No benefit from TMZ treatment in glioblastoma with truly unmethylated <i>MGMT</i> promoter: Reanalysis of the CE.6 and the pooled Nordic/NOA-08 trials in elderly glioblastoma patients
Bibliographic record
Abstract
BACKGROUND: The treatment of elderly/ frail patients with glioblastoma is a balance between avoiding undue toxicity, while not withholding effective treatment. It remains debated, whether these patients should receive combined chemo-radiotherapy with temozolomide (RT/TMZ→TMZ) regardless of the O6-methylguanine DNA methyltransferase gene promoter (MGMTp) methylation status. MGMT is a well-known resistance factor blunting the treatment effect of TMZ, by repairing the most genotoxic lesion. Epigenetic silencing of the MGMTp sensitizes glioblastoma to TMZ. For risk-adapted treatment, it is of utmost importance to accurately identify patients, who will not benefit from TMZ treatment. METHODS: Here, we present a reanalysis of the clinical trials CE.6 and the pooled NOA-08 and Nordic trials in elderly glioblastoma patients that compared RT to RT/TMZ→TMZ, or RT to TMZ, respectively. For 687 patients with available MGMTp methylation data, we applied a cutoff discerning truly unmethylated glioblastoma, established in a pooled analysis of 4 clinical trials for glioblastoma, with RT/TMZ→TMZ treatment, using the same quantitative methylation-specific MGMTp PCR assay. RESULTS: When applying this restricted cutoff to the elderly patient population, we confirmed that glioblastoma with truly unmethylated MGMTp derived no benefit from TMZ treatment. In the Nordic/NOA-08 trials, RT was better than TMZ, suggesting little or no benefit from TMZ. CONCLUSIONS: For evidence-based treatment of glioblastoma patients validated MGMTp methylation assays should be used that accurately identify truly unmethylated patients. Respective stratified management of patients will reduce toxicity without compromising outcomes and allow testing of more promising treatment options.
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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 | 0.048 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.028 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".