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Exploratory biomarker analysis of the phase 3 KEYNOTE-604 study of pembrolizumab plus etoposide for extensive-stage SCLC.

2023· article· en· W4379340377 on OpenAlexaff
Charles M. Rudin, Hye Ryun Kim, Alejandro Navarro, Maya Gottfried, Solange Peters, Tibor Csőszi, Parneet Cheema, Delvys Rodríguez‐Abreu, Mira Wollner, James Chih‐Hsin Yang, Julien Mazières, Terufumi Kato, Gregory P. Kalemkerian, Elisha J. Dettman, Mackenzie Edmondson, Amir Vajdi, Andrey Loboda, Hazem El‐Osta, Bin Zhao, Mark M. Awad

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsWilliam Osler Health SystemUniversity of Toronto
Fundersnot available
KeywordsMedicinePembrolizumabOncologyInternal medicineCancer researchCancerImmunotherapy

Abstract

fetched live from OpenAlex

8503 Background: In the phase 3 KEYNOTE-604 study of extensive-stage small-cell lung cancer (ES-SCLC; NCT03066778), first-line pembrolizumab (pembro) plus etoposide and platinum (EP) significantly improved PFS vs placebo (pbo) plus EP (HR, 0.75; P = 0.0023), with favorable OS (significance threshold not met; HR, 0.80; P = 0.0164). PFS/OS were similar regardless of PD-L1 CPS. In this exploratory analysis, tumor mutational burden (TMB), 18-gene T cell–inflamed gene expression profile (Tcell inf GEP) and SCLC transcriptional subtypes were assessed as correlates of survival. Methods: Patients (pts) eligible for this analysis of KEYNOTE-604 had previously untreated ES-SCLC with evaluable pretreatment tumor samples. TMB was assessed by whole-exome sequencing (WES) of tumor and matched normal DNA. RNA-seq was used to determine Tcell inf GEP and SCLC transcriptional subtypes (ASCL1, POU2F3, NEUROD1, YAP1, or inflamed). Associations of TMB, Tcell inf GEP, and SCLC subtype with OS were analyzed using an adjusted Cox proportional hazards model. 1-sided (pembro + EP) and 2-sided (pbo + EP) P values were calculated for TMB and Tcell inf GEP (prespecified α = 0.05); 2-sided P values were calculated for SCLC subtype (multiplicity-adjusted, α = 0.10). Clinical utility was assessed using prespecified cutoffs of ≥175 mut/exome for TMB and the first tertile for Tcell inf GEP. Clinical data cutoff date was Dec 2, 2019. Results: Of 453 pts randomized in KEYNOTE-604 (ITT), 318 had WES data (pembro + EP, n = 167; pbo + EP, n = 151), and 316 had RNA-seq data (pembro + EP, n = 159; pbo + EP, n = 157). High TMB was positively associated with OS in the pbo + EP group ( P = 0.005) but not the pembro + EP group ( P = 0.450). There was a positive association between higher Tcell inf GEP and OS in the pembro + EP ( P = 0.003) and pbo + EP ( P < 0.005) groups. SCLC subtypes were not associated with OS in either group (pembro + EP, P = 0.960; pbo + EP, P = 0.999). Clinical benefit of pembro + EP over pbo + EP was demonstrated for TMB <175 mut/exome, but not for TMB ≥175 mut/exome. Pembro + EP benefit over pbo + EP was consistent across Tcell inf GEP subgroups. Conclusions: In this exploratory analysis of biomarker subgroups of KEYNOTE-604, TMB and SCLC subtypes were not associated with OS in the pembro + EP group in pts with ES-SCLC. While Tcell inf GEP was positively associated with OS in both treatment groups, no additional OS benefit was observed with pembro + EP. Further research is warranted to better identify predictive biomarkers to immunotherapy. Clinical trial information: NCT03066778 . [Table: see text]

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)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.398
GPT teacher head0.605
Teacher spread0.207 · 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 designRandomized trial
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".

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Citations20
Published2023
Admission routes1
Has abstractyes

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Same venueJournal of Clinical OncologySame topicLung Cancer Research StudiesFrench-language works237,207