Local Control in Pelvic Ewing Sarcoma: Analysis From INT-0091—A Report From the Children's Oncology Group
Bibliographic record
Abstract
PURPOSE: The impact of the modality used for local control of Ewing sarcoma is uncertain. We investigated the relationship between the type of local control modality, surgery, radiation (RT) or both (S + RT), and subsequent risk for local failure (LF) in patients with nonmetastatic pelvic Ewing sarcoma treated on INT-0091. PATIENTS AND METHODS: Patients < or = 30 years with Ewing sarcoma, primitive neuroectodermal tumor or primitive sarcoma of bone were randomly assigned to receive chemotherapy with doxorubicin, vincristine, cyclophosphamide, and dactinomycin, (VACA) or with these four drugs alternating with ifosfamide and etoposide (VACA-IE). The local control modality, surgery, RT or both was chosen by the treating physicians. The effect of local control modality was assessed after adjusting for the size of tumor (< 8 cm, > or = 8 cm) and chemotherapy type. RESULTS: Seventy-five patients with pelvic tumors and a median follow-up of 4.4 years (0.6 to 11.4 years) comprised the study population. Twelve underwent surgery, 44 received RT, and 19 received both. The 5-year event-free survival (EFS) and cumulative incidence of LF was 49% and 21% (16%, LF only; 5%, LF and distant failure). There was no significant difference in EFS or LF by tumor size (< 8 cm, > or = 8 cm), local control (LC) modality, or chemotherapy. However, VACA-IE seems to confer an LC benefit (11% v 30%; P = .06). CONCLUSION: There was no significant effect of local control modality (surgery, RT or S + RT) selected by the treating physicians on rates of local failure or EFS. However, VACA-IE improves LC (11%) compared with previously published results for pelvic Ewing sarcoma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".