Fernandez-Teijeiro Ana, Betensky Rebecca A, Sturla Lisa M, Kim John Y H, Tamayo Pablo, Pomeroy Scott L
Division of Neuroscience, Department of Neurology, Department of Medicine, Children's Hospital, 300 Longwood Ave, Boston MA 02115, USA.
J Clin Oncol. 2004 Mar 15;22(6):994-8. doi: 10.1200/JCO.2004.03.036. Epub 2004 Feb 17.
Stratification of risk in patients with medulloblastoma remains a challenge. As clinical parameters have been proven insufficient for accurately defining disease risk, molecular markers have become the focus of interest. Outcome predictions on the basis of microarray gene expression profiles have been the most accurate to date. We ask in a multivariate model whether clinical parameters enhance survival predictions of gene expression profiles.
In a cohort of 55 young patients (whose medulloblastoma samples have been analyzed previously for gene expression profile), associations between clinical and gene expression variables and survival were assessed using Cox proportional hazards models. Available clinical variables included age, stage (ie, the presence of disseminated disease at diagnosis), sex, histologic subtype, treatment, and status.
Univariate analysis demonstrated expression profiles to be the only significant clinical prognostic factor (P=.03). In multivariate analysis, gene expression profiles predicted outcome independent of other criteria. Clinical criteria did not significantly contribute additional information for outcome predictions, although an exploratory analysis noted a trend for decreased survival of patients with metastases at diagnosis but favorable gene expression profile.
Gene expression profiling predicts medulloblastoma outcome independent of clinical variables. These results need to be validated in a larger prospective study.
髓母细胞瘤患者的风险分层仍然是一项挑战。由于临床参数已被证明不足以准确界定疾病风险，分子标志物已成为关注焦点。基于微阵列基因表达谱的预后预测是迄今为止最准确的。我们在一个多变量模型中探讨临床参数是否能增强基因表达谱对生存的预测能力。
在一个由55名年轻患者组成的队列中（其髓母细胞瘤样本先前已进行基因表达谱分析），使用Cox比例风险模型评估临床和基因表达变量与生存之间的关联。可用的临床变量包括年龄、分期（即诊断时是否存在播散性疾病）、性别、组织学亚型、治疗及状态。
单变量分析表明表达谱是唯一显著的临床预后因素（P = 0.03）。在多变量分析中，基因表达谱可独立于其他标准预测预后。临床标准并未为预后预测显著提供额外信息，尽管一项探索性分析指出，诊断时有转移但基因表达谱良好的患者生存有降低趋势。
基因表达谱可独立于临床变量预测髓母细胞瘤预后。这些结果需要在更大规模的前瞻性研究中得到验证。
