Related Experiment Video
Updated: Jul 17, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a survival nomogram in patients with primary testicular diffuse large B-cell lymphoma
Yongjin Zhi1, Shuojing Bao2, Jingcheng Mao1
1Department of Hematology, Taizhou People's Hospital affiliated to Nanjing Medical University, Taizhou, Jiangsu Province, China.
Objective:
We developed and validated a nomogram for overall survival (OS) and cancer-specific survival (CSS) prediction in patients with primary testicular diffuse large B-cell lymphoma (PT-DLBCL).
Methods:
Patients diagnosed with PT-DLBCL were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were analyzed to establish a nomogram of OS and CSS. Patients were reclassified into high- and low-risk groups; survival was compared using Kaplan-Meier curves and log-rank tests.
Results:
We collected 1099 PT-DLBCL cases (2000-2019) from SEER and randomized into training (n = 771) and validation (n = 328) cohorts. In univariate and multivariate Cox regression analyses, five prognostic indicators (age, treatment modality, diagnosis year, Ann Arbor stage, laterality) were used to establish a nomogram of OS and CSS. The nomogram demonstrated excellent discrimination and calibration, with concordance indices in the training and validation cohorts of 0.702 (95% confidence interval [CI], 0.677-0.727) and 0.705 (95% CI 0.67-0.74) for OS and 0.694 (95% CI 0.663-0.725) and 0.680 (95% CI 0.63-0.72) for CSS. The calibration curve and ROC analysis indicated good predictive capability of the nomogram.
Conclusions:
The constructed prognostic model showed good predictive value for PT-DLBCL to assist clinicians in developing individualized treatment strategies.
Related Concept Videos
Cancer Survival Analysis
Comparing the Survival Analysis of Two or More Groups

