Expert Perspectives on Controversies in Metastatic Castration-Resistant Prostate Cancer Management: Narrative Review and Report of the First US Prostate Cancer Conference Part 2
Bibliographic record
Abstract
Background: Management strategies for metastatic castration-resistant prostate cancer (mCRPC) have rapidly shifted in recent years. As novel imaging and therapeutic approaches have made their way to the clinic, providers are encountering increasingly challenging clinical scenarios, with limited guidance from the current literature. Materials and Methods: The US Prostate Cancer Conference (USPCC) is a multidisciplinary meeting of prostate cancer experts intended to address the many challenges of prostate cancer management. At the first annual USPCC meeting, areas of controversy and consensus were identified during a 2-day meeting that included expert presentations, full-panel discussions, and postdiscussion responses to questions developed by the USPCC cochairs and session moderators. Results: This narrative review covers the USPCC expert discussion and perspectives relevant to mCRPC, including neuroendocrine/aggressive-variant prostate cancer (NEPC/AVPC). Areas of broad agreement identified among USPCC experts include the benefits of poly (ADP-ribose) polymerase (PARP) inhibitors for patients with BRCA1/2 mutations, the use of radioligand therapy in patients with prostate-specific membrane antigen (PSMA)–positive mCRPC, and the need for clinical trials that address real-world clinical questions, including the performance of novel therapies when compared with modern standard-of-care treatment. Ongoing areas of controversy and uncertainty included the appropriateness of PARP inhibitors in patients with non-BRCA1/2 mutations, the optimal definition of PSMA positivity, and systemic therapies for patients with NEPC/AVPC after progression on platinum-based therapies. Conclusions: The first annual USPCC meeting identified several areas of controversy in the management of mCRPC, highlighting the urgent need for clinical trials designed to facilitate treatment selection and sequencing in this heterogeneous disease state.
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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 | 0.020 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".