Retrospective study on the benefit of adjuvant radiotherapy in men with intraductal carcinoma of prostate
Bibliographic record
Abstract
Intraductal carcinoma of the prostate (IDC-P) is an independent biomarker of recurrence and survival with particular treatment response, yet no study has tested its response to radiotherapy. The aim of our project was to test the impact of adjuvant radiotherapy (ART) in patients with localized to locally advanced prostate cancer (PC) and IDC-P. We performed a retrospective study of men with pT2-T3 PC treated by radical prostatectomy (RP) with or without ART, from two centres (1993–2015). Exclusion criteria were the use of another type of treatment prior to biochemical recurrence (BCR), and detectable prostate- specific antigen (PSA) following RP or ART. Primary outcome was BCR (2 consecutive PSA ≥ 0.2 ng/ml). Patients were grouped by treatment (RP only /RP + ART), IDC-P status, and presence of high-risk features (HRF: Grade Groups 4–5, positive margins, pT3 stage). We reviewed 293 RP specimens (median follow-up 99 months, 69 BCR). Forty-eight patients (16.4%) were treated by RP + ART. Multivariate Cox regression for BCR indicated that IDC-P had the strongest impact (hazard ratio [HR] = 2.39, 95% confidence interval [CI]:1.44–3.97), while ART reduced the risk of BCR (HR = 0.38, 95%CI: 0.17–0.85). Other HRF were all significant except for pT3b stage. IDC-P[+] patients who did not receive ART had the worst BCR-free survival (log-rank P = 0.023). Furthermore, IDC-P had the same impact on BCR-free survival as ≥1 HRF (log-rank P = 0.955). Men with IDC-P who did not receive ART had the highest BCR rates, and IDC-P had the same impact as ≥1 HRF, which are often used as ART indications. Once validated, ART should be considered in patients with IDC-P.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".