The original 1997 Reward Post

["Richard L. Hess" <lists@richardhess.com>]

I was reading this thread about $2500 rewards and found this Jan 17, 1997 

post which appears to be the original. Of course, it may have been modified 

later. It's easy to find the archives in Google...and they're easy to use.



I would be less interested in a data file than in a two-page summary of 

this work and the follow-on work. Dr. Cohen's web site is too daunting for 

someone who is not in this field.





·       To: internet RADSAFE <· radsafe@romulus.ehs.uiuc.edu>

·       Subject: $2500 award

·       From: Bernard L Cohen <·        blc+@pitt.edu>

·       Date: Fri, 17 Jan 1997 12:43:46 -0500 (EST)



         My offer of $1000 awards for help on the following matter did not

prove fruitful, so I am raising the award to $2500 and will try to explain

in more detail what I am seeking.



         In the February 1995 issue of HEALTH PHYSICS (vol.69, pp157-174),

I published a paper entitled Test of the Linear - No Threshold (LNT)

Theory of Radiation Carcinogenesis.....    in which I reported that lung

cancer mortality rates for U.S. Counties, with or without correction for

smoking prevalence, decreases rapidly (about -8% per pCi/L) as average

radon exposure increases. This represents a very large discrepancy (20

standard deviations!!) with the prediction of LNT theory that lung cancer

rates should increase rapidly (about +7% per pCi/L) with increasing

average radon exposure . My problem is in understanding this discrepancy.



         I have examined the effects of over 60 confounding factors, and

have done many other tests, but this work has done little to explain our

discrepancy. I have gone through the literature on Recological studiesS

and can easily show how the results of any other published ecological

study can be erroneous, but I cannot figure out how one can avoid

concluding from our data that LNT theory fails in this low dose region

where it has never been tested.



         What I need very badly is suggestions for not implausible specific

potential explanations for our discrepancy, in at least semi-quantitative

numerical terms, on which I can carry out calculations to determine if

they can resolve it, or can be modified to resolve it. As a possible

example, one might suggest that urban people smoke more frequently and for

unrelated reasons have lower radon exposures than rural people, both of

which are true. What I need is data for each of our 1601 counties on which

to do calculations to see if they resolve our discrepancy. You can make-up

the data, as long as you consider them to be not implausible. Since I need

these made-up data for each of the 1601 counties, it might be most

practical to give me a prescription for deriving these data. For example

you might say that the radon exposure for a rural person is x% higher than

for an urban person and an urban person is y% more likely to smoke than a

rural person. Since I know the average radon level in each county, the

fraction of people in each county who are urban and rural and the fraction

that smoke, I can then determine the predicted lung cancer rate in each

county from BEIR-IV for various values of x and y, and make comparisons

with the data.



         The only problem with this example is that I reported calculations

based on it in Section L of my paper and it did very little to reduce our

discrepancy. But you might not agree on how I did the calculation and

suggest an alternative method, or you can suggest some alternative

prescription for making up the data, perhaps utilizing random numbers or

anything else you can think of that will allow me to do calculations. Or

you can just present me with tables of numbers that you consider to be not

implausible.



         I offer a $2500 award to anyone who submits a suggestion that,

after a detailed evaluation, leads to a not-implausible explanation of our

discrepancy. I can give up to three such awards. If the submitter and I do

not agree on plausibility, I would be happy to accept the public judgement

of any prominent radiation health scientist suggested by the submitter

(letUs define prominent as 10 papers in HEALTH PHYSICS or equivalent

journals over the past 10 years). I would hope to publish a paper on this

with the submitter and judge as coauthors, but in any case, the $2500

award will be paid promptly.



         Of course the urban-rural effect discussed above was meant only as

an example; any other ideas would be equally acceptable. Alternative

suggestions for implementing my offer would be most welcome. I really need

help on this problem.



         If anyone would like a copy of our data file, I would be happy to

provide it.



Bernard L. Cohen

Physics Dept.

University of Pittsburgh

Pittsburgh, PA 15260

Tel: (412)624-9245

Fax: (412)624-9163

e-mail: blc+@pitt.edu





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