Pathologic fracture in patients with metastatic prostate cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review will describe the management of patients with prostate cancer and bone metastases with a particular emphasis on recent advances in this area. RECENT FINDINGS: Two osteoclast-targeted agents have been shown to decrease the incidence of skeletal-related events in patients with metastatic castration-resistant prostate cancer (mCRPC) and bone metastases. These agents are the bisphosphonate zoledronic acid and the monoclonal antibody denosumab. Recent advances in the field include the approval of several agents shown to extend survival in mCRPC. Among these agents, the androgen-pathway inhibitors, abiraterone and enzalutamide, are shown to decrease the incidence of skeletal-related events, whereas the radiopharmaceutical radium-223 is shown to reduce the incidence of symptomatic skeletal event. Cabozantinib, an agent in development, has shown encouraging activity in patients with mCRPC and bone metastases; definitive phase III trials of this agent are underway. Phase III metastasis-prevention trials are also underway in nonmetastatic CRPC. SUMMARY: Osteoclast-targeted agents reduce skeletal-related events in mCRPC. Disease-modifying agents also reduce the skeletal morbidity associated with mCRPC. Multiple agents are now available to reduce the skeletal morbidity of prostate cancer, whereas agents in development may provide additional options in the future.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".