Chen Haibin, Sun Liang, Yang Zhi, Qu Yuanyuan, Tong Nanyang, Sun Caixing, Xia Liang
Postgraduate Training Base Alliance of Wenzhou Medical University (PTBAWMU), Wenzhou, China.
Department of Neurosurgery, Affiliated Hospital of Jinggangshan University, Ji'an, China.
Clin Med Insights Oncol. 2024 Dec 11;18:11795549241304532. doi: 10.1177/11795549241304532. eCollection 2024.
Brain metastases are crucial in cancer progression, requiring focused efforts on the screening, early detection, and treatment. However, accurate forecasting the postoperative prognosis of patients with non-small cell lung cancer brain metastasis remains a challenge. This retrospective study aims to discern the factors that influence the prognosis of such patients.
A total of 151 cases from Zhejiang Cancer Hospital were collected. Univariate analysis was conducted using Kaplan-Meier and Log-rank test, while multivariate analysis was performed using Cox proportional hazards regression model. Student's t-test and chi-square test were employed to examine the differences between the long-term survival and the short-term survival groups. Ultimately, a predictive model was constructed using R 4.2.1.
Univariate analysis identified 12 factors as prognostic factors, showing statistical significance. In multivariate analysis, the primary contributing factors to survival were identified as age, chemotherapy of brain metastases, pathology, surgery of nonsmall cell lung cancer, targeted drugs, and GPA score. Comparing long-term and short-term groups, age, pathology, surgery of lung, targeted therapy, and radiotherapy of brain metastases were statistically differentiating factors. Based on multivariate analysis, we established a clinical predictive model predicting 2-year, 3-year, and 5-year survival rates.
Younger age, receiving chemotherapy for brain metastases, adenocarcinoma pathology, lung cancer surgery, targeted therapy, and a high GPA score are associated with longer survival. This model predicts the survival period for patients with non-small cell lung cancer brain metastasis after surgery and helps in selecting more effective treatment plans.
脑转移在癌症进展中至关重要，需要集中精力进行筛查、早期检测和治疗。然而，准确预测非小细胞肺癌脑转移患者的术后预后仍然是一项挑战。本回顾性研究旨在识别影响此类患者预后的因素。
收集了来自浙江省肿瘤医院的151例病例。采用Kaplan-Meier法和Log-rank检验进行单因素分析，使用Cox比例风险回归模型进行多因素分析。采用Student's t检验和卡方检验来检验长期生存组和短期生存组之间的差异。最终，使用R 4.2.1构建了一个预测模型。
单因素分析确定了12个因素为预后因素，具有统计学意义。在多因素分析中，确定生存的主要影响因素为年龄、脑转移化疗、病理、非小细胞肺癌手术、靶向药物和GPA评分。比较长期和短期组，年龄、病理、肺部手术、靶向治疗和脑转移放疗是具有统计学差异的因素。基于多因素分析，我们建立了一个临床预测模型，用于预测2年、3年和5年生存率。
年龄较小、接受脑转移化疗、腺癌病理、肺癌手术、靶向治疗和高GPA评分与更长的生存期相关。该模型可预测非小细胞肺癌脑转移患者术后的生存期，并有助于选择更有效的治疗方案。
