Literature DB >> 19438486

Definition of progression risk based on combinations of cellular and molecular markers in patients with Binet stage A chronic lymphocytic leukaemia.

Fortunato Morabito1, Giovanna Cutrona, Massimo Gentile, Serena Matis, Katia Todoerti, Monica Colombo, Claudia Sonaglio, Sonia Fabris, Daniele Reverberi, Mauro Megna, Mauro Spriano, Eugenio Lucia, Edoardo Rossi, Vincenzo Callea, Carla Mazzone, Gianluca Festini, Simonetta Zupo, Stefano Molica, Antonino Neri, Manlio Ferrarini.   

Abstract

IGHV mutational status and ZAP-70 or CD38 expression correlate with clinical course in B-cell chronic lymphocytic leukaemia (CLL). The three markers may be discordant in the single case and there is no consensus on their combined use in clinical practise. This multicenter study investigated this issue. Two-hundred and sixty-two Binet stage A patients were studied for the three markers. Sixty patients were profiled with HG-U133A gene expression chips. Disease progression was determined by time from diagnosis to treatment (TTT). The probability of being treatment-free at 3 years was significantly shorter in patients with unmutated IGHV genes (IGHVunmut 66% vs. 93%, chi square of log-rank = 30, P < 0.0001), ZAP-70 positive (ZAP-70pos 73% vs. 96%, chi square of log-rank = 8.2, P = 0.004) or CD38-positive cells (CD38pos 68% vs. 91%, chi square of log-rank = 21, P < 0.0001). Cox multivariate regression analysis showed that the three markers had an independent predictive value for TTT of similar power. A prognostic system based on presence of none (low-risk), one (intermediate-risk) or two or three (high-risk) markers was generated. Based on such criteria, 56%, 23% and 21% of cases were clustered in low (HR = 1), intermediate [HR = 2.8, 95% confidence interval (CI) 2.4-5.8] and high-risk group (HR = 8.0, 95% CI 3.9-16.2). Specific transcriptional patterns were significantly associated with risk groups.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19438486     DOI: 10.1111/j.1365-2141.2009.07703.x

Source DB:  PubMed          Journal:  Br J Haematol        ISSN: 0007-1048            Impact factor:   6.998


  16 in total

1.  Prognostic factors identified three risk groups in the LRF CLL4 trial, independent of treatment allocation.

Authors:  David Oscier; Rachel Wade; Zadie Davis; Alison Morilla; Giles Best; Sue Richards; Monica Else; Estella Matutes; Daniel Catovsky
Journal:  Haematologica       Date:  2010-05-29       Impact factor: 9.941

2.  A progression-risk score to predict treatment-free survival for early stage chronic lymphocytic leukemia patients.

Authors:  M Gentile; T D Shanafelt; G Cutrona; S Molica; G Tripepi; I Alvarez; F R Mauro; N Di Renzo; F Di Raimondo; I Vincelli; K Todoerti; S Matis; C Musolino; S Fabris; E Vigna; L Levato; S Zupo; F Angrilli; U Consoli; G Festini; G Longo; A Cortelezzi; A Arcari; M Federico; D Mannina; A G Recchia; A Neri; N E Kay; M Ferrarini; F Morabito
Journal:  Leukemia       Date:  2015-12-09       Impact factor: 11.528

3.  LPL is the strongest prognostic factor in a comparative analysis of RNA-based markers in early chronic lymphocytic leukemia.

Authors:  Mohd Arifin Kaderi; Meena Kanduri; Anne Mette Buhl; Marie Sevov; Nicola Cahill; Rebeqa Gunnarsson; Mattias Jansson; Karin Ekström Smedby; Henrik Hjalgrim; Jesper Jurlander; Gunnar Juliusson; Larry Mansouri; Richard Rosenquist
Journal:  Haematologica       Date:  2011-04-20       Impact factor: 9.941

4.  Evidence of canonical somatic hypermutation in hairy cell leukemia.

Authors:  Evgeny Arons; Laura Roth; Jeffrey Sapolsky; Tara Suntum; Maryalice Stetler-Stevenson; Robert J Kreitman
Journal:  Blood       Date:  2011-03-02       Impact factor: 22.113

5.  Prognostic factors in CLL.

Authors:  M Ferrarini; G Cutrona; A Neri; F Morabito
Journal:  Leuk Suppl       Date:  2012-08-09

Review 6.  CD38 and chronic lymphocytic leukemia: a decade later.

Authors:  Fabio Malavasi; Silvia Deaglio; Rajendra Damle; Giovanna Cutrona; Manlio Ferrarini; Nicholas Chiorazzi
Journal:  Blood       Date:  2011-07-15       Impact factor: 22.113

7.  Multivariable model for time to first treatment in patients with chronic lymphocytic leukemia.

Authors:  William G Wierda; Susan O'Brien; Xuemei Wang; Stefan Faderl; Alessandra Ferrajoli; Kim-Anh Do; Guillermo Garcia-Manero; Jorge Cortes; Deborah Thomas; Charles A Koller; Jan A Burger; Susan Lerner; Ellen Schlette; Lynne Abruzzo; Hagop M Kantarjian; Michael J Keating
Journal:  J Clin Oncol       Date:  2011-10-03       Impact factor: 44.544

Review 8.  Detection methods of ZAP-70 in chronic lymphocytic leukemia.

Authors:  Yin-Hua Wang; Lei Fan; Wei Xu; Jian-Yong Li
Journal:  Clin Exp Med       Date:  2011-06-21       Impact factor: 3.984

9.  Biological and clinical relevance of quantitative global methylation of repetitive DNA sequences in chronic lymphocytic leukemia.

Authors:  Sonia Fabris; Valentina Bollati; Luca Agnelli; Fortunato Morabito; Valeria Motta; Giovanna Cutrona; Serena Matis; Anna Grazia Recchia; Vincenzo Gigliotti; Massimo Gentile; Giorgio Lambertenghi Deliliers; Pier Alberto Bertazzi; Manlio Ferrarini; Antonino Neri; Andrea Baccarelli
Journal:  Epigenetics       Date:  2011-02-01       Impact factor: 4.528

10.  Recent advances in bone marrow biopsy pathology.

Authors:  Jon van der Walt
Journal:  J Hematop       Date:  2009-09-26       Impact factor: 0.196

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.