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  • Title: Clinical Characteristics of Hemophagocytic Lymphohistiocytosis Associated with Non-Hodgkin B-Cell Lymphoma: A Multicenter Retrospective Study.
    Author: Li B, Guo J, Li T, Gu J, Zeng C, Xiao M, Zhang W, Li Q, Zhou J, Zhou X.
    Journal: Clin Lymphoma Myeloma Leuk; 2021 Feb; 21(2):e198-e205. PubMed ID: 33303420.
    Abstract:
    BACKGROUND: Hemophagocytic lymphohistiocytosis (HLH) associated with B-cell lymphoma is a highly aggressive disease with unclear clinical features and has no standard treatment. PATIENTS AND METHODS: We analyzed the clinical characteristics of 31 patients from two individual centers. RESULTS: The median overall survival was only 1.5 months. Both univariate and multivariate analyses, based on lymphoma or HLH-related characteristics, revealed that patients with high Epstein-Barr virus (EBV) DNA load and ≥ 2 extranodal lesions, or hypofibrinogenemia, respectively, showed significantly poorer overall survival. Interestingly, some patients with high EBV DNA load had EBV-positive natural killer (NK) and/or T cells, which may be related to the coexistence of immunodeficiency and/or chronic active EBV infection. Molecular genetics examination confirmed that 47.4% (9/19) of patients had complex karyotypes, 37.5% (3/8) of patients had TP53 deletions, and 21.34% (3/14) of patients had TP53 mutation or alteration of malignancy-related pathways, including BCR/NF-κB, JAK-STAT, and epigenetic regulatory pathways, which may provide clues to choose targets for therapy. Treatment regimens containing etoposide, anti-CD20 monoclonal antibodies, or anthracyclines improved patient prognosis (P = .0183, .025, and .0436, respectively). Patients with infections had significantly shorter survival than those without infections (P = .00019). CONCLUSION: The patients' performance status, number of extranodal lesions, high EBV DNA load, and hypofibrinogenemia are poor prognostic factors for HLH associated with B-cell lymphoma. Molecular genetic high-risk factors are of particular importance because these factors can provide information for prognosis prediction, treatment decisions, and disease surveillance.
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