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Record W2883891816 · doi:10.2147/tcrm.s135865

Dendritic cell vaccines for high-grade gliomas

2018· review· en· W2883891816 on OpenAlexaff
Matthew E. Eagles, Farshad Nassiri, Jetan H. Badhiwala, Suganth Suppiah, Saleh A. Almenawer, Gelareh Zadeh, Kenneth Aldape

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2018
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsMcMaster UniversityUniversity of TorontoUniversity Health NetworkUniversity of Calgary
Fundersnot available
KeywordsMedicineTemozolomideAdjuvantImmunotherapyGliomaDendritic cellImmune systemOncologyInternal medicineCancer researchImmunology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.066
GPT teacher head0.376
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations55
Published2018
Admission routes1
Has abstractyes

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