ArticleFrontiers in oncology2020
Development and Validation of a Novel Risk Stratification Model for Cancer-Specific Survival in Diffuse Large B-Cell Lymphoma.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- A streamlined predictive model for predicting the risk of recurrence after liver transplantation for hepatocellular carcinoma was constructed based on preoperativeFrontiers in oncology · 2026Article
- Development and validation of a prognostic nomogram for diffuse large B-cell lymphoma: a multicenter cohort study from Northern China.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Development and validation of prediction model for overall survival in patients with lymphoma: a prospective cohort study in China.BMC medical informatics and decision making · 2023Article
- Article
- Development and External Validation of a Nomogram to Predict Cancer-Specific Survival in Patients with Primary Intestinal Non-Hodgkin Lymphomas.Cancer management and research · 2021Article
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2 authors.
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Abstract
Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogenous disease. Identifying more precise and individual survival prognostic models are still needed. This study aimed to develop a predictive nomogram and a web-based survival rate calculator that can dynamically predict the long-term cancer-specific survival (CSS) of DLBCL patients. A total of 3,573 eligible patients with DLBCL from 2004 to 2015 were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The entire group was randomly divided into the training (n = 2,504) and validation (n = 1,069) cohorts. We identified six independent predictors for survival including age, sex, marital status, Ann Arbor stage, B symptom, and chemotherapy, which were used to construct the nomogram and the web-based survival rate calculator. The C-index of the nomogram was 0.709 (95% CI, 0.692-0.726) in the training cohort and 0.700 (95% CI, 0.671-0.729) in the validation cohort. The AUC values of the nomogram for predicting the 1-, 5-, and 10- year CSS rates ranged from 0.704 to 0.765 in both cohorts. All calibration curves revealed optimal consistency between predicted and actual survival. A risk stratification model generated based on the nomogram showed a favorable level of predictive accuracy compared with the IPI, R-IPI, and Ann Arbor stage in both cohorts according to the AUC values (training cohort: 0.715
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