Literature DB >> 17489983

Testing standard and genetic parameters in 220 patients with multiple myeloma with complete data sets: superiority of molecular genetics.

John D Shaughnessy1, Jeffrey Haessler, Frits van Rhee, Elias Anaissie, Mauricio Pineda-Roman, Michele Cottler-Fox, Klaus Hollmig, Maurizio Zangari, Abid Mohiuddin, Yazan Alsayed, Monica Grazziutti, Joshua Epstein, John Crowley, Bart Barlogie.   

Abstract

Prognostic models for multiple myeloma have been fraught with tremendous heterogeneity in outcome among subgroups. In the context of Total Therapy 2, a tandem transplant trial for newly diagnosed myeloma, comprehensive information was available in 220 patients on standard prognostic factors (SPF), magnetic resonance imaging (MRI)-defined focal lesions, cytogenetic abnormalities (CA), fluorescence-in-situ-hybridisation (FISH)-derived amplification of chromosome 1q21 (amp1q21) and deletion of 13q14, as well as gene expression profiling (GEP). Five multivariate analysis-based survival models were derived, utilising SPF only (model 1), with progressive addition of CA (model 2), MRI (model 3), FISH (model 4) and GEP (model 5). The R(2) value, a measure of accounting for clinical outcome variability, increased progressively from 18% in model 1 to 38% in model 5. The hazard ratio for overall survival was highest for GEP (3.07, P < 0.001) followed by amp1q21 (1.71, P = 0.05). According to the presence of none (49%), one (35%) or both of these two risk features (16%), 3-year survival decreased progressively from 92% to 78% to 43% (P < 0.0001). Thus, the dominance over other prognostic parameters of molecular genetics justifies the generation of quantitative reverse transcription polymerase chain reaction methodology ('MM genetic kit') for the optimal risk stratification of patients participating in therapeutic trials.

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Year:  2007        PMID: 17489983     DOI: 10.1111/j.1365-2141.2007.06586.x

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


  21 in total

Review 1.  The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma.

Authors:  Sarah K Johnson; Christoph J Heuck; Anthony P Albino; Pingping Qu; Qing Zhang; Bart Barlogie; John D Shaughnessy
Journal:  Int J Hematol       Date:  2011-10-15       Impact factor: 2.490

2.  Suppression of abnormal karyotype predicts superior survival in multiple myeloma.

Authors:  V Arzoumanian; A Hoering; J Sawyer; F van Rhee; C Bailey; J Gurley; J D Shaughnessy; E Anaissie; J Crowley; B Barlogie
Journal:  Leukemia       Date:  2008-01-17       Impact factor: 11.528

3.  Chromosome 1q21 gains confer inferior outcomes in multiple myeloma treated with bortezomib but copy number variation and percentage of plasma cells involved have no additional prognostic value.

Authors:  Gang An; Yan Xu; Lihui Shi; Zhong Shizhen; Shuhui Deng; Zhenqing Xie; Weiwei Sui; Fenghuang Zhan; Lugui Qiu
Journal:  Haematologica       Date:  2013-11-08       Impact factor: 9.941

4.  Outcome of Patients with Multiple Myeloma and CKS1B Gene Amplification after Autologous Hematopoietic Stem Cell Transplantation.

Authors:  Fabian Bock; Gary Lu; Samer A Srour; Sameh Gaballa; Heather Y Lin; Veerabhadran Baladandayuthapani; Medhavi Honhar; Maximilian Stich; Nina Das Shah; Qaiser Bashir; Krina Patel; Uday Popat; Chitra Hosing; Martin Korbling; Ruby Delgado; Gabriela Rondon; Jatin J Shah; Sheeba K Thomas; Elisabet E Manasanch; Berend Isermann; Robert Z Orlowski; Richard E Champlin; Muzaffar H Qazilbash
Journal:  Biol Blood Marrow Transplant       Date:  2016-09-13       Impact factor: 5.742

5.  Gain of chromosome 1q portends worse prognosis in multiple myeloma despite novel agent-based induction regimens and autologous transplantation.

Authors:  Gunjan L Shah; Heather Landau; Dory Londono; Sean M Devlin; Satyajit Kosuri; Alexander M Lesokhin; Nikoletta Lendvai; Hani Hassoun; David J Chung; Guenther Koehne; Suresh C Jhanwar; Ola Landgren; Ross Levine; Sergio A Giralt
Journal:  Leuk Lymphoma       Date:  2017-01-12

6.  Improvement in long-term outcomes with successive Total Therapy trials for multiple myeloma: are patients now being cured?

Authors:  S Z Usmani; J Crowley; A Hoering; A Mitchell; S Waheed; B Nair; Y AlSayed; F Vanrhee; B Barlogie
Journal:  Leukemia       Date:  2012-06-18       Impact factor: 11.528

7.  Extensive Remineralization of Large Pelvic Lytic Lesions Following Total Therapy Treatment in Patients With Multiple Myeloma.

Authors:  Meera Mohan; Rohan S Samant; Donghoon Yoon; Amy F Buros; Antonio Branca; Corey O Montgomery; Richard Nicholas; Larry J Suva; Roy Morello; Sharmilan Thanendrarajan; Carolina Schinke; Shmuel Yaccoby; Frits van Rhee; Faith E Davies; Gareth J Morgan; Maurizio Zangari
Journal:  J Bone Miner Res       Date:  2017-03-27       Impact factor: 6.741

8.  Improving overall survival and overcoming adverse prognosis in the treatment of cytogenetically high-risk multiple myeloma.

Authors:  P Leif Bergsagel; María-Victoria Mateos; Norma C Gutierrez; S Vincent Rajkumar; Jesús F San Miguel
Journal:  Blood       Date:  2012-11-19       Impact factor: 22.113

9.  Identification of early growth response protein 1 (EGR-1) as a novel target for JUN-induced apoptosis in multiple myeloma.

Authors:  Lijuan Chen; Siqing Wang; Yiming Zhou; Xiaosong Wu; Igor Entin; Joshua Epstein; Shmuel Yaccoby; Wei Xiong; Bart Barlogie; John D Shaughnessy; Fenghuang Zhan
Journal:  Blood       Date:  2009-10-16       Impact factor: 22.113

Review 10.  The Arkansas approach to therapy of patients with multiple myeloma.

Authors:  Bart Barlogie; Elias Anaissie; Frits van Rhee; Mauricio Pineda-Roman; Maurizio Zangari; John Shaughnessy; Joshua Epstein; John Crowley
Journal:  Best Pract Res Clin Haematol       Date:  2007-12       Impact factor: 3.020

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