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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 

+ + + + +

SPECIAL EXPOSURE COHORT ISSUES

WORK GROUP

+ + + + +

MONDAY

JUNE 24, 2013

+ + + + +

The Work Group met telephonically 

at 1:00 p.m. Eastern Daylight Time, Jim 

Melius, Chairman, presiding.

PRESENT:

JAMES M. MELIUS, Chairman

JOSIE M. BEACH, Member

GENEVIEVE S. ROESSLER, Member

PAUL L. ZIEMER, Member
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ALSO PRESENT:

TED KATZ, Designated Federal Official

TERRIE BARRIE, ANWAG

STU HINNEFELD, NIOSH ORAU

JOSH KINMAN, NIOSH ORAU

ARJUN MAKHIJANI, SC&A

JOHN MAURO, SC&A

MARTHA McNEELY

JIM NETON, NIOSH ORAU

MICHAEL RAFKY, HHS

JOHN STIVER, SC&A
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A G E N D A

WELCOME AND ROLL CALL...................... 4

WG DISCUSSION:

DCAS draft outline of possible criteria

and guidelines for evaluating sufficient

accuracy................................... 5

Next Steps/July Board Session............. 63

ADJOURN................................... 71
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1 P R O C E E D I N G S

2 (1:02 p.m.)

3 MR. KATZ: So, let's get started 

4 with roll call. We're not speaking about a 

5 specific site so there's no conflict of 

6 interest admissions needed here. Let's just 

7 begin with -- well, I just heard the Board 

8 Chair, Dr. Melius. Let's go through the Board 

9 Members and then we'll go from there.

10 (Roll Call.)

11 MR. KATZ: Okay, very good. We have 

12 an agenda for the meeting. It's posted on the 

13 NIOSH Board page on the web under today's date 

14 for meetings. And there should also be a paper 

15 from DCAS posted there, I believe. LaVon can 

16 let me know if that's not the case. And, Jim, 

17 it's your agenda.

18 CHAIR MELIUS: Okay. Thanks, Ted. 

19 I'm glad you could make it today. And hello to 

20 Josie, Gen and Paul. 

21 And our agenda is, I think, pretty 
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1 straightforward today and I want to talk 

2 about, essentially, two things. One is to talk 

3 about the draft outline that's been prepared 

4 by NIOSH on sufficient accuracy in follow-up 

5 to our last conference call. And then, 

6 secondly, talk a little bit about -- we'll 

7 follow-up on this, and also discussions at our 

8 July Board meeting.

9 So, I thought we would start. If, 

10 I don't know, Stu or Jim, who wants to talk? 

11 But if you want to present a little bit on 

12 your -- on the outline, sort of what you --

13 MR. HINNEFELD: I think Jim will 

14 probably lead the discussion for us.

15 CHAIR MELIUS: Okay, great.

16 DR. NETON: I can get the ball 

17 rolling, I guess. This is Jim.

18 Just as a follow-up to the 

February 22nd 19 meeting that Special Exposure 

20 Cohort Work Group had where NIOSH had 

21 originally prepared a couple of papers that 
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1 you remember in January for the February 

2 meeting, and they were a review of the 

3 parameters associated with sufficient 

4 accuracy.

5 The approach that we took actually 

6 ended up reviewing, if you remember, sort of 

7 the case law that had been developed over the 

8 last year's worth of decisions on SECs to see 

9 if we could glean any particular criteria, or 

10 develop any guidance from those decisions. 

11 And, as it turned out, we really couldn't. 

12 There wasn't anything specific that popped 

13 out. Even when we looked at the thorium data 

14 that we thought might be more informative, 

15 there was nothing there, either.

16 And what came out of it was that 

17 the hierarchy of data for dose reconstructions 

18 seemed to have been used in the development of 

19 the decisions all along the way, and that's 

20 where we ended up.

At the February 22nd 21 meeting, the 
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1 Working Group, and NIOSH agreed, thought that 

2 it would be good that we might sort of 

3 summarize those salient points in a brief 

4 outline, a several-page outline to put down 

5 our thoughts on paper as to what we were 

6 thinking on this. And that's what was issued 

7 in May by LaVon.

8 And, essentially, what it has is a 

9 summary of the requirements, and then goes to 

10 the hierarchy; although, we did add some 

11 preliminary steps in evaluating the criteria, 

12 and one is this issue that was discussed at 

13 the last meeting, which was to determine the 

14 potential for exposure variability. One-size15 fits-all models I think we have come to agree 

16 are not necessarily appropriate, and we need 

17 to take care to determine if there's any 

18 underlying variability or stratification in 

19 the models.

20 And the other piece that was added 

21 as a result of the Working Group discussion 
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1 was the concept that variability in itself, a 

2 larger amount of variability or variance in 

3 the model could be tolerated given that the --

4 if the exposures were very low. In other 

5 words, the lower the exposure maybe the 

6 greater the variability that could be 

7 tolerated. When you have very high exposures, 

8 a large amount of variability wouldn't be 

9 appropriate.

10 So, those two pieces were added 

11 into the discussion to the general concept of 

12 reviewing the -- using the hierarchical 

13 approach to evaluating the data.

14 That's about what I can say. If 

15 there's any questions, I guess I can answer 

16 them. 

17 CHAIR MELIUS: Jim, it might be 

18 helpful if you use just one part of the 

19 hierarchy to sort of illustrate where you're 

20 going. I think it would be useful.

21 DR. NETON: Okay. The way that we 
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1 sort of envision the hierarchy, and this 

2 seemed to come out when we looked at the cases 

3 that we evaluated, is that the hierarchy 

4 that's included in the regulations included, 

5 you know, sort of a stratified approach. One 

6 is, you look at personal monitoring data and 

7 determine if the maximum-exposed workers were 

8 monitored. And, actually, either maximum or 

9 representative, I think, workers were 

10 monitored. And those methods, even if they 

11 were monitored, we had to determine if the 

12 monitoring methods allowed for the exposure of 

13 interest to be correctly identified. In other 

14 words, they had -- the uranium bioassay had to 

15 be appropriate; it could detect uranium if 

16 that was the exposure potential.

17 And we couldn't -- and we 

18 determined in that analysis that we also 

19 couldn't use data that would result in what we 

20 call implausibly high, and I think we might 

21 want to discuss that a little bit today; come 
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1 up with implausibly high determinations. That 

2 would be, for example, substituting thorium --

3 assuming that a gross alpha analysis for 

4 uranium could bound a thorium exposure, and 

5 result in very high intake values.

6 And then in the personal 

7 monitoring data you end up, finally, if you 

8 don't -- you know, you have to develop a 

9 coworker model. And, again, in the coworker 

10 modeling situation one needs to account for 

11 potential stratification we put into this 

12 document. And the example that was talked 

13 about at the last Working Group meeting was 

14 the case at Linde where we had construction 

15 monitoring data, decontamination data for 

16 workers that we felt bounded the overall 

17 exposures. Yet, there was another offset of 

18 the population that worked in offices where, 

19 certainly, it should have bounded their 

20 exposures, but really wasn't sufficiently 

21 accurate because it was a different set of --
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1 a different population of workers that were 

2 being exposed.

3 That kind of covers what we do for 

4 personnel monitoring. I don't know if you want 

5 me to go through the remainder or --

6 CHAIR MELIUS: No, no. Jim, that's 

7 fine. I just wanted to sort of tie it into the 

8 stratification issues, and sort of accuracy 

9 issues, and so forth.

10 Do any Board Members have comments 

11 or questions?

12 MEMBER ZIEMER: This is Ziemer. I 

13 have several questions. Is this the 

14 appropriate time to raise them?

15 CHAIR MELIUS: Yes, it is.

16 MEMBER ZIEMER: Okay. First of all, 

17 under the third item, Preliminary Steps, under 

18 B.2 where we had the statement, determine if

19 there's any potential for exposure variability 

20 within the exposed populations, that --

21 obviously, there's always potential for 
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1 variability. In fact, not just potential, 

2 there's virtually always variability. 

3 It seems to me that we need to 

4 develop that statement a little more to 

5 delineate or explain what the concept of 

6 potential for exposure variability really 

7 means in this case. I mean, I think I know the 

8 answer to it, but I think for someone just 

9 reading it, it needs to be developed a little 

10 more.

11 DR. NETON: I agree with you, Dr. 

12 Ziemer. I mean, it definitely needs to be 

13 fleshed out a little better. I think it 

14 demonstrates that we're still a little cloudy 

15 in our thinking on this.

16 MEMBER ZIEMER: Yes. Well, that was 

17 really just a comment. Then I have another 

18 question.

19 I was trying to remember -- you 

20 have the statement under 4.A under personnel 

21 monitoring data, you have the statements about 
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1 the coworker data and the stratification of 

2 exposures. 

3 There's a lot of beeps on the 

4 line. Is this my line, or is some -- are we 

5 hearing beeps?

6 CHAIR MELIUS: I'm also hearing 

7 beeps, Paul.

8 MEMBER ZIEMER: Okay.

9 CHAIR MELIUS: I think it's the --

10 MEMBER ZIEMER: Okay, I'll just 

11 proceed.

12 In any event, my question --

13 Do we have -- I can still hear it.

14 MR. KATZ: Right. Paul, I guess 

15 hold on a second. This is really getting to be 

16 difficult to listen to. Somebody is probably 

17 inadvertently mashing a button on their phone, 

18 so just everyone be aware of that. Maybe it's 

19 a cell phone and it's harder to know when 

20 you're doing that or not. 

21 MEMBER ZIEMER: Okay?
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1 MR. KATZ: Okay, Paul, why don't we 

2 try again.

3 MEMBER ZIEMER: Okay. So, I was 

4 trying to remember -- Jim, if you can -- Jim 

5 or Stu, do we have any coworker models that 

6 have been based not on personnel monitoring 

7 but on either air monitoring or source term 

8 data? You know, air monitoring of the highly 

9 exposed group, and then a coworker model 

10 developed for others who may have had other -

11 DR. NETON: I think we do have in 

12 the source term -- in the source term data, 

13 the only one that comes to mind is we 

14 developed some source term models for radon 

15 exposure. In the air monitoring data, I've not 

16 been familiar with what's been going on at 

17 Fernald, but I do understand that some daily 

18 weighted averages were being used for 

19 exposures to thorium. 

20 MEMBER ZIEMER: Yes. Well, what I 

21 was looking for here was a sort of parallel 
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1 statement about coworker models similar to --

2 or along the lines of what you have for 

3 personnel monitoring data. Are there some 

4 statements about coworker models for air 

5 monitoring data or for source term data that 

6 would require sort of a parallel statement to 

7 4.A.3?

8 DR. NETON: I understand what 

9 you're saying, and I agree with you. This is 

10 kind of -- the way this reads, it's definitely 

11 limited to bioassay, but there have been 

12 instances where we've used other models. Good 

13 point.

14 MEMBER ZIEMER: Just wondering if 

15 there would be a parallel statement or maybe 

16 any special conditions for both models under 

17 those other circumstances. That's really the 

18 question I had on those. And based on -- and 

19 maybe you need to just go back and look at 

20 what we have, and if there's anything special 

21 about what we did in those cases. I just 
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1 couldn't remember.

2 CHAIR MELIUS: Yes, that's a good 

3 point, Paul. And I was sort of thinking along 

4 the same lines, but maybe somewhat in the 

5 other direction, is that in most instances 

6 when we're relying on air monitoring or source 

7 term, we don't really have enough monitoring 

8 data, and it's not sort of dense enough to be 

9 able to even detect whether there's 

10 stratification, or differences among different 

11 people doing different tasks and so forth. 

12 It's certainly hard. It tends to be something 

13 we're falling back on that data. I think the 

14 Fernald case is an exception to that. But as 

15 we're getting into that part of the hierarchy, 

16 it -- we don't have the information, usually.

17 I don't know if that's a strength 

18 or a weakness. It means we avoid sort of 

19 having to deal with some of these issues with 

20 coworker models, but at the same time, it may 

21 be that we're ignoring a significant amount of 
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1 stratification or differences among the 

2 people doing different tasks, or with 

3 different job titles within a building, or 

4 within a -- even within the whole plant.

5 But I think they are -- I think 

6 you're right, we need to sort of think about 

7 it from -- as an overall issue, and not just 

8 something confined to personal monitoring.

9 MEMBER ZIEMER: Yes. Well, 

10 whichever way it goes -- I mean, what you just 

11 said may be exactly the answer to it. I think 

12 we just need to know.

13 CHAIR MELIUS: Yes.

14 DR. NETON: Yes. I have -- we have 

15 a concern internally, at least I do, regarding 

16 the stratification issue; and that is, at what 

17 point -- at some point you have to have almost 

18 a basis for why the data would be stratified 

19 before you start analyzing, because otherwise 

20 you can do a tremendous variety of different 

21 tests and come up with stratification that may 
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1 or may not be meaningful. But you have to 

2 almost have some underlying rationale as to 

3 why we believe this particular data set could 

4 have some stratification in it.

5 MEMBER ZIEMER: We sort of have 

6 that case, you know, at GSI where we're 

7 relying on source term data, and we're 

8 stratifying to some degree between 

9 radiographers and layout people and 

10 administrative people.

11 DR. NETON: That is true.

12 CHAIR MELIUS: Yes.

13 MEMBER ZIEMER: Those are sort of 

14 the main questions I had on the document.

15 CHAIR MELIUS: Gen or Josie?

16 MEMBER ROESSLER: Am I off mute?

17 CHAIR MELIUS: Yes, you are.

18 MEMBER ROESSLER: This is Gen. I 

19 don't have any real question, but I think when 

20 we get to the final document the thing I'm 

21 looking for the most backup on is the 
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1 discussion. And it comes up quite a bit in the 

2 outline about what happens when we have 

3 unrealistically high estimates, or implausibly 

4 high. That's something that's always just sort 

5 of been hanging there, is just where do we go 

6 from that? So, I think that really needs to be 

7 identified in the document.

8 CHAIR MELIUS: And how do we, you 

9 know, sort of evaluate that they are 

10 implausibly high? And then who are we 

11 referring to? Are we referring -- you know, is 

12 it -- are they implausibly high for the 

13 highest exposed worker or for all workers?

14 MEMBER ROESSLER: Yes, defining the 

15 population.

16 CHAIR MELIUS: Who are we comparing 

17 it -- yes, who are we saying it's implausible 

18 for, because there may be -- it may be 

19 plausible for the highest exposed worker, and 

20 totally implausible for the lower exposed 

21 worker.
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1 DR. NETON: Yes, I hear what we're 

2 saying there. It sort of puts us in an 

3 interesting situation, though, where if you 

4 say you can plausibly bound the highest 

5 exposed workers but not a subset of that, then 

6 you're sort of saying, well, I will make an 

7 SEC for a lower exposed worker class, but then 

8 it's always been difficult for us to put 

9 people in positions and places in the factory 

10 or plant. So, then you end up making a class 

11 for all workers, even though there is a subset 

12 that one might agree that you could plausibly 

13 bound their exposures. It's kind of --

14 CHAIR MELIUS: Yes, you can err on 

15 either side that way. I mean, I agree, it's a 

16 conundrum in terms of how we -- partly because 

17 we're limited by what data we have. And often, 

18 the lower exposed workers, or what we think 

19 are the potentially lower exposed workers 

20 aren't monitored, or certainly not as --

21 monitored as often and as completely as the 
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1 higher exposed -- at least potentially higher 

2 exposed workers.

3 So, then it's -- yes, I think 

4 sometimes we've dealt with it by saying well, 

5 there aren't that many of those people. I 

6 mean, sort of the discussion we were having 

7 with the -- on the Fernald Work Group call 

8 last week, talked about the coworker model 

9 there.

10 Well, if you're going to do 

11 subcontractors, who are they? Are they the 

12 construction workers, are they the plant 

13 physicians or, you know, other -- you know, 

14 delivery people, whatever. I mean, there's a 

15 range there, and how do we -- you know, how do 

16 we find the right way of describing who we're 

17 trying to, you know, do dose reconstruction 

18 for, evaluate, or put in a Class; and, yet, 

19 make it practical in terms of implementation.

20 I'll raise sort of a similar 

21 issue, but this is more in relation to the 
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1 coworker models, because I've been reading 

2 some of the reports on that. And I'm not sure 

3 if everybody else has. I know, Paul, you have, 

4 because it's come up before the Procedures, 

5 and Josie, perhaps. I don't remember when this 

6 came up.

7 But it's -- in looking at sort of 

8 ORAU and SC&A, going sort of back and forth on 

9 coworker models and doing some of the --

10 suggesting some of the kinds of statistical 

11 testing that might be done on that, it sort of 

12 struck me that we're -- there are a lot of 

13 difficulties in reaching a conclusion on that, 

14 because we really don't have a criteria for 

15 sufficient accuracy that's quantitative at 

16 all.

17 You know, we look at sort of an 

18 upper limit, an upper bound, but we don't go -

19 - really go beyond that, specifically. And, 

20 therefore, the statistical testing, I think, 

21 has limitations, and you can argue -- you can 
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1 have examples that would go both ways because 

2 if you're testing on the variance of 

3 something, a lot of that depends on the sample 

4 size more than it does on the actual numbers 

5 involved, so you can have a very high variance 

6 for a low -- relatively low exposure 

7 quantitatively, you can have the opposite of 

8 that for what's a very high exposure; yet, I 

9 think the higher exposures are the ones where 

10 they're more likely to affect dose 

11 reconstruction.

12 And I think until we think about 

13 how we're going to deal with, you know, 

14 realistically what's a -- what levels of 

15 exposure or what doses, you know, are we 

16 really interested in. And we've already dealt 

17 with that in some ways, for example, with what 

18 we refer to as environmental dose, or for, you 

19 know, residual contamination on a site where 

20 we, basically, take a fairly simple approach 

21 to that because we believe that those 
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1 exposures are quite low; and, therefore, how 

2 much variability we have in them, you know, 

3 doesn't matter. And we don't usually have a 

4 great deal of data, anyway, and we don't take 

5 those into account and so NIOSH has this in 

6 this outline. We talked about it at our last 

7 meeting. But I think what when we're trying to 

8 judge coworker models, and if we're going to 

9 assess coworker, or evaluate coworker models 

10 based on some sort of statistical testing of 

11 those, I think it's going to be very hard 

12 unless we come up with some more specific 

13 criteria in the area of what -- sort of what 

14 level of exposure are we going to worry about, 

15 and try to take into account.

16 It's hard, we've never defined a 

17 number for endangerment, health endangerment. 

18 We've always looked at it from sort of the 

19 sufficient accuracy. And there we don't really 

20 have a quantitative approach defined on 

21 sufficient accuracy, so I think we're -- I 
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1 think dealing with the application of this is 

2 going to get hard unless we come up with, I 

3 think, some sort of guidelines or guidance on 

4 what levels of exposure are we going to be 

5 concerned about taking into account in 

6 coworker models, or any other approach to 

7 dealing with sufficient accuracy.

8 MEMBER ROESSLER: Jim, you just 

9 brought up a whole new ball game, it seems 

10 like, and I'm wondering if when we talk about 

11 defining the level of endangerment, and I'm 

12 not sure if you're really suggesting that that 

13 be done, it almost seems like that's a 

14 scientific issues committee assignment.

15 CHAIR MELIUS: It could be. I mean, 

16 if you remember way back when, we as a Board 

17 talked about trying to define endangerment and 

18 decided not to, basically. Partly because it 

19 was, you know, controversial and difficult, 

20 and partly because we thought it -- we weren't 

21 necessarily sure that it needed to be done. 
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1 And I'm not saying it needs to still be done. 

2 I'm not sure we want to take that on through 

3 the Board. I'm not sure that NIOSH wants to 

4 take on that assignment either.

5 But I think we -- at the same 

6 time, there -- I think -- and we may find 

7 ourselves that we have to have some practical 

8 ways of approaching that in terms of how we 

9 deal with this issue, because we're -- the 

10 issue of sufficient accuracy, because I think, 

11 you know, that -- sufficient accuracy sort of 

12 begs for some sort of numerical criteria.

13 MEMBER ZIEMER: This is Ziemer 

14 again. Let me throw out some comments or ideas 

15 on that.

16 I think we also in a way would 

17 feel comfortable if we had a number that we 

18 could peg things on, and then say okay, we met 

19 this number criteria. I have a feeling that in 

20 a sense this could differ in every case, or at 

21 every site in the following ways. 
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1 First of all, let's take the low2 dose end of the thing where you have a 

3 particular component of the dose 

4 reconstruction that is a very small fraction 

5 of the total. We know sort of intuitively that 

6 you can tolerate a lot of variance there, and 

7 it has very little effect on the Probability 

8 of Causation. 

9 You could be within a factor of 10 

10 and still have very little effect. And we 

11 recognized that before, and we talked in the 

12 outline about, at the low dose end of things, 

13 that you can tolerate a lot of variance 

14 without having a big effect on the final 

15 outcome.

16 But what that number would be, it 

17 seems to me, could be different in every case. 

18 And it seems to me what we might want to think 

19 about was just having some criteria where for 

20 a particular situation we ask that the 

21 sufficient accuracy be demonstrated according 
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1 to some sort of rules, rather than according 

2 to a particular number.

3 It's sort of like what we do with 

4 the situation where we're looking for the --

5 one particular site to represent another in 

6 the surrogate data case. You have to look at 

7 each one specifically following some 

8 guidelines, and then make your judgment.

9 Maybe we could have guidelines on 

10 what sufficient accuracy looks like, both at 

11 the lower and at the high end without coming 

12 up with a particular number. At the high end, 

13 obviously, you don't want to have a factor of 

14 10, let's say, on your estimate and say well, 

15 it's between this and that, and one end of 

16 that is below the PoC, and the other end is 

17 above it. So, you're looking at a much tighter 

18 sort of variability in the final outcome. 

19 But I'm just wondering if we can 

20 think in terms of having a guideline, and then 

21 in each case it would -- the burden would be 
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1 to say here's what we've got, and here's why 

2 we think it is of sufficient accuracy.

3 CHAIR MELIUS: No, I don't disagree 

4 with that, Paul, but I think it's -- the high 

5 end and the low end are probably easier than 

6 the middle. 

7 MEMBER ZIEMER: That's always the 

8 case, isn't it?

9 CHAIR MELIUS: Yes, where's the 

10 cut-off. And, certainly, it's going to be 

11 individual, because it's going to depend on 

12 the site, and what the exposures are, and are 

13 there -- what materials are involved, what are 

14 the sources, what are the -- how are people 

15 exposed, and so forth. So, you know, it's not 

16 going to be by, you know, radionuclide or 

17 something like that. It's going to be, you 

18 know, really depend on the exposure situation.

19 And, somehow, I think it comes 

20 back to what extent that exposure -- that type 

21 of exposure in that particular site and, you 
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1 know, what we are assuming about the 

2 variability or non-variability of that 

3 exposure. To what extent will that affect the 

4 -- you know, a person's dose reconstruction?

5 It's going to affect it, you know, 

6 say 10 or 20 percent in terms of Probability 

7 of Causation. And then, obviously, that's, you 

8 know, a significant difference. If it's going 

9 to be a very, very small amount, you know, .01 

10 percent or less, or whatever, then I think 

11 we'd have, you know, less concern about that, 

12 and do that. 

13 So, I think that's the -- and it's 

14 sort of finding that the middle ground --

15 where do we get in the middle? And I think it 

16 is on a case-by-case basis, so I think it will 

17 be on guidelines, because I actually don't 

18 think we often have the numbers, or want to 

19 put NIOSH or whoever through all the work it 

20 might take to do these estimates. It could get 

21 quite complicated, I think, and beyond what is 
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1 necessary. So, it would be a general set of 

2 guidelines just to identify certain instances, 

3 but I don't think we can ignore it, because I 

4 don't think we'll -- I think if we found it, 

5 at least in some instances we're having 

6 difficulty dealing with sufficient accuracy. 

7 And I also think that the approach that NIOSH 

8 is taking -- and we would consider coworker 

9 models and stratification within, in coworker 

10 models, is if we're going to have any way of 

11 evaluating that using statistics, I think 

12 we're going to have to come up with some 

13 guidance to direct that.

14 As I said, when I was reviewing 

15 the OTIB -- it's not OTIB, it's ORAU, whatever 

16 report, 53 on coworker models and 

17 stratification. And then the SC&A review of 

18 that, I mean, I could agree with both -- I 

19 could think of examples where I'd agree with 

20 both what ORAU was approaching, and I could 

21 disagree with it. In SC&A's critique, I had 
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1 the same, you know, sense of, that it was --

2 that it would depend on the situation, and I 

3 wasn't sure that those were going to provide 

4 the kind of general guidance that we needed 

5 for dealing with coworker models without, you 

6 know, some more guidelines or guidance 

7 attached to it.

8 So, SC&A, you've been quiet. Do 

9 you want to add anything?

10 DR. MAKHIJANI: Dr. Melius, this is 

11 Arjun. 

12 CHAIR MELIUS: Yes.

13 DR. MAKHIJANI: I've been dealing a 

14 lot with this question of stratification and 

15 its application to Savannah River Site, as you 

16 know. We haven't seen the reports yet, but one 

17 of them has gone to DOE and you'll see it 

18 soon, I hope. 

19 But the problem is actually much 

20 more complicated. When we got into the 

21 neptunium database we found that even though 
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1 you have the minimum number of samples, which 

2 are 30, and you cross that threshold -- sorry, 

3 that came up in the thorium, sorry about that.

4 The minimum number of samples 

5 necessary to assure that you're not saying 

6 that they're the same distribution when 

7 they're not, so you're controlling that type 

8 of mistake. It will depend also on how many 

9 samples there are below the minimum detectable 

10 limit that you have to fit in with a 

11 statistical distribution, and how many are 

12 actually detectable, and the relative 

13 geometric mean compared to the geometric 

14 standard deviation. If you imagine the 

15 distribution if you have the means that are 

16 far apart, you will see the two bell curves, 

17 or two log-normal bell curves separately. And 

18 in that case, it'll be easy to tell that 

19 there's different distributions.

20 If they're close together, the 

21 means, but the deviations are large, they'll 
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1 be all smeared out and you won't be able to 

2 tell whether they're different with high 

3 confidence.

4 So, it turns out that the problem 

5 of the number of samples is somewhat more 

6 complicated even than presented in Report 53. 

7 And you might have to do it on a case-by-case 

8 basis. We examined four years in the thorium 

9 report, and in two years it came out fine with 

10 the number of samples, and two years it did 

11 not.

12 CHAIR MELIUS: Yes, that was sort 

13 of what I observed. And I agree, I think it is 

14 very much dependent on what kinds of -- what 

15 types of information you have from the site. 

16 And you're right, with below detection raises 

17 problems, as well as the nature of the way 

18 some of the sampling was done, or who was 

19 selected for sampling. 

20 DR. MAKHIJANI: Right. And the 

21 other -- one of the other issues is, was the 
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1 protocol for the sampling for the two groups 

2 the same? So, was one group monitored only 

3 after incidents mainly or largely, and the 

4 other group routinely? So, in that case they 

5 become non-comparable data sets, at least as 

6 we -- and you've seen that in the report 

7 that's already gone out from Harry.

8 CHAIR MELIUS: Right.

9 DR. MAKHIJANI: So, sort of, the 

10 stratification is necessary in some 

11 circumstances, as at Savannah River Site we've 

12 shown, but it's very complicated and 

13 difficult.

14 CHAIR MELIUS: Yes. And one of my 

15 concerns is that if we -- that we're never 

16 going to be able to reach a resolution on 

17 those issues unless we have some idea of what, 

18 you know, level of difference are we looking 

19 for? Some guidance on how to evaluate sort of 

20 the sufficient accuracy part of these coworker 

21 models.
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1 Anybody else from SC&A want to say 

2 anything?

3 MR. STIVER: This is John Stiver. I 

4 think Arjun summed it up pretty well, you 

5 know, what we're dealing with. We're finding a 

6 lot more complexities once we start really 

7 trying to implement the Report 53 approach. 

8 You know, you get to a point where there's 

9 just not enough data available to really 

10 discern whether -- and the variances are 

11 overlapping to the extent that you can't 

12 really separate out any substrata. How then 

13 do you deal with these low-exposed strata? You 

14 know there are people there for which the high 

15 exposures probably don't apply. And we're 

16 still grappling with how would we go about 

17 naturally trying to implement something like 

18 that, given the limitations we have on the 

19 data sets.

20 This is something we're dealing 

21 with at Fernald quite a bit. It's just almost 
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1 impossible to -- in earlier years to place 

2 people in particular buildings. And, 

3 oftentimes, the job descriptions are lacking 

4 or missing, so you may have somebody who was 

5 an office worker, but --

6 DR. NETON: This is Jim --

7 MR. STIVER: -- we are forced to 

8 give them the type of exposure you'd expect 

9 for a laborer. So, yes, I guess I'm talking 

10 around in circles here, but I -- how to go 

11 about quantifying sufficient accuracy. You're 

12 almost coming out of a situation where you 

13 think you recognize it when you see it in a 

14 particular circumstance, but as far as setting 

15 up rules, that's -- I don't know. We're going 

16 to have to think about this quite a bit more.

17 DR. MAURO: This is John, to weigh 

18 in a little bit. 

19 What we haven't talked about, and 

20 that's maybe because the first attempt at 

21 trying to go back historically and see what 
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1 was done, but when we did decide to deny an 

2 SEC because there was a sense that there was 

3 sufficient accuracy and completeness, so that 

4 you can reconstruct the dose, whether it be 

5 external, or thorium, or uranium, it was 

6 interesting that when we looked at the data, 

7 we were able to say -- and there was like very 

8 little discussion of well, why do we believe 

9 that's sufficiently accurate? What kind of 

10 test did we put it to with respect to 

11 completeness? 

12 And, you know, I think back to all 

13 of those times when we converged eventually, 

14 and concluded yes, I think that group and that 

15 tier or strata can be reconstructed with 

16 sufficient accuracy, and what brought us to 

17 that point? What is it about the data that led 

18 us to a place where we all achieved 

19 concurrence?

20 Most of the conversation we're 

21 having is to show right now what are all the 
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1 reasons which make it extremely difficult to 

2 come to -- draw some conclusions regarding 

3 sufficient accuracy? And, I guess, I -- when 

4 we did agree, it would be -- I would like to 

5 get a better sense of what was about it that 

6 allowed us to come to that conclusion? And I 

7 think about it, and it's almost like sometimes 

8 it's self-evident, but it was never really 

9 articulated.

10 CHAIR MELIUS: No, and I think 

11 you're right, John. And I think part of that 

12 is that we were -- there are so many SEC 

13 evaluations to do that we reached a conclusion 

14 on them one way or the other, and then the --

15 sort of the Site Profile part of it sort of 

16 got, you know, procrastinated or delayed 

17 somewhat. And, therefore, we never have spent 

18 as much time on that, and as much discussion. 

19 So, I think -- I don't think we have as much 

20 of a record of discussing that. Yes, we 

21 evaluate an SEC, we do that, and then we --
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1 before -- and I think the only place where 

2 we've done it has been on the potentially Dose 

3 Reconstruction Subcommittee, but in that case, 

4 for the most part, we sort of ignore the 

5 bigger Site Profile issues, so to speak. We 

6 don't take those on again, so I'm not sure 

7 that there's been as much discussion there. 

8 So, I'm not saying we've done 

9 anything wrong or incorrectly, but I just 

10 think it is something we haven't spent as much 

11 time as a Board or within work groups 

12 discussing. We've been doing more of it 

13 recently, I think.

14 DR. MAURO: When SC&A writes a 

15 report and has its list of findings, and we 

16 all pay attention to the findings, but where 

17 we say, well, this looks okay, I guess we 

18 usually give reasons for it. I'm almost like 

19 thinking out loud now. You know, we would look 

20 at the data, how complete it is, how many 

21 years, how different, and there's a texture to 
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1 it. But somehow we've all --

2 MR. STIVER: John, are you still 

3 on?

4 DR. MAURO: Yes, I'm sorry. Go 

5 ahead. Someone just was speaking there. All 

6 I'm saying is that to what extent would it be 

7 helpful to look at the places where we agreed 

8 that there was sufficient accuracy. Is that 

9 what we've done previously when we -- when the 

10 first attempt was made at this? And what was 

11 it about the data set that led to general 

12 consensus that this did represent sufficient 

13 accuracy?

14 CHAIR MELIUS: Yes, I just don't 

15 think the record is there enough to be 

16 helpful, as much as the -- as when NIOSH did 

17 the opposite approach, which is basically sort 

18 of looking at where situations like the 

19 thorium situations and so forth, they -- a lot 

20 of those decisions were so site-specific, and 

21 it has to do with what data was available, and 
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1 different time periods, and so forth, I think 

2 it was hard to -- it's hard to generalize from 

3 those.

4 John, one thing I question. Do you 

5 really think we pay attention to SC&A reports?

6 DR. MAURO: Absolutely.

7 (Laughter.)

8 MR. STIVER: This is Stiver. I just 

9 came back on. For some reason, I got 

10 disconnected. 

11 CHAIR MELIUS: Okay. I hope you 

12 didn't hear that then, John. 

13 (Laughter.)

14 DR. MAURO: It was okay for my 

15 ears, though. Right?

16 CHAIR MELIUS: I wanted to see who 

17 was awake. Does NIOSH have any comments on 

18 what we're talking about?

19 DR. NETON: This is Jim. I guess 

20 I've got a few thoughts on a few things that 

21 were mentioned here.
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1 CHAIR MELIUS: Yes.

2 DR. NETON: One thing I think that 

3 we haven't focused on is, you know, why were 

4 workers monitored and why weren't they 

5 monitored? In some cases, you know, it's 

6 totally appropriate, because they weren't 

7 monitored because they weren't exposed, or 

8 very lowly exposed, and a general coworker 

9 model would be appropriate. So, I think that's 

10 part of the analysis, is to say, okay, who was 

11 monitored and why. And what do we know about 

12 these unmonitored workers, to what extent? And 

13 if we can flush that out to some great extent, 

14 I think that's when we converge and agree that 

15 we can reconstruct the doses for the 

16 unmonitored workers.

17 The other point that was brought 

18 up that I guess I have some concern with is 

19 maybe tying the sufficient accuracy to 

20 Probability of Causation difference. We 

21 thought about that a lot in the past, and 
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1 there's so many combinations possible to 

2 calculate, that it probably wouldn't be very 

3 fruitful to do something like that, at least 

4 in my opinion.

5 CHAIR MELIUS: Oh, I was not 

6 suggesting that we try to do it for all these 

7 situations. I agree, I think it would be very 

8 complicated, but at some sort of -- I mean, 

9 that is sort of the test. I mean, we want to 

10 know, you know, for particular situations, to 

11 what extent does it contribute to -- you know, 

12 potentially contribute to a person's dose. 

13 And, certainly, at the low end we're making, 

14 you know -- we're already sort of implementing

15 that.

16 DR. NETON: Right.

17 CHAIR MELIUS: I just worry that 

18 without some more thought to that and so 

19 forth, I really worry whether we'll be able to 

20 get very far with dealing with the coworker 

21 issues, at least using statistical 
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1 comparisons.

2 DR. NETON: I've got a little bit 

3 more thought on this: who was monitored and 

4 why. I mean, in my simplistic mind when we 

5 first started this coworker approach, we 

6 envisioned that you have the distribution of 

7 monitored workers. And let's say that we know 

8 with some certainty that either the highest 

9 exposed workers were monitored, or a 

10 representative sampling of the workers were 

11 monitored. In that situation, then, we ended 

12 up developing what I would essentially call a 

13 two-part job exposure matrix where one would 

assign the 95th 14 percentile of that 

15 distribution to the workers that were 

potentially highly exposed, and the 50th 16

17 percentile to all other workers that weren't 

18 monitored and more in categories that were not 

19 likely heavily exposed. I thought that seemed 

20 to make a lot of sense. 

21 Now, I do agree that there are 
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1 some situations where maybe there were some 

2 categories of workers that -- and this 

3 typically comes up in the area of construction 

4 workers that had some very high exposures that 

5 are -- were not monitored that were in that 

6 upper tail of the distribution. Then you've 

7 got an issue, but for most other instances, I 

8 think it seems, in my opinion, fairly clear9 cut that you have this sort of two-compartment 

10 job exposure matrix, it works fairly well. The 

11 trick, of course, is to define which job 

12 categories fit into which bin.

13 CHAIR MELIUS: Yes. And then do you 

14 have enough information on the -- to place 

15 people in those job categories. I think that 

16 is --

17 DR. NETON: I think for the most 

18 part we have a pretty good idea of what the 

19 person was doing. I mean, whether they were 

20 administrative. And, you know, we always tend 

21 to err on the claimant-favorable side.
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1 CHAIR MELIUS: Yes, but I think 

2 that -- and I'm thinking more in terms of the 

3 SEC evaluations. There are a lot of -- well, 

4 there are a lot of workers that move around 

5 the facility, not just construction workers, 

6 security and so forth, and there are a lot of 

7 people, I think, that are hard to know where -

8 - what category to put them in.

9 DR. NETON: Well, I don't know. I 

would say the 95th 10 percentile covers the most 

11 highly exposed workers working on distinct 

12 processes, operations with their --

13 essentially their faces near the operations, 

14 and the glove boxes, and welding operations 

15 and such. And the ones who frequented the work 

16 areas on a regular basis, even, I think the 

50th 17 percentile would certainly capture that. 

18 But, again, that's just -- that's the way we 

19 set it up in the beginning, and that's why 

20 we're talking -- I guess it's not --

21 DR. MAURO: This is John. In 
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1 thinking about it in its simplest sense, are 

2 we asking ourselves the question that says 

3 okay, we have a group that may or may not be 

4 homogeneous. Okay? But we do have a lot of 

data. And we could pluck off the upper 95th 5

6 percentile, and say it's very unlikely that 

7 any worker could have experienced the upper 

95th 8 percentile day in and day out, or year in 

9 and year out. And, as a result, as you just 

10 described previously, that becomes your 

11 coworker number for the high end individuals.

12 Then doesn't the next question 

13 that goes now towards sufficient accuracy, is 

14 that you have to ask yourself the very 

15 difficult question, are there lower tier 

16 groups -- and this is what happened, of 

17 course, with the construction workers at 

18 Fernald. Are there lower tier groups that in 

theory, their upper 95th 19 percentile might be 

higher than the aggregate upper 95th 20

21 percentile?
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1 I'm sort of drawing upon the 

2 experience we just went through on Fernald. 

3 So, what it becomes is a combination of 

4 quantitative and a qualitative approach. The 

5 qualitative side is doing some introspection 

6 that within the overall group, is there reason 

7 to believe that there are subgroups that might 

8 for some reason, such as the construction 

9 workers and subcontractors, could -- it's 

10 almost a sense from experience, could have 

11 experienced something different; and, 

12 therefore, they're a different population. 

13 But then the second part becomes 

14 quantitative. Then the second part becomes 

15 yes, we do believe that there are these groups 

16 that might have been problematic.

17 Then you see if you could find 

18 data for that group. And I don't have an 

19 answer to this, but the real question you have 

20 to ask yourself is, given the data, can we 

21 assign to that sub-tier an upper 95th 
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1 percentile, and is that upper 95th percentile 

2 greater than the aggregate group? 

3 And these are a couple of -- a 

4 process that in thinking through what we've 

5 done before, it really came down to that. And 

6 if we weren't able to do that, we found 

7 ourselves in the realm of, I think we've got 

8 ourselves an SEC issue.

9 DR. NETON: Well, see, John, in my 

10 opinion you have to establish that not only 

11 were they more highly exposed, that group, but 

12 they were also not monitored.

13 DR. MAURO: Yes.

14 DR. NETON: Because by definition, 

15 you have some data from that population that 

16 is higher than the rest of the population. 

17 Grant you that.

18 DR. MAURO: Yes.

19 DR. NETON: But then I think it's 

20 C- you need to look at it and say okay, well, 

21 were there a large number of these people in 
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1 that group that weren't monitored at all?

2 DR. MAURO: And could have had 

3 these high end exposures.

4 DR. NETON: Could have had these 

5 high exposures. See, that's the key. One has 

6 to --

7 DR. MAURO: I agree with that. 

8 DR. NETON: You've got to look at 

9 the whole data set.

10 DR. MAURO: Yes, but you see, those 

11 first couple of questions are very subjective. 

12 You know, are there these groups, did they 

13 have the potential for exposure? And, if so, 

14 do we have any data? You know, so --

15 DR. NETON: We've got that. I mean, 

16 we see that. And Arjun has pointed out a 

17 couple of examples where, yes, there are 

18 construction workers that have -- at least on 

19 paper the mean value is higher.

20 DR. MAURO: Yes.

21 DR. NETON: The median value, but 
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1 there's a large amount of variability on top 

2 of that. But then were there a large number of 

3 these other workers, or any workers that were 

4 in that high category that weren't monitored 

5 at all? You know, I'm not saying they weren't. 

6 I just say that that needs to be somehow 

7 established.

8 DR. MAURO: Yes.

9 DR. MAKHIJANI: This is Arjun. Am I 

10 off mute?

11 CHAIR MELIUS: Yes, you are, Arjun.

12 DR. MAKHIJANI: The -- you know, if 

13 we look at Savannah River external and 

14 internal, we didn't have much problem with the 

15 construction worker or non-construction worker 

16 on the external dose. And NIOSH had put 

17 forward a comparison, and then we reviewed it, 

18 and we found there was one job category, or 

19 two, if I'm remembering correctly, where 

20 construction workers had higher exposure 

21 potential. And we were able to agree on a 
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1 multiplying factor for a coworker model, but 

2 that's because the amount of monitoring data 

3 available was so large that we were able to go 

4 through these comparisons with some great 

5 amount of confidence.

6 The problem with internal doses is 

7 you've got so many radionuclides, and for some 

8 of them, typically, uranium/plutonium, you 

9 often have a large amount of monitoring data, 

10 but the amount of monitoring data for many 

11 radionuclides is quite small, your neptuniums, 

12 your thoriums, and so on. And then it becomes 

13 very, very difficult to settle these questions 

14 in terms of stratification, who was higher 

15 than whom, what was the monitoring protocol, 

16 or was there a monitoring protocol?

17 And that's, I think, where many of 

18 these practical difficulties -- I actually 

19 like the paper overall that NIOSH put 

20 together. I think it needs a little bit more 

21 scientific graininess, and there's some gaps 
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1 in terms of scientific reasonableness that 

2 needs to be put in, and some statistical 

3 constraints that need to be there, but overall 

4 I think these kinds of constraints, we 

5 actually follow them in an SEC. You tend to 

6 come up against difficulties with particular 

7 radionuclides because there just isn't enough 

8 data.

9 CHAIR MELIUS: No. I think that is 

10 usually the difficulty. And I think that's 

11 often why in the past we have given -- made 

12 certain sites into SECs based on that.

13 DR. MAKHIJANI: Right. Exactly.

14 CHAIR MELIUS: And now we're coming 

15 to some situations where maybe there's, you 

16 know, some more monitoring data. But the 

17 question is, is it enough? And then how do we 

18 -- is it appropriate to apply it maybe with a 

19 less stratified model than we might use if 

20 there were -- because it wouldn't support any 

21 evaluation of stratification. 
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1 And, again, as you said, Arjun, 

2 often we have much more limited information on 

3 the sort of the sampling strategy and so forth 

4 for those. So, those are the ones that, you 

5 know, again, for these sites, they're the ones 

6 we're mostly interested in because, 

7 certainly, they're the crux of what we do in 

8 terms of making an SEC evaluation at these 

9 sites.

10 Any other comments on the report 

11 or these issues right now?

12 MEMBER ROESSLER: Jim, this is Gen.

13 CHAIR MELIUS: Yes.

14 MEMBER ROESSLER: I was trying to 

15 get off mute. I would like to not just simply 

16 dismiss the thought that John Mauro brought up 

17 about looking at the cases where we thought 

18 there was sufficient accuracy. You know, I 

19 don't think it deserves a great detailed 

20 evaluation, but I would think that someone 

21 would be able to kind of look at them and see 
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1 if there's a general trend, or if there's 

2 anything sort of on the surface there that 

3 could be looked at deeper.

4 CHAIR MELIUS: NIOSH, do you have 

5 any response to that?

6 DR. NETON: Not right at the 

7 moment. I'd have to think about that.

8 MEMBER ROESSLER: I think, at least 

9 think about this.

10 DR. NETON: It might be worth 

11 doing. I don't know. I just don't have a feel 

12 in my brain right now, as to which sites that 

13 would be, and what data might be available. 

14 MEMBER ROESSLER: I just don't want 

15 to completely dismiss it because it seemed 

16 like a pretty interesting concept.

17 CHAIR MELIUS: Yes, I think the --

18 at least, personally, I think one of the 

19 problems in thinking about that is that -- at 

20 least I was disappointed in the other reports, 

21 because I actually thought we would get more 
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1 out of those, and they'd be more helpful than 

2 they were. And I'm not faulting NIOSH or ORAU, 

3 whoever prepared those reports. I just think 

4 it's -- our SEC decisions are very much driven 

5 by the specifics about a particular site. And 

6 often, work monitoring wasn't done, and the 

7 nature of operations of these sites. And these 

8 sites are quite diverse, so in terms of sort 

9 of general conclusions, we didn't get as much 

10 out of that as we thought we might. But let's 

11 think about doing that.

12 MEMBER BEACH: Jim, this is Josie, 

13 to add onto that. SC&A uses a set of criteria 

14 when they develop whether a certain site or a 

15 certain issue is sufficiently adequate. Have 

16 we talked about looking at their criteria, and 

17 maybe that will help in the thinking of how to 

18 look at that?

19 CHAIR MELIUS: I don't know what 

20 their criteria you're referring to are.

21 MEMBER BEACH: Well, SC&A would 
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1 probably have describe that. I'm sure --

2 CHAIR MELIUS: No, no. I was making 

3 an opening for SC&A of --

4 MEMBER BEACH: Oh, thank you.

5 MR. STIVER: This is Stiver. Are 

6 you talking about our data adequacy and 

7 completeness reviews?

8 MEMBER BEACH: Yes, I believe so. I 

9 mean, you go through a set of criteria when 

10 you're looking at whether a site has adequate 

11 --

12 MR. STIVER: Well, yes, we try to 

13 list to determine whether they're -- you know, 

14 all the years and buildings where operations 

15 took place have monitoring data. Basically, 

16 the same kind of thing that's laid out here in 

17 this hierarchical approach. So, we don't 

18 necessarily have a set of fixed criteria that 

19 we look at. That's sort of a kind of approach, 

20 you know. You look at the source terms, the 

21 exposure potential, you know, the different 
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1 aspects of that, and then look to see whether 

2 the proper type of monitoring was invoked 

3 based on the types of radionuclides and so 

4 forth.

5 As Arjun said, we've mentioned 

6 earlier, Savannah River is a pretty good 

7 example. You typically have pretty good 

8 external dosimetry data which allows you to 

9 make some kinds of adjustments for certain 

10 strata, but oftentimes you don't have that for 

11 the less well represented radionuclides, like 

12 thorium or neptunium and so forth. So, it 

13 becomes a matter of looking at those and 

14 seeing what operations are going on, what 

15 radionuclides were in place, and what the 

16 exposure potential is. And then given that, do 

17 you feel they're statistically significant 

18 data available of high quality that can then 

19 be used to reconstruct dose? A lot of it comes 

20 down to a matter of professional judgment.

21 (Simultaneous speaking.)
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1 DR. MAKHIJANI: I would supplement 

2 that a little bit. This is Arjun. We have 

3 procedures by which we -- for reviewing SECs, 

4 and also for reviewing site profiles, and 

5 those were submitted to the Board early on. 

6 John Mauro, correct me if I'm wrong.

7 DR. MAURO: You are correct.

8 DR. MAKHIJANI: And we generally 

9 follow those procedures. We also, you know, 

10 bounce off of specific NIOSH reports when 

11 we're reviewing SECs with which I'm more 

12 familiar. We start with the -- we start, 

13 obviously, with the evaluation report 

14 typically when it says dose reconstruction is 

15 feasible. And then we go through a very, very 

16 similar set of criteria, but I think the 

17 scientific and statistical feasibility sides 

18 of it are a little bit more elevated than they 

19 are in the document that NIOSH sent out on the 

20th 20 of May. But the ideas about source term, 

21 the availability of monitoring data, the 
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1 various kinds of radionuclides, external and 

2 internal; external are usually not a problem, 

3 so mostly internal. And they're not very 

4 different than the ones you have before you. 

5 We have -- and I think if NIOSH 

6 probably developed a document in more detail, 

7 you won't come up with something that's very 

8 different than what we do. 

9 DR. MAURO: A good example; I mean, 

10 when we recently worked on PROC-44 where one 

11 of the things we added to the attachment was -

12 - in a funny sort of way, it goes very much to 

13 this topic where we say, well, there are a 

14 number of sites that SC&A worked on with the 

15 Board and NIOSH, and where we did come to 

16 convergence, eventually, by pushing the data 

17 through a certain process. I'm thinking -- and 

18 there are four examples, I believe, in PROC19 44. And we did it solely as a way to review 

20 the current protocol that NIOSH employs for 

21 doing SEC reviews. 
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1 And if you recall, one of our 

2 commentaries was to get more explicit, and 

3 perhaps with some examples of what does 

4 constitute -- how do you go about getting to 

5 the point where you achieve what we call 

6 completeness, accuracy, adequacy, that sort of 

7 thing?

8 Now, the best we did is give a few 

9 examples in Attachment A to PROC-44, but I 

10 think that goes toward the things we're

11 talking about. When -- under what 

12 circumstances were we able to get to a place 

13 where there was consensus, yes, we think we 

14 agree that there is data adequacy and 

15 completeness? We don't usually use the term, 

16 meets the test of sufficient accuracy, but we 

17 usually do get to a place where we say we 

18 think they're scientifically accurate and 

19 claimant-favorable.

20 I would just maybe want to point 

21 everyone to that attachment in PROC-44 review 
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1 that we submitted six months ago or so, as 

2 being a place just to take a look at, because 

3 it goes a little bit toward what Gen had 

4 mentioned earlier, that, you know, under what 

5 circumstances did we achieve convergence? And 

6 I think a few examples are in there, but 

7 certainly there are more.

8 DR. MAKHIJANI: If I might add 

9 something for Josie. You know, it's not so 

10 much the specific criteria that are different, 

11 but maybe how sometimes we look at them. So, 

12 for instance, in this paper, NIOSH says it 

13 must be possible to demonstrate that the 

14 highest exposed workers were monitored. And we

15 agree, and we -- but often the discussions and 

16 differences are, were the highest exposed 

17 workers actually monitored, and how do you 

18 demonstrate that? Because it says it might be 

19 possible to demonstrate, because once you've 

20 demonstrated that, then as Genevieve was 

21 saying earlier, then your road to a coworker 
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1 model is clear. But in terms of demonstrating 

2 that for some radionuclides, it's very, very 

3 difficult.

4 I'm recalling about a site where a 

5 certain population of workers was very 

6 frequently monitored, but we weren't able to 

7 establish the relationship, at least that's my 

8 interpretation, between that monitoring and 

9 many other groups of workers who didn't have 

10 very much monitoring, but who had exposure 

11 potential.

12 So, it's the -- and then the 

13 statistical depth to which you need to 

14 demonstrate something is a pretty important 

15 consideration, so I just ended one example. 

16 So, in Report 53, NIOSH had a hypothesis that 

17 the two distributions of construction workers, 

18 or two distributions being compared, say 

19 construction workers and non-construction 

20 workers, are the same. And the bar for 

21 rejecting that was very high, so when you look 
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1 at it the other way, the bar for -- you can 

2 often be wrong and say they're the same when 

3 they're actually not the same. But we believe 

4 that you need to look at that question with as 

5 much rigor as the first question. So, you need 

6 to control for both types of errors.

7 So, how you -- so, a lot of the 

8 differences, Josie, have arisen not in the 

9 things that we look at, because we all look at 

10 the same things. We look at the source terms, 

11 the work, and the monitoring data, and how 

12 much is available, and what the radionuclides 

13 were. It's in how we approach the 

14 demonstration of whether these data can do the 

15 job or not.

16 MEMBER BEACH: Absolutely. Thanks, 

17 Arjun.

18 CHAIR MELIUS: And I would just 

19 add, I think the -- often it's the -- that's 

20 just the numbers -- it does come down to what 

21 extent is there data available to demonstrate. 
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1 And if we're -- that data is not available, 

2 what do we -- what assumptions do we make? Do 

3 we assume that it means that the exposures 

4 aren't stratified, or that between various 

5 groups, or that they are? I mean, that's -- I 

6 think right now we would assume they aren't. 

7 And is that a valid approach? 

8 And then if we're going to make 

9 that -- if we don't have adequate data to make 

10 -- to evaluate that, then we're going back to 

11 how do we, you know, interpret, or how much do 

12 we know about, you know, what people did to 

13 make sure the sampling protocols for the site 

14 and so forth. So, there's a lot of different 

15 types of information that we would take into 

16 account. So, now we've learned that SC&A 

17 hasn't already figured this out. And the Board 

18 hasn't, and NIOSH hasn't.

19 So, what I would suggest doing, 

20 going forward, we're going to be discussing 

21 this at the Board meeting in Idaho. And I 
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1 think we, you know, should -- and we're going 

2 to also be discussing the ORAU-0053 and the 

3 SC&A review of that, so I think those two will 

4 tie together. And we have a fairly significant 

5 amount of time devoted to that. I think 

6 actually later in the meeting we'll also be 

7 discussing the Fernald site. There's an 

8 example where we'll be dealing with this 

9 coworker stratification issue, so I think 

10 there will be a lot of time to think about 

11 that and so forth.

12 I mean, what I would like to do is 

13 get some input from other Board Members, and 

14 get a sense of what should we be doing to 

15 approach this? What makes sense to do at this 

16 point in time? Is that reasonable with the 

17 other Board Members on the Work Group, and 

18 with NIOSH?

19 DR. NETON: Yes, it sounds good.

20 MR. HINNEFELD: Same here.

21 CHAIR MELIUS: Okay.
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1 MR. HINNEFELD: Now, for the July 

2 Board meeting would you expect us to have 

3 taken a shot at some of the sites where SECs 

4 were not granted, to kind of look at what was 

5 special there, or what was --

6 CHAIR MELIUS: Well, let's wait 

7 until we get up to -- out to Idaho.

8 MR. HINNEFELD: Okay.

9 CHAIR MELIUS: That's not to not do 

10 it, that's -- I just don't think there's time 

11 to --

12 MR. HINNEFELD: I don't think we 

13 could do much of it.

14 CHAIR MELIUS: Given some of the 

15 resource constraints and so forth, I don't 

16 want to burden you until we may be able to pin 

17 it down a little bit more.

18 MR. HINNEFELD: All right.

19 CHAIR MELIUS: Do that. I mean, 

20 because there are some other things that come 

21 up. One of the things I was actually thinking 
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1 about when Arjun was talking about the 

2 Savannah River is, well, what is it about the 

3 external monitoring data that led us to sort 

4 of accept that in terms of coworker models? 

5 And then what -- you know, how far did we go 

6 with that in terms of stratification, or non7 stratification and what was that based on?

8 And that would be examples where 

9 we have less constraint due to the amount of 

10 data available, and probably more information 

11 -- because the data is so dense that we have 

12 more information on understanding and 

13 confidence in the sampling strategy and so 

14 forth, so that we weren't concerned about some 

15 of those issues. Well, then what did we 

16 conclude based on that? You know, we conclude 

17 it was sufficiently accurate. It wasn't -- I 

18 mean the SEC is not based on that, so maybe 

19 that's an example of something that would be 

20 useful to think about from this perspective. 

21 But let's all think about it. There will be 
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1 other examples from other sites that --

2 different issues that we want to -- would like 

3 to get more information on. 

4 DR. MAKHIJANI: Yes, Dr. Melius, 

5 that -- you know, if I might expand on that 

6 for a moment. We've been discussing this 

7 mostly in whether an SEC was granted, or 

8 whether all parties agreed there was enough 

9 data to deny an SEC. But it may be more useful 

10 to be a little bit more fine-grained, because 

11 there have been many areas where we agreed 

12 outside of, you know, whether an SEC was 

13 granted or not. But many areas where we agreed 

14 that there was enough data, even in the 

15 internal data. Of course, SRS external data is 

16 a very good example, and there the 

17 stratification was pretty fine-grained. But, 

18 you know, plutonium data at Rocky Flats, I 

19 think we didn't have very much argument about 

20 that, if I'm remembering correctly, for 

21 example, and uranium data at some sites. So, 
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1 it may be useful to look at that.

2 CHAIR MELIUS: Okay. 

3 DR. NETON: I can speak for the 

4 Rocky Flats, and I was going to mention that 

5 earlier. That's a case where the data were not 

6 as robust as we liked, and we ended up using 

the 95th 7 percentile for all workers. That's 

8 one where we sort of agreed.

9 DR. MAKHIJANI: Yes, and we did 

10 agree that there were enough data to do that.

11 DR. NETON: Right. But we agreed 

that we would use the 95th 12 percentile for 

13 everyone, and not try to stratify it in the 

50th or the 95th 14 . That's sort of a different 

15 example, but it might be worth looking at here 

16 at this point.

17 CHAIR MELIUS: Anybody else on the 

18 Work Group with last words or suggestions? If 

19 not, we'll see everybody in Idaho. We're 

20 hoping someday Ted will find us a place to 

21 stay, other than camping behind Brad's house 
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1 or something. I'm not sure what we have in 

2 store for us, but --

3 MR. KATZ: I think Brad lives in a 

4 nice place.

5 CHAIR MELIUS: Does he? Does he 

6 have room, you know, in the garage for a bunch 

7 of us?

8 MR. KATZ: He's very handy. If he 

9 doesn't, he might be able to do something.

10 CHAIR MELIUS: Yes, that's why I 

11 say, we'll get the notice, bring sleeping 

12 bags.

13 MR. KATZ: So, everybody, the other 

14 thing -- I think it's pretty obvious to me 

15 what materials I should distribute related to 

16 this discussion. But please, to everyone on 

17 the line, give some thought as to what you 

18 might -- what might be additional reading 

19 materials that would be helpful to people, and 

20 I'll distribute those, as well. The obvious 

21 ones I'll cover.
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1 CHAIR MELIUS: Yes. No, I think 

2 this outline would be one. And then, 

3 obviously, the -- some authority you already 

4 have on your list, but 53 and the --

5 MR. KATZ: Right, right. 

6 CHAIR MELIUS: And so forth.

7 MR. KATZ: Right. No, I'm just 

8 saying, if it occurs to anyone that something 

9 else is particularly germane, just let me 

10 know.

11 CHAIR MELIUS: Yes.

12 MR. KATZ: And I'll add that to 

13 what I distribute to all the Board Members, 

14 and what we have out there at the meeting, 

15 too.

16 CHAIR MELIUS: I'll let you know. I 

17 also assigned -- tried to assign to our 

18 eminent epidemiologists on the committee the -

19 -I just remembered I left off one, but I sent 

20 them copies of the report, the 53, and the 

21 review of the 53 to read ahead of time.
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1 MR. KATZ: Oh, good.

2 CHAIR MELIUS: Yes. See if I can 

3 get them interested before the plane ride out 

4 there.

5 MR. KATZ: That's good. That's 

6 good. Well, they both could bring something to 

7 the table.

8 CHAIR MELIUS: Well, I began with 

9 four of them, and I left out -- I forgot Jim 

10 Lockey.

11 MR. KATZ: Right.

12 CHAIR MELIUS: Just thought about 

13 it. Okay. Everybody, thank you, and as I said, 

14 we'll see you in July in Idaho, if not sooner. 

15 Thank you.

16 MR. KATZ: Thanks, everyone.

17 (Whereupon, the above-entitled 

18 matter went off the record at 2:17 p.m.)

19

20

21
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1

2

3

4

5