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Record W4408555214 · doi:10.1055/s-0045-1804649

Amivantamab Plus Lazertinib vs Osimertinib in First-line EGFR-mutant Advanced NSCLC: Longer Follow-up of the MARIPOSA Study

2025· article· en· W4408555214 on OpenAlexaff
Marcel Wiesweg, Shirish M. Gadgeel, Byoung Chul Cho, Lu Shen, Enriqueta Felip, Hidetoshi Hayashi, Alexander I. Spira, Benjamin Besse, Michael Thomas, Scott Owen, Yongsoo Kim, Soo‐Youn Lee, Joana Mourão, Youngkwan Lee, Yanqiu Zhao, Yifeng Fang, Nicolas Girard, Zhe Liu, Ping Sun, S. M. P. Oliveira, Hong Shen, Luis Paz‐Ares, Shin Matsumoto, Hiroshi Tanaka, Abrar Ahmad, Т. Андабеков, Patrapim Sunpaweravong, Özgür Özyılkan, James Chih‐Hsin Yang, Maya Gottfried, Olivier Hernandez, Martin Kimmich, Diego Cortinovis, Diego Kaen, Lydia Montes, S Popat, Thomas Newsom-Davis, David R. Spigel, Jia Xie, Tao Sun, E. Fennema, Mahesh Daksh, Marguerite Ennis, Sean K. Sethi, Joshua Bauml, Duc Nguyen

Bibliographic record

VenuePneumologie · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsRoyal Ottawa Mental Health CentreMcGill University Health CentreMontreal General Hospital
Fundersnot available
KeywordsOsimertinibMutantMedicineInternal medicineOncologyLine (geometry)Cancer researchBiologyGeneticsEpidermal growth factor receptorCancerGeneErlotinibMathematics

Abstract

fetched live from OpenAlex

Introduction: Amivantamab (ami) is an EGFR-MET bispecific antibody with immune cell-directing activity. Lazertinib (laz) is a CNS-penetrant 3 rd -generation EGFR TKI. In the primary analysis of the phase 3 MARIPOSA study (NCT04487080), at a median follow-up of 22.0 months, ami plus laz significantly improved progression-free survival (PFS) by blinded independent central review vs osimertinib (osi) in patients with treatment-naïve, EGFR -mutated advanced NSCLC (HR, 0.70; 95% CI, 0.58-0.85; P <0.001). Early interim overall survival (OS) analysis showed a favorable trend for ami-laz over osi (HR, 0.80; 95% CI, 0.61-1.05; P =0.11). Here, we present updated results with longer follow-up from MARIPOSA. Methods: MARIPOSA randomized 1074 patients with treatment-naïve, EGFR -mutated (Exon 19 del or Exon 21 L858R substitutions) locally advanced or metastatic NSCLC 2:2:1 to open-label ami-laz (n=429), blinded osi (n=429), or blinded laz (n=216). This analysis, requested by health authorities, compares ami-laz with osi. Results: At a median follow-upof 31.1 months, 44% (185/421) and 34% (145/428) of patients were still on treatment in the ami-laz and osi arms, respectively. In total, 155 patients in the ami-laz arm and 233 in the osi arm had investigator-assessed progressive disease and discontinued treatment. Of those, 72% (111/155) and 74% (173/233) initiated subsequent therapy, respectively, with carbo-pem being the most common first subsequent therapy across arms (ami-laz, 26% [29/111]; osi, 28% [48/173]). PFS after first subsequent therapy (PFS2) favored ami-laz (HR, 0.73; 95% CI, 0.59-0.91; nominal P =0.004). Patients receiving ami-laz demonstrated significantly longer median time to treatment discontinuation and time to subsequent therapy vs osi. Intracranial PFS showed a favorable trend for ami-laz vs osi . While not formally tested for significance, median OS was not estimable for ami-laz vs 37.3 months for osi (HR, 0.77; 95% CI, 0.61-0.96; nominal P =0.019). At 24 months, 75% and 70% of patients were alive in the ami-laz and osi arms, respectively; corresponding values at 36 months were 61% and 53%. Conclusions: Ami-laz continues to show a trend towards improved OS while also improving post-progression outcomes vs osi, reaffirming ami-laz as a first-line standard-of-care for EGFR -mutated advanced NSCLC. Publication History Article published online: 18 March 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
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 head0.022
GPT teacher head0.340
Teacher spread0.317 · 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 designNon-randomized 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

Citations4
Published2025
Admission routes1
Has abstractno

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