Environmental Tobacco Smoke and Risk of Adult Leukemia
Bibliographic record
Abstract
BACKGROUND: The role of environmental tobacco smoke (ETS) in the causation of lung and breast cancer has been repeatedly evaluated over recent years. In contrast, its impact on the risk of adult leukemia has received little attention. METHODS: We used the lifetime residential and occupational ETS exposure histories from a population-based sample of 1068 incident and histologically confirmed adult leukemia cases and 5039 population controls age 20 to 74 years to evaluate the relationship between ETS exposure and adult leukemia risk among nonsmokers in Canada. The duration of exposure and smoker-years index were used as indices of ETS exposure. We restricted our analysis to the 266 case and 1326 control subjects who reported being lifetime nonsmokers and provided residential ETS exposure history for at least 75% of their lifetime. RESULTS: No association was found for most leukemia subtypes, and in particular for acute myeloid leukemia. In contrast, the risk for chronic lymphocytic leukemia was clearly associated with ETS exposure, with an adjusted odds ratio of 2.3 (95% confidence interval = 1.2-4.5) for more than 83 smoker-years of residential exposure and 2.4 (1.3-4.3) for more than 72 smoker-years of occupational exposure. There was a dose-response relationship for chronic lymphocytic leukemia with both indices of exposure. Risk was not higher with recent exposure, using time-window-exposure analyses. CONCLUSIONS: Regular long-term ETS exposure may be a risk factor for chronic lymphocytic leukemia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".