Pan Hui, Shi Xiaoshun, Xiao Dakai, He Jiaxi, Zhang Yalei, Liang Wenhua, Zhao Zhi, Guo Zhihua, Zou Xusen, Zhang Jinxin, He Jianxing
Department of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China.
Guangzhou Institute of Respiratory Disease, Guangzhou 510120, China.
J Thorac Dis. 2017 Mar;9(3):507-518. doi: 10.21037/jtd.2017.03.121.
Small cell lung cancer (SCLC) is a subtype of lung cancer with poor prognosis. In this study, we aimed to build a nomogram to predict the survival of individual with SCLC by incorporating significant clinical parameters.
The patients with SCLC were enrolled from the First Affiliated Hospital of Guangzhou Medical University (GMUFAH) between 2009 and 2013. We identified and incorporated the independent prognostic factors to build a nomogram to predict the survival of SCLC patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve. We also compared the accuracy of the built model with the 7 AJCC TNM and VALSG staging system. The nomogram was further validated in an independent cohort of 80 patients with SCLC from Cancer Center of Guangzhou Medical University (GMUCC) between 2009 and 2013.
A total of 275 patients with SCLC were included in the primary cohort, and seven independent prognostic factors were identified including age, N stage, metastasis status, histology, platelets to lymphocyte ratio (PLR), neuron specific enolase (NSE) and CYFRA21-1 as independent prognostic factors after using Cox regression model. A nomogram incorporating these prognostic factors was subsequently built. The calibration curves for possibilities of 1-, 2-year overall survival (OS) revealed optimal agreement between nomogram prediction and actual observation. The C-index of this nomogram was higher than that of TNM and VALSG staging system in both primary and validation cohort (nomogram TNM, primary cohort 0.68 0.65, P<0.01, validation cohort 0.66 0.62, P<0.05; nomogram VALSG, primary cohort 0.68 0.66, P<0.01, validation cohort 0.66 0.64, P<0.05).
In this study, we established and validated a novel nomogram for the prediction of OS for the patients with SCLC. This model could provide more accurate individual prediction of survival probability of SCLC than the existing staging systems.
小细胞肺癌（SCLC）是肺癌的一种亚型，预后较差。在本研究中，我们旨在通过纳入显著的临床参数构建一个列线图，以预测SCLC患者的生存情况。
2009年至2013年间，从广州医科大学附属第一医院（GMUFAH）招募SCLC患者。我们识别并纳入独立的预后因素来构建列线图，以预测SCLC患者的生存情况。通过一致性指数（C指数）和校准曲线评估列线图的预测准确性和鉴别能力。我们还将构建模型的准确性与7版美国癌症联合委员会（AJCC）TNM分期系统和退伍军人肺癌研究组（VALSG）分期系统进行比较。该列线图在2009年至2013年间来自广州医科大学癌症中心（GMUCC）的80例SCLC独立队列患者中进一步验证。
在初始队列中总共纳入了275例SCLC患者，使用Cox回归模型后，确定了7个独立的预后因素，包括年龄、N分期、转移状态、组织学类型、血小板与淋巴细胞比值（PLR）、神经元特异性烯醇化酶（NSE）和细胞角蛋白19片段（CYFRA21-1）作为独立预后因素。随后构建了包含这些预后因素的列线图。1年、2年总生存（OS）概率的校准曲线显示列线图预测与实际观察之间具有最佳一致性。在初始队列和验证队列中，该列线图的C指数均高于TNM分期系统和VALSG分期系统（列线图对比TNM分期系统，初始队列：0.68对0.65，P<0.01，验证队列：0.66对0.62，P<0.05；列线图对比VALSG分期系统，初始队列：0.68对0.66，P<0.01，验证队列：0.66对0.64，P<0.05）。
在本研究中，我们建立并验证了一种用于预测SCLC患者OS的新型列线图。该模型能够比现有分期系统更准确地对SCLC患者的生存概率进行个体预测。
