PURPOSE: The aim of this study was to analyze chromosomal aberrations in terms of frequency and impact on time to progression in patients with smoldering multiple myeloma (SMM) on the background of clinical prognostic factors. PATIENTS AND METHODS: The chromosomal abnormalities 1q21, 5p15/5q35, 9q34, 13q14.3, 15q22, 17p13, t(11;14)(q13;q32), and t(4;14)(p16.3;q32) were assessed in CD138-purified myeloma cells by interphase fluorescent in situ hybridization (iFISH) alongside clinical parameters in a consecutive series of 248 patients with SMM. RESULTS: The high-risk aberrations in active myeloma (ie, del(17p13), t(4;14), and +1q21) present in 6.1%, 8.9%, and 29.8% of patients significantly confer adverse prognosis in SMM with hazard ratios (HRs) of 2.90 (95% CI, 1.56 to 5.40), 2.28 (95% CI, 1.33 to 3.91), and 1.66 (95% CI, 1.08 to 2.54), respectively. Contrary to the conditions in active myeloma, hyperdiploidy, present in 43.3% of patients, is an adverse prognostic factor (HR, 1.67; 95% CI, 1.10 to 2.54). Percentage of malignant bone marrow plasma cells assessed by iFISH and combination of M-protein and plasma cell infiltration as surrogates of tumor load significantly confer adverse prognosis with HRs of 4.37 (95% CI, 2.79 to 6.85) and 4.27 (95% CI, 2.77 to 6.56), respectively. In multivariate analysis, high-risk aberrations, hyperdiploidy, and surrogates of tumor load are independently prognostic. CONCLUSION: The high-risk chromosomal aberrations del(17p13), t(4;14), and +1q21 are adverse prognostic factors in SMM just as they are in active myeloma, independent of tumor mass. Hyperdiploidy is the first example for an adverse prognostic factor in SMM of opposite predictiveness in active myeloma. Risk association of chromosomal aberrations is not only a priori treatment dependent (predictive) but is also an intrinsic property of myeloma cells (prognostic).
PURPOSE: The aim of this study was to analyze chromosomal aberrations in terms of frequency and impact on time to progression in patients with smoldering multiple myeloma (SMM) on the background of clinical prognostic factors. PATIENTS AND METHODS: The chromosomal abnormalities 1q21, 5p15/5q35, 9q34, 13q14.3, 15q22, 17p13, t(11;14)(q13;q32), and t(4;14)(p16.3;q32) were assessed in CD138-purified myeloma cells by interphase fluorescent in situ hybridization (iFISH) alongside clinical parameters in a consecutive series of 248 patients with SMM. RESULTS: The high-risk aberrations in active myeloma (ie, del(17p13), t(4;14), and +1q21) present in 6.1%, 8.9%, and 29.8% of patients significantly confer adverse prognosis in SMM with hazard ratios (HRs) of 2.90 (95% CI, 1.56 to 5.40), 2.28 (95% CI, 1.33 to 3.91), and 1.66 (95% CI, 1.08 to 2.54), respectively. Contrary to the conditions in active myeloma, hyperdiploidy, present in 43.3% of patients, is an adverse prognostic factor (HR, 1.67; 95% CI, 1.10 to 2.54). Percentage of malignant bone marrow plasma cells assessed by iFISH and combination of M-protein and plasma cell infiltration as surrogates of tumor load significantly confer adverse prognosis with HRs of 4.37 (95% CI, 2.79 to 6.85) and 4.27 (95% CI, 2.77 to 6.56), respectively. In multivariate analysis, high-risk aberrations, hyperdiploidy, and surrogates of tumor load are independently prognostic. CONCLUSION: The high-risk chromosomal aberrations del(17p13), t(4;14), and +1q21 are adverse prognostic factors in SMM just as they are in active myeloma, independent of tumor mass. Hyperdiploidy is the first example for an adverse prognostic factor in SMM of opposite predictiveness in active myeloma. Risk association of chromosomal aberrations is not only a priori treatment dependent (predictive) but is also an intrinsic property of myeloma cells (prognostic).
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
Authors: Michelle M McDonald; Michaela R Reagan; Scott E Youlten; Sindhu T Mohanty; Anja Seckinger; Rachael L Terry; Jessica A Pettitt; Marija K Simic; Tegan L Cheng; Alyson Morse; Lawrence M T Le; David Abi-Hanna; Ina Kramer; Carolyne Falank; Heather Fairfield; Irene M Ghobrial; Paul A Baldock; David G Little; Michaela Kneissel; Karin Vanderkerken; J H Duncan Bassett; Graham R Williams; Babatunde O Oyajobi; Dirk Hose; Tri G Phan; Peter I Croucher Journal: Blood Date: 2017-05-17 Impact factor: 22.113
Authors: Lucía López-Corral; Luis Antonio Corchete; María Eugenia Sarasquete; María Victoria Mateos; Ramón García-Sanz; Encarna Fermiñán; Juan-José Lahuerta; Joan Bladé; Albert Oriol; Ana Isabel Teruel; María Luz Martino; José Hernández; Jesús María Hernández-Rivas; Francisco Javier Burguillo; Jesús F San Miguel; Norma C Gutiérrez Journal: Haematologica Date: 2014-05-09 Impact factor: 9.941
Authors: S C Brandelik; J Krzykalla; T Hielscher; J Hillengass; J K Kloth; H U Kauczor; M A Weber Journal: Radiologe Date: 2018-01 Impact factor: 0.635