Long-Term Toxicities among Wilms Tumor Survivors
Bibliographic record
Abstract
Successive trials conducted by the National Wilms Tumor Study have resulted in very high cure rates for children with Wilms tumor (WT). These trials have also significantly reduced the indications for doxorubicin and higher doses of RT in WT. Late toxicities after multimodality treatment especially RT, continues to be a major problem among WT survivors. Higher doses of RT is the most important factor responsible for the many late effects including congestive heart failure, secondary malignant neoplasms, hypogonadism, infertility and pregnancy complications, pulmonary disease, musculoskeletal effects, renal failure and diabetes mellitus. The potential for novel RT techniques like IMRT and proton therapy to reduce the incidence of these toxicities is discussed. The surveillance recommendations for WT survivors are mainly derived from the COG long-term follow-up guidelines. The future directions in late effects research include novel research to improve current knowledge of association between RT doses to target organs and late effects, discovery of novel biomarkers, and identification of predictive genetic biomarkers. Despite all these advances, there are significant challenges facing the global health care community that need to be overcome before the benefits of these innovations in late effects research can be translated to individual cancer survivors.
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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 | 0.000 |
| 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) | 0.005 | 0.001 |
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".