Abstract 3461: Smoking cessation following a limited 5A intervention in a cohort of patients with head and neck cancer attending for treatment at a regional cancer program in Ontario, Canada
Bibliographic record
Abstract
Abstract A smoking cessation intervention at the time of cancer treatment is an important opportunity to improve patient quality of life, treatment outcome, and survival in people with cancer. This prospective observational study was designed to assess intention to quit, motivation to quit, smoking characteristics and interest in smoking cessation, and assessment of cessation following a standardized smoking cessation intervention. The intervention was a limited clinical 5A intervention offered by trained health professionals and occurred within a dental oncology clinic that offered regular follow-up and any needed pharmacotherapy through the course of cancer treatment. The cohort was composed of head and neck cancer patients who were self-reported ever-smokers at enrolment and who attended the Northeast Cancer Centre, a regional cancer centre in Northeastern Ontario, Canada, for cancer treatment. There were 377 cancer patients who participated in study, with 35.8% (n = 135/377) self-reporting as current smokers. Most current smokers had high nicotine dependence, with 82.2% (n = 111/135) reporting a time to first cigarette (TTFC) of 30 minutes or less; 84.4% (n = 114/135) were interested in quitting smoking. By 1 year post intervention 10 patients had died and 28 patients were lost to follow-up; of the remainder 29 smokers had cessated yielding a cessation rate of 29.9% (n = 29/97); or 23.2% (n = 29/125) conservatively assuming those lost to follow-up remained current smokers. Offering comprehensive smoking cessation during the course of cancer treatment yields long term smoking cessation benefits in a cohort of patients with smoking associated cancers. Citation Format: Michael S.C. Conlon, Deborah P. Saunders. Smoking cessation following a limited 5A intervention in a cohort of patients with head and neck cancer attending for treatment at a regional cancer program in Ontario, Canada. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3461.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".