Adjuvant vs. salvage radiation therapy in men with high-risk features after radical prostatectomy: Survey of North American genitourinary expert radiation oncologists
Bibliographic record
Abstract
INTRODUCTION: The management of patients with high-risk features after radical prostatectomy (RP) is controversial. Level 1 evidence demonstrates that adjuvant radiation therapy (RT) improves survival compared to no treatment; however, it may overtreat up to 30% of patients, as randomized clinical trials (RCTs) using salvage RT on observation arms failed to reveal a survival advantage of adjuvant RT. We, therefore, sought to determine the current view of adjuvant vs. salvage RT among North American genitourinary (GU) radiation oncology experts. METHODS: A survey was distributed to 88 practicing North American GU physicians serving on decision-making committees of cooperative group research organizations. Questions pertained to opinions regarding adjuvant vs. salvage RT for this patient population. Treatment recommendations were correlated with practice patterns using Fisher's exact test. RESULTS: Forty-two of 88 radiation oncologists completed the survey; 23 (54.8%) recommended adjuvant RT and 19 (45.2%) recommended salvage RT. Recommendation of active surveillance for Gleason 3+4 disease was a significant predictor of salvage RT recommendation (p=0.034), and monthly patient volume approached significance for recommendation of adjuvant over salvage RT; those seeing <15 patients/month trended towards recommending adjuvant over salvage RT (p=0.062). No other demographic factors approached significance. CONCLUSIONS: There is dramatic polarization among North American GU experts regarding optimal management of patients with high-risk features after RP. Ongoing RCTs will determine whether adjuvant RT improves survival over salvage RT. Until then, the almost 50/50 division seen from this analysis should encourage practicing clinicians to discuss the ambiguity with their patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Research integrity | 0.001 | 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".