Treatment outcomes for metastatic castrate-resistant prostate cancer (mCRPC) patients (pts) following docetaxel (D) for hormone sensitive disease.
Bibliographic record
Abstract
78 Background: There is no prospective data to guide optimal selection of treatment for first line (1L) mCRPC after D and androgen deprivation therapy (ADT) is given in the hormone sensitive setting. We explored efficacy of 1L treatment in this group. Methods: Pts with mCRPC treated with D for hormone sensitive disease were identified from a prospectively maintained multi-site mCRPC database (ePAD) of patients treated in a community and academic setting in Australia. 1L treatment, clinicopathologic and outcome data were extracted. Results: We identified 93 pts, median age 65y (range 43–85), who received median 6 cycles of D-ADT and developed mCRPC between May 2013 and Jun 2019. 58% had Gleason ≥ 8, median PSA at diagnosis was 53 ng/mL (range 0.67–7086), 65% had de-novo metastatic disease. Median time to mCRPC was 14.8mo (range 1.3 to 56.9) with median time to 1L 16.3mo (range 2.1–57.2). Eighty-five patients (91%) received at least one further active treatment for mCRPC with outcomes below. Conclusions: Abiraterone, enzalutamide, and cabazitaxel all demonstrate activity for 1L mCRPC following progression on D-ADT. Compared to historical controls, PSA responses appear less than pre-docetaxel, but greater than the post-docetaxel setting.[Table: see text]
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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 | 0.002 |
| 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 | 0.000 |
| 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".