The management of high-risk, locally advanced, prostate cancer radiation therapy
Bibliographic record
Abstract
Prostate cancer is a common malignancy with 913 000 new cases and 215 000 deaths worldwide in 2008. 1 Risk stratification systems are widely used to assist with patient counselling and guide treatment selection risk, as well to ensure prognostic uniformity in clinical trials and in the evaluation of treatment outcomes.Based on work by D'Amico and colleagues, the Genitourinary Radiation Oncologists of Canada (GUROC) developed a classification system for patients with localized/locally advanced disease based on T category, prostate-specific antigen (PSA) level at diagnosis and Gleason score. 2,3High-risk disease is defined as the presence of any of these factors: cT3 or cT4 category, PSA >20 ng/mL or Gleason score ≥8.Patients studied in clinical trials of "high-risk prostate cancer" represent a very heterogeneous group; this group includes patients with clinically organ-confined disease (cT1/T2) with high Gleason score, and/or PSA and also those with locally advanced disease.In the landmark EORTC (European Organisation for Research and Treatment of Cancer) 22863 trial, overall survival (OS) and local control were considerably improved with the use of 3 years of adjuvant androgen deprivation therapy (ADT) when given with external beam radiotherapy (EBRT) in patients with high-risk locally advanced disease (90% had cT3/T4). 4With a median follow-up of 9.1 years, the survival advantage for combination treatment was substantial with a 10-year OS of 58% in the combined treatment group compared with 40% in the radiotherapy (RT)-only group.However, despite the fact that combined modality treatment was superior to RT alone, the value of local treatment with RT remained under question as it was felt that the benefit seen may have been due to the early introduction of ADT.This has now been explored in three randomized trials (Table 1). 5-
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".