The Application of D

Reconstruction Results to 

IREP (NIOSH’s Version 

Interactive Radio-Epidem

Program) in Estimating the 

of Causation of Radiogeni

R.W. Henshaw, L.J. Elliott

National Institute for Occupational Safe

Office of Compensation Analysis an
What is NIOSH-IRE

 Computerized application of the 198

epidemiological tables, as updated b

 Based on NCI methods and risk mod

by NIOSH to fit exposures and risks covered workforce

 Two different versions of IREP - NIO

versions are similar but not identical
What is NIOSH-IREP? (

 Web-based interactive software prog NIOSH version is freely available to p

no password

 Calculates probability that a worker’s 

caused by on-the-job exposure to ion

 Created for NIOSH by SENES Oak Rid

implement “Probability of Causation” 
Probability of Causatio

 Procedures outlined in 42 CFR Part 8

for Determining the Probability of Cau

 Reflects “as likely as not” statutory re

PC must be 

≥ 50% (at upper 99% cr

 Methods designed to err on the side o Incorporation of uncertainty factors PC guidelines/results are not intended 

radiation protection standards
More on PC

 Derived from epidemiological concep

“assigned share”

 sometimes referred to as “attributable r

“attributable fraction”

 Traditionally applied to populations,  Refers to the proportion of disease i

caused by the exposure of interest
The 5 Determinants o

1. Cancer risk models2. Radiation dose3. Dose response factors4. Personal characteristics5. Uncertainty factors Inputs may be entered manually

uploaded via an Excel spreadsheavailable online)
Cancer Risk Models in NIO

 Risk coefficients derived from cancer  Based primarily on the Japanese Life 

(A-Bomb survivors), adjusted for U.S

 Modified by individual risk, based on 

dose and personal attributes unique 
Cancer Risk Models (C

 32 separate cancer risk models in NI Some cancers require running more 

model

 Each model falls into 1 of 4 broad gr ERR/Sv for each group has an uncer

on statistical analysis of epidemiolog
Cancer Groups in NIOSH

 Group 1: includes liver, breast, & oth

 ERR/Sv depends on both age at exposu

diagnosis

 Cancers in this group are of relatively h

 Group 2: lymphoma, bladder, & othe

 ERR/Sv similar to Group 1, but with mo

factored in

 Cancers in this group are of relatively lo
Cancer Groups (Con

 Group 3: lung (except from radon ex

female genitalia (excluding ovary)

 ERR/Sv not dependent on age Uncertainty considered constant at all ag

 Group 4: lung (from radon exposure)

thyroid, leukemia

 Each cancer in this group has a unique r
Dose Inputs (Except R

 Year of exposure Radiation type (and energy range)

 Electrons (<15 keV, >15 keV) Photons (<30 keV, 30-250 keV, >250 k Neutrons (<10 keV, 10-100 keV, 100 ke

MeV, >20 MeV)

 alpha
Dose Inputs - Non-Radon 

 Radiation rate

 acute or chronic

 Exposure distribution and dose (in c

 Can be a point estimate or a probability  Choices are normal, log-normal, triangu

triangular, uniform, log-uniform, consta

 Choice of distribution depends on “best 
Dose Inputs (Radon O

 Radon exposures apply only to lung 

model includes trachea and bronchu

 Risk model based on studies of uranInputs: Year of exposure Exposure distribution and dose

 Dose entered in Working Level Months  Distributions: Same as non-radon expos
Dose Response Fact

 Japanese cohort exposed primarily to 

of gamma radiation at high dose rate

 U.S. workers exposed mainly to low 

dose rates

 Background cancer incidence in U.S. 

than Japan, and varies by cancer site
Dose Response Factors 

Japanese cancer risk “transferred” to U

 Adjustment for varying background canc Use of “dose and dose rate effectivenes

 Use of radiation effectiveness factors 

 Purpose is to model the biological effect

different radiation types in causing canc

 Developed by Kocher, et. al., under con
Personal Characteristics R

for NIOSH-IREP

 Gender Year of birth Year of cancer diagnosis Type of cancer (primary organ site, 

 Determines correct IREP cancer model 

tables in NIOSH-IREP Technical Docum

 Smoking history, if lung cancer Ethnicity, if skin cancer
Uncertainty Factor

 Statistical uncertainties associated w

epidemiological studies

 measurement error, response bias, poss

confounding variables, etc.

 Uncertainty of radiation exposures Uncertainties of dose-response assum Uncertainty in transfer of risk from e

populations to target population
Effect of Uncertainty o

 Uncertainty is built into nearly every 

process of estimating causation

 Uncertainty distributions used in dose r

cancer risk models, etc.

 Distributions “sampled” via Monte Carlo 

 “Credibility limits” are placed around 

estimate; upper 99th percentile deter

 Uncertainty is often the major contri
Credibility Limits in Ac

 Example:

 Male exposed to 3 rem at age 40 (elect Diagnosed with leukemia at age 50

 Best estimate of PC is 27% (before p

credibility limits around the point est

 Apply credibility limits PC at upper 99th percentile credibility 
Examples of PC Results f

Exposure to Photons (E<

IREP Inputs (Applies to next 7 slid Gender = Male (female for breast, ov

genitalia)

 Age at exposure = 20 Age at diagnosis = 35 Smoking status = Never smoked Ethnicity = White, non-Hispanic Simulation sample size = 2,000 Random seed number = 99
Compensable at Dose of 

*Acute exp to photons (E<30 keV) at age 20

at age 35; male; white non-Hisp; never smok

Acute myeloid leukemia; chronic myeloid leuThyroid; Gallbladder Malignant melanoma; Non-melanoma skin-BaLeukemia, excl. CLL Liver 

NIOSH-IREP Cancer Model 
Compensable at Dose of 

Stomach *Acute exp to photons (E<30 keV) at age 

at age 35; male; white non-Hisp; never sm

Acute lymphocytic leukemia 

NIOSH-IREP Cancer Model 
Compensable at Dose of 

Bladder *Acute exp to photons (E<30 keV) at age 

at age 35; male (except Ovary & Breast); 

non-Hisp; never smoked

Other endocrine glands; Breast Urinary organs, excl. bladder Ovary Colon; Esophagus 

NIOSH-IREP Cancer Model 
Compensable at 10 cSv* 

*Acute exp to photons (E<30 keV) at age 

at age 35; male; white non-Hisp; never sm

Lymphoma & multiple myeloma; All digestAll male genitaliaConnective tissue; Other and ill-defined sitEye Bone 

NIOSH-IREP Cancer Model 
Compensable at Dose of 

*Acute exp to photons (E<30 keV) at age 

at age 35; male; white non-Hisp; never sm

Oral cavity and pharynx; Nervous system Pancreas Lung 

NIOSH-IREP Cancer Model 
Compensable at Dose of 

Rectum Other respiratory *Acute exp to photons (E<30 keV) at age 

at age 35; male; white non-Hisp; never sm

NIOSH-IREP Cancer Model 
Not Compensable Even at 

Female genitalia, excl. ovary *Acute exp to photons (E<30 keV) at age 

at age 35; male (except Female genitalia); 

non-Hisp; never smoked

Non-melanoma skin-squamous cell 

NIOSH-IREP Cancer Model 
How to Access NIOSH

 Linked to NIOSH/OCAS Web page Navigate to:

http://www.cdc.gov/niosh/ocas/o

 Click on NIOSH-IREP Links also provided to NIOSH-IREP T

Documentation, NIOSH-IREP User’s 

related material