Intensive chemotherapy followed by consolidative myeloablative chemotherapy with autologous hematopoietic cell rescue (AuHCR) in young children with newly diagnosed supratentorial primitive neuroectodermal tumors (sPNETs): Report of the Head Start I and II experience
Bibliographic record
Abstract
BACKGROUND: Children with newly diagnosed supratentorial primitive neuroectodermal tumors (sPNET) have poor outcomes compared to medulloblastoma patients, despite similar treatments. In an effort to improve overall survival (OS) and event-free survival (EFS) and to decrease radiation exposure, the Head Start (HS) protocols treated children with newly diagnosed sPNET utilizing intensified induction chemotherapy (ICHT) followed by consolidation with myeloablative chemotherapy and autologous hematopoietic cell rescue (AuHCR). PROCEDURES: Between 1991 and 2002, 43 children with sPNET were prospectively treated on two serial studies (HS I and II). After maximal safe surgical resection, patients on HS I and patients with localized disease on HS II were treated with five cycles of ICHT (vincristine, cisplatin, cyclophosphamide, and etoposide). Patients on HS II with disseminated disease received high-dose methotrexate during ICHT. If the disease remained stable or in response, patients received a single cycle of high-dose myeloablative chemotherapy followed by AuHCR. RESULTS: Five-year EFS and OS were 39% (95%CI: 24%, 53%) and 49 (95%CI: 33%, 62%), respectively. Non-pineal sPNET patients faired significantly better than those patients with pineal sPNETs. Metastasis at diagnosis, age, and extent of resection were not significant prognostic factors. Sixty percent of survivors (12 of 20) are alive without exposure to radiation therapy. CONCLUSIONS: ICHT followed by AuHCR in young patients with newly diagnosed sPNET appears to not only provide an improved EFS and OS for patients who typically have a poor prognosis, but also it successfully permitted deferral and elimination of radiation therapy in a significant proportion of patients.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".