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Abstract LB416: SAVANNAH: Clearance of plasma EGFRm in patients with EGFRm MET-overexpressed (OverExp) and/or -amplified (Amp) NSCLC post-osimertinib (osi) treated with savolitinib (savo) + osi

2025· article· en· W4409821093 on OpenAlexaff
Jonathan W. Riess, Filippo de Marinis, Benjamin Levy, Tae Min Kim, Quincy S. Chu, Marcello Tiseo, Adrian G. Sacher, Silvia Novello, Christina S. Baik, Lyudmila Bazhenova, Jacques Cadranel, Giulio Metro, Cheng‐Ta Yang, Tsung‐Ying Yang, Gee‐Chen Chang, Konstantinos Leventakos, Lorenzo Livi, James Chih‐Hsin Yang, Lecia V. Sequist, John R. Argue, Wanning Xu, Aleksandra Markovets, Ryan J. Hartmaier, Myung‐Ju Ahn

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsOsimertinibMedicineInternal medicineCancerAdenocarcinoma

Abstract

fetched live from OpenAlex

Abstract Background: Savo is an oral, potent and highly selective MET-TKI. In the Phase 2 SAVANNAH study (NCT03778229), savo + osi had a high rate of durable responses in pts with EGFRm advanced NSCLC and high MET OverExp and/or Amp levels. Early clearance of plasma EGFRm may predict outcomes. We report an exploratory analysis of plasma EGFRm clearance and its association with MET tissue biomarker status, ORR and PFS. Methods: Pts with EGFRm advanced NSCLC and MET OverExp and/or Amp with PD on 1L+ osi received savo 300 mg QD, 300 mg BID or 600 mg QD + osi 80 mg QD. MET OverExp/Amp was centrally confirmed (by IHC [Roche], 3+ intensity in ≥50% of tumor cells [MET IHC3+/≥50%]; by FISH [Abbott Molecular], MET gene copy number ≥5 or MET:CEP7 ratio ≥2 [FISH5+], or at higher thresholds of MET IHC3+/≥90% or FISH10+). Baseline (BL) and Wk 3 plasma EGFRm (Ex19del/L858R) were analyzed by ddPCR (Biodesix) as an estimate of tumor burden. MET Amp was not monitored in ctDNA due to low detection sensitivity. Clearance was defined as undetected EGFRm ctDNA at Wk 3, when detected at BL. PFS was investigator-assessed (RECIST 1.1). DCO: Aug 23, 2024. Results: Of 344 pts with evaluable BL ctDNA, 259 (75%) had detected EGFRm ctDNA. Of these, 225 had evaluable ctDNA at Wk 3 (82 [36%] had EGFRm clearance at Wk 3). Confirmed ORR was higher in pts with EGFRm Wk 3 clearance (56/82; 68%) vs non-clearance (38/143; 27%). PFS was longer in pts with vs without EGFRm clearance at Wk 3 (Table). Across all pts evaluable for ctDNA at Wk 3, clearance rates were higher in pts with vs without high MET (69/162 [43%] vs 13/63 [21%]; odds ratio [95% CI] 0.35 [0.16, 0.72]). Similar results were seen in the savo 300 mg QD + osi subgroup. Conclusions: In SAVANNAH, among pts with detected EGFRm ctDNA at BL, clearance at Wk 3 was associated with improved ORR and PFS. Plasma EGFRm clearance at Wk 3 is enriched in pts with MET IHC3+/≥90% or FISH10+ status, consistent with improved efficacy in this biomarker subgroup. Citation Format: Jonathan W. Riess, Filippo de Marinis, Benjamin Levy, Tae Min Kim, Laura Bonanno, Quincy Chu, Marcello Tiseo, Adrian Sacher, Silvia Novello, Christina Baik, Lyudmila Bazhenova, Jacques Cadranel, Giulio Metro, Cheng-Ta Yang, Tsung-Ying Yang, Gee-Chen Chang, Konstantinos Leventakos, Lorenzo Livi, James Chih-Hsin Yang, Lecia V. Sequist, John Argue, Wanning Xu, Aleksandra Markovets, Ryan Hartmaier, Myung-Ju Ahn. SAVANNAH: Clearance of plasma EGFRm in patients with EGFRm MET-overexpressed (OverExp) and/or -amplified (Amp) NSCLC post-osimertinib (osi) treated with savolitinib (savo) + osi [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB416.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.042
GPT teacher head0.391
Teacher spread0.350 · 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 designNot applicable
Domainnot available
GenreOther

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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Citations0
Published2025
Admission routes1
Has abstractyes

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