Members of the Working Group:

Charles Land (chairman) and Ethel Gilbert

Radiation Epidemiology Branch

Division of Cancer Epidemiology and Genetics

National Cancer Institute

James M. Smith

Radiation Studies Branch

National Center for Environmental Health

Centers for Disease Control and Prevention

Consultants: 

F. Owen Hoffman, Iulian Apostoaei, Brian Thomas, and David C. Kocher

SENES Oak Ridge, Inc.

U.S. DEPARTMENT OF HEALTH 

AND HUMAN SERVICES

National Institutes of Health

National Cancer Institute

Report of the 

NCI-CDC Working Group 

to Revise the 1985 NIH 

Radioepidemiological Tables

Acknowledgements

The Working Group wishes to acknowledge, with gratitude, the service and help of the

following group of individuals who provided advice from different viewpoints during the

period in which the approach leading to the present report was being worked out. The advisors

participated in three meetings at NCI with the Working Group and its consultants, often at no

little inconvenience to themselves, and read and commented upon several early drafts. While

these individuals cannot be held responsible for the report, it is a better product because of the

insights they provided.

Pat Buffler, Ph.D., University of California (Berkeley) School of Public Health 

Lincoln Grahlfs, Ph.D., Atomic Veterans Association 

Lars-Erik Holm, M.D., Ph.D., Swedish Radiation Protection Institute 

Jerome S. Puskin, Ph.D., EPA Office of Radiation and Indoor Air 

Dan Schafer, Ph.D., Department of Statistics, Oregon State University

Seth Tuler, Ph.D., Social and Environmental Research Institute

The Working Group also wishes to express its appreciation for the thoughtful and thorough

formal review provided by the Subcommittee to Review the Radioepidemiology Tables of the

National Academy of Sciences/National Research Council, Board on Radiation Effects

Research, Committee on an Assessment of Centers for Disease Control and Prevention

Radiation Studies from DOE Contractor Sites, under the chairmanship of Professor William J.

Schull of the Human Genetics Center, School of Public Health, University of Texas Health

Sciences Center. As discussed in our report, the review, entitled A Review of the Draft Report of

the NCI-CDC Working Group to Revise the “1985 Radioepidemiological Tables,”resulted in a

number of beneficial changes in our approach which were implemented in the months

following our receipt of the review.

Table of Contents

I. Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

II. Background of 1985 Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

A. Congressional mandate and its execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

B. “Assigned share” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

C. Methodology used in the 1985 report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

1. Data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2. Dose-response models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3. Minimal latent period and distribution of risk over time following exposure . . . . . . . . . 9

4. Dependence of excess risk on sex and on age at exposure . . . . . . . . . . . . . . . . . . . . . . . . . . 9

5. Modification of ERR by other exposures and/or by host factors . . . . . . . . . . . . . . . . . . . . . 9

D. Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

III. Reasons for Update . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

A. New data, new findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

B. New availability of risk data at the level of incidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

C. Current application of the NIH report different from that originally contemplated. . . . 14

D. New attention to cancer sites less strongly associated with radiation exposure . . . . . . . . 15

E. New analytical approaches and ways of summarizing data . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

F. More attention to uncertainty and presentation of risk. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

G. Interactive computer program an alternative to tabular presentation . . . . . . . . . . . . . 16

H. Use of organ-specific equivalent dose, in sievert (Sv) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

IV. Description of the Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

A. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

1. Assigned share. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2. Sources of uncertainty. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

B. Sources of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

C. Choice of cancer types and approach to cancer types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

D. Estimation of risk coefficients and their statistical uncertainties. . . . . . . . . . . . . . . . . . . . . . 23

1. Solid cancers from the RERF tumor registry report data. . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2. Leukemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

3. Thyroid cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

4. Skin cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

5. Radon-related lung cancer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

E. Correction for random and systematic errors in A-bomb survivor dosimetry . . . . . . . . . . 30

F. Dependence of risk on dose and dose rate for low-LET radiation . . . . . . . . . . . . . . . . . . . . 32

G. Transfer of ERR from the Japanese to the U.S. population . . . . . . . . . . . . . . . . . . . . . . . . . . 33

H. Radiation effectiveness factors for different radiation types . . . . . . . . . . . . . . . . . . . . . . . . . . 35

I. Modification by epidemiological risk factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

1. General formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

2. Breast cancer: Interaction of radiation and age at first full-term pregnancy . . . . . . . . . 39

3. Lung cancer: Interaction of radiation dose with smoking history . . . . . . . . . . . . . . . . . . 40

4. Nonmelanoma skin carcinoma: Interaction between ionizing and ultraviolet 

radiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
J. Susceptible subgroups. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

K. Additional sources of uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

V. Features of the Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

A. This is an interim update . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

B. Similarities to the 1985 report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

1. Assigned share estimates based primarily on A-bomb survivor data . . . . . . . . . . . . . . . . 71

2. Cancer sites evaluated include most of those in the 1985 report. . . . . . . . . . . . . . . . . . . 72

3. Treatment of latent period. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

C. Important changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

1. Estimates were obtained for all cancer sites for which the calculations could be 

performed, not just those established as “radiation-related”. . . . . . . . . . . . . . . . . . . . . . . . 72

2. Assigned share estimates based on incidence instead of mortality data . . . . . . . . . . . . 73

3. Assigned share estimates based on new analyses instead of published risk estimates . . 73

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

(EAR) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

5. More attention to attained age. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

6. Different default assumptions for dependence of dose-specific ERR on exposure 

age and attained age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

7. Radiation dose response and adjustment for low dose-rate exposure . . . . . . . . . . . . . . . 74

8. Transfer of estimates between populations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

9. Biological effectiveness of different types of radiation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

10. Treatment of uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 

VI. Use of the AS Estimates and Their Uncertainties for Adjudication . . . . . . . . . . . . . . . . . . . . . 77

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Appendix A: Text of Congressional mandate and excerpt from Presidential statement. . . . . . . 85

Appendix B: DHHS Charter—Ad Hoc Working Group to Develop Radioepidemiological 

Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Appendix C: Bias associated with assuming statistical independence between estimates of 

dose response and estimates of modifying factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

Appendix D: Computational details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Uncertainty due to sampling variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

Phasing in the latency period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

The dose and dose-rate effectiveness factor (DDREF). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

Appendix E: Comparison of results from IREP with results from the 1985 NIH report 

and CIRRPC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

Appendix F: Interactive RadioEpidemiological Program (IREP) . . . . . . . . . . . . . . . . . . . . . . . . . . 105

Figures

Figure IV.F.1. Probability distributions used by different authors to describe subjective 

uncertainty for DDREF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Figure IV.F.2. Subjective discrete probability distributions for DDREF applied to chronic, 

low-LET exposures in the present report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

Figure IV.F.3. Variation by dose of DDREFacute, for fixed DDREFchronic and reference 

dose DL.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Figure IV.F.4. Log-uniform uncertainty distribution of reference dose DL. . . . . . . . . . . . . . . . . 62
Figure IV.G.1. Trapezoidal probability density function f(y) for the uncertain linear 

mixture coefficient y between additive (y = 0) and multiplicative (y = 1) models for 

transfer between populations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Figure IV.G.2. Cumulative distribution functions corresponding to the trapezoidal 

probability density distribution of Figure IV.G.1, and to two site-specific variations on 

that distribution.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Appendix Figure C.1. Distribution of cancer sites by correlation of estimated linear dose 

coefficient α with estimated attained age modifier δ (ordinate) and with exposure age 

modifier γ (abcissa).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Appendix Figure F.1. Initial screen of the IREP user interface . . . . . . . . . . . . . . . . . . . . . . . . . 106

Appendix Figure F.2. Main IREP input screen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Appendix Figure F.3. Dose input screen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

Appendix Figure F.4. Help file for the selection of radiation type . . . . . . . . . . . . . . . . . . . . . . 110

Appendix Figure F.5. IREP summary report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Appendix Figure F.6. Additional inputs for skin and lung cancers. . . . . . . . . . . . . . . . . . . . . . 112

Appendix Figure F.7. Radon exposure input screen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Appendix Figure F.8. Advanced features screen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

Appendix Figure F.9. Upload saved file screen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

Appendix Figure F.10. Choose file dialog box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

Appendix Figure F.11. Success!. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

Appendix Figure F.12. View model details screen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

Appendix Figure F.13. Intermediate results and importance analysis . . . . . . . . . . . . . . . . . 118

Tables

Table II.C.1. Cancer sites covered by the 1985 NIH report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Table IV.C.1. Solid cancer sites covered in the present report. . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Table IV.C.2. Hematopoietic cancers covered in the present report.. . . . . . . . . . . . . . . . . . . . . 46

Table IV.D.1. Computation of statistical uncertainty for ERR1Sv: Approach 1 as applied 

to specific solid cancer sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Table IV.D.2. Computation of statistical uncertainty for ERR1Sv: Likelihood profile 

quantiles for parameter α obtained by Approach 2 treatment of specific cancers for 

exposure age e ≥ 30 and attained age a ≥ 50. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Table IV.D.3. Computation of statistical uncertainty for ERR1Sv: Likelihood profile 

quantiles for parameter α obtained by modified Approach 2 treatment of lung cancer 

and cancers of the female genital organs other than ovary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Table IV.D.4. Computation of statistical uncertainty for parameter α: Likelihood profile 

distributions for leukemia excluding CLL, by exposure age and time since exposure. . . . . 51

Table IV.D.5. Computation of statistical uncertainty for parameter α: Likelihood profile 

distributions for acute lymphocytic leukemia, by exposure age and time since exposure. . 52

Table IV.D.6. Computation of statistical uncertainty for parameter α: Likelihood profile 

distributions for acute myelocytic leukemia, by time since exposure. . . . . . . . . . . . . . . . . . . . 53

Table IV.D.7. Computation of statistical uncertainty for parameter α: Likelihood profile 

distributions for chronic myelogenous leukemia, by sex and time since exposure. . . . . . . . 54

Table IV.D.8. Computation of statistical uncertainty for ERR1Sv: Thyroid cancer. . . . . . . . . 55

Table IV.D.9. Computation of statistical uncertainty for ERR1Sv: Basal cell skin carcinoma 

and other nonmelanoma skin cancer.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Table IV.D.10. Computation of statistical uncertainty for ERR1 wlm: Radon-related lung 

cancer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Table IV.H.1. Subjective uncertainty in radiation effectiveness factors: Photons and 

electrons.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Table IV.H.2. Subjective uncertainty in radiation effectiveness factors: Alpha particles. . . 66

Table IV.H.3. Subjective uncertainty in radiation effectiveness factors: Neutrons. . . . . . . . . 67

Table IV.I.1. Smoking-related adjustment factors for lung cancer ERR1Sv from low-LET 

radiation, additive interaction model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Table IV.I.2. Distribution of the U.S. population by smoking habit. . . . . . . . . . . . . . . . . . . . . . 70

Appendix Table C.1. Approach 1 validation of Approach 2 estimates of the 99% upper 

statistical uncertainty limits for AS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Appendix Table E.1. Comparison of CIRRPC and IREP: ERR values for site-specific 

cancers, exposure age 20, diagnosis at age 55 unless otherwise indicated.. . . . . . . . . . . . . . 100

Appendix Table E.2. Comparison of CIRRPC and IREP: ERR values for site-specific 

cancers, exposure age 30, diagnosis at age 55 unless otherwise indicated.. . . . . . . . . . . . . . 101

Appendix Table E.3. Comparison of CIRRPC and IREP: ERR values for site-specific 

cancers, exposure age 40, diagnosis at age 55 unless otherwise indicated.. . . . . . . . . . . . . . 102

Appendix Table E.4. Comparison of 99% screening doses (in cSv) of chronic photon 

radiation at > 250 keV according to CIRRPC and IREP, by cancer site and age at 

exposure, with diagnosis at age 55 unless otherwise indicated.. . . . . . . . . . . . . . . . . . . . . . . . 103

Appendix Table F.1. Radiation weighting factors recommended in 

ICRP Publication 60. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
I. Executive Summary

The legislative mandate for the 1985 Report of the NIH Ad Hoc Working Group to

Develop Radioepidemiological Tables provided for analyses of existing data linking cancer

risk to ionizing radiation exposure to facilitate the adjudication of compensation claims for

cancers diagnosed following exposure to ionizing radiation. The 1985 Working Group did this

by estimating “probability of causation” (PC) values, defined as 

risk due to radiation exposure

PC =

baseline risk + risk due to radiation exposure

for hypothetical instances of cancer following specific histories of radiation exposure. The

report has been used mostly by the Department of Veterans Affairs (DVA) as a guide to

adjudicating compensation claims for cancers diagnosed in persons who were exposed during

military service. The amount of new information about radiation-related cancer risk has

increased markedly during the 18 years since publication of the report, and there have been

revisions in the system of dose reconstruction used for the major source of epidemiological data

for estimating risk, the cohort of atomic bomb survivors studied by the Radiation Effects

Research Foundation (RERF) in Hiroshima and Nagasaki, Japan. The DVA requested the

Secretary of the Department of Health and Human Services (DHHS) to update the report, as

provided for in the original legislative mandate, and joined with the DHHS to support the

present effort by a Working Group of the National Cancer Institute (NCI) and the Centers for

Disease Control and Prevention (CDC). 

Noting that the National Academy of Sciences/National Research Council (NAS/NRC)

Committee on Biological Effects of Ionizing Radiation (BEIR VII-Phase 2) is expected to

complete within two years or so a comprehensive survey of the scientific data linking radiation

exposure to health effects in human beings, the NCI and CDC have undertaken to provide an

interim update of the 1985 report based on statistical analyses by the Working Group of readily

available data on cancer risk following radiation exposure, notably the 1958–87 Life Span

Study (LSS) Tumor Registry data on survivors of the atomic bombings of Hiroshima and

Nagasaki made available on computer disk by RERF. It is expected that a further update to the

present report will be made following the BEIR VII review. The Working Group has replaced

the tabular format of the 1985 report by an interactive computer program (IREP, for

“interactive radio-epidemiological program”) that eliminates nearly all of the computational

labor of estimating PC values and their uncertainties, and permits a more detailed and

comprehensive expression of the various components of the calculation and their uncertainties.

I. Executive Summary 1
It has been argued, notably by the NAS/NRC Oversight Committee that provided critical

advice to the 1985 NIH Working Group (NAS/NRC 1984), that the PC values calculated

according to the formula given at the beginning of this summary pertain to populations rather

than individuals, and that they “are not probabilities in the usual sense and are truly properties

of the group to which a person belongs, but in practice are assigned to the person for purposes

of compensation.” The Oversight Committee recommended a change in terminology, replacing

“probability of causation” with “assigned share” (AS) to emphasize the difference. The NIH

Working Group did not disagree, but continued to use “PC” because the term was already in

common use. The present Working Group feels that the Oversight Committee’s point is worth

repeating and has chosen to use “AS” throughout its report, although “PC” is probably even

more commonly used than in 1985. More generally, the Working Group emphasizes that the

AS values obtained using the report and its computer program represent a summary of scientific

findings about cancer risk following radiation exposure that may be relevant to adjudication of

individual claims, but that the report makes no claims regarding the influence of individual

factors that have not been extensively studied. 

It has also been argued by Greenland and others (Greenland 1988, 1999; Robins 1989a, 1989b;

Beyea 1999) that AS is a logically flawed concept, subject to substantial bias and therefore

unsuitable as a guide to adjudication of compensation claims in cases of possibly radiationrelated cancer. The conclusion of the present Working Group is that the argument may have

theoretical merit but, as a practical matter, is unpersuasive in the light of current information

about radiation-related risk. Scientific consensus about cancer risk following radiation exposure

is constantly evolving as new information is uncovered. This is a time of rapid developments in

our understanding of the carcinogenic process, and future developments may force fundamental

changes in our view of radiation carcinogenesis. For the present, however, the Working Group

feels that current models are relevant both to radiation protection and the adjudication of

claims for possibly radiation-related instances of cancer. Similar conclusions about the

arguments of Greenland and others were reached by an NAS/NRC subcommittee specially

formed to review an earlier draft of the present report (NAS/NRC 2000).

The focus of this report is on quantitative expression of uncertainty in AS, reflecting statistical

uncertainty about risk estimates and more subjective uncertainty about model assumptions

necessary to apply such estimates to the adjudication of compensation claims for cancer

diagnosed following radiation exposure in the United States. In the U.S., unlike the United

Kingdom where a voluntary Compensation Scheme for Radiation-linked Diseases allows for

proportional compensation for AS values as low as 20% (Wakeford 1998), adjudication of

claims revolves around the likelihood that AS may exceed 50%. When there is a policy bias

(“benefit of the doubt”) in favor of the claimant, focus is on upper credibility limits for AS

rather than on a central estimate. For example, present DVA policy is to award claims for

which the upper 99% credibility limit for AS is 50% or higher.

2 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Uncertainty, including the statistical uncertainty inherent in estimates obtained by fitting

observational data to theoretical models and subjective uncertainty inherent in model

assumptions, is the primary focus of this report. One of the many advantages of replacing tables

by an interactive computer program is that much more detail can be made easily available to

the user, including a complete representation of the uncertainty pertaining to a particular AS

estimate.

The 1985 NIH report dealt with 13 different cancer sites, for most of which there was strong

statistical evidence of a radiation dose response in human populations. However, lack of a

statistically significant dose response for a particular cancer type does not preclude a

compensation award based on an upper credibility limit for AS. For example, the upper 99%

credibility limit for AS can be greater than 50% even if the radiation dose response is not

statistically significant (or even if, in extreme cases, the point estimate is less than zero). The

present report is based on the working assumption that any type of cancer can, in principle, be

induced by radiation, and that the most important question concerns the magnitude of the risk

associated with particular exposures. In all, 27 different cancers and groups of cancers are

treated, including several cancer types not significantly associated with radiation dose. The

report does not include malignant melanoma and chronic lymphocytic leukemia, for which

adequate data were lacking. Lung cancer associated with radon exposure is given separately

from that associated with external exposure. The radon-related estimates are based on an

analysis using data from a 1996 report to the U.S. Department of Justice (DOJ 1996). A more

comprehensive analysis, based on the most authoritative risk estimates published by the

NAS/NRC BEIR VI committee (NAS/NRC 1999), was judged not to be easily adaptable for

AS purposes and to require more computational and staff resources than those available to the

present Working Group. Finally, this report, like the 1985 report, does not address the health

consequences of in utero exposure to ionizing radiation.

Treatment of uncertainty in the updated report is guided by that in the original report and by

more recent analyses, notably two publications of the National Council on Radiation

Protection and Measurements (NCRP): Commentary 14 (NCRP 1996), A Guide for

Uncertainty Analysis and Dose and Risk Assessments Related to Environmental Contamination, and

Report 126 (NCRP 1997), Uncertainties in Fatal Cancer Risk Estimates Used in Radiation

Protection. Essentially, the method involves calculation of an uncertain excess relative risk

(ERR = excess risk/baseline risk) for the cancer of interest, as a function of radiation dose for

each exposure. Other factors, represented by a series of randomly distributed factors which are

assumed to be statistically independent, depend on informed but nevertheless subjective

judgments from published reports of expert committees or by the authors of this report. They

are designed to contribute bias correction and expression of additional uncertainty to a Monte

Carlo simulation which provides a corrected ERR estimate, expressed as the product of all

factors, and its uncertainty distribution combining all sources of uncertainty. If more than one

exposure is involved, separate ERR values and uncertainty distributions are calculated for each

exposure and combined. The overall ERR is then transformed to obtain the AS:

AS = ERR/(1 + ERR).

Credibility limits for the AS are obtained as percentiles of its uncertainty distribution.

I. Executive Summary 3
The various factors contributing to the overall estimate, and its uncertainty, are as follows:

ERR per unit of dose (or dose plus dose-squared) and its statistical uncertainty distribution are

taken from the appropriate tabulated likelihood curve obtained as the final output of statistical

model fitting performed by the Working Group. For most cancers, the ERR per unit of dose is

allowed to depend on sex, age at exposure, and attained age (or, in the case of leukemia, time

since exposure). The analysis specifically includes uncertainties in the parameters that quantify

these dependencies. ERR per unit dose, as estimated, may be influenced by random and

systematic errors in A-bomb survivor dosimetry, requiring several uncertain bias correction factors.

Radiation dose for the claimant is entered by the user, either as a known value or as an uncertain

value with a user-specified uncertainty distribution. Doses received at low doses and dose rates

are adjusted by a factor (with uncertainty) known as the dose and dose-rate effectiveness factor

(DDREF), which may reduce the ERR per unit dose of gamma ray or other sparsely ionizing

radiation. The DDREF does not apply to neutrons, alpha particles, or other kinds of densely

ionizing radiation which are thought to have greater biological effects than sparsely ionizing

radiation and are weighted accordingly. A separate term, the radiation effectiveness factor (REF),

is used to express the differences in the biological effectiveness for various radiation types

relative to the risk per unit dose induced by exposure to either acute or chronic exposures of

high energy gamma radiation. As with the DDREF, uncertainty in the REF is expressed as a

subjective probability distribution of possible values.

Site-specific baseline risks for many cancers differ substantially between Japanese and U.S.

populations, and there is considerable uncertainty about how this affects risks resulting from

radiation exposure. An uncertain and complex factor is required for transfer of risk estimates from

A-bomb survivors to a U.S. population. Tobacco smoking is known to modify the carcinogenic

effects of radiation to the lung, also requiring an uncertain adjustment factor. Finally, an

optional uncertainty factor is included for additional, documented factors that may be justified

as pertaining to identifiable subpopulations.

The present report is considered to be an interim update of the 1985 NIH report. Like that

report, its AS estimates are based primarily on A-bomb survivor data. The present Working

Group has had the advantage of access to comprehensive cancer incidence data from a greatly

improved RERF Tumor Registry; these data are not only more recent than those used

previously but are based on more timely and more accurate diagnoses than those available from

death certificates. Incidence data are also more relevant to compensation claims for cancers of

delayed or low fatality. Direct access to RERF data allowed the Working Group to conduct its

own analyses directed at the needs of this report, including modeling of dose-response modifiers

such as age at exposure, and inclusion of cancer types not significantly associated with radiation

exposure. 

Unlike the 1985 report, the current report is based on linear dose-response models for all solid

cancers, with an uncertain DDREF to allow for the possibility that risk per unit dose decreases

with decreasing dose and dose rate. This approach is not necessarily better than the linearquadratic model approach used previously, but it is in accord with recent recommendations by

expert committees. Also, the present report treats relative biological effectiveness of densely

compared to sparsely ionizing radiation as an uncertain quantity, relying on a report

4 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
commissioned by the National Institute for Occupational Safety and Health (NIOSH). The

present report’s treatment of the problem of transfer of estimates between populations with

different baseline rates is an important change, and accounts for a large part of the total

uncertainty for several sites.

An early draft of this report was reviewed by a specially constituted subcommittee of the

National Research Council’s Committee on an Assessment of Centers for Disease Control and

Prevention Radiation Studies from Department of Energy (DOE) Contractor Sites, namely, the

Subcommittee to Review the Radioepidemiology Tables. That subcommittee, chaired by

William J. Schull, released its report entitled A Review of the Draft Report of the NCI-CDC

Working Group to Revise the “1985 Radioepidemiological Tables” on November 29, 2000

(NAS/NRC 2000). As a result of that review, the Working Group has made a number of

changes motivated by concerns expressed by the subcommittee about usability of the

interactive computer program (IREP) by nonspecialists, the omission of certain problematic

cancer sites from the draft report, and inclusion of other sites for which the association between

risk and radiation dose is not well established—e.g., it is based on sparse data yielding very wide

confidence bounds on dose-specific risk. The present report has also been influenced by recent

legislation (Public Law [P.L.] 106-398: Energy Employees Occupational Illness Compensation

Program Act of 2000) mandating the use of the 1985 NIH report, “as such tables may be

updated from time to time under provisions of Section 7(b)(3) of the Orphan Drug Act,” for

adjudicating claims related to cancers diagnosed in workers and former workers at Department

of Energy facilities with histories of occupational exposure to ionizing radiation.

As previously mentioned, this is an interim report which is expected to be modified as new

information on radiation-related risk becomes available. It is hoped that the form of the report

may prove to be of more lasting value. In particular, the IREP program is constructed to allow

new risk estimates and statistical uncertainty distributions to replace old ones, for new cancer

sites to be added, and for the treatment of other sources of uncertainty to be modified.

I. Executive Summary 5

II. Background of 1985 Report

A. Congressional mandate and its execution 

On January 4, 1983, the President of the United States signed Public Law 97-414 (known as

the Orphan Drug Act), an act to amend the Federal Food, Drug and Cosmetic Act to

facilitate the development of drugs for rare diseases and conditions, and for other purposes. This

legislation includes a provision (Section 7(b) of the bill) directing the Secretary of Health and

Human Services (DHHS) to “devise and publish radioepidemiological tables that estimate the

likelihood that persons who have or have had any of the radiation-related cancers and who

have received specific doses prior to the onset of such disease developed cancer as a result of

these doses.” The mandate included a provision for periodic updating of the tables. 

It may be noted that the section of P.L. 97-414 pertaining to the development of

radioepidemiological tables originally was introduced by Senator Orrin Hatch (Utah) as a part

of Senate bill S 1483, Radiation Exposure Compensation Act, to provide for damages due to

radiation exposure from nuclear weapons tests in Nevada. Since neither this bill nor the

companion House bill (H.R. 6052) was reported out of the respective committees, the section

relating to radioepidemiological tables was attached as an amendment to the Orphan Drug Act

which was passed by both houses and signed into law on January 4, 1983. The complete text of

Section 7(b) of the bill and an excerpt from President Reagan’s statement, on the occasion of

his signing the Orphan Drug Act, are given in Appendix A of the present report. 

Lead responsibility for the implementation of the enacted charge was assigned to the National

Institutes of Health (NIH) by the Assistant Secretary for Health, DHHS, who also requested

that a National Research Council (NRC) committee be formed to review the

recommendations of the NIH. Subsequently (August 4, 1983), the Secretary of Health and

Human Services approved the charter for an Ad Hoc Working Group to Develop

Radioepidemiological Tables to carry out this mandate. The text of the charter is included as

Appendix B. 

An Ad Hoc Working Group, chaired by Dr. J. E. Rall, Deputy Director for Intramural

Research, NIH, was established to carry out the work. The NIH contracted with the National

Academy of Sciences for the formation of an Oversight Committee in the NRC’s Commission

on Life Sciences, with the cooperation of the Institute of Medicine. The Oversight Committee,

chaired by Professor Frederick Mosteller of Harvard University, reviewed the data sources,

assumptions, and methods of the NIH Working Group and discussed wider issues regarding the

tables in the context of their intended and possible uses. The report of the Oversight

Committee was published in 1984 and the report of the Working Group was published on

January 4, 1985.

II. Background of 1985 Report 7
Subsequent to the 1985 publication, the Committee on Interagency Radiation Research and

Policy Coordination (CIRRPC) published a report on Use of Probability of Causation by the

Veterans Administration in the Adjudication of Claims of Injury Due to Exposure to Ionizing Radiation

(CIRRPC 1988). The CIRRPC report expanded on the uncertainty evaluation in the 1985

NIH report and provided screening doses for evaluating claims, which have subsequently been

used by the Veterans Administration. 

B. “Assigned share” 

The National Academy of Sciences committee charged with oversight of the 1985 NIH

radioepidemiological tables report (NAS/NRC 1984) objected to the use of the term

“probability of causation,” or “PC,” for the ratio, 

risk due to radiation exposure

PC =

baseline risk + risk due to radiation exposure

excess relative risk

=

1 + excess relative risk

The NAS committee pointed out that a negative ERR would result in a negative “probability”

(a defect easily remedied by specifying boundary conditions for PC) and, more seriously, that

the ratio applied to populations and not individuals and could not be interpreted as the

probability that a given cancer was caused by a given radiation exposure. They recommended

using the term “assigned share” as a more appropriate term, because the computed quantities

“are not probabilities in the usual sense and are truly properties of the group to which a person

belongs, but in practice are assigned to the person for purposes of compensation.” The present

Working Group is sympathetic to this view and is in large part guided by it.

C. Methodology used in the 1985 report

1. Data sources 

Baseline rates were taken from then-unpublished U.S. cancer incidence data for 1973–81 from

NCI’s Surveillance, Epidemiology and End Results (SEER) Program; these rates were tabulated

in the 1985 report by sex and age but not by race, and averaged over time. Site-specific average

excess rates were taken from the 1980 report of the NAS/NRC Committee on the Biological

Effects of Ionizing Radiation (BEIR III) (NAS/NRC 1980, Tables V-14 and V-16) and from

other sources, as shown in Table II.C.1 (page 11). Lymphoma, multiple myeloma, and cancers

of the prostate gland, uterus and cervix, testis, and brain specifically were not covered, because

of insufficient information and lack of a statistically significant dose response. Chronic

lymphocytic leukemia (CLL) was considered to be unrelated to radiation exposure.

8 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
2. Dose-response models 

Based on a review of the experimental and epidemiological literature, a specific linear-quadratic

model was assumed for all of the sites tabulated above, with the exception of breast and thyroid

gland, for which linearity was assumed. The linear-quadratic model for a single, acute exposure

to sparsely ionizing radiation (low-LET, for low linear energy transfer) was that preferred by the

BEIR III committee (NAS/NRC 1980, equation V-10), 

excess risk = α (D + D2

/1.16),

where D is absorbed tissue dose in Gy and α depends upon site, age at exposure, and sex. The

value of α was equal to the corresponding linear-model risk coefficient from BEIR III or other

source, divided by 2.5. Excess risk associated with a chronic exposure, or with exposure to

densely ionizing (highLET) radiation, was assumed to be linear in dose. For a chronic exposure

to low-LET radiation, the coefficient α was the same as for acute exposure; for acute or chronic

high-LET radiation, it was to be multiplied by a “relative biological effectiveness factor” to be

calculated on a case-by-case basis, presumably using information from sources other than the

report. Different exposures were considered to be additive in effect; that is, excess risks

associated with radiation exposures at different times were calculated separately and summed.

3. Minimal latent period and distribution of risk over time following exposure 

For leukemia and bone cancer, radiation-related risk was assumed to be distributed lognormally

over time following exposure, with a minimal latent period of 2 years. The lognormal

distributions differed by cancer type and subtype and (for acute leukemia) by age at exposure,

and were obtained by fitting original data. For other cancers, excess risk was assumed to be

proportional to age-specific baseline risk (i.e., ERR was assumed to be constant) beginning 10

years after exposure; it was further assumed that there was no risk up to 5 years following

exposure, and that ERR increased from zero at 5 years to its full value at 10 years according to a

symmetric, S-shaped cubic polynomial function of time.

4. Dependence of excess risk on sex and on age at exposure 

Following BEIR III, risk estimates were given separately by sex and age at exposure categories,

regardless of statistical significance for these factors. Original estimates were in the form of

excess (absolute) risk per unit dose, by sex and interval of age at exposure, averaged over a

follow-up time of 5–26, 10–30, 10–33, 10–34, or 10–35 years, depending upon site; this

corresponded to the data sets on which the estimates were based. Original estimates were

converted to dose-specific ERR by dividing estimated excess risk by baseline risk, i.e., obtained

as the life-table-weighted average of age-specific SEER rates over the same follow-up period.

Thus, for sites where the excess risk estimate was based on Japanese A-bomb survivor data, and

where U.S. and Japanese baseline rates differ, it was assumed that absolute risks, and not

relative risks, averaged over the period of observation, were the same in the two populations.

II. Background of 1985 Report 9
5. Modification of ERR by other exposures and/or by host factors 

The question of host factor modification was not addressed explicitly. Modification by other

exposures was discussed generally, but specific recommendations were made only for tobacco

smoking, in the case of lung cancer, and for radiation exposures other than those at issue.

Different radiation exposures were treated as additive in effect, as discussed in II.C.1 above.

Thus, the excess cancer rate corresponding to a second exposure was assumed to be

independent of the excess cancer rate corresponding to an earlier exposure. Smoking and lowLET radiation were also considered to be additive in effect with respect to lung cancer

causation, that is, the radiation-related excess rate was assumed to be independent of smoking

history. Thus, a smoker would have a lower excess relative risk associated with exposure than

an otherwise similar nonsmoker, because the nonsmoker’s baseline rate was smaller. However,

smoking and alpha radiation from inhaled radon decay products were considered to be

multiplicative in effect, i.e., computation of ERR for radon exposure did not depend upon

smoking history, since excess risk due to radiation and baseline risk were assumed to be

proportionally affected by smoking history.

D. Uncertainty

Sources of biased and unbiased uncertainties, and propagation of errors, were extensively

discussed in Chapter VII of the 1985 report. Biased uncertainties included overestimation of

(absolute) risk 5–14 years following exposure, and underestimation associated with use by the

BEIR III committee (NAS/NRC 1980) of the T65D dosimetry system (Kerr 1979) for

estimating dose-specific risk among A-bomb survivors. (By 1983–84 it was clear that T65D was

going to be replaced, but the new system, DS86 [Roesch 1987], was not yet in place.) Unbiased

uncertainty pertained to the use of baseline rates based on the entire region covered by the

SEER registry, modeling of risk as a function of age at exposure, assumptions about dependence

of risk on time following exposure, and assumptions about the curvature of the linear-quadratic

dose-response curve estimated in BEIR III. Other sources of uncertainty were also discussed, but

only those just noted were taken into account in computing combined uncertainty, represented

by a geometric standard deviation value and a bias correction factor, for different cancer sites

and years following exposure. The emphasis of the report was on point estimates;

recommendations were given for modifying tabulated AS values to account for bias and

uncertainty. 

CIRRPC (1988) also evaluated uncertainties in the PCs estimated in the 1985 publication.

This assessment treated most uncertainties in the same way as the 1985 report, except that an

evaluation of statistical uncertainty was added, uncertainty in evaluating age at exposure was

increased, and additional probability was assigned to a linear dose response. 

The CIRRPC assessment was addressed primarily at providing doses for screening claims, and

for this purpose, it was assumed that the claimant had a baseline risk at the 10th percentile of

the distribution of the baseline risks for the cancer of interest among all counties of the United

States. Neither the 1985 publication nor CIRRPC evaluated uncertainty resulting from the use

of the additive model for transferring risks from A-bomb survivors to the U.S. population. 

10 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
II. Background of 1985 Report 11

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

Site/cancer Source of coefficients Comments

Leukemia BEIR III Absolute risk coefficient for total leukemia 

multiplied by 0.68 for AL, 0.32 for CGL 

Bone and joint BEIR III Injected 224-Ra only 

Salivary gland Survey of published results Exposure ages 0–14 only 

(Land, 1984) 

Esophagus BEIR III 

Stomach BEIR III 

Colon BEIR III Exposure ages 20+ only 

Liver BEIR III Exposure ages 20+ only

Pancreas BEIR III Exposure ages 20+ only 

Lung Low-LET radiation: Exposure ages 10+ only 

Kato and Schull 1982; high-LET

radiation: Jacobi et al. 1985 

Breast Tokunaga et al. 1987 Linear dose response assumed; no effect of 

fractionation or protraction of dose 

Kidney & bladder BEIR III Exposure ages 20+ only 

Thyroid gland LSS incidence study Linear dose response assumed; no effect of 

(Parker et al. 1973) fractionation or protraction of dose 

III. Reasons for Update

A. New data, new findings

The original NIH report (NIH 1985) was written in 1984 and based on data available at

that time. Site-specific estimates of excess absolute risk (excess cases per 106

persons per

year per rad), by interval of age at exposure, were obtained from the BEIR III report

(NAS/NRC 1980), which relied largely on A-bomb survivor mortality data for 1950–74 but

also on other studies. The NIH report also used more recent risk coefficients from the A-bomb

survivor Life Span Study (LSS) mortality report for 1950–78 (Kato and Schull 1982) and sitespecific, incidence-based studies of leukemia (Ichimaru 1978), thyroid cancer (Parker 1973;

Ishimaru, personal communication), and preliminary data on female breast cancer (Tokunaga

1987) in the same population. To a lesser extent, the report surveyed studies of cancer mortality

in British patients given therapeutic radiation for ankylosing spondylitis (Smith and Doll

1982), lung cancer among Czech, Canadian, Swedish, and U.S. uranium miners (Jacobi et al.

1985), thyroid cancer in patients given X-ray epilation for treatment of tinea capitis (Ron and

Modan 1980), breast cancer among women given medical X-rays (Boice 1977; Shore 1977),

bone sarcoma among German patients treated for benign disease with injected radium (Mays

1983), and estimates of salivary gland cancer risk in various irradiated populations (Land 1986). 

In the succeeding 15 years, the dose reconstruction system for the A-bomb survivors has been

revised, and a large amount of new information has been obtained relating radiation exposure

to subsequent cancer risk. For example, the number of cancer deaths among members of the

cohort of atomic bomb survivors followed by the RERF in Japan increased from 3842 in

1950–74 (Kato and Schull 1982) to 7827 in 1950–90 (Pierce et al. 1996). Much of the newer

information pertains to cohort members exposed during the first and second decades of life: as

these survivors reached ages at which cancer rates normally become appreciable, the newer

data supported statistically stable risk estimates not obtainable previously. The same is in

general true for other exposed cohorts that include persons exposed at young ages. In the

original NIH report it was possible to estimate risk of radiation-related cancer following

exposure before age 10 and at ages 10–19 for leukemia and cancers of the female breast, salivary

gland, thyroid gland, and bone, while lung and stomach cancer risk estimates were available for

exposure at ages 10–19. For other sites covered by the report (esophagus, colon, liver, pancreas,

and urinary cancers), no calculations were done for exposure ages less than 20.

In addition, national and international committees have evaluated the newer data and used

them for risk assessment (NAS/NRC 1990; ICRP 1991; UNSCEAR 1988, 1994). Although

none of these evaluations takes account of the latest data, they are based on more recent data

than BEIR III and their existence and current use for radiation protection purposes underscores

the fact that the estimates used in the 1985 NIH report are out of date. The risk estimates

provided in ICRP Report 60 (1991) (based on the UNSCEAR 1988 report), in particular, are

widely used and are generally higher than those in the BEIR III report. 

III. Reasons for Update 13
B. New availability of risk data at the level of incidence 

Perhaps the most important recent development, however, has been a remarkable improvement

by the Radiation Effects Research Foundation (RERF) and its collaborators in Hiroshima and

Nagasaki of the LSS Tumor Registry to a high level of accuracy and efficiency (Mabuchi 1994).

The LSS registry draws on hospital records and physician notifications accessed by the local

tumor registries of Hiroshima City, Nagasaki City, and Nagasaki prefecture, pathology, and

hematology records through the Hiroshima and Nagasaki tissue registries and the Leukemia

Registry developed in the late 1940s and early 1950s, as well as the virtually complete system of

mortality notification and ascertainment of death certificate diagnosis that is the basis of the

LSS mortality studies of atomic bomb survivors. In general, incidence data, when they can be

obtained, are superior to mortality data because they capture information on cancers of low or

delayed fatality and because they are based on diagnostic information that is more detailed and

more accurate than death certificate data. 

C. Current application of the NIH report different from that originally contemplated

The circumstances of the legislation mandating the 1985 NIH report suggested that partial

compensation for claims of radiation-related cancer might be made on the basis of assigned

share estimates between 10% and 50%, whereas full compensation would apply for AS ≥ 50%.

Thus, the main graphical displays in the report show computed, “best-estimate” AS values

corresponding to organ doses of 1, 10, and 100 rad (0.01, 0.10, and 1.0 Gy), as a function of age

at exposure and/or time following exposure, and the reader is referred to the chapter on

uncertainty limits for instructions on how to compute them. In fact, the tort law concept of 

“at least as likely as not,” corresponding to AS ≥ 50%, continues to dominate the language of

claim adjudication, with the notable modification in some important applications that claims

may be winnowed out only if there is little or no reasonable doubt that the true value of the

AS is less than 50%. For example, the Department of Veterans Affairs (DVA) screens out

claims for which the 99% upper limit for the AS is less than 50% (Dr. Neil Otchin, personal

communication). This development suggests that any revision of the 1985 report should seek a

more nearly complete expression of the scientific information related to risk of cancer following

exposure to ionizing radiation, as it applies to particular cases. In other words, emphasis should

be placed upon a comprehensive expression of uncertainty, and one that is easily accessible to

the user.

At a fairly late stage in its development, the present report was overtaken by events in the form

of the Energy Employees Occupational Illness Compensation Program Act (EEOICPA) of 2000

(Public Law 106-398). That law established new programs for assisting nuclear weapons

production employees who have work-related illnesses. These programs include a federal

program, administered by the U.S. Department of Labor (DOL), for eligible employees with

chronic beryllium disease, silicosis, and possible radiation-related cancers. The act requires that

adjudication of claims for radiation-related cancers be based on the radiation dose received by

the claimant (or a group of employees performing similar work) at such facility, and on a

determination that a probability of causation (assigned share) value of 50% or greater is

consistent with the appropriate upper 99% confidence limit in the radioepidemiological tables

published by the NIH in 1985, “as such tables may be updated from time to time under

provisions of Section 7(b)(3) of the Orphan Drug Act.” Thus, the decision rule used by the

DVA to screen (and, in practice, to award) claims has now been accorded the force of law. 

14 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
The CDC’s National Institute of Occupational Safety and Health has been charged with 

(1) providing information to the DOL on estimated radiation doses for claimants’ past

occupational exposures to radiation, in cases where exposure measurements are unavailable,

incomplete, or of poor quality (dose reconstruction), and (2) providing advice on the scientific

guidelines that DOL would use in determining whether it is at least as likely as not that an

energy employee’s cancer was caused by occupational exposure to radiation (determining the

assigned share or probability of causation). The NCI-NIH Working Group, while working to

respond to the recommendations of the NAS/NRC review committee, has had the benefit of

discussions with members of the NIOSH Office of Compensation Analysis and Support.

Mindful of its responsibilities under the EEOICPA of 2000, the NIOSH group made a number

of suggestions for the revised report to address specific NIOSH requirements. These suggestions,

and the Working Group’s responses, are discussed in the body of the present report. 

D. New attention to cancer sites less strongly associated with radiation exposure 

The cancers covered by the 1985 NIH report were those for which a statistically significant

radiation dose response had been demonstrated in one or more major analyses. Statistical

significance is equivalent to having a positive lower confidence limit, at a certain confidence

level, for dose-specific excess relative risk, and therefore also for the AS. The list of cancers

fitting this criterion is not greatly different today, but it is clearly possible for an upper

uncertainty limit for the ERR to be greater than 1, and hence for the corresponding AS limit to

be greater than 50%, even when the estimated ERR is not significantly greater than 0. Thus a

wider range of cancer sites is of interest than that covered by the 1985 report.

E. New analytical approaches and ways of summarizing data 

The 16 years since the 1985 NIH report have seen enormous advances in accessible computing

power, particularly at the level of personal computers, and the development and refinement of

statistical packages for risk analysis. An important consequence is that statistical modeling of

radiation dose response and its modification by factors such as gender, age at exposure, time

since exposure, age at observation for risk, smoking history, and reproductive history can be

carried out far more quickly and easily than before. New analyses, tailored for particular

applications like the subject of this report, are easily accomplished, especially since the most

comprehensive LSS mortality and incidence data are available from the RERF Web site, at

http://www.rerf.or.jp. These data, grouped to protect the privacy of individual survivors, are

those used in the 1950–90 mortality report (Pierce et al. 1996) and the cancer incidence

reports based on RERF Tumor Registry and Leukemia Registry data through 1987 (Thompson

et al. 1994; Preston et al. 1994). The AMFIT algorithm for Poisson model regression, part of

the Epicure statistical package (Preston et al. 1991), is particularly well suited for cohort-based

analyses of radiation-related risk and has become closely identified with analyses of A-bomb

survivor data in particular. These statistical approaches were used, for example, to develop the

models used in the BEIR IV, V, and VI reports (NAS/NRC 1988, 1990, 1999). 

III. Reasons for Update 15
F. More attention to uncertainty and presentation of risk 

The 1985 NIH report presented illustrative graphs of assigned share estimates, tables of

coefficients for various components needed to compute assigned share, and algorithms for

calculating assigned share from these coefficients for arbitrary values of radiation dose, age at

exposure, and time following exposure. Statistical and other sources of bias and uncertainty

were extensively discussed in a separate chapter, and estimates and algorithms were provided for

calculating “credibility limits” (based on statistical and subjective measures of uncertainty) for

estimates of assigned share. In the intervening years, additional attention has been paid to

quantification of uncertainty in applications to radiation-related risk, and new approaches for

evaluating uncertainty have been developed (NAS/NRC 1990; NCRP 1996, 1997; EPA 1999).

It seems clear that considerations of uncertainty are central to radiation protection and

adjudication of claims for compensation in cases of disease following radiation exposure. It is

equally clear that the concept is complex and not easily applied by nonspecialists, and would

benefit from a more user-friendly approach as indicated by the following example:

The major U.S. government user of the NIH report to date is the Department of Veterans

Affairs (DVA) which in 1985 asked the Committee on Interagency Radiation Research and

Policy Coordination (CIRRPC) of the Office of Science and Technology Policy, Executive

Office of the President, to provide guidelines on how the NIH report might be used credibly to

assist in adjudicating a veteran’s claim of radiation injury. The Science Panel of CIRRPC

interpreted the DVA’s charge as one of quantifying the likelihood that a specified “probability

of causation” (assigned share) in the NIH report would not be exceeded, with an a priori chosen

level of credibility (CIRRPC 1988). Their solution was to tabulate, by type of cancer, gender,

age at exposure, and other relevant factors, the organ doses at which the upper AS credibility

limit was 50% (“as likely as not”) at credibility levels 90%, 95%, and 99%, respectively. The

solutions were proposed as possible screening doses for specific cancers, exposure ages, and times

following exposure. The screening procedure was biased toward ensuring that a marginal claim

by an exposed veteran would not be rejected at this stage of consideration, and it was assumed

that a claim not eliminated by this screening process would be adjudicated on its merits, taking

into consideration the many factors that pertain to an individual claimant, including the AS

value calculated according to the NIH report.

G. Interactive computer program an alternative to tabular presentation 

The tabular presentation of the 1985 report allowed users to look up tabulated coefficients

appropriate to particular claims and to calculate assigned share using these coefficients

according to simple algorithms presented in the report. Increased computing power has made it

possible to calculate assigned share and its uncertainty directly, for individual claims, from the

particulars of exposure history, disease, and other relevant factors. This results in quicker, easier,

and less error-prone computation, with tabular and/or graphical output options.

16 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
H. Use of organ-specific equivalent dose, in sievert (Sv)

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

energy per kilogram of tissue), instead of the quantity used in the 1985 report, the rad (1 Gy =

100 rad; equivalently, 1 cGy = 1 rad). Equivalent dose, which incorporates weighting factors to

represent the biological effectiveness of different types and energies of radiation, is expressed in

sievert (1 Sv = 100 rem, where the rem is the quantity used previously). For irradiation by

high-energy photons, such as exposure to gamma rays from the atomic bombings of Hiroshima

and Nagasaki, the biological effectiveness is taken to be unity, by definition, and dose and

equivalent dose are numerically the same (e.g., 5 cGy = 5 cSv). For other types of radiation,

however, dose-specific risk may be the same, higher, or lower. In such cases, a weighting factor

may be used in calculating equivalent dose for purposes of radiation protection. Weighting

factors recommended by the International Commission on Radiological Protection (ICRP

1991) assign unit weights to photons and electrons, weights of 5, 10, or 20 to neutrons

depending upon energy, and 20 to alpha particles, fission products, and heavy nuclei (Appendix

Table F.1, page 117).

In the present report and the interactive computer program (IREP) developed to replace the

tables in the 1985 report, it is assumed that the starting point for calculation of AS is a single

value or set of values of tissue-specific, weighted (or equivalent) dose expressed in Sv, using the

ICRP radiation weighting factors. The purposes of the present report are, however, somewhat

different from those of radiation protection, and call for a different approach to calculation of

equivalent dose. The approach used here is, first, to extract the absorbed tissue dose in Gy from

the input value of radiation-specific, equivalent dose in Sv, using the appropriate ICRP

radiation weighting factor; and second, to recompute equivalent dose using a different, and

uncertain, weight as specified by Kocher et al. (2002) and summarized in Section IV.H of the

present report. The value of the new equivalent dose differs from the starting value in that the

weight used (called a “radiation effectiveness factor” or REF) is expressed as an uncertain

quantity with a subjective probability distribution based on radiobiological data, as opposed to a

point value of a standard quality factor or radiation weighting factor used in radiation

protection. Thus, the calculation of AS specifically takes account of the (uncertain) biological

effectiveness of each radiation type and energy of concern.

III. Reasons for Update 17

IV. Description of the Approach

A. Overview 

1. Assigned share

Assigned share (AS) for an individual who was exposed to radiation, and who has been

diagnosed with a cancer thought to be related to such exposure, is given by 

AS = ERR/(1 + ERR) 

where ERR is the excess relative risk associated with the exposure(s) of interest. ERR is a

function of radiation dose (possibly accumulated over a number of exposures), age(s) at

exposure, type of cancer, age at diagnosis, gender, and other factors possibly related to baseline

and/or radiation-related risk.

As previously mentioned (Section II.B), the Working Group is sympathetic to the view

expressed by the 1984 Oversight Committee report (NAS/NRC 1984), that the ratio, called

“probability of causation” or “assigned share” (which we prefer), applies to populations and not

individuals and cannot, for lack of detailed information and the ability to understand its full

implications, be interpreted as the probability that a given cancer was caused by a given

radiation exposure. The Working Group views assigned share as an actuarial concept, useful for

summarizing the existing scientific evidence bearing on the likelihood that prior radiation

exposure might be causally related to cancer occurrence under various circumstances, and

which may in fact be the best available information pertaining to a particular case. Similarly, a

statistical life table is a useful device on which to base social contracts such as a life insurance

contract. A life table is based on observed frequencies of deaths by age in a large population

and, with detailed information, it is easy to define and easier still to imagine subgroups for

which life-table predictions based on the larger population may perform poorly. Yet these

departures do not detract from the practicability of basing decisions about annuities,

insurability, and insurance rates on life-table predictions in the absence of such detailed

information.

2. Sources of uncertainty 

New emphasis is placed on uncertainty analysis (NCRP 1996), specifically, estimating an

uncertainty distribution for the ERR (and associated AS) as opposed to a single point estimate.

ERR is expressed as the product of several factors, which are assumed to be statistically

independent. Each factor is uncertain and is specified by an uncertainty distribution. The

specified uncertainty distributions depend to some extent on subjective judgments by expert

committees and by the authors of this report. The overall uncertainty distribution of the desired

ERR is obtained by Monte Carlo simulation. These simulations involve sampling from the

uncertainty distributions for each of the factors (or sources) included and are similar to those

conducted by the Environmental Protection Agency (EPA 1999) and the National Council on

Radiation Protection and Measurement (NCRP 1997). A computer program, here called IREP

IV. Description of the Approach 19
(for interactive radio-epidemiological program), has been developed to conduct these

simulations individually for any desired application, taking account of specific characteristics of

both the exposure and of the exposed individual. 

The sources of uncertainty that are included are listed below, with details given in the

sections that follow and in the appendices. 

1. Sampling variability in the estimated ERRs. Statistical analyses of A-bomb survivor cancer

incidence data were performed to estimate the ERR and its associated statistical uncertainty for

each type of cancer. Dose response was assumed to be linear for solid cancers, after doseresponse analyses found no evidence of departure from linearity. For leukemia, dose response

was assumed to be linear for densely ionizing radiation such as neutrons and alpha particles, and

for sparsely ionizing radiation (e.g., gamma ray, X-ray) delivered at low dose rates, but quadratic

for acute exposures to sparsely ionizing radiation. For most cancer types, the dose response was

allowed to depend on sex, age at exposure, and age at diagnosis. Details are given in Section

IV.D and Appendices C and D. 

2. Correction for random and systematic errors in A-bomb survivor dosimetry. The statistical

uncertainty discussed in the preceding paragraph pertains to assigned share for a member of the

LSS sample or for another A-bomb survivor whose radiation dose was estimated by the same

methodology. It would not pertain exactly to another irradiated population with identical

baseline cancer rates, because any biased or unbiased uncertainties in the reconstructed radiation

dose estimates for the A-bomb survivors would not apply to the second population. Thus, risk

estimates are adjusted for random errors in the DS86 doses (Roesch 1987) assigned to individual

A-bomb survivors and also to several potential sources of systematic bias in these doses. The

latter include systematic underestimation of gamma rays for Hiroshima survivors, uncertainty in

the weighting factor for neutrons, and uncertainty in the neutron component of the total dose.

Details are given in Section IV.E and Appendix D. (Note: Implementation of a revised A-bomb

survivor dosimetry system, designated “DS02,” which is in progress as this report goes to press,

presumably will correct much of the bias associated with the DS86 dosimetry.)

3. Extrapolation of risk from sparsely ionizing radiation to low doses and dose rates. Doses received at

low doses and dose rates are adjusted by a factor known as the Dose and Dose Rate

Effectiveness Factor (DDREF). The treatment of the uncertainty in this factor is described in

Section IV.F and Appendix D. 

4. Transfer of risk estimates to a U.S. population. Baseline risks for many cancers differ

substantially for Japanese and U.S. populations, and there is considerable uncertainty about

how risk estimates derived from observations on an exposed Japanese population should be

applied to an exposed U.S. population. The treatment of this source of uncertainty, described

in Section IV.G and Appendix D, is a major departure from the 1985 report.

5. Biological effectiveness of different radiations. Densely ionizing, or high-LET (for high linear

energy transfer) radiation, with high energy transfer per track length in tissue, such as protons,

neutrons, and alpha particles and other heavy ions, generally has a greater biological

effectiveness per unit dose than low-LET radiation, such as gamma rays, X-rays, and beta

particles. For radiation protection purposes, dose of high-LET radiation in Gy is weighted by a

factor, called the radiation weighting factor (wR), which depends on the type of radiation and

20 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
sometimes its energy (ICRP 1991). The resulting weighted dose, called equivalent dose, is in

Sv and provides a common metric of biologically significant dose for all radiation types. There

is no uncertainty about wR, since it is a defined value for a particular radiation type for use in

radiation protection. For purposes of estimating risk and AS, however, wR may be only a rough

approximation of the biological effectiveness relative to low-LET radiation, which is required

when risk coefficients derived from studies of populations exposed mainly to low-LET radiation

are applied in cases of exposure to high-LET radiation. In addition, the biological effectiveness

of low-LET radiations (photons and electrons) may depend on energy, and this is not normally

taken into account in radiation protection. Thus, biological effectiveness generally depends on

the radiation type, and sometimes its energy and dose rate, and is an uncertain quantity.

Treatment of uncertainties in biological effectiveness of different radiation types based on

uncertainties in radiobiological data, which is discussed in Section IV.H, relies on a separate

report commissioned by NIOSH (Kocher et al. 2002).

6. Modification by smoking history. Tobacco smoking and, to a lesser extent, exposure of

nonsmokers to side-stream tobacco smoke are powerful risk factors especially for lung cancer

and for a number of other cancers as well. Studies of uranium miners suggest that risk of

radiation-induced lung cancer is increased among smokers to a greater extent than among

nonsmokers, but perhaps not as much as would be predicted according to a multiplicative

interaction model (NAS/NRC 1999), whereas a recent analysis of A-bomb survivor data

suggests an additive interaction with no difference in excess radiation-related risk by smoking

history (Pierce et al. 2003). Treatment of the interaction between radiation exposure and

smoking history is discussed in Section IV.I. 

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

evaluated here.

1. Diagnostic misclassification in A-bomb survivor data. Both the NCRP (1997) and EPA (1999)

uncertainty evaluations were based on mortality data, for which diagnostic misclassification is a

more serious problem than for the incidence data used for this report. Also, the present report

focuses on specific cancers, and diagnostic accuracy may depend on the cancer type. Although

there is undoubtedly uncertainty resulting from diagnostic misclassification, it would be very

difficult to quantify, and it does not seem likely that this uncertainty would be large relative to

many of the other sources considered. 

2. Extrapolation of risk beyond the time period covered by data. The focus of NCRP Report 126

(1997) was lifetime cancer mortality risk associated with radiation exposure, and the report

specifically treated uncertainty about extrapolation of risk beyond the period of observation for

risk. The concern was that the A-bomb survivor mortality data for 1950–1985 represented

follow-up only until 40 years after exposure, whereas those data were being used to estimate

lifetime risk for persons exposed at various ages including children whose expected remaining

lifetime when exposed was 50, 60, 70, or more years. The NCRP report included a factor whose

uncertainty contributed 6.7% of the overall uncertainty to lifetime mortality risk for a population

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

The present report is subject to the same problems of projection of risk beyond the period of

observation, even though the vast majority of claims for which the report might be relevant are

expected to pertain to adult exposures, for which such projection contributes little compared to

IV. Description of the Approach 21
other sources of uncertainty. However, (uncertain) trends in time since exposure (leukemia) or

attained age (solid cancers), which address some of the same issues, were specifically included

in the set of variables used to model radiation-related risk for different kinds of cancer and were

retained in the model as appropriate on statistical grounds. 

B. Sources of data 

Although much new information on radiation-related risk in human populations has been

published in the 18 years since the 1985 NIH report was prepared, the present report relies

primarily on analyses by the Working Group of A-bomb survivor incidence data. The approach

involved direct calculation of risk estimates and their statistical uncertainties from original

data, in this case from the RERF Tumor Registry for 1958–87 (Thompson et al. 1994) and the

RERF Leukemia Registry for 1950–1987 (Preston et al. 1994). Thyroid cancer received a more

widely based approach, involving a new analysis of the original thyroid cancer data from the

international, pooled study of Ron et al. (1995). Inferences based on a new analysis of lung

cancer risk associated with external radiation sources and smoking (Pierce et al. 2003) were

incorporated, with the help of computations provided by Donald Pierce using the original data

from that study. Radon-related lung cancer risk estimates were computed by the Working

Group using data and statistical models consistent with those used for a Department of Justice

report (DOJ 1996). Dale Preston, Chief of Statistics at the RERF, provided estimates for

nonmelanoma skin cancer based on the original data from a published study (Ron et al. 1998).

C. Choice of cancer types and approach to cancer types 

Adjudication of compensation claims for possibly radiation-related cancer is usually specific to

organ site and often to histological type, and, for this reason, models need to be developed for

estimating risks for cancer of specific sites. Sites for solid tumor incidence data from the RERF

Tumor Registry, as tabulated by Thompson et al. (1994), are reproduced in Table IV.C.1 (page

44), and sites for hematopoietic cancers from the Leukemia Registry, as tabulated by Preston et

al. (1994) are reproduced in Table IV.C.2 (page 46). The final column of each table indicates

grouping and other treatment of each site for the present report. Estimates of the ERR per unit

of exposure for site-specific cancers are often imprecise, especially for less common cancers. The

need to estimate parameters that allow for modification of risk by sex, age at exposure, and

attained age adds to the difficulty. In the approach described below, we have tried to strike a

balance between statistical precision and allowing for differences among cancer sites. 

For solid cancers, the general approach to defining categories was to provide separate estimates

for each cancer site represented in the LSS data set by 50 or more cases among A-bomb

survivors exposed to ≥ 10 mSv. Categories, with their ICD-9 codes (DHHS 1980), that met

this criterion were oral cavity and pharynx (140–149), esophagus (150), stomach (151), colon

(153), rectum (154), liver (155), gallbladder (156), pancreas (157), lung (162), female breast

(174), uterine cervix (180), ovary (183), prostate (185), bladder (188), and nervous system

(191, 192). Thyroid cancer (193) and nonmelanoma skin cancer (173) also met this criterion,

but for those sites more extensive data from Ron et al. (1995) and Ron et al. (1998) were used.

To allow inclusion of additional categories that did not meet this criterion, uterine cervix was

merged with other female genital cancers except ovary (179–182, 184), and prostate was

merged with other male genital cancer (185–187). There was little or no evidence of dose

22 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
response for any of these cancers (Thompson et al. 1994). Additional categories for which

estimates are provided are all digestive cancers (to be used for digestive cancers not included

above, i.e., ICD codes 152, 158, 159); all respiratory cancers excluding lung (160–161,

163–165); all urinary cancers (to be used for kidney [189]); and a residual group of solid cancers

(170–172, 174-males, 175, 190, 194–199). 

For hematopoietic cancers, estimates are provided for each category shown in Table IV.C.2,

even though the number-of-cases criterion used for inclusion of solid cancer sites was met only

for the largest grouping of leukemia types. Chronic lymphocytic leukemia (CLL) was

specifically excluded from the risk calculations because of a lack of data on which to base an

estimate. CLL is almost absent among Japanese generally and among the A-bomb survivors in

particular (Parkin 1997; Preston 1994), but occurs frequently in Western populations, especially

at older ages (Parkin 1997). It has not, however, been associated with radiation exposure in

studies of irradiated Western populations (NAS/NRC 1990). Lymphoma and multiple myeloma

are grouped together and treated in a manner similar to that for solid cancers as discussed below.

Radon-related lung cancer, although included in the 1985 NIH report, was not covered by the

initial version of the present report because adaptation of the BEIR VI report (NAS/NRC

1999) for this purpose was felt to be beyond the resources of the Working Group. Inclusion was

recommended by the NRC review subcommittee and by government agencies (notably

NIOSH) likely to use the revised report to adjudicate compensation claims. It was pointed out

by the NRC review subcommittee (NAS/NRC 2000) that Appendix A of a 1996 report

prepared for the Department of Justice (DOJ 1996) contains tables of cumulative radon

exposures, in working level months (wlm), consistent with point estimates and upper 80% and

90% confidence limits for probability of causation greater than or equal to 50%. The original

data set used for these calculations, restricted to exposures ≤ 3200 wlm, was used by the

Working Group to model lung cancer risk as a function of cumulative radon exposure.

D. Estimation of risk coefficients and their statistical uncertainties

1. Solid cancers from the RERF tumor registry report data 

In the models described in this section, thyroid cancer and nonmelanoma skin cancers are

excluded, and the term “all solid cancers” is used throughout to indicate solid cancers (ICD

140–199) without these two cancers. Site-specific baseline risks were modeled by stratifying on

gender, city of exposure (Hiroshima or Nagasaki), calendar time, and attained age using the

general approach described by Pierce et al. (1996). The following linear dose-response function

was used to model the ERR:

ERR(D,s,e,a) = αD exp[ßIs

(sex) + γ f(e) + δ g(a)] 

or, equivalently for α > 0, (IV.D.1)

ERR(D,e,a) = D exp[log(α) + ßIs

(sex) + γ f(e) + δ g(a)],

where D is weighted dose in Sv = Dγ + 10 Dn, where Dγ and Dn are tissue-specific absorbed

dose, in Gy, from gamma rays and neutrons, respectively, Is

(sex) is an indicator function for the

opposite sex (i.e., Is

(sex) = 1 for females and = 0 for males if s corresponds to “male,” and

conversely if s corresponds to “female”), e is age at exposure in years, a is attained age in years,

f and g are specified functions of e and a, respectively, and α, ß, γ, and δ are unknown

IV. Description of the Approach 23
parameters. The term ßIs

(sex) in expression (IV.D.1) is a computational convenience that

allows the ratio between sex-specific estimates to be determined using site-nonspecific data, as

discussed later. Based on published analyses of the RERF incidence data for 1958–87 with f(e)

= e – 30 and g(a) = log(a/50) (Thompson 1994), it would not be necessary to include both age

at exposure and attained age, for most sites, in a parsimonious model. However, it is our

understanding that updated cancer incidence and mortality data, currently being evaluated at

RERF, indicate a more general need for both variables (D. Preston, personal communication).

In addition, the NAS/NRC review of an earlier draft of this report recommended models that

allowed for attenuation of risk with time. The parameter δ in our general model (IV.D.1) allows

for such attenuation.

The following specifications for the functions f(e) and g(a) were evaluated, and specification C

was chosen for reasons discussed in the next paragraph.

A: f(e) = e – 30, g(a) = log(a/50); 

B: f(e) = min(e – 30, 0), g(a) = min(log(a/50), 0);

C: f(e) = min(max(–15, e – 30), 0), g(a) = min(log(a/50), 0),

where “min” denotes “minimum” and “max” denotes “maximum.”

The chosen specification (C) for f(e) and g(a) can also be written as follows: 

f(e) = –15 for e ≤ 15, = e – 30 for e between 15 and 30, and = 0 for e > 30;

g(a) = log(a/50) for 0 < a < 50, and = 0 for a ≥ 50. (IV.D.2)

When fitted to data for all solid cancers, the deviance values for models using the specifications

A, B, and C were 3746.94, 3746.52, and 3743.15, respectively, with smaller deviance values

indicating a closer fit of model to data. The nearly identical fits of models using A and B

indicate that there is no direct evidence of modification of the ERR for exposure ages over 30

or attained ages over 50, and the somewhat better fit of model C indicates a lack of direct

evidence of variation of the ERR by exposure age under 15. The model using C was chosen for

application to solid cancers because it provided a better fit than the other two and because it

allowed more statistically stable estimates at the extremes of exposure ages and attained ages.

Exceptions were cancers of the thyroid gland and skin, as discussed at the end of Section IV.D

below. The chosen model, as fitted to the data, has the properties that, for fixed attained age 

a, log(ERR/Sv) is constant in exposure age e (at different levels) for exposure ages less than 15

years and greater than 30, and decreases linearly with exposure age e between 15 and 30. For

fixed exposure age, log(ERR/Sv) decreases linearly with log(a) until attained age 50, and

remains constant thereafter. With this choice of f and g, the parameter α represents (sexspecific) ERR/Sv for exposure age 30 or older and attained age 50 or older, since both f and g

are zero for these ages. For exposure age e younger than 30 and/or attained age a younger than

50, 

ERR/Sv = α × h(e, a; γ, δ), 

where

h(e, a; γ, δ) = exp{γ f(e) + δ g(a)}

and where f(e) and g(a) are defined above according to specification C (IV.D.2). 

24 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
The approach used to model parameters for site-specific cancers is based on the “joint analysis”

approach of Pierce and Preston (1993). As applied here, the approach involves an analysis with

three replicates of the data, with a “case” defined as the cancer of interest in the first set, all

other nonsex-specific cancers combined (other than lymphoma and multiple myeloma) in the

second replicate, and all other sex-specific cancers combined in the third. The first replicate

provides information about parameters α, ß, γ, and δ, the second about parameters ß, γ, and δ,

and the third about γ and δ. Letting parameters ß, γ, and δ differ between the first replicate and

the other two provides a test of homogeneity, and the site-specific parameter estimates are used

if they are statistically significantly different from the common parameter values. For most sites,

there was no significant difference and the common values were used. 

Site-specific estimates of ß were used for cancers of the stomach, colon, and liver; for liver, it

was assumed that the ERRs for the two sexes were the same (ß = 0), a result supported by

Cologne et al. (1999). For all remaining nonsex-specific cancers, the gender parameter value

was ß = 0.843, which corresponds to a female/male ratio of 2.3. In no case other than those just

mentioned was there evidence of significant departure from this common value. 

However, compromises were made in the interests of computational efficiency. A possible

approach for evaluating the uncertainty in the estimated ERR/Sv for each sex at various

exposure and attained ages would have been to conduct joint analyses as described above,

transforming the regression variables so that the parameter α reflected the ERR/Sv associated

with a particular combination of sex, exposure age, and attained age, and obtain the profile

likelihoods for the fitted α. However, this would have been extremely cumbersome (with slow

computational speed) to implement in IREP, the interactive computer program for applying the

algorithms developed by the Working Group. 

In the interests of improving the computational speed of IREP, two computational approaches

were used to estimate the statistical uncertainty distribution of ERR/Sv. In Approach 1, the

statistical uncertainty distribution was approximated by applying normal assumptions to the

point estimates and covariance matrix for the estimated parameters, sex-specific log(α), and γ

and δ. This was done for five different site-sex combinations with relatively large numbers of

cases and strong evidence of effects: all digestive cancers (male and female), stomach cancer

(female), liver cancer (combined sexes), and female breast cancer. These cancers contributed

heavily to the common estimates of γ and δ, and the correlations of log(α) with γ and δ were

therefore somewhat higher than for other sites. Also, for each of these cancers, the statistical

likelihood distribution of ERR/Sv was closely approximated by a lognormal distribution. The

means, variances, and covariances of the uncertainty distributions for the parameter estimates

are shown in Table IV.D.1 (page 47). For each of these site-sex combinations, the geometric

mean (GM) and geometric standard deviation (GSD) of the statistical uncertainty distribution

of ERR/Sv, evaluated at exposure age e and attained age a, are given by

GM = α × h(e, a; γ, δ), (IV.D.3)

GSD = exp{[var(log(α)) + 2 cov(log(α), log(h(e, a; γ, δ))) + var(log(h(e, a; γ, δ)))]1/

2},

where

cov(log(α), log(h(e, a; γ, δ))) = cov(log(α), γ) f(e)) + cov(log(α), δ) g(a),

var(log(h(e, a; γ, δ))) = var(γ) f(e)

2 + 2 cov(γ , δ) f(e)g(a) + var(δ) g(a)2

.

IV. Description of the Approach 25
Approach 2 was used for all other solid cancer sites, with the exceptions of thyroid cancer and

nonmelanoma skin cancer for which the analyses were based on different data sets. For the sites

treated using Approach 2, correlations of sex-specific log(α) with γ and δ were modest

(Appendix C), and it was considered appropriate to base the uncertainty evaluation on the

assumption that the estimated value of sex-specific α was statistically independent of the

estimates of γ and δ, or, in the case of lung cancer, that α was independent of ß, γ, and δ. The

fitting process was repeated, this time with parameters γ and δ set equal to the common values

obtained from a fit for all solid cancers: γ = –0.05255 and δ = –1.626. Thus, the site-specific

and sex-specific dose effect α was estimated assuming no correlation of log(α) with γ and δ. For

nonsex-specific cancers, joint analyses were used with a common gender parameter (ß) and

separate main effects (α) for the cancer of interest and remaining nonsex-specific cancers.

Inclusion of data for other nonsex-specific solid cancers served to stabilize the male/female ratio

of dose coefficients for males and females. Statistical uncertainty distributions for cancers

treated using Approach 2 are calculated in IREP by Monte Carlo simulation based on the

statistical likelihood profile distribution for α, given in Table IV.D.2 (page 48) for most sites for

which Approach 2 was used, and a lognormal distribution for h(e, a; γ, δ), which is assumed to

be statistically independent of α with

GM = exp{–0.05255 f(e) – 1.626 g(a)},

GSD = exp{[0.0003261 × f(e)

2 – 2 × 0.007297 × f(e) × g(a) + 0.5648 × g(a)2

]

1/

2}. 

For lung cancer, independence is assumed between log(α) (see likelihood profile, which

corresponds to never-smokers, in Table IV.D.3 [page 50]) and 

h*(s, e, a; ß, γ, δ) = exp{ß × s + γ × f(e) + δ × g(a)},

where s = –0.5 for males and 0.5 for females, and h*(s, e, a; ß, γ, δ) is assumed to be

lognormally distributed with 

GM = exp{0.843 s – 0.05255 f(e) – 1.626 g(a)},

GSD = exp{[0.06250 s

2 – 2 × 0.0003469 s × f(e) + 2 × 0.008295 s × g(a) + 0.0003301 × f(e)2

+ 2 × 0.00708 f(e) × g(a) + 0.5620 g(a)

2

]

1/

2}. 

For female genital cancers other than ovary, for which γ and δ were assumed to be zero, the

statistical uncertainty distribution of log(ERR/Sv) is completely specified by the likelihood

profile distributions for log(α), as shown in Table IV.D.3.

For e < 30 and/or a < 50, some bias is associated with the assumption of statistical

independence between the linear dose-response parameter estimate α and the age-modifier

parameter estimates γ and δ, provided the latter two parameters are not assumed to be zero.

This bias is a function of e and a, and of the correlations between log(α) and γ and between

log(α) and δ. As discussed in detail in Appendix C, Approach 2 usually overestimates the

upper 99% uncertainty limit for AS, sometimes by as much as 6% of its value (e.g., estimating

an upper limit of 53% instead of 50%) for some of the sites in Table IV.D.2 for which the

correlation between the estimates of log(α) and γ approaches 0.25. For male colon cancer and

male urinary organs other than bladder (for which the correlation between log(α) and δ is

26 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
between –0.06 and –0.08), and then only for e around 30 and a around 40, the upper limit may

be underestimated by as much as 1% of its value (e.g., as 49.5% instead of 50%). 

Lymphoma and multiple myeloma, combined into a single group because of small numbers for

multiple myeloma, were also evaluated in the manner indicated above, although these cancers

were not included in the “all solid-cancer” group used to estimate the common modifying

effects. For this category, the ERR for males was positive while that for females was negative.

For the model here, it was assumed that the ERRs for the two sexes were the same although

there was a suggestion that they differed (p = .09). The common age parameters were used

since there was little evidence of departure from these values.

As discussed above, a separate risk estimate was not computed for bone cancer because there

were too few cases in the RERF data set. The site is included in the residual group of solid

cancers.

2. Leukemia 

Site-specific baseline incidence was modeled as a function of gender, city of exposure

(Hiroshima or Nagasaki), year of birth, calendar time (where indicated), and age at observation

for risk (attained age), as discussed in Preston et al. (1994). Default dose-response models were

linear (proportional to dose equivalent D in Sv, henceforth called “dose” for brevity) for

leukemia associated with exposure to high-LET radiation or low-LET radiation delivered at low

dose rates (chronic exposure), and linear-quadratic for leukemia associated with acute exposure

to low-LET radiation. The linear-quadratic model was set to have ERR proportional to D + D2

.

By fitting a general linear-quadratic model (ERR proportional to D + ζD2

) for all types of

leukemia except chronic lymphocytic (CLL) considered as a group, and for acute myelogenous,

acute lymphocytic, and chronic myelocytic leukemia separately, various estimates of the

unknown parameter ζ were obtained, depending on the type of leukemia, that were greater

than zero. However, since all these estimates were statistically consistent with the default value

ζ = 1, the final models for leukemia and its subtypes were based on ζ = 1.

In terms of potential modifying factors such as sex (s), age at exposure (e), attained age (a), and

time since exposure (t), the model, as fitted to the mixed gamma (Dγ

) and neutron (Dn) 

A-bomb survivor dose-response data, was

ERR(Dγ

,Dn,e,a) = α (Dγ + 10 Dn + Dγ

2

) exp{ß e + γ t + δ e t}, (IV.D.4)

where α, ß, γ, and δ are unknown parameters which may be sex-specific. Parameter α was

estimated from the data, as were parameters ß, γ, and δ unless they made no significant

contribution to improvement of the fit of the model to the data, in which case they were set to

zero; similarly, individual parameters were made sex-specific only if doing so led to significant

improvement in fit. (Following Preston [1994], the leukemia dose response was modeled in

terms of e and t = a – e instead of e and a.)

Unlike the approach for solid cancers, likelihood profiles for the parameter α were computed

for different combinations of sex, exposure age, attained age, and/or time following exposure, as

follows: The parameter α corresponds to the excess relative risk when D + D2 = 1, e = 0, and 

t = 0. Thus (for example) the estimated value of parameter α for leukemia (all types except

IV. Description of the Approach 27
CLL) among females exposed at age 20 and observed 27 years following exposure can be

obtained by replacing e by e* = e – 20 and t by t* = t – 27. The statistical uncertainty

distribution of the resulting estimate is described by the profile likelihood distribution of the

fitted parameter α (Tables IV.D.4–IV.D.7). In practice, profile likelihood distributions were

computed for formulations of e* and/or t* corresponding to specific ages and times, and

obtained by interpolation for intermediate values.

For leukemia of all types combined, less chronic lymphocytic leukemia (Table IV.D.4, page 51),

parameter α was estimated for combined sexes as a function of e and t (IV.D.4). For acute

lymphocytic leukemia (ALL; Table IV.D.5, page 52), α was separately estimated for two

intervals of age ATB: e < 20 and e ≥ 20, and by t for e < 20 but not for e ≥ 20, following Preston

(1994); the two sexes were not modeled separately. For acute myelogenous leukemia (AML;

Table IV.D.6, page 53) modeling was by time since exposure, for combined sexes, while for

chronic myelogenous leukemia (CML; Table IV.D.7, page 54), modeling was by time since

exposure, separately for males and females.

3. Thyroid cancer

Thyroid cancer risk, estimated from the combined analysis data used by Ron et al. (1995),

required special handling because the data were from six different study populations (treating

Hiroshima and Nagasaki survivors separately) with possibly different baseline and excess risks.

There was no statistically significant dependence of ERR on gender or attained age, and the

common attained age parameter value used for most solid cancers was statistically inconsistent

with these data; therefore, parameters ß and δ were both set equal to zero. The final model was

ERR(D,e) = D exp(θ1I1 +...+ θ6I6 + γe),

where I1, ..., I6 are indicator functions for the 6 study populations and where θ1, ..., θ6 are

assumed to be normally distributed random variables with common mean θ. Parameter

estimates θ1, ..., θ6 and γ, and their estimated asymptotic covariance matrix, were obtained by

Poisson regression (Preston et al. 1991). The parameter estimate θ was calculated as the mean

of θ1, ..., θ6, weighted by the inverse of their estimated covariance matrix Σ. The off-diagonal

elements of Σ were positive, indicating that θ1, ..., θ6 were positively correlated.

The variance of the estimate θ was adjusted for nonhomogeneity of study populations by the

method of DerSimonian and Laird (1986) for meta-analysis of clinical trials, as adapted by Ron

et al. (1995). The method assumes statistical independence among estimates obtained from

different studies, a condition that was not strictly met in the present analysis because a

common age-at-exposure parameter was used for the several studies. Since individual study

estimates were positively correlated, use of the method is likely to have overestimated the

variance of θ and thus resulted in overestimates of the upper uncertainty limits for ERR1Sv.

The statistical uncertainty distribution for θ was assumed to be normal with mean and variance

equal to θ and its estimated (adjusted) variance, respectively. Log(ERR1Sv) for any given

exposure age e0 was estimated as θ, calculated with e defined as exposure age minus e0 (so that 

e = 0 for exposure age e0) and was assumed to have a normal uncertainty distribution with GM

and GSD as shown in Table IV.D.8 (page 55) for e0 in increments of 5. The logarithm of GM is

linear in e0, whereas log(GSD) is markedly curvilinear in e0 for e0 < 20.

28 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Thyroid is the only cancer site in this report for which the dose-response data were primarily

from populations exposed to medical X-ray. In the analysis, it was assumed that medical X-ray

dose and gamma-ray dose from the atomic bombs were equivalent in effectiveness, as in the

original analysis of Ron et al. (1995). In Section H below, arguments are presented in support

of a relative biological effectiveness (RBE) of around 2 for 30–250 keV (e.g., medical X-ray)

compared to higher-energy photons (e.g., gamma ray from atomic bomb explosions). However,

because the atomic bomb exposures considered in the Ron study were acute and the medical 

X-ray exposures were fractionated, we considered that no correction was required because, at

moderate to high doses, the fractionation and the RBE factor appropriate to medical X-ray

should have had opposite and approximately equal effects on risk.

4. Skin cancer

The Working Group was reluctant to include skin cancers in the present report, because of a

high level of uncertainty about how to transfer estimates of dose-specific ERR between the

Japanese A-bomb survivors and populations in the United States. Nonmelanoma skin cancer is

not a reportable disease in the United States (although it is in Japan), and baseline rates are

not readily available, for example, from NCI’s SEER program (SEER 1997). However, the NRC

review committee report (NAS/NRC 2000) pointed out that estimated rates were available for

white and African-American U.S. residents (Scotto 1983) and recommended that the Working

Group seriously consider including skin among the cancer sites covered by the present report.

Also, both DVA and NIOSH expressed interest in having skin cancer estimates. 

Our data source was the data set of Ron et al. (1998), located at the RERF in Hiroshima. Dale

Preston, RERF Chief of Statistics, kindly offered to run analyses for the Working Group. We

initially asked for analyses similar to those for other solid tumors, i.e., using the general model

used in Thompson et al. and the model specified in (IV.D.1) and (IV.D.2) of the present report. 

For basal cell skin carcinoma, the only subtype for which a significant dose response was

obtained by Ron et al. (1998), there was a steep decline in dose-specific ERR by exposure age,

which extended beyond age 30 and was otherwise different from the common trend assumed

for other sites, and there was no dependence on attained age. We therefore replaced the age

function f(e) specified in (IV.D.2) by 

f(e) = min(max(–30, e – 40), 0), 

(i.e., f(e) = –30 for e ≤ 10, = e – 40 for 10 < e < 40, and = 0 for e ≥ 40).

Thus, there was no dependence upon attained age and dose-specific ERR was constant in e, at

different levels, for exposure ages less than 10 and 40 or older, with a linear transition in the

logarithmic scale between e = 10 and e = 40. Likelihood profile distributions for ERR/Sv

(ERR1Sv) were computed for e = 10, 20, 30, and 40, and interpolated for e between 10 and 40

(Table IV.D.9, page 56).

For nonmelanoma skin cancers other than basal cell carcinoma, which is dominated by

squamous cell carcinoma, the unmodified point estimate of ERR1Sv was negative and no

convergent estimate could be obtained if an age-dependent modifying term was introduced

with either a free or fixed parameter value. We therefore requested a single profile for ERR1Sv,

with no modification by age (Table IV.D.9). 

IV. Description of the Approach 29
The Ron et al. data set had only 10 cases of malignant melanoma, far below our inclusion

criterion of 50 cases at doses ≥ 10 mSv, and we therefore did not include that cancer type.

5. Radon-related lung cancer 

As mentioned above at the end of Section IV.C, a 1996 report prepared for the Department of

Justice (DOJ 1996) contains tables of cumulative radon exposures, in working level months

(wlm), consistent with point estimates and upper 80% and 90% confidence limits for

probability of causation greater than or equal to 50%, and the original data set used for these

calculations, but restricted to exposures ≤ 3200 wlm, was made available to the Working

Group. The Working Group attempted to approximate Appendix Table 3a of the DOJ report,

modeling ERR as follows: 

ERR(wlm,e,t) = α wlmß exp{γ f(a) + δ g(t)},

where wlm is cumulative radon exposure in working level months, a is age at diagnosis, t is time

since last exposure, α, ß, γ, and δ are unknown parameters, and

f(a) = min[max(a – 45, 0), 30],

g(t) = min[max(t – 5, 0), 20]; 

(i.e., f(a) = 0 for a ≤ 45, = a – 45 for 45 < a ≤ 75, and = 30 for a > 75;

g(t) = 0 for t ≤ 5, = t – 5 for 5 < t ≤ 30, and = 20 for t > 25).

Thus, ERR was assumed to be proportional to an uncertain power of cumulative exposure in

wlm, to be constant in a (at different levels) for a ≤ 45 and a > 75, and to be constant in t

(again, at different levels) for t ≤ 5 and t > 25. Likelihood functions for ERR1 wlm are given in

Table IV.D.10 (page 57) for smokers and nonsmokers, for a ≤ 45, a = 69, and a > 75, and for 

t ≤ 5, t = 15, and t > 25, for interpolation in a and t. For ERR at arbitrary wlm, IREP multiplies

ERR1 wlm by wlm0.82.

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

Our treatment of random and systematic errors in A-bomb survivor dosimetry was based mainly

on the treatment described in Chapter 3 of NCRP Report 126 (1997), and the reader is

referred to this material for details. The NCRP approach was also used by the EPA (1999).

Dosimetry for the A-bomb survivors is currently being reevaluated (NAS/NRC 2001).

Revisions in dosimetry could change the estimated risk from gamma rays slightly and might also

affect the shape of the dose-response function (Kellerer and Nekolla 1997; Pierce and Preston

2000). As this report goes to press, a revised dosimetry (designated DS02) is being

implemented. In the next year or two, it is expected that analyses based on the revised doses

will be conducted. Uncertainties resulting from systematic biases in A-bomb survivors will then

need to be reevaluated. For now, the evaluation from NCRP 126 is used, and the uncertainties

discussed below in (2), (3) and (4) should be considered as “place-holders” for a more

appropriate evaluation. Changes in dosimetry should not greatly affect the random errors

discussed in (1). 

30 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
For each source of uncertainty, a bias factor with an uncertainty distribution was specified, and

this factor was used to correct ERR estimates based on the A-bomb survivor data. Sources of

bias and uncertainty that were evaluated by the NCRP are as follows: 

(1) Uncertainty in the magnitude of random errors in the doses of individual survivors, called

RE in NCRP Report 126, contributed differently to biased uncertainty for solid cancers and the

leukemias, for which the forms of the dose response were linear and linear-quadratic,

respectively. Unlike the NCRP report, the present report is concerned with individual cancer

sites and must consider the two cases separately: uncertain bias correction factors 1 + FL(RE)

and 1 + FQ(RE) for cancers with linear and linear-quadratic dose responses, respectively. Pierce

et al. (1990) recommended a lognormally distributed random error in individual dose estimates

with geometric mean (GM) = 1 and geometric standard deviation (GSD) = exp(0.35),

corresponding to an upward correction in estimated risk of 9.0% for solid cancers and 5.6% for

leukemia, with essentially no effect on the variability of the corrected risk estimates. There is,

however, some uncertainty corresponding to the assumed GSD of the lognormally distributed

random error in dose estimates: the corresponding upward corrections are 6.8% and 4.3% for

solid cancers and leukemia, respectively, assuming log GSD = 0.30, and 11.4% and 7.2%

assuming log GSD = 0.40. If we consider 0.30 and 0.40 to correspond to the 10th and 90th

percentiles of an uncertainty distribution for log GSD, and consider that random error in dose

assignment can only bias estimated risk downward, it seems appropriate to assume that FL(RE)

and FQ(RE) are lognormal with GM = 8.8% and 5.56%, respectively, with common 

GSD = 1.22 (i.e., LN(8.8%, 1.22) and LN(5.56%, 1.22)).

(2) Uncertainty in the appropriate choice of neutron RBE in analyzing A-bomb survivor data,

denoted NR in NCRP 126 with error factor f(NR) distributed according to a triangular

distribution with minimum 0.9, most likely value 1.0, and maximum 1.1 (i.e., triangular 

[0.9, 1.0, 1.1]).

(3) Uncertainty due to systematic bias in gamma dose estimates, denoted Dγ in NCRP 126 with

error factor f(Dγ

) distributed as triangular (1.0, 1.1, 1.4). 

(4) Uncertainty due to systematic bias in neutron dose estimates in Hiroshima, denoted Dn in

NCRP 126 with error factor f(Dn) distributed as triangular (1.0, 1.1, 1.3).

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

FL(D) = (1 + FL(RE))/(F(NR) × F(Dγ

) × F(Dn))

for solid tumors and

FQ(D) = (1 + FQ(RE))/(F(NR) × F(Dγ

) × F(Dn))

for leukemia. The uncertainty distributions for FL(D) and FQ(D), expressed in percent,

correspond reasonably well to normal distributions: N(83.2, 8.36) and N(80.7, 8.05),

respectively.

IV. Description of the Approach 31
F. Dependence of risk on dose and dose rate for low-LET radiation 

Radiations of different quality differ with respect to the shape of the dose-response function for

cancer risk. Risk per unit dose of radiations of high linear energy transfer (LET), such as

neutrons, alpha particles, or heavy ions, tend to be the same (or greater) at low compared to

high doses, whereas for low-LET radiations, such as gamma rays, electrons, X-rays, or beta

particles, risk per unit dose is thought to be lower at low dose levels. Evidence for a lower risk

per unit dose or unit equivalent dose (henceforth to be referred to simply as “dose”) of low-LET

radiation at low (compared to high) dose levels comes mainly from experimental radiobiology,

much of it involving outcomes other than carcinogenesis (NCRP 1980). Inferences about the

shape of the dose-response relationship based on epidemiological studies of cancer, on the other

hand, tend to be determined by data in the middle and high dose ranges, i.e., 0.1–1.0 Gy and

1.0 Gy and higher. For solid cancers, generally, there is little persuasive epidemiological

evidence of nonlinearity of dose response, whereas for leukemia there is good evidence of

positive curvature. The linear-quadratic dose-response model for leukemia used here

corresponds to a risk at 0.01 Gy (1 cGy) that is only 0.5% as high as the risk at 1 Gy, or half as

high per unit dose. 

Linear-model risk coefficients may be reduced by a dose and dose-rate effectiveness factor

(DDREF) for estimating risks at low doses and low dose rates. The International Commission

on Radiological Protection (ICRP 1991) recommended a DDREF of 2 for purposes of radiation

protection, a value roughly consistent with the default linear-quadratic dose-response model

used here for leukemia. The ICRP recommendation is also accepted by the NCRP (1993). In

their most recent discussion of the application of DDREF, the United Nations Subcommittee

on Effects of Atomic Radiation (UNSCEAR 1993) recommended that the chosen DDREF be

applied to chronic exposures (dose rates less than 6 mGy per hour averaged over the first few

hours) and to acute (high dose rate) exposures at total doses less than 0.2 Gy, a recommendation that was subsequently adopted by the EPA (1999). However, such an abrupt transition

seems unrealistic in view of observed linearity of dose response for cancer incidence and

mortality among acutely exposed A-bomb survivors, down to and including values below 0.2

Gy (Thompson et al. 1994; Pierce et al. 1996). Also, continuous uncertainty distributions for

DDREF have been used by NCRP (1997), EPA (1999), and in a report prepared for the

Colorado Department of Public Health and Environment (Grogan et al. 2000) for calculations

of lifetime risk of all cancer types combined (Figure IV.F.1, page 59). The Grogan et al.

uncertainty distribution differs from the NCRP distribution mainly in allowing a small

probability that risk per unit dose might increase at very low doses. Thus, the NCRP and EPA

distributions allowed for the possibility of DDREF values between 1 and 5, while the Grogan et

al. distribution included values as low as 0.2.

In the present report, ERR is estimated as a function of radiation dose and modified according

to exposure rate (acute or chronic) by application of an uncertain DDREF. The DDREF is

applied to all chronic exposures whereas, for acute exposure, the DDREF is phased in as dose is

decreased, beginning at an uncertain reference dose less than 0.2 Sv and decreasing smoothly

to the value appropriate for chronic exposure. Fractionated acute exposures separated by 5

hours or more are treated as separate exposures; thus, the DDREF is applied to each fraction

and their estimated effects on risk are added together. The Working Group has chosen to

derive its own subjective uncertainty distribution for DDREF (i.e., DDREFchronic) (Figure IV.F.2,

left-hand panel, page 60), mainly because the analysis of low-dose LSS cancer mortality data

32 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
(Pierce et al. 1996) is strongly consistent with linearity and suggests, however weakly, the

possibility of supra linearity of dose response below 0.5 Sv. A discrete, rather than continuous,

distribution was used (emphasizing the subjective nature of the exercise), with nonzero

probabilities on DDREF = 0.5, 0.7, 1, 1.5, 2, 3, and 5. For cancers of the female breast and the

thyroid gland, a discrete distribution was selected with greater probability at DDREF = 1

(Figure IV.F.2, right-hand panel, page 60). 

For an acute exposure, the DDREF (DDREFacute) is modeled as a random quantity that

approaches DDREFchronic as dose decreases to zero. Between zero and an uncertain reference

dose, DL (between 0.03 and 0.2 Gy), DDREFacute decreases smoothly from DDREFchronic at zero

dose to 1 at DL and above, according to a logistic function of dose (Figure IV.F.3, page 61). The

uncertainty in the reference dose DL is expressed as a log-uniform distribution (Figure IV.F.4,

page 62).

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

A major concern in using data from Japanese A-bomb survivors to estimate risks for specific

cancers in a U.S. population is that baseline risks differ between the two populations and the

dependence of radiation risks on baseline risks is not known with certainty. For example,

baseline cancer rates for breast, lung, and colon cancer are smaller in Japan than in the United

States, while rates for stomach and liver cancer are much higher in Japan. Estimation of risk for

a U.S. population based on the dose-response coefficients derived from A-bomb survivor data is

commonly referred to as the “transfer” or “transportation” problem. A more detailed discussion

of the transfer problem appears in NCRP Report 126 (NCRP 1997). 

Two simple solutions are the so-called “multiplicative” and “additive” transfer models in which

estimates of excess relative risk (the ratio between excess and baseline risk) and absolute risk

(the difference between the estimated cancer rates with and without exposure) are respectively

applied to the second population (in this case, the U.S. population). The multiplicative

transfer model is biologically plausible to the extent that ionizing radiation exposure can be

assumed to act as an “initiator” of a process such that the likelihood of resulting in cancer

depends upon the action of “promoting” agents, if these “promoting” agents are responsible for

the difference in baseline rates between the two populations. Alternatively, multiplicative

transfer also would hold if radiation were to act as a promoter of the carcinogenic effects of

other agents that are differentially effective in the two populations. According to the

multiplicative model, the excess risk from radiation exposure would be greater in a normally

high-risk population than in a normally low-risk population. The additive transfer model is

plausible to the extent that radiation can be assumed to act mainly as an initiator and the

difference between population baseline rates can be assumed to be due to the differential effects

in the two populations of other “initiator” carcinogens that act similarly to radiation. In this

view, the additional cancer risk burden of radiation exposure would be independent of the

population baseline rate. 

Several approaches have been used for transferring risk estimates based on the Japanese 

A-bomb survivor data to other populations. The multiplicative transfer model was used by

UNSCEAR (1988) for the world population and in the BEIR V report (NAS/NRC 1990) for

the U.S. population. The additive transfer model was used in the BEIR III report (NAS/NRC

1980) and the 1985 NIH report (NIH 1985). The two transfer models can lead to very

IV. Description of the Approach 33
different estimates of radiation-related risk for certain cancers for which baseline risks differ

greatly between Japan and the U.S. (Land 1990). Each of the two models receives some support

from site-specific comparisons between risk estimates based on different exposed populations,

but there are few sites for which meaningful analytic comparisons can be made. If population

differences in cancer rates may be due to both initiating and promoting agents, it is likely that

both additive and multiplicative model interactions with radiation may take place and that

some kind of mixture model may be appropriate. For example, the ICRP (1991) used the

arithmetic mean of the ERR values obtained by the two transfer models for all solid cancer

types combined (Land and Sinclair 1991), and the Environmental Protection Agency (Puskin

and Nelson 1995) used the geometric mean (except for liver cancer associated with exposure to

the radioactive contrast medium thorotrast and bone cancer from exposure to injected 224Ra,

for which an additive transfer model was chosen). More recent reports have used uncertain

(i.e., randomized) linear or geometric combinations, weighted in various ways, of the additive

and multiplicative transfer models for the estimation of total risk of cancer mortality (EPA

1999). 

Mortality rates for all types of cancer combined vary relatively little by nation, compared to

site-specific variation. The initial ERR1Sv value for mortality from all cancers combined used in

NCRP Report 126 (NCRP 1997) was the rounded average of multiplicative and additive

transfer model estimates from the LSS mortality data for five different national populations

(ICRP 1991; Land and Sinclair 1991). Thus, the problem for that report was not how to

estimate ERR1Sv for a U.S. population but to determine the uncertainty associated with

estimating ERR1Sv in a particular way. Their solution was an uncertainty factor f(T), distributed

as LN(1, 1.3). 

For the present report, the problem is how to estimate site-specific and age-specific values of

ERR1Sv for the U.S. population in the presence of possibly large differences in baseline rates

and the absence of useful information about which model might be correct. Our approach is to

use a random linear combination between the additive and multiplicative models,

(ERR1Sv)

US = y × (ERR1Sv)mult + (1 – y) × (ERR1Sv)add ,

where the random variable y varies between –0.1 and 1.1. Here, (ERR1Sv)

mult is the site-, 

sex-, and age-specific excess relative risk at 1 Sv obtained from statistical analysis of the

Japanese A-bomb survivor data and adjusted for random and systematic errors in dose to

individual A-bomb survivors (see IV.D above). (ERR1Sv)

add is the same value, adjusted for the

corresponding ratio between baseline rates in the two countries:

Here, BJapan and BUS are the sex- and site-specific, age-standardized background cancer

incidence rates in the Hiroshima and Nagasaki tumor registries (a surrogate for the A-bomb

survivor cohort) and the U.S. population, respectively, both age-standardized to the world

population age distribution (Parkin 1997). For a cancer, such as bone, for which ERR is

estimated from data for a larger group of cancers including that site (in this case residual solid

cancers, see Table IV.C.I), it is nevertheless reasonable to define additive model transfer in

(ERR1Sv)add = (ERR1Sv)mult .(

BJapan

B ) US

34 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
terms of the site-specific (e.g., bone cancer) ratio of age-standardized U.S. and Japanese rates,

which may differ from the same ratio computed for the larger group of sites.

The coefficient y of the linear combination can be used to favor one model or the other

according to the weight of evidence. For instance, y = 0 corresponds to the additive model, 

y = 1 to the multiplicative model, and y = 1

/

2 to the arithmetic average of the two. A Monte

Carlo simulation is used to express uncertainty about y, with y values sampled according to the

following probability density distribution:

The constant probability density shown above for y values between 0 and 1 reflects a complete

lack of knowledge about the appropriateness of particular weighted averages of the additive and

multiplicative transfer models, and the assignment of small probability weights (4.5% each) to

values less than 0 and larger than 1 allows for the (subjectively unlikely) possibility that

radiation-related cancer risk might be negatively correlated with population baseline risk. For

breast, thyroid, and stomach cancer, more information is available and, thus, the “uninformed”

trapezoidal density given above and in Figure IV.G.1 (page 63) may be modified by

redistributing some of the weight to the additive transfer model in the case of breast cancer

(Land et al. 1980; Little and Boice 1999; Preston et al. 2002) or the multiplicative model for

thyroid cancer and stomach cancer (Ron et al. 1995; Griem et al. 1994; Carr et al. 2002).

Thus, for breast cancer, a probability weight of 50% was assigned to the additive transfer model

(y = 0), and 50% was assigned to the trapezoidal probability density distribution. For stomach

cancer, a probability weight of 33% was assigned to the multiplicative model (y = 1), and 66% to

the trapezoidal distribution in Figure IV.G.1. The cumulative distribution functions for these

distributions are compared with that for the “uninformed” distribution in Figure IV.G.2 (page

64). For thyroid cancer, the multiplicative model was used, reflecting the international basis of

the Ron study (1995).

As discussed in IV.I.3 below, Pierce et al. (2003) found that, among A-bomb survivors with

both radiation dose estimates and smoking history data, lung cancer risk was “quite consistent”

with an additive model for interaction between radiation and tobacco smoking, but statistically

inconsistent with a multiplicative model. Given this result, and the strong dependence of

population lung cancer rates on cigarette consumption (Blot and Fraumeni 1996), the Working

Group concluded that the “informed” transfer model used for breast cancer, with 50%

probability assigned to the additive model, was also appropriate for lung cancer.

H. Radiation effectiveness factors for different radiation types

People can be exposed to many different types of ionizing radiation including photons,

electrons, alpha particles, and neutrons, and the energies of each radiation type can vary widely.

Many studies of the effects of ionizing radiation on a wide variety of biological systems, ranging

from simple cells to complex whole organisms, have shown that different types of radiation

often differ substantially in their biological effectiveness. That is, the probability that a

particular biological response is induced by radiation depends on the radiation type, and

f(y) = 0.9091 ×

{ (y + 0.1) – 0.1 < y < 0

1 0 ≤ y ≤ 1

(1.1 – y) 1.0 < y < 1.1

IV. Description of the Approach 35
sometimes its energy, as well as the dose. In estimating cancer risks and probability of causation

(assigned share) for an individual who received known exposures to particular radiation types,

it therefore is essential that differences in the biological effectiveness of the different radiations

be taken into account.

Differences in biological effectiveness of different radiation types have long been taken into

account in radiation protection. The quantity currently used in radiation protection to describe

the biological effectiveness of different radiation types is the radiation weighting factor. This

factor is used to modify the absorbed dose in an organ or tissue of humans from a given

radiation type (the total energy imparted in the organ or tissue divided by its mass), given in

Gy, to yield an estimate of equivalent dose, given in Sv. The risk of cancer (or other stochastic

radiation effect) in an irradiated organ or tissue is assumed to be proportional to the equivalent

dose, independent of radiation type.

The assigned point values of radiation weighting factors used in radiation protection are based

on data on the relative biological effectiveness (RBE) of radiations obtained from

radiobiological studies of a variety of responses in different biological systems, as well as

judgments about the applicability of estimated RBEs to induction of cancers in humans and

theoretical considerations of the relationship between biological effectiveness and the density

of ionization produced by different radiations in tissue. The radiation weighting factors

currently used in radiation protection include: 1 for photons and electrons of any energy; 20 for

alpha particles; and 20 for neutrons of energy 0.1–2 MeV including fission neutrons, 10 for

neutrons of energy 10–100 keV or 2–20 MeV, and 5 for neutrons of energy less than 10 keV or

greater than 20 MeV. Thus, photons and electrons have a biological effectiveness of 1, by

definition, and the radiation weighting factors for the other radiation types represent judgments

about their biological effectiveness in humans relative to photons and electrons. As discussed

earlier in this report (Section III.H), the radiation weighting factors just mentioned are used

here to convert equivalent dose in Sv, calculated according to the ICRP weighting factors, to

absorbed dose in Gy, preparatory to calculation of ERR and assigned share.

For the purpose of estimating cancer risks and assigned shares in identifiable individuals who

received known (estimated) radiation exposures, the term “radiation effectiveness factor,”

denoted by REF, has been developed to describe the biological effectiveness of different

radiation types (Kocher et al. 2002). There are two reasons why a new term, other than “RBE”

or “radiation weighting factor,” is used. First, “RBE” is not appropriate because this quantity

strictly applies only to results obtained from specific radiobiological studies and thus should not

be used to describe an extrapolation of such results to a different biological endpoint, biological

system, or condition of exposure. Second, as discussed above, the radiation weighting factor is a

prescribed point quantity, without uncertainty, which is used in radiation protection to

calculate equivalent doses, but it is not intended to be used to estimate cancer risks and

assigned shares in identifiable individuals who received known exposures. Furthermore, cancer

risks and assigned shares are estimated based on estimates of absorbed dose, and it is essential

that uncertainties in the biological effectiveness of different radiation types relative to a defined

reference radiation be taken into account.

The radiation effectiveness factor for a particular radiation type is used in estimating cancer

risks and assigned shares from actual exposures in accordance with one of the following

equations:

36 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Solid tumors—

Rγ,H

R = REFL × × D, (IV.H.1)

DDREFγ

R = REFH × Rγ,H × D, (IV.H.2)

Leukemias—

R = α × REFL × D, (IV.H.3)

R = α × {REFL × D + (REFL × D)

2

} (IV.H.4)

In these equations—

• R is the risk of a particular cancer (i.e., the excess relative risk, ERR) due to exposure to

a particular radiation type;

• REF is the radiation effectiveness factor for the radiation type and cancer type of

concern;

• the subscripts “L” and “H” denote low doses and dose rates and high doses and dose rates,

respectively;

• Rγ,H is the risk coefficient (ERR per Gy) at high doses and high dose rates of the

reference high-energy gamma (γ) radiation with a defined biological effectiveness of 1,

assuming linearity in the dose-response relationships for all solid tumors;

• DDREF is the dose and dose-rate effectiveness factor, which takes into account that the

ERR per Gy for solid tumors at low doses and dose rates of photons (and electrons) may

be less than the values of Rγ,H obtained from studies of exposed populations;

• α is the coefficient of the linear and quadratic terms in the linear-quadratic dose-response

relationship assumed for leukemias under conditions of acute exposure to high-energy

gamma rays (equation IV.D.4); and

• D is the estimated dose from the radiation type of concern.

For most solid tumors, the risk coefficients at high doses and dose rates of high-energy gamma

rays, Rγ,H, are obtained from studies of the Japanese atomic bomb survivors. The coefficients for

dose and dose-squared in the linear-quadratic dose-response relationship for leukemias under

conditions of acute exposure to high-energy gamma rays also are obtained from studies of the

atomic bomb survivors. The data on leukemias indicate that the two coefficients are

approximately equal numerically, and this assumption is used in this work. In the radiation

effectiveness factor (REF) for the radiation type of concern, the subscripts L and H denote that

this factor is estimated based on data on RBE at low doses and dose rates (L) or at high doses

and dose rates (H) of the reference radiation. 

The equation selected depends on the particular radiation type and cancer of concern. As

discussed by Kocher et al. (2002), eq. (IV.H.1) for solid tumors is used in cases of exposure to

photons, electrons, and alpha particles, eq. (IV.H.2) for solid tumors is used in cases of exposure

IV. Description of the Approach 37
to neutrons, eq. (IV.H.3) for leukemias is used in cases of exposure to alpha particles and

neutrons and in cases of chronic exposure to photons and electrons, and eq. (IV.H.4) for

leukemias is used in cases of acute exposure to photons and electrons. Not shown in eqs.

(IV.H.1)–(IV.H.3) is a factor representing an inverse dose-rate effect, which is applied to all

exposures to alpha particles and to chronic exposures to neutrons. This factor, which is a

multiplier on the right-hand side of these equations, takes into account that the biological

effectiveness of high-LET radiations may be higher under conditions of chronic exposure than

under conditions of acute exposure. The use of eqs. (IV.H.1)–(IV.H.4) is discussed further later

in this section. 

As noted previously, uncertainties in radiation effectiveness factors for different radiation types

are taken into account in estimating cancer risks and assigned shares. These uncertainties are

described by means of subjective probability (uncertainty) distributions. The assumed

probability distributions are intended to represent judgments about the current state of

knowledge of the effectiveness of the different radiation types, relative to high-energy gamma

rays, in inducing cancers in humans; they are not intended to represent statistical distributions

of results that would be obtained if radiobiological studies of the effectiveness of the different

radiations in inducing cancers in humans were performed. The factors representing an inverse

dose-rate effect for alpha particles or neutrons under conditions of chronic exposure also are

described by subjective probability distributions. 

The probability distributions of the radiation effectiveness factors used in this report were

developed by Kocher et al. (2002) of SENES Oak Ridge under contract with the National

Institute of Occupational Safety and Health (NIOSH), and have taken into account peer

reviews of the work by NIOSH consultants. The assumed probability distributions of the

radiation effectiveness factors for photons and electrons are summarized in Table IV.H.1 (page

65), the distributions for alpha particles are summarized in Table IV.H.2 (page 66), and the

distributions for neutrons are summarized in Table IV.H.3 (page 67). For photons and electrons,

the probability distributions of the radiation effectiveness factors are applied to all cancers,

whereas separate probability distributions are developed for leukemias (including lymphomas

and lymphocytic cancers) in cases of exposure to alpha particles and neutrons. The probability

distributions of the correction for an inverse dose-rate effect are included in Tables IV.H.2 and

IV.H.3 on pages 66 and 68, respectively. For present purposes, it is assumed that any exposure to

proton radiation, a radiation type not discussed in the analysis by Kocher et al. (2002), will be

at high proton energies, with REF = 1 relative to high-energy photons.

The procedure for using eqs. (IV.H.1)–(IV.H.4) in estimating cancer risks and assigned shares is

as follows. It is assumed that the exposure history of an individual is given in terms of the

equivalent dose, in Sv, to the organ or tissue in which a cancer has occurred—i.e., the dose in

that organ or tissue modified by a standard radiation weighting factor, denoted by wR (formerly

called the average quality factor, Q)—and that the equivalent dose is given for each radiation

type (photons, electrons, alpha particles, and neutrons) separately. From the given equivalent

dose for a particular radiation type in an organ or tissue (T), denoted by HT, the dose (D) in

that organ or tissue, in Gy, is calculated as DT = HT/wR. The dose for each radiation type is the

quantity that is input to the calculation of cancer risk and assigned share, and each of these

doses is modified by the relevant radiation effectiveness factor in accordance with the

appropriate equation. 

38 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
The treatment of the biological effectiveness of the different radiation types of concern, as

represented by the probability distributions of the radiation effectiveness factors summarized in

Tables IV.H.1–IV.H.3, differs from the 1985 NIH report in two respects. First, with the

exceptions of lung cancer among uranium miners exposed to inhaled radon and its short-lived

decay products, with exposure expressed in working level months (WLM), and bone cancer

among patients injected with the short-lived alpha emitter 224Ra, the 1985 report did not

explicitly consider radiations other than those of low LET, for which the biological

effectiveness was assumed to be unity. The report mentioned that high-LET radiations would

require incorporation of a biological effectiveness factor, not provided in the report. It was

recognized that, at low doses and dose rates, high-energy gamma rays might be less damaging

than lower-energy X-rays, but the NIH Working Group did not have sufficient information to

make such a distinction. In the present work, the various biological effectiveness values of all

radiation types (photons, electrons, alpha particles, and neutrons) are taken into account for all

cancers, with the exception that radon-related lung cancer continues to be treated separately

based on estimates of exposure in WLM. In particular, a distinction is made between the

effectiveness of high-energy gamma rays and lower-energy X-rays, as well as low-energy

electrons. The second important difference is that uncertainties in the biological effectiveness

of all radiation types relative to high-energy gamma rays are now taken into account. Since the

1985 NIH report focused on radiations that were assumed to be equally effective at any

energies, there was no need at that time to consider uncertainties in biological effectiveness.

I. Modification by epidemiological risk factors

Site-specific studies of radiation dose and cancer risk, in the LSS sample and in other exposed

populations continually followed up over time, generally proceed in a series of steps beginning

with the evaluation of evidence that a dose-related excess risk actually exists. Usually, the first

modifiers of dose response to be considered are gender, age at exposure, age at observation

(attained age), and time following exposure, since information about them is usually obtained

at the same time as information on radiation exposure and disease occurrence. Modification of

dose response by other factors is a more difficult problem, because it usually requires special

data-gathering efforts, such as with an embedded case-control study. Informative studies of

interaction between radiation dose and epidemiological risk factors have been carried out for

reproductive history in the case of breast cancer and for smoking history in the case of lung

cancer. 

1. General formulation 

If radiation dose D and factor f are multiplicative in effect, then the excess relative risk

associated with exposure D is independent of f, i.e., ERR(D|f) = ERR(D). If D and f are

additive in effect, then the conditional ERR associated with D given exposure f is

ERR(D|f) = ERR(D)/(1 + ERR(f)).

2. Breast cancer: Interaction of radiation and age at first full-term pregnancy 

Reproductive history is known to be an important breast cancer risk factor. In particular, early

age at first full-term pregnancy has been shown, in virtually every population that has been

IV. Description of the Approach 39
studied, to be protective. A case-control interview study of female A-bomb survivors examined

the interaction of this risk factor with radiation dose (Land et al. 1994) and found that an

additive interaction model was rejected, whereas a multiplicative interaction model was

consistent with the data. A general risk model, 

Rmix(D,X;ß,θ) = (1 + αED)(1 + ßX/{1 + αED}θ

),

was used to distinguish between the multiplicative model (corresponding to θ = 0),

Rmult(D,X;ß) = (1 + αED)(1 + ßX),

and the additive model (corresponding to θ = 1),

Radd(D,X;ß) = 1 + αED + ßX.

Here, D is radiation dose, X is age at first full-term pregnancy, αE is a parametric function

describing radiation dose response as a function of age at exposure E, and ß is an unknown

parameter corresponding to X. The maximum likelihood estimate of the parameter θ was

negative (–0.25) (Land 1994) and the likelihood distribution placed less than 10% probability

on values greater than zero in calculations performed for the present report. Thus, it appears

that very little additional uncertainty would be contributed by allowing for deviations from the

multiplicative interaction model, for which no adjustment of ERR1Sv is required for age at first

full-term pregnancy. This report therefore makes no uncertainty adjustment for this factor. 

3. Lung cancer: Interaction of radiation dose with smoking history 

Interaction analyses of A-bomb survivors (Blot et al. 1984) and uranium miners (NAS/NRC

1988) failed to discriminate between additive and multiplicative interaction models, although

the BEIR IV committee concluded that the data were more consistent with a multiplicative

interaction (NAS/NRC 1988). More recently, Lubin and Steindorf (1995) modeled joint

relative risks for smoking history (ever vs. never) and exposure to inhaled radon decay products

among six cohorts of U.S. uranium miners for which such information was available. They

concluded that, at that level of smoking history detail, the best-fitting interaction model was

intermediate between the additive and multiplicative interaction models. The BEIR VI

committee (NAS/NRC 1999) applied the Lubin-Steindorf approach using more recent data

and reached a similar conclusion. Treatment of smoking status for radon-related lung cancer

risk is discussed above in Section IV.D.5.

A new analysis of lung cancer and smoking history among A-bomb survivors by Pierce et al.

(2003) was based on 45,113 survivors followed through 1994, including 592 lung cancer cases,

for whom smoking history information was available from questionnaire responses and clinical

interviews. The main finding was that radiation and smoking effects on lung cancer risk were

statistically inconsistent with a multiplicative interaction model, and “quite consistent” with an

additive model. At the Working Group’s request, Dr. Pierce kindly carried out dose-response

analyses on his data set according to model (IV.D.1), which showed that the values ß = 0.843, 

γ = –0.5255, and δ = –1.626 used in Approach 2 (Section IV.D.1) were statistically consistent

with the lung cancer data. He also estimated the likelihood profile distribution for the

parameter α assuming the above parameter values, so that Approach 2 could be applied to lung

cancer (Table IV.D.3) as described in Section IV.D.1. However, because the analysis clearly

supported the additive interaction model, the analysis was adjusted for smoking and the

40 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
tabulated profile pertains to risk among lifetime nonsmokers. Also, for lung cancer, the

tabulated profile is adjusted to be midway between the values for the two sexes corresponding

to ß = 0.843.

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

by the factors indicated in columns 2 and 3 of Table IV.I.1 (page 69). These factors were

calculated as described on pp. 48–51 of the 1985 report and based on lung cancer relative risks

by smoking category given by Rogot and Murray (1980) and the distribution of the U.S.

population by smoking status in 1964–65 as published by the National Center for Health

Statistics (1967). For the present report, these factors have been updated using 1993

information on the smoking status distribution provided by the Centers for Disease Control

(1995). The updated distribution differs substantially from that used in the 1985 report as

shown in Table IV.I.2 (page 70). Because the CDC report did not provide data on amount

smoked, it was assumed that among current smokers the distribution by amount smoked was

the same as that used in the 1985 report (NIH 1985, p.50). It was also assumed that the

relative risks by smoking category remained appropriate. The revised factors for additive

interaction are given in the last two columns of Table IV.I.1. 

Absent the findings of Pierce et al. (2003), an approach guided by the BEIR VI findings for

radon-related lung cancer risk would be to multiply the ERR1Sv for lung cancer, unadjusted for

smoking, by a factor WS taken to be x + (1 – x)WS*, where S indexes smoking categories, the

WS* are the factors given in columns 4 and 5 of Table IV.I.1, and x is assumed to follow a

triangular distribution (0, 1, 1.1). This uncertainty distribution for x allows the ERR1Sv for lung

cancer to range from that obtained with an additive interaction (x = 0) to that obtained with a

multiplicative interaction (x = 1), with a probability of about .10 for a supermultiplicative

interaction (x > 1). The median of the uncertainty distribution is .74, and at this value, WS =

1.97 for male never-smokers, 0.87 for male ever-smokers, 1.75 for female never-smokers, and

0.85 for female ever-smokers. Thus, at the median value, the estimated ERR1Sv for neversmokers would be a little more than twice that for ever-smokers. A ratio of two was used by the

BEIR VI committee, and was obtained from analyses of uranium miner data (NAS/NRC 1999,

154). 

However, the analysis of Pierce et al. (2003) suggests that the radiation-smoking interaction

among LSS subjects is more nearly additive than that estimated for uranium miners.

Accordingly, for external radiation the Working Group adopted an uncertainty model for

interaction that puts 50% probability on the additive model and 50% on the model described

in the preceding paragraph. Of course, because the profile in Table IV.D.3 corresponds to neversmokers, the tabulated values WS* were normalized to the never-smoker standard, i.e., they

were divided by 4.74 for males and by 3.90 for females.

4. Nonmelanoma skin carcinoma: Interaction between ionizing and ultraviolet radiation 

Ron et al. (1998) found significantly different (p < .02) ERR1Sv values for basal cell skin

carcinoma (BCSC) occurring on the face and hands (0.4, 90% CI –0.1–2.1) and on the rest of

the body (4.7, 1.2–1.3), suggesting a submultiplicative, or possibly even additive, interaction

between UV and ionizing radiation. This finding suggests that ERR1Sv in lighter-skinned, and

therefore more UV-sensitive, populations could be less than that observed in the LSS

IV. Description of the Approach 41
population. On the other hand, Shore et al. (2002) reported 124 BCSC cases among 1699

white patients treated by X-ray during childhood for scalp ringworm, compared to 21 among

1035 white nonexposed patients. Among African Americans, however, only 3 BCSC cases

were seen among 525 exposed patients compared to 0 among 345 nonexposed patients. This

result, unlike that of Ron et al. is inconsistent with additive interaction between ionizing

radiation and protection from ultraviolet radiation by skin pigmentation or clothing, as risk

factors for BCSC. Judging that we do not now have a good basis for evaluating this interaction,

the Working Group has chosen to use the general “complete ignorance” uncertainty model

discussed in Section IV.G above for transfer of risk estimates from one population to another,

for transfer of ERR1Sv estimates for nonmelanoma skin cancer from the LSS population to

identifiable U.S. subpopulations with (on average) different levels of skin pigmentation.

The following text table shows population nonmelanoma skin cancer incidence rates (cases per

100,000 per year, directly standardized to the age distribution of the 1970 U.S. population) for

African-American, Hispanic, and non-Hispanic White Americans (Scotto 1996, Table 60-4)

and Japanese (Muir 1987, Hiroshima and Nagasaki tumor registry data):

Country U.S. Japan

Subgroup African-American Hispanic Non-Hispanic White

Sex:

Males

Rate 4.1 61.6 461.2 6.05

Standard Error 0.83 4.77 4.38 0.65

Females

Rate 4.5 45.1 246.1 4.42

Standard Error 0.76 3.49 2.86 0.48

Thus, for additive interaction model transfer of LSS-based ERR1Sv to U.S. Hispanic males,

ERR1Sv was multiplied by the ratio 6.05/61.6 = 0.098 and, for additive transfer to U.S. AfricanAmerican females, the multiplier was 4.42/4.5 = 0.98. Nonmelanoma cancer rates were not

available for the remaining two U.S. Census racial/ethnic groups, Asians and Pacific Islanders,

and Native Americans, and the LSS ERR1Sv estimate was applied to those groups without

correction for transfer (i.e., a multiplicative interaction was assumed). Finally, the additive

interaction model multiplier for an optional category, “all races/race not specified,” was

computed as the weighted mean of subpopulation-specific multipliers according to the

projected 2000 distribution (Indiana University 1999) of the U.S. population: 12% AfricanAmerican, 11% Hispanic, 72% non-Hispanic White, and 5% Native Americans, Asians, and

Pacific Islanders.

J. Susceptible subgroups

Genetic susceptibility to radiation carcinogenesis is known to occur in patients with xeroderma

pigmentosum or hereditary retinoblastoma, and the possibility of other such associations is of

great interest for theories of carcinogenesis. However, most known genetic syndromes

predisposing to cancer are rare, and interactions with radiation dose have not been quantified

(ICRP 1998). Such interactions have therefore not been explored in the present report. 

42 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
K. Additional sources of uncertainty

As mentioned above (Section IV.A), AS is not intended to represent the probability that a

particular individual’s cancer was caused by his or her radiation exposure, but rather, the

fraction of cases of a particular kind of cancer, diagnosed at a particular age among a large group

of U.S. residents with a similar exposure history, that would not have occurred in the absence

of that exposure. Possible modifying effects of age at exposure, gender, age at diagnosis, and

time following exposure, plus (for certain sites) smoking history and reproductive history have

been studied, and that information has been incorporated into the model. The Working Group

has also introduced crude uncertainty factors for transfer of risk coefficients between

populations with different baseline risks. 

It is likely that there are other sources of bias and uncertainty influencing radiation-related risk

and AS, about which we have no useful information and, thus, no solid grounds for taking

action. However, there may be instances in which a case can be made for additional

uncertainty. Following the recommendation of the NRC review committee (NAS/NRC 2000)

that any additional uncertainty adjustment be documented and justified by an authoritative

review panel, we have provided the option for such an adjustment in the expectation that it

would be used very rarely, if at all.

IV. Description of the Approach 43
44 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.C.1. Solid cancer sites covered in the present report. Cancer site Organ ICD-9 Number of cases Treatment in present report dose used site codes* Exposed Nonexposed

(≥ 10 mSv) (< 10 mSv)

All solid tumors 140

–199 4327 4286 Not calculated

Oral cavity and pharynx Skin 140

–149 64 68 Calculated as a group

Digestive system 150

–159 2355 2442 Calculated as a group

Esophagus Stomach 150 84 101 Calculated separatelyStomach Stomach 151 1305 1353 Calculated separatelyColon Intestine 153 223 234 Calculated separatelyRectum Bladder 154 179 172 Calculated separatelyLiver Liver 155 283 302 Calculated separatelyGallbladder Pancreas 156 143 152 Calculated separatelyPancreas Pancreas 157 122 118 Calculated separatelyOther Intestine 152, 158, 159 16 10 Use results for digestive system as a group

Respiratory system 160

–165 528 499 Not calculated

Trachea, bronchus, and lung Lung 162 449 423 Calculated separately (Pierce et al. 2003)Other respiratory cancers Lung 160, 161, 163

–165 79 76 Calculated separately

Bone Skeleton 170 4 11 Use results for other & ill-defined sitesSkin 172

–173 97 84 Not calculated

Melanoma 172 6 7 Not calculatedBasal cell carcinoma Skin 173 54 26 Dale Preston, personal communicationOther nonmelanoma skin ca. Skin 173 51 41 Dale Preston, personal communication

Continued on page 45 *Converted from the ICD-0, version 1 codes used by Thompson (1994)
IV. Description of the Approach 45

Table IV.C.1 (continued). Solid cancer sites covered in the present report.Cancer site Organ ICD-9 Number of cases Treatment in present report

dose used site codes* Exposed Nonexposed

(≥ 10 mSv) (< 10 mSv)

Female breast Breast 174 289 240 Calculated separatelyFemale genital 179–184 430 461 Not calculated

Ovary Ovary 183 66 67 Calculated separatelyOther female genital Uterus 179–182, 184 364 394 Calculated separately

Male genital 185–187 74 86 Calculated separately

Prostate Bladder 185 61 79 (Uses risk estimates for male Other Testis 186, 187 13 7 genital group)

Urinary system 188–189 172 153 Calculated separately

Bladder Bladder 188 115 95 Calculated separatelyKidney and residual Intestine 189.0–189.9 57 68 Uses risk estimates for urinary systemurinary organs

Nervous system Brain 191, 192 69 56 Calculated separatelyThyroid Thyroid 193 129 96 Based on data from Ron et al. 1995Other and ill-defined sites Intestine 170–172, 120 101 Calculated as a group(Residual solid cancers) 175, 190, 

194–199

*Converted from the ICD-0, version 1 codes used by Thompson (1994) 
46 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.C.2. Hematopoietic cancers covered in the present report. Cancer type ICD-9 Number of cases Treatment in present report site codes* Exposed Nonexposed Total

(≥ 10mSv)

Leukemia, all types (except 204.0, 143 90 233 Calculated as a group

chronic lymphocytic leukemia) 204.2

–208

Acute myelogenous leukemia 205.0 60 43 103 Calculated separatelyAcute lymphocytic leukemia 204.0 24 9 33 Calculated separatelyChronic myelogenous leukemia 205.1 41 17 58 Calculated separatelyLymphoma 200

–202 86 105 191 Combined, and calculated as a group Multiple myeloma 203 31 29 60

*Converted from ICD-0, version 1 
IV. Description of the Approach 47

Table IV.D.1. Computation of statistical uncertainty for ERR1Sv: Approach 1 as applied to specific solid cancer sites.Cancer site log(α) γ δ Var (log α) Cov (log α, γ) Cov (log α, δ ) Var(γ) Cov (γ, δ) Var (δ)

(correlation) (correlation)

All digestive –1.590 –.0477 –1.622 0.10621 0.001868 –0.020011 .0003332 –.007395 .56236

Males (0.314) (–0.082)

All digestive –0.8614 –.0477 –1.622 0.05018 0.001403 –0.001882 .0003332 –.007395 .56236

Females (0.343) (–0.011)

Stomach –0.7998 –.04723 –1.781 0.07512 0.001380 0.006263 .0003252 –.007185 .54764

Females (0.279) (0.031)

Liver –1.049 –.05204 –1.579 0.17108 0.002291 –0.03610 .0003255 –.007347 .57368

Both sexes (0.307) (–0.115)

Breast 0.02109 –.03722 –2.006 0.05456 0.002586 –0.01907 .0003530 –.007934 .58018

Females (0.589) (–0.107)

*ERR/Sv is assumed to be lognormally distributed with geometric mean (GM) and geometric standard deviation (GSD)

GM = α × exp{γ f(e) + δ g(a)},

GSD = exp{[var(log α) + 2 cov(log α, γ) f(e) + 2 cov(log α, δ) g(a) + var(γ) f(e)2 + 2 cov(γ, δ) f(e) g(a) + var(δ) g(a)2]1/2},

where f(e) = min[max(–15, e – 30), 0] and g(a) = min[ln(a/50), 0] for exposure age e and attained age a.
48 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.D.2. Computation of statistical uncertainty for ERR1Sv: Likelihood profile quantiles for parameter 

α obtained

by Approach 2 treatment of specific cancers for exposure age 

e

≥ 30 and attained age 

a

≥ 50.

Profile Oral cavityquantiles and pharynx Esophagus Stomach Colon Rectum Gall bladder Pancreas

Males Females Males Females Males Males Females Males Females Males Females Males Females

0.9975 0.8004 1.765 1.216 3.253 0.3802 1.531 1.671 0.4946 1.078 0.5258 1.114 0.7062 1.5100.995 0.7321 1.619 1.117 2.919 0.3516 1.429 1.567 0.4675 1.022 0.4725 1.013 0.6401 1.3790.9875 0.6404 1.423 0.9820 2.492 0.3137 1.289 1.423 0.3946 0.8701 0.4013 0.8761 0.5509 1.2010.975 0.5694 1.271 0.8755 2.179 0.2846 1.177 1.308 0.3413 0.7581 0.3465 0.7677 0.4815 1.0600.95 0.4962 1.113 0.7634 1.869 0.2545 1.058 1.185 0.2888 0.6467 0.2905 0.6538 0.4095 0.91170.875 0.3935 0.8909 0.6025 1.450 0.2112 0.8852 1.005 0.2178 0.4917 0.2128 0.4893 0.3083 0.69840.8413 0.3651 0.8288 0.5563 1.324 0.1967 0.8357 0.9537 0.1951 0.4396 0.1921 0.4442 0.2802 0.63780.5 0.2055 0.4755 0.2905 0.6759 0.1184 0.5405 0.6430 0.0812 0.1875 0.0756 0.1805 0.1227 0.28710.1587 0.0907 0.2136 0.0784 0.1779 0.0497 0.3020 0.3857 < 0 < 0 < 0 < 0 < 0 < 00.125 0.0739 0.1736 0.0545 0.1229 0.0369 0.2672 0.3523 < 0 < 0 < 0 < 0 < 0 < 00.05 0.0308 0.0724 < 0 < 0 0.0051 0.1694 0.2463 < 0 < 0 < 0 < 0 < 0 < 00.025 0.0082 0.0190 < 0 < 0 < 0 0.1134 0.1849 < 0 < 0 < 0 < 0 < 0 < 00.0125 < 0 < 0 < 0 < 0 < 0 0.0671 0.1336 < 0 < 0 < 0 < 0 < 0 < 00.005 < 0 < 0 < 0 < 0 < 0 0.0176 0.0772 < 0 < 0 < 0 < 0 < 0 < 0

0.0025 < 0 < 0 < 0 < 0 < 0 < 0 0.0409 < 0 < 0 < 0 < 0 < 0 < 0Continued on page 49
IV. Description of the Approach 49

Table IV.D.2 (continued). Computation of statistical uncertainty for ERR1Sv: Likelihood profile quantiles for parameterα obtained by Approach 2 treatment of specific cancers for exposure age e ≥ 30 and attained age a ≥ 50.*Profile Respiratory, Male Central Residualquantiles nonlung Urinary tract Bladder Ovary genital nervous system solid cancers Lymphoma*

Males Females Males Females Males Females Females Males Males Females Males Females Both sexes

0.9975 0.7400 1.716 1.480 3.561 1.561 3.887 2.02 1.51 0.9370 2.006 1.504 2.989 1.6000.995 0.7009 1.619 1.396 3.354 1.474 3.577 1.86 1.44 0.8744 1.880 1.403 2.814 1.3940.9875 0.5725 1.319 1.281 3.071 1.312 3.172 1.65 1.23 0.7444 1.618 1.267 2.575 1.1340.975 0.4810 1.105 1.189 2.848 1.188 2.864 1.48 1.08 0.6491 1.424 1.160 2.385 0.94650.95 0.3930 0.9008 1.092 2.613 1.062 2.551 1.30 0.939 0.5553 1.230 1.048 2.185 0.76510.875 0.2755 0.6291 0.9489 2.273 0.8843 2.115 1.05 0.733 0.4295 0.9661 0.8887 1.893 0.53210.8413 0.2344 0.5366 0.9080 2.176 0.8311 1.987 0.982 0.667 0.3925 0.8862 0.8440 1.810 0.47420.5 0.0606 0.1377 0.6635 1.601 0.5388 1.282 0.576 0.3348 0.2057 0.4755 0.5859 1.315 0.17800.1587 < 0 < 0 0.4650 1.137 0.3091 0.7337 0.267 0.0670 0.0759 0.1772 0.3883 0.9148 0.01420.125 < 0 < 0 0.4380 1.073 0.2778 0.6587 0.230 0.0389 0.0600 0.1403 0.3626 0.8592 0.00320.05 < 0 < 0 0.3571 0.8820 0.1869 0.4414 0.117 < 0 0.0189 0.0444 0.2871 0.6946 < 00.025 < 0 < 0 0.3102 0.7698 0.1352 0.3176 0.0569 < 0 0.0044 0.0101 0.2445 0.5986 < 00.0125 < 0 < 0 0.2712 0.6759 0.0925 0.2159 < 0 < 0 < 0 < 0 0.2099 0.5187 < 00.005 < 0 < 0 0.2285 0.5716 0.0457 0.1057 < 0 < 0 < 0 < 0 0.1726 0.4305 < 0

0.0025 < 0 < 0 0.2011 0.5038 0.0173 0.0393 < 0 < 0 < 0 < 0 0.1492 0.3738 < 0*For exposure age e < 30 and/or attained age a < 50, ERR at 1 Sv = α × h(e, a; γ, δ), where h(e, a; γ, δ) is assumed to be statistically independent of α and lognormally

distributed with geometric mean (GM) and geometric standard deviation (GSD) as follows:GM = exp{–0.05255 f(e) –1.626 g(a)},

GSD = exp{[0.0003261 × f(e)2 – 2 × 0.007297 × f(e) × g(a) + 0.5648 × g(a)2]1/2},

where f(e) and g(a) are defined in the footnote to Table IV.D.1.
50 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Table IV.D.3. Computation of statistical uncertainty for ERR1Sv: Likelihood profile quantiles

for parameter α obtained by modified Approach 2 treatment of lung cancer and cancers of the

female genital organs other than ovary.

Profile Lung Female genital less ovary

quantiles Never Smokers, Both Sexes§ Females†

0.9975 1.822 0.172

0.995 1.724 0.136

0.9875 1.590 0.0866

0.975 1.482 0.0791

0.95 1.368 0.0607

0.875 1.200 0.0463

0.8413 1.152 0.0030

0.5 0.8603 –0.189

0.1587 0.6127 –0.278

0.125 0.5792 –0.289

0.05 0.4750 < 0

0.025 0.4133 < 0

0.0125 0.3610 < 0

0.005 0.3024 < 0

0.0025 0.2642 < 0

§ For lung cancer, ERR at 1 Sv = α × h*(s, e, a; β, γ, δ), where independence is assumed between α and 

h*(s, e, a; β, γ, δ) = exp{β × s + γ × f(e) + δ × g(a)},

and where s = –0.5 for males and 0.5 for females. h*(s, e, a; β, γ, δ) is assumed to be lognormally distributed with 

GM = exp{0.843 s – 0.05255 f(e) – 1.626 g(a)},

GSD = exp{[0.0625 s2 – 2 × 0.000347 s × f(e) + 2 × 0.00830 s × g(a) + 0.000330 × f(e)

2 – 2 × 0.00708 f(e) × g(a) + 0.562 g(a)2

]

1/

2

}. 

† For female cancers other than ovary, for which γ and δ were assumed to be zero, the statistical uncertainty distribution of 

α = ERR at 1 Sv is completely specified by the tabulated likelihood profile distribution.
IV. Description of the Approach 51

Table IV.D.4. Computation of statistical uncertainty for parameter α*: Likelihood profile distributions for leukemiaexcluding CLL, by exposure age and time since exposure.Profile Exposure age 20 Exposure age 30quantiles 5 yr 10 yr 15 yr 25 yr 35 yr 45 yr 5 yr 10 yr 15 yr 25 yr 35 yr 45 yr0.9975 72.69 29.87 13.54 3.967 1.671 0.8029 37.55 18.19 9.412 3.361 1.672 0.93420.995 65.99 27.68 12.71 3.744 1.538 0.7102 34.69 17.09 8.944 3.206 1.556 0.83870.9875 57.46 24.83 11.62 3.438 1.358 0.5913 30.97 15.62 8.311 2.991 1.400 0.71540.975 51.20 22.68 10.78 3.194 1.217 0.5038 28.16 14.49 7.816 2.818 1.277 0.62390.95 45.05 20.51 9.922 2.934 1.071 0.4180 25.33 13.33 7.299 2.633 1.149 0.53340.875 36.94 17.57 8.719 2.554 0.8658 0.3065 21.47 11.70 6.559 2.358 0.9676 0.41370.8413 34.80 16.76 8.385 2.445 0.8091 0.2778 20.42 11.25 6.350 2.278 0.9168 0.38200.5 23.55 12.35 6.481 1.784 0.4911 0.1352 14.65 8.662 5.121 1.789 0.6253 0.21850.1587 16.10 9.173 5.015 1.239 0.2730 0.0585 10.52 6.674 4.124 1.366 0.4060 0.11730.125 15.21 8.776 4.824 1.168 0.2480 0.0511 10.01 6.416 3.991 1.308 0.3786 0.10620.05 12.65 7.592 4.244 0.9509 0.1783 0.0320 8.481 5.633 3.580 1.127 0.2979 0.07550.025 11.25 6.925 3.907 0.8277 0.1428 0.0234 7.627 5.180 3.338 1.019 0.2535 0.06010.0125 10.14 6.380 3.627 0.7271 0.1161 0.0175 6.933 4.804 3.134 0.9281 0.2181 0.04860.005 8.959 5.788 3.315 0.6185 0.0898 0.0123 6.184 4.389 2.905 0.8259 0.1809 0.03740.0025 8.227 5.412 3.113 0.5503 0.0745 0.0095 5.709 4.120 2.754 0.7591 0.1581 0.0310*Linear-quadratic dose response: ERR1Sv = α for chronic exposure; ERR1Sv = 2 × α for acute exposure.
52 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.D.5. Computation of statistical uncertainty for parameter 

α*: Likelihood profile distributions for acute

lymphocytic leukemia, by exposure age and time since exposure.Profile Exposurequantiles Exposure age < 20 age 

≥ 20,

5 yr 10 yr 15 yr 20 yr 25 yr 30 yr 35 yr 40 yr 45 yr 50 yr > 5 yr

0.9975 823.6 206.9 68.13 28.42 14.33 8.308 5.277 3.54 2.452 1.732 11.320.995 682.2 176.6 58.92 24.6 12.29 6.972 4.291 2.771 1.84 1.242 9.9560.9875 521.1 140.8 47.85 19.97 9.787 5.358 3.138 1.91 1.189 0.7503 8.2660.975 416.5 116.7 40.23 16.73 8.037 4.25 2.377 1.372 0.8066 0.4795 7.0580.95 324.9 94.87 33.16 13.69 6.399 3.236 1.711 0.9272 0.5096 0.2825 5.9000.875 221.3 68.87 24.52 9.91 4.382 2.041 0.9778 0.4755 0.2333 0.1151 4.4190.8413 197.1 62.56 22.38 8.96 3.88 1.757 0.8142 0.3822 0.1807 0.0859 4.0370.5 92.5 33.4 12.07 4.36 1.574 0.5685 0.2053 0.0742 0.0268 0.0097 2.1140.1587 44.1 18.11 6.22 1.83 0.503 0.1345 0.0355 0.0093 0.0024 0.0006 0.95700.125 39.5 16.53 5.59 1.57 0.4105 0.104 0.0260 0.0064 0.0016 0.0004 0.82780.05 27.4 12.24 3.83 0.910 0.1975 0.0413 0.0085 0.0017 0.0003 0.0000 0.47970.025 21.8 10.1 2.93 0.610 0.1155 0.0210 0.0038 0.0007 0.0001 0.0000 0.30680.0125 17.7 8.49 2.25 0.409 0.0673 0.0107 0.0017 0.0003 0.0000 0.0000 0.18000.005 13.8 6.90 1.57 0.236 0.0323 0.0042 0.0005 0.0000 0.0000 0.0000 0.0601

0.0025 11.6 5.96 1.19 0.153 0.0180 0.0020 0.0002 0.0000 0.0000 0.0000 0.0000*Linear-quadratic dose response: ERR1Sv = 

α for chronic exposure; ERR1Sv = 2 × α for acute exposure.
IV. Description of the Approach 53

Table IV.D.6. Computation of statistical uncertainty for parameter α*: Likelihood profile distributions for acutemyelocytic leukemia, by time since exposure.Profile Time since exposurequantiles 5 yr 10 yr 15 yr 20 yr 25 yr 30 yr 35 yr 40 yr 45 yr 50 yr0.9975 28.57 16.54 10.10 6.666 4.903 4.071 3.707 3.563 3.527 3.5500.995 25.57 15.12 9.385 6.266 4.627 3.819 3.428 3.232 3.129 3.0750.9875 21.79 13.28 8.443 5.729 4.253 3.478 3.057 2.802 2.626 2.4930.975 19.05 11.91 7.727 5.314 3.959 3.210 2.771 2.479 2.261 2.0850.95 16.40 10.55 7.001 4.884 3.651 2.931 2.477 2.157 1.907 1.7010.875 12.96 8.719 5.997 4.277 3.208 2.530 2.067 1.722 1.450 1.2280.8413 12.06 8.229 5.722 4.108 3.082 2.416 1.953 1.605 1.331 1.1100.5 7.453 5.579 4.176 3.126 2.340 1.752 1.311 0.9810 0.7346 0.54990.1587 4.548 3.742 3.024 2.356 1.734 1.217 0.8329 0.5627 0.3776 0.25230.125 4.215 3.518 2.877 2.255 1.653 1.147 0.7734 0.5140 0.3390 0.22260.05 3.267 2.860 2.435 1.947 1.401 0.9314 0.5961 0.3745 0.2329 0.14400.025 2.765 2.497 2.183 1.768 1.252 0.8064 0.4978 0.3010 0.1800 0.10690.0125 2.374 2.206 1.976 1.618 1.126 0.7024 0.4188 0.2443 0.1408 0.08060.005 1.972 1.895 1.749 1.453 0.9829 0.5880 0.3354 0.1870 0.1029 0.05620.0025 1.728 1.700 1.603 1.345 0.8885 0.5146 0.2839 0.1531 0.0815 0.0430*Linear-quadratic dose response: ERR1Sv = α for chronic exposure; ERR1Sv = 2 × α for acute exposure.
54 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.D.7. Computation of statistical uncertainty for parameter 

α*: Likelihood profile distributions for chronic

myelogenous leukemia, by sex and time since exposure.Profile Time since exposurequantiles 5 yr 10 yr 15 yr 20 yr 25 yr 30 yr 35 yr 40 yr 45 yr 50 yrMales0.9975 134.6 34.15 14.49 7.474 4.262 2.573 1.606 1.023 0.6598 0.42900.995 120.7 30.82 12.86 6.480 3.588 2.091 1.254 0.7654 0.4720 0.29310.9875 103.0 26.62 10.82 5.242 2.762 1.519 0.8548 0.4875 0.2803 0.16200.975 90.12 23.56 9.337 4.355 2.187 1.138 0.6030 0.3230 0.1742 0.09430.95 77.60 20.58 7.899 3.506 1.655 0.8031 0.3954 0.1962 0.0978 0.04890.875 61.29 16.67 6.021 2.428 1.020 0.4363 0.1881 0.0815 0.0354 0.01540.8413 57.03 15.64 5.528 2.155 0.8702 0.3565 0.1470 0.0609 0.0253 0.01050.5 35.09 10.19 2.960 0.8598 0.2497 0.0725 0.0211 0.0061 0.0018 0.00050.1587 21.24 6.515 1.354 0.2548 0.0470 0.0086 0.0016 0.0003 0.0001 0.00000.125 19.66 6.071 1.182 0.2057 0.0350 0.0059 0.0010 0.0002 0.0000 0.00000.05 15.18 4.764 0.7191 0.0938 0.0119 0.0015 0.0002 0.0000 0.0000 00.025 12.81 4.038 0.5020 0.0532 0.0055 0.0006 0.0001 0.0000 0 00.0125 10.98 3.450 0.3518 0.0303 0.0025 0.0002 0.0000 0.0000 0 00.005 9.105 2.814 0.2193 0.0144 0.0009 0.0001 0.0000 0 0 00.0025 7.972 2.412 0.1523 0.0081 0.0004 0.0000 0.0000 0 0 0Females0.9975 46.16 31.20 23.24 18.77 16.29 15.08 14.83 15.44 16.95 19.560.995 40.32 27.45 20.49 16.54 14.31 13.18 12.87 13.24 14.30 16.120.9875 33.14 22.87 17.14 13.83 11.91 10.87 10.48 10.58 11.13 12.100.975 28.06 19.63 14.79 11.92 10.22 9.259 8.804 8.728 8.957 9.4430.95 23.24 16.55 12.55 10.12 8.630 7.733 7.231 7.003 6.973 7.0860.875 17.18 12.64 9.728 7.851 6.625 5.813 5.265 4.886 4.614 4.4110.8413 15.64 11.63 9.003 7.269 6.112 5.323 4.768 4.361 4.048 3.7960.5 8.040 6.543 5.325 4.334 3.527 2.871 2.336 1.901 1.547 1.2590.1587 3.697 3.385 3.000 2.500 1.919 1.393 0.9830 0.6838 0.4718 0.32390.125 3.239 3.027 2.729 2.289 1.736 1.231 0.8466 0.5729 0.3843 0.25630.05 2.005 2.020 1.948 1.686 1.212 0.7861 0.4901 0.2998 0.1815 0.10920.025 1.410 1.501 1.526 1.366 0.9354 0.5658 0.3280 0.1865 0.1048 0.05850.0125 0.9859 1.109 1.192 1.115 0.7207 0.4049 0.2181 0.1151 0.0601 0.03120.005 0.5983 0.7262 0.8444 0.8553 0.5006 0.2530 0.1229 0.0586 0.0277 0.01300.0025 0.3972 0.5123 0.6350 0.6968 0.3686 0.1702 0.0759 0.0333 0.0144 0.0062*Linear-quadratic dose response: ERR1Sv = 

α for chronic exposure; ERR1Sv = 2 × α for acute exposure.
IV. Description of the Approach 55

Table IV.D.8. Computation of statistical uncertainty for ERR1Sv: Thyroid cancer.

Exposure age GM GSD

0 9.463 2.183

5 6.262 1.924

10 4.136 1.976

15 2.732 2.160

20 1.804 2.301

25 1.192 2.367

30 0.788 2.365

35 0.521 2.379

40 0.345 2.732

45 0.228 3.140

50 0.151 3.611
56 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.D.9. Computation of statistical uncertainty for ERR1Sv: Basal cell skin carcinoma and other nonmelanoma skin cancer. Profile Basal cell skin cancer, by age at exposure* Other nonmelanoma quantiles 0–10 20 30

≥ 40 skin cancer

0.9975 149.7 23.79 5.872 2.342 0.82430.995 129.1 21.34 5.360 2.095 0.71560.9875 104.3 18.26 4.687 1.773 0.57150.975 87.30 16.02 4.175 1.531 0.46130.95 71.53 13.84 3.655 1.288 0.34890.875 52.35 11.01 2.938 0.9613 0.19400.8413 47.61 10.27 2.742 0.8744 0.15190.5 25.22 6.441 1.645 0.4200 –0.08070.1587 13.14 3.970 0.8365 0.1495 < 00.125 11.88 3.677 0.7399 0.1235 < 00.05 8.467 2.837 0.4556 0.0579 < 00.025 6.778 2.376 0.3132 0.0323 < 00.0125 5.524 1.998 0.2125 0.0178 < 00.005 4.295 1.576 0.1245 0.0078 < 0

0.0025 3.584 1.301 0.0814 0.0041 < 0*Exponential dependence on exposure age e for 10 < e < 40.
IV. Description of the Approach 57

Table IV.D.10. Computation of statistical uncertainty for ERR1 wlm: Radon-related lung cancer. ERR is modeled to be

linear in wlm0.82 (where wlm is exposure in working-level months) and exponential in age at diagnosis between 45 and

75 years and in time since last exposure between 5 and 25 years.

Age ≤ 45 at diagnosis Age 63 at diagnosis Age ≥ 75 at diagnosis

Profile Time since last exposure Time since last exposure Time since last exposure

quantiles ≤ 5 years 15 years ≥ 25 years ≤ 5 years 15 years ≥ 25 years ≤ 5 years 15 years ≥ 25 years

Smokers0.9975 6.736 2.205 0.7714 0.6299 0.1970 0.0668 0.2205 0.0673 0.02210.995 5.334 1.747 0.6086 0.5214 0.1636 0.0553 0.1788 0.0548 0.01800.9875 3.816 1.250 0.4330 0.3966 0.1251 0.0422 0.1321 0.0408 0.01340.975 2.884 0.9457 0.3256 0.3149 0.0998 0.0336 0.1024 0.0318 0.01050.95 2.111 0.6931 0.2371 0.2432 0.0775 0.0260 0.0769 0.0241 0.00800.875 1.300 0.4271 0.1447 0.1616 0.0520 0.0173 0.0490 0.0156 0.00510.8413 1.122 0.3690 0.1246 0.1428 0.0461 0.0153 0.0427 0.0136 0.00450.5 0.4145 0.1366 0.0450 0.0608 0.0200 0.0066 0.0169 0.0056 0.00180.1587 0.1631 0.0538 0.0172 0.0256 0.0086 0.0028 0.0064 0.0022 0.00070.125 0.1412 0.0466 0.0149 0.0224 0.0075 0.0025 0.0055 0.0019 0.00060.05 0.0880 0.0291 0.0091 0.0143 0.0049 0.0016 0.0034 0.0012 0.00040.025 0.0650 0.0215 0.0067 0.0107 0.0037 0.0012 0.0025 0.0009 0.00030.0125 0.0496 0.0164 0.0051 0.0082 0.0028 0.0009 0.0018 0.0006 0.00020.005 0.0358 0.0119 0.0036 0.0059 0.0021 0.0007 0.0013 0.0005 0.0002

0.0025 0.0286 0.0095 0.0029 0.0047 0.0017 0.0005 0.0011 0.0004 0.0001Continued on page 58
58 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables Table IV.D.10 (continued). Computation of statistical uncertainty for ERR1 wlm: Radon-related lung cancer. ERR is modeled to be linear in wlm0.82 (where wlm is exposure in working-level months) and exponential in age at diagnosis between 45 and 75 years and in time since last exposure between 5 and 25 years. Age 

≤ 45 at diagnosis Age 63 at diagnosis Age 

≥ 75 at diagnosis

Profile Time since last exposure Time since last exposure Time since last exposure

quantiles

≤ 5 years 15 years

≥ 25 years

≤ 5 years 15 years

≥ 25 years

≤ 5 years 15 years

≥ 25 years

Nonsmokers0.9975 25.26 8.268 2.893 2.362 0.7387 0.2506 0.8268 0.2523 0.08300.995 20.00 6.552 2.282 1.955 0.6135 0.2076 0.6704 0.2055 0.06750.9875 14.31 4.688 1.624 1.487 0.4692 0.1581 0.4953 0.1530 0.05030.975 10.81 3.546 1.221 1.181 0.3742 0.1258 0.3838 0.1194 0.03920.95 7.917 2.599 0.8892 0.9118 0.2906 0.0974 0.2883 0.0905 0.02970.875 4.875 1.602 0.5425 0.6061 0.1950 0.0650 0.1837 0.0585 0.01920.8413 4.208 1.384 0.4672 0.5355 0.1728 0.0574 0.1600 0.0512 0.01680.5 1.555 0.5121 0.1687 0.2280 0.0758 0.0247 0.0634 0.0209 0.00690.1587 0.6115 0.2018 0.0647 0.0959 0.0323 0.0105 0.0240 0.0082 0.00270.125 0.5296 0.1748 0.0558 0.0839 0.0283 0.0092 0.0208 0.0071 0.00230.05 0.3298 0.1090 0.0343 0.0535 0.0183 0.0059 0.0127 0.0044 0.00140.025 0.2438 0.0807 0.0251 0.0400 0.0137 0.0044 0.0092 0.0032 0.00110.0125 0.1859 0.0616 0.0190 0.0307 0.0106 0.0034 0.0069 0.0024 0.00080.005 0.1344 0.0446 0.0136 0.0223 0.0078 0.0025 0.0048 0.0017 0.0006

0.0025 0.1073 0.0357 0.0108 0.0178 0.0062 0.0020 0.0038 0.0013 0.0004
IV. Description of the Approach 59

Figure IV.F.1. 

Probability distributions used by different authors to describe subjective uncertainty 

for DDREF. Relative probability (%) 

DDREF

0.2

EPA (1999)

NCRP (1997)

Grogan et al. (2002)

01234567

100

75

50

25

0
60 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Figure IV.F.2.

Subjective discrete probability distributions for DDREF applied to chronic, low-LET exposures in the present

report. Probability

DDREF

0.40

0.35

0.30

0.30

0.01

0.04

0.20

0.10

0.04

0.01

0.30

0.25

0.20

0.15

0.10

0.05

0.00

0.5 0.7 1.0 1.5 2.0 3.0 4.0 5.0

Probability

DDREF

0.40

0.35

0.30

0.23

0.01

0.04

0.35

0.10

0.04

0.25 0.23

0.20

0.15

0.10

0.05

0.00

0.5 0.7 1.0 1.5 2.0 3.0 4.0

DDREF for solid tumors other than breast and thyroid DDREF for breast and thyroid
IV. Description of the Approach 61

Figure IV.F.3.

Variation by dose of DDREFacute, for fixed DDREFchronic and reference dose DL. DL is the

(uncertain) dose above which linearity of dose response is assumed to apply. DDREFacute

Radiation dose

0 0.5DL DL

0

1

2

3

4

5

DDREFchronic = 5

DDREFchronic = 4

DDREFchronic = 3

DDREFchronic = 2

DDREFchronic = 1.5

DDREFchronic = 1
62 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Figure IV.F.4.

Log-uniform uncertainty distribution of reference dose DL. Probability density

Reference dose DL, in Gy

15

0.03

10

5

0

0.05 0.1 0.15 0.2 0.25

20

0
IV. Description of the Approach 63

Figure IV.G.1.

Trapezoidal probability density function f(y) for the uncertain linear mixture coefficient y

between additive (y = 0) and multiplicative (y = 1) models for transfer between populations. Probability distribution function

Linear mixture coefficient (y)

–0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1

0

0.2

0.4

0.6

0.8

1
64 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Figure IV.G.2.

Cumulative distribution functions corresponding to the trapezoidal probability density

distribution of Figure IV.G.1, and to two site-specific variations on that distribution. For most

cancers, the trapezoidal distribution of Figure IV.G.1 is used, whereas for breast and lung cancer

50% probability is placed on additivity (y = 0) and 50% on the trapezoidal distribution, and for

stomach cancer 33% probability is placed on y = 1 and the rest on the trapezoidal model. The

multiplicative model is used for thyroid cancer. Cumulative probability

Linear mixture coefficient (y)

–0.2 0 0.2 0.4 0.6 0.8 1.0 1.2

–0.2

0

0.2

0.4

0.6

0.8

1.0

1.2

Breast and Lung Cancer

Stomach Cancer

All Other Cancers
IV. Description of the Approach 65

Table IV.H.1. Subjective uncertainty in radiation effectiveness factors: Photons and electrons.

Factors to be applied in accordance with text equations (IV.H.1), (IV.H.3), and (IV.H.4).a

Radiation type Exposure Probability distribution of radiation effectiveness factor (REFL) 

Photons Chronic or 

acuteb

E > 250 keV Single-valued at 1.0 (higher-energy photons are assumed 

reference radiation)

E = 30–250 keV Hybrid distribution, assigning 25% probability to value 1.0 and

75% probability to lognormal distribution with 2.5 and 97.5 

percentiles at 1.0 and 5.0, respectively

E < 30 keV Distributed as product of two independent random variables, 

one distributed according to the hybrid distribution 

for E = 30–250 keV and the other distributed as triangular

with minimum at 1.0, mode at 1.3, and maximum at 1.6 

Electrons Chronic or 

acuteb

E > 15 keV Single-valued at 1.0 (assumed to be same as value for reference

higher-energy photons)

E < 15 keVc Lognormal distribution with 2.5 and 97.5 percentiles at 1.2 and

5.0, respectively 

a

The equations are given in Section IV.H of the report. Equation (IV.H.1) applies to solid tumors, equation (IV.H.3) applies to

leukemias under conditions of chronic exposure, and equation (IV.H.4) applies to leukemias under conditions of acute exposure.

b

When equation (IV.H.1) is used, DDREF is always applied under conditions of chronic exposure. At acute doses greater than 0.2

cGy, DDREF is assumed to be 1.0. At acute doses less than 0.2 cGy, a DDREF that can exceed 1.0 is applied. See Appendix D 

for details.

c

Probability distribution is based on data on RBE for low-energy beta particles emitted in decay of tritium (3H); distribution is

applied to other electrons of energy less than 15 keV including average energies of beta particles emitted by radionuclides but

excluding low-energy Auger electrons emitted by radionuclides that are incorporated into DNA.
66 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Table IV.H.2. Subjective uncertainty in radiation effectiveness factors: Alpha particles.

Factors to be applied in accordance with text equations (IV.H.1) and (IV.H.3).a

Cancer type Exposure Probability distribution of radiation effectiveness factor (REFL) 

Leukemiasb Chronicc

All energies of Hybrid distribution, assigning 25% probability to value 1.0;

alpha particles 50% probability to lognormal distribution with 2.5 and 97.5 

percentiles at 1.0 and 15, respectively; and 25% probability to 

lognormal distribution with 2.5 and 97.5 percentiles at 2.0 and 60,

respectively 

Solid tumors Chronicc

All energies of Lognormal distribution with 2.5 and 97.5 percentiles at

alpha particles 3 and 80, respectively

Correction multiplier for inverse dose-rate effectc for all exposures to alpha particles—

Discrete distribution, assigning

70% probability to value 1.0;

20% probability to value 1.5;

7.5% probability to value 2.0; and

2.5% probability to value 3.0 

a

The equations are given in Section IV.H of the report. Equation (IV.H.1) applies to solid tumors, and equation (IV.H.3) applies to

leukemias.

b

Assumed probability distribution applies to leukemias, lymphomas, and lymphocytic cancers.

c

Acute exposures to alpha particles emitted by radionuclides generally should not occur; correction factor to account for inverse

dose-rate effect under conditions of chronic exposure to alpha particles is applied in all cases.
IV. Description of the Approach 67

Table IV.H.3. Subjective uncertainty in radiation effectiveness factors: Neutrons. Factors to be

applied in accordance with text equations (IV.H.2) and (IV.H.3).a

Cancer type Exposure Probability distribution of radiation effectiveness factor

Leukemiab Chronic or 

acutec

Neutron energies

E = 0.1–2 MeVd Lognormal distribution of REFL with 2.5 and 97.5 percentiles at

2.0 and 60, respectively

E = 10–100 keV; Stepwise uniform distribution of REFL with—

E = 2–20 MeV 30% probability assigned to values from 1.0 to 4.0;

50% probability assigned to values from 4.0 to 8.0;

20% probability assigned to values from 8.0 to 40

E < 10 keV; Stepwise uniform distribution of REFL with—

E > 20 MeV 30% probability assigned to values from 1.0 to 2.3;

50% probability assigned to values from 2.3 to 3.5;

20% probability assigned to values from 3.5 to 25 

Continued on page 68
68 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Table IV.H.3 (continued). Subjective uncertainty in radiation effectiveness factors: Neutrons.

Factors to be applied in accordance with text equations (IV.H.2) and (IV.H.3).a

Cancer type Exposure Probability distribution of radiation effectiveness factor

Solid tumors Chronic 

or acutec

Neutron energies

E = 0.1–2 MeVd Lognormal distribution of REFH with 2.5 and 97.5 percentiles at

2.0 and 30, respectively

E = 10–100 keV; Stepwise uniform distribution of REFH with—

E = 2–20 MeV 30% probability assigned to values from 1.0 to 3.0;

50% probability assigned to values from 3.0 to 5.0;

20% probability assigned to values from 5.0 to 20

E < 10 keV; Stepwise uniform distribution of REFH with—

E > 20 MeV 30% probability assigned to values from 1.0 to 1.6;

50% probability assigned to values from 1.6 to 2.4;

20% probability assigned to values from 2.4 to 12 

Correction multiplier for inverse dose-rate effectc for chronic exposures to neutrons—

Discrete distribution, assigning

50% probability to value 1.0;

30% probability to value 1.5;

15% probability to value 2.0; and

5% probability to value 3.0 

a

The equations are given in Section IV.H of the report. Equation (IV.H.2) applies to solid tumors, and equation (IV.H.3) applies to

leukemias.

b

Assumed probability distributions apply to leukemias, lymphomas, and lymphocytic cancers.

c

Under conditions of chronic exposure only, correction factor to account for inverse dose-rate effect is applied.

d

Energy range includes spectrum of fission neutrons.
IV. Description of the Approach 69

Table IV.I.1. Smoking-related adjustment factors for lung cancer ERR1Sv from low-LET

radiation, additive interaction model.

Used in deriving uncertainty

Used in the 1985 report distribution for this report (WS*)

Smoking category (S) Males Females Males Females

Total 1.00 1.00 1.00 1.00

Never smokers 6.81 4.64 4.74 3.90

Former smokers 1.71 1.17 1.19 0.98

Present smokers (all) 0.604 0.411 0.42 0.35

<10 cigarettes/day 1.75 1.19 1.22 1.00

10–20 cigarettes/day 0.71 0.48 0.49 0.41

21–39 cigarettes/day 0.41 0.28 0.28 0.23

40+ cigarettes/day 0.29 0.20 0.20 0.16

Ever smoker (present and 

former smokers) 0.73 0.47 0.51 0.41

*These percentages were obtained by assuming that the distribution by amount smoked among current smokers was the same as

that used in the 1985 report (p. 41).
70 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Table IV.I.2. Distribution of the U.S. population by smoking habit.

Used in the 1985 report Used in this report 

(Status in 1964–65) (Status in 1993)

Smoking category (S) Males Females Males Females

Never smokers 29.8 59.0 42.4 57.8

Former smokers 19.2 7.8 29.9 19.7

Current smokers (all) 51.0 33.2 27.7 22.5

<10 cigarettes/day 13.6 13.5 7.4* 9.2*

10–20 cigarettes/day 24.7 15.0 13.4* 10.2*

21–39 cigarettes/day 11.2 4.4 6.1* 3.0*

40+ cigarettes/day 1.4 0.3 0.8* 0.2*

*These percentages were obtained by assuming that the distribution by amount smoked among current smokers was the same as

that used in the 1985 report (p. 41).
V. Features of the Approach 71

V. Features of the Approach

A. This is an interim update 

As noted in III A and B, in the last 15 years additional epidemiologic data have become

available, and these data have considerable potential for modifying and refining the AS

tables now in use. Also, several efforts have been made to summarize data that were not

available at the time the NIH report was published and to develop risk estimates based on these

data. However, these efforts have not evaluated data from studies published in very recent

years, including particularly the latest updates of the Japanese A-bomb survivor incidence and

mortality data. For example, the most recent BEIR assessment was published in 1990 and the

most recent ICRP assessment was published in 1991. Thus, many of the available new data

have not yet been evaluated by expert committees charged with developing and recommending

risk estimates. In addition, new data, including updated follow-up for cancer incidence in the 

A-bomb survivors, are currently being evaluated at RERF. 

In part because of this situation, the BEIR VII-Phase 1 committee has recommended that a

reassessment of the health effects of exposure to low levels of ionizing radiation be conducted,

and the BEIR VII-Phase 2 has been formed to undertake this task. It is anticipated that the

present report will be revised after the BEIR VII committee recommendations become

available, expected in one or two years. Thus, the AS algorithms described here must be

regarded as an interim update rather than one based on risk models endorsed by an official

national or international committee; therefore, it might differ appreciably from future tables

based on the BEIR VII-Phase 2 report. The current update nevertheless provides AS values

that are based on more up-to-date data and models than previously, and also makes notable

improvements in the treatment of uncertainty. 

B. Similarities to the 1985 report

Because this update must be regarded as interim, the time frame and scope for carrying out data

analyses and model development were limited. For this reason, we did not begin from scratch to

develop new models, but instead used the models used for the 1985 AS tables as a starting

point, amending them as needed to reflect the most important changes in risk coefficients and

risk modeling approaches. Specifically, the following features of the 1985 tables were retained: 

1. Assigned share estimates based primarily on A-bomb survivor data 

The AS values in the 1985 report were based primarily on the A-bomb survivor data, although

in some cases other data were also used. The AS values in the current report are based almost

entirely on A-bomb survivor data and, with the exception of thyroid cancer, did not directly

make use of data from studies of persons exposed for medical reasons, or from studies of workers
and others exposed at low doses and dose rates. Estimates based on data from low dose studies

would be far too imprecise to meet the needs of the AS tables, where estimates for specific

cancers, ages at exposure, and gender are required. However, considerable uncertainty has been

allowed for extrapolation from high doses and dose rates. 

2. Cancer sites evaluated include most of those in the 1985 report 

Our choice of cancer sites includes all but one of those in the previous report. The LSS tumor

registry data include only 15 bone cancer cases, too few for inclusion as a separate site. Bone

cancer associated with injection of 224Ra, which was included in the 1985 report, was not

included in the present report because, although an estimate of radiation-related risk is well

supported by epidemiological data from the Spiess series (Nekolla 2000), compensation claims

associated with injection of 224Ra are highly unlikely to be presented to either the DVA or

DOL. Moreover, the remarkable distribution of radiation-related risk over time following

injection does not appear to be characteristic of exposure to either gamma ray or other isotopes

of radium, and the risk estimates would be difficult to extrapolate to those exposures. Several

new cancer categories have been added. 

3. Treatment of latent period 

The time required for radiation exposure to be reflected in terms of excess cancer risk in an

exposed population is very difficult to estimate. In the present report, excess relative risk, which

itself may depend on attained age and, in the case of leukemia, on time following exposure, is

multiplied by an S-shaped function of time after exposure that increases from 0 immediately

after exposure to 1 after a transition period. The rapidity of the increase depends upon cancer

site, with an early increase becoming appreciable 1 year after exposure and reaching full value

after 5 years for leukemia; a somewhat slower increase for thyroid cancer, beginning after 2

years and ending after 8 years; and, for all other solid tumors, an increase beginning after 4

years and ending after 11 years. This is only slightly different from the approach of the 1985

report.

C. Important changes

1. Estimates were obtained for all cancer sites for which the calculations could be performed, not just 

those established as “radiation-related”

A working assumption was that radiation exposure might be a causal factor for any site or type

of cancer, at some exposure level and under some conditions. This assumption obviates the

question of whether or not a particular kind of cancer could be caused by radiation; rather, the

most pertinent problem is what values of AS are consistent with current scientific information

in a particular instance of cancer following a particular exposure. The Working Group therefore

has provided for the calculation of uncertainty distributions for AS for all cancer types for

which there were relevant data available from the sources on which the present report is based.

72 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
2. Assigned share estimates based on incidence instead of mortality data 

Although the 1985 NIH report used incidence data from site-specific studies of leukemia and

cancers of the thyroid gland, female breast, and salivary gland, it relied mainly on data from the

LSS mortality survey. By contrast, the present report bases its estimates and models on data

from the LSS Tumor Registry and, in the case of thyroid cancer, from a pooled analysis of data

from several studies. The RERF Tumor Registry is now a highly reliable source of cancer

incidence information with good coverage of that part (80%) of the surviving LSS sample

resident in the environs of Hiroshima and Nagasaki (Mabuchi 1994); this coverage goes far

toward matching the main advantage of the LSS death certificate data, viz., completeness of

ascertainment for a general population of both genders and all ages, acutely and simultaneously

exposed to a range of whole-body radiation doses and followed uniformly over time. Follow-up

for the mortality series and for incident diseases covered by the Leukemia Registry began on

October 1, 1950, the entry date for members of the LSS cohort; for the LSS Tumor Registry,

follow-up began on January 1, 1958. The later beginning of the tumor registry is a serious

problem only for cancers of short latency, most of which are covered by the Leukemia Registry

or by site-specific studies that involved special case-ascertainment efforts for the period

1950–1957, and for estimation of excess risk among persons who were over 50 or 60 years of

age when exposed. Comprehensive statistical analyses of site-specific cancer incidence through

1987 were presented for solid cancers and leukemia (Thompson 1994; Preston 1994) and,

especially important for present purposes, the original data sets were made available by RERF

on disk or downloadable from the RERF Web site.

3. Assigned share estimates based on new analyses instead of published risk estimates 

For the 1985 report, assigned shares were estimated from tabulated published estimates,

primarily from the BEIR III report. The availability of grouped numerator and denominator

data from LSS Tumor Registry for 1958–1987, plus similar data from a site-specific incidence

study of skin cancer and a pooled study of thyroid cancer in several irradiated populations,

allowed the present Working Group to model site-specific risks directly. This permitted the

Working Group to determine independently the dependence of dose-specific excess relative

risk on important modifying factors, and to choose models of suitable complexity. 

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

The ERR was modeled directly rather than converted from tabulated estimates of EAR, as was

done in the 1985 report. Note that assigned share (AS) is a simple, monotonic function of the

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

5. More attention to attained age 

For all cancer types except leukemia and bone cancer, the 1985 report models were based on

the assumption that, after a minimal latent period, the excess relative risk per Sv (ERR/Sv)

remained constant over time since exposure and therefore did not depend additionally upon

attained age. New information from analyses of A-bomb survivor information suggests that this

may not be the case generally. Modeling for the present report allows for the possibility that

ERR/Sv may depend upon attained age as well as age at exposure.

V. Features of the Approach 73
6. Different default assumptions for dependence of dose-specific ERR on exposure age and attained age 

In the 1985 report and in the 1990 draft report presented to the NRC review committee, sitespecific estimates of dose-specific ERR were fitted separately by site and were assumed not to

depend upon sex, age at exposure, or attained age unless there was site-specific statistical

evidence to the contrary. The NRC review subcommittee recommended that consideration be

given to conducting joint analyses of several cancer types (see Pierce and Preston 1993), testing

whether various parameters were comparable among cancer types, and then using common

estimates of selected parameters in developing site-specific AS values. This approach has the

potential advantage of greater statistical precision in the estimated AS values, but the

disadvantage of difficult-to-quantify uncertainty about whether the chosen models are

appropriate. Our approach was to estimate parameters for modification of dose-specific ERR by

exposure age and attained age for all solid cancers combined and to use these as default values

for site-specific estimates. Thus, values fitted from site-specific data alone were used only if they

differed significantly from the default values. Type-specific leukemia estimates were based on

type-specific data only, and included nonzero modifying parameters by time, exposure age, or

attained age only if required. 

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

Because estimates obtained directly from epidemiological data on populations exposed only at

low doses are very imprecise, it is necessary to extrapolate from risks that have been estimated

from persons exposed at higher doses (and dose rates) than those of direct interest. The

estimates used in this report are based on Japanese atomic bomb survivor data, and such

estimates tend to be driven by the cancer experience of persons exposed to doses that exceed 

0.5 Gy. This is much larger than doses for which AS values are usually desired, which are

almost always less than 0.1 Gy and often much smaller. 

Although most epidemiological data for solid cancers are compatible with a linear doseresponse function in which risk is proportional to dose, curvilinear forms cannot be excluded.

On the other hand, dose-response analyses of leukemia risk have consistently shown evidence

of upward curvature consistent with a quadratic function of dose having a substantial linear

component (“linear-quadratic” or “L-Q” for short).

a. Method used in the 1985 NIH report. The 1980 BEIR III committee chose as their “preferred”

dose-response model an L-Q model in which risk was proportional to D + D2

/1.16, where D is

organ-specific, low-LET absorbed dose in Gy, and the 1985 NIH tables committee adopted that

form for their report. Thus, with two exceptions (breast and thyroid cancer, for which linearity

was assumed), the estimated excess risk per unit dose was a little more than half as high at 0.1

Gy as at 1 Gy. Another consequence was that the risk per unit dose of the sum of several

exposures, each less than 0.1 Gy and separated in time, or a chronic exposure (treated much

the same as the sum of many very small exposures) was estimated to be about half as high as

that for a single, acute exposure of about 1.2 Gy. 

b. Method used in the present report. The approach used for the present report was to treat

leukemia risk as proportional to D + D2

, since estimates of the D2 coefficient are generally

inexact but in the neighborhood of unity and significantly greater than zero. For all other

cancers, the risk was assumed to be linear (proportional to D) for curve-fitting purposes but

with a dose and dose-rate effectiveness factor (DDREF) applied to reduce estimated risk at low

74 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
doses and dose rates. The DDREF approach was chosen because it is consistent with

recommendations by the International Commission on Radiation Protection (ICRP 1991) and

because instances of a linear dose response have been observed above a certain level in

combination with a DDREF of 2 or more at lower levels in experimental studies of radiation

carcinogenesis using fractionated exposures (Ullrich and Storer 1979).

8. Transfer of estimates between populations 

An important source of uncertainty is the applicability of risk estimates derived from Japanese

A-bomb survivor data to a contemporary U.S. population, especially for cancer types in which

baseline risks for the two countries differ markedly. On the basis of comparisons of leukemia

and breast cancer risk in different populations (BEIR III, Land et al. 1980), transfer between

populations in the 1985 NIH report was based on the assumption that absolute risks were

comparable, and no attempt was made to evaluate the uncertainty resulting from this choice.

For most cancer sites, however, there are few quantitative data other than those available from

the LSS, and it cannot be excluded that other transfer models may be appropriate for different

cancer sites (Land 1990; Land and Sinclair 1991; NCRP 1997; EPA 1999). Moreover, the

choice of transfer model involves considerable uncertainty. In the current report, uncertainty

from this source has been evaluated, and for most cancers has been addressed by treating all

simple linear probability mixtures between additive and multiplicative transfer as equally likely.

Cancers of the female breast, thyroid gland, stomach, lung, and skin were treated somewhat

differently, as discussed in IV.G above.

9. Biological effectiveness of different types of radiation

The 1985 NIH report was focused on low-LET radiation and did not specifically provide

weighting factors for high-LET radiations such as neutrons and alpha particles. The 1985 report

also did not take into account that low-energy photons and electrons may have a greater

biological effectiveness than the high-energy gamma rays to which the atomic bomb survivors

were exposed. In contrast, the present report considers exposures to different radiation types,

including photons, electrons, alpha particles, and neutrons. The biological effectiveness of

different radiations is represented by the radiation effectiveness factor (REF), which generally

depends on the radiation type and its energy. For each radiation type and energy of concern,

the REF is described by a probability distribution that is intended to represent uncertainties in

relevant data obtained from radiobiological studies.

10. Treatment of uncertainty 

The treatment of uncertainty is similar to the 1985 report in that uncertainties from each of

several components or sources are evaluated separately and then combined into an overall

assessment based on the assumption that uncertainties from different sources are independent.

It is also similar in that many sources could not be evaluated using rigorous statistical

procedures, but required subjective judgments by the investigators. However, the treatment of

uncertainties in the updated report differs from the 1985 report in several respects. First,

components of uncertainty that were not evaluated earlier have been added, including,

especially, statistical variability in the risk coefficients and uncertainty resulting from

transferring risk coefficients based on Japanese A-bomb survivors to a contemporary U.S.

population. Second, uncertainty distributions were selected to reflect available data and the

best judgment of the investigators, and were not limited to lognormal distributions as was the

V. Features of the Approach 75
case in 1985. Third, Monte Carlo simulations were used to combine uncertainties, a feature

that made flexible selection of uncertainties possible. Fourth, uncertainty was not treated as an

“add-on,” developed after the central estimates had been determined, but rather was a

fundamental part of the process. That is, emphasis was not on determining single point

estimates but on developing overall uncertainties, calculated by combining the uncertainty

distributions from each of the contributing sources. Given an uncertainty distribution, it is of

course possible to determine medians, means, and various percentiles or probability limits.

Finally, the online computer software (IREP) incorporates “customized” Monte Carlo

simulations to obtain the distribution of a desired AS, taking into account the exposure

scenario, certain characteristics of the individual, and the specific type of cancer. 

The above modifications drew heavily on developments in uncertainty analysis that have

occurred since 1985. The BEIR V report used Monte Carlo simulations to evaluate statistical

uncertainty in lifetime risks, but relied on lognormal propagation of errors for evaluating several

other uncertainty sources. More recently, both NCRP and EPA have used Monte Carlo

simulations, including flexible choice of distributions to describe uncertainties from individual

sources. However, NCRP and EPA were primarily concerned with uncertainties in lifetime risks

for general populations rather than uncertainties in age-specific risks for population subgroups

with certain characteristics. Furthermore, NCRP provided a distribution only for the lifetime

risk of all fatal cancers, although the report contains discussion of specific cancer types. To our

knowledge, the work reported here is the first to evaluate uncertainty distributions for specific

ERR (and therefore AS) values associated with any of a wide range of specific cancer types,

individual characteristics, and exposure scenarios.

76 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
VI. Use of the AS Estimates and Their Uncertainties for Adjudication

This report makes no recommendations regarding how the estimated assigned shares and the

accompanying software IREP should be used to adjudicate claims. However, some possible

applications of the 1985 tables are briefly described below. Further discussion of applications is

provided by NAS/NRC (2000). 

One approach is to use a sliding scale, and British Nuclear Fuels developed such a

compensation scheme based on the 1985 tables (with some modifications) (Thomas et al.

1991; Wakeford 1998). Under this scheme, persons whose estimated AS values are 50% or

higher receive full awards, whereas persons whose estimates are between 20% and 50% receive

graduated partial awards. This approach makes no use of uncertainties, but avoids the

arbitrariness of a full award for a person with a dose that results in a PC of exactly 50% and

nothing for a person with a slightly lower dose that results in a PC of 49%. 

Another approach is an “all or nothing” approach in which a full award is granted if the PC

exceeds some specified value, and no award is granted if the PC is less than the specified value.

When 50% is the chosen cutoff value, this approach can be considered as based on tort law in

which a claim is awarded if it is at least as likely as not that the cancer was caused by radiation. 

CIRRPC (1988) developed a procedure for screening claims of radiation-induced cancer that

made extensive use of uncertainties in the PCs that were provided in the 1985 NIH report.

Under this scheme, a person passes the screening if the upper 99% confidence limit (or some

other chosen level) on the estimated PC exceeds 50%. The CIRRPC report notes that: 

“This procedure is designed to insure that cases which have even a small chance of a

true PC that is 0.5 (50%) or greater (i.e., that meet the “as least as likely as not”

criterion), are developed for assessment of causality, yet will avoid detailed

development of those cases for which there is virtually no chance that the true PC

would be as large as 50%. The screening process is not a decision-making process that

should result in automatic compensation.”

The DVA has subsequently used the screening doses (based on the upper 99% confidence

limit) developed by CIRRPC. In practice, few cases who have passed the screening have failed

to receive rewards. This policy has the advantage that it is highly unlikely to exclude persons

with meritorious claims. However, it is likely to award many persons whose true PCs are very

much less than 50%, a use of funds that some might question. It also has the anomaly that the

more uncertain the PC estimate, the more likely that a claimant will be awarded. For example,

as noted in the NAS review of this report (2000), a claimant with a precisely estimated PC of

44% (CI: 41%–47%) would fail to receive an award, while a claimant with an imprecisely

estimated PC of 9% (CI: 0%–82%) would be awarded.

VI. Use of the AS Estimates and Their Uncertainties for Adjudication 77
Both the sliding scale approach and the “all or nothing” approach as practiced by the DVA

could be varied in many ways. For example, PCs other than 50% could be used as the basis of

awards, and less generous upper probability limits (e.g., 90% instead of 99%) could be used.

Compensation based on the years of life lost from the cancer has also been proposed and has

certain advantages (Robins and Greenland 1991).

A purely numerical consideration is that estimates obtained by Monte Carlo simulation of the

99th percentile of a probability distribution are unstable unless based on a very large sample size.

For example, an estimate based on a simulated sample of size 100 is determined by the two

highest values. With a sample of 1000, the estimate depends upon the highest 11 values, and

for a sample of 10,000 it depends upon the largest 101 values. The estimate based on 100

simulations is obtained very quickly but is highly unstable, whereas that based on 10,000

simulations is reasonably stable but requires a longer time to calculate. 

78 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
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84 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Appendix A: 

Text of Congressional mandate and excerpt from Presidential statement

Public Law 97-414—January 4, 1983

“7(b)(1) Within one year after the date of enactment of this Act, the Secretary of Health and

Human Services shall devise and publish radio-epidemiological tables that estimate the

likelihood that persons who have or have had any of the radiation-related cancers and who

have received specific doses prior to the onset of such disease developed cancer as a result of

these doses. These tables shall show a probability of causation of developing each radiation

related cancer associated with receipt of doses ranging from 1 millirad to 1,000 rads in terms of

sex, age at time of exposure, time from exposure to the onset of the cancer in question, and

such other categories as the Secretary, after consulting with appropriate scientific experts,

determines to be relevant. Each probability of causation shall be calculated and displayed as a

single percentage figure.

“(2) At the time the Secretary of Health and Human Services publishes the tables pursuant to

paragraph (1), such Secretary shall also publish—

“(A) for the tables of each radiation related cancer, an evaluation which will assess the

credibility, validity, and degree of certainty associated with such tables; and

“(B) a compilation of the formulas that yielded the probabilities of causation listed in such

tables. Such formulas shall be published in such a manner and together with information

necessary to determine the probability of causation of any individual who has or has had a

radiation related cancer and has received any given dose.

“(3) The tables specified in paragraph (1) and the formulas specified in paragraph (2) shall be

devised from the best available data that are most applicable to the United States, and shall be

devised in accordance with the best available scientific procedures and expertise. The Secretary

of Health and Human Services shall update these tables and formulas every four years, or

whenever he deems it necessary to insure that they continue to represent the best available

scientific data and expertise.”

Excerpt from President Reagan’s statement on the occasion of his signing the 

Orphan Drug Act 

“. . . there is as yet no consensus among radiation experts in relating human cancers and

exposure to low levels of radiation. Yet, Section 7 mandates that probability of causation tables

be calculated for even very small dose levels. Accordingly, I am directing the Secretary of

Health and Human Services to complete the tables to the extent that may be possible and

scientifically responsible, in light of the analysis also mandated by Section 7, which requires

him to ‘assess the credibility, validity, and degree of uncertainty associated with such tables.’”

Appendix A 85

Appendix B: 

DHHS Charter—Ad Hoc Working Group to Develop

Radioepidemiological Tables 

“Purpose

Section 7(b) of Public Law 97-414 directs the Secretary of Health and Human Services to

devise and publish radioepidemiological tables that estimate the likelihood that persons with

any radiation-related cancer who received specific radiation doses before the onset of the

cancer developed the disease as a result of such exposure. The tables must show the probability

of causation for each cancer associated with receipt of doses ranging from 1 millirad to 1,000

rads in terms of sex, age at time of exposure, time from exposure to disease onset, and such

other categories as the Secretary, after consultation with appropriate scientific experts,

determines to be relevant. In carrying out this mandate, the Secretary deems it necessary to

establish an Ad Hoc Working Group to Develop Radioepidemiological Tables comprised of

scientific experts whose qualifications will insure a thorough, competent and timely completion

of the task.

“Authority 

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

This Ad Hoc Working Group to Develop Radioepidemiological Tables is governed by the

provisions of Public Law 902-463, which sets forth standards for the formation and use of

advisory committees.

“Function 

In addition to developing radioepidemiological tables, the Ad Hoc Working Group shall:

1. Assess the credibility, validity, and degree of certainty associated with such tables; and

2. Compile the formulas that yielded the probabilities of causation listed in such tables. Such

formulas shall be published in such a manner and together with information necessary to

determine the probability of causation of any individual who has or has had a radiationrelated cancer and has received any given dose.

Appendix B 87
The tables specified in paragraph (1) and the formulas specified in paragraph (2) shall be

devised from the best available data that are most applicable to the United States, and shall be

devised in accordance with the best available scientific procedures and expertise. The Secretary

of Health and Human Services shall update these tables and formulas every four years, or

whenever necessary, to insure that they continue to represent the best available scientific data

and expertise.

“Structure 

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

members, including the chairperson. Members and chairperson shall be selected by the

Secretary, or designee, from outstanding authorities in the fields of endocrinology, radiation

biology and pathology, radioepidemiology, biostatistics, and radiobiology. Members shall be

invited to serve for a period of one year. Management and support services shall be provided by

the Office of the Director, National Institutes of Health.

“Meetings

Approximately eight meetings shall be held at the call of the chairperson who shall also

approve the agenda. A government official shall be present at all meetings. Meetings shall be

conducted and records of proceedings kept as required by applicable laws and Department

regulations. Meetings shall be open to the public, except as determined otherwise by the

Secretary; notice of all meetings shall be given to the public.

“Compensation

Members who are not full-time Federal employees shall be paid at the rate of $100 per day, plus

per-diem and travel expenses in accordance with Standard Government Travel Regulations.

“Annual Cost Estimate

Estimated annual cost for operating the Ad Hoc Working Group, including compensation and

travel expenses for members but excluding staff support, is $36,700. Estimated annual man

years of staff support required is one at an estimated annual cost of $49,213.

“Reports 

Section 7(b) of Public Law 97-414 directs that within one year after the date of enactment of

this Act (January 4, 1983), the Secretary of Health and Human Services shall publish the

radioepidemiological tables. The Ad Hoc Working Group will complete its task as outlined in

the Function section of this document and submit these findings to the Director, National

Institutes of Health, by October 15, 1983.

88 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
“Termination Date

Unless renewed by appropriate action prior to its expiration, the Ad Hoc Working Group to

Develop Radioepidemiological Tables will terminate on May 15, 1984.

Approved:

8-4-83 (signed) Margaret M. Heckler”

Date Secretary

Appendix B 89

Appendix C: 

Bias associated with assuming statistical independence between estimates

of dose response and estimates of modifying factors

The magnitude of the bias associated with Approach 2 can be estimated, for sites computed

using Approach 1 (Table IV.D.1), as follows: suppose that the 99% upper statistical uncertainty

limit for AS is 50% if computed using lognormal assumptions for ERR1Sv (i.e., the 99% limit

for ERR is 1) for dose D. The corresponding upper limit for AS based on ERR, also computed

using lognormal assumptions but with the Approach 2 assumption of zero covariance between

log(α) and h(e, a; γ, δ), is likely to be either higher or lower than 50%, thus indicating the

direction and magnitude of bias using the decision rule selected by the DVA, and mandated by

the Energy Employees Occupational Illness Compensation Program Act of 2000. The

percentages of over- or underestimation of AS using Approach 2, for the five Approach 1 sites,

are shown in Appendix Table C.1 (page 92) for exposure ages e = 18, 20, 25, and 30 (or over)

and attained ages a = 25, 30, 35, 40, 45, and 50 (or over), where a ≥ e + 7.

Approaches 1 and 2 always give the same result for e ≥ 30 and a ≥ 50, where ERR is assumed

not to depend upon γ and δ; otherwise, Appendix Table C.1 suggests that Approach 2 usually

overestimates the 99% upper limit for AS when that limit is near 50%, and apparently never

underestimates it for stomach cancer among females. The nontrivial exceptions occur for liver

cancer, female breast cancer, and digestive cancer among males when e ≥ 30; these exceptions

involve underestimation by 0.7% to 1% (i.e., estimating the 99% upper limit for AS to be as

low as 49.5% when it should be 50%) for a around 45, and underestimation by 1.3% to 2%

(estimating the limit to be as low as 49% when it should be 50%) for a around 40. The

correlation between log(α) and δ is –0.8 or lower for the three sites with nontrivial

underestimation of the 99% upper limit for AS when calculated assuming zero covariance

between log(α) and h(e, a; γ, δ), and –.01 or higher for the other two. According to Appendix

Figure C.1 (page 93), only for male colon and male urinary cancer, among sites for which

Approach 2 was used, is the correlation between log(α) and δ lower than –0.4. This suggests

that downward bias of the 99% upper limit for AS by as much as 1% is a potential problem

only for these two cancers, and then only for e ≥ 30 and a around 40.

Appendix C 91
92 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Appendix Table C.1. Approach 1 validation of Approach 2 estimates of the 99% upper

statistical uncertainty limits for AS. Tabulated values are assigned share, in percent, calculated

using Approach 1 for limits that, according to Approach 2, correspond exactly to AS = 50%.

Sex, cancer site

Age at

corr(log α, γ) corr(log α, δ) exposure Age at cancer diagnosis

25 30 35 40 45 ≥ 50

Male, all digestive cancers 18 50.9 51.5 52.2 52.8 53.3 53.5

20 51.0 51.7 52.3 52.7 53.0

.314 –.082 25 50.3 50.8 51.2 51.6

≥ 30 49.3 49.7 50.0

Female, all digestive cancers 18 51.8 52.4 53.0 53.5 53.6 53.3

20 51.9 52.5 53.0 53.2 53.0

.343 –.011 25 51.1 51.5 51.7 51.7

≥ 30 49.9 50.0 50.0

Female, stomach cancer 18 52.4 52.8 53.2 53.3 53.2 52.9

20 52.4 52.7 52.9 52.8 52.5

.279 .031 25 51.5 51.6 51.6 51.4

≥ 30 50.2 50.1 50.0

Both sexes, liver cancer 18 50.2 51.0 51.8 52.5 53.1 53.5

20 50.5 51.2 51.9 52.5 53.0

.307 –.115 25 49.8 50.4 51.0 51.6

≥ 30 49.0 49.5 50.0

Female, breast cancer 18 52.1 53.2 54.6 56.0 56.6 56.5

20 52.4 53.6 54.9 55.8 55.8

.589 –.107 25 51.1 51.9 52.7 53.2

≥ 30 49.2 49.6 50.0
Appendix C 93

Appendix Figure C.1.

Distribution of cancer sites by correlation of the logarithm of the estimated linear dose

coefficient α with estimated attained age modifier δ (ordinate) and with exposure age modifier

γ (abcissa). Large squares represent sites for which Estimation Approach 1 was used (Table

IV.D.1), with ranges of 99% upper limits for assigned share, from Appendix Table C.1,

obtained using Approach 1 when Approach 2 gave exactly 50%. Small squares represent sites

for which Approach 2 was used (Table IV.D.2).

oral (f)

oral (m) female stomach cancer

50.0–53.3

female digestive cancer

49.9–53.6

other solid (m)

other solid (f)

stomach (m)

bladder (f)

bladder (m)

CNS (f)

colon (f) CNS (m)

colon (m)

urinary(f)

urinary(m)

ovary

male digestive cancer

49.3–53.5

female breast cancer

49.2–56.5 liver cancer

49.2–56.5

genital (m)

gallb (f)

esoph (f)

esoph (m)

pancreas (m)

pancr (f)

gallb (m)

rectum oth resp

(f)

(f)

(m) (m)

Correlation of dose effect and attained age modifier

Correlation of dose effect and exposure age modifier

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60

–0.12

–0.10

–0.06

–0.08

–0.02

–0.04

0.02

0.00

0.04

0.06

Appendix D: 

Computational details

Uncertainty due to sampling variation

As described in Section IV, uncertainty due to statistical variation was approximated by fitted

lognormal distributions for five site-sex combinations in Table IV.D.1 and for thyroid cancer.

For other cancers it was calculated by likelihood profile distributions for the dose-response

parameter, either interpolated among different values of exposure age, attained age, and/or time

following exposure, or in combination with fitted lognormal uncertainty distributions for agerelated modifiers of dose response. These uncertainty models were based on analyses of A-bomb

survivor cancer incidence data, and were obtained for the ERR1Sv value associated with each

type of cancer. 

For use in IREP, the likelihood profile distributions were specified in cumulative form by

quantiles (0.25%, 0.50%, 1.25%, 2.50%, 5.00%, 12.50%, 15.85%, 50% [approximated by the

maximum likelihood estimate], 84.15%, 87.50%, 95.00%, 97.50%, 98.75%, 99.50%, and

99.75%). Intermediate values were calculated by cubic spline interpolation (Press et al. 1996).

For all cancer types other than leukemia, 400 interpolated points were used to define the

likelihood functions. For leukemia, the ERR1Sv depends on both age at exposure and time since

exposure (see below). Therefore, only 100 interpolated points were used, in order to reduce the

size of the electronic files.

To obtain the ERR1Sv for any age at exposure, age at diagnosis, and/or any time since exposure,

linear interpolation in the logarithmic scale was performed between the tabulated ERR1Sv

values. The ERR1Sv for leukemia depends on both the age at exposure and time since exposure.

In this case a bilinear two-dimensional interpolation was performed (Press et al. 1996). From

the numerical point of view, the cubic spline interpolation between percentiles was performed

first. Then, the log-linear interpolation between ages at exposure or times since exposure was

performed for each derived percentile of the likelihood function.

Phasing in the latency period

The analyses described in Section IV-C were based on a model in which the risk was assumed

to be very low (or zero) for a specified minimal latency period after exposure. To avoid an

abrupt jump in the ERR, we used a set of scaling factors to estimate the ERR1Sv for the years

between the end of the latency period and the age at which maximum risk occurs. 

For all cancers, a symmetric S-shaped function similar to the one used to describe the DDREF

(see the following section) was used to insure a smooth transition in ERR1Sv. The midpoint of

the S-shaped function (i.e., the time since exposure at which the ERR1Sv is half of the

maximum ERR1Sv) depends upon the type of cancer. For most solid tumors, the midpoint of the

Appendix D 95
S-shaped function is at 7.5 years, where the function value is 0.5, and the minimum and

maximum values of 0 and 1 are almost entirely attained at 4 and 11 years (values 0.01 and 0.99,

respectively). For thyroid cancer, the midpoint is at 5 years and the minimum and full values

essentially attained at 2 and 8 years. For leukemia, the midpoint is at 2.25 years and the

minimum and full values attained at 1 and 5 years. Because we lack precise knowledge about

the onset of different cancers, an additional random linear translation of the S-curve was

introduced by letting the midpoint vary around the nominal value of 7.5, 5, or 2.25 years after

exposure, depending on cancer type. The uncertain midpoint was assumed to be distributed

according to a triangular distribution with minimum 5, mode 7.5, and maximum 10, denoted

Tr(5, 7.5, 10), for solid cancers generally; the corresponding uncertainty distributions were Tr(3,

5, 7) for thyroid cancer and Tr(2, 2.25, 2.5) for leukemia. The main practical effect is to

increase assigned share for cancers diagnosed within a short time following exposure.

The dose and dose-rate effectiveness factor (DDREF)

As discussed in IV.F, for an acute exposure, the value DDREFacute = 1 is used for doses larger

than a randomly generated reference dose DL, above which the dose response is assumed to be

linear. As the dose approaches zero, DDREFacute approaches the values prescribed for chronic

exposure, DDREFchronic. The mathematical formulation for the transition from DDREFacute = 1 at

D = DL to DDREFacute = DDREFchronic at D = 0, as graphed in IV.F.2, is as follows:

The parameters I and S are, respectively, the inflection point (I = 0.5 × DL) and the “shape”

parameter (S = I/ln(500)); the smaller the values for S, the steeper the increase of the logistic

function 1 + exp((Dose – I)/S). 

Note that, as the dose approaches zero, the DDREFacute approaches the prescribed DDREFchronic.

The value of the “shape” parameter was chosen to obtain the least steep increase of the logistic

function that still reproduces the DDREFchronic for a zero dose1

.

1 This relationship ensures that the DDREF for a dose equal to DL is larger than 0.99.

DDREFacute = 

1

1

if Dose ≥ DL

if Dose < DL

1 + e

(1 – ) 1

DDREFchronic [ ] (Dose–I) { { } S

1 –

96 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Appendix E: 

Comparison of results from IREP with results from the 1985 NIH report

and CIRRPC 

As noted in Section VI, the DVA has based its claims procedure on screening doses that were

developed by CIRRPC (1988). These doses were based on the upper 99% credibility limits of

the uncertainty distributions for the estimated PCs. Although the development of the

screening doses was based on the 1985 NIH report, CIRRPC (1988) modified the PCs (to

account for bias) and expanded the uncertainty assessment given in the original NIH report.

As noted in Section VI, persons who pass the DVA screening procedure usually receive an

award even though CIRRPC notes that 

Passing the screening criteria should not be equated with having established causality. 

A claim based on an exposure to radiation that just passes the screening criteria has only a

very remote chance of resulting in a meritorious finding after further development of

causality.

In this appendix, we compare the median ERRs from IREP with the ERRs from the 1985 NIH

report, and also with the ERRs that formed the basis of the CIRRPC recommendations. We

also compare the CIRRPC screening doses with those that would be obtained using the upper

99% credibility limit based on models developed in this report. 

We note that CIRRPC made use of the uncertainty evaluation from the 1985 NIH publication,

but modified it by adding an evaluation of statistical uncertainty, increasing the age at exposure

uncertainty, and adding a positive probability of a linear dose response in the uncertainty

evaluation for the DDREF. We note particularly that the change in the DDREF uncertainty

evaluation shifted the ERR distributions upward by a factor of about 1.5 for cancers other than

breast and thyroid cancer (which were based on linear dose-response models with no

uncertainty assumed for the DDREF). In addition, the 1985 NIH report estimated that ERRs

based on Japanese atomic bomb survivors were too low by a factor of 1.62 because dosimetry

revisions that eventually led to the DS86 dosimetry system had not yet been incorporated. For

this reason, CIRRPC increased those ERRs that were based on atomic bomb survivor data by a

factor of 1.62. 

For the purpose of providing doses for screening claims, CIRRPC made the additional

assumption that the claimant had a baseline risk at the 10th percentile of the distribution of the

baseline risks for the cancer of interest among all counties of the United States, and the further

assumption that the ERR was inversely proportional to the baseline risk. For most cancers,

these two assumptions led to increasing the ERRs (and decreasing the screening doses) by a

factor of 2 or more. For lung cancer, the CIRRPC screening doses for those with unknown

smoking status were based on nonsmokers, whereas screening doses for those who were thought

to be smokers were based on those with unknown smoking status. For leukemia, CIRRPC

screening doses for cases occurring less than 20 years after exposure were based on the

Appendix E 97
assumption that the leukemia occurred at the time yielding the maximum PC or ERR; for cases

occurring 20 or more years after exposure, CIRRPC screening doses were based on the

assumption that leukemia occurred 15 years after exposure.

Appendix Tables E.1, E.2, E.3, and E.4 are addressed at helping readers compare results based

on the model described in this report (and implemented with IREP) with results based on the

earlier NIH report and on CIRRPC recommendations. For each of the cancers evaluated by

CIRRPC, the first three tables show ERRs for a male exposed to a chronic equivalent dose of

.01 Sv at age 20 (Appendix Table E.1, page 100), age 30 (Appendix Table E.2, page 101), or

age 40 (Appendix Table E.3, page 102) and developing cancer at age 50 or older. Additional

scenarios are shown for leukemia. Shown in the tables are the original ERRs from NIH (1985)

(column 2), modification factors used by CIRRPC (column 3), the ERRs after adjustment for

these factors (column 4 in bold), and the medians of the ERR distribution generated by IREP

(column 7 in bold). These three tables also show the deliberately biased CIRRPC ERRs based

on the assumption of a low baseline risk (column 6). 

Several factors contribute to differences in the ERRs from IREP (column 7) and the CIRRPC

ERRs shown in column 4 (bold). The reader should consult Section V.C for a complete

discussion of these differences. Most important, the IREP ERRs were based on cancer incidence

data for the A-bomb survivors for the period 1958–87, whereas most of the NIH (1985) ERRs

were based on mortality data from 1950 through 1974 or 1978. The data used by IREP include

about 8600 cancers, more than twice the number evaluated earlier. For thyroid cancer, the data

used by IREP were also much more extensive than those considered by NIH (1985). 

The ERRs from NIH (1985) were based on age-specific absolute risk estimates, and many of

these may have been statistically quite unstable, especially those for less common cancers. For

most cancers, the effects of age at exposure are much stronger for NIH (1985) than IREP, and

for this reason, results tend to be more comparable for older exposure ages. The NIH (1985)

age at exposure effects were obtained by evaluating ratios of age-specific absolute risk estimates

and age-specific baseline risks with each cancer site treated separately whereas, for most sites,

IREP age at exposure effects were obtained by estimating a single parameter based on all solid

cancers. The longer follow-up period available for developing IREP is particularly important for

evaluating the modifying effects of age at exposure, and is especially important for evaluating

risks for those who were young at the time of exposure. The longer follow-up period is also

important for evaluating the effects of attained age, and another reason for differences in NIH

and IREP ERRs is that the latter allowed for attenuation with attained age. 

Still another reason for differences is that NIH (1985) was based entirely on additive transfer

between populations, whereas IREP uses an uncertain linear mixture of additive and

multiplicative transfer, with the proportion assigned to additivity uniformly weighted over the

interval 0 to 1. This is especially important for cancers of the esophagus, stomach, and liver,

where baseline risks are much higher in Japan than in the U.S. population. NIH (1985) also

used a strictly additive model to account for the interaction of smoking and radiation in

evaluating lung cancer risks, whereas IREP is based on a model that is intermediate between

additive and multiplicative. The IREP approach decreases ERR for smokers but increases ERR

for nonsmokers as compared with the NIH (1985) approach. 

98 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Appendix Table E.4 (page 103) shows the 99% screening doses from CIRRPC Table 3 for

persons exposed at ages 20, 30 and 40. As noted in Section VI, the DVA has used these doses

as a basis for awarding claims. Also shown (in parentheses) are the 99% screening doses that

would have been obtained without the upward adjustment based on the assumption that

claimants had a low baseline risk; these doses may be more appropriate for comparing with

results obtained from IREP. The table also shows the doses that would yield an upper 99%

confidence limit for the PC of 50% based on IREP. Unlike the results in Appendix Tables E.1,

E.2, and E.3, the results in Appendix Table E.4 depend on the uncertainties in the estimated

ERRs as well as the level of the ERR. The uncertainty evaluation used for IREP is considerably

more comprehensive and rigorous than that used by CIRRPC. It should perhaps be noted that,

for chronic exposure, the IREP screening doses are based on a linear model, whereas the

screening doses from CIRRPC are based on a linear-quadratic model; in cases where the

screening doses are large (small ERR), this leads to smaller CIRRPC screening doses than

would have been obtained with a linear model. 

Appendix E 99
100 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Appendix Table E.1. Comparison of CIRRPC and IREP: ERR values for site-specific cancers,

exposure age 20, diagnosis at age 55 unless otherwise indicated. Tabular values are for a male

(female in the case of breast cancer) with exposure at organ-specific equivalent dose of 1 cSv

chronic photon radiation at > 250 keV.

(1) (2) (3) (4) (5) (6) (7)

Type of Cancer ERR851 Dose and FDL × Baseline FDL × IREP 

at 1 cSv, linearity ERR85 Factor3

, FB × ERR 

× 100 factor2

, at 1 cSv, FB ERR85 at at 1cSv4,

FDL × 100 1 cSv, × 100 × 100

Leukemia except CLL 

Peak6 6.13 2.43 14.9 1.2 17.9 16.8

15 years after exposure 2.05 2.43 5.0 1.2 6.0 4.6

30 years after exposure 0.23 2.43 0.56 1.2 0.68 0.67

Acute Myeloid Leuk. 

Peak6 5.96 2.43 14.5 1.2 17.4 5.1

15 years after exposure 1.87 2.43 4.6 1.2 5.5 2.9

30 years after exposure 0.15 2.43 0.35 1.2 0.42 1.2

Chronic Myeloid Leuk.

Peak6 6.35 2.43 15.4 1.2 18.5 26.9

15 years after exposure 2.51 2.43 6.1 1.2 7.3 2.3

30 years after exposure 0.62 2.43 1.5 1.2 1.8 0.06

Esophagus 0.207 2.43 0.50 2.3 1.16 0.34

Stomach 0.569 2.43 1.5 1.9 2.6 0.22

Colon 0.167 2.43 0.41 2.4 0.97 0.47

Liver 2.81 2.43 6.9 2.6 17.9 1.28

Pancreas 0.446 2.43 1.1 1.9 2.1 0.10

Lung (Nonsmoker) 0.831 2.43 2.0 2.2 4.44 0.40

Lung (Smoker) 0.074 2.43 0.18 2.2 0.40 0.09

Urinary 0.124 2.43 0.30 4.1 1.24 0.46 or 

0.355

Female Breast 0.606 1.00 0.61 1.9 1.15 0.38

Thyroid 2.82 1.00 2.8 2.7 6.3 1.2

1

The ERR at 1 cSv as given by NIH (1985).

2

For nonlinear estimates based on the A-bomb survivor data, the factor includes 1.62 to correct for dosimetry-related bias and 1.5 to

correct for a one-third probability of a linear dose-response.

3

To calculate CIRRPC screening doses, ERRs were adjusted upward to consider the possibility that a subject might have an

exceptionally low baseline risk. These factors were obtained as ratio of average U.S. rate divided by the 10th percentile of the

distribution for all U.S. counties. 

4

These are ERRs based on 5000 iterations with IREP. 

5

The first value is that for all urinary cancers; the second is that for bladder cancer.

6

This is the maximum ERR for all time periods after exposure. For the NIH tables, this occurred in the period 3–8 years following

exposure. For IREP, the maximum occurred five years after exposure.
Appendix E 101

Appendix Table E.2. Comparison of CIRRPC and IREP: ERR values for site-specific cancers,

exposure age 30, diagnosis at age 55 unless otherwise indicated. Tabular values are for a male

(female in the case of breast cancer) with exposure at organ-specific equivalent dose of 1 cSv

chronic photon radiation at > 250 keV. 

(1) (2) (3) (4) (5) (6) (7)

Type of Cancer ERR851 Dose and FDL × Baseline FDL × IREP 

at 1 cSv, linearity ERR85 Factor3

, FB × ERR 

× 100 factor2

, at 1 cSv, FB ERR85 at at 1cSv4,

FDL × 100 1 cSv, × 100 × 100

Leukemia except CLL 

Peak6 3.95 2.43 9.6 1.2 11.5 10.4

15 years after exposure 1.73 2.43 4.2 1.2 5.0 3.7

30 years after exposure 0.17 2.43 0.41 1.2 0.50 0.75

Acute Myeloid Leuk. 

Peak6 3.75 2.43 9.0 1.2 10.8 5.1

15 years after exposure 1.63 2.43 3.9 1.2 4.7 2.9

30 years after exposure 0.15 2.43 0.36 1.2 0.44 1.2

Chronic Myeloid Leuk.

Peak6 5.49 2.43 13.3 1.2 16.0 26.9

15 years after exposure 2.15 2.43 5.2 1.2 6.3 2.3

30 years after exposure 0.27 2.43 0.66 1.2 0.79 0.06

Esophagus 0.077 2.43 0.19 2.3 0.43 0.21

Stomach 0.270 2.43 0.66 1.9 1.25 0.13

Colon 0.077 2.43 0.19 2.4 0.45 0.28

Liver 0.843 2.43 2.05 2.6 5.3 0.76

Pancreas 0.176 2.43 0.43 1.9 0.81 0.06

Lung (Nonsmoker) 0.366 2.43 0.89 2.2 2.0 0.24

Lung (Smoker) 0.032 2.43 0.08 2.2 0.17 0.05

Urinary 0.064 2.43 0.16 4.1 0.64 0.27 or

0.205

Female Breast 0.268 1.00 0.27 1.9 0.51 0.26

Thyroid 1.19 1.00 1.19 2.7 3.2 0.53

1

The ERR at 1 cSv as given by NIH (1985).

2

For nonlinear estimates based on the A-bomb survivor data, the factor includes 1.62 to correct for dosimetry-related bias and 1.5 to

correct for a one-third probability of a linear dose-response.

3

To calculate CIRRPC screening doses, ERRs were adjusted upward to consider the possibility that a subject might have an

exceptionally low baseline risk. These factors were obtained as ratio of average U.S. rate divided by the 10th percentile of the

distribution for all U.S. counties. 

4

These are ERRs based on 5000 iterations with IREP. 

5

The first value is that for all urinary cancers; the second is that for bladder cancer.

6

This is the maximum ERR for all time periods after exposure. For the NIH tables, this occurred in the period 3–8 years following

exposure. For IREP, the maximum occurred five years after exposure.
102 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables

Appendix Table E.3. Comparison of CIRRPC and IREP: ERR values for site-specific cancers,

exposure age 40, diagnosis at age 55 unless otherwise indicated. Tabular values are for a male

(female in the case of breast cancer) with exposure at organ-specific equivalent dose of 1 cSv

chronic photon radiation at > 250 keV.

(1) (2) (3) (4) (5) (6) (7)

Type of Cancer ERR851 Dose and FDL × Baseline FDL × IREP 

at 1 cSv, linearity ERR85 Factor3

, FB × ERR 

× 100 factor2

, at 1 cSv, FB ERR85 at at 1cSv4,

FDL × 100 1 cSv, × 100 × 100

Leukemia except CLL 

Peak6 2.04 2.43 4.9 1.2 5.8 6.5

15 years after exposure 1.21 2.43 2.9 1.2 3.5 2.9

30 years after exposure 0.16 2.43 0.39 1.2 0.47 0.85

Acute Myeloid Leuk. 

Peak6 1.63 2.43 4.0 1.2 4.8 5.1

15 years after exposure 1.21 2.43 2.9 1.2 3.5 2.9

30 years after exposure 0.16 2.43 0.39 1.2 0.47 1.2

Chronic Myeloid Leuk.

Peak6 4.93 2.43 12.0 1.2 14.4 26.9

15 years after exposure 1.10 2.43 2.7 1.2 3.2 2.3

30 years after exposure 0.18 2.43 0.44 1.2 0.52 0.06

Esophagus 0.044 2.43 0.11 2.3 0.25 0.21

Stomach 0.150 2.43 0.36 1.9 0.69 0.13

Colon 0.038 2.43 0.09 2.4 0.22 0.28

Liver 0.331 2.43 0.80 2.6 2.1 0.76

Pancreas 0.094 2.43 0.23 1.9 0.43 0.06

Lung (Nonsmoker) 0.221 2.43 0.54 2.2 1.2 0.24

Lung (Smoker) 0.032 2.43 0.08 2.2 0.17 0.05

Urinary 0.040 2.43 0.10 4.1 0.40 0.27 or 

0.205

Female Breast 0.100 1.00 0.10 1.9 0.19 0.26

Thyroid 1.11 1.00 1.11 2.7 3.0 0.23

1

The ERR at 1 cSv as given by NIH (1985).

2

For nonlinear estimates based on the A-bomb survivor data, the factor includes 1.62 to correct for dosimetry-related bias and 1.5 to

correct for a one-third probability of a linear dose-response.

3

To calculate CIRRPC screening doses, ERRs were adjusted upward to consider the possibility that a subject might have an

exceptionally low baseline risk. These factors were obtained as ratio of average U.S. rate divided by the 10th percentile of the

distribution for all U.S. counties. 

4

These are ERRs based on 5000 iterations with IREP. 

5

The first value is that for all urinary cancers; the second is that for bladder cancer.

6

This is the maximum ERR for all time periods after exposure. For the NIH tables, this occurred in the period 3–8 years following

exposure. For IREP, the maximum occurred five years after exposure.
Appendix E 103

Appendix Table E.4. Comparison of 99% screening doses (in cSv) of chronic photon

radiation at > 250 keV according to CIRRPC and IREP, by cancer site and age at exposure,

with diagnosis at age 55 unless otherwise indicated.

Type of Cancer 99% screening doses 99% screening doses 99% screening doses

for exposure at age 20 for exposure at age 30 for exposure at age 40

CIRRPC1 IREP2 CIRRPC1 IREP2 CIRRPC1 IREP2

Leukemia except CLL 

Peak3 1.1 (1.3) 2.2 1.7 (2.0) 4.2 3.3 (4.0) 6.5

15 years after exposure4 3.3 (3.9) 11 3.9 (4.6) 15 5.5 (6.6) 19 

Acute Myeloid Leuk. 

Peak3 1.1 (1.3) 5.8 1.8 (2.2) 5.8 4.1 (4.9) 5.8

15 years after exposure4 3.5 (4.2) 16 4.1 (4.9) 16 5.5 (6.6) 16 

Chronic Myeloid Leuk.

Peak3 0.9 (1.1) 1.2 1.3 (1.6) 1.2 1.4 (1.7) 1.2

15 years after exposure4 2.7 (3.2) 11 3.2 (3.8) 11 5.9 (7.1) 11 

Esophagus 3.9 (8.6) 45 9.9 (21) 80 17 (34) 80 

Stomach 6.9 (12) 34 14 (24) 64 23 (41) 64 

Colon 17 (36) 49 33 (65) 90 58 (108) 90 

Liver 1.0 (2.6) 14 3.3 (8.2) 23 8.2 (20) 23 

Pancreas 5.8 (11) 122 14 (24) 226 24 (41) 226 

Lung (Nonsmoker)5 4.3 (9.1) 62 9.3 (19) 111 15 (30) 111 

Urinary 13 (44) 55 or 23 (71) 99 or 35 (100) 99 or 

626 1116 1116

Female Breast 227 (41) 63 497 (93) 80 1327 (251) 80 

Thyroid 3.47 (9.2) 8.5 7.97 (21) 21 9.57 (26) 34 

1

The main entries are the screening doses (in cSv) as given by CIRRPC, Table 3. The entries in parentheses are the screening doses

that would have been obtained without the assumption that subjects had exceptionally low baseline risks. 

2

These screening doses were based on 5000 iterations with IREP. No uncertainty was included for the dose estimate. 

3

CIRRPC screening doses for leukemia within 20 years of exposure were based on the time since exposure that resulted in the

maximum ERR. For IREP, the maximum occurred 5 years after exposure. 

4

CIRRPC screening doses for leukemia 20 or more years after exposure were based on ERRs 15 years after exposure. 

5

CIRRPC screening doses for lung cancer in persons for whom smoking status was unknown at the time of screening were based on

nonsmokers. CIRRPC screening doses for lung cancer for persons known to be smokers at the time of screening were based on the

assumption that smoking status was unknown, a category that was not available in IREP.

6

The first screening dose is based on all urinary cancers (used in IREP for urinary cancer other than bladder), and the second

screening dose is based on bladder cancer. 

7

The CIRRPC screening doses for female breast and thyroid cancer were incorrectly based on a linear-quadratic dose-response

function. The values above correct this error and are based on a linear dose-response function.

Appendix F: 

Interactive RadioEpidemiological Program (IREP)

The Interactive RadioEpidemiological Program (IREP) is a Web-based application that

estimates the assigned share (AS) for an individual with a diagnosed disease who was exposed

in the past to radiation. Throughout this text and online, the terms probability of causation

and assigned share are used synonymously.

The version of IREP presented here was created by the NCI/CDC working group in accordance

with this report. However, it is anticipated that virtually all compensation claims adjudicated

by the DVA, and by the DOL under the Energy Employees Occupational Illness Compensation

Program Act of 2000, will be decided using a modified version of the program, prepared by

NIOSH to facilitate that agency’s use of the program and to reflect various administrative

decisions made by them, e.g., related to treatment of cancer sites not covered by the present

report. The NIOSH version of IREP, and accompanying documentation, are accessible on the

Internet at http://www.cdc.gov/niosh/ocas/ocasirep.html. The original (NIH/CDC) version 

is maintained at NCI for archival and research purposes and can be accessed at

http://irep.nci.nih.gov.

The initial screen of the IREP user interface is shown in Appendix Figure F.1. IREP has been

designed to accept entry of user data (“inputs”) manually (Section F.1) or through the use of an

electronic input file (Section F.2). To initiate a calculation, click the appropriate button.

Appendix F 105
Appendix Figure F.1. Initial screen of the IREP user interface

106 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
F.1 Entering Inputs Manually

When entering inputs manually into IREP, the user supplies personal information (e.g., birth

year, year of diagnosis, gender) and information about exposure (e.g., exposure year, organ

equivalent dose, radiation type, duration of exposure). The Name and Reference ID # are

included as user options and can be left blank if desired; they do not affect the results. The

main input screen is shown in Appendix Figure F.2.

Appendix Figure F.2. Main IREP input screen

To enter exposure information, enter the number of exposures and click “Enter Doses.” The

screen shown in Appendix Figure F.3 will appear. Exposure may include one or more separate

acute or chronic exposures, each identified by year, and may including several exposures,

separately entered, in the same year.

Appendix F 107
Appendix Figure F.3. Dose input screen

IREP is set up to calculate Assigned Share based on exposure information expressed in terms of

the type of radiation and organ-specific equivalent dose in units of cSv (1 cSv = 0.01 Sv = 1

rem). Radiation protection standards are usually specified in terms of equivalent dose, and this

is the way exposure information is usually recorded by radiation safety officers. If the user is

given values of absorbed dose (expressed in units of Gy, cGy, or rad; 1 rad = 1 cGy) for

particular types and energies of radiation, equivalent dose must be calculated for each dose

value using the ICRP Publication 60 (ICRP 1991) radiation weighting factors wR, given in

Appendix Table F.1, and entered into IREP. For example, 1 cGy of gamma radiation translates

to 1 cSv equivalent dose; 1 cGy of neutron radiation at energies between 100 keV and 2 MeV

translates to 20 cGy of equivalent dose. IREP uses the same weighting factors to calculate

absorbed dose, dividing the entered equivalent dose by the ICRP radiation weighting factor

(Appendix Table F.1) selected according to the radiation type specified by the user. Then, the

risk and the assigned share for the selected cancer type are calculated by using the radiation

effectiveness factors (REF) as described in Section IV.H.

108 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Guidance is provided for the selection of radiation type by clicking the “Help” button just

above the radiation type pull-down menu. The first page of this guidance is included as

Appendix Figure F.4. Follow the instructions on the screen to navigate among various pages of

the guidance.

Help is also provided for entering parameter values for different parametric families of

probability distributions for dose equivalent. Depending on the parametric family (e.g.,

constant, lognormal, triangular) selected, the user is required to enter either 1, 2, or 3

parameters to describe the distribution (Appendix Figure F.4). In cases in which less than 3

parameters are required, any values entered in the unneeded field or fields to the right are

ignored.

Once all exposure information has been entered, click “Submit Dose Data” to return to the

main input screen (shown in Appendix Figure F.2).

Appendix F 109

Appendix Table F.1. Radiation weighting factors recommended in ICRP Publication 60

(ICRP 1991)

Radiation type and energy rangea Radiation weighting factor, wR

Photons, all energies 1

Electrons, all energiesb 1

Neutrons < 10 keV 5

Neutrons 10 keV to 100 keV 10

Neutrons > 100 keV to 2 MeV 20

Neutrons > 2 MeV to 20 MeV 10

Neutrons > 20 MeV 5

Alpha particles, fission products, heavy nuclei 20

a

All values relate to the radiation incident on the body or, for internal sources, emitted from the source.

b

Excluding Auger electrons emitted from nuclei bound to DNA.
Appendix Figure F.4. Help file for the selection of radiation type

After entering or uploading all requested input information, the assigned share is estimated by a

single mouse click on the button labeled “Generate Results” on the main input screen

(Appendix Figure F.2). The entered data will be submitted to a host computer where the

underlying IREP code resides and n number of Monte Carlo iterations (using median Latin

Hypercube sampling) will be performed.

110 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
A printable summary report (Appendix Figure F.5) will be displayed by IREP that includes all

input information required to estimate assigned share.

Appendix Figure F.5. IREP summary report

Appendix F 111
If the cancer type is skin or lung, click on “Enter Data” beside Inputs for Skin and Lung Cancer

Only (on the main input screen, Appendix Figure F.2).

For skin cancer, select ethnic origin from the pull-down menu.

For lung cancer, select the source of exposure (radon, other sources, or radon + other sources)

and smoking history.

For exposures to radon, enter the number of exposures and click “Enter Radon Exposure(s).”

The screen shown in Appendix Figure F.7 will appear.

Appendix Figure F.6. Additional inputs for skin and lung cancers

112 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
Appendix Figure F.7. Radon exposure input screen

Appendix F 113
By default, the simulation sample size (n) in IREP is set to 2,000 iterations and the random

number seed is set to 99. The user can alter the number of Monte Carlo iterations and the

initial random number seed by clicking the “Advanced Features” button located on the main

input screen. The “Advanced Features” screen is shown in Appendix Figure F.8.

Appendix Figure F.8. Advanced features screen

114 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
F.2 Entering Inputs using an Input File

To use the input file option, a preformatted electronic file is required. A standardized electronic

input file can be downloaded from the Internet by selecting the input file option on the initial

screen of the IREP user interface (shown in Appendix Figure F.1). The “Upload Saved File”

screen will appear (Appendix Figure F.9); click “Download Template.”

Appendix Figure F.9. Upload saved file screen

Appendix F 115
Once the standardized input file is downloaded, Microsoft Excel can be used to edit the

personal and exposure information in the file. After saving the modified input file (with any

desired file name), the input file can be uploaded into IREP by clicking the “Browse” button.

Appendix Figure F.10. Choose file dialog box

Appendix Figure F.11. Success!

116 Report of the NCI-CDC Working Group to Revise the 1985 NIH Radioepidemiological Tables
For more information about the IREP computer code and its underlying assumptions and

equations, click “View Model Details” in the bar across the bottom of the main input screen (as

seen in Appendix Figure F.2).

Appendix Figure F.12. View model details screen

Appendix F 117
To obtain additional results, click the “Intermediate Results” button at the bottom of the main

IREP input screen (as shown in Appendix Figure F.2). The intermediate results provided by

IREP (Appendix Figure F.13) include: absorbed dose (cGy), the radiation effectiveness factor

(REF) used in the calculation, the excess relative risk, and a series of importance analyses

results showing the parameters that contribute most to the overall uncertainty in the estimate

of assigned share.

Appendix Figure F.13. Intermediate results and importance analysis

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