MétaCan
Menu
Back to cohort
Record W3129135562 · doi:10.1136/jitc-2020-001580

Immunotherapy for sarcomas: new frontiers and unveiled opportunities

2021· review· en· W3129135562 on OpenAlexafffund
Harsimrat Kaur Birdi, Anna Jirovec, Serena Cortés-Kaplan, Joel Werier, Carolyn Nessim, Jean‐Simon Diallo, Michele Ardolino

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2021
Typereview
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsMedicineImmunotherapyMalignancySarcomaRadiation therapyDiseaseCancerSoft tissue sarcomaCancer immunotherapyOncologyCancer researchPathologyInternal medicine

Abstract

fetched live from OpenAlex

Sarcomas are a rare malignancy of mesenchymal tissues, comprizing a plethora of unique subtypes, with more than 60 types. The sheer heterogeneity of disease phenotype makes this a particularly difficult cancer to treat. Radiotherapy, chemotherapy and surgery have been employed for over three decades and, although effective in early disease (stages I-II), in later stages, where metastatic tumors are present, these treatments are less effective. Given the spectacular results obtained by cancer immunotherapy in a variety of solid cancers and leukemias, there is now a great interest in appliying this new realm of therapy for sarcomas. The widespread use of immunotherapy for sarcoma relies on immuno-profiling of subtypes, immunomonitoring for prognosis, preclinical studies and insight into the safety profile of these novel therapies. Herein, we discuss preclinical and clinical data highlighting how immunotherapy is being used in soft tissue sarcoma and bone sarcomas.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.125
GPT teacher head0.415
Teacher spread0.291 · 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 teacher head, not a consensus.

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

Citations69
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal for ImmunoTherapy of CancerSame topicSarcoma Diagnosis and TreatmentFrench-language works237,207