Incidence and management of pleural effusions in patients with Wilms tumor: A Pediatric Surgical Oncology Research Collaborative study
Bibliographic record
Abstract
Wilms tumor (WT) is the most common renal malignancy in children. Children with favorable histology WT achieve survival rates of over 90%. Twelve percent of patients present with metastatic disease, most commonly to the lungs. The presence of a pleural effusion at the time of diagnosis of WT may be noted on staging imaging; however, minimal data exist regarding the significance and prognostic importance of this finding. The objectives of our study are to identify the incidence of pleural effusions in patients with WT, and to determine the potential impact on oncologic outcomes. A multi-institutional retrospective review was performed from January 2009 to December 2019, including children with WT and a pleural effusion on diagnostic imaging treated at Pediatric Surgical Oncology Research Collaborative (PSORC) participating institutions. Of 1259 children with a new WT diagnosis, 94 (7.5%) had a pleural effusion. Patients with a pleural effusion were older than those without (median 4.3 vs 3.5 years; P = .004), and advanced stages were more common (local stage III 85.9% vs 51.9%; P < .0001). Only 14 patients underwent a thoracentesis for fluid evaluation; 3 had cytopathologic evidence of malignant cells. Event-free and overall survival of all children with WT and pleural effusions was 86.2% and 91.5%, respectively. The rate and significance of malignant cells present in pleural fluid is unknown due to low incidence of cytopathologic analysis in our cohort; therefore, the presence of an effusion does not appear to necessitate a change in therapy. Excellent survival can be expected with current stage-specific treatment regimens.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".