Whether extended pelvic lymph node dissection should be performed in prostate cancer: The present evidence from a systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Purpose To compare non‐extended pelvic lymph node dissection (nePLND) with extended pelvic lymph node dissection (ePLND) in outcomes and complications of patients with prostate cancer (PCa). Methods A comprehensive search of the PubMed, EMBASE, and Web of Science was performed. We extracted the first author, year of publication, basic characteristics of patients, method of radical prostatectomy (RP), extent of PLND, number of lymph node yields (LNY), and percentage of LN metastasis. Besides, information about inpatients outcomes and complications were also collected. The modified Newcastle‐Ottawa scale was compiled to assess the level of evidence of all controlled studies. Next, we used odds ratio (OR) with corresponding 95% confidence interval (CI) to evaluate the difference between nePLND and ePLND in meta‐analysis, and a P value of <.05 was considered statistically significant. Results A total of 11 studies including 7489 patients were included in our study. Compared with nePLND, more LNY and metastasized LNs (OR = 3.104, 95% CI: 2.407‐4.001, z = 8.74, P < .001) could be dissected by ePLND. Besides, more complications from ePLND group compared with nePLND group (ePLND vs nePLND: OR = 2.118, 95% CI: 1.107‐4.051, z = 2.27, P = .023). Furthermore, the results of subgroup analysis revealed that ePLND group led to more complications from all three RP approaches. In addition, our results showed that extender PLND led to more blood loss and longer operating room time in PCa patients with open radical prostatectomy (ORP). No statistics discrepancy in postoperative length of stay and operating room time was observed except one single study. Finally, there were no significant difference observed in transfusion and prostate weight. Conclusions The results of our study indicated that extender PLND led to more LNY and more metastasized LNs. More harm would be brought by ePLND in ORP, whereas not in LRP and RALP. In addition, ePLND may lead to more overall compilations than nePLND.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".