Recent advances in the medical therapy of high-grade gliomas
Bibliographic record
Abstract
Malignant glial neoplasms, including glioblastoma, are amongst the most devastating and intractable of solid tumors. Until recently the standard of care for newly diagnosed glioblastoma was surgical resection to the extent feasible followed by conventional fractionated radiotherapy. When administered for disease progression, chemotherapy had modest benefit and its use in the adjuvant setting was controversial. Temozolomide, an oral alkylating chemotherapeutic agent, has now been demonstrated to increase survival time in patients with newly diagnosed glioblastoma when used concurrently with radiotherapy and as adjuvant or maintenance treatment for six cycles thereafter. Correlative molecular studies suggested that the benefit of temozolomide is largely restricted to patients whose tumor has silenced the gene for methylguanine methyltransferase, a repair enzyme implicated in resistance to alkylator chemotherapy. Use of temozolomide chemotherapy upfront in the management of glioblastoma is now considered the standard of care. This significant advance has also stimulated development of therapeutic strategies that incorporate temozolomide, and other agents, in the initial management of most high-grade gliomas. Furthermore, our increased understanding of the molecular derangements that underlie gliomagenesis has identified a number of putative molecular targets against which novel therapeutics have been tested with encouraging preliminary results. Finally, the challenges presented by the blood–brain barrier to adequate drug delivery have stimulated the development of unique locoregional delivery techniques that are currently undergoing clinical evaluation. This review summarizes these recent advances, and speculates on how the field is likely to evolve in the near future.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".