Systemic therapy after first-line docetaxel in metastatic castration-resistant prostate cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: There is an urgent need for systemic treatment options for patients with castration-resistant prostate cancer who have progressed after receiving first-line docetaxel chemotherapy. The purpose of this article is to review recent developments in this area. RECENT FINDINGS: Retreatment with docetaxel has been employed with evidence of activity in selected populations. Mitoxantrone, the previous first-line standard based on its palliative effect, has also been used with clinical responses observed; however, the symptom benefit in this setting has not been established. Several classes of cytotoxic agents have been tested including platinum agents (satraplatin), epothilones (ixabepilone and patupilone) and taxanes (XRP-6258). A number of targeted therapies have also been clinically evaluated including inhibitors of cytoprotective chaperones (OGX-011) and the vascular endothelial growth factor receptor (sorafenib, sunitinib, and cediranib). An area generating great interest has been the development of agents that target the androgen receptor axis more effectively (MDV3100 and abiraterone) with encouraging early phase trial results. SUMMARY: There is no accepted standard systemic treatment for patients with castration resistant prostate cancer and progressive disease after docetaxel. Novel agents are in phase II and III clinical testing in this setting.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".