Sperber Jacob, Yoo Seeley, Owolo Edwin, Dalton Tara, Zachem Tanner J, Johnson Eli, Herndon James E, Nguyen Annee D, Hockenberry Harrison, Bishop Brandon, Abu-Bonsrah Nancy, Cook Steven H, Fecci Peter E, Sperduto Paul W, Johnson Margaret O, Erickson Melissa M, Goodwin C Rory
Department of Neurosurgery, Duke University School of Medicine, Durham, North Carolina, USA.
Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA.
Neurooncol Pract. 2024 Jun 24;11(6):763-771. doi: 10.1093/nop/npae057. eCollection 2024 Dec.
Prognostic indices for patients with brain metastases (BM) are needed to individualize treatment and stratify clinical trials. Two frequently used tools to estimate survival in patients with BM are the recursive partitioning analysis (RPA) and the diagnosis-specific graded prognostic assessment (DS-GPA). Given recent advances in therapies and improved survival for patients with BM, this study aims to validate and analyze these 2 models in a modern cohort.
Patients diagnosed with BM were identified via our institution's Tumor Board meetings. Data were retrospectively collected from the date of diagnosis with BM. The concordance of the RPA and GPA was calculated using Harrell's index. A Cox proportional hazards model with backwards elimination was used to generate a parsimonious model predictive of survival.
Our study consisted of 206 patients diagnosed with BM between 2010 and 2019. The RPA had a prediction performance characterized by Harrell's index of 0.588. The DS-GPA demonstrated a Harrell's index of 0.630. A Cox proportional hazards model assessing the effect of age, presence of lung, or liver metastases, and Eastern Cooperative Oncology Group (ECOG) performance status score of 3/4 on survival yielded a Harrell's index of 0.616. Revising the analysis with an uncategorized ECOG demonstrated a index of 0.648.
We found that the performance of the RPA remains unchanged from previous validation studies a decade earlier. The DS-GPA outperformed the RPA in predicting overall survival in our modern cohort. Analyzing variables shared by the RPA and DS-GPA produced a model that performed analogously to the DS-GPA.
脑转移瘤（BM）患者的预后指标对于个体化治疗和临床试验分层至关重要。两种常用于估计BM患者生存期的工具是递归划分分析（RPA）和诊断特异性分级预后评估（DS-GPA）。鉴于BM患者治疗方面的最新进展以及生存期的改善，本研究旨在在现代队列中验证和分析这两种模型。
通过本机构的肿瘤委员会会议确定诊断为BM的患者。数据从BM诊断日期开始回顾性收集。使用Harrell指数计算RPA和GPA的一致性。采用向后逐步回归的Cox比例风险模型生成预测生存期的简约模型。
我们的研究包括2010年至2019年间诊断为BM的206例患者。RPA的预测性能以Harrell指数0.588为特征。DS-GPA的Harrell指数为0.630。评估年龄、肺或肝转移的存在以及东部肿瘤协作组（ECOG）表现状态评分为3/4对生存期影响的Cox比例风险模型的Harrell指数为0.616。用未分类的ECOG修订分析后，指数为0.648。
我们发现RPA的性能与十年前的先前验证研究相比没有变化。在我们的现代队列中，DS-GPA在预测总生存期方面优于RPA。分析RPA和DS-GPA共有的变量产生了一个与DS-GPA表现类似的模型。
