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Morphologic and Prognostic Features of Advanced Mycosis Fungoides

  • Helmut Kerl
  • Lorenzo Cerroni
  • Stefan Hoedl
Part of the NATO ASI Series book series (NSSA, volume 265)

Abstract

Mycosis fungoides (MF) is a cutaneous T cell lymphoma (CTCL) of low grade malignancy, characterized by the proliferation of small to medium sized cells with cerebriform nuclei. Many patients show, in the advanced stages of the disease, progression to a large cell lymphoma (LCL). In this study, biopsies of tumors from 36 patients with advanced MF were examined for cytomorphologic evidence for transformation into LCL. The findings were: 44.4% of these cases showed no evidence of transformation; only classical MF with small to medium sized cells with cerebriform nuclei were seen. 13.9% showed T-immunoblastic lymphoma, with predominance of cells with round to oval nuclei and prominent, centrally located nucleoli. 25.0% showed medium sized and large T cells with pleomorphic nuclei. 5.6% showed large anaplastic T cell lymphoma with cytomorphologic features of large anaplastic and immunoblastic cells and cells resembling Reed-Sternberg cells. 11.1% showed unclassified LCL, characterized by large cells with features of pleomorphic cells and immunoblasts. Immunohistochemical investigations revealed aberrant patterns of antigen expression (loss of one or more pan-T cell antigens or simultaneous presence of activation and proliferation-associated antigens). Clusters of B lymphocytes were found in about one-third of these cases. Analysis of overall survival from time of first biopsy diagnostic of MF showed a statistically significant difference between patients with non-transformed MF versus those in which transformation to LCL had occurred (ten-year survival, 46.6% versus 11.1%; p < 0.02).

Keywords

Large Cell Anaplastic Lymphoma Mycosis Fungoides Sezary Syndrome Pleomorphic Cell Interdigitating Reticulum Cell 
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

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Helmut Kerl
    • 1
  • Lorenzo Cerroni
    • 1
  • Stefan Hoedl
    • 1
  1. 1.Department of DermatologyUniversity of GrazGrazAustria

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