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Staging of chronic lymphocytic leukaemia

Authoring team

Two clinical staging systems are used widely.

  • the Binet staging system - used in Europe,
    • is based on the
      • number of involved areas - defined by the presence of enlarged lymph nodes of greater than 1 cm in diameter or organomegaly in the following areas
        • head and neck, including the Waldeyer ring (this counts as one area, even if more than one group of nodes is enlarged)
        • axillae (involvement of both axillae counts as one area).
        • groins, including superficial femorals (involvement of both groins counts as one area).
        • palpable spleen
        • palpable liver (clinically enlarged)

and

  • the presence of anaemia or thrombocytopenia
  • it separates patients into three groups of different prognosis
    • Binet A
      • Hb ≥10.0 g/dl, thrombocytes ≥100×109/l, <3 lymph node regions involvement
      • median survival is >10 years
    • Binet B
      • Hb ≥10.0 g/dl, thrombocytes ≥100×109/l, ≥3 lymph node regions involvement
      • median survival is 7 years
    • Binet C
      • Hb <10,0 g/dl, thrombocytes <100×109/l
      • median survival is 1.5–2.5 years
  • Rai staging system - used in the United States, named after its originator, this classification categorises patients in terms of how extensive the disease is at the time of presentation
    • low risk
      • Rai 0 - Lymphocytosis >15×109/l, median survival is >10 years
    • intermediate risk
      • Rai I - Lymphocytosis and lymphadenopathy
      • Rai II - Lymphocytosis and hepatomegaly and/or splenomegaly with/without lymphadenopathy
      • median survival is 7 years
    • high risk
      • Rai III - Lymphocytosis and Hb < 11.0 g/dl with/without lymphadenopathy/organomegaly
      • Rai IV- Lymphocytosis and thrombocytes < 100×109/l with/without lymphadenopathy/organomegaly
      • median survival is 1.5 - 3 years

Note:

  • although these staging systems predicts prognosis, they are unable to identify who has indolent or progressive disease or predict response to treatment (2)

Reference:


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