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Record W4400763069 · doi:10.1038/s41698-024-00641-7

Baseline biomarkers of efficacy and on-treatment immune-profile changes associated with bempegaldesleukin plus nivolumab

2024· article· en· W4400763069 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenpj Precision Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersOno PharmaceuticalBristol-Myers Squibb
KeywordsNivolumabMedicineBiomarkerOncologyImmune systemInternal medicineImmunotherapyCD8ImmunologyBiology

Abstract

fetched live from OpenAlex

In PIVOT IO 001 (NCT03635983), the combination of the investigational interleukin-2 agonist bempegaldesleukin (BEMPEG) with nivolumab (NIVO) had no added clinical benefit over NIVO monotherapy in unresectable/metastatic melanoma. Pre-defined baseline and on-treatment changes in selected biomarkers were analyzed to explore the potential mechanisms underlying the clinical observations. In each treatment arm, higher baseline tumor mutational burden or immune infiltration/inflammation was associated with improved efficacy compared with lower levels. On-treatment peripheral biomarker changes showed that BEMPEG + NIVO increased all immune cell subset counts interrogated, including regulatory T cells. This was followed by attenuation of the increase in CD8 + T cells, conventional CD4 + T cells, and systemic interferon gamma levels at later treatment cycles in the combination arm. Changes in tumor biomarkers were comparable between arms. These biomarker results help provide a better understanding of the mechanism of action of BEMPEG + NIVO and may help contextualize the clinical observations from PIVOT IO 001.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.028
GPT teacher head0.326
Teacher spread0.297 · 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