HG-73SAFETY AND FEASIBILITY OF A MULTI-INSTITUTIONAL PHASE II TRIAL INCOPORATING BIOPSY AND MOLECULARLY DETERMINED TREATMENT OF CHILDREN AND YOUNG ADULTS WITH NEWLY DIAGNOSED DIFFUSE INTRINSIC PONTINE GLIOMAS (DIPG)
Bibliographic record
Abstract
BACKGROUND: DIPG remains a devastating disease in need of rational and effective therapeutic options. We designed a multi-institutional clinical trial incorporating diagnostic biopsy and molecularly stratified therapies with the aim of estimating overall survival of patients with DIPG treated with this strategy compared to historical controls. METHODS: Eligible patients' ages ranged from 3-18 years. Biopsies were obtained prior to administering local irradiation with bevacizumab to all patients. Stratification was based on presence(+) or absence(-) of MGMT promoter methylation and EGFR expression in tissue samples as follows: MGMT-/EGFR-(cohort 1), MGMT-/EFGR + (cohort 2), MGMT + /EGFR-(cohort 3), and MGMT + /EFGR + (Cohort 4). Erlotinib was added for patients in cohort 2, temozolomide for patients in cohort 3, and both erlotinib and temozolomide for cohort 4. RESULTS: Fifty of 53 enrolled patients were evaluable. Cohort 1 included 60% of patients; cohorts 2, 3 and 4 included 28%, 6% and 6%, respectively. EGFR expression was detected in 34% of patients and MGMT methylation in 12% of patients. EGFR and/or MGMT could not be determined in four patients. Mean time from sample submission to MGMT result was 6 days (range 1-14). EGFR status was generally reported within 24-48 hours. There were no biopsy related deaths. Following molecular stratification, remaining tissue was retained for future research. A mean of 5ug of RNA and 10ug of DNA was extracted from single frozen cores and successfully submitted for detailed molecular analysis. CONCLUSIONS: For patients with DIPG, pre-treatment biopsy is safe and molecularly guided treatment stratification feasible in real time for application to future clinical trials.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".