Survival prediction and conditional survival of primary central nervous system lymphoma: A population-based study.

Background: Primary central nervous system lymphoma is a rare and highly aggressive type of non-Hodgkin lymphoma. This study used population-based data to evaluate the clinical characteristics and prognostic factors of primary central nervous system lymphoma and develop a prediction model to estimate survival.

Methods: Patients' data were extracted from the Surveillance, Epidemiology, and End Results database. Significant prognostic factors were identified using univariate and multivariate Cox regression analyses. Conditional survival estimates were calculated as CS(x y) = S(x + y)/S(X), and a nomogram was built to predict patient prognosis.

Results: In total, 2563 patients with primary central nervous system lymphoma were included. Multivariate Cox analysis showed that age at diagnosis, sex, histology, tumor site, surgery, chemotherapy, and marital status were independent prognostic factors of overall survival. The 1-year conditional survival increased with time, and our nomogram model showed favorable discriminative ability.

Conclusion: At the population level, our study found that gross total resection and chemotherapy improved the prognosis of patients with primary central nervous system lymphoma. However, the prognosis of black patients was poor. Conditional survival provided a more accurate and dynamic survival estimate. Moreover, our nomogram had a good performance and could help predict the overall survival of these patients.