The Combination of Effects on Lung Cancer of Cigarette Smoking and Exposure in Quebec Chrysotile Miners and Millers
Bibliographic record
Abstract
Although it is well known that both cigarette smoke and microscopic airborne asbestos fibres can cause lung cancer, evidence as to how these two agents combine is nebulous. Many workers have believed in the multiplicative theory, whereby asbestos increases the risk in proportion to the risk from other causes. However, evidence against this theory is mounting: a recent review concluded that the multiplicative hypothesis was untenable, and that the relative risk of lung cancer from asbestos exposure was about twice as high in non-smokers as in smokers, a finding largely independent of type of asbestos fibre. The criteria for entry to the current study were met by 7279 men in the 1891-1920 birth cohort of Quebec chrysotile miners and millers. The data consisted of date of birth, place of employment, smoking habit, asbestos exposure accumulated to age 55 and, for those 5527 who died between 1950 and June 1992, date and cause of death; 533 of the deaths were from lung cancer. For the principal analyses, ex-smokers were excluded from the study cohort, which comprised 5888 men, of whom 473 died of lung cancer. The conventional form of analysis is simply of the double dichotomy: non-smokers of cigarettes, 'unexposed' and exposed; all others, 'unexposed' and exposed. The respective standardized lung cancer mortality ratios (SMRs) were 0.29 and 0.62; and 1.37 and 1.72. Thus, the differences in relative risk, due to exposure, were closely similar, 0.33 and 0.35. On the other hand, the effects of asbestos measured by the corresponding ratios, 2.12 and 1.25, did differ, being 1.7 times as high in non-smokers as in others. The principal analysis was much more penetrating: the method was to fit models to a 'disaggregated' 6 x 10 array, by smoking habit (excluding ex-smokers) and asbestos exposure, of lung cancer SMRs. Both linear and log-linear models were fitted: the former included the additive and linear-multiplicative; the latter embraced the more conventional multiplicative form. The additive model fitted much the best. The fit of each multiplicative model was improved by the introduction of an interaction term that implied a less than multiplicative relationship. Thus smoking and exposure to chrysotile appear to have acted independently in causing lung cancer, with 10 cigarettes a day having an effect roughly equivalent to exposure amounting to 700 million particles per cubic foot x years. The refutation of the multiplicative hypothesis in these data reinforces its inapplicability in general; but the additive hypothesis is not generally applicable either. Indeed, there seems to be no good reason to believe that interactions conform to any simple theory. The implications are important.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".