Current Hematologic Malignancy Reports

, Volume 11, Issue 2, pp 137–147 | Cite as

Risk Stratification in Multiple Myeloma

  • Melissa Gaik-Ming OoiEmail author
  • Sanjay de Mel
  • Wee Joo Chng
Multiple Myeloma (P Kapoor, Section Editor)
Part of the following topical collections:
  1. Topical Collection on Multiple Myeloma


There are many prognostic variables in multiple myeloma and the difficulty is in deciding which is truly significant. The widely used International Staging System (ISS) does not incorporate genetics, age, and other important variables in its risk stratification. Although it has its own limitations, the recently published Revised International Staging System (R-ISS) that was built upon the framework of ISS, is a more comprehensive and predictive tool for multiple myeloma patients and should be henceforth utilised. We will review the current prognostic variables and their significance in this paper.


International Staging System Multiple Myeloma Chromosomal Abnormalities Risk 


Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no competing interests.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.


Paper of particular interest, published recently, have been highlighted as: •• Of major importance

  1. 1.
    Avet-Loiseau H, Li C, Magrangeas F, Gouraud W, Charbonnel C, Harousseau J-L, et al. Prognostic significance of copy-number alterations in multiple myeloma. J Clin Oncol Off J Am Soc Clin Oncol. 2009;27(27):4585–90. doi: 10.1200/jco.2008.20.6136.CrossRefGoogle Scholar
  2. 2.
    Debes-Marun CS, Dewald GW, Bryant S, Picken E, Santana-Dávila R, González-Paz N, et al. Chromosome abnormalities clustering and its implications for pathogenesis and prognosis in myeloma. Leukemia. 2003;17(2):427–36. doi: 10.1038/sj.leu.2402797.PubMedCrossRefGoogle Scholar
  3. 3.
    Fonseca R, Debes-Marun CS, Picken EB, Dewald GW, Bryant SC, Winkler JM, et al. The recurrent IgH translocations are highly associated with nonhyperdiploid variant multiple myeloma. Blood. 2003;102(7):2562–7. doi: 10.1182/blood-2003-02-0493.PubMedCrossRefGoogle Scholar
  4. 4.
    Smadja NV, Leroux D, Soulier J, Dumont S, Arnould C, Taviaux S, et al. Further cytogenetic characterization of multiple myeloma confirms that 14q32 translocations are a very rare event in hyperdiploid cases. Genes Chromosomes Cancer. 2003;38(3):234–9. doi: 10.1002/gcc.10275.PubMedCrossRefGoogle Scholar
  5. 5.
    Brousseau M, Leleu X, Gerard J, Gastinne T, Godon A, Genevieve F, et al. Hyperdiploidy is a common finding in monoclonal gammopathy of undetermined significance and monosomy 13 is restricted to these hyperdiploid patients. Clin Cancer Res. 2007;13(20):6026–31. doi: 10.1158/1078-0432.ccr-07-0031.PubMedCrossRefGoogle Scholar
  6. 6.
    Chng WJ, Van Wier SA, Ahmann GJ, Winkler JM, Jalal SM, Bergsagel PL, et al. A validated FISH trisomy index demonstrates the hyperdiploid and nonhyperdiploid dichotomy in MGUS. Blood. 2005;106(6):2156–61. doi: 10.1182/blood-2005-02-0761.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Chng WJ, Santana-Davila R, Van Wier SA, Ahmann GJ, Jalal SM, Bergsagel PL, et al. Prognostic factors for hyperdiploid-myeloma: effects of chromosome 13 deletions and IgH translocations. Leukemia. 2006;20(5):807–13. doi: 10.1038/sj.leu.2404172.PubMedCrossRefGoogle Scholar
  8. 8.
    Pawlyn C, Melchor L, Murison A, Wardell CP, Brioli A, Boyle EM, et al. Coexistent hyperdiploidy does not abrogate poor prognosis in myeloma with adverse cytogenetics and may precede IGH translocations. Blood. 2015;125(5):831–40. doi: 10.1182/blood-2014-07-584268.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Kumar S, Fonseca R, Ketterling RP, Dispenzieri A, Lacy MQ, Gertz MA, et al. Trisomies in multiple myeloma: impact on survival in patients with high-risk cytogenetics. Blood. 2012;119(9):2100–5. doi: 10.1182/blood-2011-11-390658.PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Avet-Loiseau H, Attal M, Moreau P, Charbonnel C, Garban F, Hulin C, et al. Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myélome. Blood. 2007;109(8):3489–95. doi: 10.1182/blood-2006-08-040410.PubMedCrossRefGoogle Scholar
  11. 11.
    Avet-Loiseau H, Durie BGM, Cavo M, Attal M, Gutierrez N, Haessler J, et al. Combining fluorescent in situ hybridization data with ISS staging improves risk assessment in myeloma: an International Myeloma Working Group collaborative project. Leukemia. 2013;27(3):711–7. doi: 10.1038/leu.2012.282.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Avet-Loiseau H, Facon T, Grosbois B, Magrangeas F, Rapp M-J, Harousseau J-L, et al. Oncogenesis of multiple myeloma: 14q32 and 13q chromosomal abnormalities are not randomly distributed, but correlate with natural history, immunological features, and clinical presentation. Blood. 2002;99(6):2185–91.PubMedCrossRefGoogle Scholar
  13. 13.
    Chang H, Sloan S, Li D, Keith Stewart A. Multiple myeloma involving central nervous system: high frequency of chromosome 17p13.1 (p53) deletions. Br J Haematol. 2004;127(3):280–4. doi: 10.1111/j.1365-2141.2004.05199.x.PubMedCrossRefGoogle Scholar
  14. 14.
    Fonseca R, Blood E, Rue M, Harrington D, Oken MM, Kyle RA, et al. Clinical and biologic implications of recurrent genomic aberrations in myeloma. Blood. 2003;101(11):4569–75. doi: 10.1182/blood-2002-10-3017.PubMedCrossRefGoogle Scholar
  15. 15.
    Keats JJ, Reiman T, Maxwell CA, Taylor BJ, Larratt LM, Mant MJ, et al. In multiple myeloma, t(4;14)(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood. 2003;101(4):1520–9. doi: 10.1182/blood-2002-06-1675.PubMedCrossRefGoogle Scholar
  16. 16.
    Pineda-Roman M, Zangari M, van Rhee F, Anaissie E, Szymonifka J, Hoering A, et al. VTD combination therapy with bortezomib-thalidomide-dexamethasone is highly effective in advanced and refractory multiple myeloma. Leukemia. 2008;22(7):1419–27. doi: 10.1038/leu.2008.99.PubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Shaughnessy Jr JD, Zhan F, Burington BE, Huang Y, Colla S, Hanamura I, et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood. 2007;109(6):2276–84. doi: 10.1182/blood-2006-07-038430.PubMedCrossRefGoogle Scholar
  18. 18.
    Nemec P, Zemanova Z, Kuglik P, Michalova K, Tajtlova J, Kaisarova P, et al. Complex karyotype and translocation t(4;14) define patients with high-risk newly diagnosed multiple myeloma: results of CMG2002 trial. Leuk Lymphoma. 2012;53(5):920–7. doi: 10.3109/10428194.2011.634042.PubMedCrossRefGoogle Scholar
  19. 19.
    Chesi M, Nardini E, Brents LA, Schröck E, Ried T, Kuehl WM, et al. Frequent translocation t(4;14)(p16.3;q32.3) in multiple myeloma is associated with increased expression and activating mutations of fibroblast growth factor receptor 3. Nat Genet. 1997;16(3):260–4. doi: 10.1038/ng0797-260.PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Chesi M, Bergsagel PL, Shonukan OO, Martelli ML, Brents LA, Chen T, et al. Frequent dysregulation of the c-maf proto-oncogene at 16q23 by translocation to an Ig locus in multiple myeloma. Blood. 1998;91(12):4457–63.PubMedGoogle Scholar
  21. 21.
    Boersma-Vreugdenhil GR, Kuipers J, Van Stralen E, Peeters T, Michaux L, Hagemeijer A, et al. The recurrent translocation t(14;20)(q32;q12) in multiple myeloma results in aberrant expression of MAFB: a molecular and genetic analysis of the chromosomal breakpoint. Br J Haematol. 2004;126(3):355–63. doi: 10.1111/j.1365-2141.2004.05050.x.PubMedCrossRefGoogle Scholar
  22. 22.
    Ross FM, Chiecchio L, Dagrada G, Protheroe RK, Stockley DM, Harrison CJ, et al. The t(14;20) is a poor prognostic factor in myeloma but is associated with long-term stable disease in monoclonal gammopathies of undetermined significance. Haematologica. 2010;95(7):1221–5. doi: 10.3324/haematol.2009.016329.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Vekemans MC, Lemmens H, Delforge M, Doyen C, Pierre P, Demuynck H, et al. The t(14;20)(q32;q12): a rare cytogenetic change in multiple myeloma associated with poor outcome. Br J Haematol. 2010;149(6):901–4. doi: 10.1111/j.1365-2141.2010.08113.x.PubMedCrossRefGoogle Scholar
  24. 24.
    Chang H, Qi C, Yi Q-L, Reece D, Stewart AK. p53 gene deletion detected by fluorescence in situ hybridization is an adverse prognostic factor for patients with multiple myeloma following autologous stem cell transplantation. Blood. 2005;105(1):358–60. doi: 10.1182/blood-2004-04-1363.PubMedCrossRefGoogle Scholar
  25. 25.
    Calasanz MJ, Cigudosa JC, Odero MD, García-Foncillas J, Marín J, Ardanaz MT, et al. Hypodiploidy and 22q11 rearrangements at diagnosis are associated with poor prognosis in patients with multiple myeloma. Br J Haematol. 1997;98(2):418–25.PubMedCrossRefGoogle Scholar
  26. 26.
    Fassas AB-T, Spencer T, Sawyer J, Zangari M, Lee C-K, Anaissie E, et al. Both hypodiploidy and deletion of chromosome 13 independently confer poor prognosis in multiple myeloma. Br J Haematol. 2002;118(4):1041–7.PubMedCrossRefGoogle Scholar
  27. 27.
    Smadja NV, Bastard C, Brigaudeau C, Leroux D, Fruchart C, Hématologique GFdC. Hypodiploidy is a major prognostic factor in multiple myeloma. Blood. 2001;98(7):2229–38.PubMedCrossRefGoogle Scholar
  28. 28.
    Van Wier S, Braggio E, Baker A, Ahmann G, Levy J, Carpten JD, et al. Hypodiploid multiple myeloma is characterized by more aggressive molecular markers than non-hyperdiploid multiple myeloma. Haematologica. 2013;98(10):1586–92. doi: 10.3324/haematol.2012.081083.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Oh S, Koo DH, Kwon MJ, Kim K, Suh C, Min CK, et al. Chromosome 13 deletion and hypodiploidy on conventional cytogenetics are robust prognostic factors in Korean multiple myeloma patients: web-based multicenter registry study. Ann Hematol. 2014;93(8):1353–61. doi: 10.1007/s00277-014-2057-5.PubMedCrossRefGoogle Scholar
  30. 30.
    Decaux O, Lode L, Magrangeas F, Charbonnel C, Gouraud W, Jezequel P, et al. Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myelome. J Clin Oncol Off J Am Soc Clin Oncol. 2008;26(29):4798–805. doi: 10.1200/jco.2007.13.8545.CrossRefGoogle Scholar
  31. 31.
    Johnson SK, Heuck CJ, Albino AP, Qu P, Zhang Q, Barlogie B, et al. The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma. Int J Hematol. 2011;94(4):321–33. doi: 10.1007/s12185-011-0948-y.PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Hanamura I, Stewart JP, Huang Y, Zhan F, Santra M, Sawyer JR, et al. Frequent gain of chromosome band 1q21 in plasma-cell dyscrasias detected by fluorescence in situ hybridization: incidence increases from MGUS to relapsed myeloma and is related to prognosis and disease progression following tandem stem-cell transplantation. Blood. 2006;108(5):1724–32. doi: 10.1182/blood-2006-03-009910.PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    Rosiñol L, Carrió A, Bladé J, Queralt R, Aymerich M, Cibeira MT, et al. Comparative genomic hybridisation identifies two variants of smoldering multiple myeloma. Br J Haematol. 2005;130(5):729–32. doi: 10.1111/j.1365-2141.2005.05673.x.PubMedCrossRefGoogle Scholar
  34. 34.
    Carew JS, Nawrocki ST, Krupnik YV, Dunner K, McConkey DJ, Keating MJ, et al. Targeting endoplasmic reticulum protein transport: a novel strategy to kill malignant B cells and overcome fludarabine resistance in CLL. Blood. 2006;107(1):222–31. doi: 10.1182/blood-2005-05-1923.PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Fabris S, Ronchetti D, Agnelli L, Baldini L, Morabito F, Bicciato S, et al. Transcriptional features of multiple myeloma patients with chromosome 1q gain. Leukemia. 2007;21(5):1113–6. doi: 10.1038/sj.leu.2404616.PubMedGoogle Scholar
  36. 36.
    Kaiser MF, Johnson DC, Wu P, Walker BA, Brioli A, Mirabella F, et al. Global methylation analysis identifies prognostically important epigenetically inactivated tumor suppressor genes in multiple myeloma. Blood. 2013;122(2):219–26. doi: 10.1182/blood-2013-03-487884.PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Andrulis M, Lehners N, Capper D, Penzel R, Heining C, Huellein J, et al. Targeting the BRAF V600E mutation in multiple myeloma. Canc Discov. 2013;3(8):862–9. doi: 10.1158/2159-8290.CD-13-0014.CrossRefGoogle Scholar
  38. 38.
    Bohn OL, Hsu K, Hyman DM, Pignataro DS, Giralt S, Teruya-Feldstein J. BRAF V600E mutation and clonal evolution in a patient with relapsed refractory myeloma with plasmablastic differentiation. Clin Lymphoma Myeloma Leuk. 2014;14(2):e65–8. doi: 10.1016/j.clml.2013.12.003.PubMedCrossRefGoogle Scholar
  39. 39.
    Sharman JP, Chmielecki J, Morosini D, Palmer GA, Ross JS, Stephens PJ, et al. Vemurafenib response in 2 patients with posttransplant refractory BRAF V600E-mutated multiple myeloma. Clin Lymphoma Myeloma Leuk. 2014;14(5):e161–3. doi: 10.1016/j.clml.2014.06.004.PubMedCrossRefGoogle Scholar
  40. 40.
    Usmani SZ, Mitchell A, Waheed S, Crowley J, Hoering A, Petty N, et al. Prognostic implications of serial 18-fluoro-deoxyglucose emission tomography in multiple myeloma treated with total therapy 3. Blood. 2013;121(10):1819–23. doi: 10.1182/blood-2012-08-451690.PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Lopez-Anglada L, Gutierrez NC, Garcia JL, Mateos MV, Flores T, San Miguel JF. P53 deletion may drive the clinical evolution and treatment response in multiple myeloma. Eur J Haematol. 2010;84(4):359–61. doi: 10.1111/j.1600-0609.2009.01399.x.PubMedCrossRefGoogle Scholar
  42. 42.
    Tiedemann RE, Gonzalez-Paz N, Kyle RA, Santana-Davila R, Price-Troska T, Van Wier SA, et al. Genetic aberrations and survival in plasma cell leukemia. Leukemia. 2008;22(5):1044–52. doi: 10.1038/leu.2008.4.PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Fassas AB, Ward S, Muwalla F, Van Hemert R, Schluterman K, Harik S, et al. Myeloma of the central nervous system: strong association with unfavorable chromosomal abnormalities and other high-risk disease features. Leuk Lymphoma. 2004;45(2):291–300.PubMedCrossRefGoogle Scholar
  44. 44.
    Rasche L, Bernard C, Topp MS, Kapp M, Duell J, Wesemeier C, et al. Features of extramedullary myeloma relapse: high proliferation, minimal marrow involvement, adverse cytogenetics: a retrospective single-center study of 24 cases. Ann Hematol. 2012;91(7):1031–7. doi: 10.1007/s00277-012-1414-5.PubMedCrossRefGoogle Scholar
  45. 45.
    Terpos E, Rezvani K, Basu S, Milne AE, Rose PE, Scott GL, et al. Plasmacytoma relapses in the absence of systemic progression post-high-dose therapy for multiple myeloma. Eur J Haematol. 2005;75(5):376–83. doi: 10.1111/j.1600-0609.2005.00531.x.PubMedCrossRefGoogle Scholar
  46. 46.
    Varettoni M, Corso A, Pica G, Mangiacavalli S, Pascutto C, Lazzarino M. Incidence, presenting features and outcome of extramedullary disease in multiple myeloma: a longitudinal study on 1003 consecutive patients. Ann Oncol. 2010;21(2):325–30. doi: 10.1093/annonc/mdp329.PubMedCrossRefGoogle Scholar
  47. 47.
    Chang H, Sloan S, Li D, Patterson B. Genomic aberrations in plasma cell leukemia shown by interphase fluorescence in situ hybridization. Cancer Genet Cytogenet. 2005;156(2):150–3. doi: 10.1016/j.cancergencyto.2004.05.004.PubMedCrossRefGoogle Scholar
  48. 48.
    Avet-Loiseau H, Roussel M, Campion L, Leleu X, Marit G, Jardel H, et al. Cytogenetic and therapeutic characterization of primary plasma cell leukemia: the IFM experience. Leukemia. 2012;26(1):158–9. doi: 10.1038/leu.2011.176.PubMedCrossRefGoogle Scholar
  49. 49.••
    Rajkumar SV, Dimopoulos MA, Palumbo A, Blade J, Merlini G, Mateos MV, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. 2014;15(12):e538–48. doi: 10.1016/s1470-2045(14)70442-5. This article is an update of the criteria for the diagnosis of MM. The revised criteria makes the diagnosis of MM earlier. PubMedCrossRefGoogle Scholar
  50. 50.
    Song IC, Kim JN, Choi YS, Ryu H, Lee MW, Lee HJ, et al. Diagnostic and prognostic implications of spine magnetic resonance imaging at diagnosis in patients with multiple myeloma. Cancer Res Treat. 2015;47(3):465–72. doi: 10.4143/crt.2014.010.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Walker R, Barlogie B, Haessler J, Tricot G, Anaissie E, Shaughnessy JD, et al. Magnetic resonance imaging in multiple myeloma: diagnostic and clinical implications. J Clin Oncol Off J Am Soc Clin Oncol. 2007;25(9):1121–8. doi: 10.1200/jco.2006.08.5803.CrossRefGoogle Scholar
  52. 52.
    Dimopoulos MA, Hillengass J, Usmani S, Zamagni E, Lentzsch S, Davies FE, et al. Role of magnetic resonance imaging in the management of patients with multiple myeloma: a consensus statement. J Clin Oncol Off J Am Soc Clin Oncol. 2015;33(6):657–64. doi: 10.1200/JCO.2014.57.9961.CrossRefGoogle Scholar
  53. 53.
    Hillengass J, Ayyaz S, Kilk K, Weber MA, Hielscher T, Shah R, et al. Changes in magnetic resonance imaging before and after autologous stem cell transplantation correlate with response and survival in multiple myeloma. Haematologica. 2012;97(11):1757–60. doi: 10.3324/haematol.2012.065359.PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Bannas P, Hentschel HB, Bley TA, Treszl A, Eulenburg C, Derlin T, et al. Diagnostic performance of whole-body MRI for the detection of persistent or relapsing disease in multiple myeloma after stem cell transplantation. Eur Radiol. 2012;22(9):2007–12. doi: 10.1007/s00330-012-2445-y.PubMedCrossRefGoogle Scholar
  55. 55.
    Baur A, Stäbler A, Nagel D, Lamerz R, Bartl R, Hiller E, et al. Magnetic resonance imaging as a supplement for the clinical staging system of Durie and Salmon? Cancer. 2002;95(6):1334–45. doi: 10.1002/cncr.10818.PubMedCrossRefGoogle Scholar
  56. 56.
    Moulopoulos LA, Gika D, Anagnostopoulos A, Delasalle K, Weber D, Alexanian R, et al. Prognostic significance of magnetic resonance imaging of bone marrow in previously untreated patients with multiple myeloma. Ann Oncol. 2005;16(11):1824–8. doi: 10.1093/annonc/mdi362.PubMedCrossRefGoogle Scholar
  57. 57.
    Stäbler A, Baur A, Bartl R, Munker R, Lamerz R, Reiser MF. Contrast enhancement and quantitative signal analysis in MR imaging of multiple myeloma: assessment of focal and diffuse growth patterns in marrow correlated with biopsies and survival rates. AJR Am J Roentgenol. 1996;167(4):1029–36. doi: 10.2214/ajr.167.4.8819407.PubMedCrossRefGoogle Scholar
  58. 58.
    Moulopoulos LA, Dimopoulos MA, Kastritis E, Christoulas D, Gkotzamanidou M, Roussou M, et al. Diffuse pattern of bone marrow involvement on magnetic resonance imaging is associated with high risk cytogenetics and poor outcome in newly diagnosed, symptomatic patients with multiple myeloma: a single center experience on 228 patients. Am J Hematol. 2012;87(9):861–4. doi: 10.1002/ajh.23258.PubMedCrossRefGoogle Scholar
  59. 59.
    Derlin T, Peldschus K, Munster S, Bannas P, Herrmann J, Stubig T, et al. Comparative diagnostic performance of (1)(8)F-FDG PET/CT versus whole-body MRI for determination of remission status in multiple myeloma after stem cell transplantation. Eur Radiol. 2013;23(2):570–8. doi: 10.1007/s00330-012-2600-5.PubMedCrossRefGoogle Scholar
  60. 60.
    Nanni C, Zamagni E, Celli M, Caroli P, Ambrosini V, Tacchetti P, et al. The value of 18F-FDG PET/CT after autologous stem cell transplantation (ASCT) in patients affected by multiple myeloma (MM): experience with 77 patients. Clin Nucl Med. 2013;38(2):e74–9. doi: 10.1097/RLU.0b013e318266cee2.PubMedCrossRefGoogle Scholar
  61. 61.
    Zamagni E, Patriarca F, Nanni C, Zannetti B, Englaro E, Pezzi A, et al. Prognostic relevance of 18-F FDG PET/CT in newly diagnosed multiple myeloma patients treated with up-front autologous transplantation. Blood. 2011;118(23):5989–95. doi: 10.1182/blood-2011-06-361386.PubMedCrossRefGoogle Scholar
  62. 62.
    Bartel TB, Haessler J, Brown TLY, Shaughnessy JD, van Rhee F, Anaissie E, et al. F18-fluorodeoxyglucose positron emission tomography in the context of other imaging techniques and prognostic factors in multiple myeloma. Blood. 2009;114(10):2068–76. doi: 10.1182/blood-2009-03-213280.PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Haznedar R, Aki SZ, Akdemir OU, Ozkurt ZN, Ceneli O, Yagci M, et al. Value of 18F-fluorodeoxyglucose uptake in positron emission tomography/computed tomography in predicting survival in multiple myeloma. Eur J Nucl Med Mol Imaging. 2011;38(6):1046–53. doi: 10.1007/s00259-011-1738-8.PubMedCrossRefGoogle Scholar
  64. 64.
    Greipp PR, San Miguel J, Durie BG, Crowley JJ, Barlogie B, Blade J, et al. International staging system for multiple myeloma. J Clin Oncol. 2005;23(15):3412–20. doi: 10.1200/jco.2005.04.242.PubMedCrossRefGoogle Scholar
  65. 65.
    Gkotzamanidou M, Kastritis E, Gavriatopoulou MR, Nikitas N, Gika D, Mparmparousi D, et al. Increased serum lactate dehydrongenase should be included among the variables that define very-high-risk multiple myeloma. Clin Lymphoma Myeloma Leuk. 2011;11(5):409–13. doi: 10.1016/j.clml.2011.07.001.PubMedCrossRefGoogle Scholar
  66. 66.
    Terpos E, Katodritou E, Roussou M, Pouli A, Michalis E, Delimpasi S, et al. High serum lactate dehydrogenase adds prognostic value to the international myeloma staging system even in the era of novel agents. Eur J Haematol. 2010;85(2):114–9. doi: 10.1111/j.1600-0609.2010.01466.x.PubMedGoogle Scholar
  67. 67.
    Ferro DP, Falconi MA, Adam RL, Ortega MM, Lima CP, de Souza CA, et al. Fractal characteristics of May-Grunwald-Giemsa stained chromatin are independent prognostic factors for survival in multiple myeloma. PLoS One. 2011;6(6), e20706. doi: 10.1371/journal.pone.0020706.PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    Dispenzieri A, Zhang L, Katzmann JA, Snyder M, Blood E, Degoey R, et al. Appraisal of immunoglobulin free light chain as a marker of response. Blood. 2008;111(10):4908–15. doi: 10.1182/blood-2008-02-138602.PubMedPubMedCentralCrossRefGoogle Scholar
  69. 69.
    Snozek CL, Katzmann JA, Kyle RA, Dispenzieri A, Larson DR, Therneau TM, et al. Prognostic value of the serum free light chain ratio in newly diagnosed myeloma: proposed incorporation into the international staging system. Leukemia. 2008;22(10):1933–7. doi: 10.1038/leu.2008.171.PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Kyrtsonis MC, Vassilakopoulos TP, Kafasi N, Sachanas S, Tzenou T, Papadogiannis A, et al. Prognostic value of serum free light chain ratio at diagnosis in multiple myeloma. Br J Haematol. 2007;137(3):240–3. doi: 10.1111/j.1365-2141.2007.06561.x.PubMedCrossRefGoogle Scholar
  71. 71.
    van Rhee F, Bolejack V, Hollmig K, Pineda-Roman M, Anaissie E, Epstein J, et al. High serum-free light chain levels and their rapid reduction in response to therapy define an aggressive multiple myeloma subtype with poor prognosis. Blood. 2007;110(3):827–32. doi: 10.1182/blood-2007-01-067728.PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    Khoriaty R, Hussein MA, Faiman B, Kelly M, Kalaycio M, Baz R. Prediction of response and progression in multiple myeloma with serum free light chains assay: corroboration of the serum free light chain response definitions. Clin Lymphoma Myeloma Leuk. 2010;10(1):E10–3. doi: 10.3816/CLML.2010.n.010.PubMedCrossRefGoogle Scholar
  73. 73.
    Sthaneshwar P, Nadarajan V, Maniam JA, Nordin N, Gin Gin G. Serum free light chains: diagnostic and prognostic value in multiple myeloma. Clin Chem Lab Med. 2009;47(9):1101–7. doi: 10.1515/cclm.2009.260.PubMedCrossRefGoogle Scholar
  74. 74.
    Deng SH, Xu Y, Mai YJ, Wang YF, Zhao YZ, Zou DH, et al. Analysis of the international staging system of multiple myeloma and its comparison with the DS and IFM staging system in 122 Chinese patients. Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi. 2008;29(4):217–21.PubMedGoogle Scholar
  75. 75.
    Xu Y, Sui W, Deng S, An G, Wang Y, Xie Z, et al. Further stratification of patients with multiple myeloma by International Staging System in combination with ratio of serum free kappa to lambda light chains. Leuk Lymphoma. 2013;54(1):123–32. doi: 10.3109/10428194.2012.704033.PubMedCrossRefGoogle Scholar
  76. 76.
    Bradwell AR, Harding SJ, Fourrier NJ, Wallis GLF, Drayson MT, Carr-Smith HD, et al. Assessment of monoclonal gammopathies by nephelometric measurement of individual immunoglobulin kappa/lambda ratios. Clin Chem. 2009;55(9):1646–55. doi: 10.1373/clinchem.2009.123828.PubMedCrossRefGoogle Scholar
  77. 77.
    Bradwell A, Harding S, Fourrier N, Mathiot C, Attal M, Moreau P, et al. Prognostic utility of intact immunoglobulin Ig‘kappa/Ig’lambda ratios in multiple myeloma patients. Leukemia. 2013;27(1):202–7. doi: 10.1038/leu.2012.159.PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Ludwig H, Milosavljevic D, Zojer N, Faint JM, Bradwell AR, Hübl W, et al. Immunoglobulin heavy/light chain ratios improve paraprotein detection and monitoring, identify residual disease and correlate with survival in multiple myeloma patients. Leukemia. 2013;27(1):213–9. doi: 10.1038/leu.2012.197.PubMedPubMedCentralCrossRefGoogle Scholar
  79. 79.
    Koulieris E, Panayiotidis P, Harding SJ, Kafasi N, Maltezas D, Bartzis V, et al. Ratio of involved/uninvolved immunoglobulin quantification by Hevylite™ assay: clinical and prognostic impact in multiple myeloma. Exp Hematol Oncol. 2012;1(1):9. doi: 10.1186/2162-3619-1-9.PubMedPubMedCentralCrossRefGoogle Scholar
  80. 80.
    Batinić J, Perić Z, Šegulja D, Last J, Prijić S, Dubravčić K, et al. Immunoglobulin heavy/light chain analysis enhances the detection of residual disease and monitoring of multiple myeloma patients. Croat Med J. 2015;56(3):263–71.PubMedPubMedCentralCrossRefGoogle Scholar
  81. 81.
    Beaumont-Epinette MP, Moreau C, Besnard S, Latute F, Collet N, Sebillot M, et al. Heavy/light chain specific immunoglobulin ratios provides no additional information than serum proteins electrophoresis and immunofixation for the diagnosis and the follow-up of intact immunoglobulin multiple myeloma patients. Pathol Biol. 2015;63(4-5):215–21. doi: 10.1016/j.patbio.2015.06.001.PubMedCrossRefGoogle Scholar
  82. 82.
    Tovar N, Fernández de Larrea C, Elena M, Cibeira MT, Aróstegui JI, Rosiñol L, et al. Prognostic impact of serum immunoglobulin heavy/light chain ratio in patients with multiple myeloma in complete remission after autologous stem cell transplantation. Biol Blood Marrow Transplant. 2012;18(7):1076–9. doi: 10.1016/j.bbmt.2012.03.004.PubMedCrossRefGoogle Scholar
  83. 83.
    Dimopoulos MA, Kastritis E, Delimpasi S, Katodritou E, Hatzimichael E, Kyrtsonis M-C, et al. Multiple myeloma in octogenarians: clinical features and outcome in the novel agent era. Eur J Haematol. 2012;89(1):10–5. doi: 10.1111/j.1600-0609.2012.01784.x.PubMedCrossRefGoogle Scholar
  84. 84.
    Bringhen S, Mateos MV, Zweegman S, Larocca A, Falcone AP, Oriol A, et al. Age and organ damage correlate with poor survival in myeloma patients: meta-analysis of 1435 individual patient data from 4 randomized trials. Haematologica. 2013;98(6):980–7. doi: 10.3324/haematol.2012.075051.PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    San Miguel JF, Sànchez J, Gonzalez M. Prognostic factors and classification in multiple myeloma. Br J Cancer. 1989;59(1):113–8.PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Chretien ML, Hebraud B, Cances-Lauwers V, Hulin C, Marit G, Leleu X, et al. Age is a prognostic factor even among patients with multiple myeloma younger than 66 years treated with high-dose melphalan: the IFM experience on 2316 patients. Haematologica. 2014;99(7):1236–8. doi: 10.3324/haematol.2013.098608.PubMedPubMedCentralCrossRefGoogle Scholar
  87. 87.
    Hamaker ME, Jonker JM, de Rooij SE, Vos AG, Smorenburg CH, van Munster BC. Frailty screening methods for predicting outcome of a comprehensive geriatric assessment in elderly patients with cancer: a systematic review. Lancet Oncol. 2012;13(10):e437–44. doi: 10.1016/s1470-2045(12)70259-0.PubMedCrossRefGoogle Scholar
  88. 88.
    Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752–62. doi: 10.1016/s0140-6736(12)62167-9.PubMedCrossRefGoogle Scholar
  89. 89.
    Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146–56.PubMedCrossRefGoogle Scholar
  90. 90.
    Slaets JPJ. Vulnerability in the elderly: frailty. Med Clin North Am. 2006;90(4):593–601. doi: 10.1016/j.mcna.2006.05.008.PubMedCrossRefGoogle Scholar
  91. 91.
    Harousseau J-L, Avet-Loiseau H, Attal M, Charbonnel C, Garban F, Hulin C, et al. Achievement of at least very good partial response is a simple and robust prognostic factor in patients with multiple myeloma treated with high-dose therapy: long-term analysis of the IFM 99-02 and 99-04 Trials. J Clin Oncol Off J Am Soc Clin Oncol. 2009;27(34):5720–6. doi: 10.1200/jco.2008.21.1060.CrossRefGoogle Scholar
  92. 92.
    Lahuerta JJ, Mateos MV, Martínez-López J, Rosiñol L, Sureda A, de la Rubia J, et al. Influence of pre- and post-transplantation responses on outcome of patients with multiple myeloma: sequential improvement of response and achievement of complete response are associated with longer survival. J Clin Oncol Off J Am Soc Clin Oncol. 2008;26(35):5775–82. doi: 10.1200/jco.2008.17.9721.CrossRefGoogle Scholar
  93. 93.
    Moreau P, Attal M, Pégourié B, Planche L, Hulin C, Facon T, et al. Achievement of VGPR to induction therapy is an important prognostic factor for longer PFS in the IFM 2005-01 trial. Blood. 2011;117(11):3041–4. doi: 10.1182/blood-2010-08-300863.PubMedCrossRefGoogle Scholar
  94. 94.
    Gay F, Larocca A, Wijermans P, Cavallo F, Rossi D, Schaafsma R, et al. Complete response correlates with long-term progression-free and overall survival in elderly myeloma treated with novel agents: analysis of 1175 patients. Blood. 2011;117(11):3025–31. doi: 10.1182/blood-2010-09-307645.PubMedCrossRefGoogle Scholar
  95. 95.
    Barlogie B, Anaissie E, Haessler J, van Rhee F, Pineda-Roman M, Hollmig K, et al. Complete remission sustained 3 years from treatment initiation is a powerful surrogate for extended survival in multiple myeloma. Cancer. 2008;113(2):355–9. doi: 10.1002/cncr.23546.PubMedCrossRefGoogle Scholar
  96. 96.
    Hoering A, Crowley J, Shaughnessy JD, Hollmig K, Alsayed Y, Szymonifka J, et al. Complete remission in multiple myeloma examined as time-dependent variable in terms of both onset and duration in Total Therapy protocols. Blood. 2009;114(7):1299–305. doi: 10.1182/blood-2009-03-211953.PubMedPubMedCentralCrossRefGoogle Scholar
  97. 97.
    Ong S, Widanalage S, Chen YX, Ooi MG, Surendran S, Koh LP, et al. Early relapse post autologous transplant is a stronger predictor of survival compared to pretreatment patient factors in the novel agent era - Analysis of Singapore Multiple Myeloma Working Group. 2015.Google Scholar
  98. 98.
    Durie B, Harousseau J, Miguel J, Blade J, Barlogie B, Anderson K, et al. International uniform response criteria for multiple myeloma. Leukemia. 2006;20(9):1467–73.PubMedCrossRefGoogle Scholar
  99. 99.
    Kapoor P, Kumar SK, Dispenzieri A, Lacy MQ, Buadi F, Dingli D, et al. Importance of achieving stringent complete response after autologous stem-cell transplantation in multiple myeloma. J Clin Oncol Off J Am Soc Clin Oncol. 2013;31(36):4529–35. doi: 10.1200/jco.2013.49.0086.CrossRefGoogle Scholar
  100. 100.
    Kroger N, Asenova S, Gerritzen A, Bacher U, Zander A. Questionable role of free light chain assay ratio to determine stringent complete remission in multiple myeloma patients. Blood. 2010;115(16):3413–4. doi: 10.1182/blood-2010-01-261677. author reply 3414-3415.PubMedCrossRefGoogle Scholar
  101. 101.
    Paiva B, Martinez-Lopez J, Vidriales MB, Mateos MV, Montalban MA, Fernandez-Redondo E, et al. Comparison of immunofixation, serum free light chain, and immunophenotyping for response evaluation and prognostication in multiple myeloma. J Clin Oncol Off J Am Soc Clin Oncol. 2011;29(12):1627–33. doi: 10.1200/jco.2010.33.1967.CrossRefGoogle Scholar
  102. 102.
    Martinez-Lopez J, Paiva B, Lopez-Anglada L, Mateos MV, Cedena T, Vidriales MB, et al. Critical analysis of the stringent complete response in multiple myeloma: contribution of sFLC and bone marrow clonality. Blood. 2015;126(7):858–62. doi: 10.1182/blood-2015-04-638742.PubMedPubMedCentralCrossRefGoogle Scholar
  103. 103.
    de Larrea CF, Cibeira MT, Elena M, Arostegui JI, Rosinol L, Rovira M, et al. Abnormal serum free light chain ratio in patients with multiple myeloma in complete remission has strong association with the presence of oligoclonal bands: implications for stringent complete remission definition. Blood. 2009;114(24):4954–6. doi: 10.1182/blood-2009-06-224832.PubMedCrossRefGoogle Scholar
  104. 104.
    Paiva B, Gutiérrez NC, Rosiñol L, Vídriales M-B, Montalbán M-Á, Martínez-López J, et al. High-risk cytogenetics and persistent minimal residual disease by multiparameter flow cytometry predict unsustained complete response after autologous stem cell transplantation in multiple myeloma. Blood. 2012;119(3):687–91. doi: 10.1182/blood-2011-07-370460.PubMedCrossRefGoogle Scholar
  105. 105.
    Paiva B, Vidriales M-B, Cerveró J, Mateo G, Pérez JJ, Montalbán MA, et al. Multiparameter flow cytometric remission is the most relevant prognostic factor for multiple myeloma patients who undergo autologous stem cell transplantation. Blood. 2008;112(10):4017–23. doi: 10.1182/blood-2008-05-159624.PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    Kröger N, Badbaran A, Zabelina T, Ayuk F, Wolschke C, Alchalby H, et al. Impact of high-risk cytogenetics and achievement of molecular remission on long-term freedom from disease after autologous-allogeneic tandem transplantation in patients with multiple myeloma. Biol Blood Marrow Transplant. 2013;19(3):398–404. doi: 10.1016/j.bbmt.2012.10.008.PubMedCrossRefGoogle Scholar
  107. 107.
    Ladetto M, Pagliano G, Ferrero S, Cavallo F, Drandi D, Santo L, et al. Major tumor shrinking and persistent molecular remissions after consolidation with bortezomib, thalidomide, and dexamethasone in patients with autografted myeloma. J Clin Oncol. 2010;28(12):2077–84. doi: 10.1200/jco.2009.23.7172.PubMedCrossRefGoogle Scholar
  108. 108.
    Durie BG, Salmon SE. A clinical staging system for multiple myeloma. Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival. Cancer. 1975;36(3):842–54.PubMedCrossRefGoogle Scholar
  109. 109.
    Kimura N, Tokunaga C, Dalal S, Richardson C, Yoshino K, Hara K, et al. A possible linkage between AMP-activated protein kinase (AMPK) and mammalian target of rapamycin (mTOR) signalling pathway. Genes Cells. 2003;8(1):65–79.PubMedCrossRefGoogle Scholar
  110. 110.
    Durie BG, Kyle RA, Belch A, Bensinger W, Blade J, Boccadoro M, et al. Myeloma management guidelines: a consensus report from the Scientific Advisors of the International Myeloma Foundation. Hematol J. 2003;4(6):379–98. doi: 10.1038/sj.thj.6200312.PubMedCrossRefGoogle Scholar
  111. 111.
    Neben K, Lokhorst HM, Jauch A, Bertsch U, Hielscher T, van der Holt B, et al. Administration of bortezomib before and after autologous stem cell transplantation improves outcome in multiple myeloma patients with deletion 17p. Blood. 2012;119(4):940–8. doi: 10.1182/blood-2011-09-379164.PubMedCrossRefGoogle Scholar
  112. 112.
    Kapoor P, Fonseca R, Rajkumar SV, Sinha S, Gertz MA, Stewart AK, et al. Evidence for cytogenetic and fluorescence in situ hybridization risk stratification of newly diagnosed multiple myeloma in the era of novel therapie. Mayo Clin Proc. 2010;85(6):532–7. doi: 10.4065/mcp.2009.0677.PubMedPubMedCentralCrossRefGoogle Scholar
  113. 113.••
    Moreau P, Cavo M, Sonneveld P, Rosinol L, Attal M, Pezzi A, et al. Combination of international scoring system 3, high lactate dehydrogenase, and t(4;14) and/or del(17p) identifies patients with multiple myeloma (MM) treated with front-line autologous stem-cell transplantation at high risk of early MM progression-related death. J Clin Oncol. 2014;32(20):2173–80. doi: 10.1200/jco.2013.53.0329. This article explains the new revised International Staging System.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Melissa Gaik-Ming Ooi
    • 1
    Email author
  • Sanjay de Mel
    • 1
  • Wee Joo Chng
    • 1
  1. 1.SingaporeSingapore

Personalised recommendations