High-grade B-cell lymphoma, not otherwise specified: a multi-institutional retrospective study

BLOOD ADVANCES(2023)

引用 0|浏览30
暂无评分
摘要
In this multi-institutional retrospective study, we examined the characteristics and outcomes of 160 patients with high-grade B-cell lymphoma, not otherwise specified (HGBL-NOS)-a rare category defined by high-grade morphologic features and lack of MYC rearrangements with BCL2 and/or BCL6 rearrangements ("double hit"). Our results show that HG BL-NOS tumors are heterogeneous: 83% of patients had a germinal center B-cell immunophenotype, 37% a dual-expressor immunophenotype (MYC and BCL2 expression), 28% MYC rearrangement, 13% BCL2 rearrangement, and 11% BCL6 rearrangement. Most patients presented with stage IV disease, a high serum lactate dehydrogenase, and other high-risk clinical factors. Most frequent first-line regimens included dose-adjusted cyclophosphamide, doxorubicin, vincristine, and etoposide, with rituximab and prednisone (DA-EPOCH-R; 43%); rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP; 33%); or other intensive chemotherapy programs. We found no significant differences in the rates of complete response (CR), progression-free survival (PFS), or overall survival (OS) between these chemotherapy regimens. CR was attained by 69% of patients. PFS at 2 years was 55.2% and OS was 68.1%. In a multivariable model, the main prognostic factors for PFS and OS were poor performance status, lactate dehydrogenase >3 x upper limit of normal, and adual-expressor immunophenotype. Age >60 years or presence of MYC rearrangement were not prognostic, but patients with TP53 alterations had a dismal PFS. Presence of MYC rearrangement was not predictive of better PFS in patients treated with DA-EPOCH -R vs R-CHOP. Improvements in the diagnostic criteria and therapeutic approaches beyond dose-intense chemotherapy are needed to overcome the unfavorable prognosis of patients with HGBL-NOS.
更多
查看译文
关键词
lymphoma,retrospective study,high-grade,b-cell,multi-institutional
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