Seminal Vesicle Treatment for Localized Prostate Cancer Treated with External Beam Radiotherapy
Bibliographic record
Abstract
This study retrospectively reviewed data from men with localized prostate cancer treated with external beam radiotherapy (EBRT). We identified 359 men with localized prostate cancer treated with curative EBRT at the Cross Cancer Institute between 2010–2011. The volume of seminal vesicles (SVs) treated as well as dose values were extracted. These volumes were compared to gold standard contours drawn by a trained expert based on consensus European Society for Radiotherapy and Oncology (ESTRO) contouring guidelines. Patient and tumor characteristics were extracted for these patients. Memorial Sloan Kettering prostate cancer nomogram was used to assign a predicted risk of SV involvement for each patient based on baseline tumor characteristics. In patients with a predicted risk of SV involvement greater than 15% (n = 184), 86.5% (SD = 18.6) of the base of the SVs were treated with EBRT, compared to 66.7% (SD = 32.6) for patients with a predicted risk of SV involvement less than 15% (n = 175, p < 0.0001). Similarly, the mean percentage of proximal and total SV volumes treated with EBRT was 75.6% (SD = 24.4) and 68.7% (SD = 26.0) for patients with a predicted risk of SV involvement of greater than 15%, compared to 50.3% (SD = 31.0, p < 0.0001) and 41.0% (SD = 27.8, p < 0.0001) for patients with a risk of less than 15%. The results indicate that all parts of the SVs are more likely to be contoured in men with >15% risk of SV involvement than those with <15% risk. However, radiation oncologists still contour a high percentage of SVs in men with <15% risk of SV involvement, suggesting that there may be over-treatment of SVs that increases the risk of rectal or bladder toxicity.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".