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<p>Lung cancer (LC) remains the most common cause of cancer-related death globally, and brain metastasis (BM) is an important factor contributing to its increased morbidity and mortality. Patients with LC carrying actionable gene mutations have a higher incidence of BM. Among these mutations, epidermal growth factor receptor (<i>EGFR</i>) mutation is the most common, followed by anaplastic lymphoma kinase (<i>ALK</i>) rearrangement. These mutations can affect the behavior of tumors and treatment outcomes. However, there is a lack of relevant research on the prognosis of patients carrying these mutations. In the present study, we developed a nomogram to predict the overall survival (OS) of patients with LC and BM harboring <i>EGFR</i> or <i>ALK</i> mutations. This retrospective analysis assessed the clinical characteristics and imaging data of 534 patients with BM of LC harboring <i>EGFR</i> or <i>ALK</i> mutations from 2010 to 2023. Specifically, 220 patients with LC and BM harboring <i>EGFR</i> or <i>ALK</i> mutations comprised the training cohort. Meanwhile, 314 patients as an external validation cohort. In the training cohort, least absolute shrinkage and selection operator (LASSO) regression was employed to analyze the relationship between variables and select the most relevant predictors, and a nomogram for OS prediction was developed and validated in the validation cohort. LASSO regression identified nine variables as significant predictors of OS, namely gender; age group; smoking history; extracranial metastases; location and number of BM; and receipt of radiotherapy, targeted therapy, and chemotherapy. The nomogram constructed using the aforementioned factors achieved areas under the curve (95% confidence interval) of 0.809 (0.670–0.948), 0.754 (0.636–0.872), and 0.72 (0.626–0.814) for predicting 12-, 24- and 36-month OS, respectively, in the training cohort, whereas the values in the validation cohort were 0.902 (0.857–0.948), 0.684 (0.540–0.829), and 0.672 (0.570–0.733), respectively. We established and verified a nomogram for predicting OS in patients with LC and BM harboring <i>EGFR</i> or <i>ALK</i> mutations. The prognostic nomogram achieved satisfactory accuracy and can be used as a prognostic stratification tool.</p>

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Development and validation of a nomogram for predicting the prognosis of lung cancer patients with brain metastases harboring EGFR or ALK mutations: a multicenter retrospective study

  • 期刊论文

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  • 发表日期：

    2026年7月21日

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  • Lun Liang,
  • Muling Shen,
  • Congzhi Qin,
  • Chang Liu,
  • Chaojue Huang,
  • Liangbao Wen,
  • Shixing Qin,
  • Anqi Li,
  • Fangyi Wei,
  • Shufang Deng,
  • Donggui Wei,
  • Chujun Qin,
  • Yonggao Mou,
  • Hao Duan,
  • Yongjia Yu,
  • Daqin Feng

摘要

Lung cancer (LC) remains the most common cause of cancer-related death globally, and brain metastasis (BM) is an important factor contributing to its increased morbidity and mortality. Patients with LC carrying actionable gene mutations have a higher incidence of BM. Among these mutations, epidermal growth factor receptor (EGFR) mutation is the most common, followed by anaplastic lymphoma kinase (ALK) rearrangement. These mutations can affect the behavior of tumors and treatment outcomes. However, there is a lack of relevant research on the prognosis of patients carrying these mutations. In the present study, we developed a nomogram to predict the overall survival (OS) of patients with LC and BM harboring EGFR or ALK mutations. This retrospective analysis assessed the clinical characteristics and imaging data of 534 patients with BM of LC harboring EGFR or ALK mutations from 2010 to 2023. Specifically, 220 patients with LC and BM harboring EGFR or ALK mutations comprised the training cohort. Meanwhile, 314 patients as an external validation cohort. In the training cohort, least absolute shrinkage and selection operator (LASSO) regression was employed to analyze the relationship between variables and select the most relevant predictors, and a nomogram for OS prediction was developed and validated in the validation cohort. LASSO regression identified nine variables as significant predictors of OS, namely gender; age group; smoking history; extracranial metastases; location and number of BM; and receipt of radiotherapy, targeted therapy, and chemotherapy. The nomogram constructed using the aforementioned factors achieved areas under the curve (95% confidence interval) of 0.809 (0.670–0.948), 0.754 (0.636–0.872), and 0.72 (0.626–0.814) for predicting 12-, 24- and 36-month OS, respectively, in the training cohort, whereas the values in the validation cohort were 0.902 (0.857–0.948), 0.684 (0.540–0.829), and 0.672 (0.570–0.733), respectively. We established and verified a nomogram for predicting OS in patients with LC and BM harboring EGFR or ALK mutations. The prognostic nomogram achieved satisfactory accuracy and can be used as a prognostic stratification tool.