Emerging novel therapies in the treatment of castrate-resistant prostate cancer
Bibliographic record
Abstract
The treatment options for patients with castration-resistant prostate cancer (CRPC), until very recently, only included docetaxel. In the past 10 months, newly Federal Drug Administration (FDA) approved agents in the United States have shown survival benefit for patients with CRPC. This review takes a closer look at these newer agents: sipuleucel-T (immune therapy) and cabazi-taxel (cytotoxic therapy). We also review the evidence supporting the FDA's approval of denosumab (bone-targeted therapy) as a treatment option for men with CRPC and bony metastases. Newer agents currently being investigated in phase III clinical trials for their potential role in metastatic CRPC are also reviewed. These agents include abiraterone (hormonal therapy), TAK-700 (hormonal therapy), MDV3100 (hormonal therapy), ipilimumab (immune therapy), zibotentan (endothelin-A receptor antagonist) and dasatinib (tyrosine kinase inhibitor). As ongoing studies using all the aforementioned agents continue to evolve, our understanding of how and where these agents fit into the treatment paradigm for patients with CRPC will become clearer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".