<i>MGMT</i> Gene Silencing and Benefit from Temozolomide in Glioblastoma
Bibliographic record
Abstract
BACKGROUND: Epigenetic silencing of the MGMT (O6-methylguanine-DNA methyltransferase) DNA-repair gene by promoter methylation compromises DNA repair and has been associated with longer survival in patients with glioblastoma who receive alkylating agents. METHODS: We tested the relationship between MGMT silencing in the tumor and the survival of patients who were enrolled in a randomized trial comparing radiotherapy alone with radiotherapy combined with concomitant and adjuvant treatment with temozolomide. The methylation status of the MGMT promoter was determined by methylation-specific polymerase-chain-reaction analysis. RESULTS: The MGMT promoter was methylated in 45 percent of 206 assessable cases. Irrespective of treatment, MGMT promoter methylation was an independent favorable prognostic factor (P<0.001 by the log-rank test; hazard ratio, 0.45; 95 percent confidence interval, 0.32 to 0.61). Among patients whose tumor contained a methylated MGMT promoter, a survival benefit was observed in patients treated with temozolomide and radiotherapy; their median survival was 21.7 months (95 percent confidence interval, 17.4 to 30.4), as compared with 15.3 months (95 percent confidence interval, 13.0 to 20.9) among those who were assigned to only radiotherapy (P=0.007 by the log-rank test). In the absence of methylation of the MGMT promoter, there was a smaller and statistically insignificant difference in survival between the treatment groups. CONCLUSIONS: Patients with glioblastoma containing a methylated MGMT promoter benefited from temozolomide, whereas those who did not have a methylated MGMT promoter did not have such a benefit.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".