Smoking Behaviours of Current Cancer Patients in Canada
Bibliographic record
Abstract
Evidence shows that continued smoking by cancer patients leads to adverse treatment outcomes and affects survival. Smoking diminishes treatment effectiveness, exacerbates side effects, and increases the risk of developing additional complications. Patients who continue to smoke also have a higher risk of developing a second primary cancer or experiencing a cancer recurrence, both of which ultimately contribute to poorer quality of life and poorer survival. Here, we present a snapshot of smoking behaviours of current cancer patients compared with the non-cancer patient population in Canada. Minimal differences in smoking behaviours were noted between current cancer patients and the rest of the population. Based on 2011-2014 data from the Canadian Community Health Survey, 1 in 5 current cancer patients (20.1%) reported daily or occasional smoking. That estimate is comparable to findings in the surveyed non-cancer patient population, of whom 19.3% reported smoking daily or occasionally. Slightly more male cancer patients than female cancer patients identified as current smokers. A similar distribution was observed in the non-cancer patient population. There is an urgent need across Canada to better support cancer patients in quitting smoking. As a result, the quality of patient care will improve, as will cancer treatment and survival outcomes, and quality of life for these patients.
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".