 #15 1.6 #47 #18 1.9 2.0
log(Age)

been received at least 10 years previously. For each year of the age distribution I then multiplied
the total surviving 10-year old dose by the baseline cancer risk to arrive at an index of the number
of cancers that would be expected to occur in that year to workers of that age. Figure 17 presents
the resulting time pattern of overall cancers (other than leukemia) expected to result from dosage
delivered to DOE workers between 1944 and 1992; Figure 18 presents the same data projected in
the form of a cumulative distribution for cancers occurring between 1965 and 2030. The peak year
for the radiogenic cancers other than leukemia appears to be about 1995 or the next couple of years
in the future. About 32% of the total cancers are expected to have occurred prior to 1990; about
44% will have occurred by the end of 1995; and two thirds are expected to happen by 2005.
Table 14 shows the expected age distribution of the non-leukemia cancers occurring in
different years. The aging of the workers leads to a progressive increase in the age distribution of
the people expected to develop the radiogenic cancers.


% True Positive Cases Comp

100

104

a

T T
0.05 0.15 0.25 0.35 0.450.55 0.65 0.75 0.85 0.95

Figure ES-7

Tradeoff Between Compensating True
Radiogenic Cancers and Equalizing the
Cases Compensated to Cases Caused

—t— % True Positive Cases Comp
——*— ‘Cases Comp/Cases Caused

At .1 doubling dose, cases
J compensated are about equal

J to cases caused, although only
3 1/6 of true cases are compensated.

7

Under current policy,
total compensation is
about 1% of cases caused.

T T T T T T T

10-

Ot

001

Fraction of the Doubling Dose for Compensation

Cases Compensated/Cases Caused

14


be seen, however, there is considerable remaining uncertainty about appropriate low dose slopes
for the dose response relationships for specific cancers in relation to specific types of radiation).

The last two decades have seen important advances in our understanding of the
fundamental mechanisms of carcinogenesis. We can now be very confident that with few known
exceptions, tumors arise as a result of a series of changes or rearrangements of information coded
in DNA within single cells or cell lines?!, These changes can be induced either by DNA-reactive
chemicals, radiation, some viruses, or the free-radical byproducts of the normal use of oxygen in
the body. With the identification of “oncogenes,” and tumor suppressor genes, we are now getting
some detailed molecular characterization of what some of the resulting DNA changes are.

The fundamental multiple mutation mechanism of radiation-induced carcinogenesis has
strong implications for the likely relationship between delivered dose and incremental cancer risk.
Basically, all pharmacokinetic process, such as DNA repair, must proceed linearly at relatively low
dose rates where there is negligible saturation of the enzymes involved. Because of this, and
because the mutations induced by radiation add to other mutations that cause an appreciable
“background” cancer risk in the exposed human population, the basic expectation is that
incremental risk is a linear function of dose at low dose rates—although in some cases changes in
the efficiency of DNA repair and other processes at higher dose rates may yield an steeper increase
in risk as a function of dose at those higher dose rates.

21Vogel, F. and A. G. Motulsky (1979) Human Generics--Problems and Approaches Springer-Verlag, New York.
pp. 326-329; Fialkow, P. J. (1977) "Clonal origin and stem ceil evolution of human tumors,” In Genetics of
Human Cancer (Mulvihill, J.J., et al., eds.) 439. Raven, New York; Knudson, A. G. (1973) “Mutation and Human
Cancer,” Adv. Cancer Res. 17, 317-352; Knudson, A. G. (1977). "Genetics and Etiology of Human Cancer,” Adv.
Hum. Genet. 8, 1-66.

22Weinberg, R. A. “The molecular basis of oncogenes and tumor suppressor genes.” Ann N Y Acad Sci 758:331-
338 (1995); Weinberg, R. A. “Oncogenes and tumor suppressor genes.” CA Cancer J Clin 44: 160-170 (1994);
Yunis, J. J. (1983) "The chromosomal basis of human neoplasia,” Science 221, 227-236; Hoel, D. G. (1985)
“Epidemiology and the Inference of Cancer Mechanisms. Natl. Cancer Inst. Monogr. 67, 199-203; Fischinger P. J..
and V. T. DeVita, Jr. (1984), "Governance of science at the National Cancer Instimte: Perceptions and opportunities
in oncogene research,” Cancer Res 44, 4693-4696; Modali, R., and S. S. Yang, (1986), "Specificity of Aflatoxin B1
Banding on Human Proto-Oncogene Nucleotide Sequence.” In Monitoring of Occupational Genoroxicants Alan R.
Liss, Inc.

23 The basic reason for this is that at low doses the rates of the transport and transformation Processes that lead to
DNA damage and repair directly depend on the number of collisions between molecules of an “input” chemical (or
activated intermediate or DNA adduct) and a resident cellular reactant (or hole in a membrane or repair enzyme
molecule). At low doses the number of resident cellular reactant molecules does not change appreciably as a function
of the concentration of the “input”. Therefore the number of relevant collisions and the rates of the reactions and side
Teactions in the causal sequence at low dosage must be direct linear functions of the amounts of input chemical and
its activated derivatives. Some finite fraction of the ultimate DNA lesions must escape repair before the next ceil
teplication so long as the cells affected have a non-zero turnover rate, there are a finice number of repair enzyme
molecules, and the repair molecules operate at a finite rate. (Hanis. D_. "Pharmacokinetic Principles for Dose Rare
Extrapolation of Carcinogenic Risk from Genetically Active Agents.” Risk Anaivsis, Vol. 10. pp. 303-316, 1990.]


Table 12 .
Comparison of the Distribution of Cancer Mortality and Morbidity Among Sites
for Radiogenic ys General U.S. “Background” Cancers

Estimated Total Estimated Total Estimated %  % Radiogenic
U.S. Deaths, U.S. Cases, U.S. Deaths Ca Deaths

1995 199 from All Causes

Colon/Intestine 56420 142800 2.58 19.3
Lung 157400 169900 7.19 141
Leukemia (Acute and Non-Lymphocytic— 12445 12571 0.57 9.7
approx. 2/3 of all leukemias)

Breast 46240 183400 211 9.1
Stomach 14700 22800 0.67 8.7
Bladder 11200 50500 0.51 49
Ovary 14500 26600 0.66 3.3
Liver 14200 18500 0.65 29
Esophagus 10900 12100 0.50 18
Kidney 11700 28800 0.53 Ld
Thyroid 1120 13900 0.05 0.6
Skin 6420 Not estimated 0.29 02
Bone 1280 2070 0.06 . 02
Remainder 188475 568059 8.61 24.2

Total 547000 1252000 25.00 100.0


"59

Table 26
Enrichment of Insertions and Deletions in Radon-Associated Lung Cancers

A. Analysis Based on All Studied P53 Mutations

Agent Deletions Insertions Total Relative ~—=Relative
Mutations Enrichment Enrichment of
of Deletions Deletions +
Insertions
1.0 1.0
Non-Radon Lung 17 (5%) 2 (0.6%) 337 (defined) (defined)
Cancers
Radon-Associated Lung. 5 (13%) 2 (5%) 38 2.6 3.3
Cancers

B. Analysis After Excluding Radon-Specific Codon 249 Transversions

Agent Deletions Insertions Total Relative Relative
Mutations Enrichment Enrichment of
of Deletions Deletions +

Insertions
1.0 1.0
Non-Radon Lung 17 (58%) 2 (0.6%) 336 (defined) (defined)
Cancers
Radon-Associated Lung 5 (23%) 2 (9%) 22 4.5 5.6
Cancers

lung cancers. If the lung cancers with radon-specific transversions are excluded from both the
radon and non-radon groups (Table 26B), the apparent enrichment is increased to about 5-fold.
Because of the small sample size of radon-associated lung cancers studied, these estimates
of deletion/insertion enrichment carry considerable uncertainty. This uncertainty is likely to be
reduced in the future, however, as additional data become available. For our purposes here, they
at least allow some tentative calculations of how many workers’ compensation cases for different

radiation-induced tumors might be improved by examining their tumor p53 sequences for
insertions or deletions. To do this I assume:

* A maximum five-fold effective reduction in the doubling dose for deletions and
insertions for all tumors and all types of ionizing radiation,

° No difference in the frequency of p53 mutations for radiation-induced tumors
compared to the “background” tumors described in the p53 database (Table 25),


Figure ES-4

>. Projected: Relative Rate of Oceurrénce (1995 = 1) ~~
. .-of Radiogenic Cancer Cases (Except Leukemia)...
, Induced in DOE _Employees--1944-1992, Exposures ©

12
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- .
We. tog.
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. wo Oba: -
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&
7
oO. 024
0.0 T T T TT T
1965 1975 1985 1995 2005 2015 2025 2035
Year °
* Figure ES-5 . . me oa nn.

- +. °° Cumulative: % of. All Radiogenic Cancers Except
o Leukemia Expected to’Occur in Various Years

100

~~
= 9;
cy
| 80-4
2 70 -+
e
< . 604
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q
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T T T t
1965 1975 1985 1995 2005 2015 2025 2035
: Year


34

Figure 15

Overall Time Since Exposure Relationship
--Relative Risk for Chronic Granulocytic
Leukemia + Acute Leukemia

5
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Years After Exposure

from age-specific cancer data for males?” for 5 sites (Figure 16). With the exception of very
young and very old ages, these cancers on average increase with about the fourth power of age.
(in the framework of multistage cancer modeling, this would be compatible with a typical 5-stage
mutation process from normal stem cells through fully developed tumors).

Every 5 years beginning with 1970, I then used the age-at-exposure vs year of exposure
matrices developed in Section 2 to calculate the age distribution of the surviving dosage that had

37 Male data were used because 95% of the total radiation dosage was received by male workers. The sources of the
data were:

Lung (never-smokers only)}—Garfinkel. L. "Time Trends in Lung Cancer Mortalicy Among Nonsmokers and a Note
on Passive Smoking.” JNCI 66:1061-1066 (1981).

Larynx (from the Third National Cancer Survey, All Areas Combined, 1969-71) Austin. D. F. “Larynx” in Cancer
Epidemiology and Prevention, D. Schottenfeld and J. E. Fraumeni, eds., W. B. Saunders Co., Philadelphia. 1982. p.
557.

Liver (from the Third National Cancer Survey, All Areas Combined, 1969-71) Falk, H. “Liver” in Cancer
Epidemioloey and Prevention, D. Schottenfeld and J. E. Fraumeni, eds.. W. B. Saunders Co., Philadelphia. 1982. p.
670.

Bladder and Kidney (from the Third National Cancer Survey, All Areas Combined. 1969-71) Austin, D. F. “Urinary

Tract” in Cancer Epidemiotogy and Prevention, D. Schouenfeld and J. E. Fraumeni. eds., W. B. Saunders Co..
Philadelphia, 1982. p. 926.


ACKNOWLEDGMENT

This research was commissioned by Ashford Associates, Cambridge MA under a contract with
COMPA Industries, Inc. (Ref: DE-AC01-94EH89501) which in turn is under contract to the U.S.
Department of Energy.


31

Table 21
Frequency of the Putative Radon-Related P53 Mutations as a Function of
Estimated Radon Doses

Number of P53. Number of Codon 249% of Mutant P53s
DoseRange(WLM) Mutants Studied © AGG to ATG Changes with Codon 249 AGG

Found to ATG
0-52 (including 6 8 1 12
controls)
100 to 1000 9 5 56
1000 to 2000 8 5 6&2
2000+ 9 5 36

transformation; possibly in part due to competing risks from other causes in the highest exposure
groups and in part due to notorious inaccuracies in the individual worker dosimetry in this study.)

‘The take-home lesson from this example therefore is that there is some promise that some
radiation-induced mutations will be found to be very much more frequent in groups exposed to
specific kinds/sources of radiation than in background tumors related to other environmental
factors. For the workers whose cancers bear such mutations, there is a reasonable long term hope
that this kind of information could dramatically increase the assessed probability that their cancer
was caused by their radiation exposure. The radon information even in its present state of
development is probably sufficient to sustain more-likely-than-not determinations. However the
vagaries of the available information are such that even in this best case (radon, in the light of the
Taylor et al. study) there is room for some doubt that the basic relationship will be eventually
validated in further studies. And finding other examples of radiation “hot spots” in the P53 gene
and other cancer-related genes will require a sustained molecular epidemiological effort with only a
modest prospect of short term benefit for the workers whose tumors are studied. The section
immediately following outlines the mathematical theory thar can be used to adjust probability-of-
Causation estimates in the light of information on the preferential causation of some types of
mutations by specific kinds of ionizing radiation.

Theory

Imagine that in unexposed people, the lifetime risk of a particular cancer is Rp, and the
Proportion of those cancers with P53 mutations of a particular type is Ph. Now suppose that large


Table 2

Overall Summary Statistics for the Data on Cumulative Career Total Exposures
for 1990-1994 Retirees from Savannah River, Los Alamos, and Hanford

Ave age Total person-rem Ave rem/person with
non-zero dose

Savannah River 40.9 12,202 2.24

Los Alamos 57.6 1,104 2.19
Volunaary Early

Retirees

Hanford 38.6 10,964 2.25

Total 40.3 24,271 224

Table 3

Total number Number with any

of retirees non-zero dose
7,333 5,444
830 505
10,709 4,883
18,872 10,832

Distributions of Cumulative Radiation Exposures Among 1990-1994 Retirees
from Savannah River, Los Alamos, and Hanford

Hanford Retirees Los Alamos Voluntary Savannah River Retirees
Early Retirees

rem/person| % People with % Aggregate | % People with  % Aggregate % People with  % Aggregate

any dose over Dose over this| any dose over Dose over this |any dose over this Dose over this
this dose dose this dose. dose. dose dose
1 25.66 94.63 28.62 93.20 22.78 94.00
2 18.39 89.88 18.73 86.64 16.39 89.95
5 9.95 78.14 11.21 76.60 10.29 81.23
75 7.33 71.04 7.72 66.71 8.38 76.03
10 5.98 65.79 634 61.23 7.04 70.92
15 4.03 55.12 3.76 45.91 5.00 59.66
20 2.91 46.57 1,98 31.97 3.55, 48.52
30 1.52 31.46 0.79 19.73 L41 25.10
40 0.74 19.63 0.79 19.73 0.35 8.80
60 0.35. 10.90 0.20 6.44 0.07 3.14
80 0.06 2.43 0.00” 0.00 0.02 1.45
100 0.00. 0.00 0.00 0.00 0,02 1.45



frequently methylated. Therefore the proportion of such transitions at CpG
dinucleotides is taken as a marker for the relative contribution of spontaneous
deamination to the cancers of particular kinds.

* Other types of transitions (not at CpG dinucleotides) tend to result from small DNA
adducts-—especially methyl groups at the 06 position of guanine, which often give rise
to mistakes in pairing.

* — By contrast, bulky adducts~such as those derived from polycyclic aromatic
hydrocarbons, other carcinogens in cigarette smoke [the tobacco-specific nitrosamine,
4-(methylnitrosamino)- 1-(3-pyridyl)-1-butanone], and aflatoxin—zend to give rise to
Wansversions. The explanation for this is that these bulky adducts tend to block
passage of the normal copying enzyme, and when this happens adenine is
preferentially inserted into the complementary DNA strand. When this happens
opposite a guanine (guanine is most frequently modified by bulky adducts in this
way), a G:C to T:A transversion results.

* Ultraviolet light tends to join together two adjacent thymidine bases, causing CC to TT
tandem transitions.

* Ionizing radiation gives rise to unusual recombination events (both within and between
DNA strands) and tends to be associated with an increased frequency of deletions and
other large chromosomal changes. The degree of enrichment of deletions will be
assessed as part of the quantitative analysis below. Otherwise, deletions and
insertions are associated mechanistically with slippage of the DNA copying enzymes
and mistaken within-strand pairing at repetitive sequences in the DNA.

Beyond these relatively well understood mechanisms that tend to give rise to different
Proportions of mutations within the broad families of DNA changes, there is a more mysterious
and occasionally spectacular concentration of mutations induced by specific agents at particular
places, “hotspots,” in the DNA Sequence. “Hotspots” have been repeatedly observed ever since
the first detailed genetic maps of mutation frequencies were made based on observations in
bacterial viruses.

In the context of radiation, an extreme case of a hotspot has been reported by a single group
of investigators in a group of Colorado Plateau uranium miners exposed to large amounts of radon
(and possibly other agents). Taylor et al.50 studied the P53 sequence in the lung tumors of 52
miners who developed large-cell or Squamous-cell cancers. 29 miners (56%) were found to have a
mutation in their P53 protein, and of those, 16 (55%) were identical Gto T transversions at the
second base of codon 249. G to T transversions in general are not uncommon in other lung
cancers, but out of 337 lung cancer cases not associated with radon in an updated version of a P53
mutation data base, there was only one other case of aG to T transversion at this specific place in

then the mutation is a “frameshift” mutation because the 3-base reading frame of the DNA code has been disrupted
and all amino acids coded for by DNA translated after the point of the mutation will geaerally be changed.
S0Taylor, J. A., Watson. M. A., Devereux, T. R. Michels. R. ¥.. Saccomanno, G., and <inderson. M. “P53
Mutation Hotspot in Radon-Associated Lung Cancer.” Lancet, Vol. 343, pp. 86-87 (199-4),

49


all dosage derived in Table 16. Finally, Table 18 analyzes the cumulative total cancer deaths anid
cancer cases in order of increasing 1995 doubling dose. This table will be the starting point for our
analysis of the consequences of the current compensation system, and possible alternatives. Itcan
be seen that the majority of expected radiogenic cancers will develop at sites that have expected
doubling doses of a few hundred rem or (if the DDREF is set at 1) at least 170 rem.

Table 18
Analysis of the Distribution of Cancer Cases and Cancer Deaths, In Ascending
Order of Typical 1995 Expected Doubling Doses

% Radiogenic % Radiogenic Doubling Cum % Radiogenic Cum % Radiogenic

CaDeaths CancerCases Dose (1995) Ca Deaths Cancer Cases ~~
Leukemia (Acute and Non- 10.9 7.6 45 M1 8.0 .
Lymphocytic—approx. 2/3 of
all leukemias)
Liver 3.3 2.4 14 14.4 10.6
Bladder 55 7.6 : 98 19.9 18.6
Ovary 0.7 : 0.6 134 20.6 19.2
Stomach 9.8 7.5 147 30.5 27.1
Kidney 12 1.3 256 31.7 28.5
Colon/Intestine 21.6 27.2 339 53.6 57.1
Esophagus 2.0 140 339 55.6 58.7
> Breast ; 10 13 456 56.6 60.0
Remainder 27.1 26.4 560 84.0 87.9
Lung 15.8 115 769 100.0 100.0
Thyroid 07 ¢ 49 not cale
Skin 0.2 0.2 not calc
Bone 0.2 0.2 not calc

Total 100.0 100.0


Table ES-4
Central Projections of Absolute Numbers of Cases and Deaths That Would Be
Eligible for Compensation Under Different Scenarios

A. Conclusions Based on Total Cancer Cases

Threshold for Compensation 1991-2000 2001-2010 2011-2035 Total 1991+*
(Fraction of a Doubling Dose)
1 2.8 2.8 0.6 6
(1-5-4.2) (1-5-4.2) (0.3-0.9) (3-9)
0.5 15 17 7 39
(8-22) (9-25) (410). (21-57)
0.2 74 7B 63 210
(39-109) (41-114) (33-92) (113-320)
0.1 230 230 210 670
(122-340) 123-340) (111-310) (360-990)
0.075 380 370 340 1080
(200-560) (200-540) (178-490) ($70-1600)
B. Conclusions Based on Total Cancer Deaths
Threshold for Compensation. 1991-2000 ; 2001-2010 2011-2035 Total 1991+*
(Fraction of a Doubling Dose)
1 2.2 2.2 0.4 5
(1.4-2.9) (1.4-2.9) (0.2-0.5) G4)
0.5 il 12 4 27
(7-14) 8-16) G-6) (18-36)
0.2 47 49 35 131
(31-62) (33-65) (24-47) (87-175)
0.1 135 131 1 380
(90-180) (88-175) (74-147) (250-500)
0.075 210 200 170 590
(143-280) (135-270) (114-230) (390-780)

* Totals may not add due to rounding.


T:

able 6

Estimates of Total Collective Dose Delivered to DOE and Contractor Workers,
1965-1992

Year
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974,
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
Sum, 1965-92

* Data for 1982-1992 taken from Table 4.7 of the draft

Total collective person-rem”TM
3.13 X 104
2.79 X 104
2.45 X 104+
2.11 X 104
2.03 X 10+
1.95 X 104
1.87 X 104
1.70 X 104
1.53 X 104
1.36 X 104
1.39 X 104
1.41 X 104
1.44 X 104
1.35 X 10+
1.25 X 10+
1.16 X 104
1.04 X 104
7.88 X 105
8.16 X 103
8.42 X 103
8.68 X 103
8.26 X 103
6.35 X 105
3.93 X 105
3.38 X 103
3.33 X 103
2.94 X 103
2.68 X 105
3.64 X 105

1992 Annual Radiation Exposure Report; data for 1965-1981

calculated by distributional analyses based on dara in Table 4.2 of thar Teport (see Figures 4-12).

16


Cancer Rate Index (1995 = 1)

Cum % Total CA (Exec, Lenk.)

Figure 17

Projected Relative Rate of Occurrence (1995 = 1)
of Radiogenic Cancer Cases (Except Leukemia)
Induced in DOE Employees--1944-1992 Exposures

1.2

1.05

0.85

084

0.45

0.25

0.0 T T 7 T T T
1965 1975 1985 1995 2005 2015 2025 2035

Year
Figure 18

Cumulative % of All Radiogenic Cancers Except
Leukemia Expected to Occur in Various Years

100

90 +
80-4

- T T T T T r
1965 1975 1985 1995 2005 2015 2025 2035
Year


The analysis below seeks to produce central tendency estimates of

* The overall amounts and distribution of officially measured radiation dosage in DOE
and contractor emplovees (Section 2). For this analysis we bring together information
from (1) the distribution of career total estimated radiation dosage for individual
workers retiring in five recent years (1990-1994) from three major DOE facilities’ (2)
annual summaries of aggregate DOE and contractor dosage reports,® and (3) the
excellent historical compilation of career total dosage by age and calendar year of dose
delivery for workers included in a major epidemiological study of Hanford workers
over the years from 1944-1989.7 The result is a set of estimates of how many
workers are likely to have received various career total effective doses from exposures
between 1944 and 1992. We also use approximate data on age-specific mortality to
assess how much of this dose is likely to remain in workers who have survived to the
Present time, and in those who are likely to survive to various future years.

* The expected cancer risks likely to be associated with the exposures (Section 3). This

analysis draws on expert consensus estimates® (from Atomic Bomb survivors and
other populations) of the potency of various forms of ionizing radiation to induce
various cancers in people of different ages at different times after exposure.. The same
estimates are also used in combination with data on the age distribution of exposures in
the worker population to estimate typical “doubling doses” for various types to
tumors.

* The prospects for individual “proof” of cansation of the radiation-induced cancers
(Section 4) with either current technology (Section 4.1), new technology based on
advances in molecular biology for discriminating among different kinds of DNA
mutations,? measuring past radiation dosage, and assessing individual susceptibility

Tankersley, W. G. “Adjusting External Doses from the ORNL and Y-12 Facilities for the Oak Ridge Nuclear
Facilities Mortality Study,” Report by Oak Ridge Associated Universities in collaboration with the University of
North Carolina School of Public Health, ORISE 94/G-34 (1994); Warkins, J. P., Reagan, J. L., Cragle, D. L.
Frome, E. L., West, C. M., Crawford-Brown, D. J., and Tankersley, W. G.. “Dara Collection, Validation, and
Description for the Oak Ridge Nuclear Facilities Monnality Smdy,” by Oak Ridge Associated Universities in
collaboration with the University of North Carolina School of Public Health, ORISE 93/J-42 (1993); Checkoway,
EL, and Crawford-Brown, D., “Metabolic Modeling of Organ-Specific Doses to Carcinogens as Iustrated with
Alpha-Radiation Emitting Radionuclides, J. Chron. Dis. 40(Suppl. 2):191S-200S (1987).
ese data were graciously assembled by the individual facilities in response to the good offices of Steve Zobel of
the DOE headquarters. . .
®Smith, M. H., Hui, T. E., Strom, D. J., Miller, W. HL, and Scholes, V. A. 25th Annual Report-—Radiation
wees--1992, U. S. Department of Energy, Draft, December, 1994.
TBuschbom, R. L., and Gilbert, ES. Summa xtemal Radiation Doses for Hanford Workers 1944
1289, Report to the U.S. Department of. Energy by Batelle Pacific Northwest Laboratory, PNL-8909/AD-902. 1993.
Commitee on the Biological Effects of Tonizing Radiarions, National Research Council, Health Effects of
wy zi fiat , National Academy Press, Washington, D.C., 1990:
Puskin, J. S., and Nelson, C. B. "Estimates of Radiogenic Cancer Risks” Health Physics 69:93-101 (July, 1995).
¢ can now be very confident that cancer is fundamentally a genetic disease. The last two decades have seen
ic advances in the molecular biological tools available for (1) analysis of | changes in genetic informarion and
(2) understanding the significance of. ‘specific changes in particular genes for carcinogenesis. Such changes include
both “point mutations” (changes at particular places in the DNA code) and rearrangements of information represented
by the transfer of large sections of chromosomes in recombination events. Point mutations have been studied by
extracting specific genes from amors and other cells, copying the genes many times, and determining the detailed
sequence of DNA bases in those genes. One specific cancer related gene thar has been extensively studied in this way
is p53 (Greenblam, M. S., Benneu, W. P., Holstein, M.. and Harris. C. C. “Murations in the p33 Tumor
Suppressor Gene: Clues to Cancer Etiology and Molecular Pathogenesis.” Cancer Research 54:4855-4878, 1994.)

is)


"Table 30, Continued
Percentage of Total Radiogenic Cancer Deaths Occurring in Different Time
Periods That Would Be Eligible for Compensation

C. Requirement for 7.5% of the Doubling Dose--% Deaths Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total. All Times
Leukemia 4.88 221 2.00 0.00 9.10
Liver 0.82 0.62 0.56 0.56 2.55
Bladder 1.28 0.98 0.88 0.88 4.01
Ovary 0.14 0.11 0.10 0.10 0.44
Stomach 1.86 1.42 1.47 1.58 6.34
Kidney 0.19 * 0.14 “03 0.13 0.58
Colon/Intestine 1.37 1.05 1.52 1.72 5.65
Esophagus 0.22 0.16 0.14 0.13 0.66
Breast 0.05 0.03 0.05 0.07 20
Remainder L18 0.90 0.76 0.77 3.62
Lung 0.43 0.33 0.18 0.07 1.01

Total 12.41 7.96 7.78 6.00 34.1


Age
20
21
22

24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39

41
42
43

45
47

49
50
31
52
53
54
55
56
57
58
59
60
61
62
63

65
66
67
68
69
70
71
72

23

Table 8

Assumed Mortality Rates as a Function Of Age
Non-Smoker Mortality Risk Per Year 9% of Starting Population Alive at End of Year

0.00158
0.00166
0.0017
0.00169
0.00166
0.0016
0.00155
0.00153
0.00156
0.00162
0.00169
0.00171
0.00172
0.00172
0.00175
0.00173
0.00157
0.00167
0.00170
0.00178
0.00187
0.00198
0.00211
0.00222
0.00236
0.00253
0.00272
0.00296
0.00330
0.00367
0.00408
0.00454
0.00505
0.00568
0.00636
0.00709
0.00786
0.00874
0.00974
0.01082
0.01200
0.01323
0.0145
0.0222
0.0174
0.0189
0.0212
0.0234
0.0256
0.0279
0.0302
0.0312
0.0322

99.842 ~
99.676
99.507
99.339
99.174
99.015
98.862



Essentially the argument rests on a recognition that (1) there is uncertainty in the radiation
dose estimates and (2) because of that uncertainty, the workers presenting with tumors of types
that are sometimes caused by radiation may be more likely to have had higher doses than estimated
directly from their personal radiation records.

For example, imagine that we are dealing with a type of leukemia that we believe has a 40
tem doubling dose given the time pattern of estimated radiation exposures in a large group of 1,000
workers. Now let us say that we have an estimate that the average worker in the group received 30
rer (30,000 total-person-rem), but that the group is actually a composite of two indistinguishable
subgroups of workers—80% (800) of the workers actually received only 20 rem/person for a total
of 16,000 person-rem, and the remaining 200 workers actually received the other 14,000 person-
rem (average dose/person = 14,000/200 = 70 rem).58 Now taking the lifetime background
incidence of the relevant kind of leukemia to be about 1%, we expect the following results:

Subgroup Number of Expected Number Expected Number Average Dose

Workers of Background of Radiation- (Rem)/Worker With

. Cancers Induced Cancers Cancer
Less Exposed 800 8 4(=8* 20 ) 20
40
More Exposed 200 2 3.5 (=2* 2) 70
40
Total 1000 10 75 35.7
(= 12*20+5.5*70
12+5.5

It can be seen from the calculation in the bottom right hand box that the average true radiation
dosage per worker with cancer is about 36 rem in this example—larger than the 30 rem average for
the group as a whole, but less than the 40 rem doubling dose required to meet the “more likely than
not” standard. . .

If we make our hypothetical distribution of exposure more extreme (representing a case
with still more uncertainty in individual dosimetry) we can pass the 50% probability of causation
threshold. Let us suppose for this modified example that the 80% subgroup with less exposures
got only 15 rem/person instead of 20 rem/person. Subtracting their total dose of 12,000 person-
rem from the 30,000 person-rem of overall exposure, the average dose in the more highly exposed
group would now be 18,000/200 workers = 90 rem/worker, and the calculation of average dos:
per worker with cancer would be give us: .

58 This type of simarion could be produced either by uncertainty in dosage or. in theory, uncertainty in individual
effective dose caused by individual differences in susceptibility to radiation-induced cancers.


41

Table 16
Percentage Distribution of the Past Dosage Surviving to Different Calendar Years
that is Likely to Have Been Delivered to Workers in Different Age Ranges

. % Dose Delivered to Workers in Specific Age Ranges
Dose Surviving % Dose 229 30-39 40+

to Year Surviving
Total Delivered 640,000 100 183 27.4 543
1944-1992
1995 420,000 6 252 343 40.5
2000 360,000 56 28.5 36.5 35.1
2005 290,000 45 - 326 38.4 29.0
2010 220,000 34 378 393 29
2015 160,000 4 44.0 38.3 107
2020 100,000 16 50.5 36.7 128
Table 17

Expected Future Changes in Typical Doubling Doses for Different Cancer Sites,
Given the Changing Age Pattern of Dosage Delivered Derived in Table 16

Doubling Doses for Dose Surviving To Various Years

Cancer Site Age Dist as 1995, 2000 2005 2010 2015 2020
Delivered

Esophagus 331 339 343 348 353 358 364
Stomach 177 147 136 124 112 101 91
Colon 460 394 374 355 339 330 322
Liver 14 14 74 74 74 74 74
Lung 702 769 302 845 901 970 1051
Leukemia (Ave 3-20 49 45 4 42 (not calc) (notcalc) (not calc)
yrs after exposure)
Bladder 99 98 97 97 96 96 95
Kidney 256 256 256 256 256 256 256

Residual 555 560 561 563 566 568 369


Subgroup Number of Expected Number Expected Number Average Dose
Workers of Background of Radiation- (Rem)/Worker With
"Cancers ‘Induced Cancers Cancer
Less Exposed 800 8 3(=8* >) 15
More Exposed 200 2 4.5 (=2* >) 90
Total 1000 10 7.5 42.8
(= 11*15+6.5*90
11+6.5

Under these circumstances, we now do pass the 40 rem doubling dose, but we have had to work
pretty hard to create an example with these properties. It is clear that this Bayesian-updating
argument could have some influence on the outcome of workers’ compensation cases that would
otherwise be very close calls (i-e., assessed doses very near to the relevant doubiing dose).
However it seems unlikely that this will prove a major factor for the great bulk of occupational
radiation-induced cancers which occur at much less than half of a doubling dose.

5. The Likely Effects of Alternative Settlement Policies Which
Lower the Threshold for Recovery

With the highly skewed distribution of radiation exposures, and the substantial background
of cancers from other agents, the “more likely than not” threshold leaves a substantial portion of
radiation-induced cancers outside the realm of the workers’ compensation system. To that extent,
the goals of the system are unmet.

In this section I will therefore consider the likely effects of changes in the probability of
causation threshold for recovery for the numbers and types of radiation-induced cancers (and
“background” cancers) that would be eligible for compensation. Tables 29 and 30 show the
changes in the proportion of various radiation-induced cancers that are expected to be compensable
based on compensation standards of (a) 20% of a doubling dose, (b) 10% of a doubling dose, and
(c) 7.5% of a doubling dose. In parallel with tables 19 and 20, Table 29 gives data for total cases,
and Table 30 provides similar information for fatal cancers only. It can be seen that as


10°

2.2 Estimation of the Aggregate Dosage Delivered to DOE and Contractor
Employees
Data are readily available for radiation exposures for the period 1965-1992 from the latest

draft DOE annual radiation report.!'2, However because some cancers appear several decades after
the initiating exposure, it is desirable to build as complete a picture as possible of the history the
dosage delivered to DOE and contractor workers extending back to World War II. To do this, I
will first describe the relevant DOE-wide data, and then combine it with a more extensive data set
for Hanford workers giving information back to 1944, with important details on the age
distribution of the workers who received the dosage. The age distribution information in turn
allows us to assess (1) how much of the dosage is borne by workers who can be expected to
survive to various years in the present and the future, and (2) the time distribution of the cancers
likely to result eventually.

2.2.1 Data from the DOE-Wide Annual Compilation of Current Dosimetry
Measurements for 1965-1992

The annual radiation report includes in its Table 4.7 a summary of collective DOE-wide
dosage for 1982-1992. For 1965-1981, I calculated dosage from the distributional information
provided in Table 4.2 of the report.

Figures 4-12 show lognormal probability plots of official DOE exposure data for every
third year from 1965-1992 from DOE’s ongoing personal monitoring program for radiation
exposures(the 1989 data are not shown because there were only two usable data points).

In this kind of plot, the basic hypothesis is that the data are lognormally distributed. That is, the
logarithms of the exposures have a normal gaussian distribution. Such a distribution is expected
when the causes of variability in exposures among employees are multiplicative. The
correspondence of the points to the line allows a rapid appraisal of whether the data are reasonably
accurately described by the lognormal hypothesis. In practice, many exposure distributions for
environmental agents are approximately lognormal.!3 The correspondence to a lognormal
distribution is seen by comparing the data points to the fitted line. The slope of the fimed line is an
estimate of the standard deviation of the logarithms (base 10) of the exposures; the intercept of the
fitted line is an estimate of the median of the distribution of the logo of the exposures. The
estimated “geometric standard deviation” of the distribution is simply the antilog of this slope.

12Smith et al., cited earlier as note 6.
13Hfamis, D. and Burmaster, D. E. “Assessment of Variability and Uncertainty Distributions for Practical Risk
Analyses” Risk Anaivsis, Vol. 14, pp. 713-730, October 1994.


Table ES-1

Distributions of Cumulative Radiation Exposures Among 1990-1994 Retirees
from Savannah River, Los Alamos, and Hanford

Hanford Retirees

Los Alamos Voluntary
Early Retirees

Savannah River Retirees

rem/person| % People with % Aggregate | % People with  % Aggregate % People with % Aggregate
any dose over Dose over this} anydoseover Dose over this jany dose over this Dose over this
this dose dose this dose dose dose dose
i 25.66 94.63 28.62 93.20 22.78 94.00
2 18.39 89.88 18.73 86.64 16.39 89.95.
5 9.95 78.14 11.21 76.60 10.29 81.23
75. 7.33 71.04 772 66.71 8.38 76.03
10 5.98 65.79 6.34 61.23 7.04 70.92
15 4.03 55.12 3.76 45.91 5.00 59.66
20 2.91 46.57 1.98 31.97 3.55 48.52
30 1,52 31.46 0.79 19.73 La. 25.10
40 0.74 19.63 0.79 19.73 0.35 8.80
60 0.35 10.90 0.20 6.44 0.07 3.14
80 0.06 2.43 0.00 0.00 0.02 1.45
100 0.00 0.00 0.00, 0.00 0.02 45



25

3. Doubling Doses for Radiation-Induced Cancer, and Expected
Lifetime Excess Cancer Risk in Current and Former DOE and
Contractor Workers

3.1 Basic Dose Response Relationships for Radiation-Induced Cancer--Why
Do We Expect Low Dose Linearity?

Often the assumption of low dose linearity is presented in the context of its Original use for
cancer risk assessments over 20 years ago~as a “conservative” assumption—chosen in part for
simplicity and in part because it was considered unlikely to understate risk. I think there is now a
much stronger argument for its use, and that its status should be changed from a “conservative”
assumption to a “central tendency” or “best estimate” assumption for carcinogens that act by
primary genetic mechanisms. Ionizing radiation is a paradigmatic case in point.!8 Although there
are still some remaining adherents to older “threshold” theories, !9 and even some who advance
“hormesis” theories (under which low doses of radiation are proposed to have positive net benefit,
rather than harm),?0 I believe that our mechanistic understanding of carcinogenesis had progressed
to the point where such possibilities are highly doubrful. All recent national and international
consensus summaries of radiation risks—which are the sources of the risk estimates presented
below—-use models that incorporate low dose linearity for all radiation-induced cancers. (As will

18Hartis, D., and Smith, J., "What's Wrong with Quantitative Risk Assessment.” in Quantitative Risk Assessment,
J. M. Humber and R. F, Almeder, eds., Biomedical Ethics Reviews: 1986, Humana Press, Clifton, New Jersey,
1987, pp. 57-105.

19For example Raabe has used projections of the time distribution of bone sarcomas induced by very high doses of
tadionuclides to advance the notion that cancers produced at low dose rates should occur only ar times longer than the
normal lifespan, creating a “quasi-threshold”. [Raabe, O. G., Rosenblatt L. S., and Schlenker, R. A. “Interspecies
Scaling Of Risk For Radiation-Induced Bone Cancer, Int J Radiat Biol 57: 1047-1061 (1990); White R. G., Raabe,
O. G., Culbertson, M. R., Parks, N. J., Samuels, S. J. and Rosenblatt, L. S. “Bone Sarcoma Characteristics And
Distribution In Beagles Fed Strontium-90.” Radiation Research; 136: 178-189 (1993).] Similar arguments have
been advanced in the field of chemical carcinogenesis based on similar observations of a power law dependence of
time to tumor on dose rates of various nitrosamine carcinogens [Druckery, H. “Quantitative aspects in chemical
carcinogenesis. In Potential Carcinogenic Hazards fom Drugs, (Truhaut, R.. ed.) New York: Springer-Verlag,
1967); Peto, R., Gray, R., Brantom, P., and Grasso. P. “Nitrosamine Carcinogenesis in 5120 Rodents: Chronic
Administration of Sixteen Different Concentrations of NDEA, NDMA, NPYR, and NPIP in the Water of 4440
Inbred Rats, with Parallel Scudies on NDEA Alone of the Effect of «Age on Starting (2, 6, or 20 weeks) and of
Species (Rats, Mice, or Hamsters).” IARC Sci. Publ. $7: 627-655 (1986)}. Travis and colleagues have analyzed the
latter data and shown that the power law dependence of dose rate is not incompatible with the Moolgavkar two-stage
carcinogenesis theory—indeed it appears that the value of the time power is closely related to the power of dose seen
in the relationship between carcinogen dose and the apparent rate of proliferation of relevant initiated cells. [Travis.
C. C., and Birkner, P. D. “Druckery slope controlled by mitotic rate of enzymatically-altered foci.” J Theor Biol
149: 217-227 (1991); Travis, C. C., McClain, T. W., and Birkner, P. D. “Diethyinitosamine-induced
hepatocarcinogenesis in rats: a theoretical study.” Toxicol Appi Pharmacol: 109: 289-304 (1991).] Such
proliferative stimulation would not be expected to extend to very low dosage. linearizing any effect of this process on
tumor risk at low doses.

20 Mine, M., Okumura, Y., Ichimaru, M., Nakamura. T., and Kondo. S. “Apparently Beneficial Effect Of Low To
Intermediate Doses Of A-Bomb Radiation On Human Lifespan.” Int J Radiat Biol. 58: 1035-1044 (1990); Balaram.
P., and Mani, K. S. “Low dose radiation—a curse or a boon?” Natl Med J India: 7: 169-172 (1994).


Through the good offices of Steve Zobel of the DOE we were able to obtain detailed data
on the recorded career total radiation dosage" of nearly 19,000 workers retiring from three major
facilities (Hanford, Savannah River, and Los Alamos) over the period from 1990-1994. These
facilities were chosen to represent DOE offices and states with the greatest concentration of past
radiation dosage and therefore likely compensation cases. Overall, the three DOE field offices that
include the covered facilities report over half of the total collective radiation dose delivered to DOE
and contractor employees between 1982 and 1992.

Data for the three facilities provided very similar distributions of past dosage among
workers (Table ES-1). Combining the data, about two thirds of the aggregate dosage is carried by
workers who received at least 10 rem (100 mSv), and also about two thirds of the dose is borne by
workers retiring near the end of their normal work lives (Figure ES-1). The relative concentration
of past dosage (and resulting risks) among arelatively small fraction of former career
DOE/contractor workers is important for assessing the economic feasibility of measures to provide
equitable relief in recognition of those risks.

In order to project the number and time distribution of likely cancers, we assembled data on
the amount and time distribution of past exposures for DOE and contractor workers. To do this,
we combined 1965-1992 information on DOE-wide aggregate exposures with detailed data on age-
at-exposure and year of exposure from the Hanford facility on exposures occurring between 1944
and 1989 (Figure ES-2). It can be seen in Figure ES-3 (derived from the Hanford data) that most
exposure occurs relatively evenly in the prime work years between the ages of about 27 and 55.

Overall, we project that the aggregate dosage received by DOE and contractor workers

_ between 1944 and 1992 is about 640,000 person-rem. Given estimates of age-specific mortality
rates for never-smokers, Table ES-2 shows how much of this dose is likely to persist in the
surviving population to various times in the furure. (The data for 1970 through 1990 in this table
reflect the net effects of both accumulation and loss of exposure with mortality.) It can be seen that
as of now (1995) about two thirds of all the dosage delivered in the 1944-1992 period is expected
to occur in the population of surviving workers. Within 15 years from now (2010), however,
only half of that remaining fraction (34% of the original dose delivered) will still be carried by
living people. Ten years after that (2020), only 16% will remain, and by 2025 only 10% will

* The request was for dosage in terms of the current DOE standard for expressing career dose~the lifetime committed
dose. In theory this involves a different treatment of dosage from internal emissions from radionuclides than earlier
standard forms for expressing dosage. The new “commited” doses are defined as the entire dosage that is expected to
be delivered from work in a given year over the subsequent 50 years, if the worker survives for that period. My
impression is that earlier conventions for expressing dose recorded only the external dose plus the portion of the
internal dose that was expected to be delivered within a particular year. It is not completely clear how much
recalculation of career committed doses from long past radionuclide exposures is reflected in the dara we received.


Figure 13

Collective Dose Delivered In Various Years to 37,009
Exposed Hanford Workers Who Were First Employed
Between 1944 and 1978--Data of Buschbom and Gilbert, 1993

7000

6000 4

5000 5

4000 +

3000 5

2000 +

Total Dose (Person-rem)

1000 5

Q T 7 T T
1940 1950 1960 1970 1980 1990

Year


15

Table ES-3
Final Tradeoffs Between Compensating “True” Radiogenic Cancers and the
Overall Ratio of Cases Compensated to Cases Caused

A. Conclusions Based on Total Cancer Cases

Threshold for Compensation % True Radiogenic Cancers Ratio of Total Cases to Ratio, Cases
(Fraction of a Doubling Dose) Compensated, 1991+ True Positive Cases  Compensated/Cases Caused
1 0.527 1.74 0.0092
0.5 2.43 2.35 0.057
0.2 8.40 3.75 0.32
0.1 16.4 6.04 0.99 .
0.075 21.2 7.54 1.60 so

B. Conclusions Based on Total Cancer Deaths

Threshold for Compensation % True Radiogenic Cancers Ratio of Total Cases to Ratio, Cases
(Fraction of a Doubling Dose) Compensated, 1991+ True Positive Cases | Compensated/Cases Caused
1 0.721 1.73 0.0125
0.5 3.08 2.33 0.072
0.2 9.58 . 3.65 0.35
0.1 . 17.3 5.80 1.01

0.075 21.7 7.20 1.57


Figure ES-6

. . “Estimated Distribution of ‘Career ‘Doses
“= .°\.:«:*For Former DOE and Contractor Workers -
 .. with 1- 100° Total Rem of. Exposure

~ $0000 ~ 4)

Ovary and stomach .
134-147, all others =

Her over 200 \,

40° 60 rT es
rem/workéer |: a

Nimber of Workers Per 1 Rem- .
Interval of  Accumalated Dosage - °

Estimated Distribution of Career Doses
. , For Former DOE and Contractor Workers
" with 1-100 Total Rem of Exposure

Number of: Workers Per 1 Rem:
Interval of Accumulated Dosage’
8
rt

250 4
200 4 -
Ovary and stomach

150 ~ 134-147, all others
400 4 over 200

50 + \

9 :

(0)

rem/worker.


Table of Contents

Page
Executive SUMMary...........-ssscssecsssseeesseeseeceesscseeestcessnseesecesesseeseaeeesenees
L. Entroduction 00.02... ...eseeessscsssceseseseecssteeeeesneceeeeeeseecsessecesseseaeeeseuaeenes 1
2. Magnitude and Distribution of Past Radiation Dosage in DOE and Contractor
Emmployees..........cccesesccesssessssssenecesceeceececnseaseeseessecsaecesacessssseesseeeees 4
2.1 The Distribution of Cumulative Career Total Dosage in Recent Retirees
from Hanford, Los Alamos, and Savannah River..........:sssssescsssssesesees 4
2.2 Estimation of the Aggregate Dosage Delivered to DOE and Contractor
Employees ..........:.:secssesesssesseecsessessseesesesesanseeeceeesasensesseeaeseaes 10

2.2.1 Data from the DOE-Wide Annual Compilation of Current
Dosimetry Measurements for 1965-1992
2.2.2 Data on Hanford Exposures for 1944-1989
2.2.3 Estimates of Aggregate Radiation Doses Delivered for DOE and
Contractor Employees as a Whole, By Year and Age, 1944-1992 ...21
2.3 Expected Loss of the Inventory of Cumulative 1944-1992 Dose with Past

and Expected Future Mortality, 1970-2025.........sssssssscssssssessssesseses 21
Doubling Doses for Radiation-Induced Cancer, and Expected Lifetime Excess
Cancer Risk in Current and Former DOE and Contractor Workers .........-+--000++ 25

3.1 Basic Dose Response Relationships for Radiation-Induced Cancer~Why

Do We Expect Low Dose Linearity?..........ssssccssssssssessssssssnesnssesenese 20
3.2 Estimates of the Potency of Low Dose Rate Radiation Exposures for

Inducing Cancers of Various Types .........::sssesesesssrececeessceeseeeeseneees 27
3.3 How Many Radiation-Induced Cancers of Various Types Should Be ;

Expected When? ...
3.4 Calculation of Doubling Doses for Various Cancer Sites, Considering the

Age Distribution of the Exposures........sssscscsecceesrecseeesecseceeeereeesees 38
3.4.1 The Implications of the “Preponderance of the Evidence” Test for
Causation, Applied on an Individual Basis ..............-...sececeeeeeee 38
3.4.2 “Doubling Doses” for Induction of Various Cancers by Ionizing
Radiation Delivered at Various Ages .............0.ccssecesesceessceeeee 38
Prospects for Individual “Proof” of Causation for Radiation-Induced Cancers in
the Population of Former DOE/Contractor Workers ............s::scccsessessssseeeeee 43

4.1 Fraction of Cancers that Could be Compensable Under the Usual “More
Likely Than Not” Test...



48

there is no a priori reason to expect a specific change in relative risk, and therefore :
doubling doses would be essentially unchanged on average. ,

4.2.2 Analysis of the Potential of “Category 1” Innovations--Approaches
for Subclassifying Tumors According to Specific Putatively Causal
Somatic Mutations

Categories of DNA Damage and Repair Processes. and Implications for
Mutational Spectra

It is well known that cancers come in a variety of types. Following the diagnostic
Categories developed for cancer treatment by physicians, epidemiologists have traditionally used =~_
anatomical sites of origin of cancers, and histological types, to classify cancers to deduce possible
relationships with exposures. The new molecular biological techniques of Category 1 essentially
allow us to distinguish cancers further, by the types of DNA mutations found in specific genes that
are likely to have contributed to the development of the cancer.47 These finer subcategories
resulting from “molecular pathology” furnish epidemiologists with a set of categories that may
eventually prove even more useful than anatomy and histology for developing relationships with
specific putative causal agents.

Part of the promise of the molecular pathology categories is that they allow researchers to
bring to bear fundamental information about the ways specific kinds of mutations are produced in
Sorting out which cancers are likely to have been caused by which agents.*8 For example:

* The DNA bases cytosine and 5-methylcytosine spontaneously deaminate (lose an
amino group) at a slow rate at normal body temperature. This converts the parent
bases to uracil and thymine respectively, which tend to pair with the “wrong” base on
the opposite DNA strand. If these changes are not detected and repaired before the

next time the DNA is copied the altered bases therefore give rise to G:C to A:T
“wansitions”.“9 These changes occur most frequently at CpG dinucleotides, which are

“7One such gene, which has been found to be altered in about 37% of all cancers studied is PS3--a gene that in its
normal state helps suppress the development of cancer in part by Tecognizing the presence of extensive DNA damage
and blocking ceil replication until most of the damage is repaired. Mutations in this gene will be covered in some
detail below, but other genes in multiple pathways to cancer may eventually be subject to similar molecular
analysis.

48Greenblatt, M. S., Bennett, W. P., Holstein. M., and Harris, C. C. “Mutations in the p53 Tumor Suppressor
Gene: Clues to Cancer Etiology and Molecular Pathogenesis,” Cancer Research 54:4855-4878, 1994.

“©The four DNA bases are divided into two chemical families. Adenine (A) and guanine (G) are purines. whereas
thymine (T) and cytosine (C) are pyrimidines. Normaily adenine pairs with thymine on the complementary DNA
strand of the double-helix, and guanine pairs with cytosine. If a mutation causes one purine base to be substitured
for the other purine base (and the corresponding pyridines to be exchanged on the opposite strand), this is designated
as a “transition”. By contrast, if the mutation consists of the substitution of a purine for a pyrimidene (or vice
versa) on a particular strand, this is designated as a “transversion”, Both of these are simple single-base sutstimtion
mutations. Other kinds of mutations either eliminate one or more bases (“deletions”) or add one or more bases
(“insertions”). If a deletion or insertion does not delete or insert a an integral multiple of 3 bases (e.g., 3. 6. 9. e8c.).


for radiation-induced DNA damage (Section 4.2), and/or new Bayesian evaluation of
likely past dosage in workers presenting with cancers, based on the uncertainties in
individual dosimetry among other factors (Section 4.3). The “doubling doses”
calculated in Section 3 are important because in order to show that a particular cancer
was caused by occupational radiation exposure by a “preponderance of the evidence”
(the usual test for legal recovery) a worker must generally show personal occupational
exposure above the doubling dose for that tumor. Only a tiny proportion of former
workers with radiation-induced cancers will have received doses high enough to
qualify by this standard. The newer molecular biological techniques have promise to
both better document individual worker exposures and to identify specific kinds of
mutations in individual cancers that are somewhat more likely to have been-caused by
radiation than by other DNA damaging agents. However it is likely that only a small
minority of the radiation-induced cancers will be moved across the “more likely than
not” boundary by these techniques.

. ‘ossible effe ici ge id ve: ion 5), This
section considers the implications of specific alternative settlement policies in addition
to the traditional policy of compensating workers with greater than one doubling dose.

The alternative policies correspond to lowering the threshold for recovery to between
7.5% and 50% of the official doubling doses.

The analysis focuses on “central tendency” estimates--estimates that are based on
assumptions that are neither deliberately biased high or biased low. Nevertheless, it should be
understood that the estimates cannot be perfectly precise. The uncertainties in both past
dosimetry/reporting and dose response relationships mean that the narrowest credible ranges for
estimates of aggregate cancer cases, and other relevant factors, will include values at least two-fold
higher and lower than the stated “central tendency” values.

Persistent chromosome rearrangements suitable for assessment of past radiation doses have been sudied by both
conventional cytogenetic and chromosome banding suidies, and newer techniques that are referred to under the
“Fluorescence In Situ Hybridization FISH)” or “Chromosome Painting” rubrics (Brenner, DJ. and Sachs, RK.
“Chromosomal ‘Fingerprints’ of Prior Exposure to Densely Ionizing Radiation,” Radiation Research 140:134-142.
1994; Tucker, J. D., Ramsey, M. J., Lee, D. A, and Minkler, J. L. “Validation of Chromosome Painting as 2
Biodosimeter in Human Peripheral Lymphocytes Following Acute Exposure to Ionizing Radiation In Vitro,”
International Journal of Radiation Biology 64(1):27-37, 1993; Lucas, J. N., Poggensee, M., and Sraume, T. “The
Persistence of Chromosome Translocations in a Radiation Worker Accidentally Exposed to Tritium,” Cytogenetics
& Cell Genetics 60(3-4):255-256, 1992.)


remain. Clearly any policy measures that are considered necessary to deal with the effects of these
exposures will need to be put into place in the immediate future in order to be effective.

Expected Cancer Cases and Deaths

The last two decades have seen important advances in our understanding of the
fundamental mechanisms of carcinogenesis. We can now be very confident that with few known
exceptions, tumors arise as a result of a series of changes or rearrangements of information coded
in DNA within single cells or cell lines. The fundamental multiple mutation mechanism of
radiation-induced carcinogenesis has strong implications for the likely relationship between
delivered dose and incremental cancer risk at the limit of low dosage. Often the assumption of low
dose linearity is presented in the context of its original use for cancer risk assessments over 20
years ago—as a “conservative” assumption—chosen in part for simplicity and in part because it was
considered unlikely to understate risk. I think there is now a much stronger argument for its use,
and that its status should be changed from a “conservative” assumption to a “‘central tendency” or
“best estimate” assumption for carcinogens that act by primary genetic mechanisms. All recent
national and international consensus summaries of radiation risks—which are the sources of the risk
estimates presented below—use models that incorporate low dose lineariry for all radiation-induced
cancers, although there is still considerable uncertainty about appropriate low dose slopes for the
dose response relationships for specific cancers in relation to specific types of radiation.

Our basic starting point for estimating likely cancer risks was a compilation of the most
recent official EPA conclusions for ionizing radiation cancer potencies for exposure of the general
population at low dose rates.* The EPA risk estimates were derived by taking the geometric mean
of potency estimates from previous ICRP, NIH, and NRC risk modelsTM applied to a stationary
population with 1980 vital statistics, and then applying a downward adjustment of two-fold (the
“Dose and Dose Rate Effectiveness Factor”) for sites other than the breast to reflect an assumed
lower efficiency/greater repair of DNA damage when radiation is delivered at low dose rates
(relative to the high dose rates produced by the atomic bomb and some other sources of exposure).
Combining these overall potency estimates with our earlier overall cumulative dose estimate of
640,000 person-rem, we arrive at an expectation that there will eventually be about 250 cancer
deaths and 360 total cancer cases as the result of the occupational exposure of DOE and contractor
employees to penetrating radiation.

* Puskin, J. S., and Nelson, C. B. "Estimates of Radiogenic Cancer Risks” Health Physics 69:93-101 (July, 1995).
“* National Institutes of Health, “Report of the National Instinites of Health Ad Hoc Working Group to Develop
Radioepidemiolgical Tables.” Washington. D.C.: U.S. Government Printing Office: NIH Publication 85-2748;,
(1995); International Commission on Radiological Protection, 1990. “Recommendations of the International
Commission on Radiological Protection.” Oxford: Pergamon Press; ICRP Pubiicction 60; Ann. ICRP 21 (1991).


Table 4
Estimated Absolute Numbers of Current and Former Workers At Various Career
Dose Levels as of 1995

rem/person % People with any  % Aggregate dose over Estimated absolute numbers of
dose over this dose this dose current and former workers
. surviving to 1995

24.35 94.25 46,000

2 17.40 89.76 33,000

10.18 79.62 19,000

7.5 7.87 73.35 15,000

10 6.53 68.16 12,000

15 4.51 56.97 8,500

20 3.19 46.87 6,000

30 1.43 27.72 2,700

40 0.54 14.20 1,000
60 0.20 6.79 380
80 0.04 1.82 70
100 0.01 0.73 "7

Figure 2

Total Cumulative Person-Rem in
Hanford Retirees by Year of Age

1200 4

1000 4 _—

68% of Total Population Dose in
800 + Retirees Between 55 and 66 Years Old

600 +

Total: Person-Rem



Table 33, Continued
Ratios of Total Compensated Deaths?’True” Radiogenic Cancer Deaths for
Various Thresholds for Compensation

E. Requirement for 7.5% of the Doubling Dose
Ratio of Total Compensated/’True” Radiogenic Deaths

Total % Radiogenic Cancers 1991-2000 2001-2010 = 2011-2035 = Total, All Times
Compensated 1991+ of all

Caused by 1944-1992 Exposures
Leukemia 4.21 431 4.07 4.19
Liver 174 4.89 4.89 4.89 4.89
Bladder 2.73 5.78 5.73 3.65 3.72
Ovary 030° 6.85 6.47 6.42 - 6.59
Stomach 4.47 7.61 6.45 5.45 6.46
- Kidney 0.39 8.86 8.86 8.86 8.86
Colon/Intestine 4.28 10.54 9.82 9.67 9.94
Esophagus 0.44 9.90 9.88 10.05 9.94
Breast 0.16 10.44 10.20 10.06 10.20
Remainder 244 10.32 10.33 10.30 10.32
Lung 0.58 11.26 11.94 12.31 11.59

Total 21.74 717 6.94 157 “7.20


the threshold for compensation is relaxed, to 10% or 7.5% of the doubling doses, approximately a
quarter to a third of the radiogenic cancers (cases or deaths) could become eligible, respectively.

As the threshold for recovery is relaxed, one can expect an increasing fraction of
compensated cases to be in people whose cancers were not in fact caused by their occupational
radiation exposures. The ratio of total cases compensated to “true” radiation-induced cancers
compensated (Table 31) is simply the inverse of the probability of causation as given in equation
(1) (page 38).

One other distinction is crucial for calculating the “false positive” costs for any
compensation threshold. The values shown in Table 31 for any compensation rule provide the
maximum ratio of total cases to true radiation-induced cases for any specific compensation
threshold. Thus, for the ordinary rule for 1 doubling dose, one can say that if the system is
working correctly, there should be no more than two total cases for each true positive cases. Bur
in practice there would be expected to be fewer false positives. The compensation threshold is a
minimum threshold for compensability. Different compensated workers will necessarily have
exposures that exceed the applicable minimum by various amounts. What we need for cost
calculations is the average ratio of total cases to true radiation-induced cases for the entire exposure
distribution above the minimum cutoff. The results of such calculations for the various cancer sites
and compensation thresholds are shown in Tables 32A-32E for total cancer cases, and in Tables
33A-33E for cancer deaths. In each case, the series of tables covers thresholds for compensation

ranging from 1 doubling dose (the current system) down to as little as 7.5% of the doubling dose. *

‘The first column in each table summarizes earlier data on the percentage of all mmors induced by
1944-1992 exposures that are expected to be compensable in the period after 1990. We have
elected to exclude pre-1991 cancers from the calculated effects of our alternative policies because
we are doubtful that cancers appearing more than 5 years in the past will be the subjects of many
workers’ compensation claims. The subsequent columns show the expected ratios of total cases
compensated (“false positives” + “true positives”) to the previously calculated numbers of true
radiogenic cancer cases in each period.

The overall policy-relevant findings from these calculations are summarized in Table 34 and
Figure 19. Basically, there is a tradeoff between the percentage of true radiogenic cancers
compensated and the total expenditures made for both “true” cases and indistinguishable “false
positive” cases. If a policy decision were made that it is desirable to compensate an equal number
of cancer cases to those caused, this would be achieved by setting the threshold for compensability
at about 10% of the doubling doses. At 7.5% of the doubling doses, the cases compensated would
be about 60% greater than the cases caused. If the threshold is set at a higher level than 10% of the
doubling doses, the percentage of true radiogenic cancers compensated declines rapidly. Using
20% of the doubling doses results in only one-third of the social costs being bome, while using


A prudent policy planner will want to consider each of these estimates as the lower bound
of an approximately 2-3 fold credible central range of likely overall cancer risk (250-500 cancer
deaths; 360-1000 total cancer cases). This is because: .

* With the possible exception of tritium exposures, long term exposures from absorbed
tadionuclides appear to be reflected incompletely in the past records of “penetrating”
doses. DOE policies appear to have been changed to require reporting of “total
effective dose equivalents” (including an estimate of internal dose for the current year)
only since 1990. Most recently, the reporting definition has been changed again to
“committed effective dose equivalents” which evidently include an estimate of the total
dose that is expected to be delivered to workers over the next 50 years (if they survive)
from radionuclide dosage absorbed in the current year. The pre-1990 data which
comprise the great bulk of the cumulative dose delivered to workers, do not reflect
these expanded definitions.

* Older methods of measuring even the penetrating dose were not sensitive to some
forms of radiation (e.g., neutrons before 1972; low energy gamma radiation before
1957 at Hanford), although measurement of the predominant form of ionizing
radiation—high energy gamma—was evidently fairly complete. Additionally, the
monitoring was done primarily for compliance purposes and some workers who were
thought to have relatively small exposures were not monitored. A study of 1943-1956
measurements of external dosage at Oak Ridge National Laboratory resulted in a 50%
upward adjustment in the estimate of total collective dose for over 7000 workers at that
facility during that time period (from a mean of 1.08 to 1.63 rem/worker). A similar
analysis of dosage for nearly 8500 workers at the nearby Y-12 facility from 1947-
1960 led to an overall 80% upward revision of their collective dose (from a mean of
0.5 to 0.9 rem/worker). On the other hand, a paper in press by Gilbert er al. points
out that total penetrating dose as reported may tend to overstate the dosage delivered to
various organs, depending on the geometry of the placement of the dosimeter and
other factors. The overall upward bias was estimated at 1-27% for “deep dose”, 41-
75% for red bone marrow dose, and 6-33% for lung dose in various time periods
between 1944 and 1989.

* Classical epidemiological methods have a bias toward underestimation of the slopes of
dose response relationships where there is uncertainty in the estimation of individual
dose. If estimates of these uncertainties are made, it is possible to correct for this bias,
but such corrections are very unusual in epidemiology, and the intemational consensus
estimates of radiation potency do not include an allowance for this effect. Additionally,
there is some suggestion in the literature that the epidemiological results may tend to
become more positive as additional time passes and longer lag periods are allowed in
epidemiological analyses of relative risks.

* — Itis far from obvious that the two-fold Dose and Dose Rate Effectiveness Factor
(@DREF) is appropriate (and uniform in magnitude) as applied to all cancers other than
breast and leukemia. Surely if DNA repair saturation is the underlying mechanism,
there is likely to be a different amount of high dose saturation (and therefore high-to-
low dose change in dose response slope) for different tissues. The very fact that a
uniform factor is applied indicates that specific data relevant for different cancer sites
are probably not available, and the overall two-fold reduction in potency due to this
factor carries considerable uncertainty.

* Competing sources of mortality (in particular, cardiovascular diseases) have been
declining in recent decades, increasing the proportion of deaths due to cancer.


Table 33, Continued
Ratios of Total Compensated Deaths/’True” Radiogenic Cancer Deaths for
Various Thresholds for Compensation

C. Requirement for 20% of the Doubling Dose
Ratio of Total Compensated/"True” Radiogenic Deaths
Total % Radiogenic Cancers 1991-2000 2001-2010 2011-2035 = Total, All Times

Compensated 1991+ of all
Caused by 1944-1992 Exposures

Leukemia 3.57 2.98 2.93 2.96
Liver 1.28 3.58 3.58 3.58 3.58
Bladder 1.78 3.93 3.97 3.92 3.94
Ovary 0.15) . 4.37 4.33 4.24 431
Stomach 2.25 4.58 4.26 3.88 4.14
Kidney 0.07 4.78 4.78 4.78 4.78
Colon/Intestine 0.43 5.45 5.24 5.13 5.21
Esophagus 0.05 5.18 5.20 5.25 5.20
Breast 0.01 5.21 5.26 5.24
Remainder 0.00

Lung 0.00

Total 9.58 3.50 3.57 3.99 3.65

D. Requirement for 10% of the Doubling Dose
Ratio of Total Compensated/’True” Radiogenic Deaths

Total % Radiogenic Cancers 1991-2000 2001-2010 = 2011-2035 = Total. All Times

Compensated 1991+ of all
Caused by 1944-1992 Exposures
Leukemia 4.06 3.82 3.62 3.73
Liver 1.64 4.64 4.64 4.64 4.64
Bladder 2.55 5.11 5.06 4.99 5.06
Ovary 0.27 6.01 5.86 5.79 5.89
Stomach 3.99 6.61 5.82 4.99 5.75
Kidney 0.28 7.53 7.53 7.53 7.53
Colon/Intestine 251 8.23 8.18 8.01 8.12
Esophagus 0.26 8.04 8.03 8.17 8.08
Breast 0.09 8.64 + 7.94 8.18 8.21
Remainder 1.52 8.75 8.87 8.86 8.83
Lung 0.18 9.47 9.56 9.49

Total 17.34 5.68 3.60 6.22 5.80


81

Attachment A
Use of BEIR V Risk Coefficients to Calculate Doubling Doses

As a supplement to the presentation in Section 3.4 above, This section shows cancer
potency values and the results of calculations of doubling doses based on the more aggregated
cancer sites analyzed in the BEIR V teport, and some other data for radon. Tables Al-A3 show
tisk coefficients for different kinds of ionizing radiation exposures, as a function of age at
exposure, time after exposure, gender, and (in the case of radon progeny) smoking status.59 The
third column in Tables Al-A2 is a measure of the uncertainty—the Geometric Standard Deviation‘0-
~of the estimated risk coefficients (based on 10 rem exposures) in the fourth column.

Use of the geometric standard deviation to express uncertainties implies a lognormal
distribution for the uncertainties. Lognormal distributions are asymmetrical—they are skewed with
a hump at relatively low risk levels, and a long tail of probabilities that extends to higher risk
values. Figure Al shows a lognormal distribution, ploted arithmetically—indicating the typical
skewed shape. Because of this skewness, the mean of a lognormal distribution exceeds the
median (or 50th percentile) value. The fifth and sixth columns of the tables show calculations of
doubling doses based on the median and mean risk values respectively. It can be seen that there is
generally not a great deal of difference between these two interpretations of the risk data. I believe
the lower values for the doubling doses, based on the mean risks, better reflect the appropriate
values to be used in probability-of-causation calculations.

It is not completely straightforward to translate these data into doubling doses that are
applicable to the case of a continuous working lifetime exposure to individual workers. Among the
complications is that cancer incidence for most sites increases rapidly with age—generally in
Proportion to the fifth power of age or mMmore—just as the estimated “excess” risks relative risks per

*°Data for Tables A1-A2 were taken from Table 4F-1 in Comminee on the Biological Effects of Ionizing

Radiations, National Research Council, Health Ef to Low Level: izing i V.

National Academy Press. Washington, D.C., 1990. pp. 225-226. Dara for Table A3. on radon lung cancer risks.

were taken from page 103 of Lubin. J. H., Boice, 1D. Jr., Edling, C_, Hornung, R. W., Howe, G., Kunz. E..

Busiake R.A. Morrison. H. L. Radford. E. P., Samet. J. M., Tirmarche, M., Woodward, A.. Xiang, Y. S., and
ierce, D. A, < isk: i vsi i

normal Gaussian distribution is expected to be between the mean = 2 usual arithmetic standard deviations. Similariy
approximately 95% of a logmormal Population (a population in which the logarithms of the Parameter values have 2
normal Gaussian distribution) would be expected to fall in the range from geomemic mean/GSD2 and geometric
mean*GSD+,


Table 19
Percentage of Total Radiogenic Cancer Cases Occurring in Different Time Periods
That Would Be Eligible for Compensation

A. Requirement for 1 Doubling Dose--% Cases Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, All Times
Leukemia 0.453 0.210 0.215 0.000 0.879
Liver 0.020 0.015 0.013 0.013 0.061
* Bladder 0.020 0.015 0.014 0.015 0.063
Ovary 0.000 0.000 0.000 0.000 0.000
Stomach 0.000” 0.000 0.000 0.017 0.017
Kidney 0.000 0.000 0.000 0.000 0.000
Colon/intestine 0.000 0.000 0.000 0.000 0.000
Esophagus 0.000 0.000 0.000 0.000 0.000
Breast 0.000 0.000 0.000 0.000 0.000
Remainder 0.000 0.000 0.000 0.000 0.000
Lung 0.000 0.000 0.000 0.000 0.000
Total 0.49 0.24 0.24 0.045 1.02

B. Requirement for 1/2 Doubling Dose--% Cases Compensable

Before 1991 1991-2000 2001-2010 2011-2035 Total, Ail Times
Leukemia 1.29 0.597 0.728 0.000 2.61
Liver 0.18 0.136 0.088 0.122 0.53
Bladder 0.24 0.179 0.165 0.152 0.74
Ovary 0.01 “+ 0,005 0.006 0.003 0.02
Stomach 0.03 0.020 0.094 0.139 0.28
Kidney 0.00 0.000 0.000 0.000 0.00
Colon/Intestine 0.00 0.000 0.000 0.000 0.00
Esophagus 0.00 0,000 0.000 0.000 0.00
Breast 0.00 0.000 0.000 0.000 0.00
Remainder 0.00 0.000 0.000 0.000 0.00
Lung 0.00 0.000 0.000 0.000 0.00

Toral 1.74 0.94 1.08 0.42 4.18


the gene. Examining the whole database of documented P53 mutations for cancers at all sites, this
specific mutation was seen only six other times among 2472 cases at sites other than the lung.

Making the simplifying assumption that we can label all 29 cancers with P53 mutations
studied as “radon lung cancers” (in reality some fraction are likely not to have been related to the
radon exposure) the indicated enrichment of this mutation in this population of P53 mutants is
therefore

16 codon 249 AGG to ATG/29 "radon" cancers with P53 mutations

=186 fold (2)
1 codon 249 AGG to ATG / 337 non - radon lung cancers

If we were to modestly reduce the 29 P53 “radon” mutants to reflect the proportion likely to have
been actually caused by the radon progeny, considering the average dose in the group (about 1600
working level months), the calculated enrichment would be slightly larger.5! Moreover a further
adjustment could be made considering that there was undoubtedly some radon exposure history in
the 337 putatively “non-radon” lung cancers. The net result of this could indicate that this mutation
is for all practical purposes specific for radon exposure—if on further study with a couple other
high radon exposed groups, similar results are replicated.

There is unfornmately one other smaller study,52 of less-exposed uranium miners from
New Mexico in which the mutation was not found among 7 workers found to have P53 mutations.
The average exposure of the 7 workers bearing these mutations was 215 WLM. Because this dose
is less than the estimated doubling dose for radon-induced lung cancer for smokers (see Table A3,
Appendix A), it is possible that only a minority of the 7 lung cancers covered in this report were
actually causally related to radon.

One other aspect of the findings in the Taylor et al. (1994) paper that gives me pause is that
in order to be confident that this mutation to be truly related to radon, I would like to see a dose
response relationship—an increasing frequency of the mutation in workers with higher exposures.” _
This unfortunately is not apparent in the data (Table 21).

It should be noted that at the very high doses seen in this population, the most highly
exposed workers do not show proportional increases in the frequency of lung cancer in general as
a function of dose (the dose response relationship appears to approach a saturation level, possibly
in part due to high dose killing of cells that might otherwise be capable of carcinogenic

SUL we were use the radon potency estimates in Table A3 (see Appendix A) the correction would be very small. as

nearly all lung cancers would be expected to be caused by radon exposure,at the indicated levels.

2Vahakangas, K. H., Samet, J. M.. Metcalf, R.A, Welsh, J. A., Bennem. W. P., Lane. D. P.. and Harris. C. C.
“Mutations of p53 and ras Genes in Radon-Associated Lung Cancer From Uranium Miners.” Lancet. Vol. 339. pp.
576-580 (1992).


12

genetic factors that are likely to alter susceptibility to different classes of carcinogens.
If person were known to have a special sensitivity to radiation-induced cancers (say,
because of less efficient repair of radiation-induced DNA damage), it is possible that
their effective doubling dose for the resulting radiation-induced cancers would be
reduced. The recent publication of data on the gene responsible for Ataxia
Telangiectasia is a further case in point. This gene is important in detecting radiation
induced damage to DNA and inhibiting cell replication until repair enzymes can remove
the damage, and impaired forms of the gene are relatively common. One copy of a
mutant form of this gene is carried by about 1% of all people. These heterozygotes are
more sensitive to radiation-induced cell killing and mutagenesis. Current preliminary
epidemiology studies suggest that the heterozygotes have a threefold increase in their
relative risk of cancer in general, and a five-fold increased risk of breast cancer (the
breast is a relatively radiosensitive site in humans). If these findings are confirmed,
they would suggest larger relative increases in the risk due to specific identifiable
causes (such as radiation) and correspondingly lower doubling doses, because the
overall increases in incidence are relative to a background incidence that is related to

multiple carcinogenic agents.

«Category 4 innovations represent improvements in the recognition of non-agent-
specific individual differences in susceptibility to carcinogenesis—such as germ line
mutations in genes that contribute to the genetic pathway to cancer in specific tissues
(e.g., the retinoblastoma gene.) Although such mutations could be expected to
increase the absolute risk due to both radiation and other exposures in affected people,
there is no a priori reason to expect a specific change in relative risk, and therefore
doubling doses would be essentially unchanged on average.

Section 4.2 analyzes in some detail the most promising single category of innovation—
measurement of mutational spectra associated with radiation and other exposures as seen in specific
genes that are likely to be part of the molecular pathogenic pathway for specific cancers. Radiation
tends to cause a somewhat (3-5 fold) enhanced frequency of deletion mutations when compared to
other agents. In addition, there has been one report of a dramatic (over 100 fold) increase in the
frequency of one specific change at a particular DNA base among lung cancers in highly exposed

“ uranium miners.

In order for p53 sequence analysis for deletions and insertions to push a particular case

beyond the preponderance-of-evidence threshold, the tumor must:

A) Occur in a person who is between the original doubling dose for the tumor and the
revised doubling dose for tumors bearing p53 deletions or insertions

B) Carry a p53 mutation (The p53 analysis is potentially more helpful for cancers other
than leukemias in part because leukemias rarely carry p53 mutations.)

C) Carry a deletion mutation in p53 given the assumed 5 X multiplicative enrichment of
deletions in radiation-induced mutations (limited of course, by the upper bound of
100%).

As deduced earlier, only approximately 1%-4% of the total radiation induced tumors might
be compensable under a preponderance of evidence test without any p53 sequence analysis (with


78

Table 34
Final Tradeoffs Between Compensating “True” Radiogenic Cancers and the -’
Overall Ratio of Cases Compensated to Cases Caused

A. Conclusions Based on Total Cancer Cases

Threshold for Compensation % True Radiogenic Cancers Ratio of Total Cases to Ratio, Cases
(Fraction of a Doubling Dose) | Compensated, 1991+ ‘True Positive Cases © Compensated/Cases Caused
1 0.527 1.74 0.0092
0.5 2.43 2.35 0.057
0.2 8.40 3.75 0.32
0.1 16.4 6.04 0.99
0.075 21.2 154 1.60 oo

B. Conclusions Based on Total Cancer Deaths

Threshold for Compensation % True Radiogenic Cancers Ratio of Total Cases to Ratio, Cases
(Fraction of a Doubling Dose) Compensated, 1991+ True Positive Cases | Compensated/Cases Caused
1 0.721 1.73 0.0125
0.5 3.08 2.33 0.072
0.2 9.58 3.65 0.35
0.1 17.3 5.80 1.01
0.075 21.7 7.20 1.57


17

compensated under the current system. The estimates for cancer cases and cancer deaths (from all
causes) in DOE facilities that could be compensated is 670 and 385, respectively. Note that under
this option, about 75% of post-1991 radiogenic cancer cases will never be compensated. Thus this
option makes a significant tilt towards fairness to workers, but in no way compensates most cancer
in workers. The numbers of radiogenic cancer cases and deaths that are expected to appear after
1991 are 460 and 255, respectively. The actual numbers of radiogenic cancer cases and deaths
which get compensated under this option is 25% of these numbers, namely 111 and 65. Table ES-
5 summarizes our findings.

Table ES-5
Expected Consequences of Adopting 10% of a Doubling Dose as the Threshold
for Recovery

CANCER IN DOE OCCURRING OCCURRING NUMBER
WORKERS SINCE 1944 SINCE 1991 COMPENSATED
True Radiogenic 680 460 11
Cases (360-1000) (240-680) (60-165)
True Radiogenic 375 255 65
Deaths (250-500) (170-340) (43-87)
All Cancer Cases 670
(355-985)
All Cancer Deaths 380

(250-500)


Table 11 ;
Estimated Lethality Fractions for Different Cancer Sites (ICRP 199128, as Quoted
by Puskin and Nelson, 1995)

Cancer site Lethality fraction

Esophagus 0.95

Stomach : 0.90

Colon/Intestine 0.55

Liver 0.95

Lung 0.95

Bone 0.70 _
Skin 0.002 or sane caacers not ‘
Breast 0.50

Ovary 0.70

Bladder 0.50

Kidney 0.65

Thytoid 0.10

Leukemia (acute) 0.99

Remainder 0.71

8Intenati ional Commission on Radiological Protection. 1990. Recommendations of the International Commission
on Radiological Protection. Oxford: Pergamon Press: ICRP Publication 60; Ann. ICRP 21 (1991), Tables B-19
and B-20.


Table 32, Continued
Ratios of Total Compensated Cases/’True” Radiogenic Cancer Cases for Various
’ Thresholds for Compensation

E. Requirement for 7.5% of the Doubling Dose
Ratio of Total Compensated/’True” Radiogenic Cases
Total % Radiogenic Cancers 1991-2000 2001-2010 2011-2035 Total, All Times

Compensated 1991+ of all
Caused by 1944-1992 Exposures

Leukemia 2.94 4.31 4.07 4.19
Liver 1.26 4.89 4.89 4.89 4.89
Bladder 3.77 5.78 5.73 5.65 5.72
Ovary 0.29 6.85 6.47 6.42 6.59
Stomach 3.43 7.61 "6.45 5.45 6.46
Kidney 0.42 8.86 8.86 8.86 8.86
Colon/Intestine 5.37 10.54 9.82 9.67 9.94
Esophagus 0.32 9.90 9.88 10.05 9.94
Breast 0.21 10.44 10.20 10.06 10.20
Remainder 2.73 10.32 10.33 10.30 10.32
Lung 0.42 11.26 11.94 12.31 11.59

Total 21.2 7.50 7.34 7.83 7.54


Log(rem dose)

Log(rem dose)

Figure 6

1971--Lognormal Plot of Penetrating Ionizing Radiation
Exposures for DOE and Contractor Employees

1.0

7 ¥ = - 0.48926 +0.33888x R*2 = 0.947
0.85

064)

0.44

0.25

0.0 T T
1 2 3 4

1971 Z-Score
Figure 7

1974--Lognormal Plot of Penetrating Ionizing Radiation
Exposures for DOE and Contractor Employees

08
y = - 0.51629 +0.33102x  R*2 = 0.924
06 4 a
ioe
044
icf

024
0.0 ay r

1 2 a 4

1974 Z-Score


the 4% figure derived from the elimination of the DDREF). With the same baseline assumptions,
if there is a 5 fold enrichment of deletion and insertion p53 mutations in radiation-induced tumors,
then an additional 1.6-3.4% of the total radiation-induced tumors might be able to pass the
preponderance of evidence threshold with the p53 sequence analysis. Based on our earlier estimate
that a total of about 360-1000 extra cancers might have been initiated in DOE and contractor
employees by exposures over the 1944-92 period, then the number of potential beneficiaries from
the p53 technology in this group might be approximately 5-30, spread out over the next couple of
decades. Therefore, marvelous as the new technology is for understanding the molecular basis for
some tumors, there is no near term prospect that, by itself, it will solve the problem of under
compensation of radiation-induced tumors.

Estimated Effects Of Policies That Change The Threshold For
Recovery

Finally I consider the likely effects of changes in the probability of causation threshold for
recovery for the numbers and types of radiation-induced cancers (and “background” cancers) that
would be eligible for compensation. The overall policy-relevant findings from these calculations
are summarized in Figure ES-7 and Tables ES-3 and ES-4. Basically, there is a tradeoff between
the percentage of true radiogenic cancers compensated and the total expenditures made for both
“true” cases and indistinguishable “false positive” cases. If a policy decision were made that it is
desirable to compensate an equal number of cancer cases to those caused, this would be achieved
by setting the threshold for compensability at about 10% of the doubling doses. At 7.5% of the
doubling doses, the cases compensated would be about 60% greater than the cases caused. If the
threshold is set at a higher level than 10% of the doubling doses, the percentage of tue radiogenic
cancers compensated declines rapidly.

From a microeconomic and social efficiency perspective, the present system (which
requires that for workers to recover financially, they must receive at least the doubling dose for
their specific cancers) will fail to internalize the true social costs of operating DOE nuclear facilities
because only about 1% of the radiation-caused cancer is likely to receive compensation. If the goal
were to internalize social costs by ensuring that roughly as many cancers receive compensation as
are caused by workplace exposure to radiation, this could be done by paying full compensation to
all workers who get radiogenic cancer and are exposed to about one-tenth the doubling dose for
their specific cancer. Referring to Figure ES-7, Table ES-3 and Table ES-4, by allowing all
workers who can demonstrate that they received one-tenth the doubling dose, or greater, the
system would compensate about 25% of the radiogenic cancer cases (and 25% of deaths), rather
than the 1% of cases (and 1.4% of deaths) who develop cancer after 1991 and who could be


models.40 It should be recalled that these risk coefficients incorporate the potency reduction (and
corresponding reduction of the calculated probability of causation) embodied in the “Dose and
Dose Rate Effectivness Factor (DDREF) of 2. To calculate doubling doses without this factor, the
numbers in Table 15 should be divided by 2. A couple of other caveats are also in order:

* EPA has not chosen to list separately alll the specific sites (and tumor types within
sites) where radiation-induced cancers may occur—only, I believe, those where the
consensus documents they used as their sources provided comparable estimates of
potency. Attachment A provides another view of the basic cancer potency information
based on more aggregated cancer sites, derived principally from the BEIR V report.
The aggregation for example, treats all digestive system cancers as a group, leading to
an overall estimated doubling dose of slightly over 100 rem for men. The BEIR V risk
estimates do not incorporate a DDREF (although there is language in the report
favorable to the use of a 2-fold correction for low dose rates) and appear to indicate an
increasing relative risk with age for respiratory cancer, among other differences with
the EPA conclusions.

* Further analysis of some data has led other researchers to somewhat different
conclusions about particular cancer sites. In particular, Alexander“! has studied
combined epidemiological data from 10 U.S. worker populations, and concluded that
the combined dara indicate a modest but significant excess relative risk for brain cancer
(142 observed vs 123.3 expected). He reports that the overall 15% excess for
workers with a mean radiation dose of about 3.4 rem translates into an average relative
risk per rem of about 4%. This would imply that brain cancer is among the most
radiogenic cancers, with a doubling dose of about 25 rem. Based on the fraction of
expected brain cancer deaths to total deaths given in the Alexander report, the absolute
tisk of brain cancer per Gray would be about 2.7 X 10-2--far larger than any of the
other cancer sites (see Table 10 above). This absolute risk estimate would also lead to
an expectation of about 170 additional fatal cancers for the DOE/contractor worker

population exposed to about 6.4 X 105 person rems as of 1992.

* There probably should also be some allowance for radiogenic multiple myelomas.
‘These immune system cancers have been found to be significantly in excess in the
latest compilation of worker mortality results (Cardis et al., 1995, op. cit., note 36)
(the p value for the trend with dose was .037).

In general, workers will not have all their dosage delivered within the age ranges specified
in Table 15. Table 16 shows the expected percentages of dose surviving to various calendar years
that is likely to have been delivered in those age ranges. Table 17 then uses these age distributions
of delivered dosage for various years to calculate the doubling dosace thar are likely to be
applicable to “typical” workers who receive their personal dosage delivered in the time pattern for

40Thyroid, skin, and bone are not included because EPA chose to use absolute risk models for these sites. I believe
it does little harm to exclude them from these calculations ar this time because I have little reason to believe that the
effective doubling doses for these sites would significantly alter the picture of compensability inferred from the
remaining sites.

41 Alexander, V., “Brain Tumor Risk Among United States Nuclear Workers.” Occupational Medicine: State of the
Art Reviews 6:695-714 (1991).


4.2 Analysis of Recent Innovations in the Molecular Biology of Cancer, and

Potential Implications for the Legal Determination of Cancer Causation...... 46
4.2.1 Four Categories of Improved Information Resulting from Recent
Scientific and Technical Advances.........:cccccsssssssssrsceeesserecceee 46

4.2.2 Analysis of the Potential of “Category 1” Innovations—Approaches
for Subclassifying Tumors According to Specific Putatively Causal

Somatic Mutations ............ccsssccssssssssssescecesceeeceensesssccssesees 48
Categories of DNA Damage and Repair Processes, and Implications
for Mutational Spectra... cccsssscsscssccsssscscesseeseeee 48
Mathematical Theory .........:sccccccscscsscsssssssecceseeeecessssesseeonee 51
Data on the Enrichment of Deletions in Radiation-Induced
~ Montations ..ssssscccscccsssseesecconesssneccssseeessacecs aqeoeeeee 52
Conclusions—The Trajectory of Future Technical Developments.....63

. 4.3. The Prospect of Bayesian Modification of Individual Doubling Doses for
Cancer Cases in the Light of Uncertainties in the Individual Estimation of

5. The Likely Effects of Alternative Settlement Policies Which Lower the
Threshold for Recovery..........sssssssssccssssserscsssssencecsesecesenecneecsseseceeseee 65


Table 32
Ratios of Total Compensated Cases/’True” Radiogenic Cancer Cases for Various:
Thresholds for Compensation

A. Requirement for One Doubling Dose
Ratio of Total Compensated/’True” Radiogenic Cases

Total % Radiogenic Cancers 1991-2000 2001-2010 = 2011-2035 Total, All Times

Compensated 1991+ of all

Caused by 1944-1992 Exposures
Leukemia 0.426 1.718 1.694 1.706
Liver 0.041 1.858 1.858 1.858 1.858
Bladder 0.043 1914 1.909 1.903 1.909
Ovary 0.000 Pa
Stomach 0.017 1.887 . 1.887 : .
Kidney 0.000 .
Colon/Intestine 0.000
Esophagus 0.000
Breast 0.000
Remainder 0.000
Lung 0.000
Total 0.527 1.738 L715 1.884 1.740

B. Requirement for 50% of the Doubling Dose”
Ratio of Total Compensated/”True” Radiogenic Cases

Total % Radiogenic Cancers 1991-2000 2001-2010 = 2011-2035 = Total, All Times

Compensated 1991+ of all
Caused by 1944-1992 Exposures
Leukemia 1.325 2.279 2.221 2.247
Liver 0.345 2.426 2.426 2.426 2.426
Bladder 0.496 2.481 2.482 2.456 2.474
Ovary 0.015 2.681 2.654 2.616 2.657
Stomach 0.253 2741 2.625 2447 2.536
Kidney 0.000
Colon/Intestine 0.000
Esophagus 0.000
Breast 0.000
Remainder 0.000
Lung 0.000

Total 2.433 2.351 2.315 245 2351


Table 4.7 of the annual dosimetry report; for years before 1982, the analysis is based on the,
distributional analysis (Figures 4-12). ;

One other point related to dosimetry is worth mentioning here. The data for 1965-1986
reflect only “penetrating” radiation, whereas the 1992 data shown reflect total equivalent dosage
(including contributions from internal radionuclides and other sources that are not fully reflected in
the earlier data for “penetrating” ionizing radiation.) A very limited comparison of data at the high
end of the exposure distribution (1-2 rem) for 1992 suggests that there may be about a two-fold
difference between the two dose metrics for the most highly exposed people. A discussion with a
knowledgeable DOE health physicist! indicates that the ratio between total exposures and the
monitored “penetrating” doses is likely to be much less than 2 for the bulk of employees with
smaller exposures.

2.2.2 Data on Hanford Exposures for 1944-1989

As part of a long term mortality study, Buschbom and Gilbert (1993)!6 have extensively
documented the exposures of 44,156 workers first employed at the facility berween 1944 and
1978. The collective dose delivered in various years to the 37,012 workers with at least one
annual dose record are presented in Table 7 and Figure 13. The data show a pronounced peak of
collective exposure in the middle-1960’s. Over 90% of the recorded exposure occurred between
1952-1982; 58% occurred between 1958-1972.

These Hanford data also include a detailed characterization of the ages at which the
radiation dose was delivered. It can be seen in Figure 14 that most exposure occurs relatively
evenly in the prime work years between the ages of about 27 and 55.

158. Brooks, Office of Epidemiology and Health Surveillance. personal communication. April. 1995.
16Ses above, note 7.

17


Figure 19

Tradeoff Between Compensating True
Radiogenic Cancers and Equalizing the
Cases Compensated to Cases Caused

100 = 10
——— + ~+% True Positive Cases Comp
—~e-— Cases Comp/Cases Caused

10 3

At .1 doubling dose, cases
1 4 compensated are about equal
to cases caused, although only

% Truce Positive Cases Comp
Cases Compensated/Cases Caused

V6 of true cases are compensated. Ot
Under current policy,
total compensation is
about 1% of cases caused.
a] — 001

: 7 7 T T 7 T
0.05 0.15 0.25 0.35 0.450.55 0.65 0.75 0.85 0.95

Fraction of the Doubling Dose for Compensation

50% of the doubling doses compensates far less than 10%. The present system, of course,
compensates about 1%

Finally, Table 35 shows projections of the absolute numbers of cases we expect to be
eligible for compensation under our different scenarios for the three time periods when new
policies might be effective (that is, 1991 and after).

79


% Total Dose

Figure 14

Age Distribution of % Total Cumulative Dosage
Delivered to Hanford Workers, 1944-1989

3
24
a
4 a a
a
a
14 a
5
a
Ba
oj
0 5 ws T T T
10 20 30 40 s0 60 70

20