THE EFFECT OF SMOKING ON OUTCOME FOLLOWING EXTERNAL RADIATION FOR LOCALIZED PROSTATE CANCER
Bibliographic record
Abstract
PURPOSE: We investigated whether a smoking habit affects biochemical and survival outcome after curative external beam radiation therapy (EBRT) for localized prostate cancer. MATERIALS AND METHODS: The study population comprised 601 men treated with curative EBRT between 1994 and 1997 who had a smoking history available. Pretreatment prognostic factors were examined and high risk was defined as any of prostate specific antigen greater than 20, Gleason greater than 7 or stages T3-4. Biochemical outcome (bNED) was assessed by American Society for Therapeutic Radiology and Oncology, and Houston criteria. Biochemical, clinical, prostate cancer and nonprostate cancer death rates were examined by univariate and multivariate statistics. RESULTS: Of the men 15% were current smokers, 55% were former smokers and 31% were nonsmokers. Current smokers were younger than former smokers or nonsmokers by a mean of 2.5 years (p <0.001). Current smokers had higher risk cancers than former smokers or nonsmokers (high risk 60%, 40% and 43%, respectively, p = 0.017). Five-year bNED rates for smokers were significantly worse than for former smokers or nonsmokers (55%, 69% and 73%, p = 0.01 and 0.0019, respectively). Median followup was 59 months. Multivariate analysis confirmed smoking as an independent adverse factor for bNED (p = 0.013) even when controlling for prostate specific antigen (p <0.0001), Gleason score (p <0.0001), stage (not significant), radiation dose (not significant) and neoadjuvant hormone use (p = 0.0014). Local and metastatic failure did not differ among the groups. Prostate cancer specific mortality was nonsignificantly worse in smokers but overall mortality was much greater. CONCLUSIONS: Smokers present with higher risk prostate cancers. Outcomes following EBRT are poorer, even when accounting for differences in known pretreatment factors.
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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 | 0.001 | 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".