Longitudinal smoking patterns in survivors of childhood cancer: An update from the Childhood Cancer Survivor Study
Bibliographic record
Abstract
BACKGROUND: Survivors of pediatric cancer have elevated risks of mortality and morbidity. Many late adverse effects associated with cancer treatment (eg, second cancers and cardiac and pulmonary disease) are also associated with cigarette smoking, and this suggests that survivors who smoke may be at high risk for these conditions. METHODS: This study examined the self-reported smoking status for 9397 adult survivors of childhood cancer across 3 questionnaires (median time interval, 13 years). The smoking prevalence among survivors was compared with the smoking prevalence among siblings and the prevalence expected on the basis of age-, sex-, race-, and calendar time-specific rates in the US population. Multivariable regression models examined characteristics associated with longitudinal smoking patterns across all 3 questionnaires. RESULTS: At the baseline, 19% of survivors were current smokers, whereas 24% of siblings were current smokers, and 29% were expected to be current smokers on the basis of US rates. Current smoking among survivors dropped to 16% and 14% on follow-up questionnaires, with similar decreases in the sibling prevalence and the expected prevalence. Characteristics associated with consistent never-smoking included a higher household income (relative risk [RR], 1.16; 95% confidence interval [CI], 1.08-1.25), higher education (RR, 1.32; 95% CI, 1.22-1.43), and receipt of cranial radiation therapy (RR, 1.08; 95% CI, 1.03-1.14). Psychological distress (RR, 0.86; 95% CI, 0.80-0.92) and heavy alcohol drinking (RR, 0.64; 95% CI, 0.58-0.71) were inversely associated. Among ever-smokers, a higher income (RR, 1.17; 95% CI, 1.04-1.32) and education (RR, 1.23; 95% CI, 1.10-1.38) were associated with quitting, whereas cranial radiation (RR, 0.86; 95% CI, 0.76-0.97) and psychological distress (RR, 0.80; 95% CI, 0.72-0.90) were associated with not having quit. The development of adverse health conditions was not associated with smoking patterns. CONCLUSIONS: Despite modest declines in smoking prevalence, the substantial number of consistent current smokers reinforces the need for continued development of effective smoking interventions for survivors.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".