Treatment of the Primary Tumor in Metastatic Prostate Cancer: Current Concepts and Future Perspectives
Bibliographic record
Abstract
CONTEXT: Multimodal treatment for men with locally advanced prostate cancer (PCa) using neoadjuvant/adjuvant systemic therapy, surgery, and radiation therapy is being increasingly explored. There is also interest in the oncologic benefit of treating the primary tumor in the setting of metastatic PCa (mPCa). OBJECTIVE: To perform a review of the literature regarding the treatment of the primary tumor in the setting of mPCa. EVIDENCE ACQUISITION: Medline, PubMed, and Scopus electronic databases were queried for English language articles from January 1990 to September 2014. Prospective and retrospective studies were included. EVIDENCE SYNTHESIS: There is no published randomized controlled trial (RCT) comparing local therapy and systemic therapy to systemic therapy alone in the treatment of mPCa. Prospective studies of men with locally advanced PCa and retrospective studies of occult node-positive PCa have consistently shown the addition of local therapy to a multimodal treatment regimen improves outcomes. Molecular and genomic evidence further suggests the primary tumor may have an active role in mPCa. CONCLUSIONS: Treatment of the primary tumor in mPCa is being increasingly explored. While preclinical, translational, and retrospective evidence supports local therapy in advanced disease, further prospective studies are under way to evaluate this multimodal approach and identify the patients most likely to benefit from the inclusion of local therapy in the setting of metastatic disease. PATIENT SUMMARY: In this review we explored preclinical and clinical evidence for treatment of the primary tumor in metastatic prostate cancer (mPCa). We found evidence to support clinical trials investigating mPCa therapy that includes local treatment of the primary tumor. Currently, treating the primary tumor in mPCa is controversial and lacks high-level evidence sufficient for routine recommendation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".