An independently validated survival nomogram for lower-grade glioma
An independently validated survival nomogram for lower-grade glioma
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DOI：
10.1093/neuonc/noz191
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发表时间：
2020-05-01
期刊：
影响因子：
15.9
通讯作者：
Barnholtz-Sloan, Jill S.
中科院分区：
文献类型：
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作者：
Gittleman, Haley;Sloan, Andrew E.;Barnholtz-Sloan, Jill S.
背景胶质瘤是最常见的原发性恶性脑肿瘤。弥漫性低级别和中等级别神经胶质瘤共同构成低级别神经胶质瘤（LGG;世界卫生组织[WHO] II级和III级），由于其临床行为的异质性，对医生提出了治疗挑战。列线图是个体化估计生存的有用工具。本研究旨在开发和独立验证新诊断LOG患者的生存列线图。从癌症基因组图谱（TCGA）和俄亥俄州脑肿瘤研究（OBTS）中获得新诊断的LGG患者的数据，包括以下变量：肿瘤分级（II或III）、诊断时的年龄、性别、Karnofsky体能状态（KPS）和分子亚型（IDH突变体伴1 p/19 q共缺失[IDHmut-codel]、IDH突变体不伴1 p/19 q共缺失和IDH野生型）。采用考克斯比例风险回归、随机生存森林和递归分割分析评估生存率，并对已知的预后因素进行调整。这些模型是使用TCGA数据开发的，并使用OBTS数据进行了独立验证。使用10倍交叉验证对模型进行内部验证，并使用校准曲线进行外部验证。最后的列线图验证新诊断的LGG。提高生存率的因素包括II级肿瘤、诊断时年龄较小、KPS评分较高和IDHmut-codel分子亚型。一个诺模图，计算个体化的生存概率，新诊断的乳腺癌患者可能是有用的医疗保健提供者咨询患者的治疗决策和优化治疗方法。免费的在线软件可以实现这个诺模图：https：//hgittleman。shinyapps.io/LGG_Nomogram_H_Gittleman/.
Background. Gliomas are the most common primary malignant brain tumor. Diffuse low-grade and intermediate-grade gliomas, which together compose the lower-grade gliomas (LGGs; World Health Organization [WHO] grades II and Ill), present a therapeutic challenge to physicians due to the heterogeneity of their clinical behavior. Nomograms are useful tools for individualized estimation of survival. This study aimed to develop and independently validate a survival nomogram for patients with newly diagnosed LOG.Methods. Data were obtained for newly diagnosed LGG patients from The Cancer Genome Atlas (TCGA) and the Ohio BrainTumor Study (OBTS) with the following variables: tumor grade (II or III), age at diagnosis, sex, Karnofsky performance status (KPS), and molecular subtype (IDH mutant with 1p/19q codeletion [IDHmut-codel], IDH mutant without 1p/19q codeletion, and IDH wild-type). Survival was assessed using Cox proportional hazards regression, random survival forests, and recursive partitioning analysis, with adjustment for known prognostic factors. The models were developed using TCGA data and independently validated using the OBTS data. Models were internally validated using 10-fold cross-validation and externally validated with calibration curves.Results. A final nomogram was validated for newly diagnosed LGG. Factors that increased the probability of survival included grade II tumor, younger age at diagnosis, having a high KPS, and the IDHmut-codel molecular subtype.Conclusions. A nomogram that calculates individualized survival probabilities for patients with newly diagnosed LOG could be useful to health care providers for counseling patients regarding treatment decisions and optimizing therapeutic approaches. Free online software for implementing this nomogram is provided: https://hgittleman. shinyapps.io/LGG_Nomogram_H_Gittleman/.