ACTR-02. NRG ONCOLOGY/RTOG 0424: LONG-TERM RESULTS OF A PHASE II STUDY OF TEMOZOLOMIDE-BASED CHEMORADIOTHERAPY REGIMEN FOR HIGH-RISK LOW-GRADE GLIOMAS
Bibliographic record
Abstract
PURPOSE: To report the long-term outcomes and MGMT analysis of temozolomide (TMZ) and radiotherapy (RT) in a high-risk low-grade gliomas (LGG) population. PATIENTS/ For this single-arm phase II study, LGG patients with ≥3 risk factors (age ≥40, astrocytoma, bi-hemispheric tumor, size ≥6 cm or preoperative neurologic function status >1) received RT (54 Gy/30 fractions) with TMZ and up to 12 cycles of post-RT TMZ. The primary endpoint was overall survival (OS) at 3 years after registration. A one-sided Z-test was used to test the hazard rate based on the observed 3-year OS rate versus a prespecified historical control from the EORTC high-risk LGG population. Secondary endpoints included progression-free survival (PFS), and the association of survival outcomes with MGMT methylation status, for which the MGMT-STP27 prediction model was used based on 450k data. The initial report of this study was published in 2015, when the results of the MGMT analysis were unavailable. The study accrued 129 analyzable patients. The median follow-up for surviving patients was 9 years (range: 0.4–11.8), 4 years longer than previously reported. The 3-year OS rate was 73.5% (95% CI: 65.8–81.1%), superior to the historical control of 54% (p
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".