Abiraterone in the management of castration-resistant prostate cancer prior to chemotherapy
Bibliographic record
Abstract
The treatment armamentarium for metastatic castration-resistant prostate cancer (mCRPC) has increased significantly over the past several years. Approved drugs associated with improved survival include androgen pathway-targeted agents (abiraterone acetate and enzalutamide), chemotherapeutics (docetaxel and cabazitaxel), an autologous vaccine (sipuleucel-T) and a radiopharmaceutical (radium-223). Abiraterone acetate, a prodrug of abiraterone, inhibits the CYP17A enzyme, a critical enzyme in androgen biosynthesis. Abiraterone has regulatory approval in mCRPC in both chemotherapy-naïve patients and in the post-docetaxel setting based on results from two randomized phase III studies. In the COU-AA-302 trial, abiraterone demonstrated significant improvement in the coprimary endpoints of radiographic progression-free survival and overall survival, as well as in a number of secondary endpoints including time until initiation of chemotherapy, time until opiate use for cancer-related pain, prostate-specific antigen progression-free survival and decline in performance status. Abiraterone is well-tolerated, although adverse events associated with this agent include abnormalities in liver function testing and mineralocorticoid-associated adverse events. This review evaluates the use of abiraterone in mCRPC prior to the use of chemotherapy.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".