PURPOSE: Multivariate risk classifications for chronic (stable)-phase Ph(1+) chronic myelogenous leukemia (CML) are generally focused on hematologic variables, and the putative prognostic property of bone morphology has been neglected or even contested so far. PATIENTS AND METHODS: A total of 510 consecutively recruited patients in first chronic phase Ph(1+) CML and pretreatment bone marrow biopsy specimens were entered onto this multicenter observational trial to evaluate the effect of bone marrow histopathology. According to generally accepted criteria, patients with any signs of accelerated disease were excluded. Treatment modalities included administration of interferon alfa-2b (IFN) and chemotherapy with hydroxyurea (HU) or busulfan. Immunohistochemical and morphometric techniques were applied to identify marrow cells and to quantify fiber density. Patients were separated into learning and validation samples, and classification and regression tree (CART) analysis was performed to establish a prognostic decision tree. RESULTS: CART analysis of the validation sample (123 patients with HU therapy) revealed the amount of erythroid precursors in the bone marrow, myelofibrosis, and splenomegaly as the most important prognostic features. Three risk profiles with significantly different survival patterns were established, with median survival times ranging from 33 to 108 months (two-sided log-rank test, P =.0001). The new score was confirmed by application to the learning sample with IFN therapy (two-sided log-rank test, P =.0002). Furthermore, risk status defined by the new score was significantly correlated with the occurrence of blast transformation. CONCLUSION: Our data strongly implicate that prognostic classification of chronic-phase Ph(1+) CML can be significantly improved by the inclusion of morphologic parameters. The variables of the presented scoring system may be easily assessed by routinely processed aspirates and bone marrow trephines.
PURPOSE: Multivariate risk classifications for chronic (stable)-phase Ph(1+) chronic myelogenous leukemia (CML) are generally focused on hematologic variables, and the putative prognostic property of bone morphology has been neglected or even contested so far. PATIENTS AND METHODS: A total of 510 consecutively recruited patients in first chronic phase Ph(1+) CML and pretreatment bone marrow biopsy specimens were entered onto this multicenter observational trial to evaluate the effect of bone marrow histopathology. According to generally accepted criteria, patients with any signs of accelerated disease were excluded. Treatment modalities included administration of interferon alfa-2b (IFN) and chemotherapy with hydroxyurea (HU) or busulfan. Immunohistochemical and morphometric techniques were applied to identify marrow cells and to quantify fiber density. Patients were separated into learning and validation samples, and classification and regression tree (CART) analysis was performed to establish a prognostic decision tree. RESULTS: CART analysis of the validation sample (123 patients with HU therapy) revealed the amount of erythroid precursors in the bone marrow, myelofibrosis, and splenomegaly as the most important prognostic features. Three risk profiles with significantly different survival patterns were established, with median survival times ranging from 33 to 108 months (two-sided log-rank test, P =.0001). The new score was confirmed by application to the learning sample with IFN therapy (two-sided log-rank test, P =.0002). Furthermore, risk status defined by the new score was significantly correlated with the occurrence of blast transformation. CONCLUSION: Our data strongly implicate that prognostic classification of chronic-phase Ph(1+) CML can be significantly improved by the inclusion of morphologic parameters. The variables of the presented scoring system may be easily assessed by routinely processed aspirates and bone marrow trephines.
Authors: Heather A Himburg; Martina Roos; Tiancheng Fang; Yurun Zhang; Christina M Termini; Lauren Schlussel; Mindy Kim; Amara Pang; Jenny Kan; Liman Zhao; Hyung Suh; Joshua P Sasine; Gopal Sapparapu; Peter M Bowers; Gary Schiller; John P Chute Journal: J Clin Invest Date: 2020-01-02 Impact factor: 14.808
Authors: Bin Fu; Chi Young Ok; Maitrayee Goswami; Wei Xei; Jesse M Jaso; Tariq Muzzafar; Carlos Bueso-Ramos; Srdan Verstovsek; Guillermo Garcia-Manero; L Jeffrey Medeiros; Sa A Wang Journal: Ann Hematol Date: 2013-05-10 Impact factor: 3.673