The role of social exposure to smoking on smoking cessation in adult cancer survivors.
Bibliographic record
Abstract
9536 Background: We previously described a strong inverse relationship between social smoking exposures (at home, spousal and with peers) and smoking cessation in lung cancer, with adjusted odds ratios (aOR) of 3-8 (Eng et al, ASCO 2012, abst 9032). In the current analysis, we evaluated whether these associations hold true in adult cancers in general, particularly cancers not traditionally known to have smoking as a risk factor. Methods: 616 cancer survivors across multiple cancer sites were surveyed on their smoking, alcohol, and physical activity habits before and at various times after cancer diagnosis. Social smoking exposures were documented. Multivariate logistic regression models evaluated the association of each variable with change in each habit after diagnosis adjusted for significant socio-demographic and clinico-pathological covariates. Results: Median follow-up after diagnosis was 26 months. 15% had breast cancers; 15% gastrointestinal; 20% genitourinary-gynecological; 24% haematological; 36% other. Among current smokers at diagnosis, 56% quit after diagnosis; no ex- or never-smoker restarted. Patients without secondary home smoking exposure were significantly more likely to quit smoking than those with home exposures (aOR=9.5, 95% CI [2.4-37.8]). Similar results were seen in patients with non-smoking spouses versus smoking spouses (aOR=3.7 [1.0-13.4]), and with lack of peer smoke exposure (aOR=3.7 [1.3-10.7]). 63% patients who quit did so in the 1 year period surrounding the diagnosis date (6-months pre or post diagnosis). In comparison, first and second-hand smoking exposures did not affect other modifiable behaviours such as alcohol or physical activity. Patient awareness of quality of life and survival benefits of smoking cessation and receiving smoking cessation counselling were not associated with improved smoking cessation. Conclusions: Secondary smoking exposures are associated with lack of smoking cessation in adult cancer survivors, even in cancers not traditionally linked to smoking. Being diagnosed with cancer may be an important `teachable moment` to help patients quit, but results are strongly influenced by the surrounding social exposure to smoking. PS and GL contributed equally.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".