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Record W3124047768 · doi:10.1002/eji.202048747

Combined anti‐PD‐1 and anti‐CTLA‐4 checkpoint blockade: Treatment of melanoma and immune mechanisms of action

2021· review· en· W3124047768 on OpenAlexaff
Zena Willsmore, Ben G T Coumbe, Silvia Crescioli, Sara Reci, Ayushi Gupta, R. J. C. Harris, Alicia M. Chenoweth, Jitesh Chauhan, Heather J. Bax, Alexa McCraw, Anthony Cheung, Gabriel Osborn, Ricarda M. Hoffmann, Mano Nakamura, Roman Laddach, Jenny L. C. Geh, Alastair D. MacKenzie Ross, Ciaran Healy, Sophia Tsoka, James Spicer, Debra H. Josephs, Sophie Papa, Katie E. Lacy, Sophia N. Karagiannis

Bibliographic record

VenueEuropean Journal of Immunology · 2021
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsSt. Thomas Hospital
FundersCancer Research UKMedical Research CouncilNational Institute for Health and Care ResearchBreast Cancer Now
KeywordsIpilimumabNivolumabPembrolizumabImmune checkpointBlockadeImmune systemCTLA-4MelanomaImmunotherapyImmunologyCytotoxic T cellBiologyCancer researchT cellMedicineInternal medicineReceptor

Abstract

fetched live from OpenAlex

Cytotoxic T-lymphocyte associated protein-4 (CTLA-4) and the Programmed Death Receptor 1 (PD-1) are immune checkpoint molecules that are well-established targets of antibody immunotherapies for the management of malignant melanoma. The monoclonal antibodies, Ipilimumab, Pembrolizumab, and Nivolumab, designed to interfere with T cell inhibitory signals to activate immune responses against tumors, were originally approved as monotherapy. Treatment with a combination of immune checkpoint inhibitors may improve outcomes compared to monotherapy in certain patient groups and these clinical benefits may be derived from unique immune mechanisms of action. However, treatment with checkpoint inhibitor combinations also present significant clinical challenges and increased rates of immune-related adverse events. In this review, we discuss the potential mechanisms attributed to single and combined checkpoint inhibitor immunotherapies and clinical experience with their use.

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)0.000
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.044
GPT teacher head0.308
Teacher spread0.265 · 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

Citations196
Published2021
Admission routes1
Has abstractyes

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