Knoll Miriam A, Oermann Eric K, Yang Andrew I, Paydar Ima, Steinberger Jeremy, Collins Brian, Collins Sean, Ewend Matthew, Kondziolka Douglas
Department of Radiation Oncology.
Neurological Surgery, Mount Sinai Health System.
Am J Clin Oncol. 2018 May;41(5):425-431. doi: 10.1097/COC.0000000000000299.
Defining prognostic factors is a crucial initial step for determining the management of patients with brain metastases. Randomized trials assessing radiosurgery have commonly limited inclusion criteria to 1 to 4 brain metastases, in part due to multiple retrospective studies reporting on the number of brain metastases as a prognostic indicator. The present study reports on the survival of patients with 1 to 4 versus ≥5 brain metastases treated with radiosurgery.
We evaluated a retrospective multi-institutional database of 1523 brain metastases in 507 patients who were treated with radiosurgery (Gamma Knife or Cyberknife) between 2001 and 2014. A total of 243 patients were included in the analysis. Patients with 1 to 4 brain metastases were compared with patients with ≥5 brain metastases using a standard statistical analysis. Cox hazard regression was used to construct a multivariable model of overall survival (OS). To find covariates that best separate the data at each split, a machine learning technique Chi-squared Automated Interaction Detection tree was utilized.
On Pearson correlation, systemic disease status, number of intracranial metastases, and overall burden of disease (number of major involved organ systems) were found to be highly correlated (P<0.001). Patients with 1 to 4 metastases had a median OS of 10.8 months (95% confidence interval, 6.1-15.6 mo), compared with a median OS of 8.5 months (95% confidence interval, 4.4-12.6 mo) for patients with ≥5 metastases (P=0.143). The actuarial 6 month local failure rate was 5% for patients with 1 to 4 metastases versus 3.2% for patients with ≥5 metastases (P=0.404). There was a significant difference in systemic disease status between the 2 groups; 30% of patients had controlled systemic disease in the <5 lesions group, versus 8% controlled systemic disease in the ≥5 lesions group (P=0.005). Patients with 1 to 4 metastases did not have significantly improved OS in a multivariable model adjusting for systemic disease status, systemic extracranial metastases, and other key variables. The Chi-squared Automated Interaction Detection tree (machine learning technique) algorithm consistently identified performance status and systemic disease status as key to disease classification, but not intracranial metastases.
Although the number of brain metastases has previously been accepted as an independent prognostic indicator, our multicenter analysis demonstrates that the number of intracranial metastases is highly correlated with overall disease burden and clinical status. Proper matching and controlling for these other determinants of survival demonstrates that the number of intracranial metastases alone is not an independent predictive factor, but rather a surrogate for other clinical factors.
确定预后因素是决定脑转移瘤患者治疗方案的关键初始步骤。评估放射外科手术的随机试验通常将纳入标准限制为1至4个脑转移瘤，部分原因是多项回顾性研究报告脑转移瘤数量是一个预后指标。本研究报告了接受放射外科手术治疗的1至4个脑转移瘤患者与≥5个脑转移瘤患者的生存情况。
我们评估了一个回顾性多机构数据库，该数据库包含2001年至2014年间接受放射外科手术（伽玛刀或赛博刀）治疗的507例患者的1523个脑转移瘤。共有243例患者纳入分析。使用标准统计分析比较1至4个脑转移瘤患者与≥5个脑转移瘤患者。采用Cox风险回归构建总生存（OS）的多变量模型。为了找到在每次分割时能最佳分离数据的协变量，采用了一种机器学习技术——卡方自动交互检测树。
经Pearson相关性分析，全身疾病状态、颅内转移瘤数量和疾病总负担（主要受累器官系统数量）高度相关（P<0.001）。1至4个转移瘤患者的中位OS为10.8个月（95%置信区间，6.1 - 15.6个月），而≥5个转移瘤患者的中位OS为8.5个月（95%置信区间，4.4 - 12.6个月）（P = 0.143）。1至4个转移瘤患者的6个月精算局部失败率为5%，≥5个转移瘤患者为3.2%（P = 0.404）。两组患者的全身疾病状态存在显著差异；<5个病灶组30%的患者全身疾病得到控制，≥5个病灶组为8%（P = 0.005）。在对全身疾病状态、全身颅外转移瘤和其他关键变量进行调整的多变量模型中，1至4个转移瘤患者的OS并未显著改善。卡方自动交互检测树（机器学习技术）算法始终将性能状态和全身疾病状态确定为疾病分类的关键因素，而非颅内转移瘤数量。
尽管脑转移瘤数量此前一直被视为独立的预后指标，但我们的多中心分析表明，颅内转移瘤数量与疾病总负担和临床状态高度相关。对这些其他生存决定因素进行适当匹配和控制表明，仅颅内转移瘤数量并非独立的预测因素，而是其他临床因素的替代指标。
