Smoking is associated with worse outcomes in patients with prostate cancer treated by radical radiotherapy
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect of smoking on the outcome in a cohort of men treated for localized prostate cancer at one institution with a uniform protocol of radical external beam radiotherapy (EBRT). PATIENTS AND METHODS: The study was a retrospective review of 434 patients with cT1-T4 N0m0 prostate cancer treated with curative intent with EBRT (66 Gy in 33 fractions) between 1990 and 1999. Univariate and multivariate Cox regression analyses were used to estimate the risk associated with smoking on biochemical failure (American Society for Therapeutic Radiology and Oncology definition), local failure, distant failure, overall and disease-specific survival. RESULTS: The median follow-up was 70.3 months. A smoking history was obtained in 96% of cases; 16.8% were current smokers, 54.4% previous smokers and 28.8% non-smokers. Current smokers presented at a younger median age, by 3.6 years (P = 0.06). There were no differences in clinical T stage, Gleason score or prostate-specific antigen level amongst the three patient groups. Smoking conferred a higher risk of developing metastatic disease in both current smokers (hazard ratio 5.24; 95% confidence interval 1.75-15.72) and previous smokers (2.90, 1.09-7.67). There were also increases in risk, although not quite significant, for biochemical failure (1.49, 0.88-2.40) and overall survival (1.72, 0.94-3.15). CONCLUSIONS: After curative treatment with EBRT, a history of smoking was associated with a greater risk of developing metastatic disease. Smoking status was not associated with worse disease on presentation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".