Dendritic cell vaccines for high-grade gliomas
Bibliographic record
Abstract
Matthew E Eagles,1 Farshad Nassiri,2,3 Jetan H Badhiwala,2 Suganth Suppiah,2 Saleh A Almenawer,4 Gelareh Zadeh,3,5 Kenneth D Aldape3,6 1Section of Neurosurgery, Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada; 2Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada; 3MacFeeters-Hamilton Neuro-Oncology Program, University Health Network, Toronto, ON, Canada; 4Division of Neurosurgery, Department of Surgery, McMaster University, Hamilton, ON, Canada; 5Division of Neurosurgery, University Health Network, Toronto, ON, Canada; 6Division of Pathology, University Health Network, Toronto, ON, Canada Abstract: Glioblastoma (GBM) is the most common and fatal primary adult brain tumor. To date, various promising chemotherapeutic regimens have been trialed for use in GBM; however, temozolomide (TMZ) therapy remains the only US Food and Drug Administration-approved first-line chemotherapeutic option for newly diagnosed GBM. Despite maximal therapy with surgery and combined concurrent chemoradiation and adjuvant TMZ therapy, the median overall survival remains approximately 14 months. Given the failure of conventional chemotherapeutic strategies in GBM, there has been renewed interest in the role of immunotherapy in GBM. Dendritic cells are immune antigen-presenting cells that play a role in both the innate and adaptive immune system, thereby making them prime vehicles for immunotherapy via dendritic cell vaccinations (DCVs) in various cancers. There is great enthusiasm surrounding the use of DCVs for GBM with multiple ongoing trials. In this review, we comprehensively summarize the safety, efficacy, and quality of life results from 33 trials reporting on DCV for high-grade gliomas. Keywords: glioma, vaccine, dendritic cells, glioblastoma
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".