A Prospective Observational Study of Real-World Treatment and Outcome in Secondary CNS Lymphoma.
EUROPEAN JOURNAL OF CANCER(2024)
摘要
Background: Secondary central nervous system lymphoma (SCNSL) confers a dismal prognosis and treatment advances are constrained by the lack of prospective studies and real-world treatment evidence.Methods: Patients with SCNSL of all entities were included at first diagnosis and patient characteristics, treatment data, and outcomes were prospectively collected in the Secondary CNS Lymphoma Registry (SCNSL-R) (NCT05114330).Findings: 279 patients from 47 institutions were enrolled from 2011 to 2022 and 243 patients (median age: 66 years; range: 23-86) were available for analysis. Of those, 49 (20 %) patients presented with synchronous (cohort I) and 194 (80 %) with metachronous SCNSL (cohort II). The predominant histology was diffuse large B-cell lymphoma (DLBCL, 68 %). Median overall survival (OS) from diagnosis of CNS involvement was 17.2 months (95 % CI 12-27.5), with longer OS in cohort I (60.6 months, 95 % CI 45.5-not estimable (NE)) than cohort II (11.4 months, 95 % CI 7.8-17.7, log-rank test p < 0.0001). Predominant induction regimens included R-CHOP/highdose MTX (cohort I) and high-dose MTX/cytarabine (cohort II). Rituximab was used in 166 (68 %) of B-cell lymphoma. Undergoing consolidating high-dose therapy and autologous hematopoietic stem cell transplantation (HDT-ASCT) in partial response (PR) or better was associated with longer OS (HR adjusted 0.47 (95 % CI 0.25-0.89), p = 0.0197).Interpretation: This study is the largest prospective cohort of SCNSL patients providing a comprehensive overview of an international real-world treatment landscape and outcomes. Prognosis was better in patients with SCNSL involvement at initial diagnosis (cohort I) and consolidating HDT-ASCT was associated with favorable outcome in patients with PR or better.
更多查看译文
关键词
Secondary Central Nervous System Lymphoma,SCNSL,Real-world data,Registry study,High-dose chemotherapy,Autologous stem cell transplantation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要