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Autologous bone marrow transplantation in acute leukemia and lymphoma following ex vivo treatment with monoclonal antibodies and complement

  • Arnold S. Freedman
  • Tak Takvorian
  • Lee M. Nadler
  • Kenneth C. Anderson
  • Stephen E. Sallan
  • Jerome Ritz
Part of the Cancer Treatment and Research book series (CTAR, volume 38)

Abstract

Recent experience with both allogeneic and syngeneic bone marrow transplantation (BMT) has demonstrated that high-dose chemoradiotherapy can lead to long-term disease-free survival in patients with various hematologic neoplasms, including acute myeloblastic leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myelogenous leukemia (CML), and non-Hodgkin’s lymphoma (NHL) [1, 2]. In most instances, bone marrow donors have been siblings who are identical with the patients at the major histocompatibility complex. Therefore, BMT has been limited to the 30%–40% of patients with histocompatible siblings to serve as normal marrow donors. One of the major obstacles, even in patients with HLA-matched donors, is graft versus host disease (GVHD), which occurs in 30%–70% of patients who receive standard prophylaxis regimens. GVHD is thus a significant cause of morbidity and mortality, particularly in older patients. The use of autologous bone marrow for patients who lack histocompatible donors is an attractive alternative for two reasons. First, it eliminates the need for histocompatible donors, and secondly, the complications associated with GVHD do not occur. Unfortunately, in both leukemias and lymphomas, tumor cells are often present in the bone marrow during complete hematologic remission [3]. In Burkitt’s lymphoma, several groups have demonstrated that tumor cell lines can be derived from histologically uninvolved marrow [4].

Keywords

Graft Versus Host Disease Autologous Bone Marrow Autologous Bone Marrow Trans Normal Bone Marrow Acute Myeloblastic Leukemia 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1988

Authors and Affiliations

  • Arnold S. Freedman
  • Tak Takvorian
  • Lee M. Nadler
  • Kenneth C. Anderson
  • Stephen E. Sallan
  • Jerome Ritz

There are no affiliations available

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