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International Journal of Frontiers in Medicine, 2023, 5(9); doi: 10.25236/IJFM.2023.050912.

Research progress on the establishment of brain metastasis risk models for non-small cell lung cancer


Zhao Yang1, Wen Li2, Yami Zhang3

Corresponding Author:
Yami Zhang

1Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, 712046, China

2Ningqiang County Tianjin Hospital, Hanzhong, Shaanxi, 724499, China

3Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, 712000, China


Non-small cell lung cancer brain metastases are one of its most serious complications, with patients suffering severe irreversible neurological damage due to its low rate of early diagnosis. Numerous risk factors are the main cause of brain metastases in non-small cell lung cancer. The establishment of multiple risk models is an important method for the prediction and prevention of NSCLC brain metastasis. This paper intends to discuss the research progress of NSCLC brain metastasis risk model, and provide ideas for the prevention and treatment of NSCLC brain metastasis in clinical practice.


NSCLC brain metastasis; risk factors; model establishment; research progress

Cite This Paper

Zhao Yang, Wen Li, Yami Zhang. Research progress on the establishment of brain metastasis risk models for non-small cell lung cancer. International Journal of Frontiers in Medicine (2023), Vol. 5, Issue 9: 73-79. https://doi.org/10.25236/IJFM.2023.050912.


[1] Zhou Kaijia, Zhang Ming, Liu Bowei, et al. Analysis of risk factors for brain metastasis after surgery for locally advanced non-small cell lung cancer and establishment of risk model[J]. Modern Medicine and Health, 2019, 35(13):4.

[2] Li Xiang, Du Tianqi, Wang Jie, et al. Epidemiology of patients with radiotherapy for brain metastases and its correlation with clinical features (with 205 cases)[J]. Modern Oncology, 2020, 28(12):5.

[3] Ding Cheng, Jiang Bolun, Zhao Chenguang, et al. Research progress on brain metastasis in non-small cell lung cancer[J]. Cancer Progress, 2017, 15(4):367-370.

[4] Yuan Gang, Hao Lingfang. Erlotinib combined with whole-brain radiotherapy for the treatment of brain metastases in non-small cell lung cancer Disease Surveillance and Control, 2017, 11(11): 890-891.

[5] Li Doudou, Jiang Yanhui, Bi Zhuofei, et al. Whole-brain radiation therapy in combination with erlotinib is not small Effect of brain metastasis in lung cancer[J]. Guangdong Medical Journal, 2015, 36(15):2412-2414.

[6] Braun D A, Bakouny Z, Hirsch L, et al. Beyond conventional immune-checkpoint inhibition — novel immunotherapies for renal cell carcinoma[J]. Nature Reviews Clinical Oncology, 2021, 18(4).

[7] Xia Jing, Cang Shundong. Clinical observation of osimertinib in patients with T790M-positive non-small cell lung cancer brain metastasis[J]. China Practical Medicine, 2021, 16(26):144-146.

[8] Cui Yuanyuan, Li Hang, Zhang Yu. A study of prophylactic brain irradiation for locally advanced non-small cell lung cancer[J]. Chinese Journal of Oncology, 2016, 38(1):1-3.

[9] Warner A, Dahele M , Bo H, et al. Factors Associated With Early Mortality in Patients Treated With Concurrent Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer[J]. International Journal of Radiation Oncology Biology Physics, 2016, 94(3):612-620.

[10] Tan Xiang. Clinical value analysis of serum tumor markers CEA, CA724, CA242, CA19-9 in the diagnosis of lung cancer[J]. Labeled Immunoassay and Clinical Medicine, 2017, 24( 8) : 900-904. 

[11] Chen Wanzhen, Yin Haiqing. Association between serum CEA CA199 CA125 level and efficacy of chemotherapy for lung adenocarcinoma[J]. Chinese Journal of Clinical New Medicine, 2019, 12( 7): 786-789. 

[12] Dai H, Liu J, Liang L, et al. Increased lung cancer risk in patients with interstitial lung disease and elevated CEA and CA125 serum tumour markers[J]. Respirology, 2014, 19 (5) : 707-713. 

[13] Fei Xiaodong. Diagnostic value of circulating tumor cells combined with multiple tumor markers in advanced NSCLC [J]. Clinical Research in Medicine, 2017, 34 ( 1): 79-81. 

[14] Yu Yabo, Cong Zhanjie. Association between ECOG score, CYFRA21-1, NSE and surgical prognosis in elderly non-small cell lung cancer[J]. Journal of Clinical and Experimental Pathology, 2017, 33( 7) : 806-809.

[15] Qin Yuanjing, Wang Xuemei, Tong Yanna, et al. Association between elevated serum markers of tumors and brain metastasis in patients with non-small cell lung cancer[J]. Chinese Journal of Health and Medicine, 2020, 22( 2) : 194-196. 

[16] Christiaans M H , Kelder J C , Arnoldus E , et al. Prediction of intracranial metastases in cancer patients with headache[J]. Cancer, 2010, 94(7).

[17] Zuo Chunjian. Construction and validation of risk prediction model for pathogenesis and prognosis of lung cancer brain metastasis[D]. Chongqing Medical University, 2021.

[18] Hu N , Wang G , Wu Y H , et al. LDA-SVM-Based EGFR Mutation Model for NSCLC Brain Metastases[J]. Medicine, 2015, 94(5):e375.

[19] Wang BX, Ou W, Mao XY, et al. Impacts of EGFR mutation and EGFR-TKIs on incidence of brain metastases in advanced non-squamous NSCLC [J]. Clin Neurol Neurosurg, 2017, 160:96-100. 

[20] Fujita Y, Kinoshita M, Ozaki T, et al. The impact of EGFR mutation status and single brain metastasis on the survival of non-small-cell lung cancer patients with brain metastases [J]. Neurooncol Adv, 2020, 2(1):a64. 

[21] Ge M, Zhuang Y, Zhou X, et al. High probability and frequency of EGFR mutations in non-small cell lung cancer with brain metastases [J]. J Neurooncol, 2017, 135(2):413- 418.

[22] Yang Liu, Yongsen Jia, Lijuan Qin. Role of microRNA-155 in brain metastasis of hypoxic lung cancer [J]. Journal of Sichuan University(Medical Sciences), 2019, 50(6): 835-839.

[23] Wei L, Wang G, Yang C, et al. MicroRNA-550a-3-5p controls the brain metastasis of lung cancer by directly targeting YAP1 [J]. Cancer Cell Int, 2021, 21(1):491.

[24] Wei C, Zhang R, Cai Q, etal. MicroRNA-330-3p promotes brain metastasis and epithelial- mesenchymal transition via GRIA3 in non-small cell lung cancer [J]. Aging(Albany NY), 2019, 11(17):6734-6761. 

[25] Jiang W, Hou L, Wei J, et al. Hsa-miR-217 Inhibits the Proliferation, Migration, and Invasion in Non-small Cell Lung Cancer Cells Via Targeting SIRT1 and P53/KAI1 Signaling [J]. Balkan Med J, 2020, 37(1):208-214.

[26] Dai L, Li YH, Liang YY, et al. High expression of cell adhesion molecule 2 unfavorably impacts survival in nonsmall cell lung cancer patients with brain metastases [J]. J Thorac Dis, 2021, 13(4): 2437-2446.

[27] Shi Fuyan. Research on risk factors measurement and risk level assessment methods for common chronic diseases [D]. Fourth Military Medical University, 2015.

[28] An Yang, Li Chunsun, Zhao Wei. Validation of three lung cancer risk prediction models in patients with pulmonary nodules[J]. Academic Journal of Chinese PLA Medical School, 2020, 41(12): 1193-1196+1225.

[29] Zhao Fangchao, Wang Weijian, Liu Jianming. Risk model construction and prediction ability of recurrence and metastasis after surgery for non-small cell lung cancer[J]. Cancer Prevention and Treatment Research, 2020, 47(4):5.

[30] Jin Yanwen. Establishment and analysis of knowledge base of cancer risk prediction model[D]. Soochow University, 2019.

[31] Karel, G.M, Moons, et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration [J]. Annals of Internal Medicine, 2015.162(1): W1-73.

[32] Sun Yiyuan, Ding Guangcheng, Chen Xin, et al. Application of Nomo scoring model for brain metastasis risk prediction of non-small cell lung cancer[J]. Journal of Clinical Oncology, 2019, 24(10):5.

[33] Xie Songxi, Chen Ming, Huang Yujuan, et al. Establishment and application of protein spectroscopy diagnostic model of cerebrospinal fluid for brain metastases of non-small cell lung cancer [J]. Chinese Journal of Cancer Prevention and Treatment, 2009, 16(20):5.

[34] Tian Jianbo, Miao Xiaoping, Lin Dongxin. Research Progress on Genetic Risk Prediction Model for Common Malignant Tumors in Chinese Groups [J]. Bioindustrial Technology, 2016(6):6.