Primary Central Nervous System Lymphoma and Contemporary Clinical Prognostication

• Published in: Blood 2023-11, Vol.142 (Supplement 1), p.1768-1768
• Main Authors: Godby, Richard C., Hwang, Steven R., Gysbers, Brianna, Mwangi, Raphael, Maurer, Matthew J., Witzig, Thomas E., Paludo, Jonas, Villasboas, J. C., Durani, Urshila, Habermann, Thomas M., Nowakowski, Grzegorz S., Khurana, Arushi, Johnston, Patrick B
• Format: Article
• Language: English
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2023-182866

Background: Primary central nervous system lymphoma (PCNSL) is a rare form of non-Hodgkin lymphoma with two-year overall survival (OS) rates of 66-70% reported in prospective clinical trials. Induction therapy with high-dose methotrexate (HD-MTX) followed by consolidation has become the mainstay of treatment, however, there are few contemporary and robust prognostication indices widely available for clinical use. Some of the most used indices were developed prior to the routine use of rituximab and include the International Extranodal Lymphoma Study Group (IELSG; 1980-1999), Memorial Sloan-Kettering Cancer Center (MSKCC; 1983-2003), Nottingham/Barcelona (NB; 1986-2001), and Taipei Score (TS; 2003-2015). Herein, we describe a contemporary comparison of clinical prognostication indices using a single-center cohort of PCNSL patients treated at the Mayo Clinic. Methods: Patients with a diagnosis of PCNSL who received HD-MTX as part of induction therapy at Mayo Clinic between October 2010 and June 2022 were identified and retrospectively reviewed. Patients with prior or concurrent systemic lymphoma were excluded. Primary endpoints were progression-free survival (PFS) defined as time from diagnosis to relapse, progression, or death due to any cause; and OS defined as time from diagnosis to death due to any cause. PFS and OS were evaluated using Kaplan-Meier curves and compared by risk scores using a log-rank test. The association between baseline characteristics and survival outcome were assessed in univariate Cox regression models. Any characteristics showing significant (p-value