Re: Mossman paper in Health Physics News - The Debate is Over

[epirad@mchsi.com]

Dr. Cohen,



In Dr. Mossman's editorial he states the debate is over. From the people I talk 

to, most people agree with Dr. Mossman that indeed the debate is over.  If you 

feel it is not, what review group would you accept to make that decision?  Will 

you accept the NCRP's position?

 

You knew many years ago that your data from your company measurements were 

biased and needed further editing before you could hope to use them for 

studies.  You chose to eliminate about 30% of the data for your studies by:



1. Eliminating any test results where the house was previously tested.

2. Eliminating the test result when the homeowner said they were aware of a 

high measurement in a house within 4 miles of their own home (It would appear 

to me that this would also bias the results to overall lower values.).

3. Eliminating the test result when it was performed in an unoccupied part of 

the home.

4. Eliminating the result if they did not provide answers to the above 

questions.



Nonetheless, other biases in your data remained.



For example - in your data 



    Low-income families are grossly underrepresented.

    High rise apartments are not represented.

    People concerned with environmental issues are overrepresented

    Urban areas are greatly underrepresented

    Cigarette smokers (and those socioeconomic factors associated with smoking) 

are underrepresented

    Rented homes are grossly under represented

    You also noted that an amazingly high 27% of bedrooms in his data set were 

located in the basement.



We previously showed (Smith et al. 1998 HPJ, Field et al. 1999 HPJ) that when 

your adjusted smoking percentages for males and females were regressed on radon 

levels, significant (p < 0.00001) negative associations between smoking and 

radon were noted for both males and females. In addition, when we (Smith et al. 

1998) repeated the regression of lung cancer mortality rates on Cohen's 

adjusted smoking percentages, the resulting R2 values indicated that Cohen's 

smoking summary data explained very little (23.7% for females; 34.5% for males) 

of the variation in lung cancer mortality rates.



An ecologic study is not the way to test the validity of the LNT.  I guess the 

question is who you would find acceptable to offer a decision on the debate? 

Your smoking data is co-correlated with socioeconomic status, poor health care, 

apartment living, mobility, lower education status, etc.  You have never 

assessed all these variables in a multivariate analyses.  And in fact, it would 

be difficult to do because of non linear relationships between these factors 

within and between counties.     



In: Field, R.W., Smith, B.J., and Lynch, C.F. Cohen’s Paradox, Health Physics 77

(3): 328-329, 1999.



we stated - 



Dear Editors:



"WE APPRECIATE the opportunity to respond to Cohen's letter-to-the-editor 

(Cohen 1999a) regarding our rejoinder (Field et al. 1998a). The rejoinder 

focused on Cohen's attempts (Cohen 1995,1997) to test the Linear No-Threshold 

Theory (LNTT) using ecologic data. In our initial publication on this topic 

(Smith et al. 1998), we demonstrated that Cohen erroneously used the wrong 

model to test the LNTT. We also demonstrated that when more valid Iowa county 

lung cancer rates were regressed on Cohen's mean county radon levels, the large 

negative associations Cohen noted between radon concentrations, obtained from 

short-term radon measurements, and lung cancer disappeared for Iowa. This 

letter addresses several important points that Cohen either continues to ignore 

or continues to contest.



Cohen (1999a) continues to challenge scientists to suggest a plausible 

explanation to explain the inverse relationship he notes between mean county 

residential radon measurements and mean county lung cancer mortality rates. We 

will call this inverse relationship "Cohen's Paradox." Cohen (1999a) states 

that his challenge is for someone to suggest a "not implausible model" as a 

possible explanation and that the burden of proof will be on him to show 

that "the explanation is highly implausible." We maintain that even if 

additional plausible models are offered, Cohen will likely not be able to 

explain his own paradox. Cohen has not accepted the fact that it may be 

impossible to explain Cohen's Paradox in definitive analytical terms with his 

existing data because it is not always possible to identify empirical sources 

of ecologic bias from aggregate (ecologic) data alone (Field et al. 

1998a).



Cohen (1999a) states that he has not been able to explain the inverse 

relationship (Cohen's Paradox) for his studies even with years of effort. We 

are not surprised. Cohen (1999a) continues to miss the point made previously 

(Greenland and Robins 1994; Smith et al. 1998; Field et al. 1998a) that 

characterizing biases is often extremely difficult in ecologic studies of 

geographic regions because of the high probability of interacting covariates 

that may differ across these regions. Greenland and Morgenstern (1989) point 

out that ecological control of a covariate contributing to ecologic bias will 

usually be inadequate to remove the bias produced by the covariate even in the 

absence of measurement error. Researchers (Greenland and Robins 1994; Lubin 

1998; Smith et al. 1998; Archer 1998; Goldsmith 1999) have already presented 

very plausible theoretical examples of how Cohen's data can produce incorrect 

and even contradictory risk estimates. Cohen has rejected 

all of these examples.



Lagarde and Pershagen (1999) recently performed concurrent analyses on 

individual and aggregated data from a nationwide case-control study of 

residential radon and lung cancer in Sweden. The authors reported that the 

results confirm that ecologic studies may be misleading in studies of weak 

associations. So, are Cohen's negative point estimates a true effect or are 

they attributable to bias? To move the explanation beyond the theoretical 

level, analyses would require individual level data beyond the quality of 

Cohen's aggregate data.



Cohen continues to maintain that his ecologic studies avoided the ecologic 

fallacy, because he was testing the BEIR-IV LNTT model (Cohen 1997,1998,1999a). 

Cohen also continues to deny our assertion (Smith et al. 1998; Field et al. 

1998a) that he was not testing the BEIR-IV LNTT model. As 

we stated (Smith et al 1998; Field et al. 1998a), Cohen's risk model is not the 

BEIR-IV risk model. Cohen attempted to equate his derived LNTT model to the 

BEIR-IV model by applying unsupported primary and secondary rigid assumptions. 

The assumptions all have both an error associated with them and a non-linear 

component, which as previously pointed out, cannot be quantitatively described. 

Rather than providing references to support the validity of his assumptions, 

Cohen defends his use of these assumptions (Cohen 1999a) by stating that they 

are the same assumptions as used in essentially all case-control studies.



All epidemiologic study designs have their own set of limitations. In fact, we 

have pointed out that inadequate measurement data can affect the validity of 

case-control studies as well as ecologic studies (Field et al. 1996,1997). The 

limitations and assumptions of radon case-control 

epidemiologic studies, which use individual rather than ecologic data, have 

been presented elsewhere (Lubin et al. 1990; Field et al 1996). However, the 

nature of potential biases inherent in case-control studies is often quite 

different from an ecologic study. For example, case-control studies are not 

subject to cross-level bias. While case-control studies have their own inherent 

limitations, controlling for potential confounders in a well-designed case-

control study is much easier than dealing with confounders in an ecologic study.



Many of the assumptions used by Cohen in his ecologic study design are not 

required for the case-control study design. For example, Cohen's ecologic 

studies assumed that smoking duration and intensity are the same for each 

individual within a specified region. Unlike ecologic studies, case-control 

studies collect data at the individual level so that detailed smoking histories 

can be available to use for adjustments. We previously showed (Smith et al. 

1998) that when Cohen's adjusted smoking percentages for males and females were 

regressed on radon levels, significant (p < 0.00001) negative associations 

between smoking and radon were noted for both males and females. In addition, 

when we (Smith et al. 1998) repeated the regression of lung cancer mortality 

rates on Cohen's adjusted smoking percentages, the resulting R2 values 

indicated that Cohen's smoking summary data explained very little (23.7% for 

females; 34.5% for males) of the variation in lung cancer mortality rates. It 

is not surprising Cohen cannot control for these risk factors using aggregate 

data. In addition, Cohen's ecologic studies make numerous other assumptions not 

required for newer case-control designs (Field et al. 1996).



Cohen (1999a) continues to offer explanations for how the conclusions of other 

published ecologic studies can be wrong. We (Field et al. 1998a) offered the 

large scale ecologic study by Menotti et al. (1997) as an example of an inverse 

relationship between average blood pressure and stroke mortality rates. Cohen 

did not have actual data from the study (Menotti et al. 1997) and therefore 

could not attempt to explain the paradoxical finding in definitive analytical 

terms. However, we would be interested in Cohen's definitive analytical 

explanation for why the large negative associations disappeared for the Iowa 

data when we regressed the more valid county lung cancer rates for Iowa on 

Cohen's own mean county radon levels for Iowa (Smith et al. 1998). As we 

mentioned previously, Iowa serves as an ideal site for a radon epidemiologic 

study because it possesses the highest mean radon concentrations in the United 

States (White et al. 1992), a population with low mobility, and a quality 

cancer registry (Field et al. 1996). In addition, because of the large number 

of counties in Iowa (99), Iowa data provide a finer ecologic breakdown per 

percent population compared to much 

of the rest of the U.S. data set assembled by Cohen. Cohen offers to provide 

specific quantitative explanations for why other ecologic studies can give 

false results, but he has yet to provide a persuasive argument for our findings 

in Iowa (Smith et al. 1998), which predominantly use his aggregate data.



Cohen (1999b) states, "I have never claimed that our studies support hormesis, 

since such an interpretation suffers from the ecologic fallacy." We agree with 

that claim by Cohen. However, Cohen has not provided persuasive evidence to 

show that his test of the LNTT also does not suffer from the ecologic fallacy. 

Cohen attempts to test the LNTT by analyzing averaged multivariate 

distributions of aggregate data, followed by analyses using more county level 

summaries to correct the potential biases. Because of the heterogeneity within 

the county summaries, the aggregate data provide very little confounder 

control, especially in the presence of non-linear dependencies (Field et al. 

1998b) and interactions (Greenland and Robins 1994). It is a fallacy to think 

that Cohen's inferences made from aggregate level data can be applied to 

individual level exposure-response relationships, especially when Cohen is not 

even testing the BEIR-IV formula.



Piantadosi (1994) pointed out that "a single result at odds with theory should 

not discredit the theory unless the source of data and analysis meet the most 

rigorous methodological criteria." Cohen's data, assumptions, and study design 

failed to fulfill these criteria. Nobel Laureate, Sir Peter Medawar (1979) 

wrote, "I cannot give any scientist of any age better advice than this: the 

intensity of the conviction that a hypothesis is true has no bearing on whether 

it is true or not. The importance of the strength of our conviction is only to 

provide a proportionately strong incentive to find out if the hypothesis will 

stand up to critical evaluation." Time will tell if the LNTT will stand up to 

critical evaluation or fall. Nevertheless, we oppose the critical evaluation 

taking the form of an ecologic study."

 

These same criticisms are just as valid today as when we initially wrote them.



Bill Field

epirad@mchsi.com

> 	My response to the Guest Editorial by Ken Mossman in the June

> issue of Health Physics News is given below. Please excuse the brevity

> as it was limited to 500 words. It will be in the July issue.

> 

> Bernard L. Cohen

> Physics Dept.

> University of Pittsburgh

> Pittsburgh, PA 15260

> Tel: (412)624-9245

> Fax: (412)624-9163

> e-mail: blc@pitt.edu

> web site: http://www.phyast.pitt.edu/~blc

> 

> The Guest Editorial by Ken Mossman (2003) in your June 2003 issue declares

> "the debate is over". It claims that Puskin (2003) demonstrates a serious

> error in my test of linear-no threshold theory (LNT) utilizing data for

> 1600 U.S. counties on lung cancer mortality rate - m, radon level - r, and

> smoking prevalence - S.  Puskin fits the data to both

> 			m = A + B r

>                   and        m =  a + b r + c S

> and finds that values of B and b are both negative, with b not much

> smaller in magnitude than B. This agrees with my findings (fitting with



> the BEIR formula) but is discrepant by 25 standard deviations with the LNT

> prediction of large positive b. After many years of extensive analysis, I

> concluded that this discrepancy indicates failure of LNT.

> 	However, Puskin makes the very interesting observation that,

> applying his treatment to other smoking-related cancers, gives the same

> behavior of b. Stating that b cannot be negative for other smoking related

> cancers, Puskin (and Mossman) conclude that my S-values are erroneous,

> missing a strong negative S-r correlation.

> 	Mossman references my analysis of the Puskin observation (Cohen

> 2003), but  ignores its most vital finding, that there is no possible set

> of S-values that avoid the anomaly of the Puskin observation. Even a

> perfect negative S-r correlation does not give a positive b value for lung

> cancer as predicted (by many standard deviations) from LNT, and it makes

> radon appear to cause the other smoking-related cancers (b positive for

> them).



>  Faced with this failure to explain the Puskin observation with erroneous

> S-values, I offer the suggestion that Mossman "makes light of", that body

> organs exposed to cigarette smoke are also exposed to radiation from

> radon. Low level radiation is known to stimulate production of DNA repair

> enzymes, to stimulate the immune response, to improve scavenging of free

> radicals, etc, all of which are protective against development of cancer.

>    On an unrelated matter, Mossman claims that my data, interpreted as a

> dose-response relationship, are discrepant with data from case-control

> studies. The reference he cites for the latter gives no such data, but my

> comparisons with published case-control studies (Cohen 1999) show no such

> discrepancy. Moreover, Mossman ignores my frequently emphasized point that

> my data cannot be interpreted as a dose-response relationship; they serve

> only as a test of LNT.

> 	Mossman misinterprets my reward offer. It was to seek suggestions,



> other than failure of LNT, for explaining my data. Since I had tried

> unsuccessfully for several years to find such an explanation, without such

> suggestions I could only conclude that LNT fails the test. I therefore

> thought I should use every practical means for obtaining such suggestions.

> 

> 

> 

> REFERENCES

> Cohen, BL. Response to Lubin rejoinder, Health Phys 76:438-439;1999

> 

> Cohen, BL. The Puskin observation on smoking as a confounder in ecologic

> correlations of cancer mortality rates with average county radon levels,

> Submitted to Health Physics (April 2003); also item #15 on web site

> www.phyast.pitt.edu/~blc

> 

> Mossman, KL. The debate is over: lessons learned from Cohen's ecological

> study.         Physics News, June 2003, page 3.

> 

> Puskin, JS, Smoking as a confounder in ecological correlations of cancer

> mortality rates with average county radon levels. Health Phys

> 84:526-532;2003

> 

> 

> ************************************************************************



> You are currently subscribed to the Radsafe mailing list. To unsubscribe,

> send an e-mail to Majordomo@list.vanderbilt.edu  Put the text "unsubscribe

> radsafe" (no quote marks) in the body of the e-mail, with no subject line.

> You can view the Radsafe archives at http://www.vanderbilt.edu/radsafe/

> 



************************************************************************

You are currently subscribed to the Radsafe mailing list. To unsubscribe,

send an e-mail to Majordomo@list.vanderbilt.edu  Put the text "unsubscribe

radsafe" (no quote marks) in the body of the e-mail, with no subject line.

You can view the Radsafe archives at http://www.vanderbilt.edu/radsafe/