Cystic Nephroma, Cystic Partially Differentiated Nephroblastoma and Cystic Wilms’ Tumor in Children: A Spectrum with Therapeutic Dilemmas
Bibliographic record
Abstract
BACKGROUND: Cystic renal tumors are a diagnostic and therapeutic challenge. Cystic nephroma (CN), cystic partially differentiated nephroblastoma (CPDN) and cystic Wilms' tumor (CWT) are a spectrum with CN at the benign end, CWT at the malignant end and CPDN in the intermediate position. CN and stage 1 CPDN are often treated with surgery alone. International Society of Pediatric Oncology (SIOP) protocols for Wilms' tumor (WT) advocate preoperative chemotherapy, which may be unnecessary and potentially harmful in CN and in stage 1 CPDN. There are difficulties in differentiating the three types using imaging techniques. Therefore, controversies exist regarding the optimal treatment. METHODS: We describe 6 children, who each had a postoperative diagnosis of CN, CPDN or CWT, and we retrospectively evaluate the treatment strategies. RESULTS: The three types cannot be differentiated using imaging techniques, although the presence of solid components in the tumor is indicative of WT. CONCLUSIONS: Surgery as first-line therapy should be seriously considered in children who have a cystic renal tumor, but further collaborative studies are needed since the distinction line between CPDN and CWT is not always clear.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".