Linear Model

[JMUCKERHEIDE@delphi.com]

Wade Patterson writes:

> 4. The paper by the IARC study group on cancer risk among nuclear industry
> workers, Lancet, 344:1039;1994 fits the data to a linear model and therefor
> cannot be used as an argument for the validity of the linear model. (not
> unless you believe one can pull himself up by tugging on his bootstraps.)

The following summarizes the fallacy produced by the IARC in its desperate
effort to support the linear model. 

Regards, Jim
-------------------------------

Professor Emeritus Myron Pollycove, MD, notes that a recent
report by the International Association for Research on Cancer
(IARC) similarly misrepresents dose-response data to report a
"linear model" result. The IARC report chooses to ignore data
that shows lower risk, i.e., a risk decrement. 
   First, in this combined occupational exposure group it chooses
to ignore the most accurate data, the Nuclear Shipyard Worker
Study compared to the early weapons facility workers with the
questionable dosimetry and confounding factors in their exposure
data. 
   Then, in a population of 15,825 total deaths, IARC reports on 119 
leukemia deaths, that excludes non-radiogenic leukemia. The data
show that there are 60 deaths observed with 62.0 expected for
doses of less than 1 cSv, and there are 59 deaths observed with
57.0 expected for doses greater than 1.0 cSv (Table 2). Clearly,
there is no excess leukemia found in this data.

Table 2 IARC Observed/Expected leukemia 
(except CLL) mortality 
(119 deaths in 15,825 total deaths)

Cumulative     Deaths
dose (cSv)     Obs / Exp

  0-           60 / 62.0
  1-           19 / 17.2*
  2-           14 / 17.4
  5-            8 / 9.0
 10-            8 / 6.4*
 20-            4 / 4.7
>40             6 / 2.3*

>1             59 / 57.0

   Dr. Pollycove notes that the IARC report states explicitly in
the Statistical Methods section that they applied (they presumed)
the linear model across 11 dose categories, and that "As there
was no reason to suspect that exposure to radiation would be
associated with a decrease in risk..., one-sided tests are
presented throughout." This states that they explicitly ignore
all contrary data, even within the context of such statitical 
small-numbers results.
   For the table, the eleven dose categories were collapsed to
seven, resulting in greater-than-expected leukemias in three of
the seven dose groups (the * groups in Table 2). Since only
positive data are allowed to be considered, ONLY THE DATA FROM THESE THREE
GREATER-THAN-EXPECTED DOSE GROUPS ARE USED, even though these dose groups are
not even contiguous. Since the selected data are not significant, the IARC
performs a Monte Carlo calculation on 5 000 trials (effectively multiplying
the data by roughly a factor of 100) to "find" that the results show

a "significant" linear dose-response "trend".
   This fallacious "result" was then the subject of a world-wide 
media campaign, reasonably reported even in Nuclear News, 
that the "linear model" is "confirmed". This report was widely 
distributed long before the data and analysis were published 
and available for review (similar to numerous other media 
campaigns designed to foster public fear of radiation).
   IARC also similarly reports that the _44_ multiple myeloma
deaths are "found significant" (with very few in any dose 
group). They note that this is "attributable primarily to the 
associations reported previously ... in the Hanford and 
Sellafield cohorts." This note indicates that they are aware, 
without so stating, that this "association" is not found in 
other cohorts and is generally considered to be erroneous 
in these studies, consistent with the weakness in the 
dosimetry and the confounding effects. (The study also reports
that cancer relative risk is 0.99 and leukemia is 1.22 at 10
cSv.)
   These are the sole bases for the "conclusion" that the IARC
study finds that the data is consistent with the linear model. 
IARC is blatantly abusing science to achieve the results
desired by government bureaucracies.
   Clearly, if all data were considered by IARC without
arbitrarily excluding contrary data, and presuming the linear
model to represent the data, the mortality data in these combined
populations do not support the "linear model." As Dr. Luckey has
found, objectively examining all the data in each of the cohorts
indicate positive/beneficial effects for the exposed populations
exposed above negligible doses. This result can be reasonably 
expected to result in a positive (beneficial) effect in the combined 
populations. The IARC, consistent with BEIR, NCRP and other 
government data presentations, capriciously misrepresents the 
data to conform to the costly radiation protection policy mandate.

>Jim Muckerheide, ANS Biology and Medicine Division
dents in radon spa areas show less-than-normal cancers and
other adverse health effects.< 

   Professor Emeritus Dr. Sohei Kondo presents data that show
significant cancer reductions in Misasa Spa area residents in
Japan who live with continous exposure to very high radon
concentrations, as shown in Figure 5. Extensive data from high
radon water areas throughout the world, especially in Germany and
the central European region, show equivalent results. These data
contradict "linear model" projections at low-to-moderate (and
even relatively high) radon dose levels.

>Lung cancer data by US county show a negative correlation with
indoor radon levels.< 

   Dr. Bernard Cohen, and Professor Emeritus Myron Pollycove, MD,
present the data from 272 000 home radon measurements, in 1759 US
counties (covering more than 90% of the US population.) The data
show a highly significant, very strong, NEGATIVE correlation of
lung cancer rates with increasing radon levels, for males and
females, with and without a correction for smoking (Fig 6). The
study resolves all identified potential confounding factors, and
shows that any unknown confounding factor that could change the
relationship would have to exceed the effect of smoking on lung
cancer, and be in direct negative correlation to radon
concentrations. 
   Dr. Cohen and Dr. Pollycove note that the study also
demonstrates that the "ecological fallacy" does not apply for a
no-threshold relationship. The actual data also dramatically
refute the "linear model"-predicted health effects which are
extrapolated over orders of magnitude from the early, incomplete,
and confounded, uranium miner data.
>Jim Muckerheide, ANS Biology and Medicine Division