Primary Retroperitoneal Lymph Node Dissection in Marker-Positive Clinical Stage II Nonseminomatous Germ Cell Tumors
Bibliographic record
Abstract
PURPOSE: Guidelines usually recommend chemotherapy rather than primary retroperitoneal lymph node dissection (pRPLND) for clinical stage II nonseminomatous germ cell tumors (NSGCTs) with elevated serum tumor markers (STMs). This study evaluated oncologic and perioperative outcomes of pRPLND in patients with marker-positive vs marker-negative clinical stage II NSGCTs. MATERIALS AND METHODS: A retrospective review from our prospectively maintained database identified patients undergoing pRPLND (1983-2022). The primary end point was relapse-free survival. Secondary end points included cancer-specific survival (CSS), relapse location, and perioperative outcomes. Outcomes were compared using Kaplan-Meier analysis, log-rank testing, and multivariable COX regression. RESULTS: = .009). Of 4 cancer-specific deaths, 2 involved somatic transformation, 1 patient declined chemotherapy at relapse, and 1 death occurred during chemotherapy. Elevated alpha fetoprotein correlated with worse CSS, and dual marker elevation predicted greater relapse risk. Surgical complication rates did not differ between groups. CONCLUSIONS: Although elevated STMs are associated with increased relapse and mortality risk, pRPLND is associated with long-term disease control in approximately 75% of patients. Most relapses can be successfully treated in compliant individuals. Multidisciplinary decision-making should weigh relapse risk and potential salvage chemotherapy needs against the long-term morbidity of primary chemotherapy.
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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) | 0.000 | 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) | 0.001 | 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".