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IARC Study Review
Response to comments by Will Atkinson:
Will, Sorry about the delay. Wanted to go back to the article then -- just
too much going on.
> Just got back from vacation to find Jim Muckerheide's report of
> Professor Pollycove's critique of the IARC Lancet paper waiting for me.
> Ploughed through all the rest of the email confident that someone
> would have corrected all the mistakes. Since noone has, here goes:
No mistakes to correct ? :-)
> >... 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 IARC study fits data to a linear model for a low dose population
> and compares the excess relative risk (ERR) per Sv with that obtained
> from a high dose population (the Bomb survivors). If risk was non
> linear over the whole dose range and the studies had sufficient power
> we would expect the values to be significantly different. This is a
> perfectly valid approach. In fact the IARC ERRs are not significantly
> different from the Bomb survivors, but the study team don't make much
> of that because of the low power of the study.
This isn't accurate. First, they _presume_ linear results in analyzing and
reporting "effects/Sv" no matter how "non-linear" the data. See the
radium-burden populations, the bomb survivors, the TB flouroscopy populations,
etc. When they do that to 2 data sets, there is no effect to be found in
examining the "difference".
And actually the ERRs are not "significantly different" than either twice the
bomb survivors or a negative correlation. But that didn't stop the false
reporting of results and an international media campaign from announcing from
the Nature article on that "we have confirmed the linear model" and "we have
found consequence at low doses" !
> > ... 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...
>
> The IARC study is not a review paper. It combined data donated to it
> by the Nuclear Industries of three countries most of which was not from
> early weapons facility workers. Considerable efforts were made to
> standardise the dosimetry over time and between employers.
Not industries. By the governments and its agents with a policy to support,
and this NSWS data is DOE's, a $10M effort with 70,000 workers studied
representing 700,000 workers is explicitly constrained from being included.
Maybe IARC didn't have a choice, like most workers in this area, it can claim
it was manipulated by government constraints in the data to be considered,
though it could have objected or noted the lack of completeness of the data,
if it were really looking for the definitive results (but from the analysis
its clear they weren't).
> >..., 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...
>
> I would question the use of one-sided tests myself, but it certainly
> doesn't mean that they ignored all contrary data in the sense implied
> by the quote below:-
>
> >... 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.
Sorry, it's their own Methods Section, and though as you note, my conclusory
statement is not strictly true, I note that it IS the practical effect of what
they do.
> This is just plain wrong. I assume it is a bizarre misinterpretation
> of the effect of one-sided testing.
It's the practical effect of what they do to show a trend.
You should have included/responded to the table (extracted from the paper
Table III, please confirm the accuracy of the extracted data if you have any
doubts) which shows the prima facie case that there is no increase in leukemia
mortality data except ABOVE 40 cSv (unless you JUST take the positive Obs/Exp
data).
(Why did you delete the data? I was going to put it back here to refer to, but
time is fleeting :-) [ For reference, I decided to append the original
article and data below. ]
> >...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 is equally bizarre! The Monte Carlo simulation was done to
> calculate the probability of obtaining a trend as large as observed by
> chance. Compared to the alternative of using the normal approximation
> it REDUCES the chance of seeing a significant result.
Again, address the data. In this case you will find in the table that the
effect is to create significance where there is none. What "trend" is seen "by
chance" EXCEPT by selecting only the positive dose groups?
This doesn't even include small things like changing doses by 20% without
justification beyond that they "judged that bone marrow doses were
overestimated by 20%", increasing the basis for showing a positive trend. And
wondering about the effect of collapsing the analysis of 11 dose categories to
7 dose categories without any explanation. (And many other quizzical elements
that are not explained though no shortage of space for a rather rambling and
redundant statement and restatement of conclusory remarks.)
> > 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.
>
> This just sounds like right wing politics rather than science.
That's easier and more effective than addressing the data.
But it does explain the basis for responding to the politics and funding that
cause these national bodies to create and support the justification for
government authority and funding and public expenditure by fostering public
fear, including the intensive media campaign to get these intentionally
misleading results widely distributed before the data is available. (And of
course, even with this fairly voluminous report, most of the essential
machinations are glossed over begging the matter of the actual data and
analysis in the internal report.)
However, in the first analysis, its the data and its lack of support of the
conclusions, that is the first cause. It would help if you could explain the
reported data as it is proposed to support the finding of a linear "trend".
Note: if we exclude >40 cSv (as they note, the range in which the Japanese
survivors show excess leukemia deaths -- and I note, BEIR V says the survivors
have NO excess leukemia below 40 cSv (p. 242), and leukemia is LOWER than
controls below 20 cSv, which is then also erroneously reported as a linear
result to support rad protection at very low doses), then the total mortality
for 1 - 40 cSv is, I believe, (you might want to check) 53 Obs to 54.7
Expected ! LOWER than expected (and remember that 0 - 1 cSv is 60 Obs to 62.0
Exp. You could combine them: 113 Obs to 116.7 Exp. So at > 40 cSv, 6 Obs vs.
2.3 Exp is ALL the data that shows an excess (and I'll stipulate that we would
expect an increase at > 40 cSv; BUT NOT BELOW), that is what is found. YET,
IARC does the typical magic of finding effects at a few mrem ! And
campaigning it, fostering unjustified public fear and supporting horrendous
rad protection costs to a few mrem !
When effects/Sv are reported, it is just the invalid presumption of linear
taking high dose effects and assigning them to low dose despite the data. I
guess we could debate whether this is malicious or just ignorant, but... I
don't think _everybody_ here is stupid.
What more would it take to show that there can be no "linear dose response" in
this data, unless it were "rationalized" from some extreme ("heroic") efforts.
And that only makes sense when there are great pressures to support the
funding agencies who are explicitly clear on the only acceptable result. (And
of course, clear knowledge of the fate of people and programs and careers of
most of those who choose not to 'go along'. But since there's no one else
funding any work, at least that is not also subject to substantial government
control, their are few if any who have the programs or resources to
substantially criticize the results.)
> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
> These are my views, not my employer's
>
> Will Atkinson Internet: will.atkinson@aeat.co.uk
> Health Effects
> AEA Technology, 364 Harwell, Didcot Phone: +44 1235 434370
> Oxfordshire, OX11 0RA, U.K. FAX: +44 1235 432134
> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
And you know no employer supports my views :-)
Thanks. I appreciate your response.
Regards, Jim Muckerheide
----------------------article extract-----------------
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 their
questionable dosimetry and confounding factors.
Then, in a population of 15,825 total deaths, IARC reports on
119 leukemia deaths, excluding 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
* groups where Observed is greater than Expected
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.
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 "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.
IARC also similarly reports that the 44 multiple myeloma
deaths are "found significant", noting 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.
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,
a result which would be reasonably expected to result in a
positive (beneficial) effect in the combined populations. The
IARC, consistent with BEIR, NCRP and other government data
presentation, capriciously misrepresents the data to conform to
the costly radiation protection policy mandate.
-J. Muckerheide