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Record W4397007301 · doi:10.1016/j.esmoop.2024.103220

198P Pembrolizumab plus olaparib vs pembrolizumab plus chemotherapy after induction with pembrolizumab plus chemotherapy for locally recurrent inoperable or metastatic TNBC: Patient-reported outcomes from KEYLYNK-009

2024· article· en· W4397007301 on OpenAlexaff
Antonio Llombart‐Cussac, H.S. Rugo, Mark E. Robson, S-A. Im, F. Dalenc, Eduardo Yañez Ruiz, F.A. Reyes, J.M. Walshe, Y-H Im, Svitlana Kulyk, Alexander S. Dudnichenko, N. Llinas, Shigehira Saji, A. Bardia, N. Harbeck, Amin Haiderali, L. Fan, Allison Martin Nguyen, J.A. Mejia, David W. Cescon

Bibliographic record

VenueESMO Open · 2024
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsPrincess Margaret Cancer Centre
FundersGenentechJapanese Society of Medical OncologyDaewoong Pharmaceutical CompanyChugai PharmaceuticalSeagenRadius HealthGilead SciencesEisaiDaiichi Sankyo EuropeSanofiAmgenPfizerLes Laboratories Pierre FabreAstraZenecaEli Lilly and Company
KeywordsPembrolizumabMedicineChemotherapyOlaparibOncologyInternal medicineImmunotherapyCancerPolymerase

Abstract

fetched live from OpenAlex

The phase II KEYLYNK-009 (NCT04191135) study evaluated maintenance pembrolizumab (pembro) + olaparib (ola) vs pembro + chemotherapy (chemo) in patients (pts) with metastatic TNBC who had clinical benefit from induction with first-line pembro + chemo. We present patient-reported outcomes (PROs) from this study to provide important evidence on the benefit/risk profile of these treatments.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.045
GPT teacher head0.336
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 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
GenreEmpirical

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

Citations5
Published2024
Admission routes1
Has abstractyes

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