Patterns of referral for adjuvant radiotherapy after radical prostatectomy in men with prostate cancer: A population-based analysis.
Bibliographic record
Abstract
140 Background: Randomized trials have shown improved biochemical disease free survival after adjuvant radiotherapy (ART) in patients with pT3 or margin positive disease after radical prostatectomy for prostate cancer. This study examines the rates of referral to a radiation oncologist for patients with high risk pathologic features after prostatectomy. Also, the impact of the presentation of these randomized trials will be examined. Methods: All men diagnosed in the province of Manitoba with prostate adenocarcinoma between 2003 and 2008 who underwent radical prostatectomy were identified through a central cancer registry database. Manual chart review was performed and detailed demographic and clinico-pathologic data were analyzed to determine their influence on referral to a radiation oncologist within 6 months of surgery. Analysis of referral rates before and after the presentation of 2 randomized trials were also examined. Results: A total of 1080 patient records of men undergoing prostatectomy for prostate cancer were reviewed. Of these, 546 (50.6%) men had at least one high risk pathologic feature. This includes pT2 margin positive disease in 298/546 (54.6%), pT3a in 154/546 (28.2%), and pT3b in 94/546 (17.2%). Multivariable logistic regression was performed adjusting for age, distance from cancer centre, Gleason score, T stage, perineural invasion, and margin status. Gleason score 8-10 (p<0.0001), higher pathologic T stage (p<0.0001), and farther distance (p=0.0028) were associated with referral for ART. Age and margin status were not significantly associated. Men with pT3a (odds ratio 3.35) and pT3b disease (odds ratio 5.32) were more likely to be referred than pT2 margin positive disease (p<0.0001). There were 78/546 (14.3%) patients with a high risk factor who were referred for ART within 6 months of surgery. The rates of referral were not significantly different before and after the presentation of randomized trials (p=0.60). Conclusions: Men with higher pathologic stage (pT3) and grade (Gleason 8-10) are more likely to receive ART. However, referral for ART did not increase significantly after presentation of the randomized trials and remains underutilized.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".