Amivantamab in Participants With Advanced NSCLC and MET Exon 14 Skipping Mutations: Final Results From the CHRYSALIS Study
Bibliographic record
Abstract
INTRODUCTION: Amivantamab is an EGFR-MET bispecific antibody with immune cell-directing activity. We assessed the safety and efficacy of amivantamab in participants with advanced NSCLC harboring primary MET exon 14 skipping mutations (METex14). METHODS: CHRYSALIS enrolled participants with METex14 NSCLC who progressed after or declined standard-of-care therapy. Participants received intravenous amivantamab weekly for 4 weeks and biweekly thereafter. Objective response rate, duration of response (DoR), clinical benefit rate, progression-free survival, overall survival, safety, and circulating tumor DNA were analyzed. RESULTS: Among 97 participants, 16 were treatment naive, 28 received prior treatment without MET therapies, and 53 received prior MET therapies. Objective response rate was 32% overall, 50% in treatment-naive participants, 46% in participants without prior MET therapies, and 19% in participants with prior MET therapies. In participants without prior MET therapies, amivantamab activity was observed regardless of co-occurring genomic alterations. Clinical benefit rate was 69% overall, 88% in treatment-naive participants, 64% in participants without prior MET therapies, and 66% in participants with prior MET therapies. Median DoR was 11.2 months; 61% (19/31) of the responders had DoR greater than or equal to 6 months. Median progression-free survival was 5.3 months (95% confidence interval, 4.3-7.0); median overall survival was 15.8 months (95% confidence interval, 14.6-not estimable). Most common adverse events were rash (79%) and infusion-related reactions (72%), most being grades 1 to 2 (52%). CONCLUSIONS: The safety profile was consistent with previous reports of amivantamab in EGFR-mutant NSCLC. Amivantamab demonstrated clinically meaningful and durable antitumor activity in participants with METex14 advanced NSCLC, including those who progressed on prior MET therapies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".