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DR. HARRISON: Yes. So either way you look at it, is asking for money.
DR. STOTO: No.
DR. HARRISON: I mean, if you're just asking for a study section to spend a half a day .
DR. STOTO: No. No, I'm not asking for a study section. I'm saying that there are hundreds of study sections already, and that they could perfectly well review proposals that are submitted; you know, if it's a proposal about diabetes it will go to a certain study section and so on.
But the problem is that most investigators who have the potential for writing applications like this don't know about the resource.
DR. MINER: We have in fact taken some steps to increase our public output, and I've asked SAIC to give us a communications plan, including that as updating of web page and so forth. So we're going down that road, but not fast enough.
DR. STOTO: Yes, I'm not sure; we'll have to see what the plan is, but I'm not sure that relates to the researchers; People who are not working in, certainly in herbicides, or veterans but may be interested in dioxin may be interested in just longitudinal aspects of aging.
DR. GOUGH: That's what I would think.
DR. STOTO: They may not care at all about the dioxin.
DR. HARRISON: Let's try and do what we're
DR. GOUGH: I'd like to see that in the minutes; we want some publicity about these datasets, and we want to see people like you using them, Bob.
DR. HARRISON: Those are good points, and I can't help but agree. I don't disagree at all. I think we just wandered just a little bit from what we were supposed to be doing first here.
Well, the only thing left on sheet is a question, administer the spousal questionnaire.
DR. MICHALEK: That is a repetition of a questionnaire we gave at baseline and cycle 1 and cycle 2 and cycle 3 to the women, to the spouses and sexual partners of the men asking about their ability to conceive children.
Not every spouse and partner has received the questionnaire. Since we only have one more time available to contact these women, we wanted to finish that dataset and release that to the public. That's a fairly low-level activity in terms of cost and resources. So it's something we really want to do.
DR. STOTO: It wouldn't be part of the analysis of these blue books?
DR. MICHALEK: No, it wouldn't be part of the big report, no. This will come later. This will simply complete our dataset so we can write a better research paper on biotech data.
DR. HARRISON: Go ahead.
DR. STOTO: So this does fit into the category of, if you don't gather it now, you won't --
DR. MICHALEK: That's it, we're going to lose it forever.
DR. HARRISON: Right.
DR. MICHALEK: There is one item left that's not on the list.
DR. HARRISON: Well, first of fall, we feel that that's a very sensible thing to do.
DR. GOUGH: Analytically it's going to be complicated, though.
DR. MICHALEK: We've got an analytical effort in place already to address the data with. Debbie del Junco, University of Texas-Houston, Brenda Escanazi, UC-Berkley.
DR. GOUGH: But because --
DR. HARRISON: Well, you're going to go back and ask everybody, though? You're not going to just ask the ones you missed the first time.
DR. MICHALEK: We're going to ask anyone who hasn't received it yet.
DR. GOUGH: That's the issue that comes up, is that if you ask a 22-year old woman, twenty years ago about her reproductive history and you ask a 42-year old woman today--
DR. MICHALEK: Maybe I said that wrong; they were going to update all of that. But whatever it is, we'll do --
DR. GOUGH: I think that's the analytical problem.
DR. HARRISON: Well, I agree.
DR. MICHALEK: We should go back and try to retrieve information on any pregnancies or attempted pregnancies since the last time we gave it, which was in 1987.
DR. HARRISON: Well, the better way would be to just treat it as though it were --
DR. GOUGH: Never done.
DR. HARRISON: a new survey.
DR. MICHALEK: I think you're right.
DR. GOUGH: It needs to compare yes and no I mean old and new, once you have both of them.
DR. MICHALEK: I stand corrected.
DR. GOUGH: We're in favor of that.
` DR. HARRISON: Okay, so the first recommendation is for the spousal questionnaire in a revised form to be administered to as broad a population as possible.
I find it hard to read this thing. Okay, so we've done statistical models, we've done covariates and interactions.
DR. STOTO: No, no, we haven't finished with --
DR. HARRISON: We haven't? We haven't finished statistical models?
DR. STOTO: No, we haven't gotten into the meat of it yet.
DR. HARRISON: Oh.
DR. MICHALEK: No, this is just
DR. HARRISON: I'll tell you what, in 30 minutes, we're due to have our open public session, and then our work will be done for the day. So can we cover statistical models in the 30 minutes?
DR. GOUGH: Let me note the dichotomy. Everybody except Joel and Mike say "sure."
DR. STOTO: I think we can.
DR. GOUGH: Okay.
DR. HARRISON: Come on. Go for it.
DR. MICHALEK: Let me at least mention the item that should be on the list that I forgot to put on there.
There was one item left, I said. That was the item from Dr. Favata that we question the individuals about chemical exposure in the home. I'm sorry, I forgot to put that on there.
DR. HARRISON: She's been trying to get you to do that since the previous cycle.
DR. MICHALEK: I'd like for the record to put that on there; that was an oversight, and we intended to address that, wanted the committee to address that issue. We would like Dr. Favata to tell us what series of questions we should ask the participants in that area; maybe she would give us a literature citation so we could inserting those questions into our in-person interview that we'll give at the next physical.
DR. HARRISON: Okay, so since she's not here right now, we'll presume she'll at least be here by tomorrow, we'll make that a go issue for tomorrow.
DR. HARRISON: Mike?
DR. STOTO: In section 3.6.1 in the subparts, there are a number of changes. I think that they generally are not controversial, like using SAS rather than BMBDP and using body mass index versus percent fat, and so on.
The one that I think does deserve some discussion is let's see, where is it. It's section 126.96.36.199; it's at the bottom of page 23 of the one we got today.
DR. HARRISON: Health versus Initial?
DR. STOTO: Right. And it has to do with, how do you figure out what was the level of exposure to dioxin during the time these guys were in Vietnam. And previously if someone had a body burden of 10 ppt or less at the time of the exam, they were dropped out of the analysis. And I think what they're proposing to do now is to include them in the analysis but not extrapolate back or extrapolate back in a flat line from the earliest measurement, if they have two measurements.
DR. MICHALEK: We'll just use the current measurement, basically. We only have one value. Suppose the guy has 9 parts per trillion in 1987.
DR. STOTO: Some of them have two measurements.
DR. MICHALEK: Well, yes, some of them do. 300 and some of the veterans had more than two.
DR. STOTO: And I guess that's better than leaving them out.
DR. MICHALEK: We agree with you.
DR. STOTO: I've got two things to say. One is, an alternative would be to extrapolate back by the average half-life.
DR. MICHALEK: Right.
DR. STOTO: Because even if you start out with, even if you end up with 9, it's more likely that you had 18 so many years ago than you had --
DR. GOUGH: You have no idea if that's true.
DR. HARRISON: I was going to say, that --
DR. GOUGH: None at all.
DR. HARRISON: I have to agree with Mike.
DR. MICHALEK: We have data in the comparison group to suggest that an individual will fluctuate over his lifetime, between an interval of 0 to 10.
DR. STOTO: I guess I've come to the bottom line. I would like to see an analysis to support this. That may be right, but I'd like to I think it's the kind of thing that I'd like to know more about.
DR. MICHALEK: Okay. I'd like to show you, we have a paper just accepted to a journal which shows that in the comparison group.
DR. CAMACHO: the ability to go back? You want to see something more about--?
DR. STOTO: No, if someone had a body burden of 20, they would extrapolate back to their about what their exposure was.
DR. HARRISON: Use the half life.
DR. STOTO: Use the half life.
DR. HARRISON: But if you're less than 10, they don't use the half life.
DR. MICHALEK: Don't extrapolate.
DR. STOTO: That's better than dropping them out altogether, which is what they used to do. And --
DR. CAMACHO: It came up last time.
DR. HARRISON: Comes up every time.
DR. CAMACHO: Ha, ha, ha.
DR. MICHALEK: The approach that Mike just described has already passed peer review, so to speak. Because I presented that approach at the Dioxin Conference in California and all the guys from EPA were there and they liked it. In fact they want to coauthor a paper in that direction.
An extension of the there are two possible extensions here to address the idea here that the analysis suffers from changes in the elimination rate from one person to another. We know that individuals who are lean will eliminate dioxin more quickly than those who are obese, and so we might have a way to adjust for that.
And what we've done in the past, because our statistical models are not sophisticated enough to provide a bodyfat-specific elimination rate, what we do is stratify the cohort into low, medium, high by body fat or BMI when they were in Vietnam, and then within each of those strata we estimate the elimination rate. And based on those elimination rates, which are now body fat specific, to a fairly narrow range, we estimate the initial dose in Vietnam. There we've carried the analysis one step further to use available data to address a criticism; namely, that the initial dose in Vietnam may be wrong because of changes in body fat.
Now that's a refinement that we can include and we will include in our datasets that we give to SAIC to carry out the analyses in the big report. That's not something we expect SAIC to do, but it is something certainly that we can and we will do.
Another refinement of this method is not just to use the dioxin level, but to use the amount of time since Vietnam to the present. To accumulate the dioxin dose in the body by effectively taking what's called the area under the curve. In that analysis you also use the elimination rate, for those that had high levels; you take full advantage of the 343 Ranch Handers that have up to four dioxin measurements so you can actually compute an area under an exponential curve.
Use all available information. And we've found that when we do that, we get slightly sharper results, the way we analyze diabetes, as opposed to using the straight dioxin levels that we've been using in our reports. However, if we go ahead and do the AUC analysis in this report, there will be no precedent for it in any of the previous reports.
That argues for putting the AUC analysis in as an additional model, over and above this one, but that increases cost, which could be considerable; the cost of the last report including overhead, was about $1.5 million. So this might increase, you're going to now increase the models from four to five, that's roughly a 20 percent increase.
So we're talking about cost constraints and time constraints here, too.
DR. STOTO: So does this fall into the category of things you might want to do, further analysis you might want to do that don't necessarily have to fit into the blue report?
DR. MICHALEK: Yes. I would say that the body fat adjusted initial dose estimate can easily be done within the constraints of the report, simply by giving them the body fat adjusted elimination rates. So when they do this you'll have automatically, be an adjusted analysis. So that's our proposal.
DR. STOTO: I guess I agree that this proposal here is better than what's been done in the past for the blue reports. I don't think I would want to stop there, but as long as we understand it in terms of what do we do for the blue reports, I would be happy with that.
DR. HARRISON: If you have a group of people whose dioxin levels is the less than ten the level of sensitivity of the ?
DR. MICHALEK: The value ten has been singled out, and some people think
DR. HARRISON: So it's not the limit of sensitivity.
DR. MICHALEK: No. The number ten is simply the 99th percent of the comparison group. 99 percent of the comparisons have less than ten. In round numbers.
It just happens to be a round number, like ten.
DR. HARRISON: And if you had a group of subjects with a level of ten or eight or something like that, and you assayed them again after a five year interval, the levels would be lower?
DR. MICHALEK: We have done that in the comparison group and we have found that the pieces, unfortunately you asked a question and now you opened up another area of complication.
The dioxin levels in the comparison group are dropping. If you look at the dioxin levels in 1987, those in 1992 and those in 1997 in the comparisons, you'll see they're coming down. And they're coming down, following a trajectory that is parallel to a decrease that's been published in corresponding populations in Germany and other parts of Europe.
The thinking at the EPA is that this downward trend is reflective of cleanup of industries around the world in their emissions of chemicals into the environment. So that this is reinforcing the idea, status consistent with the hypothesis that general regulation of industry has caused a decrease in environmental pollution, and that has decreased body burdens.
DR. STOTO: I think that complicates it. I think the point is --
DR. MICHALEK: I've asked the question and not given you the answer.
DR. STOTO: But I think the point is--
DR. HARRISON: Well, that wasn't my question.
DR. STOTO: Let me see if I understand the question.
DR. HARRISON: My question relates to the physiologic mechanism of action of dioxin, and whether the level of 10 falls let's say an order of magnitude or more below a dissociation rate constant for dioxin age-receptor interactions.
DR. MICHALEK: Don't know that. All we know is that 10 seems to be the threshold for background exposure in U.S. white males, which are the representative biocomparison group.
DR. HARRISON: Okay, but if I remember the argument that I heard at the EPA a couple of years ago, the EPA wants to say that any whiff of dioxin is bad, that there is a continuous dose of
AUDIENCE: That's wrong.
DR. HARRISON: I believe it's wrong, don't worry. I don't know that beliefs matter a whole lot; but one argument is that there's a continuous response all the way down until there's no dioxin left, I mean, until you whisper dioxin.
|Advisory committee on immunization practices||Medical Devices Advisory Committee|
|Veterinary medicine advisory committee||National Vaccine Advisory Committee (nvac)|
|External Advisory Committee on Cities and Communities||Wildlife Diversity Policy Advisory Committee|
|Peer reviewed by the Arizona Department of Commerce Economic Research Advisory Committee||Food and drug administration national institutes of health advisory Committee on: transmissible spongiform|
|Advisory Committee, Cuyahoga Valley School-to-Career Consortium, Broadview Heights, Ohio 1996-2002||Jane D. Siegel, md; Emily Rhinehart, rn mph cic; Marguerite Jackson, PhD; Linda Chiarello, rn ms; the Healthcare Infection Control Practices Advisory Committee|