EGFR 突变型 NSCLC 脑膜转移个体化管理风险分层模型的开发与验证 (LM-Index)
Development and validation of a risk-stratification model for individualized management of leptomeningeal metastases in EGFR- mutant NSCLC (LM-Index).
作者
作者单位
- Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Institute of Cancer Research, Henan Academy of Innovations in Medical Science, Zhengzhou, China; State Key Laboratory of Neurology and Oncology Drug Development, China; Henan International Joint Laboratory of Drug Resistance and Reversal of Targeted Therapy for Lung Cancer, China; Henan Medical Key Laboratory of Refractory Lung Cancer, China; Henan Province Engineering Technology Research Center of Refractory Lung Cancer Drug Treatment, China.
- Department of Medical Oncology, Henan Provincial Chest Hospital, Chest Hospital of Zhengzhou University, Zhengzhou, China.
- Department of Clinical Research Management, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou 450008, China.
- Department of Geriatric Oncology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
- Department of Respiratory Medicine, Nanjing Chest Hospital, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China; Brain Metastases Diagnosis and Treatment Centre, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
- Department of Thoracic Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, China.
- Comprehensive Oncology Center, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing, China.
- Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Institute of Cancer Research, Henan Academy of Innovations in Medical Science, Zhengzhou, China; State Key Laboratory of Neurology and Oncology Drug Development, China; Henan International Joint Laboratory of Drug Resistance and Reversal of Targeted Therapy for Lung Cancer, China; Henan Medical Key Laboratory of Refractory Lung Cancer, China; Henan Province Engineering Technology Research Center of Refractory Lung Cancer Drug Treatment, China. Electronic address: qimingwang1006@126.com.
摘要
中文
携带 EGFR 突变的非小细胞肺癌合并脑膜转移患者预后高度不确定,使治疗决策复杂化。本研究旨在开发并验证一种多模态风险评分,以预测总生存期 (OS) 并实现风险分层管理。本回顾性多中心研究包括推导队列 (n=350) 与独立外部验证队列 (n=302)。通过 Cox 回归筛选独立预后因素,并整合为基于整数计分的风险评分。模型性能通过 C-index、校准度及决策曲线分析进行评估。多因素分析确定 5 个较差 OS 的独立预测因素:ECOG PS ≥3、脑转移、MRI 上脑膜强化、脑脊液细胞学 (CSFC) 阳性及颅内压 >220 mmH₂O。由此构建的风险评分将患者分为低危组和高危组,中位 OS 分别为 22.6 个月和 9.9 个月 (p<0.001)。模型表现出良好的区分度,偏差校正 C-index 为 0.73。在外部验证队列中,所有因素仍具有显著性,模型性能保持一致 (C-index=0.71)。模型显示出良好的校准度和正向净获益。我们开发并验证了一种稳健、临床可行的风险评分,能够准确分层 EGFR 突变型 NSCLC 合并 LM 患者的 OS。该实用工具可促进风险分层患者咨询,并可能有助于未来临床试验设计。
English
Prognosis for patients with EGFR- mutant non-small-cell lung cancer and leptomeningeal metastasis is highly uncertain, complicating treatment decisions. We aimed to develop and validate a multimodal risk score for predicting overall survival to enable risk-stratified management. In this retrospective, multicenter study, a derivation cohort (n = 350) and an independent external validation cohort (n = 302) were used. Independent prognostic factors were identified via Cox regression and integrated into an integer-based risk score. Model performance was evaluated by the C-index, calibration, and decision curve analysis. Multivariate analysis identified five independent predictors of poorer OS: ECOG PS ≥ 3, brain metastasis, meningeal enhancement on MRI, positive Cerebrospinal Fluid cytology (CSFC) and intracranial pressure > 220 mmH2O. The resulting risk score stratified patients into low-risk and high-risk groups, with median OS of 22.6 months versus 9.9 months, respectively (p < 0.001). The model demonstrated good discrimination, with a bias-corrected C-index of 0.73. In the external validation cohort, all factors remained significant, and the model maintained consistent performance (C-index = 0.71). The model showed good calibration and positive net benefit. We developed and validated a robust, clinically accessible risk score that accurately stratifies OS in patients with EGFR- mutant NSCLC and LM. This practical tool facilitates risk‑stratified patient counseling and may aid in the design of future clinical trials.
分类与指标
- 研究类型
- 临床研究
- 病种
- 肺癌
- JCR 分区
- Q1
- 影响因子
- 5.3
- 新锐分区
- 2区