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

Area of Science:

• Oncology
• Hematology
• Epidemiology

Background:

• Primary pulmonary diffuse large B-cell lymphoma (PP-DLBCL) is a rare extranodal non-Hodgkin's lymphoma (EN-NHL).
• PP-DLBCL is an aggressive lymphoma with a poor prognosis.
• Current predictive models for PP-DLBCL prognosis are lacking.

Purpose of the Study:

• To identify independent risk factors affecting patient prognosis in PP-DLBCL.
• To construct and validate a novel predictive model (nomogram) for PP-DLBCL survival.
• To aid clinical decision-making for PP-DLBCL patients.

Main Methods:

• Screened 831 patients diagnosed with PP-DLBCL from 2010-2019 using the SEER database.
• Employed univariate and multivariate COX regression analyses to identify prognostic factors.
• Developed and validated a nomogram using training (70%) and validation (30%) cohorts.

Main Results:

• Identified age, extrapulmonary metastasis, radiotherapy, chemotherapy, and surgical intervention as independent risk factors.
• The developed nomogram demonstrated accurate predictive capability in both training and validation groups.
• Model performance was confirmed through ROC curves, calibration curves, and decision curve analysis.

Conclusions:

• This is the first large population-based study on PP-DLBCL prognosis.
• A novel, validated nomogram can accurately predict survival for PP-DLBCL patients.
• The predictive model can assist clinicians in making informed treatment decisions.