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Nomogram to predict the EGFR mutation status in stage III-IV solid lung adenocarcinoma patients
Wenjian Tang1, Yuan Kang1, Bo Lan1
1Ganzhou 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.
Background:
To 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.
Methods:
In 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.
Results:
A 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).
Conclusions:
A 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.
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