非小细胞肺癌脑转移立体定向放射治疗后的个体化早期死亡和长期生存预测：两个外部验证的列线图
Individualized early death and long-term survival prediction after stereotactic radiosurgery for brain metastases of non-small cell lung cancer: Two externally validated nomograms.
作者信息
Zindler Jaap D, Jochems Arthur, Lagerwaard Frank J, Beumer Rosemarijne, Troost Esther G C, Eekers Daniëlle B P, Compter Inge, van der Toorn Peter-Paul, Essers Marion, Oei Bing, Hurkmans Coen W, Bruynzeel Anna M E, Bosmans Geert, Swinnen Ans, Leijenaar Ralph T H, Lambin Philippe
机构信息
Department of Radiation Oncology (MAASTRO Clinic), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, The Netherlands.
Department of Radiation Oncology (MAASTRO Clinic), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, The Netherlands.
出版信息
Radiother Oncol. 2017 May;123(2):189-194. doi: 10.1016/j.radonc.2017.02.006. Epub 2017 Feb 23.
INTRODUCTION
Commonly used clinical models for survival prediction after stereotactic radiosurgery (SRS) for brain metastases (BMs) are limited by the lack of individual risk scores and disproportionate prognostic groups. In this study, two nomograms were developed to overcome these limitations.
METHODS
495 patients with BMs of NSCLC treated with SRS for a limited number of BMs in four Dutch radiation oncology centers were identified and divided in a training cohort (n=214, patients treated in one hospital) and an external validation cohort n=281, patients treated in three other hospitals). Using the training cohort, nomograms were developed for prediction of early death (<3months) and long-term survival (>12months) with prognostic factors for survival. Accuracy of prediction was defined as the area under the curve (AUC) by receiver operating characteristics analysis for prediction of early death and long term survival. The accuracy of the nomograms was also tested in the external validation cohort.
RESULTS
Prognostic factors for survival were: WHO performance status, presence of extracranial metastases, age, GTV largest BM, and gender. Number of brain metastases and primary tumor control were not prognostic factors for survival. In the external validation cohort, the nomogram predicted early death statistically significantly better (p<0.05) than the unfavorable groups of the RPA, DS-GPA, GGS, SIR, and Rades 2015 (AUC=0.70 versus range AUCs=0.51-0.60 respectively). With an AUC of 0.67, the other nomogram predicted 1year survival statistically significantly better (p<0.05) than the favorable groups of four models (range AUCs=0.57-0.61), except for the SIR (AUC=0.64, p=0.34). The models are available on www.predictcancer.org.
CONCLUSION
The nomograms predicted early death and long-term survival more accurately than commonly used prognostic scores after SRS for a limited number of BMs of NSCLC. Moreover these nomograms enable individualized probability assessment and are easy into use in routine clinical practice.
引言
用于预测脑转移瘤（BM）立体定向放射外科治疗（SRS）后生存情况的常用临床模型存在局限性，缺乏个体风险评分且预后分组不均衡。在本研究中，我们开发了两个列线图以克服这些局限性。
方法
在荷兰的四个放射肿瘤中心，确定了495例因有限数量的脑转移瘤接受SRS治疗的非小细胞肺癌（NSCLC）患者，并将其分为训练队列（n = 214，在一家医院接受治疗的患者）和外部验证队列（n = 281，在其他三家医院接受治疗的患者）。利用训练队列，根据生存预后因素开发了用于预测早期死亡（<3个月）和长期生存（>12个月）的列线图。预测准确性通过受试者操作特征分析的曲线下面积（AUC）来定义，用于预测早期死亡和长期生存。列线图的准确性也在外部验证队列中进行了测试。
结果
生存的预后因素包括：世界卫生组织（WHO）功能状态、颅外转移的存在、年龄、最大脑转移瘤的靶体积（GTV）以及性别。脑转移瘤数量和原发肿瘤控制情况不是生存的预后因素。在外部验证队列中，列线图预测早期死亡的效果在统计学上显著优于递归分区分析（RPA）、剂量分割分级预后评估（DS - GPA）、GGS、放射肿瘤学会（SIR）和Rades 2015的不良组（AUC = 0.70，而相应的AUC范围为0.51 - 0.60）。另一个列线图的AUC为0.67，预测1年生存的效果在统计学上显著优于四个模型的良好组（AUC范围为0.57 - 0.61），除了SIR（AUC = 0.64，p = 0.34）。这些模型可在www.predictcancer.org上获取。
结论
对于有限数量的NSCLC脑转移瘤，列线图预测SRS后的早期死亡和长期生存比常用的预后评分更准确。此外，这些列线图能够进行个体化概率评估，并且易于在常规临床实践中使用。
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