Prognostic factors and predictive models for primary pulmonary diffuse large B-cell lymphoma: a population-based analysis

Background: Primary pulmonary diffuse large B-cell lymphoma (PP-DLBCL) is a rare extranodal non-Hodgkin's lymphoma (EN-NHL). Its prognosis as an aggressive lymphoma is abysmal, and predictive models are still lacking. Methods: We screened patients diagnosed with PP-DLBCL between 2010 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. Then, univariate and multivariate COX regression analyses were used to identify independent risk factors affecting patient prognosis. Finally, a novel nomogram was constructed and the model was evaluated by looking at three dimensions. Results: A total of 831 patients were included in this study. Most of the patients were elderly (526 (63.8%)) and female (428 (51.9%)). The included patients were randomized in a 7:3 ratio into a training group (577 (70%)) and a validation group (248 (30%)). We concluded that the independent risk factors of prognosis were age, extrapulmonary metastasis, radiotherapy, chemotherapy, and surgical intervention. The results of 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 PP-DLBCL. Conclusion: This study is the first large population-based clinical data study on PP-DLBCL. A novel predictive model about prognosis has been developed to help clinical decision-making.