A Nomogram for Predicting Survival in Advanced Non-Small-Cell Lung Carcinoma Patients: A Population-Based Study

Abstract

Non-small-cell lung cancer (NSCLC) remains the most common malignant cancer. We identified 43140 advanced NSCLC patients from the SEER database to develop and validate a new prognostic model. The prognostic performance was evaluated by P value, concordance index, net reclassification index, integrated discrimination improvement, and decision curve analysis. The following variables were contained in the final prognostic model: age, sex, race, TNM stage, and grade and treatment options. Compared to the AJCC staging system, this prognostic model is conducive to the implementation of individualized clinical treatment schemes and can be an important part of the precise medical care of NSCLC tumors.

Keywords:

• Advanced non-small-cell lung cancer
• prognostic factors
• nomogram
• survival prediction
• SEER database

Acknowledgment

We are thankful for the contribution of the SEER database and the 18 registries supplying cancer research information.

Ethics statement

All data from the SEER database was free, and this study was approved by the Institutional Research Committee of the First Affiliated Hospital of Xi’an Jiaotong University.

Author contributions

(I) Conception and design: Siying Chen, Haisheng You, Yalin Dong; (II) Administrative support: Siying Chen, Haisheng You, Yalin Dong; (III) Provision of study materials or patients: Bo Yang, Meng Teng; (IV) Collection and assembly of data: Bo Yang; (V) Data analysis and interpretation: Bo Yang; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Declaration of Interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.

Data availability statement

The datasets presented in this study can be found in the SEER database (2010–2015).

Additional information

Funding

This work was supported by grants from the Science and Technology Development of Shaanxi Province, China [No. 2020SF-210], Clinical Research Award of the First Affiliated Hospital of Xi’an Jiaotong University, China [No. XJTU1AF-CRF-2019-006], and Institutional Foundation of the First Affiliated Hospital of Xi’an Jiaotong University, China [No. 2019QN-25].