These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Prognostic impact of bone marrow erythropoietic precursor cells and myelofibrosis at diagnosis of Ph1+ chronic myelogenous leukaemia--a multicentre study on 495 patients.
    Author: Kvasnicka HM, Thiele J, Schmitt-Graeff A, Diehl V, Zankovich R, Niederle N, Leder LD, Schaefer HE.
    Journal: Br J Haematol; 2001 Mar; 112(3):727-39. PubMed ID: 11260078.
    Abstract:
    A multicentre clinicopathological study was performed on 495 patients with chronic-phase Ph1+ chronic myelogenous leukaemia (CML) to determine bone marrow characteristics that exert a significant impact on survival under standard treatment regimens. Immunohistochemical and morphometric techniques were applied to identify nucleated erythroid precursor cells in the bone marrow and to quantify argyrophilic fibre density. Application of the Sokal index and another recently proposed CML score failed to distinguish three clearly defined risk groups. A borderline increase in fibre content (i.e. doubling of the normal density) and a relevant reduction of medullary erythropoiesis proved to be important predictors for survival, even in low-risk classified patients, according to both clinical scores. With regard to optimal treatment strategies, patients with manifest myelofibrosis showed no significant difference in survival rates under interferon or hydroxyurea treatment. Multivariate analysis confirmed the prognostic value of histological features. A risk model based on three variables (fibre density, erythropoietic precursors and spleen size) was constructed that enabled a distinct discrimination of risk profiles. In conclusion, the presented data provide compelling evidence that bone marrow features at diagnosis exert a significant impact on prognosis in CML. In this context, the generally clinical-based multivariate risk classification can be improved by consideration of morphological variables that are acting independently of treatment modalities.
    [Abstract] [Full Text] [Related] [New Search]