Development and Validation of a Prognostic Nomogram for Lung Adenocarcinoma: A Population-Based Study

Author:

Xie Bin12ORCID,Chen Xi3,Deng Qi4ORCID,Shi Ke15,Xiao Jian12ORCID,Zou Yong6,Yang Baishuang12ORCID,Guan Anqi12,Yang Shasha12,Dai Ziyu12,Xie Huayan12,He Shuya7,Chen Qiong12ORCID

Affiliation:

1. National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China

2. Department of Geriatrics,Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China

3. Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha 410008, China

4. Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China

5. Department of Geriatrics, Xiangya Hospital, Central South University, Changsha 410008, China

6. Department of Emergency Medicine, Xiangya Hospital, Central South University, Changsha 410008, China

7. Institute of Biochemistry and Molecular Biology, Hengyang Medical College, University of South China, Hengyang 421001, China

Abstract

Purpose. To establish an effective and accurate prognostic nomogram for lung adenocarcinoma (LUAD). Patients and Methods. 62,355 LUAD patients from 1975 to 2016 enrolled in the Surveillance, Epidemiology, and End Results (SEER) database were randomly and equally divided into the training cohort (n = 31,179) and the validation cohort (n = 31,176). Univariate and multivariate Cox regression analyses screened the predictive effects of each variable on survival. The concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were used to examine and validate the predictive accuracy of the nomogram. Kaplan–Meier curves were used to estimate overall survival (OS). Results. 10 prognostic factors associated with OS were identified, including age, sex, race, marital status, American Joint Committee on Cancer (AJCC) TNM stage, tumor size, grade, and primary site. A nomogram was established based on these results. C-indexes of the nomogram model reached 0.777 (95% confidence interval (CI), 0.773 to 0.781) and 0.779 (95% CI, 0.775 to 0.783) in the training and validation cohorts, respectively. The calibration curves were well-fitted for both cohorts. The AUC for the 3- and 5-year OS presented great prognostic accuracy in the training cohort (AUC = 0.832 and 0.827, respectively) and validation cohort (AUC = 0.835 and 0.828, respectively). The Kaplan–Meier curves presented significant differences in OS among the groups. Conclusion. The nomogram allows accurate and comprehensive prognostic prediction for patients with LUAD.

Funder

National Multidisciplinary Cooperative Diagnosis and Treatment Capacity Building Project for Major Diseases

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

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