Characteristics and survival of 750 children diagnosed with a renal tumor in the first seven months of life: A collaborative study by the SIOP/GPOH/SFOP, NWTSG, and UKCCSG Wilms tumor study groups
Bibliographic record
Abstract
BACKGROUND: To review the clinical characteristics and survival of infants diagnosed with a primary renal tumor in the first 7 months of life. PROCEDURE: A retrospective data review of patients registered in five large international protocols (SFOP/GPOH/SIOP9/93-01, UKW3 and NWTSG 4 and 5) spanning 1985-2002. RESULTS: 750 (7.2%) of 10,430 registered patients were diagnosed with a renal tumor before age 213 days. Tumor types were Wilms tumor (WT) 58%; congenital mesoblastic nephroma (CMN) 18%; malignant rhabdoid tumor (MRTK) 8%; clear cell sarcoma (CCSK) 2%; non-Wilms tumor (unspecified) 6%; histology unknown, 9%. CMN predominated among tumors diagnosed in the first month of life (54%) but its relative contribution diminished to <10% of all cases diagnosed after the age of 3 months (P < 0.001). Among 639 cases with specified histology and stage, 9/11 stage IV tumors were MRTK, 37/39 bilateral tumors were WT. In 626 children where surgical approach was specified, 522 had immediate nephrectomy. For all cases, 5 years event-free survival (EFS) was 80% and overall survival (OS) 86%. Five years EFS and OS respectively by tumor type were WT (86%, 93%), CMN (94%, 96%), CCSK (49%, 51%), MRTK (16%, 16%). CONCLUSION: Renal tumors diagnosed in the first 7 months of life generally have an excellent prognosis though histology is an important prognostic factor. In the first 2 months of life the prevalence of CMN is high. The relative occurrence of WT increases rapidly with age thereafter. Bilateral tumors are usually WT. Tumors with metastases at diagnosis are usually MRTK.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".