Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous B-cell malignancy influenced by immune dysregulation, posing significant clinical challenges. Lymphocyte subsets (e.g., CD4 + T helper 1/ T helper 2 cells) and their cytokines (IFN-γ/IL-4) are readily measurable immune markers involved in DLBCL pathogenesis and may independently predict prognosis. However, the prognostic value of these two combined clinical laboratory findings in newly diagnosed DLBCL patients remains uninvestigated. Here, we retrospectively analyzed 94 newly diagnosed DLBCL patients treated at our institution between 2017 and 2023. The prognostic influences of lymphocyte subsets, cytokines levels and other factors on progression-free survival (PFS) and overall survival (OS) were studied by Kaplan-Meier analysis and Cox regression (univariate/multivariate). Then we constructed an immune-related prognostic score model (IRPS) and validated it in another independent cohort. The results suggested that a high IFN-γ/IL-4 ratio and elevated CD4 + T cell count were favorable risk variables for both PFS and OS in DLBCL patients. Besides, multivariate analysis showed that age was marginally associated with the worse OS whereas low CD8 + T cell count was associated with the inferior PFS. Moreover, elevated pretreatment IFN-γ/IL-4 ratio was significantly correlated with better clinical response efficacy. Compared to those treatment-responsive patients, lower level of IFN-γ/IL-4 ratio was discovered in patients experienced with progression during the subsequent treatment cycles. Additionally, a new immune-related prognostic score model was constructed based on age, CD4 + T cell count and IFN-γ/IL-4 ratio, where high-risk patients had worse overall survival than low-risk patients. Meanwhile, the IRPS could refine the International Prognostic Index (IPI) score well and validation of the IRPS in another independent cohort confirmed its effectiveness. IFN-γ/IL-4 ratio is a practical prognostic marker in newly diagnosed DLBCL, and the IRPS model shows potential for predicting PFS and OS in DLBCL, enabling improved risk stratification.
Zhou et al. (2025) studied this question.