The role of lymph node dissection in the management of renal cell carcinoma: a systematic review and meta‐analysis
Bibliographic record
Abstract
Our objective was to evaluate the role of retroperitoneal lymph node dissection ( LND ) in non‐metastatic (M0) and metastatic (M1) renal cell carcinoma ( RCC ). We searched Medline, EMBASE , Web of Science and Scopus from database inception to 29 August 2017 for studies of patients who underwent partial or radical nephrectomy for M0 or M1 RCC . Two investigators independently selected studies for inclusion. Risk of bias was assessed using the Newcastle–Ottawa scale, Cochrane Collaboration tool and National Heart, Lung and Blood Institute Quality Assessment Tool. Random effects meta‐analysis was performed for all‐cause‐mortality. The GRADE approach was used to characterize quality of evidence. A total of 51 unique studies were included in the qualitative systematic review. Risk of bias was low in 41/51 (80%) studies. LND was not associated with all‐cause mortality in either M0 (hazard ratio [ HR ] 1.02, 95% confidence interval [ CI ] 0.92–1.12; I 2 = 0%; four studies), M1 ( HR 1.04, 95% CI 0.83–1.29; I 2 = 0%; two studies), or pooled M0 and M1 settings ( HR 1.00, 95% CI 0.92–1.09; I 2 = 0%; seven studies), with no statistically significant differences according to M stage subgroups ( P = 0.50). In the three studies that examined M0 subgroups with a high risk of nodal metastasis, LND was not associated with improved oncological outcomes. Studies on the association of extent of LND with survival reported inconsistent results. Meanwhile, a small proportion of patients with pN 1M0 disease demonstrate durable long‐term oncological control after surgery, with 10‐year cancer‐specific survival of 21–31%. Nodal involvement is independently associated with adverse prognosis in both M0 and M1 settings. GRADE quality of evidence was moderate or low for the outcomes examined. Although LND yields independent prognostic information, the existing literature does not support a therapeutic benefit to LND in either M0 or M1 RCC . High‐risk M0 patient groups warrant further study, as a subset of patients with isolated nodal metastases experience long‐term survival after surgical resection.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".