Evidence map›Paper›PMID 40251527›Full record

SynthesisBMC cancer2025

MET tyrosine kinase inhibitors in combination with EGFR tyrosine kinase inhibitors in NSCLC patients with EGFR mutations and acquired MET alterations: a systematic review and meta-analysis.

Defeng Hu, Yixuan Hu, Shipeng Lei, Dongdong Wu, Yubo Wang

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Defeng Hu *Department of Respiratory and Critical Care Medicine, Chongqing University Jiangjin Hospital, 725# Jiangzhou Avenue, Dingshan Street, Jiangjin District, Chongqing, 402260, China.
Yixuan Hu *Basic Medicine School, Army Medical University, Chongqing, 400038, China.
Shipeng LeiDepartment of Respiratory and Critical Care Medicine, Chongqing University Jiangjin Hospital, 725# Jiangzhou Avenue, Dingshan Street, Jiangjin District, Chongqing, 402260, China.
Dongdong WuDepartment of Information, Daping Hospital, Army Medical University, 10# Changjiang Zhi Road, Yuzhong District, Chongqing, 400042, China. wudd01@tmmu.edu.cn.
Yubo WangDepartment of Respiratory and Critical Care Medicine, Chongqing University Jiangjin Hospital, 725# Jiangzhou Avenue, Dingshan Street, Jiangjin District, Chongqing, 402260, China. wangyubo_110@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcquired MET alterations is one of the resistance mechanisms to advanced NSCLC patients treated with EGFR tyrosine kinase inhibitors (TKIs). Several clinical trials combined MET-TKI (such as capmatinib, tepotinib, savolitinib) with EGFR-TKI to overcome MET alterations resistance. We performed this meta-analysis to determine the efficacy and safety of MET-TKI plus EGFR-TKI combined therapy in NSCLC patients.

methodsPubmed, Embase and the Cochrane Library were searched for relevant studies up to August 19, 2024. Data of objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), median duration of response (mDOR) and adverse events were extracted from the publications and analyzed.

resultsSix studies involving 562 patients were included in this meta-analysis. Our study showed a pooled ORR of 49.2% (95% confidence interval [CI] 0.402-0.582), a pooled DCR of 78.6% (95%CI 0.680-0.893), a mDOR of 6.85 months (95%CI 5.85-7.86), and a mPFS of 5.62 months (95%CI 4.74-6.50) in MET-TKI plus EGFR-TKI combination therapy for NSCLC patients with acquired MET-driven resistance after EGFR-TKI treatment. The pooled efficacy data suggested that combining MET-TKI with a third-generation EGFR-TKI was numerically superior to combining MET-TKI with a first-generation EGFR-TKI in patients who were T790M negative with MET-dependent resistance mechanism (ORR: 56.8% vs. 47.8%, p = 0.15; DCR: 81.6% vs. 75%, p = 0.57; mDOR: 9.08 vs. 7.00 months, p = 0.25; mPFS: 7.45 vs. 4.55 months, p = 0.05). The efficacy data of capmatinib plus EGFR-TKI, savolitinib plus EGFR-TKI and tepotinib plus EGFR-TKI (regardless of generation of EGFR-TKIs) was similar (ORR:47.7% vs. 50.7% vs. 48.8%, p = 0.96; DCR: 71.4% vs. 84.9% vs. 63.3%, p = 0.02; mDOR: NR vs. 8.4 vs. 8.01 months, p = 0.18; mPFS: 5.49 vs. 6.88 vs. 5.48 months, p = 0.56). Capmatinib subgroup seemed to demonstrate lower hepatotoxicity compared with savolitinib and tepotinib subgroups numerically (increased AST level: 12.8% vs. 18.8% vs. 17.4%, p = 0.66; increased ALT level: 14.2% vs. 17.6% vs. 20.1%, p = 0.91). And a lower occurrence rate of ≥ 3 grade TRAEs was observed in the capmatinib subgroup compared to the savolitinib or tepotinib subgroups (30.0% vs. 46.7% vs. 41.2%, p = 0.07).

conclusionThe findings from this meta-analysis suggest that the combination of MET-TKI and EGFR-TKI represents a promising therapeutic approach for NSCLC patients who have acquired MET alterations following EGFR-TKI treatment. Notably, the combination of MET-TKI and a third-generation EGFR-TKI demonstrated enhanced survival benefits compared to the combination with a first-generation EGFR-TKI. Furthermore, different MET-TKIs based combination therapy did not display significant differences in efficacy, while capmatinib based combination therapy showed better safety profile and lower hepatotoxicity.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, Non-Small-Cell LungLung NeoplasmsProtein Kinase InhibitorsProto-Oncogene Proteins c-metDrug Resistance, NeoplasmErbB ReceptorsHumansMutationTyrosine Kinase InhibitorsEGFR protein, humanErbB ReceptorsMET protein, humanProtein Kinase InhibitorsProto-Oncogene Proteins c-metTyrosine Kinase Inhibitors

Identifiers

PMID40251527
PMCPMC12007359

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.