Evidence map›Paper›PMID 41023700›Full record

ArticleBMC medical imaging2025

Nomogram to predict the EGFR mutation status in stage III-IV solid lung adenocarcinoma patients.

Wenjian Tang, Yuan Kang, Bo Lan, Zhiqiang Zhang, Jiawei Feng, Feng Li, Xinyi Zeng, Junyuan Zhong, Shuhua Luo, Jianping Zhong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Wenjian Tang *Ganzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Yuan Kang *Ganzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Bo Lan *Ganzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Zhiqiang ZhangGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Jiawei FengGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Feng LiGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Xinyi ZengGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Junyuan ZhongGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China.
Shuhua LuoGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China. luoshuhua@mail.gzsrmyy.com.
Jianping ZhongGanzhou Institute of Medical Imaging, Ganzhou Key Laboratory of Medical Imaging and Artificial Intelligence, Medical Imaging Center, Ganzhou People's Hospital, The Affiliated Ganzhou Hospital, Jiangxi Medical College, Nanchang University, Ganzhou, 341000, China. zhongjianping@mail.gzsrmyy.com.

Funding

the Clinical Research Center for Medical Imaging in Jiangxi Province No. 20223BCG7400199the Ganzhou Health Commission Scientific Research Planning Project GZWJW202402108the Ganzhou Science and Technology Planning Project No. GZ2024YLJ016, GZ2024YLJ026, GZ2024ZSF064 and 2022-ZD1373the National Natural Science Foundation of China 82160330the Science and Technology Program of the Health Commission of Jiangxi Province 2025110045
6 · The paper itself

Abstract

backgroundTo assess the clinical characteristics and CT findings associated with epidermal growth factor receptor (EGFR) mutation status in stage III-IV solid lung adenocarcinoma (LAD) patients.

methodsIn this retrospective study, stage III-IV solid LAD patients who underwent chest CT from January 2015 to July 2025 were included. Clinical characteristics and CT findings significantly associated with the EGFR mutation status were identified via multivariable logistic regression.

resultsA total of 420 patients with stage III-IV solid LAD were included (training cohort: 375 patients, from January 2015 to April 2024; validation cohort: 45 patients, from May 2024 to July 2025). Compared with wild-type EGFR patients, EGFR-mutant LAD were significantly younger (< 60 years), more likely to be female, nonsmokers, and to have stage IV disease. In terms of CT findings, patients with mutant EGFR were more likely to have a tumor size < 4.5 cm, a well-defined tumor boundary, a vessel convergence sign, pleural indentation and obstructive pneumonia or atelectasis. In the multivariable analysis, age (OR, 0.428; 95% CI 0.242-0.756), sex (OR, 0.200; 95% CI 0.112-0.356), overall stage (OR, 2.230; 95% CI 1.141-4.359), tumor size (OR, 0.474; 95% CI 0.260-0.864, P = 0.015), tumor boundary (OR, 3.461; 95% CI 1.877-6.382), the presence of the vessel convergence sign (OR, 2.869; 95% CI 1.675-4.913), and obstructive pneumonia or atelectasis (OR, 3.870; 95% CI 2.028-7.385) were identified as factors that independently predict the EGFR mutation status. We further constructed a nomogram for predicting the EGFR mutation status via a logistic regression model. Logit (P) = 0.197 + (-1.599) × sex + (-0.850) × age + 0.900 × overall stage + (-0.762) × tumor size + 1.246 × tumor boundary + 1.042 × vessel convergence sign + 1.367 × obstructive pneumonia or atelectasis. The area under the curve (AUC) of the nomogram in training cohort was 0.829 (95% CI: 0.783, 0.876). In the validation cohort, the AUC was 0.826 (95% CI: 0.681, 0.970).

conclusionsA nomogram including sex, age, overall stage, tumor size, tumor boundary, the vessel convergence sign, and obstructive pneumonia or atelectasis, was helpful in predicting the EGFR mutation status in stage III-IV solid LAD patients.

Indexed as

Adenocarcinoma of LungLung NeoplasmsNomogramsAdultAgedErbB ReceptorsFemaleHumansMaleMiddle AgedMutationNeoplasm StagingRetrospective StudiesTomography, X-Ray ComputedEGFR protein, humanErbB ReceptorsAdenocarcinomaComputed tomographyEGFR mutation statusLungNomogram

Identifiers

PMID41023700
PMCPMC12482595

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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.