The role of lymph node dissection in salvage radical prostatectomy for patients with radiation recurrent prostate cancer
Bibliographic record
Abstract
PURPOSE: To examine the effect of lymph node dissection on the outcomes of patients who underwent salvage radical prostatectomy (SRP). MATERIAL AND METHODS: We retrospectively reviewed data from radiation-recurrent patients with prostate cancer (PCa) who underwent SRP from 2000-2016. None of the patients had clinical lymph node involvement before SRP. The effect of the number of removed lymph nodes (RLNs) and the number of positive lymph nodes (PLNs) on biochemical recurrence (BCR)-free survival, metastases free survival, and overall survival (OS) was tested in multivariable Cox regression analyses. RESULTS: About 334 patients underwent SRP and pelvic lymph node dissection (PLND). Lymph node involvement was associated with increased risk of BCR (p < .001), metastasis (p < .001), and overall mortality (p = .006). In a multivariable Cox regression analysis, an increased number of RLNs significantly lowered the risk of BCR (hazard ratio [HR] 0.96, p = .01). In patients with positive lymph nodes, a higher number of RLNs and a lower number of PLNs were associated with improved freedom from BCR (HR 0.89, p = .001 and HR 1.34, p = .008, respectively). At a median follow-up of 23.9 months (interquartile range, 4.7-37.7), neither the number of RLNs nor the number of PLNs were associated with OS (p = .69 and p = .34, respectively). CONCLUSION: Pathologic lymph node involvement increased the risk of BCR, metastasis and overall mortality in radiation-recurrent PCa patients undergoing SRP. The risk of BCR decreased steadily with a higher number of RLNs during SRP. Further research is needed to support this conclusion and develop a precise therapeutic adjuvant strategy based on the number of RLNs and PLNs.
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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) | 0.000 | 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".