Primary Central Nervous System Lymphoma: Predictors of Response to Induction Therapy and Patterns of Progression

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is a rare and aggressive variant of non-Hodgkin lymphoma. While PCNSL is often sensitive to induction high-dose methotrexate (HDMTX) based chemotherapy, recurrence rates remain high, approaching 50% within 5 years. The most common molecular alterations in PCNSL include mutations in MYD88 and CD79 and CDKN2A homozygous deletion. There are no predictive or prognostic molecular markers in PCNSL. METHODS: We conducted a retrospective review of 40 patients with PCNSL treated at Thomas Jefferson University and Ohio State University between 2011 and 2023. We created a clinically annotated database of patient characteristics and outcomes. For 13 patients whose paraffin-embedded tissue was available for analysis, Illumina's Infinium Global Diversity Array with Cytogenetics was used to make copy number change calls. RESULTS: The most commonly used induction chemotherapy regimens were HDMTX monotherapy and HDMTX with rituximab. The overall response rate to induction chemotherapy was 75%. A total of 25% had resistant disease to induction chemotherapy. The median follow-up was 20.3 months. The median progression-free survival for the entire cohort was 30.64 months (range 3.42-57.86 months); 2.56 months for the resistant group and 44.88 months for the sensitive group (P-value < .001). The median overall survival for the entire cohort was 64.8 months (range 41.47-88.13 months); 13.97 months for the resistant group and 81.43 months for the sensitive group (P-value = .046). CONCLUSIONS: The initial response to induction chemotherapy is an important prognostic factor in PCNSL. There is a need for improved predictive biomarkers of response to treatment in PNCLS.

Publication Details

Journal
The Medicine Forum
Published
2025-04-24
Primary Topic
Theoretical and Computational Physics
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article
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article

Primary Central Nervous System Lymphoma: Predictors of Response to Induction Therapy and Patterns of Progression

The Medicine Forum
Theoretical and Computational Physics
article

Primary Central Nervous System Lymphoma: Predictors of Response to Induction Therapy and Patterns of Progression

article en

Abstract

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is a rare and aggressive variant of non-Hodgkin lymphoma. While PCNSL is often sensitive to induction high-dose methotrexate (HDMTX) based chemotherapy, recurrence rates remain high, approaching 50% within 5 years. The most common molecular alterations in PCNSL include mutations in MYD88 and CD79 and CDKN2A homozygous deletion. There are no predictive or prognostic molecular markers in PCNSL. METHODS: We conducted a retrospective review of 40 patients with PCNSL treated at Thomas Jefferson University and Ohio State University between 2011 and 2023. We created a clinically annotated database of patient characteristics and outcomes. For 13 patients whose paraffin-embedded tissue was available for analysis, Illumina's Infinium Global Diversity Array with Cytogenetics was used to make copy number change calls. RESULTS: The most commonly used induction chemotherapy regimens were HDMTX monotherapy and HDMTX with rituximab. The overall response rate to induction chemotherapy was 75%. A total of 25% had resistant disease to induction chemotherapy. The median follow-up was 20.3 months. The median progression-free survival for the entire cohort was 30.64 months (range 3.42-57.86 months); 2.56 months for the resistant group and 44.88 months for the sensitive group (P-value < .001). The median overall survival for the entire cohort was 64.8 months (range 41.47-88.13 months); 13.97 months for the resistant group and 81.43 months for the sensitive group (P-value = .046). CONCLUSIONS: The initial response to induction chemotherapy is an important prognostic factor in PCNSL. There is a need for improved predictive biomarkers of response to treatment in PNCLS.

The Medicine Forum
Good health and well-being
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Theoretical and Computational Physics
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