Development and Validation of a Nomogram for Predicting Survival in Patients With Resected Non–Small-Cell Lung Cancer

Author:

Liang Wenhua1,Zhang Li1,Jiang Gening1,Wang Qun1,Liu Lunxu1,Liu Deruo1,Wang Zheng1,Zhu Zhihua1,Deng Qiuhua1,Xiong Xinguo1,Shao Wenlong1,Shi Xiaoshun1,He Jianxing1

Affiliation:

1. 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...

Abstract

Purpose 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). Patients and Methods 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. Results 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. Conclusion 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.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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