Bibliographic record
Abstract
Introduction and Objectives:The efficacy of treatment with curative intent in patients with locally advanced prostate cancer (aPCA) is a subject of continuous debate.We tested the impact of initial treatment type (radical prostatectomy [RP], radiotherapy, hormonal therapy [HT] and observation) on cancer-specific (CSM) and other-cause mortality (OCM).Methods: We focused on 3910 patients with clinically T3-T4 PCa, within the Surveillance, Epidemiology, and End Results-Medicare linked database.Patients were stratified according to treatment type, and either Gleason score or age categories.Competing-risks survival plots and regression analyses were used to estimate the impact of treatment type on CSM and OCM rates.Results: At 10 years, CSM and OCM rates were respectively 14 and 28% in RP patients vs. 20 and 38% in radiotherapy patients vs. 36 and 47% in HT patients vs. 26 and 49% in observation patients (all p≤0.001).The same trend was observed when patients were stratified according to Gleason score or age groups.In the multivariable competing-risks analyses, the adjusted hazard ratios recorded for RP, radiotherapy, and HT were respectively 0.51 (95% CI: 0.36-0.72),0.80 (95% CI: 0.65-0.99),and 1.28 (95% CI: 1.05-1.56)relative to observation (all p≤0.04).Conclusions: Our results indicate that patients with locally aPCA should be considered for treatment options with curative intent (RP or radiotherapy), whenever feasible, regardless of tumour characteristics or patients age.With respect to treatment type, RP appears to provide the most favourable CSM rates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.543 | 0.292 |
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".