Salvage therapies for first relapse of SHH medulloblastoma in early childhood
Bibliographic record
Abstract
BACKGROUND: Sonic hedgehog (SHH) medulloblastoma is the most common molecular group of infant and early childhood medulloblastoma (iMB) and has no standard of care at relapse. This work aimed to evaluate the post-relapse survival (PRS) and explore prognostic factors of patients with nodular desmoplastic (ND) and/or SHH iMB. METHODS: This international retrospective study included 147 subjects diagnosed with relapsed ND/SHH iMB between 1995 and 2017, <6 years old at original diagnosis, and treated without initial craniospinal irradiation (CSI). Univariable and multivariable Cox models with propensity score analyses were used to assess PRS for those in the curative intent cohort. RESULTS: The 3-year PRS was 61.6% (95% confidence interval [CI], 52.2-69.6). The median age at relapse was 3.4 years (interquartile range [IQR], 2.6-4.1). Those with local relapse (40.8%) more often received salvage treatment with surgery (P < .001), low-dose CSI (≤24 Gy; P < .001), or focal radiotherapy (P = .008). Patients not receiving CSI (40.5%) more often received salvage marrow-ablative chemotherapy (HDC + AuHCR [P < .001]). On multivariable analysis, CSI was associated with improved survival (hazard ratio [HR] 0.33 [95% CI, 0.13-0.86], P = .04). Salvage HDC + AuHCR, while clinically important, did not reach statistical significance (HR 0.24 [95% CI, 0.0054-1.025], P = .065). CONCLUSIONS: Survival of patients with relapsed SHH iMB is not satisfactory and relies on treatments associated with toxicities including CSI and/or HDC + AuHCR. Cure at initial diagnosis to avoid relapse is crucial. For patients with localized relapse undergoing resection, alternative salvage regimens that avoid high-dose CSI (>24 Gy) can be considered.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".