Prognostic significance of cell-of-origin, gene expression profiles, and frontline therapy in predicting secondary CNS lymphoma in newly diagnosed diffuse large B-cell lymphoma

Abstract

Abstract Background Secondary central nervous system lymphoma (SCNSL) is a rare but significant complication, affecting approximately 2–10% of patients with diffuse large B-cell lymphoma (DLBCL), often leading to poor outcomes. The CNS-International Prognostic Index (CNS-IPI) remains a widely adopted tool for estimating CNS relapse risk; however, recent advances in molecular profiling and evolving treatment paradigms have challenged the adequacy of CNS-IPI alone in guiding risk assessment. This study evaluates the prognostic relevance of CNS-IPI in conjunction with molecular and clinical factors, specifically cell-of-origin (COO), gene expression, and frontline treatment regimens. The aim is to refine risk stratification and identify patients at highest risk for SCNSL. Method Building on our previous study, we analyzed data from patients with newly diagnosed DLBCL between 2002 and 2023, enrolled in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource. Patients with primary CNS lymphoma, CNS involvement at diagnosis, or who received CNS-directed therapy were excluded. COO was determined using the Hans algorithm and/or Nanostring profiling. Multivariate cause-specific Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for predictors of CNS relapse that were measured at the time of initial DLBCL diagnosis. Cumulative incidence with competing risks and cause-specific Cox models were used to analyze relapse risk. Result We included 2137 patients in our analysis, median age at diagnosis was 63 (IQR 53-72), with 41.6% (n=890) females. The albumin level was below normal in 32.5% (n=350), 64.0% (n=1367) had CNS-IPI of intermediate/high, 37.5% (n=586) had non-germinal center B-cell (GCB) COO, and 14.5% (n=309) were double expressor positive. At a median follow-up of 83 months (IQR 42 -143), 82 (3.8%) SCNSL relapses were observed; the 3 and 5 yrs cumulative incidence for SCNSL from time of DLBCL diagnosis were 3.7% (95% CI 3.0-4.7) and 3.8% (95% CI 3.1-4.8) respectively. In models accounting for death as a competing risk, the 5-year cumulative SCNSL incidence estimate for patients with a CNS-IPI low was 1.5% (95% CI 0.8-2.7), Intermediate was 4.9% (95% CI 3.7-6.4), and high was 6.1% (95% CI 3.8-9.6). The 5-year cumulative SCNSL incidence estimate for patients with non-GCB COO was 5.2% (95% CI 3.6-7.4) compared to 2.4% (95% CI 1.6-3.6; p=0.001) for GCB patients, and the 5-year cumulative SCNSL incidence for double expressor positive patients was 8.6% (95% 5.8-12.6) compared to 1.5% (95% CI 0.8-2.7; p<0.001) for double expressor negative patients. In a multivariable model (including CNS-IPI, COO, double expressor, treatment group, extranodal involvement, and albumin group), CNS-IPI intermediate (HR 2.85 [1.58-5.14]; p<0.001) and high (HR 4.31 [2.15-8.65]; p<0.001), non-GCB COO (HR 2.36 [1.37-4.06]; p=0.002], double expressor (HR 5.56 [2.88-10.73]; p<0.001), and below normal albumin (HR 1.89 [1.02-3.50]; p=0.042) were independently associated with increased risk of SCNSL. The majority of the SCNSL relapse occurred within the first 2 years after DLBCL diagnosis; 81.7% (n=67), with only 6.1% (n=5) occurring after 5 years. For patients who developed SCNSL, the median OS from the time of SCNSL diagnosis was 24 months (95% CI 17-34), with 5 years OS of 31% (95% CI 22-43). These findings are being validated using an external, international cohort, and final analysis will be presented at the time of presentation at ASH. Conclusion In this large, prospectively followed cohort with long-term follow-up data, SCNSL remains a rare but devastating complication of DLBCL, with a 5-year cumulative incidence of 3.8% and it is associated with very poor long-term survival. While CNS-IPI remains a strong predictor of SCNSL risk, our study identifies non-GCB COO and double expressor phenotype as independent, additive molecular risk factors. These findings suggest that current risk stratification tools may underestimate the risk of CNS relapse in molecularly defined high-risk subgroups. Considering the poor outcomes linked to SCNSL and the absence of a connection with frontline treatment types, future research should aim to enhance risk prediction models through molecular profiling and explore prophylactic strategies to reduce the likelihood of SCNSL.