Tumor Necrosis in Pediatric Osteosarcoma: Impact of Modern Therapies
Bibliographic record
Abstract
Tumor necrosis following preoperative chemotherapy in patients with osteosarcoma is a predictor of overall survival. With modern therapies, 45% of patients are expected to achieve more than 90% tumor necrosis. Investigators at the authors' center, however, increasingly noted that patients were experiencing inferior necrosis responses. A retrospective study of treated patients at the center was undertaken to examine this. The purpose of this study was to determine (1) whether the number of patients with favorable histological responses had changed over time and (2) whether the percentage of patients with favorable responses was similar to published outcomes. Chart reviews were performed on patients treated from 1993 to 2003 according to the Pediatric Oncology Group 9351, regimen A protocol. Twenty-one patients met all eligibility requirements; 52% of patients had more than 90% necrosis. No correlation existed between degree of necrosis and year of treatment (r = 0.06; P = .8). Patients with osteosarcoma treated at the authors' institution have comparable tumor necrosis responses to published outcomes, and no change occurred over time. This study stresses the importance of rigorous retrospective reviews before implementing treatment changes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".