[vs

biologically effective than higher doses or acute exposures. To the contrary, studies of
exposure to alpha-radiation among miners suggest an inverse exposure rate effect (that is,
radiation effects were of larger magnitude when doses were accrued at lower dose rates).(3)

e therefore re e at the either _be equal to a

The factor used to adjust for systematic bias in DS86 gamma dose estimates should be
modified. The authors of the IREP model divide estimates of the excess relative risk per unit
dose by a factor with a value centered around 1.1 (with an uncertainty distribution ranging
from 1.0 to 1.4). This is not an acceptable approach, and is not supported by empirical
evidence. We recommend treating the DS86 doses as the current best estimate of the
survivors’ true doses (this factor be assigned a value of unity). If the authors of the radio
epidemiological tables wish to account for uncertainty in risk estimates due to uncertainties
in this component of dose, since it is not clear at this time whether these errors in dosimetry
would lead to inflation or attenuation of risk estimates, we would suggest that any adjustment
factor should have be centered around 1.0 with a symmetric error distribution.

Similarly, the IREP model assumes that neutron radiation dose estimates, as indicated by
DS86, systematically underestimate the true exposure of survivors. The authors of the IREP
model divide estimates of the excess relative risk per unit dose by a factor with a value
centered around 1.1 (with an uncertainty distribution ranging from 1.0 to 1.3). We

Current radiation protection guidelines are premised on a multiplicative model in which it
is assumed that ERR estimates derived from the LSS can serve as a quantitative basis for
worker protection. The same should be said for issues of worker compensation. We

t ly. iplicative a

A linear term is used in the IREP model to describe changes in sensitivity to the effects of
ionizing radiation with age-at-exposure over the entire human lifespan. It is known that
infants and young children are especially vulnerable to ionizing radiation when compared
to adults. For issues of workers compensation, however, we are concerned with variation
in sensitivity to the effects of ionizing radiation at adult ages (e.g., age 18+ years). We
recommend that the IREP model include categorical parameters for age at exposure, or else
limit analyses to a range of ages at exposure that is directly relevant to workers. We also
suggest that NIOSH conduct further investigation into the use of data from occupational
cohort studies to inform these radiation risk estimates. and understand variation in risk
estimates with age at exposure.

Page 12 of


(Procedures for Assessing Occupational Radiation Monitoring Data for Use in
Epidemiologic Studies, Crawford-Brown, Watson, Strom, Tankersley, ORAU, 1989).

» Uncertainties in the modeling parameters including assumption of “reference”
individual, uncertainties with the biokinetic parameters (f1, fu, etc.), breathing rates,
organ sizes, etc. These parameters vary among individuals and within an individual
over time (Evaluating Reliability of Biokinetic and Dosimetric Models and
Parameters Used to Assess Individuals for Risk Assessment Purposes, NCRP No.15)

» Uncertainty regarding the quality of the data reporting system. The best
measurement schemes can be negated if one has no confidence that the results were
correctly recorded (Paducah Exposure Assessment Project, Department of Energy,
PACE and University of Utah, January 2001).

» Uncertainty in measurement procedures (Paducah Exposure Assessment Project,
Department of Energy, PACE and University of Utah, January 2001).

» Uncertainties in the bioassay and air sampling data including sample size (collection
period, volume, etc.), chemical yield, interference from other radionuclides, counting
efficiencies, background, etc.

» Uncertainty in defining the expOsure scenario including the mode of exposure
(chronic or acute), the date or period of exposure, the knowledge regarding the source
term, the chemical form and the pajticle size (Paducah Exposure Assessment Project,
Department of Energy, PACE and University of Utah, January 2001).

e African Americans and other minorities may have been subjected to harsher working
conditions with far less extensive exposure monitoring. Subcontractors may have followed
different monitoring protocols when compared with M&O contractors.

e Uncertainty analysis for most dosimetric data at the DOE sites does not exist. Further, it is
unlikely that data will be available for quantifying the uncertainties for all parameters of
concern such as counting result, particle size, solubility, chemical yields, calibration error,
and biokinetic model parameters. There is wide variability between the results produced by
internal dosimetrists because of the varying use of “expert” assumptions,” even when
working with a given set of assumptions up front. In some situations, usually involving
potentially high doses, health physicists have used an independent review process for
purposes of quality assurance. (Mound Roundtable Meeting, 2001) Differences in dose
estimates of 100% are not unlikely.

Recommendations:

1. Independent auditing and oversight--To address this major and complex task, a strong

Page 3 of


radiation dose is 50% of more of the benefits potentially payable to a claimant or a group of
claimants (based on expected excess relative risk), it should not be deemed feasible to estimate dose.

Further, if data needed to estimate a dose with reasonable confidence does not exist-- a list
of this essential data should be developed--in the time periods when the claimant was employed in
a covered facility performing work functions that may have endangered their health, then it should
be deemed not feasible to estimate dose.

Cc. Definition of “sufficient accuracy.”

This should be defined by the degree of confidence in the estimates. If the data collected is
such that the calculated uncertainty at ~3 times the standard deviation (99% confidence interval) is,
for discussion purposes, 6-10 times the size of the mean, then NIOSH should conclude that the dose
cannot be estimated with “sufficient” accuracy (unless the mean dose estimate establishes eligibility).

D. Definition of “may have been endangered.”

EEOICPA (Section 3621(14)) requires dosimetry badging as a criteria for members of
Special Exposure Cohorts at 4 sites (Paducah, Portsmouth, Oak Ridge and Amchitka Island). In
drafting the legislation, dosimetry badging and term of employment was used as a proxy for whether
the worker “may have been endangered”. The purposes of using a dose badge as a threshold was a
crude way to exclude those who were presumed not to be at material risk. Specifically, the law
requires that the covered employee: - 7

“was monitored through the use of dosimetry badges for exposure at -
the plant of the external parts of employee’s body to radiation; or
worked in a job that had exposures comparable to a job that is or was
monitored through the use of dosimetry badges.”

The use of dosimetry as a proxy should be expanded to include workers who were monitored
through a radio bio-assay program or worked in a job that had exposure comparable to a job that is
or was monitored through the use of radio bioassay programs. (The DOE criteria for film badging
is the individual’s potential to receive 100 mrem occupational dose in a year.)

E. Development of an Administrative Process for Receiving and Rendering a
Determination.

What documentation should petitioners have to submit? Should there be a minimum size
to a Special Exposure Cohort? What happens to people in groups whose size that fall below the
minimum? Are there any classes of cases that automatically fall into the Special Exposure Cohort?

Petitions should be reviewed and decided in a 120 day period, with time extensions provided
only with the concurrence of the Advisory Board. The petitioner(s) should be afforded the right to
a public hearing, and to receive all of the documentation that went into a recommendation prior to
a draft decision or recommendation being sent to the advisory board. Petitioners should be permitted
to present their case to the Advisory Board. Petitions to the Secretary of HHS should be sent to the

Page 16 of


Board on Radiation and Worker Health. Issuance of an Interim Rule should not be used to
circumvent the consultation process, as this review is required by law, is essential to assuring
public confidence and providing a means for public involvement.

Section 3623(c) of the EEOICPA requires the President to establish guidelines to determine
whether a covered employee’s cancer was at least as likely as not caused by their occupational
exposure to radiation. The statute requires use of radio epidemiological tables (at the upper 99
percent confidence interval of the probability of causation), plus consideration past health-related
activities (such as smoking), information on risk of developing a radiation related cancer from
occupational exposure, and other relevant factors. Executive Order No. 13179 assigned this
requirement to the Department of Health and Human Service (“HHS”). - NIOSH will develop the
regulation. :

The radio epidemiological tables were originally mandated by the Orphan Drug Act, which
required that the HHS develop a systematic guide for determining the causal connection between
exposure to radiation and cancer. The original tables from 1985 were based on atomic bomb
survivor data at Hiroshima and Nagasaki. An update was prepared the National Cancer Institute-
Centers for Disease Control in May 2000. The quantitative basis for these updated radio.
epidemiological tables is, again, the study of atomic bomb survivors in Hiroshima and Nagasaki.
These updated tables (a) do not incorporate the results of epidemiological studies of workers, (b)
pertain to a select population of Japanese survivors of an atomic blast and subsequent depravation,
in a situation where radiation doses were primarily received as an acute exposure resulting from an
atomic bomb blast instead of a long term, low-dose exposures typically received over a working
lifetime, and (c) are based on a study that primarily concerns the effects of external exposures to
photons rather than intemal exposure to alpha particles which were the largest sources of radiation
dose at many of the DOE sites under consideration.

These tables should be revised to better account for the experiences confronted by
populations in the nuclear weapons complex. To obtain credibility, NIOSH should not promulgate
regulations or issue interim regulations umtil it has resolved the major deficiencies in the radio-epi
tables and the supporting interactive computer program (IREP).

A. The following parts of the IREP Model rely on questionable assumptions (citations are
referenced in end notes to this section):

1, The radio epidemiological tables assume that the effectiveness of radiation at causing cancers

decreases at low doses. For chronic exposures, the IREP model specifies a dose and dose-
rate effectiveness factor (DDREF) with a value that is distributed around 2, even though

Page 8 of


we

quality and use of respirators is a major assumption when estimating internal radiation dose.
One effective way to encourage worker participation is to work in cooperation with the
union(s), where present (similar to the methods used by the DOE in gathering data for
oversight reports at the three enrichment plants). Both open meetings and one-on-one
interviews should be used.

NIOSH should provide workers/claimants the opportunity to review the paper history
provided by DOE/contractor or vendor to NIOSH, and then compare this paper record
against their recollection. Where there is a divergence, workers should be afforded the
opportunity to provide an affidavit to NIOSH that records the knowledge of the worker and
the inconsistencies with the paper record. The affidavit should be included as part of the
administrative record in the case.

Where there is a succession of contractors/vendors, NIOSH must ascertain whether is there
achain of custody for the records. NIOSH must identify if there are gaps in the work history
for certain contractors. Where data gaps exist that cannot impair the ability to estimate dose
with sufficient accuracy, then NIOSH should flag data this major data gap as a possible
predicate for including such individuals or groups of workers in a special exposure cohort.
NIOSH needs to record and catalogue such findings or flags, as these have legal significance.
History must be evaluated for individuals where there is multi site exposure (i.e. both Y-12
and K-25) or multi facility (i.e., at Hanford PFP and PUREX). As part of the process, NIOSH
must insist through documentation that the DOE has looked for and produced all records (to
avoid loss of credibility when other records surface later on).

NIOSH should seek out historical data that may be available from DOE medical surveillance
grantees, and incorporate where applicable.

NIOSH Should Not Presume Adequacy of the Dose Record--Individual exposures
contained in the employee’s record, although potentially useful, should not be deemed a
“reasonable” estimate without first validating the dose against air monitoring data, radiation
surveys, thorough knowledge of work practices, analysis of the source term, and, if available
and reliable, co- located worker exposure data. For example, where individual records show
no internal dose, but the air monitoring or rad surveys show the presence of high alpha
contamination, then NIOSH needs to perform a job task analysis, conduct source term
analysis, look at air sampling data and breathing zone data, and estimate dose accordingly.
This scenario was identified at a major DOE site, casting doubt on the credibility of the
internal dose records. Likewise, at the uranium enrichment plants and certain vendor-
operated uranium processing sites, worker dosimetry did not account for uptakes of insoluble
Y-Class transuranics, leading to substantial missed dose in the paper record. Instead, the
paper record assumes almost exclusively soluble uranium compounds. This deficiency
caused historic dose estimates to be understated by at least an order of magnitude for
hundreds of workers.

Page 5 of


Nv

scientific underpinning and public credibility are essential elements of quality control and
quality assurance. (A good model that could achieve these objectives of a scientific and fair
process has been demonstrated at the Los Alamos National Laboratory in the context of
federal Clean Air Act radionuclide emission standards. This endeavor included an
independent technical audit that was reviewed by stakeholder experts relative to workscope,
ongoing analysis and final work product. The process yielded multiple benefits relative to
achieving and validating Clean Air Act compliance in a way that now has strong public and
laboratory support.) This same approach could be adapted to apply to the multi year NIOSH
dose reconstruction contract.

When contracting for dose estimation services, NIOSH should provide two levels of quality
control/quality assurance and a process to disqualify firms and individuals with a potential
conflict of interest.

Level I: Models for dose estimation should be set up by a competent consortium
working closely with NIOSH staff. These models and procedures can then be
implemented by other contractors, provided there is adequate QA/QC, so that
judgement calls can be made in advance on each group of workers. Models should
also be made available to the Advisory Board. .

Level II: A stakeholder technical review group with expertise in DOE’s radiation
dosimetry should be assembled and retained by NIOSH to provide QA on the work
of Level 1 contrattors. This group should be given full access to workers, the
models, and the data. Their analysis should also be made available to the Advisory
Board. Level 1 contractors would have to respond to questions and critiques of the
stakeholder technical review group and NIOSH would oversee this process.

Worker History is Essential to Reconstruct Dose —Worker history will need to be taken
with respect to job hazards, industrial processes, work practices, history of monitoring
(internal and external), isotopes known, location of external badges with respect to radiation
hazard, air monitoring (breathing zone and area), and the history of contamination control
practices. As part of the interviews, individual and group history will need to be taken to
determine respirator availability, quality of equipment with respect to the hazard (particle
size), equipment hygiene, and the extent to which such equipment was used. Assessing the

Page 4 of


advisory board upon receipt. A process must be established for the Advisory Board to evaluate and
make recommendations on expanding the special exposure cohort after receiving recommendations
from NIOSH, and input from the petitioner(s) if so requested. .

An added eligibility issue need to be addressed by NIOSH and DOL: Can a covered

employee (or their claimant) who was denied compensation after dose reconstruction be
subsequently included:as a member of a Special Exposure Cohort?

Page 17 of


10.

11.

Correction factors were used by DOE contractors which had the effect of reducing external
dose estimates—in some cases, to less than zero. Where there is doubt about the validity of
external dose badge data, NIOSH should seek to obtain the film badges and have them read
to cross check and validate. (Dose badge re-reading was performed at Rocky Flats where
neutron exposures were systematically underestimated, and dose estimates were revised at
Portsmouth after it was determined that a radiation dose was administratively “assigned”
when badges would not read out on automated reading equipment). Extemal dose readings
should not be used as a proxy for internal dose.

External Dosimetry—Neutron exposures were not accounted for at a number of DOE sites.
Examination of hard copies of early TLD glow curve data, radiation surveys, and records on
neutron poisons should be conducted, where appropriate, in determining if significant
neutron exposures existed. Dose badges were not necessarily located’on the parts of the
worker where individuals may have received dose. For example, workers may have had their
dose badges on a pocket that was shielded by lead when the face of person received intense
gamma emissions from a dissolution tank while inserting a fuel rod. A popular photo shows
a worker sitting on a uranium derby at Fernald when the dose badge is on his shirt, rasing
questions about the dose to the gonad. Workers who routinely carried “hot” samples from
their left hand may not have recorded an accurate dose when the dose badges were always
pinned to the right pocket. Interviews will assist in ascertaining the potential for missed
dose.

Group Dose Estimates-May Be Required--When adequate individual information is not
available, NIOSH should consider grouping like workers based on job category, department
or building information to assist in dose estimation.

Air Monitoring Data, if Available, Should be Used— Air monitoring data, where available.
should be used to estimate dose (using area and breathing zone data) or validate dosimetry.
In many cases this will require determining source term composition, since the air sampling
was likely not isotopic specific. In some cases assumptions which were made were
erroneous and could have great consequences with regard to internal doses. At the Mound
site in Ohio, all early data was assumed to be plutonium. The rationale behind this was that
it was the most conservative assumption. Subsequently, however. many of these areas were
determined to have actinium-227 and high fired plutonium oxides (both more restrictive
cases with regard to internal exposures). If source term composition cannot be validated for
each work activity over time, potentially significant uncertainties will result.

NIOSH Should Use Committed Dose Estimates--NIOSH should aggregate internal and
external dose into annual committed dose equivalents for use in the IREP model from the
date of exposure through the diagnosis of the illness.

Consultation with the Advisory Committee--Before the dose estimate regulations are
promulgated in either an Interim or Final Rule, they should be reviewed by the Advisory

Page 7 of


Government Accountability Project
1612 K Street, NW ® Suite 400

Washington, DC 20006 lou $2 Nar
202-408-0034 © fax: 202-408-9855 JUN 25 2001
Email: gap1@erols.com * Website: www.whistleblower.org
June 17, 2001 cy FOR YOUR
NFORM,
Larry Elliott ATION
NIOSH
Robert Taft Laboratories
4676 Columbia Parkway
Cincinnati, OH 45226

Dear Mr. Elliott:

In response to your letter of March 21, 2001 requesting input, attached please find
detailed recommendations to NIOSH related to the development of regulations to implement the
Energy Employees Occupational Illness Compensation Program Act of 2000. These
recommendations were developed through a workshop convened at the Government
Accountability Project on May 30, 2001 in Washington, DC involving representatives of
stakeholder groups who were involved in the development of the Act and experts on the issues of
science and policy related to dose estimation and the NCI-CDC radioepidemiology tables.

As part of the workshop, we invited Dr. Charles Land to present the recent update of the
Working Group to Revise the 1985 NIH Radioepidemiology Tables and respond to questions
about the assumptions and methods underlying the report.

Those participating included: Mark Griffon, a health physicist who has performed dose
assessments and risk mapping work within the DOE nuclear weapons complex; Arjun Makhijani,
a physicist with the Institute for Energy and Environmental Research who has done extensive
dose assessment work at Fernald and other weapons supplier facilities, Robert Alvarez with the
Institute for Policy Studies and a former Senior Policy Advisor to the Secretary of Energy; David
Michaels, associate professor at George Washington University and former Assistant Secretary
of Energy for Environment, Safety and Health; David Richardson, Department of Epidemiology
at University of North Carolina; Jordan Barab, consultant to the AFL-CIO and former senior
advisor to the Assistant Secretary of Labor for Occupational Safety and Health; Dan Guttman,
former Executive Director for the President’s Advisory Committee on Human Radiation
Experiments; Jaya Tiwari, Physicians for Social Responsibility; and staff from the Government
Accountability Project (GAP) including Louis Clark, Richard Miller, Bob Stix and Frank
Morales.

GAP advocates for whistleblowers within the workplace, and has dedicated significant
resources to investigating worker health and safety problems in the DOE nuclear weapons
complex. GAP has initiated a project to evaluate and communicate on the challenges and
opportunities facing the implementation of the Energy Employees Occupational Illness
Compensation Program Act of 2000. This landmark legislation presents significant challenges to


[vs

of neutrons at low doses or low dose rates, and that effects may be larger for neutron doses
accrued at lower rates.(8)

The IREP model assumes that there is a systematic underestimation of atomic bomb
survivors’ radiation doses that can be accounted for by dividing all DS86. doses by a factor
of approximately 1.1 (to account for bias in gamma dose estimates) and by a factor of
approximately 1.1 (to account for bias in neutron dose estimates). This is done in the radio
epidemiological tables by dividing all radiation risk estimates by a factor of approximately
1.1, and again by a factor of approximately 1.1. The naive reduction of these risk estimates
by a simple multiplier (and consequently a simple reduction in risk estimates) is an
unsupported approach to addressing problems of non-random measurement error in gamma
and neutron dose estimates.

The IREP model assumes that gamma radiation dose estimates, as indicated by DS86,
systematically underestimate the true gamma exposure of survivors. The authors of the IREP
model divide estimates of the excess relative risk per unit dose by a factor with a value
centered around 1.1 (with’an uncertainty distribution ranging from 1.0 to 1.4). This is not
an acceptable approach, and is not supported by empirical evidence. There is little evidence
that gamma doses in Nagasaki are underestimated by DS86; and errors in gamma dose
estimates for survivors in Hiroshima are unlikely to be proportional to total dose (for
example, errors may be-greater for survivors with low doses than for survivors with high
doses, as suggested by Maruyama et al., 1987). While we agree that errors in radiation dose
estimates are an important concern in the LSS study, the naive use of a single factor applied
to all dose estimates will not necessarily reduce bias (and may in fact increase the bias in
radiation risk estimates.)

Similarly, the IREP model assumes that neutron radiation dose estimates, as indicated by
DS86, systematically underestimate the true exposure of survivors. The authors of the IREP
model divide estimates of the excess relative risk per unit dose by a factor with a value
centered around 1.1 (with an uncertainty distribution ranging from 1.0 to 1.3). Again, errors
in neutron dose estimates may differ by city (as indicated by some empirical evidence), and
the magnitude of error may vary with DS86 dose; it has been noted that further investigation
of measurement techniques for evaluating the contribution of the neutron component of dose
in each city, and at varied distances, is needed to understand the error distribution.9) A
simple inflation of all doses by a fixed correction factor is an inadequate assumption about
the distribution of measurement error.

In applying epidemiological risk estimates from the study of Japanese atomic bomb
survivors to United States populations, NCI uses a model that leads to an estimate with a
value between the additive and multiplicative relative risk approaches. Current radiation
protection guidelines are premised on a multiplicative model in which it is assumed that
excess relative risk (ERR) estimates derived from the LSS can serve as a quantitative basis
for worker protection. The same should be said for issues of worker compensation. We

Page 10 of


analyses of the atomic bomb survivor data (which are the quantitative basis for these tables)
suggest that there is no reduction in effectiveness at causing cancer at low doses (indicating
a DDREF of 1). Furthermore, the radio epidemiological tables are applied to workers who
were exposed to alpha and neutron radiation as well as gamma radiation, and who will report
a dose in units of Sv. There is no empirical basis for a DDREF value greater than unity
when doses were due to high-LET exposures (in fact, the literature suggests a DDREF value
of less than unity for high-LET exposures).

Epidemiological analyses of atomic bomb survivors do not support the conclusion that the
dose-response relationship for solid cancers departs from linearity (that is, the atomic bomb
survivor study does not support a DDREF greater than unity for solid cancers).(1,2)
Analyses of leukemia among atomic bomb survivors have been interpreted as supporting a
DDREF greater than unity, although there is substantial uncertainty in estimates of the excess
relative risk for leukemia in the low dose range of the Life Span Study (LSS) data; and, when
broader groups of solid cancers are examined there is strong evidence of linearity. The
authors of the radio epidemiological tables largely rely on evidence from radiobiological
studies to support the decision to apply a DDREF value of approximately 2 for all chronic
and low dose exposures. This evidence from studies of chromosomal damage, and animal
experimentation (often evaluating non-cancer outcomes), is of questionable relevance to
radiation-induced cancer in humans. Epidemiological studies of populations other than the
Japanese atomic bomb survivors offer minimal support for a DDREF greater than unity.
Studies of breast cancers among tuberculosis patients who were exposed to multiple chest
fluoroscopies, for example, have ben considered in evaluations of the effect fractionation of
low-LET radiation doses. There is no evidence in these studies of a reduction: in’breast
cancer risk with protracted exposure.(3) Some have argued that a lack of a dose-related
excess of lung cancer among tuberculosis patients suggests a DDREF greater than unity for
that cause of death (4); however, necrosis and surgical removal of lung tissue among
tuberculosis patients (related to risk of lung cancer and duration of treatment) precludes any
clear interpretation of dose, or dose-rate, effects on ung cancer. (5.6)

Given the epidemiological findings of linearity in the atomic bomb survivor study, which is
used as the quantitative basis for the risk estimates in these tables, there is little support for
the decision to divide risk estimates by a factor of approximately 2 for purposes of
compensation.

In addition, the radio epidemiological tables are to be applied in decision making for workers
exposed to high-LET radiation as well as low-LET radiation. Doses will be reported in units
of Sv, combining different radiation types. There is little support for the assumption that low
doses of high-LET radiation, or chronic exposure to high-LET sources of radiation. are less
biologically effective than higher doses or acute exposures. To the contrary, studies of
exposure to alpha-radiation among miners suggest an inverse exposure rate effect (that is,
radiation effects were of larger magnitude when doses were accrued at lower dose rates).(7)
Similarly, a recent review concluded that there is no evidence of a reduction in effectiveness

Page 9 of


7. NIOSH Must Account for Uncertainty in Dose Estimates When Establishing a
“Reasonable” Estimate— Uncertainty and sensitivity analysis should be conducted on all
parameters, when possible. It is unlikely that data will be available for quantifying the
uncertainties for all parameters of concern (see above). Quality assurances (described above
in recommendation #1 (Level II)) which are transparent to the claimant and the public should
be included as part of the process. While the conclusions may be subjective in nature,
introducing the steps formally within the regulation will assure that all documentation is
scrutinized. -

As part of estimating uncertainty NIOSH should evaluate:

a. The completeness and appropriateness of the facility radiation monitoring program
over time along with the radiological hazards over time to ensure that the
instrumentation and methods employed (actual practices in the field) were capable
of measuring significant exposures. Additionally, consideration should be given to
the question of the extent to which the radiation hazards were identified with
acceptable precision and completeness. If these facts can not be determined than
there is a question as to whether the measured values are representative of actual
exposures.

b. Quantitative analysis of the uncertainty of the metabolic and dosimetric models
should be performed. All relevant models should be used for dose estimation
purposes. The mode] selected for the final dose calculation should be noted and an
explanation for the model selection should be provided.

c. NIOSH, or contractors should used validation and verification procedures to assure
the accuracy and completeness of the dosimetric records.

4. Determining What is a “Reasonable” Dose for DOL to Use in Ascertaining Eligibility—
If the average dose estimate does not render a claimant eligible for compensation, then
NIOSH should determine whether a claimant would be eligible if the estimate falls within
a range of uncertainty around the mean dose estimate. For example, NIOSH could modify
the IREP model to apply the upper 95% or 99% confidence interval of the dose estimate
instead of the average (mean) dose. However, if the uncertainties are so large (i.e., the 99%
confidence interval is 6-10 times greater than the average) then NIOSH may want to flag this
claimant as a candidate for the special exposure cohort. The reason is that it isn’t feasible
to estimate dose with “sufficient accuracy.” However, the fact that a dose can be estimated
without excessively wide confidence intervals, does not mean that the employee monitoring
program was appropriate and adequate for the hazards over time and may not be reasonable.

5. All isotopes and types of ionizing radiations should be considered. Where there is a
possibility of decay products affecting dose estimates, these should be taken into account.

Page 6 of


At many of the sites, internal dosimetry programs, especially prior to 1989, have been
determined to be inadequate for the detection of all potential significant internal doses.
Existing bioassay data, in many cases, will be difficult to use for estimating dose due to
insufficient information regarding critical parameters such as specific radionuclide of
interest, solubility, particle size, date of intake, type of intake (chronic or acute), etc. Often
only net counts are available with no indication of isotope, solubility, particle size, or
detection efficiency.

There are numerous examples within the DOE of radiation monitoring programs which
~ inadequately monitored for potentially significant exposures or did not monitor individuals
who were potentially exposed to significant levels of radiation. Several studies have revealed
inadequacies in historical radiation monitoring programs by comparing monitoring programs
(actual implementation of the documented programs) over time against the radiological
hazards over time. The inadequacies identified included: field practices not consistent with
procedures, significant hazards not being monitored, inadequate detection capabilities,
instruments were not calibrated, samples left unanalyzed, etc. Review of the personnel
dosimetry records alone would not have uncovered these cases of potentially significant
unmonitored exposures and would have resulted in an underestimate of dose. Testimony of
the General Accounting Office before the House Energy and Commerce Committee,
Subcommittee on Oversight and Investigations, March 17, 1994; Testimony of Richard
Miller before the House Energy and Commerce Committee, Subcommittee on Oversight and
Investigations, June 29, 1999; Portsmouth Mortality Study, NIOSH 1996; Paducah
Exposure Assessment Project Report, DOE, PACE and University of Utah, January 2001;
INEEL Risk Mapping Session, June 2001 ,Griffon; Evaluation of Protection, Bioassay, and
Dose Assessment Programs for Internal Radiation Exposure at the Nevada Test Site
Particularly With Respect to Three Exposure Situations, Prepared for REECO, French,
Skrable, September 30, 1995. (Also see: hearing records from Senate Government Affairs
Committee, March 23, 2000, Senate Government Affairs Committee, August 2, 1989, Senate
Health, Education and Labor Committee, May 15, 2000, DOE Tiger Team Reports.)

Even in the most ideal situations, the radiation dose reconstruction process is a very uncertain
science. This is true for dose estimates of both external radiation exposures as well as
internal radiation exposures, although the uncertainties in the internal dose estimates are
generally believed to be greater (Procedures for Assessing Occupational Radiation
Monitoring Data for Use in Epidemiologic Studies, Crawford-Brown, Watson, Strom.
Tankersley, ORAU, 1989). The uncertainties of concern regarding dose reconstruction
include:

» Appropriateness of monitoring program for the hazards.
» Uncertainties in the metabolic and dosimetric models used for calculating the dose.

These models rarely are based on a detailed understanding of how the radiation
interacts with the human body and often are formed on the basis of limited data

Page 2 of


The IREP Model should require the input of committed effective internal dose from the date
of exposure(s) to the date of disease, particularly for isotopes that have high energy potential
orare not soluble. Failure to use committed dose estimates in the IREP model will result in
the potential for significant amounts of missed dose.

Intermediate Term Recommendations--

6.

10.

Account for bias and uncertainty due to selective survival in the atomic bomb survivor
cohort. There is evidence selective survival was dose-related, such that people in the high
dose categories were more select than people in lower dose categories.(20) Such a pattern
is consistent with a healthy survivor effect in the cohort, and would lead to a downward bias
in radiation risk estimates.(21,22) We recommend that NIOSH develop and include a
correction factor for this source of bias and associated uncertainty.(23)

The decision to divide the lung cancer radiation risk estimate approximately in half for all
workers who ever smoked should be questioned. We recommend that NIOSH re-evaluate
the logic and justification for applying a factor which leads, at the median level, to the ERR
at 1 Sv for lung cancer among ever-smokers to be half as large as the estimate for never
smokers. This decision has little support from empirical evidence; as the authors of the report
acknowledge, much of the epidemiological evidence is consistent with a multiplicative
model. Apparently, the authors of the updated Tables have followed a precedent set in the
1985 radio epidemiological tables-- despite the lack of empirical evidence supporting this
approach. In contrast, as a basis for using a multiplicative model, one might draw a parallel
to the use of a multiplicative model for describing the effect of radiation with increasing age
at risk, which presumably is also associated with an increase in cancer due to the accrual of
damage from environmental exposures (and for which radiation effects are routinely
described as multiplicative). Furthermore, the authors show little sensitivity to the
misclassification that arises if workers are simply classified as ever or never smoked.

We recommend that NIOSH develop an approach to use data from occupational cohort
studies of nuclear workers to further inform risk estimation and to address potential variation
in risk estimates with age at exposure.

NIOSH should examine, in detail, the entire IREP model. This should include review of raw
LSS incidence data and DS-86 dosimetry data which was used to determine the model.

Segregate types of cancers where possible (i.e. do not lump cancers such as leukemia
together, rather, when data allows, break them into subgroups of various types of leukemia).

Citations

1. Pierce DA, Preston DL. Radiation-related cancer risks at low doses among atomic bomb

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response analyses. Washington, DC: National Institutes of Health, 1997: 57-68.

21. Shimizu Y, Pierce DA, Preston DL, Mabuchi K. Studies of the mortality of atomic bomb
survivors. Report 12, part II. Noncancer mortality: 1950-1990. Radiat Res 1999;152(4):374-89.
22. Stewart AM, Kneale GW. A-bomb survivors: factors that may lead to a re-assessment of the
radiation hazard. Int J Epidemiol 2000;29(4):708-714.

23. Little MP, Charles MW. Bomb survivor selection and consequences for estimates of population
cancer risks. Health Phys 1990;59(6):765-75.

TI. ESTABLISHING SPECIAL COHORTS

Under section 3623(b) of the EEOICPA provides that the President may, in consultation with
the Advisory Board, designate additional classes of workers for designation as a Special Exposure
Cohorts (SEC). The statute states: “[m]embers of a class of employees at a Department of Energy
facility maybe treated as members of the Special Exposure Cohort for purposes of the compensation
program if the President, upon recommendation of the Advisory Board of Radiation and Worker
Health, determines that-(1) it is not feasible to estimate with sufficient accuracy the radiation dose
that the class received, and (2) there is a reasonable likelihood that such radiation dose may have
endangered the health of the workers. Once in the Special Exposure Cohort, claimants receive an
irrebuttable presumption of workplace causation for one of a list of 22 covered cancers. We
strongly recommend that NIOSH convene a workshop to explore this issue in more detail before
issuing draft regulations.

- A. When The Process of Dose Estimation Indicates that a Special Exposure Cohort
Designation may be Triggered, the Rule Should Flag These Cass for Designation in the SEC
‘In the regulation, NIOSH should establish a procedure for reporting “flags” or indicators
that arise during the dose estimation process which suggest that a reasonable dose estimate is not
going to be feasible, including very large uncertainties in the estimate (greater than a rule of thumb)
or inadequacy of the data. At the point a flag goes up, NIOSH will need to review the case to
determine whether dose estimation may need to stop. If it appears fruitless to continue with a dose
estimate, NIOSH should notify claimants so they may be advised of the process to petition to be
included in a special exposure cohort. In the alternative, NIOSH should initiate the process of
evaluating a group for inclusion in the special exposure cohort. This will prevent claimants from
being denied based on the inability to estimate dose.

B. Definition of “feasibility.”

How long should a claimant have to wait to obtain a reasonable dose estimate? If it takes
more than 6 months from the time DOL refers the dose estimation work to NIOSH for NIOSH (or
its contractors) to acquire the data, interview workers and calculate estimates, prepare a dose
estimate for an individual or group, and have it reviewed for quality control/quality assurance by
NIOSH, then it should not be deemed “feasible” for purposes of the statute to estimate the dose.

Likewise, if the costs of dose estimation is so large relative to the group of eligible workers,
it may be a waste of resources to invest in dose estimates. For example, if the cost to estimate

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These recommendations analyze 3 major areas: Dose Reconstruction, the
Application of NCI-CDC Radioepidemiological Tables and IREP Model, and
Eligibility for the Special Exposure Cohort. They were prepared by the staff
of the Government Accountability Project (GAP), in consultation with David
Richardson, University of North Carolina, Mark Griffon, CPS
Environmental, Arjun Makhijani, Institute for Energy and Environmental
Research, Robert Alvarez, Institute for Policy Studies, Dan Guttman, former

‘Director of the President’s Advisory Committee on Human Radiation

Experiments, and David Michaels, George Washington University.
RECONSTRUCTING THE RADIATION DOSE

Section 3623(d) of the EEOICPA requires the President to establish, by regulation, methods

for arriving at reasonable estimates of the radiation doses received by an individual at their place of
employment, including employees who were not monitored, inadequately monitored or whose
records are missing or incomplete. Executive Order No. 13179 assigned this responsibility to the
Department of Health and Human Service (“HHS”). EEOICPA assigned responsibilities given to
HHS to the National Institute for Occupational Safety and Health (“NIOSH”). ~

The challenges to “reasonable” dose estimates outlined below should be addressed in regulations: :

There is inadequate internal dosimetry data on worker exposure to radiation at many sites,
and the quality and reliability is uneven, at best. Thus, there should be no presumption of
regularity in terms of adequacy in monitoring practice, unless otherwise demonstrated
through investigation. Dose records are frequently unreliable or inaccurate. Even up to the
current time frame, DOE radiation protection programs are marked by deficiencies,
according to audits by the Price Anderson Enforcement Program

Access to records is complicated by changes in DOE contractors and lack of a chain of
custody. DOE has also blocked researchers’ and workers’ access to records.

DOE vendors in most cases did not retain records, and in numerous cases, the plants no
longer exist and have been bulldozed. Access to some records will be complicated by
clearance issues related to the data of interest or the document which contains the data of
interest (e.g., K-25, Mound, Portsmouth, Paducah). Declassification of the documents is a
time consuming and costly process and it may cause problems with the interpretation of the
data of interest. Additionally, some records may have been transferred to other repositories.
This may further complicate the identification and recovery of pertinent documents. This
caused extensive delays in the Mound dose reconstruction project.

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the four agencies charged with its implementation if it is to benefit those it is intended to serve.
To this end, GAP looks forward to working with and supporting the efforts of NIOSH with its
major responsibilities.

As a follow-on to this set of recommendations, we would welcome the opportunity to
brief you and those charged with drafting regulations.

Sincerely,
Richard Miller
Policy Analyst

ce: Kathleen Rest, Acting Director, NIOSH
Workshop Participants


recommend that NIOSH apply the multiplicative approach for all cancers. The assumption
that a multiplicative relative risk model is valid has been argued in much of the literature on
radiation effects. Further, there is substantial scientific literature that examines the
application of estimates derived from the LSS under a multiplicative relative risk model to
other populations, such as patients exposed to medical irradiation that supports the
conclusion that a multiplicative model is appropriate for transferring epidemiological results
between populations.(10,11) Furthermore, the multiplicative model would give the benefit
of doubt to the claimant in a situation where there is scientific uncertainty.

Under the current radio epidemiological tables, the probability that a worker’s cancer was
caused by radiation tends to be lower for workers exposed at older ages than for workers
exposed at younger ages, in contrast to recent occupational epidemiological studies that
indicate the opposite pattern of association. Studies of US radiation workers suggest that
older adults are more vulnerable to the cancer causing effects of ionizing radiation than
young adults (6); most studies of other chemical and physical hazards find a similar pattern
of increasing vulnerability to hazards in later life.(12,13) .

For issues of workers compensation, we are concerned with variation in sensitivity to the
effects of ionizing radiation at adult ages (e.g., age 18+ years). The slope of the age-at-
exposure term may be predominantly influenced by the relatively high radiosensitivity of -
children, which is not relevant to the issues undér consideration-(14) Several ~
epidemiological studies (including worker studies) suggest that among sensitivity to the
carcinogenic effects of radiation may increase in adulthood with older ages at exposure
(suggesting a non-linear trend in sensitivity across the lifespan).(15-19)

A number of recent studies have concluded that there is convincing evidence that mortality
following the bombings of Hiroshima and Nagasaki left a select group of healthy survivors.
These analyses of radiation effects clearly pertain to a highly select population. Furthermore,
there is evidence that this selection was dose-related, such that people in the high dose
categories were more select than people in lower dose categories. Overall mortality rates, for
example, in the first 15 years after the bombing, are negatively associated with dose.(20)
Such a pattern is consistent with a healthy survivor effect in the cohort, and would lead to
a downward bias in radiation risk estimates.(21,22)

Recommendations to modify the IREP Model:

Short term recommendations—

In the face of the epidemiological findings of linearity in the atomic bomb survivor study,
which is used as the quantitative basis for the risk estimates in these tables, there is little
support for the decision to divide risk estimates for all chronic and low dose exposures by
a factor of approximately 2.0 for purposes of compensation. In addition, the radio
epidemiological tables are to be applied in decision making for workers exposed to high-LET
radiation as well as low-LET radiation. There is little support for the assumption that low
doses of high-LET radiation, or chronic exposure to high-LET sources of radiation, are less

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survivors. Radiat Res 2000;154(2):178-86.

2. Little MP, Muirhead CR. Curvilinearity in the dose-response curve for cancer in Japanese atomic
bomb survivors. Environ Health Per 1997;105(Suppl 6):1505-9.

3. Boice JD, Jr., Land CE, Shore RE, Norman RE,Tokunaga M, Risk of breast cancer following low
dose radiation exposure. Radiology 1979; 131(3):589-97.

4. Howe GR. Lung cancer mortality between 1950 and 1987 after exposure to fractionated
moderate-dose-rate ionizing radiation in the Canadian fluoroscopy cohort study and a comparison
with lung cancer mortality in Atomic Bomb survivors study. Radiat Res 1995; 142(3):295-304.
5. Davis FG, Boice JD, Jr., Hrubec Z, Monson RR. Cancer mortality in a radiation exposed cohort
of Massachusetts tuberculosis patients. Cancer Research 1989; 49(21):6130-36.

6. Richardson DB, Wing S, Hoffman W. Cancer risk from low level ionizing radiation: the role of
age at exposure. Occupational Medicine: State of the Art Reviews 2001; (16(2): 191-218.

7. National Research Council, Committee on Health Risks of Exposure to Radon (BEIR VI). Health
effects of exposure to radon. Washington, DC: National Academy Press, 1999.

8. International Agency for Research on Cancer. Ionizing Radiation, Part 1: X- and Gamma-
Radiation, and Neutrons. Lyon, France: LARC Press, 2000.

9. National Council on Radiation Protection and Measurements. Uncertainties in fatal cancer risk
estimates used in radiation protection. Bethesda, Maryland: National Council on Radiation
Protection and Measurements, 1997.

10. Little MP. Comparison of the risks of cancer incidence and mortality following radiation therapy .

for benign and malignant disease with the cancer risks observed in the Japanese A-bomb survivors.
International Journal of Radiation Biology 2001;77(4):43 1-64.

11. Little MP, Weiss HA, Boice JD, Jr., Darby SC, Day NE, Muirhead CR. Risks of leukemia in
Japanese atomic bomb survivors, in women treated for cervical cancer, and in patients treated for
ankylosing spondylitis. Radiat Res 1999;152(3):280-92. 7

12. Kaplan GA, Haan MN, Wallace RB. Understanding changing risk factor associations with
increasing age in adults. Annual Review of Public Health 1999; 20:89-108 -

13. Cohen HJ. Biology of aging as related to cancer. Cancer 1994; 74(7 Suppl): 2092-2100.

14. Richardson DB, Wing S, Hoffnann W. Cancer risk from low-level ionizing radiation: The role
of age at exposure. Occupational Medicine: State of the Art Reviews 2001;16(2):191-218.

15. Richardson DB, Wing S. Radiation and mortality of workers at Oak Ridge National Laboratory:
positive associations for doses received at older ages. Environ Health Perspect 1999;107(8):649-56.
16. Ritz B, Morgenstern H, Moncau J. Age at exposure modifies the effects of low-level ionizing
radiation on cancer mortality in an occupational cohort. Epidemiol 1999;10(2): 135-40.

17. Ritz B. Radiation exposure and cancer mortality in uranium processing workers. Epidemiol
1999;10(5):531-8.

18. Wing S, Richardson DB, Wolf S, Mihlan G, Crawford-Brown D, Wood J. A case control study
of multiple myeloma at four nuclear facilities. Ann Epidemiol 2000;10(3):144-53.

19. Kneale GW, Stewart AM. Factors affecting recognition of cancer risks of nuclear workers.
Occup Environ Med 1995;52(8):515-23.

20. Pierce DA. Dealing with imprecision in dose estimates for analyses of the a-bomb survivor data.
In: Ron E, Hoffmann FO, eds. Uncertainties in radiation dosimetry and their impact on dose-

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