Development and validation of a prognostic model of resectable small-cell lung cancer: a large population-based cohort study and external validation

Author:

Wang Yu,Pang Zhaofei,Chen Xiaowei,Yan Tao,Liu Jichang,Du Jiajun

Abstract

Abstract Background Survival outcomes of patients with resected SCLC differ widely. The aim of our study was to build a model for individualized risk assessment and accurate prediction of overall survival (OS) in resectable SCLC patients. Methods We collected 1052 patients with resected SCLC from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were selected by COX regression analyses, based on which a nomogram was constructed by R code. External validation were performed in 114 patients from Shandong Provincial Hospital. We conducted comparison between the new model and the AJCC staging system. Kaplan–Meier survival analyses were applied to test the application of the risk stratification system. Results Sex, age, T stage, N stage, LNR, surgery and chemotherapy were identified to be independent predictors of OS, according which a nomogram was built. Concordance index (C-index) of the training cohort were 0.721, 0.708, 0.726 for 1-, 3- and 5-year OS, respectively. And that in the validation cohort were 0.819, 0.656, 0.708, respectively. Calibration curves also showed great prediction accuracy. In comparison with 8th AJCC staging system, improved net benefits in decision curve analyses (DCA) and evaluated integrated discrimination improvement (IDI) were obtained. The risk stratification system can significantly distinguish the ones with different survival risk. We implemented the nomogram in a user-friendly webserver. Conclusions We built a novel nomogram and risk stratification system integrating clinicopathological characteristics and surgical procedure for resectable SCLC. The model showed superior prediction ability for resectable SCLC.

Funder

National Natural Science Foundation of China

Shandong Province Key R & D Plan

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3