AUTHOR=Yang Ziyue , Li Zhenfen , Fu Chunmeng , Zhu Yuanyuan , Lin Ying , Deng Ying , Li Ning , Peng Fang TITLE=Development and validation of a nomogram to predict overall survival and cancer-specific survival in patients with primary intracranial malignant lymphoma: A Retrospective study based on the SEER database JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2023 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1055046 DOI=10.3389/fonc.2022.1055046 ISSN=2234-943X ABSTRACT=Introduction

Primary intracranial malignant lymphoma (PIML) is a rare form of lymphoma that most often occurs in the brain and has an extremely low 5-year survival rate. Although chemotherapy and radiotherapy are widely used in the clinical management of PIML, the choice of treatment regimen and the actual circumstances of patients remain challenges when assessing survival rates in different patients.

Methods

Considering this, we obtained clinical treatment and survival information from the Surveillance, Epidemiology, and End Results database (SEER) on patients with lymphoma, the primary site of which was the brain, and performed statistical analyses of the demographic characteristics. Survival analyses were performed using the Kaplan–Meier method, and univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic factors.

Result

We identified age, pathology, the Ann Arbor stage, and treatment as the risk factors affecting patient prognosis. The areas under the curve (AUCs) for overall survival at 1, 3, and 5 years were 0.8, 0.818, and 0.81, respectively. The AUCs for cancer-specific survival at 1, 3, and 5 years were 0.8, 0.79, and 0.79. The prediction ability in the development and verification cohorts was in good agreement with the actual values, while we plotted the clinical decision curves for the model, suggesting that the nomogram can provide benefits for clinical decision-making.

Conclusion

Our model provides a prognostic guide for patients with PIML and a reliable basis for clinicians.