MétaCan
Menu
Back to cohort
Record W4399616908 · doi:10.1016/j.omton.2024.200825

Transforming pancreaticobiliary cancer treatment: Exploring the frontiers of adoptive cell therapy and cancer vaccines

2024· review· en· W4399616908 on OpenAlexaff
Nawal Amhis, Julie Carignan, Lee‐Hwa Tai

Bibliographic record

VenueMolecular Therapy Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineImmunotherapyPancreatic cancerCancerModalitiesCancer immunotherapyAsymptomaticIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Pancreaticobiliary cancer, encompassing malignancies of both the pancreatic and biliary tract, presents a formidable clinical challenge marked by a uniformly bleak prognosis. The asymptomatic nature of its early stages often leads to delayed detection, contributing to an unfavorable 5-year overall survival rate. Conventional treatment modalities have shown limited efficacy, underscoring the urgent need for alternative therapeutic approaches. In recent years, immunotherapy has emerged as a promising avenue in the fight against pancreaticobiliary cancer. Strategies such as therapeutic vaccines and the use of tumor-infiltrating lymphocytes have garnered attention for their potential to elicit more robust and durable responses. This review seeks to illuminate the landscape of emerging immunotherapeutic interventions, offering insights from both clinical and research perspectives. By deepening our understanding of pancreaticobiliary cancer and exploring innovative treatment modalities, we aim to catalyze improvements in patient outcomes and quality of life.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.132
GPT teacher head0.415
Teacher spread0.283 · 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 designNot applicable
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

Citations9
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMolecular Therapy OncologySame topicPancreatic and Hepatic Oncology ResearchFrench-language works237,207