Re: Radon and Lung Cancer

[Bernard L Cohen <blc+@pitt.edu>]

On Sun, 12 Mar 2000, Otto G. Raabe wrote:
> 
> As I understand Jay Lubin's point about Cohen's data, in an ecological
> process it is mathematically possible to consistently obtain an overall
> inverse correlation between radon in countries and lung cancer rates
> (Cohen's results) even if the dose response relationship for radon is LNT
> if there are regular complex interactions (cross correlations) among the
> various factors that contribute to or hinder lung cancer rates. This
> mathematical possibility exits even if we don't understand the nature of
> these interactions. Hence, I believe Lubin is saying that we cannot be sure
> that Cohen's results show anything but the results of these complex
> interactions between all of these factors. The factors themselves may look
> straightforward, such as age and associates radon exposure history, smoking
> history, environmental factors, available medical services, economic and
> employment factors, etc. Even though we might understand these various
> factors by themselves and separate them out (stratify the data), the
> complex cross interactions of these factor may me difficult to interpret or
> predict and may continue to affect the results. In a case-control study it
> is theoretically possible to control for know factors. 

	I have always understood these problems, and even give examples in
my papers of cross level biases that could explain my results. However, I
show in my papers that the required assumptions are very highly
implausible. Lubin's mathematics show that such explanations are possible,
but say nothing about their plausibility. The only way to test
plausibility is with specific examples
	As any theoretical physicist will tell you, if a general principle
is derived mathematically, it is always easy to devise specific examples.
That is why I am seeking specific examples of explanations so I can test
their plausibility. If the proposed specific examples are very complex
(which, in itself may strain plausibility), it may be very difficult for
me to analyze them for plausibility, but that is my problem. I only ask
for proposals of specific explanations that are plausible enough to be
accepted for publication - I have no control over that.
	I would bet that I could figure out complex interactions that
would invalidate any case control study. They don't consider anything
nearly as elaborate as what is suggested in Otto's message.
	I could go further and similarly challenge all of epidemiology. A
disease develops as a result of thousands of complex interacting
biological factors, and epidemiology does not even attempt to consider
their effects. It blithely assumes that these things average out in
considering their study group. How can epidemiologists then take this
"holier than thou" attitude toward my study?
	


> 
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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