Re: Definition of Epidemiology

[muckerheide@highway1.com (James Muckerheide)]

Daniel J Strom wrote:
 
> BLC =3D Bernard L. Cohen <blc+@pitt.edu>
> DJS =3D Daniel J. Strom <dj_strom@pnl.gov>
> 
> >>>> BLC: I am not sure that my work should be called "epidemiology."  
> 
> It is a test of a specific theory. Tests of a theory are at the heart of 
> "the scientific method" and apply rigorously to all of science. The 
> baggage attached to ecological studies does not apply to, or affect such 
> a test.
> 
> >>>> DJS: Definition of Epidemiology.  The study of the distribution and 
> determinants of health-related states or events in specified =
> populations, and the application of this study to control of health =
> problems.  "Study" includes surveillance, observation, hypothesis =
> testing, analytic research, and experiments.  "Distribution" refers to =
> analysis by time, place, and classes of persons affected.  =
> "Determinants" are all the physical, biological, social, cultural, and =
> behavioral factors that influence health.  "Health-related states and =
> events" include diseases, causes of death, behavior such as use of =
> tobacco, reactions to preventive regimens, and provision and use of =
> health services.  "Specified populations" are those with identifiable =
> characteristics such as precisely defined numbers.  "Application to =
> control..." makes explicit the aim of epidemiology - to promote, =
> protect, and restore health (Last 1995).

All semantics: Bernie seems to distinguishe "epidemiology" by whether it
proposes a health effect relationship, vs the specific mathematical test
of data and model; Dan seems to say if the math testing is about health
effects, its epidemiology. Again, the only "scientific" issue is the
data, not the semantics.

> >>>> BLC: It is a test of a specific theory.  Tests of a theory are at 
> the heart of "the scientific method" and apply rigorously to all of =
> science.  The baggage attached to ecological studies does not apply to, =
> or affect such a test.
> 
> >>>> DJS: Dr. Cohen has not convinced me or other critics that "the =
> baggage attached to ecological studies" does not apply to a study for =
> which there are no individual exposures, no individual confounder =
> measures, and no individual bias measures associated with individual =
> health outcomes.  =

Then Dan seems to leap from the semantics that this is "epidemiology" to
presume that "the baggage", which is the weakness of ecological studies
to produce dose-response models, (read again Stidley & Samet and others
about the "ecological fallacy" - it does not say ecological studies are
invalid, it only says there are potential weaknesses and, especially,
that **in the case of the lack of dose-response at low doses** the
relationship can not be taken as reflecting a valid dose-response!
Bernie addressed all of the *identified* weaknesses of ecological
studies as they apply to the data and statistics of his study, and
considered their implications. He reflects the significance, and
potential significance from the recognized uncertainties, of those
factors, and has asked for any additional substantive contributions to
explain the data, and to assess uncertainties. In the absense of any
considerations that have been shown to affect the relationship beyond
noise level (even the effect of eliminating the population of CA, AZ and
FL to reduce the influence of retirement migration had small influence
on the statistical results: note that the database is massive, which has
a great impact on the lack of effect of variables that confound small
ecological and case-control studies.) Dan also refers to the few
"critics" that just ignore the data in the interest of the result.  

> See Figure 3 of Lubin and Boice (1997) for an example of how Dr. Cohen's  
> results are statistically rejected by more cogent studies.

It doesn't seem that the stretch in logic and mis-use of small-studies
data, mischaracterized as "more cogent" :-) "reject" Cohen's results
flys in the face of the data.

> >>>> BLC: I have clearly shown that testing a linear- no threshold =
> theory does not require data for individuals.  If Strom disagrees with =
> these demonstrations, he should say specifically why.  I can very easily =
> explain why data for individuals is needed to determine a dose-response =
> relationship; why can't he explain why data for individuals is necessary =
> to test an LNT theory?
> 
> >>>> DJS: The county radon measurements made long after many of the =
> cancer deaths apply only weakly to the individuals who died of lung =
> cancer in those counties.  Most importantly, many other causes of lung =
> cancer (i.e., confounders) that may be associated with (covary with) =
> geographic location, e.g., air pollution, different genetic make up, and =
> lifestyle factors (especially smoking), cannot be controlled in any =
> meaningful way despite Dr. Cohen's attempts and his claims.  Dr. Cohen's =
> study is useful for generating the hypothesis that radon exposure is =
> causally related to lung cancer (one way or the other).  That hypothesis =
> has been, and is being, tested by more cogent epidemiologic methods.  =

This doesn't hold up under thoughtful consideration. If the objective
observer thinks about comparing the "population dose estimate" to the
typical "estimated dose to an individual" in a small-sample (even
few-thousand) case-control study, you realize that the same
considerations apply: most are monitoring radon today for a lung cancer
patient that says little about where the individuals really spent their
time and their exposure over the last 10-20 years. Those variations are
typically very large (except in a study like Blot in China where the
women are much less mobile with a full year of radon monitoring in both
of the primary living areas of the homes - with negative correlation;
and involved the US National Cancer Institute who probably had less
opportunity at that point to suppress publication than a US study :-)).
That's why most case-control studies are essentially indeterminate,
though not reported that way. 

Note that this lack of knowledge, the uncertainty, about the real dose
to the individual is not considered in the normal statistical variation
that is reported in the case-control studies. The variability of dose
based on radon-monitoring estimates to each individual is much larger
than the normalizing effect of the dose estimate to a large population,
with millions of people and 10,000s of deaths, in which the "dose
estimate" reflects one relatively stable "sample" in a large continuum
of radon exposure, and a large continuum of lung cancer deaths, that
reflects the mean in a county (that doesn't move much, though building
standards "could" have an effect on changes in home radon estimates over
the years, but which have been shown to be very small (houses may
change, but again, the "housing stock" doesn't; it, like most macro
variables, change only very slowly with time). 

See Norm Frigerio's 1973 discussion of the statistical basis for
recognizing that even with 17 years of death statistics, they represent
the statistics of generations in the absence of significant change
(clearly atmospheric weapons tests did not change population doses,
etc.) Of course smoking is such a change. Without smoking, lung cancer
mortality is 2-3/100,000 as Rosalyn Yalow and others note. Smoking is
the kind of change that shows up in ecological studies. Just like
chemical pollution shows up in ecological studies, (in France, Doucet
shows that urban chemical pollution effects the population in the same
study that shows a negative correlation with radon concentration). In
radon spa areas, and in the Chinese studies, the negative correlation is
also confirmed, but usually not statistically significant in smaller
populations with less variation in smaller geographic regions where
variations in doses to individuals are less distinct. Individual
movements and differences in lifestyle significantly affect the
"average" and variability in small populations that wash out
distinctions, but affect much less averages and variability in large
populations in larger geographic areas with more significant differences
in mean doses.

Again, all of this reflects "considerations" for the validity for a
particular study with particular data. NONE of it says, nor even did
Samet and and others, that ecological epi studies are invalid. Thousands
of eco epi studies have produced meaningful data, that confirm and are
confirmed by related work, as noted above. Bernie rightly recognizes
that his study is more powerful and more definitive and with more
assessment of confounding factors - technically more robust and
well-founded - than typical eco epi studies. But to discuss weaknesses
and limitations in terms of questions about "modeling results" **on
conditions that apply to no effects at low doses**, then characterize
the entire methodology as invalid to prevent honest consideration of
this particular study, is especially "un-scientific".
 
Of course all of this is only one small part of one leg of the stool
that includes the lack of substance to the miner data, the animal data,
and the human histopathology that refute the possibility that lung
cancer can be caused at low doses of radon. All of that data is ignored
when arguing that we can't know what "shade of white" Bernie's data
represent, we are justified in assuming that we should call it "black"
(and, oh by the way, I have a lot of self-interest in selling black
paint :-)


> These simple statements have been made repeatedly in print (see, e.g., =
> Lubin and Boice 1997), but Dr. Cohen doesn't accept them.  His =
> persistence doesn't change the truth of the simple statements.
>
> See Lubin and Boice (1997) and Lubin et al. (1997) for good recent =
> discussions.  Stay tuned for BEIR VI, due out this spring.  =

It seems they "announced" their conclusions last spring at the BEIR VII
workshop (even at the NCRP meeting). Lubin was noted stating that they
would "destroy Bernie Cohen". They are committed to continuing the
charade. More of the same. Close the doors to science and satify EPA
funding direction. See Walinder, Jaworowski, and others, who have
reported from ICRP, UNSCEAR, etc on what Walinder kindly calls "not a
question of fraudulent manipulation but, again, it has to do with our
conviction that if experimental or epidemiological results do not agree
with the doctrines - ... there must be something wrong with the
investigations and, therefore, the results have to be corrected." :-)  
and his conclusion that "I do not hesitate to say that this is the
greatest scientific scandal of the century". With Lauriston 

> Lubin, J.H.; Tom=E1sek, L.; Edling, C.; Hornung, R.W.; Howe, G.; Kunz, E. 
> Kusiak, R.A.; Morrison, H.I.; Radford, E.P.; Samet, J.M.; Tirmarche, M.; 
> Woodward, A.; Yao, S.X.  Estimating Lung Cancer Mortality from =
> Residential Radon Using Data for Low Exposures of Miners.  Radiation =
> Research 147(2):126-134; 1997.

Reflecting $Millions in EPA, DOE, FDA funding, including whole academic
departments and programs, with some leading the list on Steven Milloy's
"junk science" home page, with a special question about how a Samet can
come from no academic or scientific substance except for his radon junk
to have $millions to be "found in a nationwide search" to head the Dept.
of Epidemiology at Johns Hopkins U.; like Howe suddenly moving to
Columbia U. to head the program that DOE "annouced would be reassigned
the RERF program from the Nat. Acad of Science, as though RERF doesn't
already bias and obfuscate the data enough :-)  

RERF learned well from DOEs termination of the Argonne "Center for Human
Radiobiology" following the 1983 HPJ (44, Suppl 1) on the Radium
Conference (where Robley Evans concluded that all the data, with 1000s
of cases developed in the 70's and int'l work, confirmed the conclusions
of the smaller programs, esp his 600 cases at MIT, that there are no
effects <50 uCi systemic uptake, ~1000 rad to bone) what happens to the
funding of those who fail to adequately obfuscate the data. 

RERF's secrecy, control and manipulation of the data is becoming
increasingly visible, especially now that it has become even more
important as essentially the sole source of support to the linear model
(even though the basis for applying essentially unknown atomic bomb
exposures, with neutrons, etc, with massive unresolved confounding
factors to chronic exposures down to mrem levels, and even with bias in
ascribing deaths to 'radiogenic causes', and complete secrecy in the
data, even to the BEIR analysts). The addition of 10,000 new cases to
the recent "analysis", with no review, and no outside access to the case
data, and "instant acceptance" by the linear model apologists in ICRP,
is "fascinating". :-)

> The opinions expressed above are my own, and have not been reviewed or =
> approved by Battelle, the Pacific Northwest National Laboratory, or the =
> U.S. Department of Energy.

> Daniel J. Strom, Ph.D., CHP
> Staff Scientist


Regards, Jim Muckerheide
jmuckerheide@delphi.com