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Record W4292884011 · doi:10.2217/fon-2022-0595

HERIZON-GEA-01: Zanidatamab + chemo ± tislelizumab for 1L treatment of HER2-positive gastroesophageal adenocarcinoma

2022· article· en· W4292884011 on OpenAlex
Josep Tabernero, Lin Shen, Elena Elimova, Geoffrey Y. Ku, Tianshu Liu, Kohei Shitara, Xiao Lin, Lisa Boyken, Huiyan Li, Jonathan Grim, Jaffer A. Ajani

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

VenueFuture Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsZymeworks (Canada)Princess Margaret Cancer Centre
FundersNational Cancer Institute
KeywordsMedicineTrastuzumabInternal medicineChemotherapyOncologyGastroesophageal JunctionMonoclonal antibodyCancerAdenocarcinomaAntibodyImmunologyBreast cancer

Abstract

fetched live from OpenAlex

HER2-positive gastroesophageal adenocarcinomas (GEAs) are common cancers with high mortality and the treatment options for advanced/metastatic disease are limited. Zanidatamab and tislelizumab are novel monoclonal antibodies targeting HER2 and PD-1, respectively, and have shown encouraging antitumor activity in early phase studies in multiple cancers, including GEA. Preliminary data suggest that dual targeting of the HER2 and PD-1 pathways could further improve upon the results achieved with targeting either pathway alone. Here, we describe the design of HERIZON-GEA-01, a global, randomized, open-label, active-comparator, Phase III study to evaluate and compare the efficacy and safety of zanidatamab plus chemotherapy with or without tislelizumab to the standard of care (trastuzumab plus chemotherapy) as first-line treatment for patients with advanced/metastatic HER2-positive GEAs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.294
Teacher spread0.277 · 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