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Predictive model for survival outcomes in rare primary glandular diffuse large B-cell lymphoma
Jun Lu1, Chengtong Liang2, Xijun Zhu1
1Department of Hematology, Xuancheng People's Hospital, Xuancheng, Anhui, China.
Medicine
|May 19, 2026
Summary
This study developed a predictive model for rare primary glandular diffuse large B-cell lymphoma (PG-DLBCL). Tumor location significantly impacts survival, aiding personalized treatment for PG-DLBCL patients.
Area of Science:
- Oncology
- Hematology
- Cancer Epidemiology
Background:
- Primary glandular diffuse large B-cell lymphoma (PG-DLBCL) is an exceptionally rare malignancy.
- Prognostic factors for PG-DLBCL are not well-defined, necessitating further research.
Purpose of the Study:
- To develop and validate a predictive model for overall survival (OS) and cancer-specific survival (CSS) in patients with PG-DLBCL.
- To identify key prognostic factors influencing survival outcomes in this rare cancer subgroup.
Main Methods:
- Utilized the Surveillance, Epidemiology, and End Results (SEER) database for patient data.
- Randomly split data into training (70%) and validation (30%) sets.
- Developed Cox regression-based nomograms to predict OS and CSS, validated for accuracy.
Main Results:
- Identified age, Ann Arbor stage, tumor site, and treatment as key prognostic factors.
- Demonstrated significantly higher OS rates for primary thyroid DLBCL compared to primary adrenal DLBCL.
- Nomograms showed strong predictive accuracy with C-indices of 0.75 for OS and 0.77 for CSS.
Conclusions:
- The developed predictive model effectively assesses risk for PG-DLBCL patients.
- Tumor location is a critical prognostic factor in PG-DLBCL.
- The model enables healthcare professionals to evaluate survival probabilities and tailor treatment strategies.
