Salvage therapy for progressive, treatment-refractory or recurrent pediatric medulloblastoma: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Central nervous system tumors remain the leading cause of cancer-related mortality amongst children with solid tumors, with medulloblastoma (MB) representing the most common pediatric brain malignancy. Despite best current therapies, patients with recurrent MB experience have an alarmingly high mortality rate and often have limited therapeutic options beyond inadequate chemotherapy or experimental clinical trials. Therefore, a systematic review of the literature regarding treatment strategies employed in recurrent pediatric MB will evaluate previous salvage therapies in order to guide future clinical trials. The aim of this systematic review will be to investigate the efficacy and safety of salvage therapies for the management of children with progressive, treatment-refractory, or recurrent MB. METHODS: We will conduct literature searches (from 1995 onwards) in MEDLINE, EMBASE, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, and Cochrane Central Register of Controlled Trials. Studies examining the survival and toxicity of therapies administered to treatment-refractory pediatric MB patients will be included. Two reviewers will independently assess the search results based on predefined selection criteria, complete data abstraction, and quality assessment. The primary outcomes of this review will be overall and progression-free survival. Secondary outcomes will include safety and toxicity of each therapy administered. The study methodological quality (or bias) will be appraised using an appropriate tool. Due to the nature of the research question and published literature, we expect large inter-study heterogeneity and therefore will use random effects regression analysis to extract the combined effect. In additional analyses, we will investigate the role of re-irradiation and mono- vs. poly-therapy in recurrent disease, and whether molecular subgrouping of MB influences salvage therapy. DISCUSSION: This systematic review will provide an overview of the current literature regarding salvage therapies for relapsed MB patients. Investigation of clinically tested therapies for children with recurrent MB has significant implications for clinical practice. By reviewing the efficacy and toxicity of MB salvage therapies, this study will identify effective therapeutic strategies administered to recurrent MB patients and can inform future clinical trials aimed to improve patient survivorship and quality of life. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020167421.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.033 | 0.007 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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; both teacher heads agree on what is shown here.
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".