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Article Open Access

A nomogram prediction model for brain metastases in patients with lung adenocarcinoma 

  • Authors:
    • Hao Liu
    • Lan Wang
    • Xiaolei Zhuo
    • Yucheng Hu
    • Ziming Li
    • Huishan Deng
    • Mingshu Mo
  • View Affiliations / Copyright

    Affiliations: Department of Neurology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510163, P.R. China
    Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 400
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    Published online on: July 8, 2026
       https://doi.org/10.3892/ol.2026.15755
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Abstract

Patients with lung adenocarcinoma (LUAD) with brain metastasis (BM) frequently present without central nervous system (CNS) symptoms at initial diagnosis, underscoring the clinical need for early predictive tools. This study aimed to evaluate the role of epidermal growth factor receptor (EGFR) mutation subtypes in BM risk and to develop a nomogram prediction model combining EGFR mutation status with serum biomarkers in patients with LUAD. A retrospective cohort of 615 patients with LUAD‑401 with BM and 214 without BM, matched by age and sex‑was recruited from a single center in China between June 2021 and June 2024. Logistic regression, receiver operating characteristic (ROC) curve analysis and nomogram modeling were performed, with internal validation via 10‑fold cross‑validation. Although the overall distribution of EGFR mutations did not differ significantly between BM and non‑BM groups, the proportion of exon 19 deletion (19del) mutations was significantly higher in the BM group (P=0.013), with an odds ratio of 2.10 in the univariate analysis, and 19del was confirmed as an independent risk factor in the multivariate analysis. Serum concentrations of neuron‑specific enolase, CEA, CA125, CA153 and cytokeratin 19 fragment were markedly elevated in patients with BM (all P<0.0001); ROC analyses stratified by 19del mutation status demonstrated further improvement in predictive performance for selected biomarkers. A nomogram integrating 19del mutation status with the five serum biomarkers achieved an area under the ROC curve (AUC) of 0.835 in the training cohort and a cross‑validated AUC of 0.814, with good calibration confirmed by the Hosmer‑Lemeshow test (P=0.151). These findings indicate that LUAD patients harboring EGFR 19del mutations have an elevated BM risk and the combined nomogram provides an effective tool for BM risk stratification in clinical practice.
View Figures

Figure 1

Lung cancer biomarker concentrations
in patients with LUAD with EGFR mutations. The concentrations of
(A) NSE, (B) CEA, (C) CA125, (D) CA153 and (E) CYFRA21-1 in the
serum of different LUAD groups were detected. Patients were
stratified into four groups according to BM and EGFR mutation
status: nBMsnEGFR, non-BM without EGFR mutation; nBMsmEGFR, non-BM
with EGFR mutation; BMsnEGFR, BM without EGFR mutation; BMsmEGFR,
BM with EGFR mutation. The data are presented in scatter plots and
the median is shown by a horizontal line. P-values are shown above
the comparison brackets. Comparisons between groups were performed
with the Kruskal-Wallis test and Dunn's multiple-comparisons test.
LUAD, lung adenocarcinoma; NSE, neuron-specific enolase; CYFRA21-1,
cytokeratin 19 fragment; BM, brain metastasis.

Figure 2

Lung cancer biomarker concentrations
in patients with lung adenocarcinoma with the 19del mutation. The
concentrations of (A) NSE, (B) CEA, (C) CA125, (D) CA153 and (E)
CYFRA21-1 in the serum of patients with 19del mutation or BM were
detected. Patients were stratified into four groups according to BM
and 19del mutation status: nBMsn19del, non-BM without 19del;
nBMs19del, non-BM with 19del; BMsn19del, BM without 19del;
BMs19del, BM with 19del. The data are presented in scatter plots
and the median is shown by a horizontal line. P-values are shown
above the comparison brackets. Comparisons between groups were
performed with the Kruskal-Wallis test and Dunn's multiple
comparisons test. NSE, neuron-specific enolase; CYFRA21-1,
cytokeratin 19 fragment; BM, brain metastasis; 19del, exon 19
deletion.

Figure 3

ROC curves of 19del combined with
lung cancer biomarkers for the prediction of BM in patients with
LUAD. ROC curves of serum levels of (A) NSE, (B) CEA, (C) CA125,
(D) CA153 and (E) CYFRA21-1 were generated to distinguish BM in
patients with LUAD. The three subgroups are shown: 19del, patients
harboring the exon 19 deletion; n19del, patients without the exon
19 deletion; 19del+n19del, the overall cohort. ROC, receiver
operating characteristic; AUC, area under the ROC curve; NSE,
neuron-specific enolase; CYFRA21-1, cytokeratin 19 fragment; BM,
brain metastasis; 19del, exon 19 deletion; LUAD, lung
adenocarcinoma.

Figure 4

ROC curves of the combined method for
the prediction of brain metastasis in lung adenocarcinoma. ROC
curves of combined tumor markers, including NSE, CEA, CA125, CA153
and CYFRA21-1, were analyzed in subgroups of (A) 19del and (B) EGFR
mutations. ROC, receiver operating characteristic; AUC, area under
the ROC curve; NSE, neuron-specific enolase; CYFRA21-1, cytokeratin
19 fragment; 19del, exon 19 deletion.

Figure 5

Construction and validation of the
nomogram for BM. (A) Nomogram was constructed for predicting BM in
patients with lung adenocarcinoma, and (B) ROC curves and (C)
calibration plots were analyzed. (D) Decision curve analysis was
used to evaluate the clinical value of the nomogram model and TNM
model for the prediction of BM. ROC, receiver operating
characteristic; AUC, area under the ROC curve; NSE, neuron-specific
enolase; BM, brain metastasis; CYFRA21-1, cytokeratin 19 fragment;
19del, exon 19 deletion.
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Copy and paste a formatted citation
Spandidos Publications style
Liu H, Wang L, Zhuo X, Hu Y, Li Z, Deng H and Mo M: A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;. Oncol Lett 32: 400, 2026.
APA
Liu, H., Wang, L., Zhuo, X., Hu, Y., Li, Z., Deng, H., & Mo, M. (2026). A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;. Oncology Letters, 32, 400. https://doi.org/10.3892/ol.2026.15755
MLA
Liu, H., Wang, L., Zhuo, X., Hu, Y., Li, Z., Deng, H., Mo, M."A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;". Oncology Letters 32.3 (2026): 400.
Chicago
Liu, H., Wang, L., Zhuo, X., Hu, Y., Li, Z., Deng, H., Mo, M."A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;". Oncology Letters 32, no. 3 (2026): 400. https://doi.org/10.3892/ol.2026.15755
Copy and paste a formatted citation
x
Spandidos Publications style
Liu H, Wang L, Zhuo X, Hu Y, Li Z, Deng H and Mo M: A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;. Oncol Lett 32: 400, 2026.
APA
Liu, H., Wang, L., Zhuo, X., Hu, Y., Li, Z., Deng, H., & Mo, M. (2026). A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;. Oncology Letters, 32, 400. https://doi.org/10.3892/ol.2026.15755
MLA
Liu, H., Wang, L., Zhuo, X., Hu, Y., Li, Z., Deng, H., Mo, M."A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;". Oncology Letters 32.3 (2026): 400.
Chicago
Liu, H., Wang, L., Zhuo, X., Hu, Y., Li, Z., Deng, H., Mo, M."A nomogram prediction model for brain metastases in patients with lung adenocarcinoma&nbsp;". Oncology Letters 32, no. 3 (2026): 400. https://doi.org/10.3892/ol.2026.15755
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