AUTHOR=Yin Mengchen , Guan Sisi , Ding Xing , Zhuang Ruoyu , Sun Zhengwang , Wang Tao , Zheng Jiale , Li Lin , Gao Xin , Wei Haifeng , Ma Junming , Huang Quan , Xiao Jianru , Mo Wen 

TITLE=Construction and validation of a novel web-based nomogram for patients with lung cancer with bone metastasis: A real-world analysis based on the SEER database

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1075217

DOI=10.3389/fonc.2022.1075217

ISSN=2234-943X

ABSTRACT=Purpose: The lung cancer patients with bone metastasis often have a very poor prognosis. The purpose of this study was to characterize the prevalence, associated factors and develop a prognostic nomogram to predict the overall survival (OS) and cancer specific survival (CSS) for lung cancer patients with bone metastasis (LCBM) using multicenter population-based data.
Methods: Patients with LCBM at the time of diagnosis were identified using the Surveillance, Epidemiology and End Result (SEER) database of the National Cancer Institute from 2010 to 2015. Multivariable and univariate logistic regression was performed to identify factors associated with all-cause mortality and lung cancer-specific mortality. The performance of nomograms was evaluated with the calibration curves, area under the curve (AUC), and decision curve analysis (DCA). Kaplan-Meier analysis and log-rank tests were used to estimate the survival times of LCBM patients.
Results: We finally identified 26367 LC patients with BM who were selected for survival analysis. Multivariate analysis demonstrated age, sex, T stage, N stage, grade, histology, radiation therapy, chemotherapy, primary site, primary surgery, liver metastasis and brain metastasis as independent predictors for LCBM. In the training cohorts, AUC values of the nomogram for the prediction of OS were 0.755, 0.746, and 0.775; 0.757, 0.763 and 0.765 in the internal validation; 0.769, 0.781 and 0.867 in the external validation cohorts. For CSS, the values were 0.753, 0.753, and 0.757 in the training cohorts; 0.753, 0.753, and 0.757 in the internal validation cohorts; 0.767, 0.774, and 0.872 in the external validation cohorts.
Conclusions: Our study constructs new prognostic model and clearly presents the clinicopathological features and survival analysis of patients with LCBM. The result indicated that the nomogram had favorable discrimination, good consistency and clinical benefits in patients. In addition, our constructed nomogram prediction models may assist physicians in evaluating the individualized prognosis and deciding on treatment for patients.