Document 2qJpBaJ74MnGbDzkXXpz3vqxL

Recorded telephone conversation between Selevan of NIOSH and Dr. J. Rafter Dr. J. K. Wagoner & Ms. Sherry & Jan. 1977 1977 J.R. Let me tell you what I have then we'll kind of be on the same wave length maybe I have transcript that Ms. Selevan gave at the American Public Health Association on October 20th I have a transcript of that talk . I also have a listing of 94 deceased individuals and a more detailed listing of 17 who died some tables from respiratory causes which I understand were and finally given to I have finally the three companies involved in your probably equivalent to the report slides and I think they're that were shown on the | I. SS they are equivalent I. ! J.R. Pardon SS ? J.R. So that's where I stand and now I need generally some information so I can understand how they were analyzed | and maybe go over it myself so I can report to people that | ask me whether or not I think it's a reasonable analysis and so forth JKW Well basically the underlying assumption of the whole analyses are that one person observed for ten years equates LN out with ten person years at risk which is to say that ten persons observed for one year equates out to ten . person years at risk However there is one additional ii | a parameter that added into it because of the fact that hie as disease causation if not an instantaneous event manifest t by death and that is we analyzed our basic data if you could draw on a piece of paper a matrix which has on one scale axis duration since onset of which for easier terminology we classify as latency on the other axis you have duration of employment Within if you draw out seven different categories in each one of those axis actually eight being the marginal total the first category which is cell'l x yo : yu ou with of duration of employment and me is less than five years less than five years since onset of employment Going cell is 5 through 19..where over have to your you got right the second duration of employment on top R. JKW on top Within latency less than five 5 to 9 years it's a nonsense You understand that , duration of employment it's an impossibility o.k. | J.R. Yes JKW Basically let me go back one further step I'll give you the five variables six variables that we consider We consider age which is an always increasing function | Protected Document to Protective order 0012193 JNJ 000048141 JKY JR JKW R. JKW we consider calendar time which is since function we consider interval since an onset which is an always increasing function that's latency is that correct always increasing of employment latency and we consider duration employment which is a static or increasing function depending on whether a person terminates employment or not ThTo hose se are your basic four variables that are considered other th than an = - oo+ of variables such as race and sex Now withiwnithin within within each one these cells in this big matrix that I had had had given given given you we have a life table in terms of calendar time time and age age in five year intervals calendar time in five year intervals The reason that we analyze in terms of these two variables is that disease is obviously associated with aging disease is also a secular phenomenon in terms of diagnostic differences and things like this that lung cancer is an increasing function over time and what we hope to do when we analyze is to control for these nonsense variables so that later in our final analyses we can after analyzing for these variables we can collapse the table and just consider dosage and intervals since onset holding each of these other variables constant as we controlled for them in the analyses C.K. Yes On your axis you have five year intervals less than five five to nine ten through fourteen fifteen through nineteen twenty through twenty twenty through twenty greater equal to thirty and a total which is the largest total summation of all the events in that column row In going five down five you have the same numeric breakout of less than through nine O.5 What we do is we take each individual as he comes in we ask the basic question did he get employment into the life table in he began employment in 1940 the age he had 1940 entered achieved in 1940 and the latency 0 because he had just began employment duration of onset of employment of 0. Assuming that he has continuous employmenhte passes down through the diagonal of the table both in terms of calendar time in terms of aging in terms of increasing employment and in terms of interval since set of employment until he stops employment in which case he no longer increases in terms of duration of employment but just increases in terms of onset interval since onset of employment O.K. As he ages of course he progresses in calendar time He can get out of the life table in terms events Either he expired in which case of he two different is removed from risk of dying at the date that removed totally from further accumulation that point expired expired of and is risk person time or he can come to the end of the study period when everybody drops out of the study who does not expire O.K. Now if a person continues employment from 1940 and the study period the behg e a begn an employment in ceases in 1975 he will contribute five years of risk in cellli of risk in cell II O.K. he will contribute five years because has spent five years Protected Document to Protective order 0012194 JNJ 000048142 JR JKW JR JKW . 1 at risk of dying as he was accumul he his ninth year of employment and employment ninth year since onset of employment five wise five in the third cell 36. ac umul he employment employment five ng his was wwasas in fifth through his fifth through at at that time And like- five in cell 44 five in cell cell 55 five in cell 66 and six inin cell 77. that is 1970 '72 '73 74 and 175. O.K. Now let's letlet's 's as ume assume that we have another individual that comes through but he dies on the 10th anniversary of his initial employment He will contribute five years at risk in cell II he will contribute five years at risk in cell 22 and will be removed from the the life table at that point in time as deceased due to the underlying cause as certified on the death certificate O.K. I will take a third individual who just dies on the fifteen anniversary of his employment initial employment but he only works for ten consecutive years He will contribute five years in cell II five years in cell 22 and five years in cell 23 two being duration of employment Its 32 across the the way top that I have it would be it I 32 in guess since I terms of o.k. have duration Essentially he goes on cell and then drops out the due diagonal and then drops one to the cause of death that he died from O.K7 You with me Yes The only other case that really theoretically can happen you can work out all sorts of combinations on those would be a person who was initially employed worked for five years left the industry for five years came back and worked for another five years Alright That person contributes five years at risk in cell II he contributes five years at risk in cell 12 one being less than five years of duration but at the fifth to ninth year since onset o.k. and then he contributes five years at risk in cell 23 during the period that he accumulated his fifth through ninth year of employment but he was in his tenth through his fourteenth years since onset of employment That will be your third type individual fourth type of individual that can of fit into the life table at risk The other condition obviously a person who begins employment in 1920 of our study period begins in 1940 because that when the record system or thats when our follow up started because we use social security as method of ascertaining whether a person is deceased or alive and that system really came into effect in 1935 or 36 actually '37 or '38 If that person began in 1920 and was still on the payroll in 1940. then this is the first date of our study period He will be in cell 5-5 when he enters our period at risk He has accumulated 20 through 24 years of employment he's actually on the 20th year of the onset of his employment He contributes no risk during the interval prior to that because he has no probability of dying otherwise he would not be on the payroll as of 1940 when we had the first chance of picking Protected Document to Protective order 0012195 JNJ 000048143 J.R. JKW J.R. JKW R. him up O.K Yes Basically you have the matrix 2se 2se from Each our in this one of these case the VermontVermont obviously as Tale go workers through themselves each one of these cells is put into that additional matrix within the cell of a series of sixteen groups and approximately eight calendar periods 1940 through 1944 1944 1945 through 1949 , '50 through '54 O.K. These individual individual numbers that we are distributing are individual person years that each individual contributes that risk of dying during the period of the study O.K. Now to get what one would expect to have occurred in this population if they had experienced the same death rate of the control group this case the U.S. white male population we generate calendar period that we used in our life table distribution and the same age groups that we use in our life table distribution death rates per 100,000 population due to specific causes of death 001 through 0119 ICD code tuberculosis --- - .- 140 through 199 or In order to provide comparability because the coding 205 of death has changed over a study deaths in terms of at the time of death and period of time we interpret our the revision that was in effect then we convert that code to a seventh revision code number for ease of handling O.K. So we do have comparability We code out the U.S. population and death statistics as published by the National Vital Statistics Division and put them together using that same comparability arrangement We take these death rates for 100,000 population specific for five years age groups and five year calendar time periods and bring them back in and multiply them by the person years at risk in the life table that we just distributed which are now specific for calendar time and age group within dosage and latenc,y if you -and for ease of statistical notation we will YZ 20 say that latency xc lets is age make it group , where a is dose 1 b is cd 20 is calendar time 1 we take that person year at risk times the death rate of the general population specific for age group c and calendar time group b O.K. That generates out the expected numbers of deaths that would occur in this population within age group c calendar time period tize d . latency group 1 if they had experienced the group 1 death rate due to that particular cause of the general population O. Let me ask references you for a question the United what was it sex at States sex race cause age calendar tine Oh so there is age in there Protected Document to Protective order 0012196 JNJ 000048144 JKW JR JKW SS JR SS J.R. JKW JR JKW JR JKW JR JKW Oh yes Age there These is in there sex is in are race sex specific there race race is in How about in these job classifications Is there anything like that Well not at this time here O.K. We'll get into that sub _ clarification at a later time You mean for the U.S. rate . Yeh I'm just trying to get an idea of what these references give The rates for the U.S. don't have any aia a information I see These are just U.S. general white male population rates Yet anything the use of the .S white male population general population as a reference population tends to underestimate what one would expect in a population if all things other than age and sex rate and calendar time were the same The rate in being that a working population consists of people who are physically able enough to seek employment and are medically sound enough to pass routine company medical examinations in order to accepted for employment They are also well enough to withstand the normal rigors of a physical type of employment whereas the general population not only includes many of the same people from that industry but all other industries but they also contain the sickly the people who are in hospitals with diagnosed cancer already who have yet to expire and things like that In addition during general population medical rejects and U.S. population and the war years you tend to find that the in many cases contains many of the things like this which are left in the during those years the population at risk really was continental U.S. not population overseas etc. The use of the general population has been referenced in many articles as producing what we call the healthy worker effect and that is i underestimate of the risk that one would experience if in fact everything other than these nonsense variables were equated Is this information reference available to me in the library someplace What the healthy worker effect No the references that you used for the U.S. Yes they're published vital statistics That's what I would ask for Each year they put out two big volumes on it Protected Document to Protective order 0012197 JNJ 000048145 JR JKW JR JKW JR JKW JR JKN JR JKW JR JKW JR Who puts it out Public Health The U.S. Vital Statistics Division What about the references available someplace for Vermont Are they also There are two different types of references Either you can get population and death from the same volume that we were talking about for many but not as.large an array of causes of death as you can from the U.S. The U.S. breaks out about 251 specific causes of death I think each state breaks 68 or 56. of specific types Its a less detailed of causes of death breakout in or the state terms of Vermont themselves have their own data available I would have to contact an agency in Vermont I would imagine the State Health Department State Health Department and this also has job classifications this state Health Department | No no job classifications The reason being that one assumes that the general population as I said before if anything underestimataensd too that it contains because of the fact that its a large population relative to a very small restrictive geographic region tends to contain all segments of the population and is really in a sense smoothed out in terms of risk factors O.K. Yes I understand When que gets through with this whole array that we are talking about where increments the calendar time and increments the age and then goes in and calculates another expected death and goes all the way through for each one of the cells then we update the cause of death and go into the second cause of death and do all the same sequentially through the vil. When all of this is done we sum over all calendar periods and all age groups within specific latency and dosage cell O.K. The reason being we have now controlled for age the effects of age we have standardized for the effects of age and calendar time and we are really not interested in terms of these as disease causation standardized for and held at constant We summarize over those and then within latency we sum within dosage over latency and we sum over dosage to get our marginal total O.K. You with me Yes Then come you out can the sum your marginal total and they same O.K. which will give you a had better grand total Right of the number of deaths Protected Document to Protective order 0012198 JNJ 000048146 JKW JR JKW SS JKW JR JKW of deaths expected and you can sum your person also Only for descriptive purposes the marginal total person years years in any calculation is statiscaly you in a sense have sacrificed because or purpose the staiscaly staiscaly staiscaly stsatiscaltyiscaly your because they're additive the actual years of grand total person in balance because statiscal y age calendar time consideration O.K. You with me Wel Well Well basically that is the general philosphy were presented by Ms. the behind the Selevan on distribution distribution distribution people that occasion presented the grand total for various causes of death on other occasion presented the the marginal totals to marginal according intervals since onset of employment as we wish to look at look latency O.K. The reason we wish to at latency is if in fact one usually sees or one sees that one has an excessive risk as measured by the ratio of the observed over the expected times 100 which is the SMR early in the game with very short latency latency can one become very latency one suspicious of an occupational risk The reason being that its toward that excessive impossible impossible or very unlikely that one has instantaneous death due to an exposure for a chronic disease Of course there is a problem there there and that is in some instances people were a very exposed ago and it know they exposure very small appears that they have have a long timesince exposure tends tends to very short time a long time long latency where you exposure but they had a be misleading in some cases I would think Well you've got your option in looking at both spectrums dosage and latency O.K. The orignal tables that you've got they latency because the effect was much more It was a ten minute presentation in the just looked at pronounced there final draft we also looked at exposure but that opportunity we just didn't have enough time to give all the data and the pronounced effect was with latercy a ~uch lesser effect as there was with exposure ? Corpses Tl -\" B B ' fK, ~fl ... ACO moos Well one can normally say is that we really don't know takes to really induce a disease either it manifests manifests by its diagnosis and death in but if terms its a chronic disease after a person was of diagnosis and deathdeath is very minimal Certainly all of our population studies to date have de- monstrated that exposed I'm sorry I didn't quite understand that would you repeat that What I'm saying is that whereas your dose group 1 in your SMR latency group would be not expected expected ratio 100 o.k. the of observed over to have an above expected should not exceed 1 the further you get down removed on the latency scale even with the possibility of certain exposure Protected Document to Protective Order 0012199 JNJ 000048147 if there is an affect you would expect to see an increasing relative risk Ratio of observed to expected would increase If in fact there is an occupational ideology and if in fact short term exposure is is rreeallyalreally lyassociated with this phenomena O.K. JR There is another question occurs to me and that is since there you have few people in your sample that you are working I said for example even out kind in with does this change what you've just can understand that if things would lot of people but when you have very few people can you ..can mistakes be made by making that assumption because you just have so few people JKW Well I think one could hood of overestimating basis that the test of distribution take into tend to underestimate but the likeli- of the the risk would be unlikely on the _ significance uses al ? consideration the magnitude | numbers JR Does this test of significance something that you do or is it done by your computer JKW Really we use table Biometrica Volume I Biometrica Table for Statisticians Persall & Hartley Its a standard process that is used internationally in the field JR So given an SMR then you would look in this table JKW Actually the table gives you the bounds on the observed number of cases JR I see I noticed in one place in these tables you made comparisons between the expected number for the Vermont miners and Vermont population excuse me the observed for the miners and the expected for the Vermont as well as the observed for the miners and the expected for the U. S. population JKW We use two different standard populations to generate our expected one the U.S. white male population and two the Vermont white male population JR Did you use the same table to do the analysis and does the | table take into account acount that you are doing multiple comparisons using the same expected number of people the same observed number of people JKW No no Protected Document to Protective order 0012200 JNJ 000048148 JR JKW JR JKW JR JKW JR JKW JR JKW JR JKW JR JR So its like you had several tests pair comparisons with each of the to do and possible you just did Right right Have you adjusted your P values for that at all No no make any relative In this case I would doubt very much if it difference in light of the extremely large risk And this is going to be heresy that would I'm going to state being a School of Public Health graduate of Harvard University both in biostatistics and epid^'- miology but I often view tests of significance to be a crutch that have been imposed upon the statisticians by the incompetent medical profession who are too damn * inadept to interpret their own data I would prefer to biologically interpret the significance of my data as well as the statistical significance of my data I should hope anyone would do that Too often this is not the case The unfortunate thing is people will P values and take them as gospel I with you tend to think I look at am agreeing mo . This basically is why we tend to restrict ourselves to just the 05 and anytime you start getting down to the exact and multiple comparisons its ludicrous Of course times does the sample the fact that you reuse the same sample several tend to make the conclusions more dependent upon and less relevant to the total population It depends on which standard population you are referring to Well I assume that the underlying population is something along the lines of people who are or will be employed in talc mines that's the inference I guess that's being No. I mean in which general population If one does multiple comparisons look at the and looks at the U.S. population Vermont population and certainly the first is says let's an in- dependent step Yes that's trus expect you're you're using the same observed in each case that was my point Could I ask you some specific questions about the people that had died of respiratory causes For example on this listing there are about ten of them where its listed as smoking unknown has this been updated at all is there new information about that Protected Document to Protective order 0012201 JNJ 000048149 -10- JKW JR JKW SS JKW JR JKW SS JR I think there is update going on on it yes Obviously we are attempting to get the complete smoking history as possible However I think one has to see very categorically I would hope red herring that we and let are not going to be using me explain what I mean on smoking as a that Single population consists of approximately 60 x or current smokers that We are not using U.S. white male population rates specifically for smokers and when one tends to say well you haven't considered cigarette smoking and obviously cigarette smoking it is often stated that consideration being given to the type that it must be due to we would without a sizable portion of the general white x cigarette smokers smokers vs. smokers male population are also current and In spite of that fact that we do have and they may differ in quantity of cigarette smoking but there is no data which would support that at present The only criticism I would have of that is that its generally true if you have a that you have a rather small large sample again the fact sample cigarette smoking could be more of an influence than if you had a larger sample even though as you mentioned account small numbers your Pason tables : he take into There are a few other things that I think we ought to consider Since we did break the population down into miners and into millers two independent categories and miscellaneous Miscellaneous both places are mixed categories people who worked in -- O.K. YesI know about that The likelihood of an independent effect of cigarette smoking in the ideology this diseas that we are observing seems very small unless one further evokes the hypothesis that there is job specific smoking patterns within specific corporations in the same geographic area That is why do miners smoke less than millers and if they don't why do we see an excessive risk of malignant respiratory disease in the millers and not the miners Why also cancer in conversely the miners do we see an excess of but not the millers respiratory Well the point is I agree that you can make ca n ask these questions except when you've got only like for example six people who died of cancer and if two or three of them died as a ...... which I don't know but if two or three died as a result of cigarette smoking you know that really affects the sample If you had sixty people and two or three had died as a result that doesn't effect the sample Protected Document to Protective order 0012202 JNJ 000048150 JKW SS SS JKW SS JR JKW JR JKW SS We're not pushing on the lung cancer at the present time We are not making any conclusions its just that you work expect of the consistent excessives patterns if smoking we're observing you is truly the would expect cause the pattern not to be opposite bui to be consistent and they are That's the only point I'm making I'm not drawing any conclusions as to the lung cancer at this point My point is that its hard to see trends when you have few people Well the only trend that we're really is that and respiratory disease It is specifically striking identifying Let me ask you do you have information with regard to length of exposure and period of employment of the other than the ninety four who died I understand people there was a sample of 405 taken Do you have information on these people who are still alive with regard to things like exposure to talc and working history Oh yes They are distributed in the matrix This includes everyone living and dead in that 405 people ? And they are included in the calculation of expected ? Oh yes In order to generate death you have to have people in years and who observe and expected are generatinogf course, All of these that adds up people add up to to more than 94. have 94 there's none of them took it to mean that you : Oh no there are 94 deaths Actually there's a correction there are people without death certificates and we two of those 94 to be alive But its 92 92 we had some had since found now we will have corrected tables Is it possible for me to with regard to length of get i notes dk notes of exposure the living people That information is confidential It will be made available What the living people No No No. He asked for living people of person years You want distribution Protected Document to Protective order 0012203 JNJ 000048151 JR SS JR JKW JR SS JR 00 Well which what I would like is that gives me a distribution as exposure would be helpful something to the regard to the You don't workers want actual individual information about individual No I don't need regard to length of employment of history of those that I'm interested in distributions with of exposure of live people and also period live people and if possible the smoking live people We don't have smoking histories of live people Is it possible for me to get that or can I come and pick it up or can you send it to me Can I ask another question while you are deciding First of all we do not have cigarette smoking habits patterns among the surviving O.K. Many of the surviving people no longer are regularly employed with the companies in question some of them are dispersed throughout the U.S. and I think we run into a severe problem of privacy in addition to the possible harrassment of individuals trying to go back and evoke this type of information Its cumbersome O.K. so don't give me their names I don't want What about the length of exposure tables which length of for for living exposure people for Are living people and those available period them summarize of employment Well if you wanted you nothing but work history could have in it It identifiers we would blind out any could give you that a master file that has won't have any individual personal identifiers we That ages need would be fine I don't care to know their names Their would be nice or distribution of their ages I don't the raw data I can get by with summary data A life table has the number of person years per age group we've got all that kind of breakdown the person years rather than specific flow for each person in the various life span exposure category so that you could get that indirectly from the life table It would be much less complicated that way These are available to me the life tables Well they certainly will be made available when we have our general meeting here O.K. Protected Document to Protective order 0012204 JNJ 000048152 JR SS JKW JR SS JR SS JR The point is I've been asked by someone who I have to rely on to pay my salary you know to get this information Is as quickly as possible and to try to make some head and tail out of it Is it possible that I could come there or you the could send me this kind of information about either living or everybody in terms of these life tables or both Pause While you are thinking can I ask you a second question about this Wait a second we'll try to work this one out Go ahead shoot your second question There are number of 405 people that you talk about is this the total people that were available or is it a sample Irom the people \ It's the total number of people with who worked a minimum \ of one year with at least one day of that time between 1940 | January 1940 and the current year has to be before ; 1970 and one day of that time had to be at least one day of that time had to be after 1940 So as far as you know it's a complete census as opposed to sample It's as a matter of fact probably well it's as complete as we can get considering data the Health Dept. data as they had in their the problems with the company data what with the Health Dept. data a greater percentage of the people with the greater exposures and the companies more names but the additional names all seemed to be had those people who worked much less than a year like two weeks The companies also were missing quite a few of the people who worked there longer periods of time and we think that this is probably due to the sketchy work histories kept in some of the companies in the past 2 the fact that the companies have changed quite a few of them have changed hands several times and the records were lost in the changes but we ultimately went more reliable of their with own the and Health Dept. records there were originally they're 826 people in the described Health Dept. and 405 fit our criteria , as is oo I can continue asking questions if you want to continue thinking about the other one We've been trying to get a hold George Lee has been trying to a hold of the death certificates of the people who died and he would like to know if you could provide the information with regard to the state in which the death is registered for three people If I give you those could you find those out..tell me Protected Document to Protective order 0012205 JNJ 000048153 JR SS JKW SS Which people One is Treffeley West Shall I continue or wait Treffeley West Who else The second one is Guyett Daniel his third one was Reil the first name is first name Edson and the O.K. I can get that information for you it with me right this second I'll have to our original file I don't look it have up in George asked me to ask a second question with regard to these respiratory deaths he noticed that in your transcript you mention that you had excluded people who had died from influenza and pneumonia and he notes that peo fop r pl eope le on the list of malignant respiratory deaths who were listed as dying from pneumonia or some Its a coding It's coded by the underlying Any causes death for the immediate cause of pneumonia but that's not the underlying cause of they die cause of death instantly death and that's not the way they're coded by nosologist a qualified nosologist The tables that I sent you where it had and the coding that coding by a there's either three or four professional nosologist columns depends on how many causes we found on them prime cause there's contri- butory case 1 contributory cause 2 contributory cause 3 and the -. .. . is the cause of death ~.. _. ~ classified under As an example congestive heart failure due to due to chronic fibrosis of the lung It would out necessarily as congestive heart failure influenza not be coded It would be coded under the underlying causes | JR That's the ICD column I think that's it Is that the first cause of death JKW JR The first cause on the death certificate underlying Yes that's what the column ICD contains JKW Yes And then ClC and C are Contributory cause 1 contributory cause O.K. I understand Protected Document to Protective order 0012206 JNJ 000048154 SS JR JKW SS JR JKW JR So although the immediate cause of death might be pneumonia pneumonia might be a resulting factor from something else and in these death certificates they all were at least according to the physician who attended the patients O.K. Well I'm out of questions now What can we decide about getting this other data I'll tell you George would really like to come out there he's asked me several times he said that I should press that point I don't want to become offensive to you Yes well let me explain my position on this Our general feeling is that we certainly don't intend to shy away and certainly would be more than receptive to interact with other people in the wish to be put in a scientific community However we don't position and we refuse to be put into a position of dealing differentially with management and labor and my general feeling is that since there are multiple corporations involved from multiple corporations there has been multiple requests I would prefer that other than what we're really talking about here that we refrain from any further distribution of hard raw data pending the joint meeting of both management and labor and any consultants that they wish to bring to very candidly go over and discuss our interpretation of the data the analyses any questions that of this nature or for brought may be resolved obviously are to tend up Meetings a briefing of our feeling our interpretation of the data answering any any questions and illiciting opinions that may be certainly scientifically sounded we have no corner on the market of course but reserving the right to interpret the final data as we so fit consistent with good scientific inter- pretation and its in that sense that I'm a little reluctant to openly essentially dump our computer volumes that are least three to four inches thick a computer dumpout four of them Possibly duplicated pages I means it's hundreds and hundreds of From my personal point of view the was asked to attend such a meeting problem is that if I and I probably will be it would be very beneficial to me if I had been able to look at the data before going to the meeting otherwise it would seem to me that people would have to take what's given at the meeting go back and digest it and then come and ask for a second meeting so our point of view is that we would like to get as much information as possible before the meeting so that we can come prepared to discuss our feelings at that meeting Can I ask you a question briefly Sure Protected Document to Protective order 0012207 JNJ 000048155 JKW JR JKW JR JKN JR JKW JR JR If you came to a scientific rence do you leave the scientific conference with the feeling that you had to see somebody's basic raw data and before you arrived at a judgem entire distribution as to the validity of that data and interpretation sultant for the company Come Forget on that you're a con- ; When I go to a understand it so that I have a conference I usually five minutes to take what's go home and study it like crazy what is necessary to understand in pursuing it further get in gave the talk and pursue it that I would I wouldn't certainly somebody a liar or anything like a paper I usually don't minutes after they start I'm lost given in terms of hand outs and and look up in the literature it and then if I'm interested contact with the people that point is go to a that I really can't say meeting and call Well I'm not asking about liar guilt Scientific protocol I'm just talking about Generally if I go to a meeting other than a statistical kind of conference and people present statistical it's my experience that I should question that data I'm not saying you obviously know a so I'm certainly not lot more than I do about this subject questioning you but that's my basic feeling I tend to question data when people do statistics because I've seen so much misuse of it I don't deny that It's too much garbage in garbage out My point still is if I have to come to a meeting whereby I'm going to talk intelligently about important work that's being done I would like to have information before that as opposed to coming in cold and having to say well can we talk in a week or two weeks when I've had a chance to digest the information Well I'll tell you what you tell Mr. Lee that one we will be sending a copy of the paper out at least a week before the meeting o.k. and two at that time with descretion we will provide = couple of pertinent matrixes to give you the answers that you're you're really after You couldn't send them before that time talking Well basically we're talking within essentially a week and about getting the paper days right now so out we are not talking about any les o.k. The thing is that we've attempted to crank up this mes to occur as fast as we can however in light of th 7 titive requests that have come in from Windsor Minerals Minerals inson & Johnson & Engelhard I suppose everybody is doing the same thing Protected Document to Protective order 0012208 JNJ 000048156 JKW JP SS JKW JR SS JR If they wish to manuscript then have the meetimeetning meetging and wish to have the you're going to to have to sit back and let us finish it o.k. What back will about these three death certificates now can I call or have George call back to get that information or you send it to us We'll send them out We'll send them out we can send them Do you have an address there that I can give you my address it's John Rafter Johnson & Johnson Research Center New Brunswick N.J. 08903 So that's Johnson & Johnson Research Center New Brunswick N.J. 08903 and your phone number Area Code 201-524-5087 Protected Document to Protective order 0012209 JNJ 000048157