From Upfront Nephrectomy to Preoperative Chemotherapy and Back
Bibliographic record
Abstract
BACKGROUND: Over the past decades, 2 different approaches for the treatment of Wilms tumor have emerged: upfront nephrectomy (UN) and preoperative chemotherapy (PC), with adjuvant treatment adjusted to stage, histology, and chemotherapy response. METHODS: In July 2005, we switched our strategy from UN to PC. This study is a retrospective review of patients treated at our institution between January 2003 and October 2007. RESULTS: Thirty-six children (20 males) with Wilms tumor were studied. Median age was 3.45 years (range: 0.3 to 15.8 y). Nineteen patients (53%) were treated according to the International Society of Paediatric Oncology 93-01/German Pediatric Oncology Hematology, Group protocol (PC group) and 17 (47%) according to the National Wilms' Tumor Study-5 (UN group). UN group received more radiation dose and less cumulative doses of doxorubicin. The 3-year event-free survival and overall survival estimates for the whole group were 86% and 89%, respectively. Survival estimates were similar in both groups. CONCLUSIONS: The use of PC reduced the use of radiation; however, patients treated using the SIOP 93-01/German Pediatric Oncology Hematology Group protocol received higher cumulative doses of doxorubicin; these doses were believed to be high in this young group of patients with potential for long-term toxicity. Although selecting a specific protocol for Wilms tumor is important, the development of surgical expertise and referral to specialized centers takes priority.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".