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Biomarkers of response to PD-1/PD-L1 inhibition

2017· review· en· W2621587943 on OpenAlexaff
Saman Maleki Vareki, Carmen Garrigós, Ignacio Durán

Bibliographic record

VenueCritical Reviews in Oncology/Hematology · 2017
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsLawson Health Research Institute
FundersU.S. Food and Drug AdministrationUniversity of ChicagoBristol-Myers Squibb
KeywordsMedicinePD-L1ImmunotherapyMelanomaImmune systemOncologyHead and neck squamous-cell carcinomaLymphomaCytotoxic T cellCancerRenal cell carcinomaHead and neck cancerInternal medicineCancer researchAntigenImmunologyBiology

Abstract

fetched live from OpenAlex

Immunotherapy is a promising treatment strategy for cancer that has recently shown unprecedented survival benefits in selected patients. A number of immunomodulatory agents that target immune system checkpoints such as the cytotoxic T-lymphocyte antigen 4 (CTLA-4), the programmed death-1 (PD-1) or its ligand (PD-L1), have received regulatory approval for the treatment of multiple cancers including malignant melanoma, non-small cell lung cancer, renal cell carcinoma, classical Hodgkin lymphoma, and recurrent or metastatic head and neck squamous cell carcinoma. Nevertheless, a substantial proportion of patients treated with checkpoint inhibitors have little or no benefit while these treatments are costly and might have associated toxicities. Hence, the establishment of valid predictors of treatment response has become a priority. This review summarizes the current evidence around biomarkers of response to PD-1/PD-L1 inhibition, considering features related to the tumor and to the host immune system.

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)0.005
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.179
GPT teacher head0.511
Teacher spread0.332 · 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 designOther design
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

Citations318
Published2017
Admission routes1
Has abstractyes

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