Nomogram-Based Prediction of Overall and Cancer-Specific Survival in Patients with Primary Bone Diffuse Large B-Cell Lymphoma: A Population-Based Study. (5th May 2022)

• Record Type: Journal Article
• Authors: Yang, Xing-yao; He, Xin; Zhao, Yun
• Other Names: Li Qing Academic Editor.
• Is Part Of: Evidence-based complementary and alternative medicine. Volume 2022(2022)
• Publication Date: 2022-05-05
• Subjects: Alternative medicine -- Periodicals; 615.505
• DOI: 10.1155/2022/1566441
• Languages: English
• ISSNs: 1741-427X

Abstract

Abstract : Background . Primary bone diffuse large B-cell lymphoma (PD-DLBCL) accounts for more than 80% of primary bone lymphoma. We created two nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with PD-DLBCL for this rare disease. Methods . In total, 891 patients diagnosed with PB-DLBCL between 2007 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to explore independent prognostic factors and create nomograms for OS and CSS. The area under the curve (AUC), the calibration curve, decision curve analysis (DCA), and Kaplan–Meier (K-M) curve analysis were used to evaluate the nomograms. Results . Four variables were identified as independent prognostic factors for OS, and three variables were identified as independent prognostic factors for CSS. The receiver operating characteristic (ROC) curves demonstrated the strong discriminatory power of the nomograms. The calibration and DCA curves showed that the nomograms had a satisfactory ability to predict OS and CSS. The K-M curves showed that age, gender, primary site, chemotherapy, and tumor stage affected patient survival. Conclusions . In patients with PD-DLBCL, age, race, primary site, and chemotherapy affected OS, while age, race, and chemotherapy affected CSS. The two nomograms created based on the aforementioned variables provided more accurate individual survival predictions for PD-DLBCL patients and can help physicians make appropriate clinical decisions.