National Institute for Occupational Safety and Health

Interactive RadioEpidemiologic Program (IREP) Update

Timothy D. Taulbee, PhD, CHP

Daniel Stancescu, PhD

Division of Compensation Analysis and Support (DCAS)

Advisory Board on Radiation and Worker Health (ABRWH) Meeting

Augusta, Georgia| August 16, 2023
Preview of the IREP Update

 Proposing to change Probability of Causation (PC) procedure, 

not the cancer risk models nor any dose reconstructions

 Update will correct a negative bias in IREP that is observed in 

some claims thus generally increasing the Probability of 

Causation

 Update ensures no claims are being incorrectly denied 

compensation when the Probability of Causation is close to 50% 

 Update likely only impacts a few claims (2-4) with a Probability 

of Causation (PC) greater than 49.5%

2
Overview

 Background - Probability of Causation

 Quantile Computation Methods

 Potential Computation Impact on Claims

 IREP Update – New Probability of Causation Procedure 

 Expected Programmatic Impact

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Background – Probability of Causation
Probability of Causation Rule - (42 CFR § 81)

 Guidelines for Determining the Probability of Causation Under 

the Energy Employees Occupational Illness Compensation 

Program Act of 2000; Final Rule

 Rule promulgates EEOICPA’s “at least as likely as not” standard

– Is there at least a 50-50 chance that a worker’s cancer was 

caused by occupational radiation exposure (rather than by 

something else)? 

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Probability of Causation

 Frequently abbreviated as “PC” or “PoC,” refers to the proportion of 

disease in a given population that would not have occurred absent 

the exposure of interest

 RadRisk = the risk of an individual's cancer due only to occupational 

radiation exposure

 BasRisk = the baseline (background) risk of that cancer

RadRisk BasRisk

RadRisk PC

+

=

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NIOSH-IREP propagates the uncertainty using 

Monte Carlo methods to compute the Probability 

of Causation

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Probability of Causation Distribution

 EEOICPA requires the calculation of PC, expressed as a 

percentage (e.g., a PC of 0.5 is expressed as 50%). 

 “At least as likely as not” standard means the claim is 

compensable if PC ≥50% at the upper 99th percent confidence 

interval (credibility limit) of the PC (42CFR§81.2)

 Upper 99th percentile of PC is calculated within the NIOSHIREP software program (42CFR§81.10)

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Example PC Credibility Limits

 Male, age 20y at first exposure, exposed to 1 rem of photons (E>250 keV) each year 

for 30 years. Diagnosed with liver cancer at age 65. (n = 10000 PC simulations)

9
Procedure to Update NIOSH-IREP 42CFR§81.12

 NIOSH may periodically revise NIOSH-IREP to 

– Add, modify, or replace cancer risk models

– Improve modeling uncertainty

– Improve functionality and user interface of NIOSH-IREP

 NIOSH will submit substantive changes of NIOSH-IREP to the 

Advisory Board on Radiation and Worker Health (ABRWH) for 

review and address any recommendations from the Board’s review 

before completing and implementing the change

 NIOSH will also inform the public of proposed changes and address 

relevant public comments through Federal Register Notices 

10
Quantile Computation Methods
Sample Quantile Definitions

 Hyndman and Fan (1996) presented nine sample quantile 

definitions with a goal of standardization

 Currently there is No standard definition of a percentile, 

however there are multiple definitions currently in use

 Probabilistic modeling and risk analysis software packages 

such as Crystal Ball, @Risk, Analytica, and Model Risk (Vose) 

have different methods implemented to compute percentiles

 Statistical Software Packages (SAS and R) have multiple 

methods available with one method being the default. 

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Select Examples of Sample Quantile Definitions

Method Software Description

Type 1 Nearest rank method Inverse of empirical cumulative distribution function

Type 2 SAS (default) Same as Type 1 but with averaging at discontinuities

Type 3 The Observation numbered closest to Np

Type 4 @Risk, Crystal Ball Linear interpolation of the empirical distribution function 

(EDF)

Type 5 Piecewise linear function where the knots are the values 

midway through the steps of the EDF

Type 6 Excel (PERCENTILE.EXC) Linear interpolation of the expectations of the order 

statistics for the uniform distribution [0,1]

Type 7 R (default),

Analytica (IREP)

Linear interpolation of the modes for the order statistics 

for the uniform distribution [0,1]

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Comparison of Different Methods

 Sample from a Simple Lognormal Distribution

– Geometric Mean (GM)= 3

– Geometric Standard Deviation (GSD) = 6

– Theoretical 99% = 193.808

– RLH: Random Latin Hypercube

– MLH: Median Latin Hypercube

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Method Comparison with Increasing Sample Size (1 of 2)

Figure 2: Executive Summary

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Method Comparison with Increasing Sample Size (2 of 2)

Figure 2: Executive Summary

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Convergence as the sample size increases

Figure 3: Executive Summary 17
Summary of Method Evaluation

 At low number of iterations (small sample size), relative bias 

can be 1% to 2% for individual distributions

 Type 2 (SAS) appears to be least impacted by sample size

 Type 4 (@Risk) and Type 7 (Analytica-IREP) appear to have a 

negative bias at small sample sizes

 Type 6 (Excel) and VOSE appear to have a positive bias at 

small sample sizes

 All methods converge to the same value as sample size 

increases

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Potential Computational Impact on Claims
Potential Impact on Claims

 IREP uses the Analytica statistical engine and can result in a 

negative bias at the 99th percentile

 The bias is more pronounced when:

– Large dose uncertainty 

• Dose distribution has a large Geometric Standard Deviation (GSD)

– Large number of IREP input exposures

 These can translate into a Probability of Causation (PC) 

distribution with a longer tail with larger distance between PC 

realizations

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PC Number of Iterations

 PC @ 99th %

– n=2000, PC = 50.41%

– n=10000, PC = 49.66%

– n=20000, PC = 49.81%

– n=30000, PC = 49.99%

 Overall goal is to improve 

the modeling uncertainty at 

the 99th percentile of the PC

Figure 12: Executive Summary 21
Current Methodology – 30 runs at 10,000 iterations

Figure 14: Executive Summary 22
Current Methodology – Confidence Interval

Figure 15: Executive Summary 23
IREP Update – Change to PC Procedure 
IREP Update Changes (version 6.0)

 Current IREP (v5.9)

– Maximum number of iterations is 10,000

 New IREP (v6.0)

– Maximum number of iterations is 20,000

 Current IREP_EE (v5.9)

– Averages 30 runs at 10,000 iterations for final PC

 New IREP_EE (v6.0)

– Capability for either 30 or 300 runs at 20,000+ iterations

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Proposed Probability of Causation (PC) Procedure

PC Value IREP 

Version

Current Procedure

(# of Iterations)

Proposed Procedure 

(# of Iterations)

<45% or > 52% IREP 2,000 20,000

45% to 52% IREP-EE 30 runs @ 10,000 30 runs @ 20,000

49.5% to 50.5% IREP-EE 30 runs @ 10,000 300 runs @ optimal 

# of iterations

(20,000 – 70,000+)

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Improving the Modeling Uncertainty

Figure 15: Executive Summary

Similar to

300 runs @

20000+ 

iterations

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IREP Predictive Tool for Claims 49.5% to 50.5% PC

 New tool that evaluates the width of the confidence interval 

(CI) based on the claim uncertainty distributions

 IREP Predictive Tool will be run by NIOSH/ORAU to determine 

the optimal number of iterations

 The tool rapidly conducts 300 runs using only 1,000 iterations 

and then applies a power function to predict the optimal 

number of iterations in order to achieve a CI of less than 0.1

 Final PC will be the average of 300 runs at the optimal number 

of iterations 

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Expected Programmatic Impact
Expected Programmatic Impacts

 Overall IREP 6.0 should have minimal programmatic impact

 Greater precision in the PC value will be achieved

 Probability of Causation run times will increase as the number 

of iterations increases (computer power changes over time)

 Slightly more complicated evaluation process when the PC 

value is near the 50% (49.5% to 50.5%)

 Additional computational time increase will be minimized 

with the use of the IREP Predictive Tool to optimize number of 

iterations

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Program Evaluation Report (PER) (1 of 2)

 All PC calculations for claims between 45% to <50% will be reevaluated using the new PC procedure

 Minimal impact on claims in this region as we have been using

30 runs at 10,000 iterations for many years (since 2006)

 Relatively few claims with PC’s in the 49.5% to 50.5% range

 PRELIMINARY Evaluation of using 2019 data is that 2-4 claims

may exceed 50% PC

 Considering programmatically over 50,000+ claims evaluated

to date 2-4 claims is approximately 0.008%

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Program Evaluation Report (PER) (2 of 2)

 PER will be initiated once we implement IREP 6.0; however,

this will take some time due to current IT constraints

– (i.e. require contractor to querying claims and current

inability to batch process IREP claims)

 Dose Reconstructions do not have to be redone; this is purely

a PC calculation of already completed Dose Reconstructions

 Subcommittee on Procedure Review (SPR) will likely review

the PER when it is completed

 Target implementation is September 2023

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Summary

 Proposing to change Probability of Causation procedure, not 

the cancer risk models nor any dose reconstructions

 Increasing the number of iterations in IREP will correct a 

negative bias in IREP observed with some claims thus 

generally increasing the Probability of Causation

 Increasing the number of iterations also improves the 

modeling uncertainty by decreasing the width of the 

Confidence Interval (CI), thus ensuring that claims close to 

50% will be properly evaluated 

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References

 Stancescu D., Comparison of Several Percentile Definitions, DCAS, 

October 2022.

 Stancescu D., Effect of Alternative Percentile Definition on PC 

Values, DCAS, July 2023.

 Stancescu D., Increasing the Accuracy of the 99th PC values, DCAS, 

July 2023.

 Stancescu D., Percentile Definitions Comparison, Effect on PC 

values, and Increasing Accuracy of PC Values - Executive Summary, 

July 2023

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Questions?

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