Evaluation of O6-methylguanine-DNA methyltransferase enzyme expression effect on survival of patients with Grade 4 brain astrocytoma.
Bibliographic record
Abstract
BACKGROUND: High-grade astrocytoma (Grade 4) or glioblastoma multiforme (GBM) are deadly brain tumors. New therapies attempt to increase lifetime and quality of life in patients with malignant astrocytoma. O6-methylguanine-DNA methyltransferase (MGMT) enzyme expression may be effective in prognosis and response to treatment of these patients. The aim of this study was assessment of MGMT enzyme expression in patients with astrocytoma Grade 4. MATERIALS AND METHODS: In this study, 48 patients with GBM that were treated with surgery, chemotherapy and radiotherapy were investigated and followed-up for 47 months for the survival rate. Pathology blocks of patients were examined for MGMT enzyme expression using immunohistochemistry method. RESULTS: The patients were 34 males and 14 females. The ages ranged from 24 to 77 years, with a mean age of 53.52 ± 13.39 years. There was no significant difference between two groups (positive and negative MGMT enzyme expression) in overall survival (median [range] 11.5 [4-30] vs. 13 [5-22], P = 0.9). The results of our study showed that patients although who were undergone near total surgery had higher overall survival than the group of patients who had biopsy only however, it was not significant. Patients who were treated with temozolomide (TMZ) (Temodal, Merck Canada) had significant overall median survival (14.5) more than the patients who were treated with Procarbazine (Roche, Swiss)-Lomustine (Lilly, USA)-Vincristine (Lilly, USA) regimen (8.75) (P < 0.05). CONCLUSION: O6-methylguanine-DNA methyltransferase enzyme expression had no effect on survival of patients with Grade 4 brain astrocytoma TMZ may increase survival rate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".