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Record W3005004081 · doi:10.1097/jom.0000000000001827

Letter to the Editor: Response to Finkelstein Re: the Fordyce et al. Vermont Talc Miners and Millers Cohort Study Update

2020· letter· en· W3005004081 on OpenAlexaboutno aff
Tiffani A. Fordyce, Megan J. Leonhard, Fionna Mowat, Suresh H. Moolgavkar

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2020
Typeletter
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsnot available
Fundersnot available
KeywordsFinkelstein's testAsbestosMesotheliomaCohortMedicinePopulationFamily medicineDemographyPathologyEnvironmental healthPhysical therapySociology

Abstract

fetched live from OpenAlex

Readers are invited to submit letters for publication in this department. Submit letters online at http://joem.edmgr.com. Choose “Submit New Manuscript.” A signed copyright assignment and financial disclosure form must be submitted with the letter. Form available at www.joem.org under Author and Reviewer information. Reply: We are pleased that we have several points of agreement with Dr Finkelstein. We are in agreement that mesothelioma can occur spontaneously without asbestos exposure and that the rate of mesothelioma in women in the United States is a good approximation to the rate of spontaneous mesothelioma, which implies, of course, that the vast majority of mesotheliomas among women in the United States are not attributable to asbestos exposure. Be that as it may, we reiterate here what we said in our earlier publication1 and discuss in more detail below: it is totally inappropriate to compare mesothelioma rates in an occupational cohort with rates in a population that has never been exposed to asbestos. We are also in agreement with Dr Finkelstein that, even if an excess of mesotheliomas is observed in an occupational cohort, additional investigation needs to be performed before the excess can be attributed to any exposure in the cohort. This principle is well-illustrated in publications by Fritschi et al2 and Boice et al.3 Finally, we are in agreement that standardized mortality ratios (SMR) should not be estimated for mesothelioma or, for that matter, for any other disease for which International Classification of Disease (ICD) codes are not available over the period of the study. Indeed, we did not report an SMR for mesothelioma in our study for precisely that reason, although we were able to report SMRs for another rare condition, ocular tumors, because ICD codes were available for this condition over the period of the study.4 For the one case of mesothelioma that we discovered, we followed the procedure to which Dr Finkelstein apparently subscribes and reported all the information that we could, subject to confidentiality considerations.4 That information confirmed that this single case of mesothelioma had asbestos exposure outside the Vermont talc mines and mills.4 Apparently, in his comments, Dr Finkelstein is advocating that the SMR not be used for identifying mesothelioma risks in a cohort even if ICD codes for mesothelioma are available over the entire course of the study. We address this contention later in this response. On other issues, we have fundamental disagreements with Dr Finkelstein. With all due respect to Dr Finkelstein's expertise in the use of PubMed, we can assure him that we have been involved in the conduct and analyses of occupational cohort studies in which workers were incontrovertibly exposed to asbestos; the Vermont cohort cannot be described as an asbestos-exposed cohort as Dr Finkelstein assumes. As we said in our response to Egilman et al,5 the original authors of the Vermont cohort study6 believed that the cohort had not been exposed to either asbestos or substantial levels of silica. In fact, Selevan et al6 chose this particular cohort for study precisely because it was believed not to be exposed to either asbestos or significant levels of free silica. Selevan et al6 say, “[a]s a result of unanswered questions concerning the toxicity of talc free of both asbestiform minerals and significant quantities of free silica, the National Institute for Occupational Safety and Health undertook an industry-wide study (cohort mortality study, industrial hygiene study, and cross-sectional medical examination) of Vermont talcs meeting these criteria (ie, low free silica and no asbestiform minerals).” We understand that the absence of asbestos in Vermont talc is currently disputed, but for Dr Finkelstein to suggest that this is an asbestos-exposed cohort on par with asbestos cement workers, employees at an amosite insulation manufacturing plant, or the cohort of workers in the mines and mills at Libby, Montana, is, to put it mildly, totally preposterous. In any case, the basic principles for the conduct of SMR studies are the same no matter the exposure at issue. We stand by our statements regarding the choice of appropriate control groups for SMR studies and, in particular, for diseases like mesothelioma, for which a distinct ICD code is not available over the entire period of the study. The main goal of an occupational cohort SMR study is to determine whether the workplace environment creates risks that are larger than the risks faced by the underlying population from which the workforce is drawn. It is disingenuous for Dr Finkelstein to suggest that the only reason for the choice of the underlying population as the control group is stability of disease rates. If that were the case, would he use a population from Australia as a control group for an occupational cohort study in Ontario? The SMR study design is a well-established and accepted method in occupational epidemiology and has been used for decades for the investigation of diseases in occupational cohorts, including occupational cohorts exposed to asbestos.7–14 Dr Finkelstein is apparently willing to accept the standard method, based on rates in the population from which the occupational cohort is drawn, for the estimation of the expected number and, therefore, the SMR for every disease condition, even if extremely rare, except mesothelioma. Dr Finkelstein asserts that the appropriate comparison rates for mesothelioma in an occupational cohort SMR study are not rates in the underlying population from which the occupational cohort is drawn but rates from a population that has never been exposed to asbestos. In fact, after 1999, when a code for mesothelioma became available in ICD 10, occupational cohort studies have used this code for the estimation of SMRs for mesothelioma based on rates from the underlying population (eg, Dunning et al7). Using Dr Finkelstein's logic, lung cancer rates in an occupational cohort should be compared with lung cancer rates in never-smokers. He gives the example of a toxicology study in which the rates in a group of animals exposed to a specific suspected carcinogen are compared with rates in a control group not exposed to any carcinogen. In this highly artificial example, we know that every individual in the exposed group has exposure to only the specific suspected chemical at issue and is exposed to no other carcinogen. If a similar situation could be guaranteed in the Vermont talc cohort, that is, if we could be assured that workers in the cohort were not exposed to asbestos either prior to entering the cohort or after leaving it, then use of a control group that has never been exposed to asbestos would be appropriate. But, epidemiology, as Dr Finkelstein surely knows from his 40 years as an epidemiologist, is a lot more complicated. We think the following example illustrates the situation far better than the experimental example provided by Dr Finkelstein. Suppose one were conducting a cohort study to determine whether smoking marijuana increases the risk of lung cancer. The simplest design would have a group of marijuana smokers drawn from the general population and a control group of individuals who had never smoked marijuana drawn from the same population. If, after appropriate follow-up, no increased risk of lung cancer was observed in the exposed group, one could conclude that smoking marijuana does not increase the risk of lung cancer. Of course, the implicit assumption in this simple cohort study is that, with respect to cigarette smoking, the exposed and control groups are balanced. To apply Dr Finkelstein's argument to this situation would require that the control group consists of individuals who had never smoked cigarettes. But then, the marijuana exposed group should also have all cigarette smokers purged, that is, the risk of lung cancer should be estimated only among marijuana smokers who had never smoked cigarettes. Based on the principles enunciated here, we provided the best estimate for the SMR for mesothelioma based on a control rate from Surveillance, Epidemiology, and End Results Program in our response1 to Egilman et al.5 We stand by this estimate. Dr Finkelstein's estimates of rate ratios, based as they are on mesothelioma rates in a population never exposed to asbestos, are not credible.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.015
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0040.001
Research integrity0.0150.020
Insufficient payload (model declined to judge)0.0090.008

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.277
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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