ORIGINAL RESEARCH article

Front. Med.

Sec. Hematology

Volume 12 - 2025 | doi: 10.3389/fmed.2025.1572919

This article is part of the Research TopicClinical prediction models in cancer through bioinformaticsView all 6 articles

Competing risk nomogram for predicting cancer-specific survival in patients with primary bone diffuse large B-cell lymphoma: A SEER-based retrospective study

Provisionally accepted
Rongbin  ShenRongbin Shen1Sichun  XiangSichun Xiang1Jianyou  GuJianyou Gu1YU  ZHANGYU ZHANG1Lili  QianLili Qian1Jianping  ShenJianping Shen1Qing  GuoQing Guo2Shana  ChenShana Chen2Chenyang  MaChenyang Ma3*Jingjing  XiangJingjing Xiang4*
  • 1The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
  • 2International Mongolian Hospital of Inner Mongolia, Hohhot, China
  • 3Department of Traditional Chinese Medicine, The Second People's Hospital of Xiaoshan District, Hangzhou, China
  • 4Department of Hematology, First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, China

The final, formatted version of the article will be published soon.

Background: Cardiovascular death (CVD) represents a significant determinant affecting the long-term survival outcomes of cancer patients, independent of primary tumor effects. Consequently, this study aims to identify prognostic factors in patients with primary bone diffuse large B-cell lymphoma (PB-DLBCL) using CVD as a competing risk and to develop a competing risk nomogram.Methods: Data for patients diagnosed with PB-DLBCL from 2000 to 2015 were sourced from the Surveillance Epidemiology, and End Results (SEER) database and a total of 1,224 PB-DLBCL patients were eventually included in this study. The approach of multiple imputation is utilized to address the issue of missing data.Univariate Cox regression analysis and the best subset selection method are utilized for variable screening, from which overlapping independent risk factors are identified for subsequent multivariate Cox analysis and multivariate competing risk analysis.The Fine-Gray test was applied for univariate competing risk analysis. Significant variables from the multivariate competing risk analysis were selected as independent prognostic factors to construct a competing risk nomogram for predicting 1-, 5-, and 10-year cancer-specific survival (CSS). The model's performance was evaluated by Harrell concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and calibration curves.Results: Compared with the competing risk model, the conventional Cox regression model overestimates the impact of variables on the incidence of cancer-specifc death (CSD). Age, income, B symptoms, Ann Arbor stage, primary site, laterality, chemotherapy, and systemic therapy were identified as independent risk factors for CSD. A competing risk nomogram was developed incorporating these variables to predict CSS. In the training set, the areas under the curve (AUC) for 1-year, 5-year, and 10-year CSS were 0.879, 0.848, and 0.839, respectively, while in the testing set, the AUC values were 0.794, 0.781, and 0.790, respectively. The C-index of the model was 0.853, 0.823, and 0.819 for 1-, 5-, and 10-year survival in the training set, and 0.777, 0.757, and 0.754 in the testing set. The calibration curve indicated favorable consistency for the competing risk nomogram.The competing risk nomogram was effectively utilized to predict CSS in patients with PB-DLBCL It exhibited robust predictive performance and holds potential for enhancing treatment decision-making in clinical practice.

Keywords: primary bone diffuse large B-cell lymphoma, Competing risk model, Cancer-specific survival, Cardiovascular death, nomogram

Received: 07 Feb 2025; Accepted: 17 Apr 2025.

Copyright: © 2025 Shen, Xiang, Gu, ZHANG, Qian, Shen, Guo, Chen, Ma and Xiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Chenyang Ma, Department of Traditional Chinese Medicine, The Second People's Hospital of Xiaoshan District, Hangzhou, China
Jingjing Xiang, Department of Hematology, First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, China

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