Phase 2 trial of veliparib, local irradiation, and temozolomide in patients with newly diagnosed high-grade glioma: a Children’s Oncology Group study
Bibliographic record
Abstract
BACKGROUND: The outcome for pediatric patients with high-grade glioma (HGG) remains poor. Veliparib, a potent oral poly(adenosine diphosphate-ribose) polymerase (PARP) 1/2 inhibitor, enhances the activity of radiotherapy and DNA-damaging chemotherapy. METHODS: We conducted a single-arm, non-randomized phase 2 clinical trial to determine whether treatment with veliparib and radiotherapy, followed by veliparib and temozolomide, improves progression-free survival in pediatric patients with newly diagnosed HGG without H3 K27M or BRAF mutations, compared to patient-level data from historical cohorts with closely matching clinical and molecular features. Following surgical resection, newly diagnosed children with non-metastatic HGG were screened by rapid central pathology review and molecular testing. Eligible patients were enrolled on Stratum 1 (IDH wild-type) or Stratum 2 (IDH mutant). RESULTS: Both strata were closed to accrual for futility after planned interim analyses. Among the 23 eligible patients who enrolled on Stratum 1 and received protocol therapy, the 1-year event-free survival (EFS) was 23% (standard error, SE = 9%) and the 1-year overall survival (OS) was 64% (SE = 10%). Among the 14 eligible patients who enrolled on Stratum 2 and received protocol therapy, the 1-year EFS was 57% (SE = 13%) and 1-year OS was 93% (SE = 0.7%). CONCLUSIONS: Rapid central pathology review and molecular testing for eligibility were feasible. The protocol therapy including radiation, veliparib, and temozolomide was well tolerated but failed to improve outcomes compared to clinically and molecularly matched historical control cohorts treated with higher doses of alkylator chemotherapy. CLINICALTRIALS.GOV IDENTIFIER: NCT03581292 (first posted: July 10, 2018).
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".