Abstract 4453: Smoking characteristics, intention to quit, and nicotine dependence in patients with head and neck cancer
Bibliographic record
Abstract
Abstract There are high rates of smoking among head and neck cancer patients, and successful smoking cessation may offer a treatment and survival benefit for these patients. This prospective study was designed to assess baseline smoking characteristics, and intention to quit in a cohort of patients with head and neck cancer. All patients attended the dental oncology clinic within the regional cancer centre for assessments before, during, and after primary treatment. Primary treatment included one or more of radiation therapy, chemotherapy, or surgery. Participation in this study was offered to ever smokers (defined as having smoked at least 100 cigarettes in their lifetime), and involved completing a questionnaire that assessed baseline smoking related behaviours, including nicotine dependence using the Fagerstrom Test for Nicotine Dependence (FTND), and intention to quit smoking. Patients were asked for consent to provide a saliva sample for genetic analyses and for future contact to assess smoking cessation and other health-related outcomes. Personalised counselling about smoking cessation, by trained staff, was also offered. One hundred and eleven consecutive patients have agreed to participate. Most (77 %) are male, with a median age of 65 years (range 36-92 years). Participants reported a median of 37 pack-years of smoking, and 43% were nicotine dependent (FTND score indicating high or very highly dependent). Nicotine dependence level was significantly associated with smoking status at enrolment, with current smokers more likely to report significantly higher nicotine dependence levels than those who were not smoking (p=0.03). While 96% (n=104) of the participants had previously attempted smoking cessation, 35% (n=39) were current smokers at study enrolment. Most of the current smokers (80%) were interested in quitting smoking and in receiving personalized counselling for cessation. This study demonstrates the need to support cessation efforts in this population of cancer patients, and highlights the role of nicotine dependence and smoking behaviour. Future research into smoking cessation methods, including the role of genetic variants in nicotine dependence and cessation, may help us better address smoking behaviours in cancer patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4453. doi:1538-7445.AM2012-4453
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".