Wenhua Liang, Qiuhua Deng, Xinguo Xiong, Wenlong Shao, Xiaoshun Shi, and Jianxing He, The First Affiliated Hospital of Guangzhou Medical University; Wenhua Liang, Qiuhua Deng, Xinguo Xiong, Wenlong Shao, Xiaoshun Shi, and Jianxing He, Guangzhou Institute of Respiratory Disease and China State Key Laboratory of Respiratory Disease; Wenhua Liang, Li Zhang, and Zhihua Zhu, Cancer Center of Sun Yat-Sen University, Guangzhou; Gening Jiang, Shanghai Pulmonary Hospital of Tongji University; Qun Wang, Shanghai Zhongshan Hospital of Fudan University, Shanghai; Lunxu Liu, West China Hospital, Sichuan University, Chengdu; Deruo Liu, China and Japan Friendship Hospital, Beijing; and Zheng Wang, Shenzhen People's Hospital, Shenzhen, People's Republic of China.
J Clin Oncol. 2015 Mar 10;33(8):861-9. doi: 10.1200/JCO.2014.56.6661. Epub 2015 Jan 26.
A nomogram is a useful and convenient tool for individualized cancer prognoses. We sought to develop a clinical nomogram for predicting survival of patients with resected non-small-cell lung cancer (NSCLC).
On the basis of data from a multi-institutional registry of 6,111 patients with resected NSCLC in China, we identified and integrated significant prognostic factors for survival to build a nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort of 2,148 patients from the International Association for the Study of Lung Cancer (IASLC) database. The predictive accuracy and discriminative ability were measured by concordance index (C-index) and risk group stratification.
A total of 5,261 patients were included for analysis. Six independent prognostic factors were identified and entered into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (primary cohort, 0.71 v 0.68, respectively; P < .01; IASLC cohort, 0.67 v 0.64, respectively; P = .06). The stratification into different risk groups allowed significant distinction between survival curves within respective TNM categories.
We established and validated a novel nomogram that can provide individual prediction of OS for patients with resected NSCLC. This practical prognostic model may help clinicians in decision making and design of clinical studies.
列线图是一种用于个体化癌症预后的有用且方便的工具。我们旨在开发一种用于预测接受手术治疗的非小细胞肺癌（NSCLC）患者生存的临床列线图。
基于中国多机构登记处 6111 例接受手术治疗的 NSCLC 患者的数据，我们确定并整合了对生存有显著影响的预后因素，以构建列线图。该模型通过自举内部验证以及来自国际肺癌研究协会（IASLC）数据库的 2148 例患者的外部验证进行验证。预测准确性和区分能力通过一致性指数（C-index）和风险分组分层来衡量。
共纳入 5261 例患者进行分析。确定了 6 个独立的预后因素，并将其纳入列线图。1 年、3 年和 5 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。列线图的 C-index 高于第七版美国癌症联合委员会 TNM 分期系统（原发性队列，分别为 0.71 和 0.68，P <.01；IASLC 队列，分别为 0.67 和 0.64，P =.06）用于预测 OS。不同风险组的分层可在各自的 TNM 类别内显著区分生存曲线。
我们建立并验证了一种新的列线图，可为接受手术治疗的 NSCLC 患者提供 OS 的个体预测。这种实用的预后模型可能有助于临床医生进行决策和临床研究设计。
