Bone-targeted therapy in castration-resistant prostate cancer: where do we stand?
Bibliographic record
Abstract
INTRODUCTION: In the last years, there have been significant developments in the therapeutic armamentarium of metastatic castration-resistant prostate cancer (mCRPC). New evidence shows that the addition of bone-targeted agents (BTA) to "life-prolonging agents" result in improved clinical benefit. This review aims to give an overview of data for the use of BTAs in a new era of mCRPC where new agents are used in daily practice. EVIDENCE ACQUISITION: A non-systematic review of the literature was performed combining the keywords: "castration-resistant prostate cancer" and "bone-targeted therapy". The primary objective was to provide a critical assessment of data for the use of BTAs in mCRPC, and the secondary objective was to assess novel targeted therapy. EVIDENCE SYNTHESIS: Zoledronic acid and denosumab have shown to be effective in reducing the risk of SREs in patients with mCRPC. The point at which treatment with bisphosphonates or denosumab should be initiated during PCa evolution has yet to be determined. The EMA has restricted the usage of Ra-223 to patients who have had two previous treatments for mCRPC to the bone or who cannot receive other treatments. Ra-223 should only be used as monotherapy or in combination with ADT for the treatment of mCRPC, symptomatic bone metastases and without visceral metastases. With recent developments in PSMA-targeted radiopharmaceuticals, PSMA RLT agents are now under investigation for the treatment of mCRPC. CONCLUSIONS: Reducing skeletal-related morbidity remains a crucial goal of palliative life-extending therapy in mCRPC. New data about dosing schedules and combinations of different treatments will continue to refine the optimal strategy for incorporating BTAs into the new treatment paradigms for PCa. Novel molecules such as PSMA-targeted small molecules promise theranostic agents in the management of PCa patients.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".