Survival improvements with adjuvant therapy in patients with glioblastoma
Bibliographic record
Abstract
BACKGROUND: Evaluate survival of patients diagnosed with glioblastoma multiforme (GBM) managed with adjuvant intensity modulated radiation therapy and temozolomide since the introduction of the European Organisation for Research and Treatment of Cancer and National Cancer Institute of Canada Clinical Trials Group (EORTC-NCIC) protocol. METHODS: All patients with GBM managed between May 2007 and December 2014 with EORTC-NCIC protocol were entered into a prospective database. The primary endpoint was the median survival. Univariate predictors of survival were evaluated with respect to tumour resection, age and Eastern Cooperative Oncology Group (ECOG) performance status using log-rank comparisons. RESULTS: Two hundred and thirty-three patients were managed under the protocol and analysed for outcome. The median age was 57 years; the rate of gross total resection, subtotal resection and biopsy were 47.2%, 35.2% and 17.6%, respectively. At progression, 49 patients had re-resection, and in addition to second-line chemotherapy, 86 patients had Bevacizumab including 26 with re-irradiation. Median survival was 17.0 months (95% CI: 15.4-18.6). On univariate evaluation, extent of resection (P = 0.001), age, ECOG performance status and recursive partitioning analysis class III were shown to significantly improve survival (P < 0.0001). The median survival for gross total resection, age <50 years, ECOG 0-1 and recursive partitioning analysis class III were 21, 27, 20 and 47 months, respectively. CONCLUSION: This study confirms the significant improvement in median survival in GBM that has occurred in recent years since introduction of the EORTC-NCIC protocol. Further improvements have occurred presumably related to subspecialized care, improved resection rates, sophisticated radiotherapy targeting and early systemic salvage therapies. However, the burden of the disease within the community remains high and the median survival improvements over time have plateaued.
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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 | 0.000 | 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".