ORAU TEAM

Dose Reconstruction

Project for NIOSH

Oak Ridge Associated Universities I Dade Moeller & Associates I MJW Corporation

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Document Title:

Analysis of Coworker Bioassay Data for 

Internal Dose Assignment

Document Number: ORAUT-OTIB-0019

Revision: 01

Effective Date: 10/07/2005

Type of Document: OTIB

Supersedes: Revision 00

Subject Expert: Elizabeth M. Brackett

Document Owner

Approval: Signature on File Approval Date: 09/23/2005

Judson L. Kenoyer, Task 3 Manager

Concurrence: Signature on File Concurrence Date: 09/26/2005

Richard E. Toohey, Project Director

Approval: Signature on File Approval Date: 10/07/2005

James W. Neton, Associate Director for Science

 New Total Rewrite Revision Page Change

FOR DOCUM ENTS MARKED AS A TOTAL REWRITE, REVISION, OR PAGE CHANGE, REPLACE THE PRIOR 

REVISION AND DISCARD / DESTROY ALL COPIES OF THE PRIOR REV ISION.
Document No. ORAUT-OTIB-0019 Revision No. 01 Effective Date: 10/07/2005 Page 2 of 10

PUBLICATION RECORD

EFFECTIVE 

DATE

REVISION

NUMBER DESCRIPTION

12/29/2004 00 New technical information bulletin for the analysis of coworker 

bioassay data for internal dose assignment. First approved issue. 

Initiated by Elizabeth M. Brackett.

10/07/2005 01 Revision to update and expand current practices. Approved issue of 

Revision 01. Training required: As determined by the Task 

Manager. Initiated by Joseph Lochamy.
Document No. ORAUT-OTIB-0019 Revision No. 01 Effective Date: 10/07/2005 Page 3 of 10

TABLE OF CONTENTS

SECTION TITLE

1.0 Purpose.................................................................................................................................

PAGE

5

2.0 Background...........................................................................................................................5

3.0 Responsibilities and Process .................................................................................................6

 3.1 Site Team Leader............................................................................................................6

 3.2 Subject Matter Expert......................................................................................................7

 3.3 Coworker Bioassay Statistics Team Leader....................................................................7

 3.4 Data Statistics Analyst.....................................................................................................7

 3.5 Validator..........................................................................................................................8

 3.6 Modeler............................................................................................................................8

 3.7 Tools Development Group...............................................................................................9

ATTACHMENT A, RESPONSIBILITIES AND PROCESS FOR COWORKER

 BIOASSAY DATA FOR INTERNAL DOSE ASSIGNMENT ..................................10
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ACRONYMS AND ABBREVIATIONS

GM geometric mean

GSD geometric standard deviation

MDA minimum detectable activity or amount

SME subject matter expert

TIB technical information bulletin

U.S.C United States Code
Document No. ORAUT-OTIB-0019 Revision No. 01 Effective Date: 10/07/2005 Page 5 of 10

1.0

Technical information bulletins (TIBs) are general working documents that provide guidance 

concerning the preparation of dose reconstructions at particular sites or categories of sites. They will 

be revised in the event additional relevant information is obtained. TIBs may be used to assist the 

National Institute for Occupational Safety and Health in the completion of individual dose 

reconstructions.

PURPOSE

In this document the word “facility” is used as a general term for an area, building, or group of 

buildings that served a specific purpose at a site. It does not necessarily connote an “atomic weapons 

employer facility” or a “Department of Energy facility” as defined in the Energy Employees 

Occupational Illness Compensation Program Act of 2000 [42 U.S.C. Sections 7384l(5) and (12)].

This document provides technical guidance and assigns responsibilities for analyzing coworker 

internal bioassay data to develop intake values for assigning doses to unmonitored or partially 

monitored workers. Deviation from the guidance may be necessary because each bioassay data set 

has unique characteristics based on facility procedures, monitoring periods and methods, and other 

factors. 

Each analysis of coworker internal dosimetry data, including the results and deviations from the 

process, will be documented in a site-specific TIB or a site profile.

2.0

In general, participation in a bioassay program involves workers who have the largest potential for 

exposure. While there are exceptions to this generality such as accidents involving unmonitored 

workers, it is unlikely that an unmonitored worker would have received a larger dose than the most 

highly exposed monitored worker at a site.

BACKGROUND

The analytical method described in this document assumes that the bioassay results for groups of 

workers have a lognormal distribution. Studies of worker dosimetry results (bioassay results, 

dosimeter results, etc.) tend to support this assumption. Alternate distributions may be used if a 

lognormal fit is not deemed satisfactory.

To calculate internal dose, intake rates must be determined. To determine coworker intake rates from 

bioassay, the 50th-percentile (median) and 84th-percentile bioassay results are calculated for specific 

periods from the available data. The R2 fit parameter is also calculated as an indicator of 

reasonableness of fit for each distribution of bioassay results. Coworker intake rates are determined 

from the resultant two data sets, and the geometric standard deviation (GSD) of the coworker intake 

distribution is calculated by dividing the 84th-percentile intake(s) and/or intake rate(s) by the 

50th-percentile intake rate(s). 

This statistical method eliminates the need to define the minimum detectable activity or amount (MDA) 

for uncensored data sets (that is, data sets that include all values regardless of statistical 

significance). However, where the data sets are censored, there may be insufficient information for 

performing a fit to obtain the 50th- and 84th-percentile values. These censored data often are 

recorded as zeroes, numbers preceded by a less-than symbol (<) or as a code such as “ND.” In such 

cases, a method for substituting a range of values for that censored data may be used, if the reporting 

level or cutoff value is specified or can be determined. This method is only to be used for cases 

where the fitting of the positive data yields unsatisfactory results. If the reporting level cannot be 

determined, the data may need to be used without modification. In some cases, such as when
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monitored individuals typically had a measurable body burden from natural or manmade sources 

(e.g., atmospheric nuclear testing), substituting a range of values below the reporting level could be 

inappropriate. These cases are usually obvious because they often create a sharp bend in the plot 

where the substituted values join the uncensored data. As with the rest of this analytical process, 

professional judgment is important for extracting the best possible information from the data.

The statistical calculations described in this document may be by month, quarter, year, or even 

multiple years depending on the size of the data set and the number of positive values. 

All decisions regarding the statistical analysis are recorded in instructions to the statistics analyst and 

in a site-specific document such as the site profile or a TIB. 

This method eliminates the need to remove what could appear to be unreasonable outliers because 

the data distribution is evaluated rather than each datum. However, outliers may be removed at the 

discretion of the site team leader and the subject matter expert (SME).

3.0

The following sections describe the analysis process and responsibilities for the following functions:

RESPONSIBILITIES AND PROCESS

• Site team leader

• SME

• Coworker statistics team leader

• Data statistics analyst

• Validator

• Modeler

• Tools Development Group

Attachment A depicts these functions and the process in a flow chart. For smaller sites with limited 

data, one individual may serve in many of these roles.

3.1 SITE TEAM LEADER

The team leader’s tasks are:

• Coordinate all aspects of the coworker statistical analysis process for the site

• Provide information to and answer the questions of those involved in the analysis, maintain 

schedules, and compile the statistical analysis information into a TIB

• Review the data to be analyzed and provide information to the statistics analyst. The 

information consists of at least the following items:

o Site name

o Radionuclides of interest

o Database names and locations

o Fields (columns) of interest in each database (e.g., results, dates, and identifiers)

o Years to be included in analyses

o Analytical periods (e.g., quarterly or annually)

o Data units and any factors for normalizing or converting the data to other units

o Censored data (i.e., where a reporting level was used) identified by year

o Criteria for handling censored data
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o Exclusion criteria by year (e.g., inadequate sample volumes)

o Code explanations for fields that have a bearing on the data

o Special exclusions (e.g., entry errors and medical intakes)

o Other information the data analyst could need to do the analyses

When compiling the site TIB, the site team leader documents:

• The information listed above

• Deviations from the process and recommendations in this TIB

• A summary of the results of the statistical analyses

• Unmonitored radionuclides associated with the primary radionuclides and the relative activities 

to include in intake calculations

• Intake periods and intake rates of primary (monitored) radionuclides and associated 

absorption types 

3.2 SUBJECT MATTER EXPERT

The SME’s tasks are:

• Review the data and related technical information to determine their completeness and 

usability, identify problems, and recommend solutions

• In concert with the site team leader, determine which data sets are useful for assigning 

coworker doses and, for sites with several methods of monitoring (e.g., urine and lung 

counting), determine which methods to use to assign best estimates of dose and which data to 

use to verify that the results are reasonable 

• Assist and support the site team leader in compiling the detailed technical information used in 

the statistical analyses and provide a review prior to statistical analysis

• Review and approve the completed statistical analyses and modeled intake results

3.3 COWORKER BIOASSAY STATISTICS TEAM LEADER

The coworker bioassay statistics team leader provides overall statistical analysis coordination, 

technical support, and interface assistance between those involved in the analyses. This person 

works closely with the SME, the site team leader, the data statistics analyst, and the data validator.

3.4 DATA STATISTICS ANALYST

The analyst performs the statistical analyses in accordance with the site team leader’s detailed 

instructions. 

If there are unexpected data anomalies not fully addressed by the instructions, the analyst consults 

the site team leader. The site team leader and the SME may recommend deviations from the data 

analysis instructions. 
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The data statistics analyst performs the following tasks (as the data allow or as makes sense for the 

data set), typically using one or more spreadsheets designed to automate most of the analyses. 

Detailed guidance for performing these calculations are documented in ORAUT-PROC-0095, 

Generating Summary Statistics for Coworker Bioassay Data.

• Sort the data for each identified period from low to high results, rank the data using the 

midpoint of each percentile (e.g., given 10 results, the midpoint of the percentile for the first 

ranked datum is 0.05), and determine the 50th- and 84th-percentile values for the ranked data. 

If the data are censored, rank all the data, but fit only the uncensored data unless directed to 

substitute a linear distribution (or another approved distribution) of values for the censored 

data.

• Log-transform the data, calculate the z-score for each transformed data point, and plot the zscores on the x-axis and the natural logarithms of their respective data on the y-axis.

• Use a line equation to calculate the 50th-percentile value, the GSD, and the 84th-percentile 

value for each period of dosimetry data.

• Calculate the associated R2 fit parameter. A value greater than 0.9 indicates a very good fit; 

however, values as low as 0.7 are acceptable, and even lower values may be acceptable if no 

better equation seems appropriate.

• Build a summary table of the results for site team leader and SME review. The table design 

should enable easy transfer into internal dosimetry modeling programs such as IMBA. The 

columns should include the period of the data, an effective bioassay date (midpoint of the 

analysis period), the 50th-percentile values, and the 84th-percentile values.

• Document any items not covered by the written instructions from the team leader and SME 

(e.g., averaging of results, exclusion of anomalous results). Any such deviation should be 

discussed with the team leader and SME prior to application.

3.5 VALIDATOR

The validator’s tasks are:

• Verify the analyst’s results by performing essentially the same analyses.

• If there are discrepancies between the sets of results, resolve them with the analyst.

• Issue a summary report showing the percent variations between the sets of results. There 

should not be differences if rounding is discounted. Differences of up to 1% are not 

considered significant.

3.6 MODELER

The modeler determines intake rates by performing fits of the two data bioassay data sets (50th- and 

84th-percentile results) associated with each radionuclide. For most data sets, intakes will be 

assumed to be chronic. There could be large, short-term releases that need to be addressed 

individually. The modeler’s tasks are:
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• Use site information (e.g., dates of shutdowns and known operating periods) where possible to 

break chronic intakes into periods. These periods should be adjusted as necessary to obtain a 

reasonable fit, but the assumed intake periods should generally not be very short. 

• Assess intakes for each of the absorption types associated with the site and document the 

intake regimes and rationales for assumptions.

• Provide the site team leader with these data in a form suitable for the site TIB.

3.7 TOOLS DEVELOPMENT GROUP

The tools development group builds software tools for dosimetrists to use to determine organ doses in 

accordance with the site TIB and the site profile.
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Attachment A

Responsibilities and Process for Coworker Bioassay Data for Internal Dose Assignment