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2011 117: 4696-4700Prepublished online February 3, 2011;doi:10.1182/blood-2010-10-300970 Consensus recommendations for risk stratification in multiple myeloma:
report of the International Myeloma Workshop Consensus Panel 2

Nikhil C. Munshi, Kenneth C. Anderson, P. Leif Bergsagel, John Shaughnessy, Antonio Palumbo,
Brian Durie, Rafael Fonseca, A. Keith Stewart, Jean-Luc Harousseau, Meletios Dimopoulos, Sundar
Jagannath, Roman Hajek, Orhan Sezer, Robert Kyle, Pieter Sonneveld, Michele Cavo, S. Vincent
Rajkumar, Jesus San Miguel, John Crowley, Hervé Avet-Loiseau and on behalf of the International
Myeloma Workshop Consensus Panel 2
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Perspectives
Consensus recommendations for risk stratification in multiple myeloma: report ofthe International Myeloma Workshop Consensus Panel 2 Nikhil C. Munshi,1,2 Kenneth C. Anderson,1 P. Leif Bergsagel,3 John Shaughnessy,4 Antonio Palumbo,5 Brian Durie,6Rafael Fonseca,3 A. Keith Stewart,3 Jean-Luc Harousseau,7 Meletios Dimopoulos,8 Sundar Jagannath,9 Roman Hajek,10Orhan Sezer,11 Robert Kyle,12 Pieter Sonneveld,13 Michele Cavo,14 S. Vincent Rajkumar,12 Jesus San Miguel,15John Crowley,16 and Herve´ Avet-Loiseau,7 on behalf of the International Myeloma Workshop Consensus Panel 2 1Dana-Farber Cancer Institute, Boston, MA; 2Boston Veterans Administration Healthcare System, West Roxbury, MA; 3Mayo Clinic, Scottsdale, AZ; 4University of Arkansas for Medical Sciences, Little Rock, AR; 5University of Torino, Torino, Italy; 6Cedars-Sinai Medical Center, Los Angeles, CA; 7Universitaire de Nantes, Nantes, France; 8University of Athens, Athens, Greece; 9Mt Sinai Medical Center, New York, NY; 10University of Brno, Brno, Czech Republic; 11University Medical Center, Hamburg, Germany; 12Mayo Clinic, Rochester, MN; 13Erasmus MC, Rotterdam, The Netherlands; 14University of Bologna, Bologna, Italy; 15University of Salamanca, Salamanca, Spain; and 16Cancer Research & Biostatistics, Seattle, WA A panel of members of the 2009 Interna-
patients, it is necessary to evaluate for
ties, is not considered a high-risk feature.
tional Myeloma Workshop developed
high-risk features at relapse. Although
High serum ␤2-microglobulin level and Inter-
guidelines for risk stratification in mul-
detection of any cytogenetic abnormality
national Staging System stages II and III,
tiple myeloma. The purpose of risk strati-
is considered to suggest higher-risk dis-
incorporating high ␤2-microglobulin and low
fication is not to decide time of therapy
ease, the specific abnormalities consid-
albumin, are considered to predict higher
but to prognosticate. There is general
ered as poor risk are cytogenetically de-
risk disease. There was a consensus that
consensus that risk stratification is appli-
tected chromosomal 13 or 13q deletion,
the high-risk features will change in the
cable to newly diagnosed patients; how-
t(4;14) and del17p, and detection by fluo-
future, with introduction of other new
ever, some genetic abnormalities charac-
rescence in situ hybridization of t(4;14),
agents or possibly new combinations.
teristic of poor outcome at diagnosis may
t(14;16), and del17p. Detection of 13q
(Blood. 2011;117(18):4696-4700)
suggest poor outcome if only detected at
deletion by fluorescence in situ hybridiza-
the time of relapse. Thus, in good-risk
tion only, in absence of other abnormali-
Introduction
Multiple myeloma is a heterogeneous disease with variable disease significance or SMM do not need initiation of therapy, irrespective courses, response to therapy, and survival outcome that ranges from of any associated risk factors, except on specifically targeted less than 1 year in patients with aggressive disease to more than protocols. For example, if a patient with clear diagnosis of SMM 10 years in patients with indolent disease presentation. Various has 17pϪ by fluorescence in situ hybridization (FISH) or del13 on patient-, disease-, and therapy-related characteristics have been cytogenetics analysis, it does not constitute an indication to start identified to predict the disease course as well as outcome in therapy. The risk stratification being described here is only for patients with myeloma. Such evaluation of prognostic factors and determining prognosis and stratification of treatment, rather than to risk stratification is important to define treatment strategies, decide whether to initiate treatment.
compare outcome of therapeutic trials, and predict survival from There has been general consensus on the risk factors that diagnosis. This consensus panel report has evaluated various help stratify patients receiving conventional therapeutic modalities.
aspects of risk stratification, including its purpose and timing, especially However, there are studies that suggest that bortezomib and, to an at diagnosis and at relapse, its relationship to therapy, and defined extent, lenalidomide may be able to overcome some of the poor-risk clinical and laboratory features, including genomic changes, that features and achieve clinical benefit.2-8 Further studies are needed to may be used to stratify patients and predict outcome at present.
decide on the ability of these agents to overcome the poor-risk features.
At the present time, it is important to stratify, but the availableinformation does not indicate selection of therapies—for example, if Purpose of risk stratification
patient has t(4:14)—it does not suggest that we should use a specifictherapy or novel agent.
The general purpose of risk stratification is not to decide whether or Currently, to mandate definitive treatment according to cytoge- not to treat a patient but to prognosticate.
netic abnormalities is premature, although there are emerging data The decision to treat is based on the criteria set for in the suggesting that some of the novel agents could overcome the diagnosis of symptomatic myeloma, which includes the hypercalce- negative prognosis of the cytogenetic abnormalities.9 mia, renal dysfunction, anemia, and bone lesions criteria.1 Patients It is important to continue to assess the impact of risk factors with clearly defined monoclonal gammopathy of undetermined with novel therapies and combinations. Clinical trials should be Submitted October 14, 2010; accepted January 6, 2011. Prepublished online This work was developed as part of the 12th International Myeloma Workshop, as Blood First Edition paper, February 3, 2011; DOI 10.1182/blood-2010-10- Washington, DC, February 26–March 1, 2009.
2011 by The American Society of Hematology BLOOD, 5 MAY 2011 ⅐ VOLUME 117, NUMBER 18 Table 1. Investigation for risk stratification
while on therapy and short duration of response.6,13 Unlike in the Investigation recommended for risk stratification
past, speed of response does not suggest overall outcome with Serum albumin and ␤2-microglobulin to determine ISS stage Bone marrow examination for t(4;14), t(14;16), and del(17p) on identified PCs If a patient already has an identified high-risk feature at diagnosis, then there is no need to look for the same feature again.
For example, if a patient at diagnosis has t(4;14), then one does not need to look for it again at relapse with the same FISH probe.
However, cytogenetic and FISH investigation should be performed Additional investigation for risk stratification
at relapse to look for additional changes. If a patient is in a low-risk group, then it is recommended that cytogenetics and FISH studies be performed at relapse for risk restratification as if not detected at the presentation, at relapse, because of selection of a preexisting DNA copy number alteration by CGH/SNP array clone they may attain a detectable level.
PCs indicates plasma cells; FISH, fluorescence in situ hybridization; LDH, lactate dehydrogenase; MRI/PET, magnetic resonance imaging/positron emission tomogra-phy; and CGH/SNP, comparative genomic hybridization/single nucleotide polymor-phism.
Is risk stratification specific for specific
treatment?
done based on risk stratification, to try and test whether certain patients There is general agreement that the risk stratification should be a benefit more or less from certain therapeutic agents or strategies.
global stratification, and not stratification for old versus newtherapy or risk stratification for particular one treatment. Werecognize that the risk features may be relevant to a given therapy.
Timing of risk stratification
For example, when patients with del13 are considered to have poorprognosis, it is based on a large number of studies focused on At diagnosis
outcome after high-dose therapy and transplantation. However,with the use of novel agents, for example bortezomib, del13 does There is consensus that the current risk stratification is applicable to not seem to be predictive of high risk.14,15 Thus, risk factors for newly diagnosed patients. All current efforts are directed at individual novel therapies are to be determined on an ongoing trial.
stratification at diagnosis using the parameters obtained at diagno- There was a consensus that the high-risk features will change in sis. The suggested investigations are listed in Table 1.
the future, with introduction of other new agents or possibly new At relapse
It is unclear whether risk stratification should change after There has been documentation of change in risk factors at relapse.
patients receive certain treatments. For example, bortezomib is able For example, in one study, the mean labeling index increased from to overcome, at least in part, the poor risk associated with t(4;14)2; 1% at diagnosis to 2.5% at relapse. If patients are followed do we need to identify different risk factors for patients after individually, it is always higher at relapse than at diagnosis. Similar bortezomib treatment? The general opinion was that there is not data exist for detection of p53 deletion at relapse or disease adequate information to implement such a recommendation.
progression compared with time of diagnosis.
The evolving consensus is that, if a patient acquires high-risk features at relapse or progression, then that patient should bereclassified as having high-risk disease. For example, if a patient What risk factors to look for
was not detected to have del(17p) at diagnosis but at relapse 60% There is a consensus that both cytogenetics and FISH play an cells show this change, then it is our consensus that this patient now important and independent role in risk stratification. Both FISH should be reclassified as having high-risk disease.
with specific markers and cytogenetics with specific abnormalities There is general consensus that the same genetic abnormalities need to be performed on bone marrow samples.
characteristic of poor outcome at diagnosis may suggest poor Although detection of any cytogenetic abnormality is consid- outcome if detected at the time of relapse.
ered to suggest higher-risk disease, the specific abnormalities Among the nongenetic risk factors, redetermination of factors, considered as poor risk are: cytogenetically detected chromosomal such as ␤2-microglobulin or International Staging System (ISS) at 13 or 13q deletion, t(4;14), and del17p; and detection by FISH of relapse or at follow-up, is not currently considered as predictive of change in risk stratification. The role of level of serum lactate dehydrogenase (LDH) at relapse is less clear. A very high LDH is 2-microglobulin level and ISS stage II and III considered to represent proliferative disease. High LDH levels are 2-microglobulin and low albumin are consid- uncommon in myeloma but carry poor prognosis at diagnosis orrelapse.10-12 Moving forward, an important goal for relapse trials would be to evaluate these and other risk factors at relapse, keeping in consideration What additional risk factors to look for
the type of therapy used at relapse. This is important as noveltherapies are becoming available and patients are living longer.
A number of individual risk factors have been identified. However, In patients with relapsed disease, additional risk stratification there is, in general, emphasis to use a system that combines criteria include type of response and length of response to prior multiple factors, such as ISS. Some of these factors were consid- therapy. Therapy-related poor-risk features include progression ered in developing the ISS risk stratification systems.
BLOOD, 5 MAY 2011 ⅐ VOLUME 117, NUMBER 18 Because of lack of uniform availability of the data for analysis, which led to proposal of the ISS, there are a number of factors that DS classification system
still may have a significant role in risk stratification as individualfactors (eg, LDH was not available for all patients and was not A clinical staging system at diagnosis using standard laboratory considered in developing ISS). However, in the limited patients measurement, developed by Durie and Salmon, was predictive of who had this information, LDH was found to have significant clinical outcome after standard-dose chemotherapy. However, with the use of high-dose therapy and novel agents, the Durie-Salmon Some of the features considered significant as individual factors (DS) system is less predictive of outcome.17,23 This may be are LDH, IgA, extramedullary disease, renal failure, high serum- explained by the fact that the DS system is focused predominantly free light chain, and serum-free ␬/serum-free ␭ ratio, plasmablastic on tumor burden; and as these newer therapies are able to better disease, and plasma cell leukemia.12,18-22 These features are useful reduce tumor burden, its significance has changed. There is under some circumstances, but their general applicability is increasing importance of tumor biology–related factors. DS system unknown. In addition, it is very much a constellation of features is still considered a means to measure tumor mass.
that often determine high risk, rather than a single factor that may There is general agreement that the DS system can supplement make it intermediate risk. Unlike FISH/cytogenetics, which may the diagnostic criteria for myeloma, such as hypercalcemia, renal suggest a change in therapeutic approach to more aggressive dysfunction, anemia, and bone disease; however, if a patient has treatment, no change in treatment approach is currently indicated already been diagnosed as having symptomatic myeloma based on based on such single higher-risk features.
current criteria, then there is no need to use the DS system inregular practice for diagnosis. As only patients with symptomaticdisease should be placed in clinical trials, reporting of DS system is Consensus for evaluation of genomic changes
not considered essential. As stage I represents early stage ofdisease, description of patients in clinical studies by DS staging As described in “What risk factors to look for,” there is a consensus system is encouraged. However, its routine clinical use is unclear.
that both cytogenetics and FISH have some adverse risk features.
Both highlight different disease parameters, and both preferablyshould be performed to have a better understanding of the behavior Incorporation of imaging results
FISH data should be reported specifically for clonal plasma The number of bone lytic lesions, per DS system, is not considered cells determined by surface marker or cytoplasmic immunoglobu- of any prognostic significance. Although there are small single- lin light chain expression, and not all cells. The positivity is to be institution studies indicating that achieving magnetic resonance determined by the percentage of positive cells that are above the imaging–directed complete remission has prognostic signifi- individual laboratories’ standard.
cance, this observation requires further studies to include No specific global cutoff should be applied. It is unclear imaging parameters in risk stratification or response definition.24 whether the number of positive cells carries any different risk. For Similarly, a recent study has pointed to the presence of more than example, if a patient has 7% versus 57% cells positive for a 3 fluorodeoxyglucose-avid focal lesions as the leading independent specific FISH abnormality, the relative risk for both patients is parameter associated with inferior overall and event-free sur- considered the same at present. This is not true for del(17p). In a vival.25 However, these results require further independent confir- report, del(17p) is prognostic only if present in at least 60% of mation before they are widely applied.
None of the imaging studies or results are currently recom- There is consensus that (1) detection of t(4;14), t (14;16), or17p mended for inclusion in risk stratification.
by FISH suggests higher-risk disease; (2) del13 or 13qϪ detectedonly by FISH independently in the absence of other abnormalitydoes not carry significant higher risk, whereas t(11;14) does not Inclusion of expression/genomic profile
predict superior outcome; and (3) there are some reports that 1qϩ,del1p may have clinical significance as a poor-risk feature; Expression profile data generated by a number of groups have been however, the consensus is that the data are not yet adequate to very helpful in identifying an expression signature that may suggest routine use of these FISH markers to predict prognosis.
identify a poor-risk group. Shaughnessy et al26 investigated theexpression profile of myeloma cells in 532 newly diagnosedmyeloma patients treated on 2 protocols incorporating tandem autologous transplantation. Using log-rank tests of expressionquartiles, 70 genes linked to shorter durations of complete remis- The ISS, incorporating serum albumin and ␤2-microglobulin, is sion, event-free survival, and overall survival were identified. The applicable as a prognostic system in the majority of settings. ISS is ratio of mean expression levels of up-regulated to down-regulated validated for conventional treatments as well as high-dose therapy.17 genes defined a high-risk score, which was an independent However, its validity with combination novel agent therapy still predictor of outcome endpoints in multivariate analysis (P Ͻ .001) that included the ISS and high-risk translocations. A subset of The method used for measurement should be standard. The ISS, patients with a high-risk score had a 3-year continuous complete although extremely convenient to use, requires incorporation of remission rate of only 20%, as opposed to a 5-year continuous additional myeloma-specific features to make it more robust or complete remission rate of 60% in the absence of a high-risk score.
more applicable using the newer generation of drugs and studies.
Interestingly, multivariate discriminant analysis identified a The ISS is a baseline lowest common denominator, to be 17-gene subset that performed as well as the 70-gene model.26 supplemented and not necessarily supplanted. There is a clear need A second large study published by Decaux et al27 from the and consensus to add cytogenetics/FISH or other markers to ISS.
Intergroupe Francophone du Myelome studied gene expression profiles of myeloma cells obtained at diagnosis in 182 patients and S. Siegel (Hackensack, NJ), Philippe Moreau (Nantes, France), identified the 15 strongest genes to calculate a risk score associated Hermann Einsele and Seema Singhal (Chicago, IL), Irene M.
with the length of survival. This analysis divided patients into Ghobrial (Boston, MA), Go¨sta Gharton (Stockholm, Sweden), high-risk group, characterized by the overexpression of genes James R. Berenson (West Hollywood, CA), Jayesh Mehta (Chi- involved in cell cycle progression and its surveillance, and low-risk cago, IL), Angela Dispenzieri (Rochester, NY), Sagar Lonial patients, with hyperdiploid signature and heterogeneous gene (Atlanta, GA), Ruben Niesvizky (New York, NY), Robert Schloss- expression. The results were confirmed in a test set, as well as man (Boston, MA), David H. Vesole (New York, NY), Asher independent cohorts composed of 853 patients with multiple Chanan-Khan (Buffalo, NY), Jeffrey Wolf (San Francisco, CA), myeloma. Overall survival at 3 years in low-risk and high-risk Michael Kuehl (Bethesda, MD), Johannes Drach (Vienna, Austria), groups was 91% and 47%, respectively. These results were Rik Schots (Brussels, Belgium), Giampaolo Merlini (Pavia, Italy), independent of traditional prognostic factors.27 Maurizio Zangari (Salt Lake City, UT), Jeffrey Zonder (Detroit, It is interesting to note that, although both these studies have MI), L. Thompson Heffner Jr (Atlanta, GA), Ramon Garcia Sanz included patients undergoing high-dose therapy, the 15 and 17 gene (Valencia, Spain), Philip R. Greipp (Rochester, MN), and Vinod models do not share common genes. This highlights the complexity of biologic behavior of the tumor and the fact that ultimate use ofsuch expression data will require significantly more work. Func-tional commonality or functional association between these variousgenes needs to be considered in developing a more composite Authorship
model. It also highlights the molecular redundancy in tumor cellsdriving their clinical behavior.
Contribution: N.C.M., K.C.A., P.L.B., J.S., A.P., B.D., R.F., A.K.S., The factors that require standardization are method used to J.-L.H., M.D., S.J., R.H., O.S., R.K., P.S., M.C., S.V.R., J.S.M., assess expression profile, the data analysis technique, consensus J.C., and H.A.-L. developed the consensus, provided critical review and validation of genes to be considered important for risk and edits to the manuscript, gave approval to the final manuscript, stratification, and standardization of method to apply this definition and participated significantly in the development of the consensus to expression profile for a single patient.
A more robust and comprehensive analysis is needed to analyze Conflict-of-interest disclosure: N.C.M. is a consultant/advisory significance of stratification using comparative genomic hybridiza- board member of Millenium, Celegene, Novartis, and Onyx.
tion/single nucleotide polymorphism array.
K.C.A. is a consultant/advisory board member of Millenium, In the future, a specific polymorphism may help identify patients Celegene, Novartis, Merck, BMS, Signalgenetics, and Onyx and with differential response profile and/or higher risk of toxicity. However, cofounded and owns stock in Acytelon. R.F. has received a patent currently, there is lack of data to propose any specific single nucleotide for the prognostication of MM based on genetic categorization of polymorphisms that can be used for such decision.
the disease and received consulting fees from Medtronic, Otsuka,Celgene, Genzyme, BMS, and Amgen and research support fromCylene and Onyx. J.S. has been awarded patents, or has submitted Consideration of risk factors in special
patent applications on molecular diagnostics and therapeutics in therapeutic scenario
cancer medicine; receives royalties related to patent licenses fromGenzyme, Novartis, and Signal Genetics LLC; cofounded and owns There are emerging data that allogeneic transplantation may have stock in Signal Genetics LLC, a molecular diagnostics company; beneficial outcomes in high-risk patients defined by cytogenetics/ consulted/advised Signal Genetics LLC, Array Biopharma, Celgene, FISH. These data are limited and require further confirmation.28 Genzyme, Millennium, Centocor Ortho Biotech, and Novartis; and However, the group feels that allogeneic transplantation could be received honoraria from Array Biopharma, Celgene, Centocor Ortho considered in this group of patients.
Biotech, Genzyme, Millennium, and Novartis. A.K.S. is an advisor for The current level of evidence does not provide direction in deciding whether patients with a specific risk group will benefit Signalgenetics. O.S. has received honoraria from Amgen, Celgene, Janssen, and Novartis. M.C. has received honoraria from Janssen-Cilag,Millennium Pharmac, and Celgene. The remaining authors declare nocompeting financial interests.
Acknowledgments
Correspondence: Nikhil C. Munshi, Dana-Farber Cancer Insti- tute, 44 Binney St, Boston, MA 02115; e-mail: nikhil_munshi@ The authors thank the following colleagues for their participation dfci.harvard.edu; and Herve´ Avet-Loiseau, 42 rue Jules Simon, on the Consensus Panel: Drs Shaji Kumar (Rochester, MN), David 44000 Nantes, France; e-mail: [email protected].
References
1. International Myeloma Working Group. Criteria Bortezomib therapy response is independent of lenalidomide and dexamethasone. Blood. 2009; for the classification of monoclonal gammopa- cytogenetic abnormalities in relapsed/refractory thies, multiple myeloma and related disorders: a multiple myeloma. Leuk Res. 2007;31(6):779-782.
6. Avet-Loiseau H, Soulier J, Fermand JP, et al. Impact report of the International Myeloma Working 4. Reece D, Song KW, Fu T, et al. Influence of cyto- of high-risk cytogenetics and prior therapy on out- Group. Br J Haematol. 2003;121(5):749-757.
genetics in patients with relapsed or refractory comes in patients with advanced relapsed or refrac- 2. Avet-Loiseau H, Leleu X, Roussel M, et al. Bor- multiple myeloma treated with lenalidomide plus tory multiple myeloma treated with lenalidomide plus tezomib plus dexamethasone induction improves dexamethasone: adverse effect of deletion dexamethasone. Leukemia. 2010;24(3):623-628.
outcome of patients with t(4;14) myeloma but not 17p13. Blood. 2009;114(3):522-525.
7. Mateos MV, Oriol A, Martinez-Lopez J, et al. Bor- outcome of patients with del(17p). J Clin Oncol. 5. Kapoor P, Kumar S, Fonseca R, et al. Impact of tezomib, melphalan, and prednisone versus bor- risk stratification on outcome among patients with tezomib, thalidomide, and prednisone as induc- 3. Chang H, Trieu Y, Qi X, Xu W, Stewart KA, Reece D.
multiple myeloma receiving initial therapy with tion therapy followed by maintenance treatment BLOOD, 5 MAY 2011 ⅐ VOLUME 117, NUMBER 18 with bortezomib and thalidomide versus bort- methasone with or without bortezomib: prospec- 22. Sher T, Miller KC, Deeb G, Lee K, Chanan-Khan A.
ezomib and prednisone in elderly patients with tive evaluation of the impact of cytogenetic abnor- Plasma cell leukaemia and other aggressive untreated multiple myeloma: a randomised trial.
malities and of previous therapies. Leukemia. plasma cell malignancies. Br J Haematol. 2010; Lancet Oncol. 2010;11(10):934-941.
8. Cavo M, Tacchetti P, Patriarca F, et al. Bor- 14. Sagaster V, Ludwig H, Kaufmann H, et al. Bor- 23. Barlogie B, Jagannath S, Desikan KR, et al. Total tezomib with thalidomide plus dexamethasone tezomib in relapsed multiple myeloma: response therapy with tandem transplants for newly diag- compared with thalidomide plus dexamethasone rates and duration of response are independent nosed multiple myeloma. Blood. 1999;93(1):55- as induction therapy before, and consolidation of a chromosome 13q-deletion. Leukemia. 2007; therapy after, double autologous stem-cell trans- 24. Walker R, Barlogie B, Haessler J, et al. Magnetic plantation in newly diagnosed multiple myeloma: 15. Jagannath S, Richardson PG, Sonneveld P, et al.
resonance imaging in multiple myeloma: diagnos- a randomised phase 3 study. Lancet. 2010; Bortezomib appears to overcome the poor prog- tic and clinical implications. J Clin Oncol. 2007; nosis conferred by chromosome 13 deletion in 9. Barlogie B, Pineda-Roman M, van Rhee F, et al.
phase 2 and 3 trials. Leukemia. 2007;21(1):151- Thalidomide arm of Total Therapy 2 improves 25. Bartel TB, Haessler J, Brown TL, et al. F18- complete remission duration and survival in my- 16. Avet-Loiseau H. Role of genetics in prognostica- fluorodeoxyglucose positron emission tomogra- eloma patients with metaphase cytogenetic ab- tion in myeloma. Best Pract Res Clin Haematol. phy in the context of other imaging techniques normalities. Blood. 2008;112(8):3115-3121.
and prognostic factors in multiple myeloma.
Blood. 2009;114(10):2068-2076.
10. Garcia-Sanz R, Gonzalez-Fraile MI, Mateo G, et al.
17. Greipp PR, San Miguel J, Durie BG, et al. Inter- Proliferative activity of plasma cells is the most national staging system for multiple myeloma.
26. Shaughnessy JD Jr, Zhan F, Burington BE, et al.
relevant prognostic factor in elderly multiple my- J Clin Oncol. 2005;23(15):3412-3420.
A validated gene expression model of high-risk eloma patients. Int J Cancer. 2004;112(5):884- 18. Drake MB, Iacobelli S, van Biezen A, et al. Pri- multiple myeloma is defined by deregulated ex- mary plasma cell leukemia and autologous stem pression of genes mapping to chromosome 1.
11. Shaughnessy J Jr, Tian E, Sawyer J, et al. Prog- cell transplantation. Haematologica. 2010;95(5): Blood. 2007;109(6):2276-2284.
nostic impact of cytogenetic and interphase fluo- 27. Decaux O, Lode L, Magrangeas F, et al. Predic- rescence in situ hybridization-defined chromo- 19. Rajkumar SV, Greipp PR. Prognostic factors in tion of survival in multiple myeloma based on some 13 deletion in multiple myeloma: early multiple myeloma. Hematol Oncol Clin North Am. gene expression profiles reveals cell cycle and results of total therapy II. Br J Haematol. 2003; chromosomal instability signatures in high-risk 20. Kumar S, Zhang L, Dispenzieri A, et al. Relation- patients and hyperdiploid signatures in low-risk 12. Terpos E, Katodritou E, Roussou M, et al. High ship between elevated immunoglobulin free light patients: a study of the Intergroupe Francophone serum lactate dehydrogenase adds prognostic chain and the presence of IgH translocations in du Myelome. J Clin Oncol. 2008;26(29):4798- value to the international myeloma staging sys- multiple myeloma. Leukemia. 2010;24(8):1498- tem even in the era of novel agents. Eur J 28. Lokhorst H, Einsele H, Vesole D, et al. Interna- Haematol. 2010;85(2):114-119.
21. Barlogie B, Tricot GJ, van Rhee F, et al. Long- tional myeloma working group consensus state- 13. Dimopoulos MA, Kastritis E, Christoulas D, et al.
term outcome results of the first tandem auto- ment regarding the current status of allogeneic Treatment of patients with relapsed/refractory transplant trial for multiple myeloma. Br J Haema- stem-cell transplantation for multiple myeloma.
multiple myeloma with lenalidomide and dexa- J Clin Oncol. 2010;28(29):4521-4530.

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