title: Progression in smoldering myeloma is independently determined by the chromosomal abnormalities del(17p), t(4;14), gain 1q, hyperdiploidy, and tumor load.
abstract: OBJECTIVE
  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.
  
  
  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.
  
  
  CONCLUSIONS
  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.affiliation: Kai Neben, Anna Jauch, Jens Hillengass, Nicola Lehners, Martin Granzow, Marc S. Raab, and Anthony D. Ho, University of Heidelberg; Thomas Hielscher, German Cancer Research Center; and Anja Seckinger, Hartmut Goldschmidt, and Dirk Hose,University of Heidelberg and National Center for Tumor Diseases, Heidelberg, Germany.
authors.forename: Kai
authors.initials: K
authors.lastname: Neben
authors.forename: Anna
authors.initials: A
authors.lastname: Jauch
authors.forename: Thomas
authors.initials: T
authors.lastname: Hielscher
authors.forename: Jens
authors.initials: J
authors.lastname: Hillengass
authors.forename: Nicola
authors.initials: N
authors.lastname: Lehners
authors.forename: Anja
authors.initials: A
authors.lastname: Seckinger
authors.forename: Martin
authors.initials: M
authors.lastname: Granzow
authors.forename: Marc S
authors.initials: MS
authors.lastname: Raab
authors.forename: Anthony D
authors.initials: AD
authors.lastname: Ho
authors.forename: Hartmut
authors.initials: H
authors.lastname: Goldschmidt
authors.forename: Dirk
authors.initials: D
authors.lastname: Hose
mesh_terms: D002872:Chromosome Deletion; D002878:Chromosomes, Human, Pair 1; D002883:Chromosomes, Human, Pair 14; D002886:Chromosomes, Human, Pair 17; D002894:Chromosomes, Human, Pair 4; D018450:Disease Progression; D020022:Genetic Predisposition to Disease; D006801:Humans; D017404:In Situ Hybridization, Fluorescence; D009101:Multiple Myeloma / Q000235:genetics* / Q000473:pathology*; D015999:Multivariate Analysis; D010641:Phenotype; D011003:Ploidies; D016016:Proportional Hazards Models; D012307:Risk Factors; D014178:Translocation, Genetic; D047368:Tumor Burden