Evidence map›Paper›PMID 42170267›Full record

ArticleTranslational lung cancer research2026

The IASLC grading system as a predictor for EGFR-TKI therapy in patients with

Chaoqiang Deng, Molin Zhang, Fangqiu Fu, Qiang Zheng, Yuan Li, Yang Zhang, Haiquan Chen

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In one paragraph

Article in Translational lung cancer research, 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

7 authors.

Chaoqiang Deng *Department of Thoracic Surgery and State Key Laboratory of Genetics and Development of Complex Phenotypes, Fudan University Shanghai Cancer Center, Shanghai, China.
Molin Zhang *Department of Thoracic Surgery and State Key Laboratory of Genetics and Development of Complex Phenotypes, Fudan University Shanghai Cancer Center, Shanghai, China.
Fangqiu FuDepartment of Thoracic Surgery and State Key Laboratory of Genetics and Development of Complex Phenotypes, Fudan University Shanghai Cancer Center, Shanghai, China.
Qiang ZhengInstitute of Thoracic Oncology, Fudan University, Shanghai, China.
Yuan LiInstitute of Thoracic Oncology, Fudan University, Shanghai, China.
Yang ZhangDepartment of Thoracic Surgery and State Key Laboratory of Genetics and Development of Complex Phenotypes, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID https://orcid.org/0000-0002-9081-0802
Haiquan ChenDepartment of Thoracic Surgery and State Key Laboratory of Genetics and Development of Complex Phenotypes, Fudan University Shanghai Cancer Center, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: We previously validated the grading system proposed by International Association for the Study of Lung Cancer (IASLC) for invasive nonmucinous lung adenocarcinoma (LADC) for its reproducibility, prognostication function and predictive value of adjuvant chemotherapy (ACT). In this exploratory study, we aimed to investigate the role of IASLC grading system in EGFR tyrosine kinase inhibitor (TKI) therapy selection either as adjuvant or palliative therapy. Methods: From 2008 to 2021, a cohort of 2,160 patients with invasive nonmucinous Results: Conclusions: This retrospective study first revealed the feasibility of IASLC grading system as a potential prediction factor for EGFR-TKIs therapy in patients with

Indexed as

EGFR mutationsInternational Association for the Study of Lung Cancer grading system (IASLC grading system)outcometyrosine kinase inhibitor (TKI)

Identifiers

PMID42170267
PMCPMC13186656

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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.