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U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

CENTERS FOR DISEASE CONTROL

NATIONAL INSTITUTE FOR OCCUPATIONAL

SAFETY AND HEALTH 

+ + + + +

ADVISORY BOARD ON RADIATION AND

WORKER HEALTH 

+ + + + +

WORK GROUP ON FERNALD

+ + + + +

THURSDAY

MARCH 7, 2013

+ + + + +

 The Work Group convened via 

teleconference at 9:00 a.m., Bradley P. 

Clawson, Chairman, presiding.

PRESENT:

BRADLEY P. CLAWSON, Chairman

MARK GRIFFON, Member

PAUL L. ZIEMER, Member

 
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ALSO PRESENT:

TED KATZ, Designated Federal Official

ROBERT BARTON, SC&A

ELIZABETH BRACKETT, ORAU Team

HARRY CHMELYNSKI, SC&A

STU HINNEFELD, DCAS

KARIN JESSEN, ORAU Team

TOM LaBONE, ORAU Team

JENNY LIN, HHS

JOYCE LIPSZTEIN, SC&A

MARK ROLFES, DCAS

JOHN STIVER, SC&A

MATT ARNO, ORAU Team
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A-G-E-N-D-A 

Welcome and Roll Call/Introduction......... 4 

Issue 1: Coworker Model for

Uranium Internal Exposures................. 8 

Issue 6: Use of Chest Counts to Reconstruct

Th-232 Exposures 1978-1988................ 99

Issue 6a: Worker Placement Issue for Thorium 

Exposures Based on DCAS Coworker Model

Employing DWE (1953-1967)................ 138

WG Plans................................. 174
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1 P-R-O-C-E-E-D-I-N-G-S 

2 9:00 a.m.

3 MR. KATZ: So it's 9:00 now; it's 

4 time. So let's get started with roll call. 

5 Board Members and then all Agency-related 

6 people please speak to conflict of interest as 

7 well. And let's get started with the Chair.

8 (Roll call.)

9 MR. KATZ: The agenda for this 

10 meeting is posted on the NIOSH website under 

11 the Board section, under meetings for today's 

12 date. And there are no other papers posted 

13 for this meeting. And Brad, it's your 

14 meeting, so carry on. 

15 Let me just remind everyone to 

16 mute your phones except when you're speaking. 

17 If you don't have a mute button press *6 to 

18 mute your phone and *6 again to come off of 

19 mute. Thanks.

20 CHAIRMAN CLAWSON: Okay. I 

21 understood that Mark Rolfes isn't going to be 

22 here so you're filling in for him, Stu? 
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1 MR. HINNEFELD: I am attempting 

2 to, to a certain extent. I think I'll be 

3 relying on the ORAU participants pretty 

4 heavily.

5 CHAIRMAN CLAWSON: Okay. Well I 

6 just wanted to kind of make sure if they had 

7 somebody designated to replace him so that I 

8 pointed my questions towards them.

9 Well, first of all, I think I'm 

10 just going to whip out the agenda here and I'm 

11 going to turn it over to John Stiver. We've 

12 got a few issues laid out. Is somebody trying 

13 to talk in?

14 MEMBER GRIFFON: Brad, this is 

15 Mark Griffon. I just got on.

16 CHAIRMAN CLAWSON: Oh thanks, 

17 Mark. 

18 MEMBER GRIFFON: And I have no 

19 conflicts on Fernald. 

20 CHAIRMAN CLAWSON: Okay, that 

21 sounds good. The agenda has been posted on 

22 the website there, Mark, and we're just 
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1 turning it over to John Stiver and let him 

2 start to speak. So John, do you want to just 

3 take off?

4 MR. STIVER: Okay. This is John 

5 Stiver at SC&A. As all of you realize, it's 

6 been over a year since we had a Work Group 

7 meeting so a lot of these issues have kind of 

8 been languishing on the back-burner. 

9 We did -- back in April, a Class 

10 was added to the SEC which was based on the 

11 inability to perform dose reconstructions for 

12 the in vivo thorium measurements from 1968 to 

13 1978.

14 And there was basically three big 

15 issues that we still needed to look at that 

16 might have SEC implications. The first was 

17 the TIB-78 applicability for bounding 

18 construction trade worker subcontractor 

19 exposures. That was discussed pretty 

20 intensively back in February of 2012.

21 And the next one was kind of a 

22 follow-on on the in vivo thorium during the 
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1 later period. There's actually two periods 

2 that span about 20 years. The first period is 

3 `68 to `77 and that was when the data were 

4 reported in milligrams thorium based on kind 

5 of a rule-of-thumb algorithm. After that from 

6 `78 up through `88, data were reported in 

7 actual activity units of the thorium-232 

8 progeny, gamma-emitting progeny that were used 

9 to estimate thorium-232 lung burdens as being 

10 actinium-228 and lead-212.

11 And finally, we had an issue --

12 this goes way back, I believe, almost 5 years. 

13 And this was the thorium coworker model to be 

14 used from 1953 to 1967 that employed the daily 

15 weighted exposure data that had been collected 

16 by the HASL, Health and Safety Laboratory, 

17 during that period of time. And we had 

18 reached a tentative agreement with NIOSH in 

19 their Revision 3 of their coworker model back 

20 in November of 2010 where they had developed a 

21 one size fits all model based on the most 

22 highly exposed category of workers for each 
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1 building in each year. 

2 And we had a caveat on that that 

3 conceptually we thought that was a 

4 scientifically valid approach given that they 

5 had developed an uncertainty methodology based 

6 on a peer-reviewed paper by Davis and Strom 

7 back in 2008.

8 And so the only thing that was 

9 left to be done there was to look at the 

10 implementation, really to have enough 

11 granularity in the data regarding worker 

12 placement to really be able to put people in 

13 those buildings in those years.

14 So, I guess we can get back to 

15 issue number 1. And this is the suitability 

16 of the TIB-78 model for construction trade 

17 workers. 

18 And as you recall back in February 

19 2011, NIOSH had proposed a method where they 

20 had taken these, what they call type 50 urine 

21 bioassay samples. And it turned out that most 

22 of the subcontractors had these type 50 data. 
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1 And they were kind of termed special sample. 

2 And so the original approach on 

3 this, because NIOSH didn't really know what 

4 proportion of these type 50s really belonged 

5 to subcontractors versus the prime 

6 contractors. What they proposed doing was 

7 just lumping all the data together, those type 

8 50s in with the TIB-78, HIS-20 urine bioassay 

9 data and then seeing what kind of an increase 

10 was there overall. And kind of used one of 

11 these adjustment factors kind of similar to 

12 TIB-52, that TIB-52 approach.

13 And there was a lot of discussion 

14 about this. There was basically -- NIOSH had 

15 indicated there were really three reasons why 

16 they didn't get a comparison separately and in 

17 turn decided to pool the data. One being they 

18 could have done the contaminated samples so 

19 would that really be applicable to use in a 

20 coworker model obviously. The other would be 

21 that there's a small number of samples so 

22 outliers could skew the data, have a lot of 
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1 leverage. A third being that they really 

2 hadn't -- had some data for these coworkers 

3 or, excuse me, construction workers, which 

4 we're just going to -- we're going to call 

5 them subcontractors for lack of a better term 

6 at this point. 

7 The problem being that these type 

8 50 data for the subcontractors have just 

9 bioassay date. They didn't have employment 

10 date. And of course the only way you can get 

11 the employment date in the file -- just how 

12 this data is provided and the employment 

13 history and so forth. And so you have then a 

14 way to really get a handle on what the 

15 exposure period might have been.

16 But if you're trying to look a 

17 priori at the unmonitored workers or the 

18 workers that did submit bioassays that did not 

19 submit claims, you're kind of stuck in the 

20 position where you can't really define the 

21 upper limit of what this exposure period could 

22 be.
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1 And so I would direct everybody 

2 now to a Word document that was sent around by 

3 Ted. Last Friday we had a teleconference 

4 call. It was kind of a technical call to 

5 clarify some of the issues on this particular 

6 set of documents that were provided by NIOSH. 

7 And NIOSH had provided an update to TIB-78. 

8 This is reviewed in TIB-78, and also a 

9 comparison study of the subcontractors to the 

10 prime contractors. 

11 And so we had some questions on 

12 that. And went ahead and sent a set of 

13 clarifying questions, sent off to NIOSH 

14 towards the end of February. They came back

15 with their responses February 28.

16 We had this teleconference call on 

17 March 1. And I went ahead and annotated that 

18 and sent it around. I believe Steve sent back 

19 a comment, a clarifying comment. But the name 

20 of this file is notes from Technical Call 13-

21 03-01 SC&A 13-03-04.doc. If you could all 

22 pull that up and kind of follow along on this 
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1 because a lot of this is sort of laid out. 

2 And if everybody has that open, on 

3 the first page really it just lays out the 

4 background. On January 24, Mark Rolfes from 

5 DCAS submitted these two files. TIB-78 

6 Revision 2. And this was updated to include 

7 these previously excluded type 50 analyses 

8 results. 

9 And they also incorporated the new 

10 TIB-52 one person-one sample averages, a 

11 statistical model for stratified coworker data 

12 sets. So there were two big changes there.

13 The second was this Fernald strata 

14 evaluation discussion Rev 1. And what they 

15 did here was they attempted to do an OPOS 

16 comparison to subcontractors to the prime 

17 contractors to determine is there really --

18 based on hypothesis testing protocol in TIB19 53, was there really a discernible, a 

20 significant difference between these two 

21 groups. They also submitted some Excel files 

22 that were sort of the basis for the OPOS 
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1 comparisons. 

2 And let me get down to the 

3 clarifying questions. It was really, you get 

4 down to page 3 and question 2 is really where 

5 you get to the substance here. 

6 And it turned out that really 

7 there just wasn't enough data to do an OPOS 

8 comparison. If you take a look at the strata 

9 Evaluation Report in Table 1, they have data 

10 for 9 years, or essentially -- yes, 9 years, 

11 1950, 1969, `71, `72, `73, `81, and then `83, 

12 `84, `85. And there's -- until you get up 

13 until 1983, you don't have enough data in 

14 these subcontractor, enough OPOS data. They 

15 look for about a minimum of about 30 or so for 

16 statistical analysis. 

17 And so at that point NIOSH and 

18 ORAU decided we really can't do an OPOS 

19 comparison. And so what they then decided to 

20 do was take a look at the conclusion of the 

21 document. Basically they say, well, we can't 

22 really do a comparison so it's kind of 
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1 inconclusive. So what we recommend doing is 

2 taking a high percentile of the TIB-78 data 

3 which now includes these type 50 data. And we 

4 believe that that would be sufficiently 

5 bounding to cover all the subcontractors. 

6 Well, first of all, we tried to 

7 look back at the subcontractor comparison and 

8 there were about 939, 940 give or take records 

9 that were found for these subcontractors in 

10 the pre-1986 environment. And that's really 

11 what we're concerned with because after 1986 -

12 - remember this is the time period where 

13 Westinghouse management came in, took over the 

14 M&O contract and they instituted a fairly 

15 robust health and safety program, really 

16 beefed up the radiation safety program. And 

17 from that point on they have the urine 

18 bioassay for the subcontractors and for the 

19 primes is pretty much in lockstep.

20 But before that we didn't have any 

21 bioassay data that was put into HIS-20 for 

22 these subcontractors. And so it kind of is a 
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1 quandary. What do you do about this? We 

2 don't have any records for these guys. 

3 And so NIOSH went out to DOE 

4 Legacy Management, and actually found some 

5 hard copy records for about 140 of them for a 

6 group of subcontractors at these different 9-

7 year periods. 

8 And so we had to go and question 

9 well, is this really all there is and were 

10 there any data that could have been -- is this 

11 a full set or is there potentially untapped 

12 data that are out there. And during the call 

13 Stu and Mark kind of clarified that, that 

14 really this was all they were able to locate. 

15 They had -- and Stu kind of elaborated on 

16 this. I don't really need to go into it but 

17 the net result is this is what we've got to 

18 work with.

19 And so this kind of leads us into 

20 the next question. This is really the gist of 

21 the -- really the heart of the matter is that, 

22 okay, you have this coworker data in TIB-78 
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1 and there's like 185,000 individual records 

2 here. And there are also I believe, I think 

3 there were like 10,400 give or take of these 

4 type 50 data. And so these were all combined.

5 And so then we're feeling 

6 concerned. How are we going to really 

7 determine whether this is actually bounding 

8 for the subcontractors? And it's going to 

9 become a weight of evidence argument. And we 

10 kind of distilled this down to three elements 

11 in this weight of evidence. 

12 The first one was, okay, to even 

13 use these type 50 records we really need to 

14 get an idea of what the exposure period is. 

15 Now, there's kind of an assumption that these 

16 are short-term special samples, probably 

17 incident-driven and may be related to short18 term exposures but there's really no way to 

19 tell that. Because we know a lot of these 

20 subcontractors were onsite for years and some 

21 of them moved back and forth between the prime 

22 and the sub. So it's not quite as clear-cut 
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1 as that.

2 And so what we had decided at the 

3 last meeting, a year ago, was that Steve would 

4 go out and basically do a claimant file 

5 sampling and take a look at, okay, we know 

6 these people are subcontractors. We're going 

7 to look at these claimant files that have 

8 these type 50 data and determine, okay, what 

9 is really the exposure period we're looking 

10 at.

11 And Mark indicated if you come 

12 down here on page 4 of the minutes, this 

13 highlighted section. They were to go out and 

14 do a claimant file sampling and really try to 

15 get a handle on what the limit might be on 

16 this. And Mark indicated that approximately 

17 half of these were -- exposure periods were a 

18 month or less and others on the upper bound of 

19 the 95th percentile was about 9 months. 

20 And so that was one of the things 

21 we were really concerned with getting as part 

22 of our review. If you could provide that 
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1 report or the analysis that was done there. 

2 And Mark indicated that yes, they would do 

3 that.

4 Another aspect I kind of thought 

5 of as I was putting together responses right 

6 before the meeting last week was that well, 

7 you know, you're adding this type 50 data in 

8 to make this model presumably bounding for 

9 subcontractors. There's sort of an implicit 

10 acceptance, an implicit argument that the type 

11 50 data for the primes is indeed 

12 representative of the type 50 data for the 

13 subcontractors. So really are we comparing 

14 apples and apples here, or is there some 

15 difference that might result in higher 

16 exposures for the subcontractors by virtue of 

17 the dirty jobs they were doing?

18 And during the discussions I 

19 believe Liz Brackett indicated that sometime 

20 in the past few years ago she had done kind of 

21 an empirical comparison of the subcontractor 

22 to the prime contractor bioassay data. And 
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1 what had there -- at least the excretion rates 

2 were about -- they were comparable with each 

3 other. And so we requested that that be 

4 provided as well. And I guess Liz was going 

5 to go look into that and see if she could 

6 possibly provide it.

7 Then a third thing we thought of, 

8 well, you know, when all is said and done what 

9 we really ought to do, let's take some sample 

10 subcontractors and let's go out and have data. 

11 Because we know now we have 940 samples from 

12 a group of individuals. Let's look at several 

13 of those cases and get a statistically valid 

14 sample of these things. And let's do a dose 

15 reconstruction based on their data. And then 

16 let's take this coworker model, the 95th 

17 percentile, and run it through that way and 

18 we'll see, hey, how is this model really 

19 bounding. 

20 And so it was determined we at 

21 SC&A, we would come up with some criteria on 

22 that which we did. And so I guess we could 
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1 kind of talk about that for a minute.

2 We figured that we wanted to get 

3 about 20 to 30, and ideally you'd want at 

4 least 30 of the subcontractors from the pre5 1986 period. We had data. We wanted to 

6 definitely have data. We were kind of 

7 presuming that an annual exposure is sort of 

8 the limiting exposure duration for chronic 1-

9 year exposure. 

10 And we tried to select the 

11 employees who were active during the 

12 construction trade work. Stu had mentioned 

13 that there was a period in the 1970s when, 

14 because there were very little capital funds 

15 available there just wasn't any construction 

16 going on. There wasn't any expansion. So we 

17 want to look at the -- not, obviously not the 

18 very initial construction when there was no 

19 exposure potential but periods where there 

20 were, for various reasons there might have 

21 been an expansion in production. You would 

22 have these people being out there working in 
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1 areas that were contaminated. So we'd want to 

2 if possible look at those years.

3 And then again we did assess 

4 intakes based on the conventional dose 

5 reconstruction methods and then based on the 

6 95th percentile, the coworker model compare of 

7 course for all three solubility types. 

8 And so that's really what we had 

9 in mind. And I'd just ask Stu if you guys had 

10 thought of -- or the ORAU team if you think 

11 those are reasonable criteria for a DR 

12 comparison.

13 MR. HINNEFELD: Which is the 

14 criteria you're describing exactly, John?

15 MR. STIVER: It would be, you 

16 know, we were talking about doing some sample 

17 dose reconstructions using this methodology. 

18 And we thought that about -- you'd want to get 

19 about 20 to 30 of these pre-1986 

20 subcontractors who had data who were employed 

21 during the periods of expansion and activity 

22 when there was actually more potential for 
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1 them to be dosed.

2 And then assess the intakes based 

3 on both conventional dose reconstruction 

4 methods using their data and then using the 

5 coworker model and for all three solubility 

6 types and just compare the results. 

7 MR. HINNEFELD: Okay. So really 

8 we're just going to be comparing excretion 

9 data. 

10 MR. STIVER: Well, we'd actually 

11 want -- not just the excretion data. You'd 

12 want to calculate the intakes.

13 MR. HINNEFELD: Okay.

14 MR. STIVER: No, no, it would 

15 basically be proportional if we're assuming 

16 annual exposure. 

17 MR. HINNEFELD: Okay. I don't see 

18 a particular issue with that. It seems like 

19 that's a comparison that should work.

20 MR. STIVER: Yes, I think it's 

21 pretty straightforward.

22 MR. HINNEFELD: If ORAU team wants 
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1 to speak up, they can. If someone's speaking, 

2 they're on mute.

3 MS. JESSEN: Matt Arno, did you 

4 want to say anything on this? Matt, are you 

5 on mute?

6 MR. ARNO: Yes, I'm sorry. We 

7 haven't done a comparison like this for any of 

8 the other coworker studies and I don't 

9 actually know what sort of result we would get 

10 if we did it even for another side where we 

11 have all workers monitored and we picked a 

12 random sample of 30 people. There's a lot of 

13 variation and you're going to get a different 

14 answer if you do a claimant-specific dose 

15 reconstruction versus the generic techniques 

16 and assumptions that we make in a coworker 

17 study. Even if we do it I'm not sure how we 

18 would evaluate what the results mean.

19 MR. STIVER: I think what we're 

20 really trying to get at is sort of an 

21 empirical weight of evidence comparison to 

22 say, okay, here's the situation. We really 
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1 have some of these people. They have data. 

2 And let's take a look at how the coworker 

3 model assesses their exposure compared to what 

4 we really know. You know, given the 

5 assumptions, obviously, that we're going to 

6 make, and see if that comes out with a higher 

7 value. Basically does it bound their intakes 

8 that would be calculated if they did have 

9 data. 

10 And then you have a better idea, 

11 just a better sense that you're going into 

12 this for the unmonitored workers with what is 

13 going to be a bounding exposure. 

14 I guess this kind of gets back to 

15 the idea that, is the TIB-78 -- first of all, 

16 is it representative? We kind of laid out 

17 three aspects of that. And if it is then the 

18 upper end of that distribution should cover 

19 these personnel. Once you've established 

20 that, I would think that you'd be on pretty 

21 solid ground.

22 MR. BARTON: This is Bob Barton 
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1 with SC&A. Just to kind of clarify what we're 

2 talking about, we spent probably the majority 

3 of the time at the last meeting on this issue 

4 talking about how maybe it's inappropriate to 

5 simply compare excretion rates because maybe a 

6 lot of these subcontractors were only onsite 

7 for a short period of time and if they had a 

8 sample right after their work was done, it 

9 might have a higher result but that might not 

10 necessarily indicate a higher intake.

11 So you know, there was a lot of 

12 discussion on that. And we kind of came out 

13 that the best way to try to get a handle on 

14 the exposure potential of subs versus the 

15 prime contractors was to do some sort of 

16 claimant sampling and compare the intake 

17 rates.

18 And just real quick, a couple of 

19 quotes from that last meeting. I'm just 

20 reading right from the transcript. On page, 

21 the bottom of page 36, Dr. Glover: I think 

22 we'd be willing to do it, talking about these 
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1 sample DRs and claimant study. I think we 

2 want to do it and I was going to offer would 

3 it help to take a few example DRs. Mr. 

4 Rolfes: I mean that is ultimately what we're 

5 getting down to. We could just compare intake 

6 to intake. Dr. Glover: Take some of those 

7 guys who are -- we can't do it for everybody 

8 but maybe we could say that this is some 

9 examples of how it would be applied for a guy 

10 who had data, and compare how those intakes 

11 would have been used if he didn't. And here's 

12 what the real intake would have been.

13 And you know, it goes on and on. 

14 And at the very end, I mean that was sort of 

15 the path forward. On page 142, Mr. Rolfes: We 

16 can compare statistically the distribution 

17 differences or the total intake differences 

18 between the two populations. And then 

19 CHAIRMAN CLAWSON: Okay, then it's looking like 

20 we've got a path forward for issue number 1 

21 here. And one more time, Mr. Rolfes, what we 

22 just proposed is to compare the total intake 
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1 experienced by the subcontractor to the total 

2 intake experienced by our coworker intake 

3 model.

4 So I mean that's where we were the 

5 last time out. So I guess that's where we're 

6 coming from here. We haven't really seen any 

7 comparison of the intake potential between 

8 these two groups. So it's kind of difficult 

9 for us to evaluate how bounding the proposed 

10 approach is when we don't even really have a 

11 handle on the relative exposure potential 

12 between the two.

13 MR. ARNO: Given the amount of 

14 data we have I think we may be in a position 

15 where we never will be able to make that 

16 comparison for most years, especially 

17 essentially all years prior to the nineteen 

18 eighties. 

19 I mean one thing I would like to 

20 clarify is that we did not add the code 50 

21 data in to support use of the coworker study 

22 for subcontractors. We added the code 50 data 
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1 in because, during the course of our 

2 investigations, we determined that that was 

3 the right thing to do.

4 Code 50 can more or less be 

5 interpreted as samples taken for some reason 

6 other than your routine periodic samples which 

7 could be, you know, pre-job, post-job, you 

8 know, suspected incident whether it's for a 

9 contractor or a subcontractor. You always 

10 include that data for all the coworker studies 

11 and you always have the distance of the fact 

12 that yes, the sample taken immediately after 

13 acute intake or immediately after the end of 

14 the chronic will have a higher result than 

15 some periodic sample that may be taken at some 

16 length of time after the intake period 

17 actually ended. That's a known conservatism 

18 for all the coworker studies.

19 COURT REPORTER: Excuse me, is 

20 that Matt Arno who is speaking?

21 MR. ARNO: We need to do dose 

22 reconstructions we can, but one of the things 
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1 we should do is we should do some similar dose 

2 reconstructions or pull them up anyway out of 

3 the ones we've already completed for the 

4 actual contractor employees so that we can see 

5 how well the coworker model fits people whose 

6 data is included in the coworker model 

7 relative to people whose data is not included 

8 in the coworker model. 

9 MR. STIVER: So this is John 

10 Stiver. I see what you're getting at, Matt. 

11 The TIB-78 is not -- certainly didn't do this 

12 just to address the coworker issue, but the 

13 coworker issue depends on that data. So it's 

14 kind of like a sub-element of the 

15 applicability of TIB-78. 

16 I never meant to imply that the 

17 coworker side was driving all the changes that 

18 went into TIB-78. But because we have the 

19 situation where we've got this group of people 

20 and we think they have higher exposure 

21 potential. But we really can't tell. 

22 I mean we've got this small sample 
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1 of guys now, or of samples who are 

2 representative of a smaller number of 

3 individuals, about 940 of them, and this is in 

4 the pre-1986 period over several years. So 

5 we're not going to ever come back with a 

6 definitive result that we can prove at the 

7 95th percentile.

8 But you know what we can do? We 

9 can at least give ourselves some assurance in 

10 an empirical way that, given a sub-sampling of 

11 the people we do have, we're pretty confident 

12 that this model as proposed will bound their 

13 intakes. That's really all we're proposing 

14 here, just some sort of proof of concept, I 

15 guess, you know. A weight of evidence 

16 argument that you can use to justify this 

17 assertion that really isn't that 

18 substantiated, it's more of an assumption that 

19 this data set is going to be sufficiently 

20 bounding for this subpopulation that we feel 

21 is probably in the upper tail of the 

22 distribution.
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1 MR. HINNEFELD: This is Stu. If I 

2 can kind of help frame this from my 

3 understanding. I think someone was asking a 

4 while ago if that was Matt Arno speaking and 

5 it was Matt Arno speaking.

6 But to re-frame the question. The 

7 question that you're asking here is, look. 

8 We, NIOSH, are proposing that this coworker 

9 study with this data set that we have, this 

10 large data set is sufficient to do a bounding 

11 dose reconstruction for construction workers 

12 who are not monitored, because you only need 

13 it for people who are not monitored.

14 So let's find a population of 

15 construction workers who were monitored and, 

16 had they not been monitored, would this 

17 coworker bound their exposure? Isn't that 

18 kind of what you're -- isn't that where we're 

19 going here?

20 MR. STIVER: Yes, Stu, that's 

21 exactly where we're going with it.

22 MR. HINNEFELD: Okay. So then 
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1 that's the comparison you're looking for. And 

2 you guys in your things you delivered this 

3 week, kind of conveniently identified a 

4 population of it looks like about 12 or 13 

5 people, I think maybe 12 with multiple samples 

6 for a short period of time in `69 that may be 

7 something could be done on that. 

8 I don't know what other people's 

9 opinions are on this. And in fact I know 

10 you've done some work on it in terms of the 

11 distributions of the excretion rates. 

12 Just speaking out loud here 

13 though, I wonder if the sampling dates that we 

14 have encompass all or a significant fraction 

15 of their employment period. And I don't know 

16 of any other way that we would be able to 

17 identify their employment period. You 

18 understand what I'm saying?

19 MR. STIVER: Right.

20 MR. HINNEFELD: That would be --

21 if you were doing an annual intake for these 

22 people, you could make some assumptions that 
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1 they worked all year and they were sampled 

2 only on these dates, or I guess you could do 

3 that. I don't know how --

4 MR. STIVER: I think, Stu, we 

5 might have to do that because it's one of the 

6 assumptions that's built into the model, 

7 chronic annual exposure. 

8 MR. HINNEFELD: Right.

9 MR. STIVER: You know, that was 

10 one of the reasons. The first aspect was to 

11 look at the sampling of the NOCTS to identify 

12 what are the distribution of the exposure 

13 periods for these type 50 data. And which you 

14 had to have at least a feel for what that 

15 might be. It certainly appears to be less 

16 than a year in almost all cases. But I think 

17 we were more comfortable using that assumption 

18 of the one-year chronic annual intake.

19 MR. BARTON: If I could ask a 

20 question here. This is Bob Barton. Does 

21 anyone on the NIOSH side or ORAU side know how 

22 many subcontractor claimants are available in 
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1 NOCTS who would have at least some bioassay 

2 data that could be used to reconstruct their 

3 intake? I mean is there only a handful? Is 

4 there 10, 20? I mean because that would be 

5 one way to go is you pull out those claimants 

6 and you can know their employment period, and 

7 if they have bioassay data you can do a best 

8 estimate intake based on that bioassay data. 

9 Then you have a chronic intake rate per day. 

10 Then you go and you compare that 

11 to what they would have gotten from the 

12 coworker model and that's really, that was 

13 actually proposed by Sam Glover in the last 

14 meeting. I mean that would be one way. You 

15 might not get definitive answers because you 

16 can only go from the claimant population, but 

17 again at least it's some sort of quantitative 

18 approach to try to get a handle on this. 

19 So do we know how many claimants 

20 there are that do have some bioassay data that 

21 could be used to reconstruct their intake in 

22 the claimant population that are also 
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1 subcontractors? 

2 MR. HINNEFELD: You're talking 

3 about construction subcontractors. Okay. 

4 Well, as I understand it, the subcontractor 

5 data will not be in NOCTS and so it will not 

6 be in their claim files.

7 MR. BARTON: Well, also it was 

8 indicated during the technical call that these 

9 939 data points that we do have are now being 

10 electronically linked to the claimant files so 

11 that those claimant files would now have, you 

12 know, if they're included in that population 

13 of 940 samples then now those bioassay samples 

14 would be available for any subcontractors.

15 MR. HINNEFELD: Right. That would 

16 be the way to do it and I don't know that we 

17 have that result of that yet. That would be a 

18 way to identify construction workers prior to 

19 1986 who we now have bioassay data for who 

20 were also claimants. So I suspect nobody on 

21 the phone is up on the progress of that 

22 linking. That's what we call SPEDELite 
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1 process. 

2 But perhaps we can send a message 

3 and find out where that is. And presumably 

4 the result of that SPEDELite matching would 

5 tell us how many of these people who we found 

6 bioassay data for are in our claimant 

7 database. 

8 A quick look at the names from the 

9 data you sent this week kind of tells me 

10 pretty clearly that none of those people seem 

11 to be claimants. But that's -- the easy way 

12 to do it though would be to do -- finish the 

13 SPEDELite linking and then determine how much 

14 data we have. So that would be the way to do 

15 that. In that case then we do have the 

16 employment history for these people.

17 MR. STIVER: Yes, this is John. 

18 Thanks for bringing that up, Bob. That's 

19 something Mark had mentioned that sort of 

20 implied that there -- or at least some of them 

21 were in the claimant population.

22 MS. BRACKETT: This is Elizabeth 
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1 Brackett. This doesn't address the direct 

2 question that's being discussed but as far as 

3 comparing the individual subcontractors to the 

4 doses or intakes assessed by the coworker 

5 study, the coworker study is an approximation 

6 of people's intakes. It's not going to be 

7 exact.

8 You know, we put together all the 

9 bioassay data and then make the assumption of 

10 a chronic intake which is not necessarily the 

11 case for all individuals. But it approximates 

12 a number of acute intakes.

13 Now, for samples that are code 50, 

14 those are specifically meant to indicate an 

15 occurrence happened. So those are likely from 

16 an acute intake. 

17 So I think the comparison would 

18 best be served if we assumed that the code 50s 

19 were due to acute intakes to look at an 

20 individual to see if we did them as an 

21 individual case where we have their data those 

22 would be assessed as acute intakes rather than 
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1 chronic. And so we could take that intake and 

2 compare it to what would have been assigned 

3 had they had no data and we assigned coworker, 

4 in which case we would have assumed a chronic 

5 intake. So I think that's the comparison that 

6 needs to be done. 

7 We don't take the code 50s and 

8 force-fit a chronic intake to some period. We 

9 just make the assumption of an acute intake 

10 and then see what the equivalent chronic 

11 intake would have been over their employment 

12 period. I think that would be the correct 

13 comparison because that would be the way the 

14 cases would be done.

15 MR. HINNEFELD: This is Stu. And 

16 unless there was a change in the numbering 

17 system the code 40 was an incident sample. 

18 The 50s was something that was taken off, not 

19 on the routine schedule, but apparently not 

20 because there was an over incident. Unless 

21 there was a change in the naming.

22 MS. BRACKETT: It says something 
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1 about follow-up or a special study is what it 

2 indicated.

3 MR. HINNEFELD: Right, special 

4 studies would be something. I mean these 

5 people are not on the routine bioassay 

6 program. But an incident that prompted 

7 samples usually -- now, that code may have 

8 been used sometimes for that purpose but by 

9 the eighties there was -- type 40 was 

10 specifically an incident sample.

11 MS. BRACKETT: The patterns 

12 definitely look like --

13 MR. HINNEFELD: Yes, the patterns 

14 look like it. You have end of shift and start 

15 of shift samples fairly close together.

16 MS. BRACKETT: But then looking 

17 at, for example, the ones in 1969, the people 

18 were sampled over a couple of weeks. And it 

19 decreases the way you would expect an acute 

20 intake to.

21 MR. STIVER: Well, then I guess --

22 talk about that 1969 comparison study we did. 
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1 We just did this over a couple of days. 

2 And we did pick that year because 

3 it did appear as though there was an exposure 

4 experienced by the subs that was not 

5 experienced by the primes. Now, whether this 

6 was -- it looks from the baseline data that 

7 they were continuously exposed to uranium but 

8 there was at least some kind of -- whether it 

9 was chronic or acute there does appear to be 

10 some exposure that they experienced, was not 

11 experienced by the primes which is why we kind 

12 of looked at that data set. 

13 And we did compare them, you know, 

14 just looking year to year, as Liz said. If 

15 you don't know the duration, why, you have to 

16 make some assumptions and so it was kind of an 

17 annual comparing apples to apples type thing.

18 But we felt this was pretty 

19 important, the result there was that the 

20 geometric mean in the subs for that period 

21 from I believe it was July through October `69 

22 was higher than 95th percentile for the 
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1 primes. 

2 And you know, Harry sent out --

3 and it might be time to take a look at that. 

4 Let me pull this up here real quick. So many 

5 files open right now. Yes. It's called 

6 Fernald 1969 data comparison I sent out 

7 yesterday. 

8 And I'm just going to read this. 

9 The Table 1 you can see comparison of log 

10 normal model for `69 subcontractors in HIS-20 

11 data. Geometric means for the subcontractors 

12 is 25.8, for HIS-20 is 3.99. The 95th 

13 percentile of HIS-20 is 21. In that 

14 situation, the subcontractors' geometric mean 

15 is actually higher than the 95th percentile of 

16 the HIS-20 data. 

17 Harry, would you like to talk 

18 about this a little bit since you did the 

19 study?

20 DR. CHMELYNSKI: Well, I think 

21 that it's pretty obvious when you look at the 

22 set of numbers that they stand out as being 
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1 different than most of the coworker samples 

2 would be, also higher than what you see in 

3 HIS-20 which does include a lot of workers who 

4 probably weren't in exposed situations.

5 I don't know that there's any 

6 particular reason to talk about the 

7 statistical methods. The numbers themselves 

8 stand out quite distinctly as being a 

9 different population. Why that's true I'm not 

10 sure.

11 MR. STIVER: I guess the important 

12 thing to take home from this is that this data 

13 does show, this comparison shows that there's 

14 a particular exposure that involved the subs 

15 and not the primes and we couldn't predict 

16 those results by looking at only the results 

17 of the primes. 

18 So one particular year, one subset 

19 of the data we just happened to take a quick 

20 look at found the situation the coworker model 

21 probably wouldn't provide a bounding exposure 

22 for this other group. 
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1 You know, again, it begs the 

2 question obviously well, what other potential 

3 exposures are out there for which we just 

4 don't have data. I guess that's why we wanted 

5 to bring this up during the discussion was 

6 that here's an example of just the thing we 

7 were concerned with. 

8 And I don't know that there's 

9 really a solution to this at this point. You 

10 know we can do --

11 DR. LIPSZTEIN: John? May I?

12 MR. STIVER: Sure.

13 DR. LIPSZTEIN: When we look at 

14 the subs' urine excretion rate since `69 and 

15 we looked at `69 because that's the year it 

16 started the subs have data from July until 

17 October. In particular, in August they had a 

18 very high excretion rate. 

19 Most of the workers, they had 

20 monitoring results for the whole period that 

21 they were, you know, from July to October. 

22 And so probably they were continuously 
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1 employed there. Some of them had also -- `71, 

2 the next year that we have data.

3 But anyway, there were 53 results 

4 instead of -- if you go through the OPOS it's 

5 12. But if you go through the results itself 

6 you have 53. 

7 In particular, August made us look 

8 at the table of results and see oh, something 

9 happened here in August. And then we looked 

10 at the same period of time for the prime and 

11 they didn't have that. So August was, you 

12 know, just a normal month. Nobody had very, 

13 very high excretion rates. 

14 So probably the subs were having, 

15 you know, some special job, something that the 

16 primes were not involved in. That could --

17 either this or we don't have complete data 

18 set. It depends if there was a contamination 

19 in the lab because. But I don't think --

20 unless they went to different labs. If they 

21 went to the same, you know, if they were 

22 measured in the same laboratory there is no 
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1 why should we suspect that there was a 

2 contamination just for the subs. 

3 So, what happens is that this 

4 particular month, something that the subs did 

5 depended on it too. Also, if you look at the 

6 other month they also have excretion rates 

7 that are higher than the prime in general. 

8 And this you can see by the plots that Harry 

9 did using the OPOS and using the whole data, 

10 the whole 53 data results that we had. 

11 And then we looked, these August 

12 results, they were so high that couldn't be 

13 predicted by any using the prime and 95th 

14 percent. So there is something that can be 

15 predicted. 

16 What I'm saying is that you can't 

17 -- unless there is proof that there was, you 

18 know, this was a special case that everybody 

19 that was on that particular job that had such 

20 a high exposure where the only people involved 

21 were the unmonitored subs were not involved in 

22 this job, we certainly can't use the coworker 
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1 for the contractors for the prime for the subs 

2 because they have a different kind of 

3 exposure, a different kind of job. 

4 And even the 95th percent doesn't 

5 satisfy it because you can see from Harry's 

6 data that the GM for the subs is higher than 

7 the 95th percentile. So, it's -- that's one 

8 point that we wanted to make. Is the 95th 

9 percent for the -- I don't think so looking at 

10 the `69 data. 

11 MR. HINNEFELD: This is Stu one 

12 more time. And Liz's point awhile ago. Let's 

13 think about how this would -- how this data 

14 would be used as coworker and then how it 

15 would be used if it were an individual's data.

16 The coworker study doing one 

17 person/one sample I guess you do essentially 

18 an average excretion rate for a person based 

19 on their data for that year and that's your 

20 one person/one sample data point. Is that a 

21 true statement?

22 DR. LIPSZTEIN: We used both. 
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1 Harry's work, he used both.

2 MR. HINNEFELD: I'm actually 

3 asking the ORAU team.

4 DR. LIPSZTEIN: Oh, I'm sorry.

5 MR. HINNEFELD: When we do a one 

6 person/one sample we have a person with 

7 multiple samples in a year, do what, an 

8 arithmetic average of his data and that's the 

9 data point for that one person?

10 MR. ARNO: That's correct. 

11 MR. HINNEFELD: Okay. So if 

12 that's the case then if we were to treat this 

13 subcontractor data set, that 1969 as a -- if 

14 that were treated the way a coworker data set 

15 would be you would do an arithmetic average of 

16 one of these individuals -- and say that's his 

17 average excretion rate for the year. And then 

18 you would say then you could come up with an 

19 intake that would correspond with that. 

20 But Liz's point earlier, it's 

21 pretty clear and Joyce's point that the 

22 highest intakes occurred, it looks like they 
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1 occurred sometime in July because they were 

2 identified -- samples taken at the end of 

3 July. And the same individuals were sampled 

4 again later on. And you have much smaller 

5 numbers. 

6 And so you do not have 

7 essentially, you don't have this exposure for 

8 these individuals for a year that gives them 

9 that average intake rate. You have an 

10 exposure in July and then a much lower level 

11 of exposure following that to allow those 

12 urine data to come down the way they did. 

13 So, back to the original request 

14 that SC&A made. And I guess I can plead some 

15 ignorance here because I wasn't at the meeting 

16 last year when this topic was discussed about 

17 sample dose reconstruction. 

18 It seems like how would we treat 

19 these cases might be one thing. But would --

20 have a person with this data, what does the 

21 dose reconstruction look like or the intake 

22 estimate look like.
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1 And then to Bob's point earlier on 

2 of can we finish the SPEDELite linking and 

3 identify the larger data set, identify a data 

4 set of construction workers with data now 

5 linked to them that are claimants in NOCTS and 

6 determine -- where we will have employment 

7 histories, where we can do something of a dose 

8 reconstruction with that bioassay data. 

9 So that sounds like possibly two 

10 possible things that could advance the 

11 discussion a little bit. Am I right or wrong 

12 on that?

13 MR. STIVER: Stu, this is John. I 

14 kind of see your point regarding what Liz had 

15 brought up about the potential for acute 

16 intakes.

17 You know, this particular data set 

18 does look like there was some sort of an event 

19 either in late July or August that caused 

20 these people to get an intake that wasn't 

21 experienced by the primes. 

22 And I can see that assuming you 
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1 can't really make the assumption this is a 1-

2 year chronic intake given each of these data 

3 points. You would have to use some sort of an 

4 averaging. So maybe I would ask Joyce if she 

5 thinks that would be a reasonable thing to do 

6 to have DCAS go ahead and do some 

7 reconstructions. 

8 First, these are kind of separate 

9 things. The SPEDELite obviously you want to 

10 do. But rather than make the same assumptions 

11 we would for the coworker model go ahead and 

12 fit the data like you normally would for a 

13 dose reconstruction. 

14 The wrinkle there being if you 

15 don't have the SPEDELite connection to the 

16 employment information you've got to make some 

17 assumptions about when they're taking place. 

18 So there will be obviously some professional 

19 judgment involved in that.

20 DR. LIPSZTEIN: I really think 

21 that the first thing to do is to see how 

22 representative the prime data are for the subs 
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1 even if used in 95th percent. We just looked 

2 at `69 and we compared, you know, we only had 

3 data from July to October. And we compared 

4 the same data from July to October also that 

5 was Harry's work for the prime. 

6 And we can see that the workers 

7 who were exposed in July, August, September 

8 and October, most of the workers have high 

9 results for all the four months. And in 

10 August they have super high exposures. We 

11 didn't see that pattern for the prime. So I 

12 think that the data we have for the prime is 

13 not representative of the subs.

14 And the 95th percent is just, you 

15 know, there is no justification of why the 

16 95th percent, why the 95th percent would be 

17 bounding for the sub when we see from this 

18 sample that it's not. 

19 And then if we do this comparison 

20 for the years we have -- we just have data 

21 from -- we don't have data for all the years, 

22 but we have one year that it doesn't match. 
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1 So why should we assume that the distribution 

2 of the subs may be well represented by the 

3 prime and use a 95th percent? Why this 

4 number, 95th percent? 

5 When I looked at the data for `69 

6 I clearly see that there were no primes 

7 involved in that exposure. Because there is 

8 no data that is so high as the others at the 

9 same month. And we can see that they started 

10 in July and then in August they have a very 

11 big explosion. Then it decays in September 

12 and October, but doesn't decay to the level of 

13 the prime. 

14 So for me it's like if you want to 

15 use one distribution for the other you have to 

16 prove in some place that the 95th percent is 

17 really bounding. It doesn't look for me that 

18 it's bounding.

19 MS. BRACKETT: This is Liz 

20 Brackett. I would just point out that there 

21 is one prime whose result is equal to the 

22 largest value of the results for the subs in 
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1 that time. 

2 DR. LIPSZTEIN: In August? It was 

3 1,000. There were two workers with 1,000 dpm. 

4 There is.

5 MS. BRACKETT: Okay, maybe it was 

6 July then. Because there was --

7 DR. LIPSZTEIN: I think it's one 

8 hundred and something. And it's close to 

9 1,000.

10 MS. BRACKETT: I think it was 450. 

11 There is one -- maybe it's the July set, but 

12 there was one -- I mean I'm not saying all of 

13 them, but there was one prime whose result was 

14 equal to the largest sub. 

15 DR. LIPSZTEIN: But it's not --

16 you know, it's not the same exposure, not at 

17 the same time. In August there was an 

18 exposure where the two workers was 1,000. One 

19 worker, I don't remember anymore, but 600, 

20 400. Many workers was -- there was some 

21 exposure situation in August.

22 CHAIRMAN CLAWSON: John, this is 
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1 Brad. I'd like to make a comment, please, 

2 with this. The reason I asked, the point was, 

3 Stu, and I hope that you take this with a 

4 grain of salt. 

5 I want you to understand my 

6 frustration because right now I'm looking at 

7 my understanding out of the last Work Group 

8 meeting when we were coming here basically 

9 NIOSH was going to prove their point. They 

10 were going to bring back and show us how this 

11 was going to work. 

12 And this new rev to the coworker 

13 model in my opinion is a step backwards. We 

14 still haven't proven what's really out there 

15 and how we're going to bracket these people 

16 into a coworker model and how we're going to 

17 separate them. 

18 This type 50 data I've been told 

19 for years now and understand, this is going 7 

20 years now that we've been doing this work. 

21 Actually I was told the other day it was 8 

22 years by Sandra Baldridge and I can feel her 
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1 frustration on this.

2 This coworker problem has been a 

3 big issue. When we get into this type 50 data 

4 I've heard no, this is for event-driven, this 

5 is going on with this. No, I was told that 

6 when the subcontractors started coming in onto 

7 the site they didn't have a real place to be 

8 able to put them so they put them into the 

9 type 50 and they'd sample them as they go 

10 through. And this is how we were going to 

11 segregate them out. I've heard we're going to 

12 pull the type 50 data out, not use the type 

13 50, go back in. And to tell you the truth, 

14 right now I'm feeling like we're nowhere near 

15 where we were supposed to be a long time ago. 

16 And there's an awful lot of 

17 frustration here because we have actually in 

18 my eyes gone full circle with this coworker 

19 model here. We're back to basically square 

20 one. And with the time frame that we had put 

21 into this I'll be right honest I'm pretty 

22 disappointed in it. 
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1 And I'm sitting here listening to 

2 this discussion and to me we are nowhere close 

3 at all to where we were supposed to be. We've 

4 made some progress but I want you to also 

5 understand these -- and Stu, you're probably 

6 more aware of this than I am. In talking with 

7 the construction trades, these people came in 

8 there, a lot of them worked at Fernald for 

9 different contractors but they were there for 

10 18 to 19 years. And they would go on projects 

11 that the primes would not because the prime 

12 contractors were responsible for -- their 

13 doses were enough that they were getting into 

14 it. So big projects, they would come in.

15 But these people also never left. 

16 They continued on. They just went from one 

17 contractor to another contractor going on. 

18 They had no way of having a routine bioassay 

19 program or whatever. A lot of it was driven 

20 by a job or a project that maybe they may have 

21 worked. It's like they said, in the 

22 summertime they tried to get some of these big 
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1 projects done in the summertime so that when 

2 winter and stuff come like that that they 

3 wouldn't have these problems.

4 I still have not seen a way that 

5 we are going to be able to make a very good 

6 coworker model. Now, I don't know all the ins 

7 and outs of it and you guys may be able to, 

8 but I want you to know my frustration. 

9 And I want to go on the record 

10 that I'm very, very disappointed. We should 

11 have been a heck of a lot further to this. 

12 And out of the last Work Group meeting my 

13 understanding was we were going to prove that 

14 this project, how it was going to work and how 

15 it was going to tie everyone that we would be 

16 able to do a dose. And what I got back was a 

17 new rev to this paper and basically two steps 

18 back and we still have to be able to prove 

19 that it fits to the workers.

20 MR. HINNEFELD: Well, I appreciate 

21 your frustration, Brad, but all I can say is 

22 from where we are now. And I don't think --
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1 and I really can't speak to the SPEDELite 

2 linking process so I don't know where that's 

3 at.

4 MS. JESSEN: Stu?

5 MR. HINNEFELD: Yes.

6 MS. JESSEN: This is Karin. We've 

7 checked with Cheryl and this should be ready 

8 for you tomorrow.

9 MR. HINNEFELD: So all the 

10 SPEDELite will be linked tomorrow and we'll 

11 know where the construction workers that are 

12 in our database have claims.

13 MS. JESSEN: Well, the linking 

14 will begin today and it should be completed by 

15 tomorrow.

16 MR. HINNEFELD: Okay. And then 

17 the next step will be how many people did we 

18 find in the database in the claimants, among 

19 the claimants that we just link data to. 

20 That's the next, second thing. And then from 

21 that we can try to -- how many there are. 

22 There may not be that many in which case we 
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1 could see what would the dose reconstruction 

2 be with these data and compare that to what 

3 the coworker model would say.

4 This isn't particularly relevant 

5 to anything other than I'd like us to all be 

6 able to look at the interpretation of this 

7 data the same way. I'm looking now at the 

8 data set that SC&A sent with construction 

9 workers from `69.

10 They're ordered by date and you'll 

11 notice that the crews, the large results, 

12 there is one large result in July. But the 

13 really large results occurred in a sampling at 

14 the end of August, late August, and it's a 50 

15 sample which means it was a start of shift 

16 sample. And it had been roughly a month since 

17 the last bioassay data set out of this crew. 

18 So, I think it -- but it kind of 

19 indicates pretty clearly is whatever they were 

20 doing between July 28 and August 27 there were 

21 some really high exposures to this crew during 

22 this time. But I don't think I would conclude 
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1 that that was particularly an incident. I 

2 think that they were in a particularly high3 exposure environment for some portion of that 

4 month. And then apparently they were in a 

5 lower-exposure environment later on because 

6 the bioassay data come down. Well, they come 

7 down pretty dramatically even in a week. And 

8 then additional sampling then at the end of 

9 October, or early October is also certainly 

10 far lower than -- there are plenty of positive 

11 results in there, not trivial results based on 

12 numbers that I'm used to. But they're 

13 certainly far down from the August numbers. 

14 So the exposure patterns is pretty 

15 clear from this work. And I would not expect 

16 to have the same exposure patterns of a 

17 subcontractor crew that quite likely was doing 

18 a demolition of -- you know, that's the 

19 problem. We don't know what these people were 

20 doing. Quite likely they were doing a 

21 demolition of something and I wouldn't expect 

22 a prime to have that kind of exposure 
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1 experience. 

2 But a prime would have a chronic 

3 exposure experience, be more likely to have a 

4 chronic exposure experience over 12 months 

5 rather than an experience that was largely 

6 episodic but with one large episode. Just so 

7 we all look at this in the same way here.

8 MR. STIVER: I guess that's the 

9 question though. You have -- is the prime 

10 data set then representative of the exposures 

11 to these subs, you know, regardless. It may 

12 be a short-term exposure to say type F 

13 material but that's still certainly going to 

14 result in high doses to anything other than 

15 the lungs in comparison to the insoluble type 

16 which might have been experienced by the 

17 primes. So I think we still have that issue, 

18 is this really a representative data set.

19 MR. HINNEFELD: Well, I don't 

20 think the issue is whether the prime data set 

21 is representative. The issue is does a 

22 coworker model developed from the prime 
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1 provide a bounding annual intake for people 

2 who were construction workers. That is a 

3 little bit different question than is one 

4 representative of the other.

5 MR. BARTON: This is Bob Barton. 

6 I'm sorry. Could I ask a clarifying question 

7 on that point? Because I wasn't quite clear. 

8 When -- let's say you had a subcontractor who 

9 didn't have any data. And you know, you have 

10 his employment record obviously. And say he 

11 was onsite for only 2 weeks in the year. When 

12 you apply the coworker model are you then 

13 saying even though there's only onsite for 2 

14 weeks in that year we're going to assume had a 

15 full year of chronic intake based on the 

16 coworker model? Or would you only assign it 

17 for the days he was onsite?

18 MR. HINNEFELD: I'm not smart 

19 enough to answer that. Maybe somebody.

20 MS. BRACKETT: This is Liz 

21 Brackett --

22 MR. ARNO: This is Matt Arno. 
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1 That would depend on where your Probability of 

2 Causation. You could just make the assumption 

3 for all year which --

4 CHAIRMAN CLAWSON: Who was that 

5 talking?

6 MR. ARNO: This is Matt Arno. I 

7 was saying you would assume a full year of 

8 exposure if you were doing it as an 

9 overestimate with a PoC less than 45 percent. 

10 And then you would refine it down to the 

11 actual duration if you PoC increased above 45 

12 percent. 

13 MS. BRACKETT: Well, this is Liz 

14 Brackett. The correct way to do it would be 

15 to assign the specific dates, the intake over 

16 the specific dates of the employment. 

17 MR. BARTON: Well, then I guess my 

18 response to that would be you can make the 

19 argument that a chronically exposed worker 

20 over a year is going to have a higher intake 

21 of uranium than someone who was only on the 

22 site for 2 weeks and had a very short but 
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1 high-level intake. But if you're still going 

2 to only assign uranium intakes based on the 

3 coworker model and so you're only getting 

4 uranium per day I think that kind of 

5 conservatism kind of flies out the window. 

6 Because you still have only assigned him the 

7 14 days or 10 days of uranium intake based on 

8 -- it's based on the chronic full-year 

9 exposure but they're not going to get the 

10 full-year exposure intake in that way.

11 MS. BRACKETT: Well, that's why a 

12 comparison would need to be done to see what 

13 the acute intake might have been versus what

14 the chronic over that same period.

15 MR. BARTON: I agree, I agree. I 

16 think we're in agreement.

17 MR. STIVER: Typically that's the 

18 way it's done is you do both and then pick the 

19 highest. Would that be a correct assessment, 

20 Liz?

21 MS. BRACKETT: No. If you --

22 well, if you had the data for the individual 
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1 and you knew that they had an acute intake 

2 then that's what you would assign. If you 

3 didn't know what the exposure pattern was, you 

4 could do it that way. But it's all dependent 

5 on what data you have, what information you 

6 have about them as to what assumptions would 

7 be made.

8 MR. STIVER: I guess I can see 

9 Bob's point though. I mean you might have had 

10 somebody who was unmonitored who was involved 

11 in one of these incidents yet they would get, 

12 you know, a much lower value for that same 

13 period of time.

14 MS. BRACKETT: Well, I guess --

15 MR. STIVER: Certainly 

16 underestimate.

17 MS. BRACKETT: I guess one of the 

18 issues is, I mean how many people would be 

19 expected to be involved in these incidents 

20 that weren't being monitored. Since there are 

21 a large number of subcontractors that were 

22 monitored for this particular case clearly 
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1 they knew something had happened so they 

2 monitored them. How likely is it that someone 

3 would have the intakes equivalent to these 

4 people and have no monitoring data? 

5 MR. BARTON: Well, I don't think 

6 we have the data to answer that question. I 

7 mean do we know that this, you know, the 

8 subcontractor data we're looking at here for 

9 August of 1969. I mean, you know, were there 

10 unmonitored people in that population because 

11 maybe they only monitored half of them.

12 And to go to something Joyce said 

13 earlier, for periods where we don't have any 

14 data do we know that incidents -- we call them 

15 incidents. Maybe that's not the right word. 

16 A special project like a demolition. Do we 

17 know that these types of exposure potential 

18 which could be very high, do we know when they 

19 existed and how do you deal with that when 

20 you're applying sort of the one size fits all 

21 model. 

22 I know the 95th percentile is 
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1 being proposed but these types of activities 

2 that have the higher exposure potential could 

3 have been happening at different times other 

4 than this one example that we gave. And I 

5 don't know if we have sufficient information 

6 right now to be able to characterize that.

7 MR. STIVER: I guess it gets down 

8 to do you have the information to put a 

9 reasonable bound. In this particular 

10 situation it would illustrate that if you did 

11 have unmonitored workers that were exposed to 

12 that type of -- that particular special 

13 project for lack of a better term they would 

14 not have been -- they would not be 

15 particularly bounding. 

16 So that just bumped into the 

17 question how many other times could this have 

18 happened in earlier times and other years. 

19 And one of these people might just not have 

20 been monitored. Probably a small number but 

21 we don't know. We don't know.

22 CHAIRMAN CLAWSON: Well, this is 
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1 part of the problem. And if you remember --

2 this is Brad speaking. If you remember what 

3 the construction worker that was in the room 

4 with us told us there, he had worked at 

5 Fernald for over 20 years. Now, not for one 

6 contractor, it was always for different ones. 

7 When they would get done with 

8 major projects which one of the things they 

9 tried to do with a lot of these in the 

10 summertime when they were replacing piping in, 

11 I can't remember what the name of the process 

12 room was or anything else like that. 

13 Then they would take one or two of 

14 the people would have a sample given and that 

15 was it. And they were looking at this as 

16 being a representative sample for the rest of 

17 the construction workers that were involved 

18 with this. So, this probably needs an event19 driven. I think I'd call it -- it looks like 

20 to me an event or a project, a very hot 

21 project just like we do today sometimes. When 

22 we get done with a project there's a lot of 
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1 times we're submitting bioassay to be able to 

2 understand what we went through.

3 MR. HINNEFELD: This is Stu. 

4 First of all, these data are -- I'm not going 

5 to -- I think there are a lot of arguments by 

6 SC&A here that carry some weight. And I can 

7 kind of speak -- I don't know that we're in an 

8 argument or a debate, or if I'm on the side of 

9 a debate or not. If so I'm probably switching 

10 sides.

11 But to your point, Brad, these are 

12 clearly not end of the job samples because 

13 they're spread over 4 months. I mean, they 

14 were sampling during the work it seems to me. 

15 CHAIRMAN CLAWSON: Yes, they very 

16 possibly could. I guess my whole thing is 

17 this comes back to one question with me. Are 

18 we going to be able to, and this is a thing 

19 that I threw out to Mr. Rolfes a very, very 

20 long time ago with the construction workers is 

21 how are we going to be able to 

22 representatively make sure that we can bound 
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1 their dose. And to tell you the truth I'm 

2 still waiting to be able to see how we can do 

3 this.

4 One of the things to me that is 

5 very interesting about Fernald. Stu, you'll 

6 probably understand. They have so many 

7 samples for the workers. It's one of the ones 

8 that we've seen the most of. But it was 

9 mainly towards the prime contractors. We've 

10 got a good data set to be able to work out 

11 from them.

12 For the subcontractors and stuff 

13 like that I see a very large gap and how would 

14 we be able to do it. There's such a 

15 difference in my eyes as from the contractor 

16 to the prime that I think it would be hard for 

17 us to be able to make a comparison. But you 

18 guys have proved me wrong before. That's kind 

19 of where I see the issue, the crux of 

20 everything lying is right there.

21 MR. HINNEFELD: Yes, this is Stu 

22 and I don't dispute that at all. I think my -
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1 - I wasn't there in the sixties but my 

2 observation in the early eighties was that it 

3 was a different -- that subcontractors were 

4 regarded somewhat differently than the prime 

5 contractors, employees. 

6 And so to the point that the thing 

7 that always that is sticking with me on what 

8 we're talking about. We have -- since we're 

9 just talking about this 1969 data an awful lot 

10 we have this project where someone decided, 

11 you know, maybe we should monitor these 

12 people. And so they put them on this bioassay 

13 program. We've got some 4 months’ worth of 

14 monitoring. We don't know how that 

15 corresponds to the duration of the job either. 

16 You know, did they say right away 

17 we should monitor these people or did they 

18 work for a while and then they say we should 

19 monitor these people? We don't know if the 

20 job ended in October and that's why there are 

21 no more samples. So there's a lot we don't 

22 know about it. 
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1 We don't know what the decision2 making process was that said this group of 

3 subcontractors should sampled. Because I'm 

4 pretty sure we have people in the database who 

5 look like subcontractors who we don't have 

6 data for. So we don't really know who made 

7 the decision or what the decision process was 

8 for sampling contractors and whether the 

9 decision process was constant and uniform over 

10 the time. 

11 So, I see where you're coming 

12 from, Brad. There is a certain amount of 

13 question I think about that. And I don't know 

14 that those are answerable questions to be 

15 completely honest. I don't know who you would 

16 ask at this point.

17 MR. STIVER: Well, I guess that's 

18 where if it's our main concern -- this is 

19 Stiver again. The uncertainty of those 

20 questions is just -- we don't have the process 

21 knowledge and history necessarily to truly 

22 answer those with any degree of confidence. 
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1 So that to my mind is why you have to 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

demonstrate that this coworker model will be 

sufficiently bounding for the -- whatever the 

highly exposed groups are. And this 

particular group in `69 certainly would 

illustrate just the type of concerns we've 

got.

 So, I guess the question is where 

do we go from here. I think it's certainly 

worthwhile to do some of these comparisons, 

some example reconstructions, to at least try 

to get a better handle using the data we do 

have, really explore that thoroughly. Is this 

going to be able to answer the question with 

any degree of confidence. 

 MR. HINNEFELD: Yes, I would think 

that we can do some of those comparisons and 

then I think we should have some discussions 

on our side as well.

 MR. STIVER: Yes. And so you will 

have that link-up tomorrow then.

 MR. HINNEFELD: Apparently they 
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1 can link those pretty quickly and they'll have 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

the SPEDELite links done.

 MR. STIVER: -- an idea what 

number of claimants are actually able --

 MR. HINNEFELD: We'll have an idea 

of how many claimants do we have who were in 

that -- have data now. I don't know how many 

it will be and how much data they'll have so 

we won't --

 CHAIRMAN CLAWSON: This is Brad. 

Is SC&A going to be able to have access to 

this information too?

 MR. HINNEFELD: Yes, sure.

 CHAIRMAN CLAWSON: I didn't know

if it was in one of your own systems or if --

 MR. HINNEFELD: It's in NOCTS. I 

mean the thing we could do is just identify to 

SC&A which are the claim files.

 MR. STIVER: Yes, identify the 

claim files.

 MR. HINNEFELD: You can find it in 

there. It'll be in the documents part of the 
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1 claim and it'll be under personal exposure 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

information. 

 CHAIRMAN CLAWSON: Well, these are 

questions we need to be able to answer. And 

unfortunately these are the questions that 

I've been requesting for the last 4 to 5 years 

and have been worrying me about this.

 And I don't see any way -- somehow 

we've got to be able to prove this is going to 

be able to be a bounding or if this is not as 

we've got two avenues that we can go on this. 

But I'm going to be really honest. This is 

coming to the end of the ball game here. We 

have spent so much time on this and we are 

nowhere -- we're not anywhere close to when we 

began on this. 

 So, I really -- when we sit down 

with this, and John and Stu, I want you to be 

thinking about this. I want to have a clear 

path forward when we get done with this of 

what we're going to do and if we can prove it 

or not, bottom line. Because this has -- this 
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1 has been one of my issues with this. And I've 

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been assured that they have enough information 

that they were going to be able to build this 

coworker and that it was going to be 

representative for the construction trades.

 I want to go back in the history a 

little bit of where we have been on this. At 

one time we were going to task the contractor. 

Earlier we had enough information we were 

going to leave the type 50 out and we were 

going to just put them in with the whole body. 

We've been through several iterations. But 

I'm the only Board Member on here so I'm just 

speaking for myself but I'm telling you we're 

hitting near the end of the road. This has 

gone on way, way too long. 

 MEMBER ZIEMER: Brad, this is 

Ziemer. I just wanted to let you know that 

I'm on the line. 

 CHAIRMAN CLAWSON: Okay.

 MEMBER ZIEMER: I've heard a fair 

amount of this particular discussion. Yes. 
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1 So I would hope we could come to closure 

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fairly soon even if we have to separate or I 

guess it's going to come down to whether 

there's going to be a separate coworker model 

for these workers versus the prime. Is that 

what it would come to, Stu, or not?

 MR. HINNEFELD: Well, Paul, I 

think what it would come to is, is there a way 

to do dose reconstruction for subcontractors. 

 MEMBER ZIEMER: Right, right.

 MR. HINNEFELD: That's what -- I 

mean that's the question. 

 CHAIRMAN CLAWSON: And there's one 

other part to that too, Stu, is if you're 

going to be able to separate the contractors 

away from the prime. Because I understand in 

the earlier years this was kind of a -- that's 

going to be a little bit of a problem too, 

that you're --

 MEMBER ZIEMER: You mean 

identifying them, Brad?

 CHAIRMAN CLAWSON: Yes.
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1 MEMBER ZIEMER: I was assuming we 

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could identify them.

 MR. HINNEFELD: I'm not aware of 

an issue with that. I would think we should 

be able to tell who their employer is.

 CHAIRMAN CLAWSON: Okay. Well, I 

understood the earlier years there was kind of 

a problem with that because they weren't able 

to really, really separate them out. They 

felt that they had a good idea of how they 

could separate them out but in the earlier 

years in some of the programs they weren't 

separated out that well. So I just want to 

make sure that that's one of the keys to it 

that we are able to be able to do. Because 

they had a good bioassay program from the very 

get-go of this, but how they brought the 

subcontractors in and out of that was not the 

best. So I just want to make sure that that's 

one key to it that we need to make sure we can 

do.

 MR. HINNEFELD: Okay. I'd be 
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1 surprised if we weren't able to tell if 

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somebody was an employee of the prime. That 

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 CHAIRMAN CLAWSON: Well, and 

correct me if I'm wrong, John, but one of the 

other problems was being able to have 

substantial data. Because one of the things 

Mark was trying to do was link the bioassay 

program, this big pot of bioassay with the 

primes to be able to make a good coworker 

model for that.

 MR. STIVER: Yes, Brad, that's the 

issue of representativeness.

 CHAIRMAN CLAWSON: Right. This is 

why --

 MR. STIVER: -- somebody that 

doesn't really -- is not really applicable to. 

And so in my mind the question is, okay, are 

we going to have enough subcontractor data to 

characterize their exposures for all the years 

prior to 1986. I guess that's one aspect of 

it is the data completeness and the other 
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1 being the data adequacy. It always comes down 

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to those two things. The adequacy really is 

that do you have enough information to really 

characterize their exposures. Now this is 

assuming we're trying to do a separate model.

 MR. BARTON: Yes, John, this is 

Bob Barton. I think we're talking about kind 

of two separate things. Certainly if we had a 

claimant and we had their exposure record or 

their employment history we could see who they 

were employed by and say yes, they were 

probably a subcontractor. 

 But to what Dr. Ziemer said, if in 

fact these are two completely different 

populations that need, you know, the 

subcontractors need a separate coworker model 

I'm not entirely certain if there's enough 

subcontractor data out there to really put 

together a coworker model. And I guess I'd 

kind of ask, you know, NIOSH and ORAU what 

their feeling is. It just doesn't, I mean it 

seems like there's kind of a paucity of data, 
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1 at least what we have so far, of actual 

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subcontractor results that we can identify as 

subcontractor results. 

 And I guess I'd ask if it came 

down to making a separate coworker model and 

that the current prime coworker model was not 

representative. I mean would we even be able 

to do that?

 MR. HINNEFELD: Well, this is Stu. 

That's why I asked it as saying that I think 

the question is whether we can do the 

construction, you know, do dose reconstruction 

for the construction people. Because just on 

the face of it from looking at the numbers we 

have so far most of the years we don't have 

any construction contractor bioassay. So, me, 

I don't know that we would have a lot of 

confidence to that.

 Now, there is the question of the 

`83, `84 and `85 where there is actually a 

fair amount of construction. We do have a 

fair amount of contractor bioassay. I mean 
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1 there might be a question about those years 

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but prior to that it seemed to me that it 

wouldn't be much point in trying to build a 

coworker data set.

 MR. STIVER: There's only 9 years 

of data, you know, 940 samples in total.

 MR. HINNEFELD: And most of them, 

I mean I don't think any of those years until 

you get to maybe `83, I mean it's 30 

individuals. 

 MR. STIVER: Yes, yes. They're 

definitely underrepresented in those earlier 

years. 

 MR. HINNEFELD: So, you know, to 

me I don't see a lot of possibility of a 

coworker model with the possible exception of 

the `83, `84, `85, or whenever the later years 

of the period we're talking about. Because I 

just don't see a lot of -- it doesn't seem 

like it's going to work.

 I do agree, Brad, that we've got 

to be toward the end of the game on this.
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1 CHAIRMAN CLAWSON: Well, I just, 

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and I apologize if I seem a little bit rash. 

I just, you know, if you go back into the 

minutes. And Paul, you go back 4 years, you 

know. We were talking about a lot of this and 

how much information and if we were going to 

be able to do this. 

 So I don't mean to be rude in any 

way, it's just we're pretty well to the end of 

the road on this. So we've got to make a 

decision of which way we're going to be able 

to go and go with that. 

 Because I look back at the 

revisions that we have done to this and I 

understand that we're all trying to get to the 

same point and different aspects. But we've 

gone through quite a bit on these and we're 

just getting to the end to where we've got to 

make a decision one way or the other.

 MEMBER ZIEMER: And this is Ziemer 

again. I think your request for a clear 

delineation of the path forward, Brad, makes 
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sense. And perhaps a couple of these 

questions could be answered fairly soon. 

 Can we identify the worker 

population for the sub-primes, and also can 

you even build a coworker model for them yea 

or nay. And when will we know the answer to 

those. Those would be helpful. 

 CHAIRMAN CLAWSON: Yes. And one 

other thing is that I've always noticed in 

this is that we tried to take the prime 

contractor and use their bioassay to offset 

for the subcontractor. And I don't think that 

we can with that. We see too much of a 

difference between the two. You know, these -

- you know, you're right, Paul, but we've got 

to have a path forward. So, and I'm not that 

smart to figure this one out. But I guess 

that's what I'm expecting from both sides here 

is a path forward on this. And I think it 

kind of falls into NIOSH's lap right now where 

and what they're going to do.

 MR. HINNEFELD: This is Stu again.
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1 CHAIRMAN CLAWSON: Yes.

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 MR. HINNEFELD: So far the things 

I have are can we -- well, (a) can we build a 

subcontractor coworker -- and whether that 

would be for -- prior to `86 or whatever. Can 

we identify which claimants are employees of 

the prime versus employees of the 

subcontractor. 

 And then the comparisons we talked 

about earlier, after the SPEDELite linking, 

combining construction workers with some 

bioassay now and see what their bioassay would 

tell you about a -- a dose reconstruction 

versus what the coworker model would tell you.

 Also, to do some looking at the 

1969 data into what, given the actual data 

that we have there, what does the intake 

assessment look like for those workers. I 

don't know that that's going to be terribly 

illustrative but it's something that could be 

done.

 MR. KATZ: Okay. This is Ted. 
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1 Just another thought while you're on. And I 

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don't know if this applies or not, but several 

times, Stu, you or others have mentioned that 

there was a period early on I guess, or I'm 

not sure when, or multiple periods, I don't 

know which, when there really wasn't exposure 

potential because the buildings were being 

built, not operated yet. So, if you get to 

the point where you can't do a model you also 

need to delineate when exposure potential 

began for these subs. 

 MR. HINNEFELD: Right. I mean 

that would -- I mean when they were building

the facilities new you're talking about, what, 

`50 to `52 probably.

 MR. KATZ: Oh, okay. So that's.

 MR. HINNEFELD: Yes.

 MR. STIVER: Yes, that was like in 

the seventies where there was not much 

activity going on.

 MR. HINNEFELD: I think there will 

be sort of a natural selection that there 
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1 probably were not very many -- contractors 

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until they start remodeling things. And so 

there wouldn't be very many claimants for 

those years that were construction 

subcontractors. So I mean that to me is sort 

of naturally selecting. 

 MR. STIVER: It would kind of be 

self-selecting, wouldn't it?

 MR. HINNEFELD: Yes.

 MR. ROLFES: Stu, this is Mark. 

Are you able to hear me?

 MR. HINNEFELD: I am.

 MR. ROLFES: Okay. I was able to 

step out of the room where we have all the 

jurors here. I'm on jury duty today. But 

I've been listening along and I'm able to --

and I've been looking through the Site 

Research Database. And I have found a couple 

of references that explain the work that the 

subcontractors with the high urine excretion 

rates were doing.

 There's a document in the Site 
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1 Research Database, it's 99708 and it describes 

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some of the contaminated ferrous iron scrap 

metal that was taken from Fernald in 1969 and 

then I believe processed offsite. It might be 

worth taking a look. I haven't looked at it 

in too much detail but I did want to point 

that out since there was a concern about the 

exposure specifically in 1969.

 CHAIRMAN CLAWSON: So you're 

saying that it was from scrap metal that they 

were doing?

 MR. ROLFES: Yes, correct. It was 

a subcontractor company. I looked at a couple 

of the bioassay results that SC&A had 

identified as being elevated and it looks like 

those individuals worked for the subcontractor 

I. Deutsch & Sons. And that company was 

involved in the processing of some ferrous 

scrap metal that was contaminated. It looks 

like they might have went in and got some of 

the contaminated process equipment and then 

taken it offsite to basically I guess 
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1 decontaminate and then sell the materials for 

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scrap value.

 CHAIRMAN CLAWSON: Well, with that 

kind of an uptake that would be interesting to 

watch in decon. But you know what that brings 

to my mind about that is I'd like to see what 

the people got that ripped that equipment out 

of there before this scrap company came in. 

 These are all issues that we need 

to get to and I appreciate you weighing in on 

that, Mark.

 MR. HINNEFELD: This is Stu. I 

just sent -- Mark had sent, as I see he sent 

me an email with that SRDB number and I have 

forwarded that to Brad, Mark and Paul and John 

Stiver. I don't have all the email addresses 

for your attendees, John.

 MR. STIVER: Okay, I'll go ahead 

and send it on to the rest of my crew.

 MR. HINNEFELD: I just read this 

over the phone.

 MR. ROLFES: Thank you.
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1 MR. STIVER: Thanks, Mark.

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 MR. BARTON: I think that still 

kind of begs the question if we can identify 

all of these such projects and then you could 

come up with a way to bound the dose for those 

specific projects, if we had all of them that 

would be good. 

 But that's not really addressed, 

you know, one size fits all coworker model 

because we're still applying doses from the 

entire worker population. So you have these 

workers who were exposed to these specific 

activities and you have some monitoring data. 

Maybe you don't have monitoring data for 

everyone who was involved in that activity so 

eventually you're going to be put in a 

situation where you have to apply some sort of 

uranium intake to these workers who maybe they 

were involved a short time doing this decon 

work. 

 Again, how representative is the 

proposed approach going to be for that kind of 
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1 situation? I mean if we had modified it, if 

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we knew every single such activity we could 

sort of I guess put it on a little extra for 

the subcontractors for those specific time 

periods. 

 But again, if you're just doing a 

chronic intake model and you come across an 

unmonitored worker who was involved in this 

you may not be applying a claimant-favorable 

intake based on the current method. I'm not 

saying you aren't. I mean maybe the 95th 

percentile actually does bound some of these 

activities but maybe it doesn't. I don't 

think that's actually been demonstrated yet.

 MR. STIVER: I think the 

uncertainties involved in trying to subsume 

the subs into the prime data is kind of a big 

issue which has been prompting this kind of 

second look at whether it's possible to 

actually build a separate model for these 

subcontractors. 

 CHAIRMAN CLAWSON: Well, that's 
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1 the question for the day. I think, you know, 

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we can beat this around all day long but where 

we're at is we've got to plan a path forward. 

We may not be able to do it by this time and 

we've got a few more items that we can go 

over. But before we leave today I would 

really if possible like to have a clear path 

forward and exactly what we can do on this.

 Looking at, and I'm -- I can just 

look at part of it, but boy, I'll tell you 

what. Looking at this construction worker 

information I think we're going to be very, 

very hard-pressed to be able to do anything 

there. But I've been proven wrong. But I 

guess my question is do we want to discuss 

what our options are and a path forward right 

now or do we want to take a little time and 

think about it, proceed with some of these 

other points.

 MR. STIVER: I would say we should 

probably get some actions out of this. Would 

it be possible to take about a 5-minute 
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1 comfort break here before we do?

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 CHAIRMAN CLAWSON: We're all at 

home, we've got mute. No, yes, I think we 

could.

 MR. STIVER: Okay, thanks.

 CHAIRMAN CLAWSON: Is that right, 

Ted?

 MR. KATZ: Yes, that's good. 

That's good. I was going to suggest the very 

same thing. So, I'm right in there with you, 

John.

 MR. STIVER: All right, thanks.

 CHAIRMAN CLAWSON: Okay. So we'll 

-- while we're on our comfort break let's be 

thinking of a path forward. So, okay. We'll 

come back in 5 minutes then.

 (Whereupon, the foregoing matter 

went off the record at 10:36 a.m. and went 

back on the record at 10:47 a.m.)

 MR. KATZ: So, reconvening after 

the break. Brad?

 CHAIRMAN CLAWSON: Yes. Okay, 
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1 sorry. Well, we're still -- I think that's 

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more that just joined us.

 So, I guess my question here is 

what do we need for a path forward on this. I 

guess I'd like to talk with Stu and John of 

what we need for a path forward to be able to 

come to a resolution on this.

 MR. HINNEFELD: I named four 

things that we needed to do. I think the 

fifth maybe that you're looking for that I 

didn't name might be essentially a description 

of the logic that leads us to the conclusion 

that -- there was comments made today about 

different types of exposures and how are you 

going to do this. The logic that leads us to 

the conclusion that the coworker model which 

is built from essentially the prime employees, 

the logic that leads us to the conclusion that 

that coworker model is sufficient bounding, 

will provide a sufficient bounding dose 

estimate for construction workers. So to me 

that would be the other item.
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1 CHAIRMAN CLAWSON: Right.

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 MR. HINNEFELD: And other than 

that I don't know of other items that have to 

be done. Now, as any of this stuff gets 

prepared we can certainly make it available 

for review by the Work Group and SC&A rather 

than wait till we meet again before anybody 

sees it. And there may be --

 MR. STIVER: I would certainly 

want to do it in parallel.

 MR. HINNEFELD: There would be 

some room for technical calls as they arise, 

if the need arises.

 CHAIRMAN CLAWSON: John or any of 

the SC&A group, is there anything else that 

you see at this time or feel that we would 

need more of?

 MR. STIVER: I think what Stu 

mentioned pretty well covers the suite of 

activities that we actually could perform.

 I would ask Joyce or Bob if 

there's anything else that they wanted to add.
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1 MR. BARTON: No, John. This is 

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Bob. I think we covered a lot of the bases. 

And just, you know, we've got to try to -- I 

mean I think maybe it's overblown that this 

coworker model, we're not saying right out 

it's not representative. I think what we're 

saying is there hasn't been an analytical 

approach adopted yet to try to get a handle on 

what the exposure potentials of subcontractors 

were. 

 And you know, in the latest 

revision, essentially what's being proposed is 

we're going to give the 95th percentile. But 

again, there's no real quantitative basis for 

that number. So I think that that's really 

what we need to try to get at if we're going 

to kind of solve this as an SC&A issue. 

 We need to say whether this 

coworker model can be applied in such a way 

that it's going to bound the exposures of 

subcontractors. And I think that's where 

we're at.
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1 MR. STIVER: Yes, I think all 

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these things are going to kind of get to that. 

I like that last item number 5 which was to 

really kind of identify the logical sequence 

that results in the assertion that that model 

really is in fact bounding. 

 But yes, that's really where we 

stand. We have a model. SC&A is -- I'm not 

saying that this model is not representative 

and acceptable. We have pointed out some of 

our concerns, some anecdotal examples where we 

can definitely say that at least in this 

particular case it's not. And so where do we 

go from there.

 CHAIRMAN CLAWSON: Now, one of the 

questions that I have is this coworker model 

that we're looking at right now is for the 

construction workers. What -- for the prime 

do we need to have a coworker model? Because 

I thought in the earlier years that this is --

that we did. Because I thought we had some 

people that were not monitored and also ended 
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1 up showing up with uranium in their --

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 MR. STIVER: Yes, Brad, I think I 

can speak to that. It was one of the first 

items that we addressed in these SEC 

deliberations was the -- actually there were 

two things. One of them was the completeness 

and adequacy of the HIS-20 database and the 

other was the TIB-78 as applied to the prime 

contractors. 

 CHAIRMAN CLAWSON: Right.

 MR. STIVER: And we determined 

that it was in fact adequate. Most of the 

people were in fact measured. I believe it 

was like 90-plus percent, there is a small 

pool of primes to which this coworker model 

would apply. But we had already made the 

determination that that was an acceptable 

model.

 CHAIRMAN CLAWSON: So we do have a 

coworker model for the prime though.

 MR. STIVER: The wrinkle there is 

that Rev 2 has a new approach to assessing the 
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1 doses, using the OPOS methods and new exposure 

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intervals. And so we are, recall that we are 

tasked to review that.

 CHAIRMAN CLAWSON: Right.

 MR. STIVER: We have -- actually 

the subs issue was kind of subsumed within 

that review.

 CHAIRMAN CLAWSON: This is where I 

get confused with the subcontractor and the 

prime on this. It was a little bit there. So 

I just, I want to make sure that we -- as SC&A 

that we don't, that you don't miss that one. 

I thought that we had agreed on it but I 

wanted to make sure.

 MR. STIVER: But this is a new 

revision so we have to do the due diligence of 

reviewing that particular document as well.

 CHAIRMAN CLAWSON: Okay. With 

that I guess I'll pass it back to you, John, 

and we'll proceed on.

 MR. STIVER: Okay. The next issue 

was 6b which was the use of the chest counts 
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1 to reconstruct thorium-232 exposures in the 

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1978 to 1988 time frame.

 And Bob Barton and Joyce did the 

yeoman's job in doing a very comprehensive 

completeness and adequacy assessment for that 

data set. And so Bob, if you don't mind I 

would kind of like you to give the 

presentation on your report and the main 

findings and kind of the highlights of what we 

found.

 MR. BARTON: Sure, John. And I 

think there's also a response from DCAS on the 

work that we haven't seen yet so I'll kind of 

just go through and say what we find. And 

DCAS, maybe they have some preliminary 

responses or something along those lines.

 The actual report that I'll be 

referring to is called "Completeness and 

Adequacy of Thorium In Vivo Records: 1979-

1989." Does everybody have that available to 

them? Because it would probably be helpful to 

kind of be able to look through the tables and 
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1 such as we're going through it. So does 

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anyone have a problem accessing that report? 

 CHAIRMAN CLAWSON: I'm just 

bringing it up now but you can go ahead and 

go.

 MR. BARTON: Okay. Sure, okay. 

As John said we're looking at thorium in vivo 

records in the 1979-1988 time frame. This is 

sort of the second time frame where we looked 

at looking at in vivo records to create a 

coworker model. 

 The reason we kind of split it up 

into the two is because in the prior period 

which was 1968-1978 the reporting convention 

was to report in milligrams of thorium. And 

in this later period which we're going to 

discuss right now they switched the reporting 

convention from milligrams of thorium to the 

thorium daughter products lead-212 and 

actinium-228 which is measured in nanocuries. 

So that's kind of the reason that was split 

up.
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1 Now, important to know about this 

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later period. Aside from 1979 it appears from 

multiple sources that much of the actual 

processing of thorium had ceased. There was 

definitely some processing in 1979. So most 

of the exposure potential in this later period 

was probably related to stewardship activities 

such as there was a problem onsite with drum 

deterioration. The bins that were holding 

them were often outside and those kind of 

deteriorated. So they often had to go in and 

repackage that thorium material. 

 We also, we did a pretty extensive 

search on the SRDB to see, just to really kind 

of characterize what sort of exposure 

potential there would have been to thorium at 

this time. And there are some indications 

that maybe there was some small-scale kind of 

one-off thorium processing campaigns after 

1979 that could be taken into account.

 I think a lot of what we looked at 

when we tried to kind of establish exposure 
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1 potential is to say, well, is there any. And 

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I believe Section 3 of the report kind of 

speaks to that. While we found some 

production orders for thorium after 1979 and 

certainly there were some concerns about the 

drums deteriorating so there was some 

repackaging going on throughout the nineteen 

eighties. 

 And I guess, you know, I don't 

want to get too specific into that because I 

don't think it's necessarily conducive to 

discussions today. But my takeaway from that 

is there is some exposure potential and so 

there's obviously a need for a coworker model 

that can bound the potential doses to workers. 

And I think that's kind of implicitly agreed 

upon since NIOSH and ORAU have put forth the 

coworker model so they are -- I think we're 

all in agreement that there is some thorium 

exposure potential. So I kind of put that 

section in just to kind of give the reader 

some clarification as to what was going on and 
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1 what we're really looking at.

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 One of the main aspects that I 

think everyone should keep in mind is that 

similar to the earlier period we evaluated you 

really can't identify which workers were 

involved in the re-drumming or any of these 

potential small-scale operations. 

 So I think one of our sort of 

overarching findings of this is just if you're 

going to implement a coworker model such as 

this to cover it and you don't know which 

workers, you know, in this data set which 

records are representative of those workers 

you just want to kind of assure that whenever 

you apply the coworker model that you're going 

to be bounding to this group of workers who 

handle thorium. You know, you don't really 

know necessarily what the results are. So 

when you apply a coworker model like this you 

just want to assure that the number you're 

assigning is going to cover that. So that's 

kind of one of our main findings there.
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 And kind of to start at the end 

and then I'll kind of work through the 

evidence. Bottom line from a completeness 

standpoint is we do not see any reason that 

this data set could not be used in such a 

manner as to bound doses to the potentially 

exposed claimants. And there's a couple of 

reasons for that which we can certainly get 

into now.

 I think as kind of an overarching 

finding when you look at the data set as a 

whole 95 percent of the monitored workers 

never had a result above the MDA for either of 

these daughters. So there's a whole lot of 

the data that we're using that is not an 

actual positive result. 

 This is kind of further emphasized 

by 98 percent never had a measurement for both 

daughters at the same time. So in other words 

95 percent of the population may have had a 

positive result for actinium and a less-thanMDA result for lead. And if you want to go, 
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1 well, who had positive results for both now 

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you're only down to less than 2 percent of the 

monitored population. 

 So the records are actually, you 

know, most of them are below the MDA which I 

guess doesn't really matter when you're 

looking at a coworker model because the data 

is uncensored so you're still going to take 

those less-than-MDA values and use them to 

kind of build your intake.

 Kind of moving onto the actual 

completeness analysis which is sort of my half 

of this and then I'll turn it over to Joyce to 

talk about adequacy. 

 We kind of looked at four main 

facets from a completeness standpoint. 

Temporal gaps. In other words, when we look 

at the data are there large sections that we 

don't have any measurements taken. We usually 

look on the order of years but I can tell you 

from going in I mean usually the gaps were on 

the order of more maybe 5 months at most. So 
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1 that's one facet, do we have data throughout 

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the period we're trying to cover.

 The second one is was there a 

potential bias to a job site. For example, if 

only the secretaries or very low-exposure 

potential jobs are the ones constantly being 

counted well then maybe you have a potential 

problem because you're just going to be 

missing all the actual workers who had 

exposure potential. 

 Along that same line we looked at 

it by plant area which is pretty convenient in 

these in vivo records because they do list in 

almost all cases what that person's job title 

was and what plant they were working in at the 

time of the measurement. So what we have is 

the temporal, job site, plant area.

 Then the last one we looked at is, 

all right, let's look at this 2 percent of the 

monitored worker population that had positive 

results. How frequently were they monitored? 

I mean, were they the same? Did they have a 
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1 positive result and then years later they were 

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finally measured again, or did it seem like 

there was a focus on those workers who had a 

positive measurement? Were they brought in 

more frequently for more counts? Which is 

obviously important when you're building a 

coworker model because if you're bringing in 

the more highly exposed workers more often 

then you're kind of biased already towards the 

higher exposures.

 So, I guess we can start with the 

temporal analysis which I think the best table 

to look at is Table 3. Let's see, it's on 

page 21 but I'm looking at the non-PA-cleared 

version. But it should be Table 3. And this 

kind of gives the number of samples by year.

 And as you can see, like the 

minimum was in 1988 when there were 180 

measurements taken. But I mean it's 

consistently above 100 and could get as high 

as four or five hundred there in the `86 to 

`87 period. So --
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1 CHAIRMAN CLAWSON: Hello?

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 MR. KATZ: Bob? I think we've 

lost you.

 MR. STIVER: Bob, we lose you 

there.

 MR. KATZ: He doesn't know that 

he's been lost. Does someone have another 

cell number they can reach him to let him know 

he's not talking to us?

 MR. STIVER: Let me try.

 MR. BARTON: I'm sorry, hello? 

Can anyone hear me?

 MR. KATZ: Yes, you're back. 

Okay. Whatever you said in the last minute or 

so, we haven't heard it.

 MR. BARTON: Oh, really. Okay. 

Where did I leave off?

 MR. KATZ: You were just going 

into Table 3.

 MR. BARTON: Okay, Table 3. So 

this kind of demonstrates the temporal 

analysis that we did. And you can see in that 
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1 second column we have the number of samples or 

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measurements taken by year. And as you can 

see from `79 to `88 the lowest was in 1988 

with still over 100 samples. And it could 

range up to four or five hundred samples. So 

we really didn't see any situation where there 

was a large temporal gap which would obviously 

beg the question what was going on at the site 

then. And in that case you'd sometimes look 

to see if you could use surrogate data from 

surrounding years. But in this case we really 

didn't have any issues from a temporal 

consideration standpoint.

 So, I mean if we keep scrolling 

down we did some magnitude analysis which I'm 

not sure really ties in from an SEC discussion 

here. But it was certainly informative if you 

kind of look at the exposure potential by 

year. As we can see sort of in the early 

years, I'm looking at Table 4 now which has 

the actinium results. 

 In the earlier years, `79, `80, 
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1 `81 you generally had a higher -- the 95th 

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percentile is actually above the minimum 

detectable activity. And of course 1979 you 

still had operations going on so that's not 

surprising. And we also had some indication 

that there may have been operations in 1980 

and maybe a few after that. So that might 

explain why you see a little bit higher 

results in the earlier years. 

 Also, it could be a result of the 

previous operational period where you had 

workers who were exposed there and they're 

still showing a lung burden from a longer 

solubility type.

 So, the next test that we did 

which is shown in Table 7 is we said okay, we 

don't have any real problems from a temporal 

standpoint. Let's take a look at the job 

titles and let's see who was monitored, how 

many samples for each worker do we have and 

what is the relative magnitude of those 

results. Because obviously as I said before 
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1 if your monitoring program was focused on job 

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types that really didn't have any exposure 

potential such as the office workers, well, 

there might be a problem here.

 And when we looked at it we really 

found just the opposite where 55 percent of 

the samples that we have were for chemical 

operators which is obviously a very 

encouraging sign. They're generally 

considered the highest exposed worker type.

 And if we look at that chemical 

operator group they also have the highest 

actinium and lead results compared to the 

other job types. So not only were you 

monitoring the highest exposed worker type 

that are included in there. They're also kind 

of biased towards that higher exposure 

potential which is obviously very encouraging, 

you know, from a coworker discussion. 

 Am I still on the line? I feel 

like I have to check every now and then.

 MR. KATZ: You're still there, 
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1 you're still there. Thanks.

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 MR. BARTON: Okay, good. Okay. 

So there are a couple of other -- the cells 

that are highlighted here are instances where 

that 95th percentile was above the minimum 

detectable activity. You know, there's a 

couple of maybe you'd call them aberrations. 

Like the health and safety group had some high 

lead results. And you know, maybe not as many 

samples. But that could also be a function of 

the fact that there weren't as many health and 

safety as there were some of these other job 

titles. 

 But I think the takeaway from that 

is as we looked at it you're focusing on the 

highest exposed job category which obviously 

is very encouraging to be able to build a 

coworker model that can effectively bound 

doses to these workers. So that's sort of 

what we looked at from a job standpoint which 

was kind of the second facet.

 The third one as I said before was 
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1 let's take a look by plant area. And this is 

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shown by plant area in Table 8. 

 And this kind of unfortunately did 

not give us a whole lot to go on. As you can 

see the number of samples, the highest 

proportion of samples was associated with 

other areas. And this doesn't mean we don't 

know what areas they were, it's just they 

didn't fit into these categories of specific 

plant numbers. 

 As I discussed before a lot of the 

exposure potential would likely have been redrumming activities and stewardship activities 

which a lot of the stuff was stored outside of 

buildings. And so you may not see that when

looking at the in vivo records that they would 

have focused on the pallet outside of Plant A 

where they were doing repackaging of drums or 

something like that. 

 So while we don't really see a 

trend either way I think this kind of just 

shows us that we're not focused on maybe any 
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1 one plant. But then again when we're talking 

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about thorium activities these workers are 

kind of pulled from different plants as 

needed. 

 So based on interviews and based 

on this fact we really didn't expect to find 

anything. But you know, we took a look at it 

anyway. You know, I don't think there's 

anything here that would indicate that this 

coworker model can't be used to bound doses in 

an SEC context. 

 And I think when you take this 

particular test along with the other tests 

such as the fact that they sampled the 

chemical operators more often and what we're 

going to get into next which is the frequency 

of sampling among positive workers, I think 

when you take the whole body of evidence I 

think it really bodes well for the usability 

of this data set from a completeness 

standpoint. 

 So that's kind of the third thing, 
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1 we looked at it by plant. Couldn't really see 

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anything but then didn't really expect to find 

anything earth-shattering there anyway.

 So the last thing we looked at was 

the frequency. So we looked at those workers 

who did have positive results and said all 

right, how much time between that positive 

result and the next time they were measured. 

You know, how does that compare with the rest 

of the monitored worker population? Were they 

sampled much quicker than the standard worker 

who had results below the MDA? Or were they 

the same? Or were they kind of ignored? So, 

I mean that's an important question. 

 And the results from that study 

are in Table 9. And what we see here is the 

number of days between a positive sample and 

the next sample you see. And there's three 

groups shown. There's everybody and then 

there's the group that had a positive sample. 

And then you had sort of the group that 

didn't have a positive sample. So the first 
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1 one you have everybody and then you kind of 

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parse it into those who have positive and 

those who didn't. 

 And I think what this -- this is 

kind of very telling is we see, I mean just 

looking at the arithmetic average if you had a 

positive sample on average you were sampled 

again within 3 months, 106 days. Whereas if 

you didn't have a positive sample you know 

it's over a year, you know, 480 days. 

 And if you go to the other 

methods, the geometric mean and the rankordered median it becomes even more pronounced 

where if you had a positive sample you were 

sampled again 10 times faster than those 

workers who had a measurement and they didn't 

have a positive result. 

 So again that's a very important 

piece of evidence because it pretty much 

indicates that if they saw that you had a 

positive result which would be indicative of 

exposure potential they're like all right, 
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1 we've got to count you again. So they're 

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actually focusing on the group that they were 

measuring that had higher results. So I 

thought that that was another piece of 

evidence that was just a very encouraging 

sign.

 So, to kind of summarize here, you 

don't see any issues from a temporal 

standpoint because we have a fair number of 

data points in each year that we looked at. I 

guess one important point here is this is from 

1979 to 1989 but we only had data up to 1988. 

And so a surrogate approach is going to have 

to be used to kind of bound 1989. That's why 

there's kind of a discrepancy there.

 When we looked at the job title 

the most -- over half the samples were for 

chemical operators which when you look at the 

magnitude of the results they also had the 

highest samples among the different job types 

so that's very encouraging. They were looking 

at the highly exposed job classification.
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1 We looked at the plant and can't 

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really pull a good conclusion there which we 

kind of expected. As I said at Fernald for 

thorium work they would kind of pull you from 

a plant as needed. So it wasn't like there 

was a specific plant where they would always 

pull thorium workers from. I mean it was 

really an as-needed basis. 

 And again, a lot of the exposure 

potential would likely be associated with 

stewardship activities which could be anywhere 

that thorium was stored and a lot of times 

that was outside so maybe they wouldn't assign 

you necessarily a specific plant number if 

that's kind of the work you were doing. And 

so that's a plant kind of analysis. 

 And then finally what's the focus 

as far as if you had a positive sample? How 

quickly did they bring you again. Looking at 

that, how they range anywhere from a factor of 

4 to a factor of 10 times faster if you had a 

positive result. 
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1 So I think taking all those things 

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together it's SC&A's belief that we don't see

any reason who you can't use this data set. 

And that the main caution I guess we would say 

is that since you can't identify which of 

these workers in the data set or otherwise 

worked with thorium that when you apply this 

coworker model even though it's biased towards 

those with higher results, biased towards 

higher job titles, you just want to kind of 

assure that when you assign an unmonitored 

dose and you don't know if they worked with 

thorium that you're going to bound the 

potential for that worker to have been exposed 

to thorium.

 So I guess that's where we come 

out on completeness. Does anyone have any 

questions before we kind of move onto 

adequacy? Am I still on the line?

 CHAIRMAN CLAWSON: Yes, this is 

Brad. I don't have any questions at this 

time.
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1 MS. BALDRIDGE: This is Sandra. I 

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do. Can you tell from the data results 

whether there is a significant transition in 

what one year reveals as compared to the 

other? Since this time frame prior to 1985 

was when National Lead of Ohio was under 

investigation for corrupted data and 

ultimately transitioned to Westinghouse 

somewhere `85 or beyond.

 MR. BARTON: Okay, I certainly 

understand the question. In this report I'm 

not sure if, Sandra, you have a copy of this 

to be able to look at. It is PA cleared so 

I'm sure we can get you a copy. But in Tables 

4 and 5 we did look at the magnitude of the 

results by year at the 95th percentile. We 

found that the highest results we observed 

were in the 1979 to 1981 period in general. 

 And that I'm kind of looking at 

the data and I don't see a specific sort of 

transition from when they went from NLO too 

Westinghouse. I can say during those years of 
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1 transition around 1985-1986 they had a spike 

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in the number of measurements that were taken 

but not necessarily -- I mean we haven't done 

a statistical analysis to see if there's a 

significant difference in magnitude. 

 But just looking at the results I 

don't -- it doesn't appear that they went from 

extremely low values to an extremely high 

value as if there was any falsification going 

on. But again, we haven't done a rigorous 

statistical analysis looking at that specific 

transitional period.

 MR. STIVER: Yes, Bob. Something 

else that I noticed is that 98 percent of the 

data, or 95 to 98 are below the MDA.

 MR. BARTON: Right.

 MR. STIVER: And the only time you 

really see many results above the MDA -- that 

earlier period when they're transitioning over 

from production to stewardship. So it appears 

that -- first of all, you wouldn't be able to 

determine from this data set that there was 
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1 any kind of a difference going from the NLO to 

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Westinghouse. Mainly more -- you're seeing 

some kind of residual effect from carryover 

for production. That's how I would interpret 

that.

 MR. BARTON: I think Ms. Baldridge 

was maybe asking if there was a significant 

jump.

 MR. STIVER: Yes, but there's 

really no way you could tell. Almost all that 

data is less than the detection limit at that 

point.

 MR. BARTON: Right, right. I'm 

sorry, Ms. Baldridge, does that sort of answer 

your question?

 MS. BALDRIDGE: That's fine, thank 

you.

 MR. STIVER: Is there any other 

questions on completeness?

 MEMBER ZIEMER: This is Ziemer. 

I'm back on the line. I don't have any 

further questions on it.
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1 MR. BARTON: I guess did DCAS or 

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ORAU have any initial comments they would like 

to make? Or we can just wait for their 

official response on this topic? Is there 

anything else out there?

 MR. HINNEFELD: I don't know what 

to say other than thank you. But I don't know 

of anything responsive.

 MR. BARTON: Okay. Well I guess 

if there's nothing more on completeness, 

Joyce, are you on the line to kind of talk 

about your work on the adequacy standpoint?

 DR. LIPSZTEIN: Okay. When I 

looked at the data the data is -- it's okay. 

We have data on lead and we have data on 

actinium. And my problem is not an SEC 

problem, it's more like something that will 

come after how I -- is NIOSH going to 

interpret the data.

 The problem is that NIOSH has 

proposed to use lead-212 results and discard 

the actinium-228 results. The problem is that 
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1 we have much more actinium-228 results that 

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are higher than the MDA than lead-212. And 

actinium-228 doesn't have any influence of 

radon on the measurements. 

 So, and when you measure actinium228 and you are able really to measure

actinium-228 in a worker it means that really 

there was exposures to thorium-232. So, I 

would just ask NIOSH to review. 

 It's not, again, it's not an SEC 

problem now, it's more like a TBD problem. 

But I think SC&A would like to ask NIOSH to 

review how they are going to interpret the 

results from measuring actinium-228 and lead212, interpret in terms of thorium exposure. 

 MR. HINNEFELD: Okay. Karin, is 

there someone on your team who's ready to 

speak to that?

 MS. JESSEN: Tom LaBone.

 MR. LABONE: Was the question how 

we were going to model this data? 

 MR. HINNEFELD: The question was
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1 how will we -- for dose reconstruction how 

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will we interpret an in vivo result where the 

lead-212 result is below the detection level 

but the actinium-228 is detectable.

 MR. LABONE: All the work that we 

have been doing modeling this is based upon 

the lead-212. To my knowledge we haven't 

looked at folding both of those, the actinium 

and the lead into the evaluation. So we have 

not looked at that.

 DR. LIPSZTEIN: So that's what we 

would like you to do. Because if you built a 

coworker model based on the lead-212 you are 

going to have much different results than if 

you looked at the actinium-228 and made 

claimant-favorable assumptions about actinium228. 

 MR. HINNEFELD: Okay. This is Stu 

and I did recognize that from your report. 

And we are working with the contractor to get 

to that. I had a conversation with Matt McFee 

about it yesterday. So that, we know that 
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1 that is a question we need an answer to.

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 MR. STIVER: Stu, this is John. 

Do you have any idea, like a time frame for 

that?

 MR. HINNEFELD: I don't. This is 

wrapped up into also how do we -- what 

separation history are we going to assume for 

these dose assessments. Because remember the 

separation history for thorium is going to say 

how much, you know, what's the difference 

between the lead-212 that's there and the 

thorium-232 that's there. 

 So in combination with that it 

would seem to me that there's an answer here 

that falls out of that approach, that with a 

particular interpretation of separation 

history that there should be a way to deal 

with this. Either that -- and I really hate 

to speculate any further here because I 

haven't -- we haven't gone through it. But 

it's tied to that.

 You know, clearly we don't have an 
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1 expectation that the chain is going to be in 

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equilibrium. There's going to be some sort of 

disequilibrium depending upon its separation 

history. The separation history in all 

likelihood is going to be unknown. In fact, I 

can almost -- with certainty the in vivo 

results of separation history of material that 

was taken is going to be unknown. 

 And so we have to make some 

appropriate assumptions about the separation 

history and therefore those various ratios in 

order to do a bounding dose assessment. And 

it could be that -- and so this question of 

how you deal with actinium that is detectable 

and lead that is not is also related to that, 

that various ratio question. So I think it's 

going to come out of that.

 I don't have a time frame, but I 

don't really envision it taking a whole lot of 

time I hope.

 MR. STIVER: I was kind of under 

the impression that NIOSH was going to go with 
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1 a bounding triple separation assumption.

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 MR. HINNEFELD: Yes, I think

that's where we are is that we're expecting 

that. And so that puts your lead-212 at 

somewhere just like 20 percent of the thorium.

 MR. STIVER: Yes, I think it's 

like 19 percent or something. 

 MR. HINNEFELD: And there's some

other value of actinium-228 that goes in 

there. And so it's an evaluation of that and 

what adjustments, if any, are needed.

 It would seem to me, I'm pretty 

sure the actinium at that point is somewhere 

between the lead and the thorium-232. 

 And it may come down to a 

magnitude of difference between actinium and 

lead-212. And if it's less than sub-magnitude 

you do nothing because it fits with your 

assumption separation. 

 So I don't know. I think it's 

going to come down to an analysis of those.

 MR. LABONE: This is Tom. Can I 
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1 make another clarification? I interpreted 

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Joyce's question to mean when we're going to 

evaluate the lead-212 I think it has a lot of 

advantages versus the actinium. 

 The question was what are you 

going to do when basically you're getting some 

positive hits for actinium but with no lead. 

And so what I would respond is that we have 

not to my knowledge, I mean we know how to 

handle lead. We proposed that -- the 

methodology. But we haven't built into that 

to check to see does the actinium make sense. 

So that's what I was answering.

 Everything Stu said was right, 

it's just I think I interpreted the question 

differently. When you have this disagreement 

are you going to check for it and what are you 

going to do about it. That's the thing we 

haven't done yet.

 MR. STIVER: Tom, this is John. I 

had stepped out for a couple of minutes, and I 

had missed that little part of the discussion. 
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1 Thanks for clarifying.

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 MR. LABONE: Want me to repeat it?

 MR. STIVER: No, thank you for 

clarifying that point.

 MR. LABONE: Okay.

 DR. LIPSZTEIN: Because when you

have actinium counts, if you can really see 

actinium then it means the person was exposed 

to thorium. And actinium doesn't, you know, 

it's not affected by the number of separations 

that you do. So if you are going to use the 

actinium data then the bounding assumption has 

to be different than the bounding assumptions 

for lead-212. 

 MR. LABONE: If you see actinium -

- 

 DR. LIPSZTEIN: And between the 

thorium and the lead you have radon in the 

middle. So --

 MR. LABONE: If you see actinium 

all you really know is that they were exposed 

to radium.
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1 DR. LIPSZTEIN: Yes.

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 MR. LABONE: Yes, okay. And 

whereas if you see the lead then you know they 

were exposed to thorium-228. 

 DR. LIPSZTEIN: Yes, but some of 

it could be only radon.

 MR. LABONE: Yes. That's why I 

think that the lead is a more reliable 

indicator of the actual thorium there as 

opposed to were they just exposed to radium228 which is --

 DR. LIPSZTEIN: I don't know. I 

don't know if there was the separation and you 

just had thorium then actinium can be linked 

to thorium. When we measure people that are 

exposed to thorium we measure actinium. So, 

and in general it's very difficult to get 

positive counts for actinium if you have -- if 

you possibly have an exposure. 

 But you know, it's not an SEC 

problem now. But I think it's a problem for 

interpretation of results, what to do with 
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1 these results.

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 MR. HINNEFELD: This is Stu. I 

think that might be all we can say about this 

at this point, right?

 DR. LIPSZTEIN: Yes.

 MR. HINNEFELD: I don't know if 

you have other points to make on your in vivo 

report.

 DR. LIPSZTEIN: No, that's it.

 CHAIRMAN CLAWSON: So, John, this 

will be -- that part of it will be marked as a 

TBD issue. 

 MR. STIVER: Yes. It's just a 

matter of kind of DCAS coming back with an 

explanation or response and their best 

estimate as to why they're seeing what they're 

seeing.

 CHAIRMAN CLAWSON: The one 

question I had was using this information, you 

know, that said that they'll be able to do it. 

I guess the one question I had was kind of 

like, well, so who are they going to use this 
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1 on. Are they going to use this as site-wide 

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or because I don't think they can really 

separate even though there is good chemical 

operator. My question is how are they going 

to implement this to the site. Is it going to 

be the whole site or how are they going to do 

this dose reconstruction. 

 MR. HINNEFELD: I'm not sure if we 

specified that yet. Certainly if we haven't 

yet we will.

 CHAIRMAN CLAWSON: Well, and this 

is the one question that I had on it is how 

are we going to implement this. So I guess 

this would be a question for you guys, if 

you're going to try to separate it out to 

people which I think personally that you'd 

have a problem with. Or is this going to go 

site-wide?

 MR. STIVER: Brad, maybe I can 

step in. This is John Stiver. The original 

thorium model, they had planned to assign I 

believe the geometric mean to those with data. 
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1 I think the problem that we have 

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identified in all these thorium discussions is 

that you just, as Bob has pointed out, we 

really are -- because you don't have the 

granularity in the data to determine who was 

working with thorium at a given plant in a 

given year. It becomes, it kind of devolves 

to a situation where you really need to have 

kind of a bounding one size fits all model 

that in my mind would apply to everybody 

during that period, everybody in the plant.

 CHAIRMAN CLAWSON: Yes, and I 

understand that, John. I just wanted to make 

sure that with NIOSH and ORAU that that is how 

we were looking at it is that it was going to 

be for the whole plant or not. I guess that's 

what I wanted to make sure of.

 DR. LIPSZTEIN: May I? Excuse me. 

I was thinking of what Tom said is right. 

There is a problem. If they find out that the 

actinium measurement is not, you know, is not 

matching the lead-212 and there is no 
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1 explanation then and we don't know if we can 

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trust this data. So I think that Tom's 

interpretation is very great.

 In order to determine if this is 

an SEC issue or not you have to see if the 

actinium-228 measurement results make sense 

with the lead-212. 

 MR. STIVER: Yes, I think you've 

got two issues, the possibility of a radium228 exposure and the absence of thorium-232. 

And then also the idea of translocation due to 

the radon migration out of the lungs. It 

could result in a lower lead-212 in 

comparison.

 DR. LIPSZTEIN: Yes. So that's 

what Tom said he was going to look at, right?

 MR. HINNEFELD: Well, this is Stu. 

I'm not aware of any potential for a radium228 exposure at Fernald. 

 MR. STIVER: In the absence of 

thorium.

 MR. HINNEFELD: In the absence of 
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1 thorium, right.

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 MR. STIVER: The only thing that 

came to my mind would be some raffinate 

workers that might have had exposure without 

the thorium. That would seem kind of 

farfetched in comparison to the translocation 

model. But anyway, I guess that's in your 

court then to work on that particular issue.

 CHAIRMAN CLAWSON: So help me 

clarify what Joyce just said. Is this still 

an SEC issue?

 MR. STIVER: I would say that it's 

predominantly Site Profile. There is this 

idea that how do you explain the actinium in 

the absence of lead. And I guess that's what 

NIOSH is looking into at this point.

 CHAIRMAN CLAWSON: Okay. And so 

that'll just be an action item for them of how 

they're --

 MR. STIVER: Right.

 CHAIRMAN CLAWSON: -- they're 

going to do that. How it's interpreted. 
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1 But also on the other hand too 

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part of it is how they're going to disperse 

this as far as who will be using this.

 MR. STIVER: Sorry to interrupt 

you.

 CHAIRMAN CLAWSON: No, just my 

question of so how are they -- who's going to 

receive this? How are they going to disperse 

it. That was one question that I brought up 

earlier and I believe Stu was going to get 

back with this of how we were going to 

implement this data. 

 MR. HINNEFELD: Yes.

 CHAIRMAN CLAWSON: And who it was 

going to go to.

 MR. HINNEFELD: Yes.

 MR. STIVER: Any more comments or 

questions on in vivo thorium? Am I still on?

 MR. KATZ: It sounds like you can 

go on, John, to Issue 6a.

 MR. STIVER: All right, Issue 6a. 

This relates to the coworker model for 
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1 thorium for the period 1953 to 1967 using 

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daily weighted exposure alpha air 

concentration data. 

 This is an issue that has been 

active for about 5 years. In fact, when I 

first came to SC&A this was my first 

assignment was to respond to NIOSH's 2009 

paper, their coworker model which was Revision 

2 where they developed a construct for DWE to 

be used in kind of a general sense for any 

kind of alpha-emitting airborne concentration 

in the absence of urine bioassay monitoring 

data. 

 So what we'd like to do since this 

has been such a long process to get to where 

we are today I'd kind of like to just set the 

stage just briefly without going into too much 

detail of how we got here and what the big 

issues were.

 Now, if you'll recall back in July 

of 2009 SC&A produced a White Paper response 

to I believe a -- document Morris 2009 which 
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1 is Revision 2 of the coworker model. 

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 And in that particular White Paper 

we identified about 20 different findings. 

And those were discussed in detail at the 

January 2010 meeting. And probably not until 

November of 2010 that NIOSH put forth Revision 

3. 

 Now, Revision 2, basically those 

20 findings are distilled down to two big 

issues. And these were first the construct 

that NIOSH had developed to assess a bounding 

dose in Revision 2 was to take DWEs for a 

given plant in a given year, fit them to a 

probability plot, do a log normal fit and then 

pick off different proportions of that 

distribution as if you were looking at urine 

bioassay data or unweighted air sampling data, 

and then assign whatever you thought. The 

95th percentiles were the most highly exposed 

workers and so forth. 

 And the problem you had with that 

was it seemed to be a conflation of unweighted 
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1 air sampling data and DWEs. You've got to 

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remember what a DWE really is. A daily 

weighted exposure is a weighted average 

concentration experienced by a worker in a job 

category on the day that that sample is taken. 

The point being it's an average value for a 

category of workers. It doesn't represent an 

upper -- you can't plot all these on a line 

and then pick off a 95th percentile. Anybody 

who's above that 95th percentile, that 

assignment is no longer or is not a bounding 

dose. In fact, way low because each of those 

values represents an average for a particular 

category.

 Combined with that there was no 

estimate of uncertainty applied in the HASL 

reports which drive these data. So you have 

these two big issues. You've got the approach 

or the basic construct, the basic concept was 

flawed. And then on top of that there was the 

issue of uncertainty and granularity in the 

data.
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1 Now, back in 2010, in November of 

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2010 in relation to the Weldon Springs 

activities that were going on, it was kind of 

similar with the DWE problem. NIOSH indicated 

that well, we've got a new approach. There's 

this report by Davis and Strom of PNNL in 2008 

that really looked at this notion of how are 

we going to address uncertainty in DWEs. 

 And what they did was they took 

DWE data from about six facilities, processed 

uranium, thorium and also looked at radon in 

the late forties and early fifties. And they 

did a couple of different approaches where 

they went through and did Monte Carlo sampling 

of all the different air concentrations for 

each task and propagating to drive an 

uncertainty distribution. 

 And at the end of the day they 

determined that a GSD of 5 was probably 

adequate for most situations. I believe they 

ranged, the GSDs ranged from about on average 

I think about 4 to about 7 to 8. And so they 
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1 recommended this GSD of 5.

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 And also in a situation where you 

didn't know where a worker was, you didn't 

have that type of worker placement data that 

assigning the 95th percent DWE or the highest 

DWE in a particular facility for that year 

with this uncertainty estimate would be 

adequately bounding. And that's in essence 

what NIOSH did in Revision 3.

 We looked at that. We thought 

well, we think that conceptually this is 

acceptable from a scientific standpoint.

 What we were not 100 percent sure 

on was how well this could be implemented. 

Did NIOSH indeed have the data that would 

allow them to place workers in a particular

plant in a particular year so that they could 

go in and say, okay, this guy was in Plant 9 

in 1955. We're going to give him the highest 

DWE which is 685 MAP for that particular year 

in the plant.

 And so Bob Barton set out to take 
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1 a look at this idea like we did with the in 

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vivo data. Let's look at data completeness.

 And he did a very thorough job as 

he always does. And produced a report that we 

delivered back in October which is entitled 

"Feasibility of Identifying Workers in 

Specific Plants and Areas of Fernald for 

Identification with Thorium Operations in 

1953-1967." And I believe you've all seen 

that report.

 And so before Bob gets into that I 

would just like to say the two biggest 

important aspects of this. In terms of the 

latest model which is Revision 4 that NIOSH 

just delivered to us last Friday is that it 

appears that they have gone and abandoned the 

Revision 3 approach which we thought was 

scientifically acceptable using the highest 

DWE for the facility, giving it to everybody, 

a one size fits all model where you know not 

everybody was in that most highly exposed 

group but you have data that indicate that 
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1 some workers were with the GSD of 5. So those 

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two issues.

 They appear to have gone back to 

the Revision 2 approach where what they did, 

they determined because Bob found that there 

was -- I'm going to steal a lot of your 

thunder here, Bob -- found that there wasn't 

enough worker placement data to really 

implement it as they had by plant and year.

 NIOSH went back. They picked out 

all the DWEs per year. But they used the old 

Revision 2 approach that fit into a log normal 

in taking percentages off as though they were 

working with air sampling data and not DWE. 

So they kind of brought us full circle back 

around.

 But Bob, if you can kind of give a 

little more detail on what you found with the 

feasibility study. 

 MR. BARTON: Sure, John. As John 

said we kind of looked at how feasible is it 

to implement this type of approach. Were you 
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1 able to identify claimant-specific plants by 

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year? Because that's kind of the criteria you 

need to implement what was proposed in 

Revision 3. 

 So what we did is we took two 

different approaches. First, we did a 

claimant sampling. We then go into claimant 

files because this is obviously who you'd be 

applying this model to and we selected 20 

semi-randomly selected claimants. 

 When I say semi-randomly basically 

what I mean is, one, we wanted to get 

claimants that actually were working in the 

period of interest. We wanted to get 

claimants who had maybe the higher-risk job 

titles because again those are the workers 

you're really worried about. 

 And the third thing was there was 

a memo in 1967 by [identifying information 

redacted] which identified by name and by 

badge number thorium workers. So I kind of 

biased it towards that. I wanted to pull a 
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1 few of those workers, look in their claim 

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files and see well, can we tell where these 

workers were as they were at the plant. What 

plant were they and what year as you would 

kind of need to implement the Rev 3 approach.

 And looking through these claimant 

files there's a number of different sources 

that do give some information on work 

location. And in this report we're looking at 

they're listed on page, let's see, what are we 

on here. Bottom of page 7, Section 4.1. And 

there's kind of a list of bullets there.

 You see that some uranium 

urinalysis reports would give the plant 

number. If there was a film badge 

investigation that would often give the work 

location similar to radiation exposure 

investigation which is kind of similar to the 

film badge investigations. It's a different 

form but it still will provide information on 

work location.

 You had personal clothing and 
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1 monitoring reports, health and safety 

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information reports. And then sometimes they

would note work location on a periodic 

physical exam.

 And then all of those first six 

sources, they all come from the DOE files used 

that have all the bioassay data and monitoring 

data. 

 We also did look through the 

Department of Labor files. They were far less 

informative and generally if there was any 

information it would just be mirrored in what 

was already in the DOE files.

 The last source there is the 

computer-assisted telephone interview, 

otherwise known as the CATI report. And 

employment records. And there's a reason that 

I put employment records on the same line as 

the computer-assisted telephone interview. We 

only saw 1 of the 20 claimants who had a full 

employment record. And by that I mean we 

actually could tell where he was pretty much 
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1 with a good degree of accuracy throughout his 

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employment. 

 The reason I put that with the 

CATI report is that information was supplied 

by the claimant. They actually had their 

employment records on hand and they supplied 

that information to NIOSH as part of their 

claim. I did not see any examples of that in 

just files gotten from DOL or DOE. So I kind 

of wanted to make that delineation. I don't 

know how feasible it is to get that type of 

employment record for all of the workers but 

that is certainly not available at this time 

for 19 of the 20 claimants we looked at.

 So I think the real sort of meat 

and potatoes here is if you scroll down to 

Table 1. And this kind of describes the list 

of 20 claimants that we looked at. And for 

example, the very first one, the job title is 

redacted but they were employed from 1953 to 

1963. And the only source of information we 

had on location was some of the urinalysis 
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1 results. And it was only four of the samples 

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which was roughly 17 percent and only for the 

years 1956 to 1957. So there's a large 

portion of that worker's employment that you 

just don't know where they were working.

 And in that case the CATI report 

and the claim application which is part of the 

Department of Labor files, they specify an 

area but don't give a date of when they worked 

in that area. And as we know at Fernald they 

could move around quite a bit.

 I think something else to remember 

when you're looking at information supplied by 

the CATI report, oftentimes they don't give 

specific dates on what plant they worked in 

and when. Oftentimes the CATI report is not 

available. And oftentimes the CATI report is 

conducted by the survivor who may not have 

specific information on where the claimant had 

worked. So there's always that caveat when 

you look at CATI interviews for the 

information. 
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1 The prime source you'd really want 

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to have for implementing such a model would be 

in the information supplied by DOE and DOL. 

 So as you kind of go through this 

table you can kind of see that many of these 

workers just don't have a lot of locationspecific information in their files. You 

might have a few samples. I mean if we look 

at the second one you had six film badge 

investigations. 

 It's important to note that those 

only cover a week of exposure. So those six 

reports, we may know where they were that week 

but the rest of the year we really don't know. 

They had, again, 17 samples of urinalysis but 

they had about 100 that didn't have any 

location specified. So again there's really a 

paucity of information out there to try to 

piece to where these workers were located. 

And that's really the main conclusion from the 

claimant sampling we did.

 But we didn't stop there. We kind 
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1 of wanted to take also a more macroscopic 

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view. As you look at Table 1 you see a lot of 

the information we were able to find about 

work location was in the urinalysis results. 

 So what we did is we then said 

okay, let's look plant-wide. Let's look into 

the HIS-20 database. Let's pull out all the 

urinalysis results and let's see how many 

actually specify the work location. 

 And when we did that and that 

review was done in Section 4.2 and is kind of 

represented in Table 2 which is on page 14. 

We see that really the urinalysis results only 

really report location for 1955 through 1957 

and sparingly before and one year after that. 

And you know, there were a few in 1961 but 

all the other years urinalysis results don't 

actually report the work location. 

 I mean 1955 to 1957 you have 

roughly 60 to 70 percent of the urinalysis 

results do report a work location but the rest 

of the years you really don't have anything. 
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1 So I guess to kind of wrap this up 

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we looked at the 20 claimants and the 

information regarding where they worked was 

pretty sparse. And even when we looked at 

sort of the macroscopic big picture view, the 

HIS-20 database, again we came up with a 

similar conclusion that maybe aside from these 

years `55 to `57 there's just not really data 

out there to characterize and place workers 

into specific plants as you would sort of need 

to implement the Revision 3 strategy as it was 

outlined. 

 So I guess that's where we stand 

from the feasibility for Rev 3 and that sort 

of predicated Rev 4. Does anyone have any 

questions on this particular study? Am I 

still on the line?

 MR. HINNEFELD: You're still on,

Bob.

 CHAIRMAN CLAWSON: We're listening 

to you.

 MR. BARTON: Okay. Well I mean 
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1 that's pretty much. Just to wrap it up we did 

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two separate approaches. One was a claimant 

sampling where we did try to focus on those 

workers who were employed during the period of 

interest who had likely high exposure 

potential. 

 And also took it the next step and 

said well, we have a list of people we know 

worked with thorium at least around in the 

late sixties as the memo came out in 1967. 

Let's look at those workers specifically 

because they did work with thorium. And again 

we just couldn't place them, where they might 

have worked with it and when.

 MR. STIVER: Thanks a lot, Bob. 

If there's no other questions I just wanted to 

make a couple of more statements before I ask 

Stu to talk a little bit more about Rev 4. 

 But as I said we've got some 

pretty serious concerns about reverting back 

to the Rev 2 conceptual approach. And I 

believe if that is indeed the approach that 
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1 you're going to be taking, that NIOSH is going 

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to take that we have some real problems with 

it. It basically sets us back about 3 and a 

half years in terms of where we were in this 

particular issue that we thought was resolved 

as of November 2010 for all intents and 

purposes.

 MR. HINNEFELD: Yes, this is Stu. 

I'm confused by that. You say that -- help 

me out with what's the Rev 2 approach. The 

Rev 3 approach versus.

 MR. STIVER: Rev 3 was basically a 

one size fits all model with a level of 

granularity that would allow a researcher to 

identify a worker by building and by year. 

And once that was established then the highest 

DWE for that year and building combination 

would then be applied to everybody. Basically 

it's going to apply it to everybody in that

particular year and building. So anybody who 

fell into that category would get that DWE. 

 Because Bob was able to 
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1 demonstrate that he didn't have that level of 

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granularity in the data, that you couldn't 

identify somebody by a particular plant in a 

given year because people were moving among 

the plants as they were needed.

 And so what the Rev 4 model does 

is it takes all the DWEs for a given year 

across all plants and then does this log 

normal fit, then picks off percentiles of the 

log normal distribution to assign DWE 

exposures for various categories of workers. 

Essentially what Revision 2 did. 

 And we don't believe that that is 

a scientifically defensible approach because 

the DWEs actually represent average exposures 

as measured on that day for those workers who 

were actually involved in the study. But 

they're averages for a particular category of 

worker. And so there's a whole range of 

uncertainty associated with each of those 

DWEs. 

 So you can take the person who's 
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1 got the highest DWE for a year and that is 

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just an average for that subgroup. And then 

Davis and Strom provides the statistical 

analysis for DWEs in general that allow an 

uncertainty estimate to be placed on that DWE. 

 But you can't -- take a 95th 

percentile of the plots of all the DWEs for a 

year, you're going to have a certain number 

who are above that 95th percentile and those 

people are going to be way underestimated. It 

will not be a claimant-favorable assignment. 

You have to look at the highest DWE for a 

given year. That's the only way that I would 

see that that would be feasible. 

 But the approach that's outlined 

in Revision 4 essentially goes back to the 

Revision 2 conceptual model.

 MR. HINNEFELD: Okay. This is 

Stu. The change you're describing is foreign

to me. I don't recall seeing that. Can 

somebody from the ORAU team help me out here?

 MS. JESSEN: Yes. This is Karin. 
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1 We would actually like to have a written 

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response to this because I'm not able to 

respond to this today.

 MR. HINNEFELD: Now, John what 

you're referring to is Rev 4?

 MR. STIVER: Revision 4 is the 

response that Mark Rolfes sent out a week ago 

on March 1 after our teleconference call. And 

it's a completely different model than what we 

had accepted in Revision 3 back in 2010.

 MR. HINNEFELD: Is the title of 

this document "Fernald Thorium Worker Location 

Issue Response to SC&A White Paper, Rev 1, 

February 21, 2013?"

 MR. STIVER: Yes, that's it. It's 

"Fernald Thorium Worker Location Issues." 

Yes, that's the one right there.

 I didn't really want to go into a 

detailed analysis of this right now but just 

to present some of the kind of conceptual 

issues that kind of jumped out at me right 

away as soon as I looked at this.
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1 MR. HINNEFELD: Is this the one 

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that has -- okay, I'm sorry I'm being dense 

here.

 Table 2 which has geometric mean 

standard deviation 95th percentiles calculated 

from log normal fit. And Table 3 which has a 

GSD 95th percentile doing a minimum GSD of 5. 

 And then so what you're saying is 

that the intake values were derived from level 

2 rather than level 3?

 MR. STIVER: Well, you might take 

a look, just a more illustrative example of 

what I'm talking about here. If you go down 

to page 13 there's a log normal -- actually, 

let's take a look at on page 14 for 1955. 

There's a log normal fit to DWE for that year. 

 And you can see there's the DWEs 

are represented by these blue diamonds and 

then the log fit is the red line here. And 

you can -- your typical construct that you 

might use to fit air concentration data, 

unweighted air data or urine bioassay data. 
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1 What I'm telling you, if you take 

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a look at that plot there's a cluster in the 

high end. And those are DWEs that would not 

be -- those workers for which those DWEs apply 

would not be given a claimant-favorable 

bounding dose. If anything it would be 

exceedingly low given that those DWEs, each 

one of those blue diamonds represents an 

average value for a particular category of 

worker. 

 So if you look at the very highest 

one there's probably, I don't know, it could 

be somebody working in the metal production 

doing the really dirty jobs. And so they have 

essentially the highest DWE for that year 

basically in the whole -- across all plants 

for that year.

 And our contention that we 

accepted in the Revision 3 methodology was 

that, okay, you're going to take that highest 

value. It's a classic one size fits all 

model. You know not everybody was involved in 
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1 that work but you know that some were. And so 

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that is a plausible upper bound for that most 

highly exposed group. And because you don't 

have information on who was doing what at any 

given time it has to be applied across the 

site. It has to be applied to everybody. 

 And this particular construct 

takes us back to Revision 2. They did the 

exact same type of thing only instead of 

looking at the entire complex by year they had 

it broken down by year and plant and then 

tried to pick off by worker type. It's the 

exact same conceptual construct. 

 And most of the problems, all the 

findings that we had in our initial report 3 

and a half years ago was in relation to this 

construct.

 MR. HINNEFELD: Okay, I've got it 

now.

 MR. STIVER: Okay. 

 MR. HINNEFELD: Okay. So this 

seems relatively understandable then that what 
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you referred to, our Revision 3, what document 

title is this described in? What's the 

document title or date or something so I can 

make sure? 

 MR. STIVER: This is -- we call it 

Morris 2010. I can pull this up for you here. 

Let me find it. Just a minute. I'll go back 

in my files here. Okay, I'm having a hard 

time pulling it up here.

 MR. HINNEFELD: You guys call it 

Morris 2010 and you referenced it in your 

report. 

 MR. STIVER: Right.

 MR. HINNEFELD: I think you did.

 MR. STIVER: I'm trying to find 

that exact one that I could send to you.

 MR. HINNEFELD: Okay, I've got it. 

It's in your report. It's a reference in 

your report. October 2010, okay. 

 MEMBER ZIEMER: All right, this is 

Ziemer. Is this the one referenced in the 

second bullet on the first page of your 
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1 report? "White Paper on Use of FMPC DWE 

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Reports for Estimation of Chronic Daily Intake 

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 MR. HINNEFELD: That sounds like 

it, Paul. That's how it's described in the 

references section.

 MR. BARTON: I think -- I don't 

know if we're still looking for the Rev 3 to 

get it up. I mean, we do pull one quote in 

the location study that I just described from 

the Morris 2010. It says, "Due to variation 

situation job assignments it is unlikely that 

unambiguous exposure scenarios can be defined 

for most workers. In addition, dust emissions 

have not been quantified except as a general 

air sampler indicator. 

 "To ensure thorium intake 

potential is not underestimated the DWE value 

associated job title or job description with 

the highest DWE value in an FMPC plant where 

thorium was handled for a specific year should 

be assigned to every worker in that facility. 
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1 A GSD of 5 should be assumed." That is from 

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Morris 2010.

 And I guess where we came out with 

it is we agree with that in principle but then 

when we really looked into it you probably 

can't identify workers with a specific plant. 

So you can't say well, he was in Plant 5 so 

we'll give him the highest DWE because he 

could have been in Plant 6 or Plant 8. That's 

kind of I guess the only outstanding thing we 

found with the Revision 3 methodology is that 

we agreed that if you're going to give the 

highest DWE value in each plant and year with 

a GSD of 5 that sounds good to us. But then 

if you can't identify that worker with the 

specific plant now you kind of run into the 

issue of how you implement that model.

 MR. HINNEFELD: I got it.

 MR. STIVER: Yes, so you basically 

lose one degree of freedom. In your log you 

no longer can identify by particular plant 

within a year. But instead of keeping with 
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1 the Rev 3 approach the new Rev 4 approach goes 

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back to the old approach of doing log fits and 

assigning percentile. 

 MR. HINNEFELD: Okay.

 MR. STIVER: It's a lot to absorb 

considering that it's been 3 years since we 

really delved into this in any detail at all.

 MR. HINNEFELD: Okay. I think the 

issue's clear. I don't think that we 

necessarily need a written response. I think 

the issue's clear from the conversation and we 

should see what we can come up with on that.

 MR. STIVER: Okay. 

 CHAIRMAN CLAWSON: Well, this is 

another one of those stepping backwards again. 

I thought the reason we had brought it up 3 

years ago was because we'd already brought 

this information up. And now all of a sudden 

we're stepping back again. We're losing a 

little bit of ground now.

 MR. STIVER: Yes. I was kind of 

surprised when I saw that because I really 
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1 thought that we had had that sewn up. I would 

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suppose there would be other ways to deal with 

the inability to assign by plant other than to 

completely abandon the approach. 

 CHAIRMAN CLAWSON: Well if there 

is we need to --

 MR. STIVER: We need to have some 

--

 CHAIRMAN CLAWSON: Clarification. 

 MR. STIVER: Yes. So I guess for 

a path forward. I realize everybody's still 

trying to absorb this. But Brad, would you 

want us to do a formal response to that? Then 

have NIOSH go ahead and maybe provide some 

more.

 CHAIRMAN CLAWSON: I'm going to be 

honest here. I've already spoken that I'm a 

little bit frustrated. I don't know what good 

it would do you because we've already brought 

up these issues 3 years ago. And that's why 

we went --

 MR. STIVER: If we did a report it 
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1 would basically -- the gist of it would be 

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what I just presented here.

 CHAIRMAN CLAWSON: Right. And so, 

you know, if NIOSH would like us to give a 

formal report I guess we can. I just don't 

see what the good of it would be because we've 

already been through this once before in 

detail.

 Now, if they have something new 

which I didn't see anything new in it in how 

their approach was or how they could justify 

that they could do it that's a different 

thing. So I guess this has come down to Stu 

of what would you like us to be able to do.

 If you want us to formally do it 

again that would be fine. I think it's a 

waste of resources my personal self.

 MR. HINNEFELD: Just so I'm clear, 

is this issue the only issue with the document 

we sent? The Rev 1 February 1, 2013 document.

 MR. STIVER: Yes. It is the 

issue, yes. It's really the conceptual 
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1 paragraph is just in our view is not 

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scientifically valid.

 MR. HINNEFELD: I'm just, I'm 

thinking just expediently here if this is the 

issue then -- I mean the only issue. I don't 

mean the big one, I mean the only issue then 

we have enough information to try to see if we 

can respond to this, to your concern. 

 MR. STIVER: Any other issues 

would kind of be subsumed within this one.

 MR. HINNEFELD: If there are other 

issues within - 

 (Simultaneous speaking.)

 MR. STIVER: -- 100 percent, every 

technical detail, but if we were to do a 

report certainly we might find some other 

issues as we did more in-depth research. But 

at first pass given the first order of 

approximation, this is the big one.

 MR. HINNEFELD: Okay. I'm just, 

you know, if this is the only issue then I 

think we don't need a report from SC&A. It's 
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1 pretty clear what it is.

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 There has been in addition --

there is a description in this paper. I want 

to make sure. There's one issue in here that 

I just described that hadn't been described 

before. I want to make sure we're okay with 

that. 

 I'm looking at the bottom of page 

6 on our report "Fernald Thorium Worker 

Location Issue Response to SC&A White Paper 

Rev 1 February 21, 2013." Bottom of page 6. 

Yes, starting at the last paragraph on page 6. 

We describe the apportionment of this alpha 

certainly, the various thorium alpha-emitting 

-- the various alpha-emitting radionuclides. 

 And in the choice of a triple 

separated for certain -- actually triple 

separated when it's favorable and a 50/50 

split between the thorium-232 and thorium-228 

when it's more -- when that is more 

beneficial. 

 MR. STIVER: Yes, this is 
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1 something -- this is another change. It 

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hadn't addressed disequilibrium in the 

previous report.

 MR. HINNEFELD: Right. Well, I 

don't expect you guys to analyze it on the 

phone but in the meantime if there is some 

issue with this we would need to be -- I'd 

like to be notified about that rather than 

have us go do something and then come back and 

then start dealing with other issues. Because 

I'm with Brad here, let's get to the end of 

the ball game.

 MR. STIVER: Yes, absolutely. I 

think that we can kind of do this in parallel 

through emails and technical calls. I would 

certainly want to have my crew take a look at 

some of the implications of the other aspects 

aside from the fundamental construct.

 CHAIRMAN CLAWSON: And we need you 

to look at that. But it would be under my 

impression -- this is Brad again -- that the 

separation that you're talking about, it would 
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1 also depend on how you're going to -- how 

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you're going to implement into the program. 

That's -- because me and you talked about this 

the other day on this. It all stems back to 

that on how you're going to implement it. 

But.

 MR. STIVER: The implementation 

aspect kind of gets back to the fundamental 

construct. You know, if it's going to be a 

one size fits all model this is what we agreed 

that would be appropriate under Revision 3. 

And all the other aspects of implementation 

that are laid out here in Revision 4 stem from 

that fundamental difference. 

 CHAIRMAN CLAWSON: Now, John, my

question to you and we didn't touch on this 

the other day but can you take a look at what 

they're proposing for this without having how 

they're going to implement it? I guess, you 

know, this is kind of a little bit of a 

different approach. 

 MR. STIVER: Well, that's really
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1 the big issue that we just laid out is -- the 

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way they would lay out an implementation based 

on the fundamental construct is to assign this 

95th percentile that would fit which is not 

claimant-favorable to the most highly exposed 

group. So that's a showstopper right there.

 CHAIRMAN CLAWSON: Right. Well, 

you know, Stu was just bringing up how --

 MR. STIVER: Are there aspects 

that might be related? Like I say --

 CHAIRMAN CLAWSON: Yes, this 

triple separation or whatever. This is 

something new.

 MR. STIVER: Yes, I think this is 

a disequilibrium issue that really came up in 

our discussions of the in vivo thorium. And 

so at first pass I don't really have any 

problem with that. They're just trying to 

address, you know, once you get an intake what 

kind of assumptions are you going to make to 

give the most claimant-favorable dose under a

particular circumstance. So that's really 
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1 what that gets down to. It's respiratory or 

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non-respiratory cancer. How would you then 

give the highest dose and that's really what 

that comes down to. So in principle I don't 

have any problem with that.

 CHAIRMAN CLAWSON: Okay. Well, I 

just -- I wanted to make sure. I'm like Stu, 

I just want to make sure that if we get how 

this is going to be implemented that we -- and 

this was the only other real change that we 

saw to this, this Rev 4, right?

 MR. STIVER: Yes. Yes. That is 

the big change.

 CHAIRMAN CLAWSON: Okay. 

 MR. BARTON: John, I think what 

you're saying is after you get an intake then, 

you know, all these, the triple separation, 

all that sort of stuff comes into play. But 

we're kind of still stuck on how you get to 

that intake.

 MR. STIVER: Getting to the intake 

is the big issue. Once you're there how you 
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1 do claimant-favorable assumptions to yield the 

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highest dose for a particular claimant is a 

separate issue altogether.

 MEMBER ZIEMER: This is Ziemer and 

I think that part of it would not be an SEC 

issue if you got to that point. Yes. So the 

first question is the more critical one at 

this point.

 MR. STIVER: Yes, that's our view 

exactly. 

 CHAIRMAN CLAWSON: So I know we're 

not going to be able to solve this here so I 

guess this is another action item for NIOSH. 

 MR. KATZ: And I think that brings 

us to the end of the agenda. Is that right? 

Is there anything else left to talk about?

 MR. STIVER: That's really it. I 

would just say that going forward we've had a 

lot of issues that have kind of been 

transferred over to the Site Profile bin. 

They're kind of being held until all the SEC 

issues are decided.
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1 I would say that it might help us 

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to kind of re-baseline an issues matrix going 

forward for the Site Profile side of things. 

And kind of in parallel with resolving this 

last aspect of the SEC. 

 And getting an idea of when we'd 

want to meet again. Obviously before the next 

Board meeting in July. But I guess, yes, that 

would be something we might want to talk 

about.

 MR. KATZ: Yes. I mean I think, 

John, the one issue with updating the TBD 

issues is that until you know how some of 

these play out you don't know what your full 

plate is there.

 MR. STIVER: We can get the 80 

percent solution though. I can at least --

 MR. KATZ: Yes. I'm just not sure 

what we're going to do with that in advance of 

solving these questions. 

 CHAIRMAN CLAWSON: Right. Well,

part of this, Ted, is my request. I didn't 
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1 want to lose sight of some of it. I'd talked 

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to John earlier about losing sight with some 

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 We only have -- we have two or 

three that are in this pile that could be 

there. I was just kind of asking John to make 

sure that we didn't lose sight of some of 

these other ones. Some of these depending on 

--

 MR. KATZ: I understand, Brad. 

I'm just saying that I'm not sure it makes

sense to put out a new version of the TBD 

issues matrix until the dispositioning of 

these SEC matters. Because they'll impact 

that.

 CHAIRMAN CLAWSON: Right.

 MR. KATZ: That's all.

 CHAIRMAN CLAWSON: They will. I 

just -- I'm going to be honest. It's been a 

long time and we've lost a lot into it. And I 

was just asking John if he could kind of catch 

that up for me to make sure where we were at 
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1 on some of them. So that's why he was 

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bringing that up.

 I guess my whole thing was just to 

make sure that when we get -- when we do get 

these solved that it won't be a long period to 

be able to bring that matrix up to speed of 

where we were at.

 MR. KATZ: Right.

 MR. STIVER: I think once we have 

a good solid handle on what all the Site 

Profile issues are it would be pretty 

straightforward to put them all into some sort 

of an order.

 MR. KATZ: Right. That sounds 

good.

 CHAIRMAN CLAWSON: Well, also the 

same too if just everybody remembers right. 

We've been through one, two, three people --

and this was my issue -- on SC&A's side. You 

know, John is the latest one. And I just 

wanted to make sure that we had --

 MR. KATZ: So John's going to 
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1 stick with it till the end.

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 MR. STIVER: That's an optimistic 

outlook.

 CHAIRMAN CLAWSON: That's what I 

thought about John 1 and Hans but doggone it, 

they let me down, you know. So now we're at 

John 2 here.

 MR. KATZ: I have faith in John 2.

 CHAIRMAN CLAWSON: Okay.

 MR. KATZ: Okay. So Brad, are you 

ready to adjourn or is there something else?

 CHAIRMAN CLAWSON: Well, actually 

I wanted to make sure that we went over the 

items that we have and make sure that we are 

all on the path forward. I know that SC&A had 

some and I know that Stu had some. 

 And I just want to make sure that 

-- or do you guys need a little bit of time to 

write these up and want to send them out to 

us? I just want to make sure we are going in 

the direction that we all have figured that 
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1 we're going.

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 MR. KATZ: Why don't we just do 

that? Why don't we just get a little piece of 

paper like we normally do back and forth with 

the action items, just very brief summarize 

them.

 MR. STIVER: Yes, that seems to 

work pretty well.

 CHAIRMAN CLAWSON: Okay. That 

would be good. Would that be all right with 

you, Stu?

 MR. HINNEFELD: Yes.

 CHAIRMAN CLAWSON: Okay. Well, 

with that being said this brings us to the 

close of the Fernald Work Group. I guess with 

Sandra on here I was just wondering if she had 

anything. I know there's not really a public 

comment but if she had anything that she 

wanted to say.

 MS. BALDRIDGE: I do. I'd like to 

thank the Group for their efforts today and 

for trying to save the past 3 and a half years 
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1 of work. I really appreciate it.

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 MR. KATZ: Thank you, Sandra. 

Okay, and we are adjourned.

 CHAIRMAN CLAWSON: Okay. Thanks, 

everybody, for their help. We'll chat at you 

later.

 (Whereupon, the above-entitled 

matter went off the record at 12:15 p.m.)

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