Evidence map›Paper›PMID 42719457›Full record

ArticleExperimental and therapeutic medicine2026

Integrating clinical outcomes with molecular simulations to guide the selection of non-classical EGFR-TKIs: A comprehensive analysis and development of treatment strategies.

Fang Wei, Niu Niu, Chang Li, Ge Gao, Nan Li, Yan Wang

Abstract read
In one paragraph

Article in Experimental and therapeutic medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Fang WeiDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China.
Niu NiuDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong 518116, P.R. China.
Chang LiSchool of Computer and Information, Hefei University of Technology, Hefei, Anhui 230009, P.R. China.
Ge GaoSchool of Computer and Information, Hefei University of Technology, Hefei, Anhui 230009, P.R. China.
Nan LiSchool of Computer and Information, Hefei University of Technology, Hefei, Anhui 230009, P.R. China.
Yan WangDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-classical EGFR mutations in non-small cell lung cancer (NSCLC) are uncommon and heterogeneous, and the optimal EGFR-tyrosine kinase inhibitor (TKI) strategy remains uncertain. This retrospective study analyzed 31 patients with advanced/metastatic, recurrent or post-resection NSCLC harboring non-classical EGFR mutations who were treated at the Chinese Academy of Medical Sciences Cancer Hospital (Beijing, China) between 2013 and 2020, with follow-up updated to June 30, 2024. EGFR mutation status was obtained from routine clinical molecular pathology reports based on clinically validated targeted next-generation sequencing and/or amplification refractory mutation system PCR. Molecular docking and Prime Molecular Mechanics Generalized Born Surface Area (MM-GBSA) calculations were used to evaluate drug-mutant EGFR binding. Clinical outcomes varied by mutation subtype and EGFR-TKI regimen; relatively favorable progression-free survival (PFS) was observed with dacomitinib in L861Q and with afatinib- or dacomitinib-based treatment in selected S768I compound mutations. Exploratory Spearman analysis suggested that lower docking scores and more negative MM-GBSA ∆G_bind values were associated with longer PFS. These findings provide hypothesis-generating evidence that molecular simulation may help inform personalized EGFR-TKI selection for non-classical EGFR mutations, although validation in larger, consecutive and prospective multicenter cohorts is required.

Indexed as

EGFR-TKImolecular simulationNon-classical EGFR mutationsnon-small cell lung cancerpersonalized therapeutic strategies

Identifiers

PMID42719457
PMCPMC13554644

What Socratic holds

Textmetadata
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Registered trials

None linked

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 Socratic graph.