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307 Atezolizumab plus vemurafenib and cobimetinib provides favorable survival outcomes in patients with high tumor mutation burden and proinflammatory gene signature in the phase 3 IMspire150 study

2020· article· en· W3103606205 on OpenAlexaff
Karl D. Lewis, Paolo A. Ascierto, Caroline Robert, Rodrigo Ramella Munhoz, Gabriella Liszkay, Luis De La Cruz Marino, Judit Oláh, Paola Queirolo, Jacek Mackiewicz, Kalpit Shah, Harper Forbes, Christian Hertig, Yibing Yan, Ralf Gutzmer, Grant A. McArthur

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsRoche (Canada)
FundersPritzker School of MedicineAmerican Society of Hematology
KeywordsVemurafenibInternal medicineMedicineAtezolizumabHazard ratioOncologyProgression-free survivalMelanomaPembrolizumabImmunotherapyCancer researchCancerOverall survivalMetastatic melanomaConfidence interval

Abstract

fetched live from OpenAlex

Background The phase 3 IMspire150 study (NCT02908672) showed that first-line atezolizumab (A) combined with vemurafenib (V) + cobimetinib (C) improved progression-free survival (PFS) vs placebo (P) + V + C in patients with BRAFV600 mutation–positive advanced melanoma (15.1 vs 10.6 months; hazard ratio [HR] 0.78; 95% CI 0.63–0.97; P=0.0249). Insights into the clinical benefit of the A+V+C triple combination in prognostic molecular subgroups of patients can inform treatment selection and future clinical research. Methods 514 patients were randomized 1:1 to A+V+C (n=256) or P+V+C (n=258). The efficacy endpoints analyzed included PFS and duration of response (DOR) estimated using the Kaplan-Meier method. Outcomes were based on investigator-assessed best overall response per Response Evaluation Criteria in Solid Tumors v1.1. Patients were primarily categorized into binary subgroups defined by tumor mutation burden (TMB; low or high: <10 or ≥10 mutations/Mb, respectively) or by the < or ≥ median values of interferon (IFN)-gamma or CD8+ tumor cells. In addition, these subgroups were further broken down based on the proportion of programmed death-ligand 1 (PD-L1)-expressing tumor-infiltrating cells as PD-L1+ (≥1%) or PD-L1– (<1%). Results Patients treated with P+V+C with high and low TMB had similar PFS outcomes. However, the magnitude of the PFS benefit with A+V+C vs P+V+C was markedly higher in patients with high TMB (≥10 mutations/Mb) compared with patients with low TMB (<10 mutations/Mb) in whom the benefit between treatment arms was comparable (figure 1A). The magnitude of the PFS benefit with A+V+C was further enhanced in patients with high TMB and PD-L1– compared with patients with high TMB and PD-L1+. Overall, patients with potential for increased antitumor immunity (IFN-gamma ≥ median or CD8+ ≥ median) who received A+V+C had more favorable outcomes compared with their counterparts with IFN-gamma < median or CD8+ < median. In general, the PFS benefit with A+V+C vs P+V+C was more readily apparent in PD-L1– subgroups. Similar trends were seen with DOR (figure 1B). Conclusions There was a trend of larger magnitude of PFS benefit with A+V+C vs P+V+C in PD-L1– patient subgroups, who benefit less with single-agent immunotherapy. The PFS and DOR benefits were more evident in patients with high IFN-gamma or TMB >10 mutations/Mb. Additional multivariate analyses are ongoing to delineate the PFS trends observed. Trial Registration ClinicalTrials. gov, identifier NCT02908672

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.219
Teacher spread0.210 · 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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Citations3
Published2020
Admission routes1
Has abstractyes

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