Construction of a nomogram predicting the overall survival of patients with distantly metastatic non-small-cell lung cancer

构建预测远处转移性非小细胞肺癌患者总生存期的列线图

阅读:1

Abstract

PURPOSE: This study aimed to establish a nomogram to predict the overall survival (OS) of the general non-small-cell lung cancer (NSCLC) patients with distant metastasis. PATIENTS AND METHODS: We investigated Surveillance, Epidemiology, and End Results database for NSCLC patients with distant metastasis diagnosed between 2010 and 2014. Statistically significant prognostic factors were identified using uni- and multivariable Cox regression analyses. A nomogram incorporating these prognostic factors was developed and evaluated by the Harrell's concordance index (C-index), calibration plots, and risk group stratifications. RESULTS: We finally included 18,209 patients for analysis. These patients were divided into two groups, 14,567 cases for the training cohort and 3,642 for the validation cohort. Marital status, sex, race, age, histology, T stage, N stage, histological differentiation, bone metastasis, brain metastasis, liver metastasis, with M1a disease, surgery of primary cancer, and chemotherapy were identified as the prognostic factors of the OS and integrated to construct the nomogram. The nomogram had a C-index of 0.704 (95% CI: 0.699-0.709) in the training set and 0.699 (95% CI: 0.689-0.709) in the validation set. The calibration curves for 1- and 2-year OS in the training and validation sets showed acceptable agreement between the predicted and observed survival. Also, the nomogram was capable of stratifying patients into different risk groups within the patients who presented with bone, liver, or brain metastasis, as well as in each T, N stage, respectively. CONCLUSION: A nomogram was established and validated to predict individual prognosis for the general patients with distantly metastatic NSCLC. Global prospective data with the latest TNM classification and more comprehensive prognostic factors are needed to improve this model.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。