Department of Radiotherapy, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, 230022, China.
Department of Nuclear Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, 230022, China.
Sci Rep. 2018 Apr 4;8(1):5670. doi: 10.1038/s41598-018-23946-7.
Using random survival forest, this study was intended to evaluate the prognostic value of serum markers for lung adenocarcinoma patients with brain metastasis (BM), and tried to integrate them into a prognostic model. During 2010 to 2015, the patients were retrieved from two medical centers. Besides the Cox proportional hazards regression, the random survival forest (RSF) were also used to develop prognostic model from the group A (n = 142). In RSF of the group A, the factors, whose minimal depth were greater than the depth threshold or had a negative variable importance (VIMP), were firstly excluded. Subsequently, C-index and Akaike information criterion (AIC) were used to guide us finding models with higher prognostic ability and lower overfitting possibility. These RSF models, together with the Cox, modified-RPA and lung-GPA index were validated and compared, especially in the group B (CAMS, n = 53). Our data indicated that the KSE125 model (KPS, smoking, EGFR-20 (exon 18, 19 and 21) and Ca125) was the best in survival prediction, and performed well in internal and external validation. In conclusions, for lung adenocarcinoma patients with brain metastasis, a validated prognostic nomogram (KPS, smoking, EGFR-20 and Ca125) can more accurately predict 1-year and 2-year survival of the patients.
本研究采用随机生存森林（random survival forest，RSF）评估脑转移（brain metastasis，BM）肺腺癌患者的血清标志物的预后价值，并尝试将其整合到一个预后模型中。2010 年至 2015 年，从两个医疗中心中检索到患者。除 Cox 比例风险回归外，还使用随机生存森林（RSF）从组 A（n=142）中开发预后模型。在组 A 的 RSF 中，首先排除最小深度大于深度阈值或具有负变量重要性（VIMP）的因素。随后，C 指数和赤池信息量准则（Akaike information criterion，AIC）用于指导我们寻找具有更高预后能力和更低过拟合可能性的模型。这些 RSF 模型与 Cox、改良-RPA 和肺-GPA 指数一起进行了验证和比较，特别是在组 B（CAMS，n=53）中。我们的数据表明，KSE125 模型（KPS、吸烟、EGFR-20（外显子 18、19 和 21）和 Ca125）在生存预测方面表现最佳，内部和外部验证均表现良好。总之，对于脑转移的肺腺癌患者，验证后的预后列线图（KPS、吸烟、EGFR-20 和 Ca125）可以更准确地预测患者的 1 年和 2 年生存率。
