Molecular features of glioblastomas in long-term survivors compared to short-term survivors—a matched-pair analysis
Bibliographic record
Abstract
BACKGROUND: Although glioblastoma (GB) is associated with a devastating prognosis, a small proportion of patients achieve long-term survival rates. We herein present a matched-pair analysis of molecular factors found in long- and short-term survivors (LTS, STS). METHODS: We performed a cross-institutional analysis of 262 patient records and matched a group of 91 LTS (≥ 3 years) with two groups of STS (STS-1, n = 91; STS-2, n = 80). Matching was performed according to age, Karnofsky Performance Status, initial therapy and adjuvant therapy. Molecular factors were compared between LTS (total of 91 patients) v. STS-1, and LTS (subgroup of 80 patients) v. STS-2. We included glial fibrillary acidic protein (GFAP), O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, isocitrate dehydrogenase 1 (IDH-1); furthermore, the proliferation index was analyzed (Ki-67/MIB-1). RESULTS: IDH-1 and decreased Ki-67 were numerically associated with LTS but the difference was only significant compared to STS-1 (n.s. v. STS-2). LTS was associated with MGMT promoter hypermethylation (p = 0.013 and p = 0.022) and GFAP expression (p < 0.001 and p = 0.001). Positivity for both factors combined compared to negativity for one factor occurred more often in the LTS group (p = 0.002 and p = 0.006); negativity for both factors combined did not occur in the LTS group. CONCLUSION: In this retrospective analysis, GFAP expression and MGMT promoter methylation were associated with LTS. Given the hypothesis-generating nature of our study, these observations should be confirmed in prospective clinical trials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".