Metastatic castrate-resistant prostate cancer: a new horizon beyond the androgen receptors
Bibliographic record
Abstract
PURPOSE OF REVIEW: Systemic chemotherapy and second-generation androgen receptor-axis targeted therapies have been in the forefront of management for metastatic castrate-resistant prostate cancer (mCRPC) patients with low or high symptom burden. However, in the recent past, due to improvement in molecular characterization, management of mCRPC has witnessed long strides of advancement. We aim to review the novel nonhormonal and nonchemotherapeutic treatment options. RECENT FINDINGS: Poly (ADP-ribose) polymerase inhibitors (PARPis) such as olaparib and rucaparib have been recently approved by the US FDA for use in mCRPC with germline or somatic mutations in homologous recombination repair. The combination of PARPi with androgen receptor axis-targeted agents (ARAT) or dual ARAT-based therapy has shown superior radiographic progression-free survival as a first-line treatment. A combination of AKT inhibitor ipatasertib and abiraterone has shown improvement in radiographic progression-free survival as a first-line treatment. Prostate-specific membrane antigen (PSMA)-targeted radiopharmaceutical like 177Lu-PSMA-617, a beta particle emitter has demonstrated improvement in overall survival in mCRPC patients pretreated with ARAT or taxanes. Although immune checkpoint inhibitors are being tested in mCRPC, there is no robust evidence to support this premise. SUMMARY: These new agents have widened the treatment options for mCRPC patients. Overall treatment should be focused on improving survival while limiting the deterrent effect on the quality of life.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".