Journal of Occupational Medicine and Toxicology - Latest Comments

Author reply

Peter Morfeld — 2013-04-23T17:06:42Z

I¿d like to thank Drs Silverman and Attfield for their profound reply [1] to my commentary [2] and their in-depth explanations of specific aspects of the Diesel Exhaust in Miners Study [DEMS, 3, 4]. It was my motivation to instigate discussions about this important and impressive epidemiological project. Thus, I highly appreciate that the leading DEMS authors responded to my commentary in such a great detail. The Editors of JOMT invited me to follow-up on this discussion and I will respond to the points as they were numerated in Silverman and Attfield [1].

1) The DEMS findings about the effect of long-term respirable elemental carbon (REC) exposure estimates on lung cancer mortality depended critically on the adjustment by location (surface vs. underground work). Cox models that followed the analysis plan did not show any convincing association between REC exposure estimates and lung cancer mortality. Only after subdividing the cohort into ¿surface only workers¿ vs. ¿ever underground workers¿ or after adjusting for a ¿surface only/ever underground work¿ indicator the Cox models returned pronounced dose¿response relationships with REC exposure estimates. Silverman and Attfield [1] agreed. They confirmed that the distinction between surface and underground work is of major importance for an understanding of DEMS. Of note, they did not agree with my statement that ¿this factor `surface/underground work¿ remains unexplained.¿ They argued that ¿the observed difference in risk between surface only and underground workers is explained by smoking and diesel exposure¿. Unfortunately, this statement appears to be wrong. If their statement were true we expected to see that the location variable could be substituted by a combination of the smoking and exposure variables without affecting the REC exposure estimates. Thus, models that follow the original study protocol and included no location factor but smoking information should return large REC exposure effect estimates. In addition, the location variable should show a clearly reduced and non-significant effect in models after adjusting for smoking and exposure. Based on the DEMS papers, my understanding is that this is not true. If Drs. Silverman and Attfield [1] still disagree I¿d like to ask them to reveal a) the REC exposure coefficients (with CIs and p-values) returned by conditional logistic regression with and without adjustment for location, while always controlling for smoking and b) to show the location coefficient (with CI and p-value) after adjustment for smoking and REC exposure (smoking and location variables should be entered into the models as separate variables so that we can distinguish their effects on lung cancer mortality).

Silverman and Attfield [1] made an observation that they interpreted as evidence for identical risks among surface and underground workers after appropriate adjustment:: ¿As shown in Table 2 [2], after adjustment for diesel exposure, the risk among underground nonsmoking workers is virtually identical to that among surface-only nonsmoking workers (OR for 15-year lagged cumulative REC = 0.90), providing evidence that the observed difference in risk between surface only and underground workers is explained by smoking and diesel exposure.¿ However, the 95%-confidence interval of the cited odds ratio (OR) spanned from 0.26 to 3.09. This can hardly be interpreted as evidence in favor of the null hypothesis.

There are other interpretations of the DEMS authors about smoking that are difficult to follow. Möhner [5] noted in his Letter to the Editor: ¿According to the authors, there was no evidence of an increased smoking prevalence in those employees working underground. Yet a comparison of the smoking data from controls by location of employment (Table 2 [2]) yielded a significantly higher percentage of never smokers and significantly lower percentage of heavy smokers (¿2 packs per day) among surface-only workers than among ever-underground workers (34.2% vs. 22.1% and 6.3% vs. 13.6%, respectively). Although underground workers smoked significantly more, were more burdened with exposure to other occupational lung carcinogens (see for example standardized mortality ratios (SMR) for pneumoconiosis, Supplementary Table 2 [1]) and were much more exposed to DME than surface workers, their lung cancer mortality is lower. We would be grateful to the authors if they could provide readers with additional data so that the studies¿ conclusions can be comprehended. In particular, we would like to know, how the SMR reflect differences by exposure parameters.¿ The authors did not reply to this. Silverman et al. [4] wrote: ¿a comparison of confounder data derived directly from living and from next of kin for deceased control subjects revealed comparability of responses¿. This statement appears to be odd when applied to smoking. Pallapies et al. [6] noted: ¿Silverman et al. [4] obtained smoking data in cases from next of kin only. However, they obtained such data from living control subjects as well as from next of kin of other control subjects. This may have led to considerable bias, as different percentages of ``current smokers¿¿ from direct versus next of kin interviews (11 vs. 23 %) demonstrate¿.

In this respect I like to repeat point 4 in Morfeld [2] that remained unanswered: ¿The REC exposure risk estimates differed with location [1]: the authors reported a twenty times higher excess risk per ¿g/m3-y on ¿surface only¿ in comparison to ¿ever underground¿. After taking logs of exposure the ¿surface only¿ REC coefficient was about twice the one calculated for workers ¿ever underground¿. The researchers [1] tested the differences of the effect estimates (significant on the log scale, not significant on the linear scale) but neither reported how they performed the tests nor did they show any details of the results. The usual way to perform such a test is to add an interaction term ¿REC exposure x location¿ to the models. It is surprising that the authors [1,2] did not present such interaction models.¿

Silverman and Attfield [1] wrote that I misquoted them as hypothesizing that ¿high REC exposures are protective against lung cancer excess risks due to smoking.¿ I am not sure whether this comment is on substance or on semantics. I just wanted to make clear that Silverman et al. [4] listed mechanisms that they believe could be true and may reduce lung cancer risk from smoking because of elevated diesel motor emission exposures, e.g., ¿¿constituents of diesel exhaust may suppress enzymes that activate or induce enzymes that detoxify carcinogens in tobacco smoke. For example, diesel exhaust particles have been shown to reduce activity of CYP2B1, which plays a role in the activation of certain tobacco-specific nitrosamines [24]. Also, diesel particulate matter has been shown to reduce the initiation of skin tumors in Sencar mice treated with the potent PAH dibenzo[a]pyrene, possibly through inhibition of enzymes that carry out its metabolic activation [25].¿

2) I¿d like to thank Drs Silverman and Attfield [4] that they presented the ORs when not adjusting for an interaction of location and smoking. This analysis demonstrated that an inclusion of the cross-product term was not necessary to estimate the effect of REC exposure. Unfortunately, they did not show other results I asked for: ¿ORs for REC exposure after controlling for only those variables used in SMR calculations, and ¿ ORs for smoking in underground and surface workers without adjustment for REC exposure¿ [2] Furthermore, like Möhner [5] I showed interest in lung cancer SMRs across REC exposure categories to judge whether the study has pronounced deficits of lung cancer mortality in low categories of exposure and whether there are any significant SMR excesses in the highest exposure categories. Thus, the authors did not present data to rule out my hypothesis that the lung cancer mortality structure is strange and similar to the leukemia pattern observed in NCI¿s formaldehyde cohort [7, 8]. Silverman and Attfield [1] confirmed that their mortality follow-up procedure was the same or very similar to the method applied in the NCI formaldehyde cohort. Of note, NCI formaldehyde researchers had missed about 1000 deaths out of 9500 which led to distorted exposure-response findings [9]. Silverman and Attfield [1] did present no arguments that DEMS may not suffer from the same problems.

3) Silverman and Attfield [1] wrote: ¿Dr. Morfeld goes on to focus on the external vs. internal analysis results, finding it `perplexing¿ that they should differ. In response, we note that it is well established that external analysis is subject to factors including the healthy worker effect that are better addressed through internal analysis.¿ I¿d like to emphasize that I was not talking about exposure. I found it perplexing (and still find it perplexing) that such a large location effect popped up after adjusting for REC exposure and went unnoticed otherwise. The idea of Silverman and Attfield [1] that this observation may be associated to the healthy worker effect appears to be off the track.

4) Silverman and Attfield [1] ¿were unable to comprehend what Dr. Morfeld is recommending with respect to analysis by worker location. We employed a time dependent stratification approach (e.g., a worker was surface-only until the first time they went underground, at which time they became an ever-underground worker).¿ I will try to explain it differently. The binary variable ¿location¿, as defined and used in the DEMS analysis, does not tell us for each person-year whether the miner was underground or on surface. Here is why: Assume that a miner worked underground up to year x but then changed to a surface job and stayed on surface until year x+s. Then the variable ¿location¿, as defined and used in the DEMS analysis, is set to ¿underground¿ during the years x to x+s although the miner was on surface. In contrast to what had been done in DEMS I recommended and I still recommend that the variable ¿location¿ should correctly reflect for each person-year whether the miner was underground or on surface. According to the description of the exposure assessment process a REC estimate was allocated to every person-year. And because REC exposures differed between surface and underground work a reliable exposure assessment should take account of workers¿ location in every person- year. Thus, the variable ¿location¿ can be defined in the suggested way (if not, the DEMS exposure estimates are obviously inaccurate). Note that it is improbable that in this large cohort miners only changed from surface to underground work but never vice versa. Because the variable ¿location¿ is so important in DEMS this variable should be defined in a better way than Silverman and Attfield [1] did.

Silverman and Attfield [1] wrote ¿We cannot imagine that Dr. Morfeld was advocating using underground tenure as a primary exposure variable rather than using the available quantitative exposure data.¿ I never recommended using underground tenure as a primary exposure variable. This appears to be a misunderstanding.

5) Silverman and Attfield [1] wrote: ¿it is generally accepted that retrospective exposure assessments in occupational studies such as DEMS have some imprecision [4]. If, as is likely, the error is non-differential, the exposure-response slopes may be attenuated. Considerable effort went into evaluating the exposure assessment in DEMS, including a separate paper on this topic [5]. We also developed a number of alternative exposure metrics. These are discussed in the cohort paper [1] and were found not to impact the findings in any significant way.¿This does not justify taking the exposure data as fixed and assuming ¿no exposure errors¿ when modeling risks. Monte Carlo sensitivity and Bayesian bias analyses are well developed and these procedures are able to cover the involved uncertainty. I will provide two examples that may help to understand what kind of potential problems exist in DEMS. The REC exposure assessment was mainly based on a correlation between CO and REC measurements [10]. The authors admittted ``¿that the observed coefficient derived from this cross-sectional study might not apply longitudinally to past conditions.¿¿ This induces problems because the DEMS analysis relies on life-long cumulative exposures. The relevance of such uncertainties can be measured by appropriate bias analyses. Moreover, the coefficient chosen by DEMS researchers to transfer CO values into REC values was not supported by the data [11]. Thus, this may have distorted the risk estimates. Again, this motivates to perform bias analyses.

6) I¿d like to thank Drs. Silverman and Attfield [1] that they were open to clarify even some of the minor issues that I raised (sub-issues 1 to 5 in Silverman and Attfield [1]). Sub-issue 3: I am not clear whether the authors wanted to say that the case-control study was analyzed twice (two different ways to deal with missing data)? Sub-issue 4: I had interest in the smoking patterns. Can the patterns be presented? One issue remained without response: the suggestion of a curvilinear modeling.

I¿d like to add that the paper describing the re-analysis of the German potash miner cohort was accepted for publication [12]. Silverman et al. [4] stated:¿We observed an increased lung cancer risk associated with diesel exposure as was seen among German potash miners [11].¿ This statement is no longer evident because of the null results reported in Möhner et al. [12] after taking account of prior exposures in Uranium mining.

Final remark

Silverman and Attfield [1] wrote as a final comment: ¿Despite the complexities of the cohort and case-control analyses, there is no doubt that excess risks of lung cancer were detected, and that these elevations were associated with increasing levels of diesel exhaust. We do not accept that our methods suffer from errors so egregious that the findings could be spurious. In fact, the scientific community seems to have had no difficulty in accepting our results, as reflected by the recent IARC review of the carcinogenicity of diesel exhaust, in which our findings played an important role in the evaluation process¿. I do have to insist that pronounced and clear-cut lung cancer excess risks were only observed after adjustment for location. Anyhow, Silverman and Attfield [1] were right when they reported on the evaluation of a working group who met at IARC, Lyon in June 2012 [13]. I attended that meeting as an observer. Indeed, the group of invited experts took the exceptionally large REC exposure estimates of the DEMS for granted without mentioning the potential problems involved. I have to admit that the frustrating commentary published by another observer is appropriately describing the downsides of the evaluation process at this IARC monograph meeting [14]. John Gamble reminded the reader that the Preamble of the IARC monographs [e.g., 15] defines clearly what the working group should do: ¿When an important aspect of a study that directly impinges on its interpretation should be brought to the attention of the reader, a Working Group comment is given in square brackets¿. Regarding DEMS the working group had no square brackets added to mention the discussed weaknesses of the study. They did so although the weaknesses were brought to their attention, even in published form [2]. Another striking example is linked to the European-Canadian pooled case-control study [16]. In the abstract the authors described a positive association between diesel exhaust exposure and lung cancer risk in a smoking-adjusted analysis. The working group repeated these statements of the authors and noted in a square bracket that this finding is unlikely to [¿be explained by bias or confounding¿]. Tim Lash, another observer and well-known for his high-level work on bias adjustment in epidemiological studies [e.g., 17], commented on this square bracket during the epidemiological subgroup meetings and also in the plenary meeting of the full working group. Lash noted that this pooled case-control study was very large and one of the rare investigations that studied lung cancer risks among never smokers. He made clear that a lack of association was found among never smokers, possibly the group that could provide the least confounded risk estimates after Diesel exhaust exposure [Table 3, 16]. Contrary to the statement of the working group Lash explained that the positive result after smoking adjustment could be due to residual confounding, in particular in the light of the null finding within never smokers. Again, this comment went unnoticed by the working group. The square bracket statement about Olsson et al. [16] was not changed and this important information about never smokers was not brought to the attention of the monograph readers. Thus, the fact that the working group at the IARC meeting did not critically assess weaknesses of the DEMS should not be given much weight. Of note, a well designed re-analyses of the DEMS cohort and case-control studies may return results different from those reported by the IARC working group and in the original papers [3, 4]. Such complementary research is in the planning stage and it may help to understand the important DEMS project in more detail.

References

1. Silverman DT, Attfield MD. RE: "Diesel exhaust in miners study: how to understand the findings?" by Peter Morfeld. J Occup Med Toxicol 2013:http://www.occup-med.com/content/7/1/10/comments (13th March 2013, date last accessed).
2. Morfeld P. Diesel exhaust in miners study: how to understand the findings? J Occup Med Toxicol 2012;7(1):http://www.occup-med.com/content/7/1/10 (13th March 2013, date last accessed).
3. Attfield M, D., Schleiff PL, Lubin JH, Blair A, Stewart PA, Vermeulen R, Coble JB, Silverman DT. The diesel exhaust in miners study: a cohort mortality study with emphasis on lung cancer. J Natl Cancer Inst 2012;104(11):869-83.
4. Silverman DT, Samanic CM, Lubin J, H., Blair AE, Stewart PA, Vermeulen R, Coble JB, Rothman N, Schleiff PL, Travis WD, et al. The diesel exhaust in miners study: A nested case-control study of lung cancer and diesel exhaust. J Natl Cancer Inst 2012;104(11):855-68.
5. Möhner M. To the editor: The impact of selection bias due to increasing response rates among population controls in occupational case-control studies. Am J Respir Crit Care Med 2012;185(1):104-6.
6. Pallapies D, Taeger D, Bochmann F, Morfeld P. Comment: Carcinogenicity of diesel-engine exhaust (DE). Arch Toxicol 2013;87(3):547-9.
7. Hauptmann M, Lubin JH, Stewart PA, Hayes RB, Blair A. Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries. J Natl Cancer Inst 2003;95(21):1615-23.
8. Beane Freeman LE, Blair A, Lubin JH, Stewart PA, Hayes RB, Hoover RN, Hauptmann M. Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: the national cancer institute cohort. J Natl Cancer Inst 2009;101(10):751-61.
9. Marsh GM, Youk AO, Morfeld P, Collins JJ, Symons JM. Incomplete follow-up in the National Cancer Institute's formaldehyde worker study and the impact on subsequent reanalyses and causal evaluations. Regul Toxicol Pharmacol 2010;58:233-6.
10. Vermeulen R, Coble JB, Yereb D, Lubin JH, Blair A, Portengen L, Stewart PA, Attfield M, Silverman DT. The diesel exhaust in miners study: III. Interrelations between respirable elemental carbon and gaseous and particulate components of diesel exhaust derived from area sampling in underground non-metal mining facilities. Ann Occup Hyg 2010;54(7):762-73.
11. Crump K, Van Landingham C. Evaluation of an exposure assessment used in epidemiological studies of diesel exhaust and lung cancer in underground mines. Crit Rev Toxicol 2012;42(7):599-612.
12. Möhner M, Kersten N, Gellissen J. Diesel motor exhaust and lung cancer mortality: reanalysis of a cohort study in potash miners. Eur J Epidemiol 2013:http://rd.springer.com/article/10.1007/s10654-013-9784-0 (13th March 2013, date last accessed).
13. Benbrahim-Tallaa L, Baan RA, Grosse Y, Lauby-Secretan B, El Ghissassi F, Bouvard V, Guha N, Loomis D, Straif K, International Agency for Research on Cancer Monograph Working G. Carcinogenicity of diesel-engine and gasoline-engine exhausts and some nitroarenes. Lancet Oncol 2012;13(7):663-4.
14. Gamble JF. IARC evaluations of cancer hazards: Comment on the process with specific examples from volume 105 on diesel engine exhaust. J Clinic Toxicol 2012;2:http://www.omicsonline.org/2161-0495/2161-0495-2-e106.digital/2161-0495-2-e106.html (13th March 2013, date last accessed).
15. IARC. Carbon black, titanium dioxide, and talc. Lyon: International Agency for Research on Cancer; 2010.
16. Olsson AC, Gustavsson P, Kromhout H, Peters S, Vermeulen R, Brüske I, Pesch B, Siemiatycki J, Pintos J, Brüning T, et al. Exposure to diesel motor exhaust and lung cancer risk in a pooled analysis from case-control studies in Europe and Canada. Am J Respir Crit Care Med 2011;183(7):941-8.
17. Lash TL, Fox MP, Fink AK. Applying quantitative bias analysis to epidemiologic data. Dordrecht: Springer Science+Business Media, LLC; 2009.

Letter-to-the-Editor RE: ¿Diesel exhaust in miners study: how to understand the findings?¿ by Peter Morfeld

Debra Silverman — 2013-03-05T13:51:37Z

We thank Dr. Morfeld for providing us the opportunity to clarify several points regarding the analyses of data from both the cohort (1) and case-control (2) components of the Diesel Exhaust in Miners Study (DEMS).

First, we agree with Dr. Morfeld¿s statement ¿The distinction between surface and underground work is obviously of major importance for an understanding of this study.¿ In fact, to ignore location and simply estimate risk by exposure and adjusting for smoking would have led to erroneous results. However, we do not agree with Dr. Morfeld¿s statement ¿this factor `surface/underground work¿ remains unexplained.¿ The smoking effect among surface-only workers shown in Table 2 (2) is similar to that observed in previous cohort studies of smoking and lung cancer (3), whereas the smoking effect among underground workers who smoke at least 1 pack per day is attenuated. As shown in Table 2 (2), after adjustment for diesel exposure, the risk among underground nonsmoking workers is virtually identical to that among surface-only nonsmoking workers (OR for 15-year lagged cumulative REC = 0.90), providing evidence that the observed difference in risk between surface only and underground workers is explained by smoking and diesel exposure. When smoking and location are included as separate variables in the model, estimates of risk are quite similar to those in Table 3 (2) (e.g., ORs for quartiles of 15-year lagged cumulative REC: 1.0 (referent), 0.87 vs. 0.74, 1.60 vs. 1.54, 2.97 vs. 2.83, respectively) with the P for trend = 0.001 in both models. Because the interaction between smoking and location was borderline significant, we included a cross-product term in the models to fully capture this interaction. The inclusion of the cross-product term had a negligible impact on the estimates of risk, however. Dr. Morfeld also misquotes us as hypothesizing that ¿high REC exposures are protective against lung cancer excess risks due to smoking.¿ We wrote that the effect of smoking is ¿attenuated¿ in the presence of high levels of diesel exposure, which is not the same as ¿protection¿ since smoking does indeed cause lung cancer among underground workers who were heavily exposed to diesel exhaust.

Second, Dr. Morfeld questions whether we have a systematic underestimation of lung cancer deaths, especially at lower diesel exhaust exposure levels. The mortality follow-up was undertaken by NIOSH using typical and standard methodology and data from the National Death Index, Social Security Administration, and Internal Revenue Service. Other sources, such as postmasters, tracing agencies, and company records were also employed. Overall, the information from the various sources was internally very consistent. Third, Dr. Morfeld goes on to focus on the external vs. internal analysis results, finding it `perplexing¿ that they should differ. In response, we note that it is well established that external analysis is subject to factors including the healthy worker effect that are better addressed through internal analysis. In addition, as noted in the cohort paper (1), different patterns of lung cancer mortality by location, which were shown by the case-control analysis (2) to be caused by smoking, obscured the exposure-response relationship evident in the complete cohort. Clear exposure-response patterns were identified after stratification by location (Tables 4 and 5 of the cohort paper (1)), and were also observed after adjustment for location (Table 6 of the cohort paper (1)). Fourth, we were unable to comprehend what Dr. Morfeld is recommending with respect to analysis by worker location. We employed a time dependent stratification approach (e.g., a worker was surface-only until the first time they went underground, at which time they became an ever-underground worker). We cannot imagine that Dr. Morfeld was advocating using underground tenure as a primary exposure variable rather than using the available quantitative exposure data.

Fifth, it is generally accepted that retrospective exposure assessments in occupational studies such as DEMS have some imprecision (4). If, as is likely, the error is nondifferential, the exposure-response slopes may be attenuated. Considerable effort went into evaluating the exposure assessment in DEMS, including a separate paper on this topic (5). We also developed a number of alternative exposure metrics. These are discussed in the cohort paper (1) and were found not to impact the findings in any significant way.

Dr. Morfeld asks several detailed questions concerning our methods. In response: 1) We did not censor or otherwise treat deaths over age 85 differently from younger deaths (but only 3 of 200 lung cancer deaths in the cohort were >85 years and all available pathology reports for the lung cancer cases were evaluated by an expert pathologist to confirm lung cancer as the cause of death). 2) In the cohort analysis, all confounder variables were entered into the model together and each examined for their apparent influence on lung cancer mortality. In the case-control study, each potential confounder was added one-at-time to the conditional model containing an exposure metric, the cross product of smoking and location, employment in a high-risk occupation for at least 10 years, and a history of nonmalignant respiratory disease for at least 5 years to create a base model. We also ran full models that simultaneously included the base model plus the other potential confounders. 3) In the cohort analysis, observations with missing data for a particular analysis were dropped; in the case-control analysis, missing confounder data were included as a separate level. When we evaluated this approach by excluding missing confounder data from key analyses, observed patterns of risk were similar to those when missing data were included as a separate level. 4) Although workers were not permitted to smoke underground in the trona mines, patterns in exposure-response were similar by mine type, suggesting that differential smoking patterns across facilities did not impact the findings. 5) In the cohort analysis, there was no overall effect of dropping those whose age at first exposure was greater than 40 (the cumulative REC exposure hazard ratio dropped slightly while that for exposure intensity increased).

Despite the complexities of the cohort and case-control analyses, there is no doubt that excess risks of lung cancer were detected, and that these elevations were associated with increasing levels of diesel exhaust. We do not accept that our methods suffer from errors so egregious that the findings could be spurious. In fact, the scientific community seems to have had no difficulty in accepting our results, as reflected by the recent IARC review of the carcinogenicity of diesel exhaust, in which our findings played an important role in the evaluation process (6).

Debra T. Silverman
Michael D. Attfield

References
1. Attfield MD, Schleiff PL, Lubin JH, Blair A, Stewart PA, Vermeulen R, Coble JB, Silverman DT. The Diesel Exhaust in Miners Study: A cohort mortality study with emphasis on lung cancer. J Natl Cancer Inst 2012;104(11):869-883.

2. Silverman DT, Samanic CM, Lubin JH, Blair AE, Stewart PA, Vermeulen R, Coble JB, Rothman N, Schleiff PL, Travis WD, Ziegler RG, Wacholder S, Attfield MD. The Diesel Exhaust in Miners Study: A nested case-control study of lung cancer and diesel exhaust. J Natl Cancer Inst 2012;104(11):855-868.

3. Blot WJ, Fraumeni JF, Jr. Lung and pleura. In: Schottenfeld D, Fraumeni JF Jr. eds. Cancer Epidemiology and Prevention. 2nd Ed. New York: Oxford University Press, 1996:637-665.

4. Stewart PA, Coble JB, Vermeulen R, Blair A, Lubin J, Attfield M, Silverman DT. Response to Borak et al., 2010 on the Diesel Exhaust in Miners Study. Ann Occup Hyg 2011;55(3): 343-346.

5. Stewart PA, Vermeulen R, Coble JB, Blair A, Schleiff PL, Lubin JH, Attfield M, Silverman DT. The Diesel Exhaust in Miners Study: V. Evaluation of the exposure assessment methods. Ann Occup Hyg 2012 Mar 1 Epub.

6. Lamia Benbrahim-Tallaa, Robert A Baan, Yann Grosse, Béatrice Lauby-Secretan, Fatiha El Ghissassi, Véronique Bouvard, Neela Guha, Dana Loomis, Kurt Straif. Carcinogenicity of diesel-engine and gasoline-engine exhausts and some nitroarenes. Lancet Oncol 2012;13(7):663-664.

Affiliations of authors: Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD (DTS); Surveillance Branch, Division of Respiratory Disease Studies, National Institute for Occupational Safety and Health, Morgantown, WV (MDA).

Value of biomonitoring for organic diisocyanate exposure

Heikki Savolainen — 2011-12-20T12:01:13Z

Dear Editor,

The careful study points out the requirements for correct interpretation of biomonitoring of exposure to diisocyanates (1). The initial urinary elimination half-lives of hexamethylene diisocyanate (2) or toluene diisocyanate monomers (3) are short which may limit the optimal sampling period immediately after the exposure peak (4). However, even end to the shift sampling can reveal the order of the magnitude of the exposure (5,6).

Finally, the mass spectrometric detection of the metabolites may have forensic value as they reveal the polyurethane source in e.g. the fire smoke victims (7).

1 Budnik LT, Nowak D, Merget R, et al. Elimination kinetics of diisocyanates after sepcific inhalative chanllenges in humans: mass spectrometry analaysis as a basis for biomonitoring strategies. J Occup Med Toxicol 2011; 6: 9

2 Rosenberg C, Savolainen H. Determination in urine of diisocyanate-derived amines from occupational exposure by gas chromatography-mass fragmentography. Analyst 1986; 111: 1069

3 Rosenberg C, Savolainen H. Determination of occupational exposure to toluene diisocyanate by biological monitoring. J Chromatogr 1986; 367: 385

4 Huynh CK, Vu-Duc T, Savolainen H. Occupational asthma due to isocyanate exposure: New orientations in the hygienic studies. Soz Präventivmed 1992; suppl. 2: S128

5 Maitre A, Berode M, Perdrix A, et al. Biological monitoring of occupational exposure to toluene diisocyanate. Int Arch Occup Environ Hlth 1993; 65: 97

6 Maitre A, Berode M, Perdrix A. Urinary hexane diamine as an indicator of occupational exposure to hexamethylene diisocyanate. Int Arch Occup Environ Hlth 1996; 69: 65

7 Rosenberg C, Savolainen H. Mass fragmentographic determination of urinary amine metabolites in rats exposed to degradation products from heated rgid polyurethane. J Chromatogr 1986; 358: 385

Cancer incidence ecological study in Rhineland-Palatinate, Germany, provides strong support for the ultraviolet B–vitamin D–cancer hypothesis

William B. Grant — 2010-07-19T11:50:01Z

The paper by Seidler et al. [1] provides strong support for the ultraviolet B–vitamin D–cancer hypothesis [2-5]. This study was designed to look for a potential association between pesticide exposure and cancer risk. By dividing the state into three categories, (small: >0 to 5 percent; medium: >5 to 20 percent; large: >20 percent area under wine cultivation), the study essentially divided the state into urban, mixed, and rural regions. It is reasonable to expect that those living in the rural region would have greater solar ultraviolet (UV) irradiance, and, based on the standardized incidence ratios (SIR) for non melanoma skin cancer (NMSC) and malignant melanoma for men shown in Table 4, that seems to be the case. The situation is not as clear for women as shown in Table 5, but those living in the urban regions had lower skin cancer and malignant melanoma SIR than those living in the mixed or rural regions.

As has been discussed in several papers, NMSC incidence and mortality rates serve as an index of solar UVB irradiance experienced by individuals and the population [6-11]. While the effect is stronger at latitudes equatorward of about 40º [9,10], there is evidence that the effect is also observed at higher latitudes in Europe [8,11]. Risk factors for melanoma include both UVA and UVB; with sunscreen use at high latitudes, UVA is the more important risk factor while for lower latitudes, sunburning from UVB is more important [12].

The role of solar UVB in reducing the risk of cancer can be estimated from the results in Tables 4 and 5. For this, I will assume that the lower 95% confidence interval (CI) for NMSC and malignant melanoma should be higher than the upper 95% CI interval for other cancers for the mixed or rural regions. For males, the cancers that satisfy this criterion for both regions are: stomach; colon, sigmoid & rectum; trachea, bronchus and lung; urinary tract; leukaemia; and all malignancies excluding C44. For females, the cancers that satisfy this criterion for both regions are: stomach; colon, sigmoid & rectum; trachea, bronchus and lung; cervix uteri; and ovary and other unspecified female genital organs. All of these cancers have been identified as having reduced risk from solar UVB in one or more ecological studies [5, 7, 13, 14].

However, puzzling is why some well-studied vitamin D-sensitive cancers did not show inverse correlations. For males, the reduced SIR was not statistically significant. Bladder cancer is vitamin D sensitive [5], but also sensitive to pesticides. Risk for prostate cancer is hypothesized to be linked to genetics and diet rather than vitamin D [15]. For non-Hodgkin’s lymphoma for both males and females, the SIR was significantly reduced in one region but not the other. Other studies have found NMSC correlated with risk of lymphoma [16]; however, at least in sunny countries, there is a benefit for UVB irradiance [17]. For females, the SIR for breast cancer was not significantly reduced. Alcohol is a risk factor for breast cancer [18], and in an affluent, wine-growing county in California, alcohol consumption is a risk factor for breast cancer [19]. The SIR for corpus uteri cancer was higher than for NMSC, malignant melanoma. Alcohol is also a risk factor for this cancer [20]. Thus, increased alcohol consumption in the winegrowing regions might explain these findings.

To extend this study, serum 25(OH) levels could be measured in summer for a cross-section of the older population living in each region.

In terms of policy, it would be worthwhile to recommend raising serum 25-hydroxyvitamin D levels to above 100 nmol/L at the population level, a value estimated to reduce all-cause mortality rates by 15-20% and health system costs by 10-15% [21-25]. In the absence of solar UVB, it would take 2000-5000 IU/day of vitamin D3 (cholecalciferol) to achieve this goal since each 1000 IU/day increases serum 25-hydroxyvitamin D levels by 15-25 nmol/L [26].

References
1. Seidler A, Hammer GP, Husmann G, König J, Krtschil A, Schmidtmann I, Blettner M. Cancer risk among residents of Rhineland-Palatinate winegrowing communities: a cancer-registry based ecological study. J Occup Med Toxicol. 2008 Jun 6;3:12.

2. Garland CF, Garland FC. Do sunlight and vitamin D reduce the likelihood of colon cancer? Int J Epidemiol. 1980;9:227-31.

3. Garland CF, Garland FC, Gorham ED, Lipkin M, Newmark H, Mohr SB, Holick MF. The role of vitamin D in cancer prevention. Am J Public Health. 2006;96:252-61.

4. Garland CF, Gorham ED, Mohr SB, Garland FC. Vitamin D for cancer prevention: Global perspective. Ann Epi. 2009;19:468-83.

5. Grant WB, Mohr SB. Ecological studies of ultraviolet B, vitamin D and cancer since 2000. Ann Epidemiol. 2009;19:446-54.

6. Grant WB. A meta-analysis of second cancers after a diagnosis of nonmelanoma skin cancer: additional evidence that solar ultraviolet-B irradiance reduces the risk of internal cancers. J Steroid Biochem Mol 2007;103:668-74.

7. Grant WB. An ecologic study of cancer mortality rates in Spain with respect to indices of solar UV irradiance and smoking. Int J Cancer. 2007;120:1123-7.

8. de Vries E, Soerjomataram I, Houterman S, Louwman MW, Coebergh JW. Decreased risk of prostate cancer after skin cancer diagnosis: A protective role of ultraviolet radiation? Am J Epidemiol. 2007 165: 966-972.

9. Tuohimaa P, Pukkala E, Scelo G, Olsen JH, Brewster DH, Hemminki K, Tracey E, Weiderpass E, Kliewer EV, Pompe-Kirn V, McBride ML, Martos C, Chia KS, Tonita JM, Jonasson JG, Boffetta P, Brennan P. Does solar exposure, as indicated by the non-melanoma skin cancers, protect from solid cancers: Vitamin D as a possible explanation. Eur J Cancer. 2007;43:1701-12.

10. Grant WB. The effect of solar UVB doses and vitamin D production, skin cancer action spectra, and smoking in explaining links between skin cancers and solid tumours. Eur J Cancer. 2008;44:12-15.

11. Soerjomataram I, Louwman WJ, Lemmens VE, Coebergh JW, de Vries E. Are patients with skin cancer at lower risk of developing colorectal or breast cancer? Am J Epidemiol. 2008;167: 1421-9.

12. Gorham ED, Mohr SB, Garland CF, Chaplin G, Garland FC. Do sunscreens increase risk of melanoma in populations residing at higher latitudes? Ann Epidemiol. 2007;17:956-63.

13. Boscoe FP, Schymura MJ. Solar ultraviolet-B exposure and cancer incidence and mortality in the United States, 1993-2000. BMC Cancer. 2006;6:264.

14. Grant WB. Does Solar Ultraviolet Irradiation affect Cancer Mortality Rates in China? Asian Pac J Cancer Prev. 2007;8:236-42.

15. Grant WB. A multicountry ecological study of risk-modifying factors for prostate cancer: Apolipoprotein E 4 as a risk factor and cereals as a risk reduction factor. Anticancer Res. 2010;30;189-99.

16. Adami J, Frisch M, Yuen J, Glimelius B, Melbye M. Evidence of an association between non-Hodgkin's lymphoma and skin cancer. BMJ. 1995;310:1491-5.

17. Kricker A, Armstrong BK, Hughes AM, Goumas C, Smedby KE, Zheng T, Spinelli JJ, De Sanjose S, Hartge P, Melbye M, Willett EV, Becker N, Chiu BC, Cerhan JR, Maynadie M, Staines A, Cocco P, Boffeta P; for the Interlymph Consortium. Personal sun exposure and risk of non Hodgkin lymphoma: A pooled analysis from the Interlymph Consortium. Int J Cancer. 2008;122:144-54.

18. Grant WB. An ecologic study of dietary and solar ultraviolet-B links to breast carcinoma mortality rates. Cancer. 2002;94:272-81.

19. Keegan TH, Chang ET, John EM, Horn-Ross PL, Wrensch MR, Glaser SL, Clarke CA. Recent changes in breast cancer incidence and risk factor prevalence in San Francisco Bay area and California women: 1988 to 2004. Breast Cancer Res. 2007;9:R62.

20. Friberg E, Orsini N, Mantzoros CS, Wolk A. Alcohol intake and endometrial cancer risk: a meta-analysis of prospective studies. Br J Cancer. 2010;103:127-31.

21. Grant WB, Cross HS, Garland CF, Gorham ED, Moan J, Peterlik M, et al. Estimated benefit of increased vitamin D status in reducing the economic burden of disease in Western Europe. Prog Biophys Mol Biol. 2009;99:104–13.

22. Grant WB. In defense of the sun: An estimate of changes in mortality rates in the United States if mean serum 25-hydroxyvitamin D levels were raised to 45 ng/mL by solar ultraviolet-B irradiance. Dermato-Endocrinology, 2009;1:207–14.

23. Grant WB, Schwalfenberg GK, Genuis SJ, Whiting SJ. An estimate of the economic burden and premature deaths due to vitamin D deficiency in Canada, Molec Nutr Food Res. 2010 Mar 29. [Epub ahead of print]

24. Grant WB, Schuitemaker G. Health benefits of higher serum 25-hydroxyvitamin D levels in The Netherlands. J Steroid Biochem Molec Biol. 2010 Apr 14. [Epub ahead of print]

25. Zittermann A. The estimated benefits of vitamin D for Germany. Mol Nutr Food Res. 2010 Apr 1. [Epub ahead of print]

26. Heaney RP, Davies KM, Chen TC, Holick MF, Barger-Lux MJ. Human serum 25-hydroxycholecalciferol response to extended oral dosing with cholecalciferol. Am J Clin Nutr. 2003;77:204-10.

Principal author's response to the August 24, 2009 comments by the chief editors

James Heller — 2010-03-11T14:11:34Z

December 21, 2009

Editors-in-Chief, Journal of Occupational Medicine and Toxicology

Prof. Axel Fischer (Email: axel.fischer@charite.de)
Head, Allergy Research Division
Charité - School of Medicine, Free University and Humboldt University of Berlin
Berlin, Germany

Prof. David A. Groneberg (Email: david.groneberg@charite.de)
Professor and Director, Institute of Occupational Medicine
Charité - School of Medicine, Free University and Humboldt University of Berlin
Berlin, Germany

Dear Sirs:

Re: Science and industry: Conflict-of-interests in the field of toxicology

I am writing to respond to your letter of August 24, 2009 commenting on our manuscript, New views on the hypothesis of respiratory cancer risk from soluble nickel exposure; and reconsideration of this risk's historical sources in nickel refineries, published in the JOMT in September 2009. I have been away this fall and this is my first opportunity to address certain issues raised by your letter; and to correct one matter in our paper.

First, the correction: our paper was originally submitted on February 15, 2008, not March 5, 2009. It was peer reviewed, subsequently rewritten, and resubmitted in revised form on March 5, 2009. Following further minor revisions, it was accepted for publication in early June 2009, and published in September 2009. Please make the necessary revisions to the online paper on your journal’s website.

Second, it is truly unfortunate that you have chosen to write this letter. You and your publisher had the option at the time of the manuscript’s first submission in February 2008 to consider it for publication or to refuse its consideration when it raised questions of ‘integrity’ and ‘conflict of interest’ in your minds. However, to choose this third option of passing the paper and ourselves through an intensive, 18 month peer review, rewriting and revision process, before revealing your position to your readership and ourselves was underhanded and mean spirited behaviour, and likely violates codes of ethical conduct for peer reviewed scientific journalism.

Let me provide you with some background concerning the sponsorship issue. Since the current regulatory view is that all nickel compounds are carcinogenic (viz. IARC’s March 2009 Meeting on nickel), all new hypotheses testing their carcinogenicity must, perforce, be ‘negative’ hypotheses and, in your opinion therefore, ‘pro-industry’ hypotheses. In fact, our hypothesis arose from observations by environmental professionals in several nickel refineries that soluble nickel was unwarrantedly being characterized as carcinogenic; and that the supporting evidence for this opinion appeared to be concentrated in KNR’s epidemiology. As the previous administrative head of a government agency legislatively mandated to investigate industrial disease in Ontario, I had a great deal of experience in this field and was asked to investigate the basis for the opinion concerning soluble nickel’s carcinogenicity. At no time was my research on this issue interfered with or my views prescribed. On the contrary, I had access to industry professionals and data from around the world whenever I needed information unavailable through public channels, thanks to my co-author, Dr. Bruce R. Conard. Consequently, the scientific judgments reached in the submitted manuscript and its integrity rest entirely on my shoulders since I enjoyed a de facto arm’s length relationship with my sponsors. You couldn’t have known that in advance but this fact goes to the heart of my concerns about your reactionary and self-righteous behaviour.

It is reflexively assumed that industry sponsored research is inherently biased whereas research originating in academic institutions or public health agencies is inherently unbiased; and that the peer reviewed scientific literature provides a fact based body of knowledge upon which sound regulatory policy on chemicals can be constructed. Our ability to look beyond the published literature, however, has shown that its conclusions cannot always be taken at face value; and that regulators who rely unquestioningly on this source of information to build policy are liable to serious errors in scientific judgment.

This brings me to the freedom of speech issue. Your readers should appreciate that the publisher disallowed publication of fifteen files of additional data and information attached to our paper out of fear of infringing the intellectual property rights of their original owners. Yet we had already confirmed that this information was in the public domain and had been filed previously with regulators (e.g. environmental data) or with nickel researchers who eventually published their work [e.g. Thornhill (1986) was filed with Sir Richard Doll’s ICNCM Committee whose research appeared in ICNCM (1990)], or with other publicly accessible repositories. Those files were intended to support the conclusions in our paper and reconsideration of regulatory policy on nickel. Even worse, the publisher suggested rewording of a sentence in the concluding remarks of the abstract to our paper, again fearing liability with the strong implication that it would not be published had we refused the proposed change. This is censorship! So it is ironic indeed that you are taking pride in your liberal views on freedom of speech when we were forced to comply with your publisher’s censorial dictates.

The JOMT informs us that there have been 1,488 accesses to the article since its publication (not including PubMed Central or other archive sites), a level the journal rates as ‘Highly Accessed’ relative to age. In the 3+ months since its publication, however, the paper has not generated a single comment. This can only mean that, by tainting honestly conducted research with innuendoes of bias, your reckless letter has effectively discouraged debate and discussion by the interested readership. This result is antithetical to the aims of science, scholarship and journalistic integrity. I write, therefore, to request a retraction of your remarks and an apology. I also request that these responses be posted alongside this letter and our article on the JOMT website.

Yours sincerely,

James G. Heller, PhD, DECH

c.c. Bruce R. Conard

Response to comments posted by Drs David A. Groneberg and Axel Fischer, JOMT Editors-in-Chief

Adriana Oller, Ph.D., DABT — 2010-03-11T14:10:47Z

In their comments, JOMT editors suggest that arguments made in the Heller et al. paper were not supported by solid scientific data, but they decided to publish this paper because "it can be regarded as a typical example of the approach of private companies towards the scientific discussion of compound toxicity and carcinogenicity," among other reasons. If the editors were of the view that the Heller et al. paper was not based on solid science, then it was their responsibility to reject it, as the whole purpose of the peer-review process is to ensure publication of sound science. Whether the author of a paper is an industry scientist or an academic scientist, different opinions can aid the scientific discourse as long as they are supported by solid, transparent data and subjected to the process of thorough peer review. No paper should be published unless this criterion is met.

As a toxicologist employed by the nickel industry (NiPERA), I believe that the nickel industry can and does support and publish scientifically rigorous studies. Although I disagree with the way that Heller et al. interpreted the nickel animal toxicology data and believe that the overall assertive tone of the paper goes beyond what the data warrants, this paper raises awareness about some key nickel refinery issues that could have (in a different format) contributed to the scientific debate on the carcinogenicity of soluble nickel. However, as it stands now, the JOMT missed an opportunity to assure that Heller’s paper meets accepted scientific standards. Publication of Heller’s paper in an appropriate format might have provided useful input to scientific debate in this area.

Adriana R. Oller, Ph.D, DABT
Toxicologist with NiPERA (Nickel Producers Environmental Research Association)

Science and industry: Conflict-of-interests in the field of toxicology

David A. Groneberg — 2009-08-24T10:45:55Z

In this report by Heller et al., two companies which are involved in the exploration, mining, and processing of nickel, sponsored a study that questions soluble nickel as a carcinogenic substance.
Although the editors agreed to publish this hypothesis, we feel that some clarifying words should be stated:

1) The editors-in-chief and the publisher questioned the integrity of the article on first sight. The first impression was to reject the article due to the magnitude of the conflict of interest. This conflict of interest arises from the nature of the sponsoring companies: The companies are Vale Inco and Falconbridge Ltd. Vale Inco is the second largest mining company in the world, with a market capitalization of more than US$ 125 billion and over 12,000 employees worldwide with net sales last year of over US$8 billion last year [1]. The second company Falconbridge Limited was a Canadian natural sources company that was absorbed in 2006.
2) After reviewing the article, the editors-in-chief decided to publish the article because: a) the conflict of interest is clearly stated: “Drs. Heller and Conard received financial support from Vale Inco Ltd. for the preparation of this paper. Dr. Heller also received financial support previously from Falconbridge Ltd. to conduct the underlying research in this paper. Mr. Thornhill has received no financial support.” b) the article reviews a large amount of studies and data – although partly onesided – that should be discussed by other non-biased scientists and c) it can be regarded as a typical example of the approach of private companies towards the scientific discussion of compound toxicity and carcinogenity.

The authors hypothesize that the true causes of historical lung cancer risk at certain nickel refineries may lie in other exposures, including insoluble nickel compounds, arsenic, sulphuric acid mists and smoking. This hypothesis is based by their failure to accurately identify the source(s) of observed lung cancer risk in one nickel refinery (KNR).
Freedom of speech is an important issue in science but also, the integrity of arguments represents a keystone when it comes to the discussion of toxic and carcinogenic effects. Ideally, scientists that are involved in research on nickel toxicity should now discuss the different points raised by Heller et al. in order to substantiate the knowledge on nickel toxicity.

David A. Groneberg, MD
Editor-in-Chief, Journal of Occupational Medicine and Toxicology
Professor of Medicine/Occupational Medicine

Axel Fischer, MD
Editor-in-Chief, Journal of Occupational Medicine and Toxicology
Professor of Medicine/Allergy

[1] http://www.inco.com/
[2] http://www.xstrata.com/

its a good report about music

Gul Ghuttai — 2009-01-27T18:28:18Z

HI<br><br> this is a very informative article..i learned a lot from it. I want to ask that is music also toxic to brain? are there new experiments done in this regard?

DENTAL ASSISTANTS (and the rest of the dental personnel) MUST BE GLAD

Servando Pérez-Domínguez — 2008-08-21T16:16:22Z

INDEED, dental assistants and the rest of the dental personnel, including dentists, must be glad because their professions (considered by the International Labour Organization as professions at risk for Chronic Mercury Poisoning), are, at last, really starting to be better studied, and, therefore, the dangers are timidly starting to be not fully hidden at the Faculties of Dentistry, Medicine, etc., or ‘underneath’ research projects, books or articles written by authors with various conflicts of interest, empty words, promises... We all know (the FDA had to recently recognised it publicly: www.mercuriados.org/es/pag254), that also those who have in their mouths dental amalgam fillings are at risk (but this was not the aim of this article).

Most probably, future generations will hardly understand why such dental material was still generally used in the 21st century, without at least considering the Precautionary Principle, and also knowing that, as Prof. Dr. Maths Berlin stated in the 2003 Report for the Swedish Dental Material Commission “Mercury in Dental-Filling Material--An Updated Risk Analysis in Environmental Medical Terms" — www.toxicteeth.org/Berlinbilaga.doc: “…fully adequate and less toxic alternatives are available” (p. 25).

All in all, our most sincere CONGRATULATIONS to the authors for conducting the research and for writing the article, and also our sincere CONGRATULATIONS to the Journal of Occupational Medicine and Toxicology for publishing the article, and, thus, allowing the readers to continue learning about the subtle (but relevant) health effects of such powerful heavy metal.

Santiago de Compostela, 20th August 2008

Servando.

www.mercuriados.org

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Prof. Servando Pérez-Domínguez

(President of the mercury poisoned patient organisation MERCURIADOS, and Medicine Student)

University of Santiago de Compostela, Spain

Email: servando.mercuriados@gmail.com

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"Real science is the one always open for constructive discussion" (José Ortega y Gasset).

Need for greater restraint in prescribing skeletal muscle relaxants specially to the elderly

Samuels hurstong — 2008-01-02T09:14:39Z

I would like to add to this article by pointing out the potential toxicity of skeletal muscle relaxant at theraputic doses, especially in the elderly population. I am interested in geriatric medicine, as guest faculty at UCSF we have seen a spate of confusion and agitation associated with the prescription of this class of drugs recently. Poly pharmacy in the elderly is something that needs to be looked at. This class of agents in particular can be associated with vast manifestations.