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KEYNOTE-006 study of pembrolizumab (pembro) versus ipilimumab (ipi) for advanced melanoma: Efficacy by PD-L1 expression and line of therapy.

2016· article· en· W2477245600 on OpenAlexaff
Adil Daud, Christian U. Blank, Caroline Robert, Igor Puzanov, Erika Richtig, Kim Margolin, Steven O’Day, Marta Nyakas, Jose Lutzky, Ahmad A. Tarhini, Elaine McWhirter, Christian Caglevic, Peter Mohr, Michael Millward, Marcus O. Butler, Kenneth Emancipator, Scot Ebbinghaus, Nageatte Ibrahim, Georgina V. Long

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer CentreMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsPembrolizumabMedicineIpilimumabInternal medicineOncologyFamily medicineImmunotherapyCancer

Abstract

fetched live from OpenAlex

9513 Background: In KEYNOTE-006 (NCT01866319), pembro (MK-3475) provided superior OS and PFS and a lower grade 3-5 treatment-related AE rate over ipi in patients (pts) with advanced melanoma and ≤ 1 prior therapy. We assessed the impact of PD-L1 expression and prior therapy on outcomes in KEYNOTE-006. Methods: Pts were randomized to pembro 10 mg/kg Q2W or Q3W or ipi 3 mg/kg Q3W. Pembro was given for 24 mo or until progression, intolerable toxicity, or investigator decision. Ipi was given for 4 cycles or until progression, intolerable toxicity, or investigator decision. PD-L1 was assessed by IHC using the 22C3 antibody; positivity was defined as ≥ 1% staining in tumor and adjacent immune cells. Response was assessed at wk 12, Q6W until wk 48, then Q12W. Survival follow-up was every 12 wk. Primary end points were OS and PFS (RECIST v1.1, central review). Data cutoff date was Mar 3, 2015. Pembro arms were pooled for this analysis. Results: Of the 834 pts enrolled, 80% were PD-L1+, 18% were PD-L1–, and 2% were PD-L1 unknown; 66% were treatment naive and 34% had 1 line of prior therapy. PFS and ORR were improved with pembro regardless of line of therapy or PD-L1 status (Table); OS was improved with pembro in all but PD-L1– pts, although the sample size was small and the CI was wide. For pembro, the best outcomes occurred in treatment-naive pts and those with PD-L1+tumors, with marginal additional benefit in pts with both characteristics (Table). There was a relationship between increasing PD-L1 expression and improved outcomes with pembro vs ipi when PD-L1 was scored as IHC 0 (0% staining), 1 ( < 1%), 2 (1-9%), 3 (10-32%), 4 (33-65%), and 5 ( ≥ 66%). Conclusions: Pembro provides benefit over ipi in pts with advanced melanoma, regardless of tumor PD-L1 expression or whether pts received prior therapy. Clinical trial information: NCT01866319.Pembro vs Ipi PD-L1+ PD-L1– Treatment Naive 1 Prior Therapy PD-L1+, Treatment Naive PFS 6-mo rate, % 51 vs 25 32 vs 28 52 vs 28 38 vs 23 55 vs 28 HR (95% CI) 0.52 (0.43-0.64) 0.83 (0.55-1.26) 0.55 (0.44-0.69) 0.74 (0.55-0.99) 0.49 (0.38-0.63) OS 6-mo rate, % 87 vs 74 81 vs 73 87 vs 76 83 vs 71 88 vs 75 HR (95% CI) 0.56 (0.43-0.73) 0.95 (0.56-1.62) 0.63 (0.46-0.85) 0.67 (0.45-0.98) 0.55 (0.39-0.78) ORR, % 39 vs 13 25 vs 13 40 vs 13 29 vs 12 43 vs 13

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.002

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 head0.111
GPT teacher head0.464
Teacher spread0.353 · 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".

Quick stats

Citations15
Published2016
Admission routes1
Has abstractyes

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