# Survival Prediction in Middle‐Aged and Elderly Patients With Burkitt Lymphoma: A Comprehensive Nomogram Approach Based on SEER Data

## TL;DR

This study creates a survival prediction tool for middle-aged and elderly Burkitt lymphoma patients using SEER data to improve risk stratification and treatment planning.

## Contribution

A novel nomogram model for predicting survival in middle-aged and elderly Burkitt lymphoma patients based on SEER data.

## Key findings

- Age, Ann Arbor stage, chemotherapy, and other factors were independently associated with overall and cancer-specific survival.
- The nomogram accurately predicted 1-, 3-, and 5-year survival probabilities for BL patients.
- Validation confirmed the model's accuracy in distinguishing survival probabilities across risk groups.

## Abstract

Burkitt lymphoma (BL) in middle‐aged and elderly populations presents unique prognostic challenges due to distinct biological behaviors and therapeutic vulnerabilities. Current prognostic tools inadequately address age‐specific survival determinants in this understudied cohort.

This study used the Surveillance, Epidemiology, and End Results (SEER) data from patients diagnosed with BL between 2000 and 2020, aged 45 years and older. Through univariate and multivariate Cox regression analyses, we identified independent prognostic factors affecting overall survival (OS) and cancer‐specific survival (CSS). Finally, nomograms were constructed, and the models were evaluated across three dimensions.

Multivariate analysis results indicated that factors such as age, race, Ann Arbor stage, and chemotherapy were independently associated with OS, while age, Ann Arbor stage, radiotherapy, chemotherapy, and number of tumor masses were independently associated with CSS. The nomogram model effectively predicted the 1‐, 3‐, and 5‐year probabilities of OS and CSS. The results from receiver operating characteristic curves, calibration curves, and decision curve analysis in the training and validation groups confirmed that the risk prediction nomogram could accurately predict the survival of BL patients.

The nomogram model constructed in this study provides a personalized survival prediction tool for BL patients, effectively distinguishing the survival probabilities of different risk groups. This research offers new insights for risk stratification and treatment management of middle‐aged and elderly BL patients.