Influence of aggressive-variant prostate cancer (AVPC) features on outcome of metastatic hormone-sensitive prostate cancer (mHSPC) treated by chemohormonal therapy (CHT).
Bibliographic record
Abstract
193 Background: Outcomes of patients (pts) undergoing CHT for mHSPC are heterogeneous, with some rapidly developing castration-resistance (CRPC). While AVPC ("anaplastic") features are described in CRPC, less is known in the mHSPC setting. In this multi-institutional cohort, we explored pre-treatment factors associated with poor outcome. Methods: De-novo mHSPC pts treated with CHT from June 2014 to July 2017 at The Ottawa Hospital Cancer Centre (TOHCC) and London Regional Cancer Centre (LRCC) were retrospectively identified. AVPC features (defined below) were collected and cumulatively scored (0, 1, or 2+), along with baseline, treatment and outcome data. Statistical comparisons utilized Cox regression analysis and Kaplan-Meier method for association with CRPC and survival. Results: 92 pts (58 TOHCC, 34 LRCC) met inclusion for study; 83 (90%) had "high-volume" disease (≥4 bone lesions; or ≥1 visceral metastasis), 69/73 (95%) prostate biopsies scored Gleason 8-10, and 55 (60%) had AVPC features: >5 cm nodal/pelvic mass (28), visceral metastases (21), lytic bone metastases (16), elevated LDH (12), low PSA (4), or neuroendocrine differentiation (2). Pre-docetaxel PSA fall of <50, 50-75, 75-90, and ≥90% baseline occurred in 12, 13, 19, and 56% respectively. Docetaxel was initiated a median of 66 days after androgen-deprivation, with 82% completing 5 or 6 cycles. 9 pts (10%) progressed during docetaxel, and 31 pts (34%) developed CRPC < 12 months. Median time to CRPC was 18.4, 14.0, and 11.0 months for 0, 1, and 2+ AVPC features (log rank p=0.009). CRPC was also associated with pre-docetaxel PSA fall <75% (p<0.001) and high alkaline phosphatase (p=0.016). At 18 months median follow-up, 16/55 (29%) with AVPC features have died versus 1/37 (3%) without (log rank p=0.001). In multivariable analysis, AVPC features and pre-docetaxel PSA fall were independently (p<0.05) associated with survival. Conclusions: In our study, mHSPC pts with AVPC features and suboptimal (<75%) pre-docetaxel PSA decline had poor prognosis. These features should be validated in larger cohorts to potentially identify mHSPC pts suitable for further study in clinical trials.
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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 | 0.000 | 0.000 |
| 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".