Skip to main content
Log in

Achieving minimal residual disease-negative by multiparameter flow cytometry may ameliorate a poor prognosis in MM patients with high-risk cytogenetics: a retrospective single-center analysis

  • Original Article
  • Published:
Annals of Hematology Aims and scope Submit manuscript

Abstract

The aim of our study was to evaluate the prognostic impact of minimal residual disease (MRD) and high-risk cytogenetics (HRCs) on outcomes in multiple myeloma (MM) patients. We applied multiparameter flow cytometry (MFC) to detect MRD in 123 consecutive patients diagnosed with MM for the first time who achieved very good partial remission (VGPR) or better after bortezomib or thalidomide-based induction therapy. Moreover, we examined the cytogenetic features of MM patients using magnetic-activated cell sorting and interphase fluorescence in situ hybridization (MACS-iFISH) at diagnosis. In all 123 MM patients, progression-free survival (PFS) and overall survival (OS) were better in the MRD− group (n = 31) than in the MRD+ group (n = 92) (median PFS: not reached (NR) vs. 26 months (m), P = 0.0002; 4-year OS, 91.7% vs. 66.3%, P = 0.008). PFS and OS were significantly shorter for each increase of one log per MRD level (P < 0.0001 and P = 0.001). The median PFS of the four groups according to the ratio of aberrant plasma cells (less than 0.01%, 0.01–0.1%, 0.1–1%, and more than 1%) were NR, 37 m, 26 m, and 15 m, respectively, and the 4-year OS rates were 91.7%, 69.3%, 76.1%, and 54.0%, respectively. In addition, our results show that PFS and OS were better for the standard-risk cytogenetic (SRC) patients than the HRC patients (median PFS: NR vs. 26 m, P = 0.004; 3-year OS: 95.8% vs. 76.0%, P = 0.006). The independent predictors of PFS were HRC and MRD+, which had hazard ratios of 1.901 (95% CI 1.094–3.303) and 3.486 (95% CI 1.449–8.386), respectively; while those for OS were an LDH level ≥ 250 U/L, HRC, and MRD+, which had hazard ratios of 2.789 (95% CI 1.080–7.199), 2.697 (95% CI 1.053–6.907), and 7.714 (95% CI 1.040–57.227), respectively. Furthermore, for SRC patients or HRC patients, PFS and OS were all longer in MRD− than in MRD+ patients. Strikingly, there was no significant difference in PFS or OS between the MRD-HRC and MRD+SRC groups (median PFS 45 vs. 34 m, P = 0.300; 4-year OS 100% vs. 83.6%, P = 0.196). PFS was superior in MRD-SRC than in MRD-HRC (NR vs. 45 m, P = 0.035); however, there was no significant difference in the 4-year OS between MRD-SRC and MRD-HRC (87.5% vs 100%, P = 0.480). MRD+ and HRCs were both independent prognostic factors in MM patients. Moreover, achieving MRD− may ameliorate a poor prognosis in MM patients with HRCs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

MFC:

Multiparameter flow cytometry

BM:

Bone marrow

MRD:

Minimal residual disease

SRC:

Standard-risk cytogenetics

HRCs:

High-risk cytogenetics

HD:

Hyperdiploidy

NHD:

Non-hyperdiploidy

APCs:

Aberrant plasma cells

NPCs:

Normal plasma cells

MACS-iFISH:

Magnetic-activated cell sorting and interphase fluorescence in situ hybridization

CR:

Complete remission

sCR:

Stringent CR

VGPR:

Very good partial remission

Ig:

Immunoglobulin

ISS:

International Staging System

LC:

Light chain

PFS:

Progression-free survival

OS:

Overall survival

NR:

Not reached

IMWG:

International Myeloma Working Group

PCR:

Polymerase chain reaction

NGS:

Next-generation sequencing

References

  1. Kyle RA, Rajkumar SV (2008) Multiple myeloma. Blood 111(6):2962–2972. https://doi.org/10.1182/blood-2007-10-078022

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Richardson PG, Weller E, Lonial S, Jakubowiak AJ, Jagannath S, Raje NS, Avigan DE, Xie W, Ghobrial IM, Schlossman RL, Mazumder A, Munshi NC, Vesole DH, Joyce R, Kaufman JL, Doss D, Warren DL, Lunde LE, Kaster S, Delaney C, Hideshima T, Mitsiades CS, Knight R, Esseltine DL, Anderson KC (2010) Lenalidomide, bortezomib, and dexamethasone combination therapy in patients with newly diagnosed multiple myeloma. Blood 116(5):679–686. https://doi.org/10.1182/blood-2010-02-268862

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Moreau P, Masszi T, Grzasko N, Bahlis NJ, Hansson M, Pour L, Sandhu I, Ganly P, Baker BW, Jackson SR, Stoppa AM, Simpson DR, Gimsing P, Palumbo A, Garderet L, Cavo M, Kumar S, Touzeau C, Buadi FK, Laubach JP, Berg DT, Lin J, Di Bacco A, Hui AM, van de Velde H, Richardson PG, Group T-MS (2016) Oral lenalidomide, and dexamethasone for multiple myeloma. N Engl J Med 374(17):1621–1634. https://doi.org/10.1056/NEJMoa1516282

    Article  CAS  PubMed  Google Scholar 

  4. Dimopoulos MA, Oriol A, Nahi H, San-Miguel J, Bahlis NJ, Usmani SZ, Rabin N, Orlowski RZ, Komarnicki M, Suzuki K, Plesner T, Yoon SS, Ben Yehuda D, Richardson PG, Goldschmidt H, Reece D, Lisby S, Khokhar NZ, O'Rourke L, Chiu C, Qin X, Guckert M, Ahmadi T, Moreau P, Investigators P (2016) Daratumumab, lenalidomide, and dexamethasone for multiple myeloma. N Engl J Med 375(14):1319–1331. https://doi.org/10.1056/NEJMoa1607751

    Article  CAS  PubMed  Google Scholar 

  5. Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65(1):5–29. https://doi.org/10.3322/caac.21254

    Article  Google Scholar 

  6. Ocio EM, Richardson PG, Rajkumar SV, Palumbo A, Mateos MV, Orlowski R, Kumar S, Usmani S, Roodman D, Niesvizky R, Einsele H, Anderson KC, Dimopoulos MA, Avet-Loiseau H, Mellqvist UH, Turesson I, Merlini G, Schots R, McCarthy P, Bergsagel L, Chim CS, Lahuerta JJ, Shah J, Reiman A, Mikhael J, Zweegman S, Lonial S, Comenzo R, Chng WJ, Moreau P, Sonneveld P, Ludwig H, Durie BG, Miguel JF (2014) New drugs and novel mechanisms of action in multiple myeloma in 2013: a report from the International Myeloma Working Group (IMWG). Leukemia 28(3):525–542. https://doi.org/10.1038/leu.2013.350

    Article  CAS  PubMed  Google Scholar 

  7. Cooke F, Bakkus M, Thielemans K, Pico JL, Apperley JF, Samson D (1999) Use of quantitative ASO-PCR to predict relapse in multiple myeloma. Br J Haematol 105(1):317–319

    Article  CAS  PubMed  Google Scholar 

  8. Ding C, Cantor CR (2003) A high-throughput gene expression analysis technique using competitive PCR and matrix-assisted laser desorption ionization time-of-flight MS. Proc Natl Acad Sci U S A 100(6):3059–3064. https://doi.org/10.1073/pnas.0630494100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ladetto M, Bruggemann M, Monitillo L, Ferrero S, Pepin F, Drandi D, Barbero D, Palumbo A, Passera R, Boccadoro M, Ritgen M, Gokbuget N, Zheng J, Carlton V, Trautmann H, Faham M, Pott C (2014) Next-generation sequencing and real-time quantitative PCR for minimal residual disease detection in B-cell disorders. Leukemia 28(6):1299–1307. https://doi.org/10.1038/leu.2013.375

    Article  CAS  PubMed  Google Scholar 

  10. Roussel M, Lauwers-Cances V, Robillard N, Hulin C, Leleu X, Benboubker L, Marit G, Moreau P, Pegourie B, Caillot D, Fruchart C, Stoppa AM, Gentil C, Wuilleme S, Huynh A, Hebraud B, Corre J, Chretien ML, Facon T, Avet-Loiseau H, Attal M (2014) Front-line transplantation program with lenalidomide, bortezomib, and dexamethasone combination as induction and consolidation followed by lenalidomide maintenance in patients with multiple myeloma: a phase II study by the Intergroupe Francophone du Myelome. J Clin Oncol 32(25):2712–2717. https://doi.org/10.1200/JCO.2013.54.8164

    Article  CAS  PubMed  Google Scholar 

  11. Tembhare PR, Yuan CM, Venzon D, Braylan R, Korde N, Manasanch E, Zuchlinsky D, Calvo K, Kurlander R, Bhutani M, Tageja N, Maric I, Mulquin M, Roschewski M, Kwok M, Liewehr D, Landgren O, Stetler-Stevenson M (2014) Flow cytometric differentiation of abnormal and normal plasma cells in the bone marrow in patients with multiple myeloma and its precursor diseases. Leuk Res 38(3):371–376. https://doi.org/10.1016/j.leukres.2013.12.007

    Article  PubMed  Google Scholar 

  12. Kumar S, Paiva B, Anderson KC, Durie B, Landgren O, Moreau P, Munshi N, Lonial S, Blade J, Mateos MV, Dimopoulos M, Kastritis E, Boccadoro M, Orlowski R, Goldschmidt H, Spencer A, Hou J, Chng WJ, Usmani SZ, Zamagni E, Shimizu K, Jagannath S, Johnsen HE, Terpos E, Reiman A, Kyle RA, Sonneveld P, Richardson PG, McCarthy P, Ludwig H, Chen W, Cavo M, Harousseau JL, Lentzsch S, Hillengass J, Palumbo A, Orfao A, Rajkumar SV, Miguel JS, Avet-Loiseau H (2016) International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma. Lancet Oncol 17(8):e328–e346. https://doi.org/10.1016/S1470-2045(16)30206-6

    Article  Google Scholar 

  13. Rawstron AC, Child JA, de Tute RM, Davies FE, Gregory WM, Bell SE, Szubert AJ, Navarro-Coy N, Drayson MT, Feyler S, Ross FM, Cook G, Jackson GH, Morgan GJ, Owen RG (2013) Minimal residual disease assessed by multiparameter flow cytometry in multiple myeloma: impact on outcome in the Medical Research Council Myeloma IX Study. J Clin Oncol 31(20):2540–2547. https://doi.org/10.1200/JCO.2012.46.2119

    Article  PubMed  Google Scholar 

  14. Rawstron AC, Gregory WM, de Tute RM, Davies FE, Bell SE, Drayson MT, Cook G, Jackson GH, Morgan GJ, Child JA, Owen RG (2015) Minimal residual disease in myeloma by flow cytometry: independent prediction of survival benefit per log reduction. Blood 125(12):1932–1935. https://doi.org/10.1182/blood-2014-07-590166

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Avet-Loiseau H, Attal M, Moreau P, Charbonnel C, Garban F, Hulin C, Leyvraz S, Michallet M, Yakoub-Agha I, Garderet L, Marit G, Michaux L, Voillat L, Renaud M, Grosbois B, Guillerm G, Benboubker L, Monconduit M, Thieblemont C, Casassus P, Caillot D, Stoppa AM, Sotto JJ, Wetterwald M, Dumontet C, Fuzibet JG, Azais I, Dorvaux V, Zandecki M, Bataille R, Minvielle S, Harousseau JL, Facon T, Mathiot C (2007) Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myelome. Blood 109(8):3489–3495. https://doi.org/10.1182/blood-2006-08-040410

    Article  CAS  PubMed  Google Scholar 

  16. Avet-Loiseau H, Attal M, Campion L, Caillot D, Hulin C, Marit G, Stoppa AM, Voillat L, Wetterwald M, Pegourie B, Voog E, Tiab M, Banos A, Jaubert J, Bouscary D, Macro M, Kolb B, Traulle C, Mathiot C, Magrangeas F, Minvielle S, Facon T, Moreau P (2012) Long-term analysis of the IFM 99 trials for myeloma: cytogenetic abnormalities [t(4;14), del(17p), 1q gains] play a major role in defining long-term survival. J Clin Oncol 30(16):1949–1952. https://doi.org/10.1200/JCO.2011.36.5726

    Article  PubMed  Google Scholar 

  17. Boyd KD, Ross FM, Walker BA, Wardell CP, Tapper WJ, Chiecchio L, Dagrada G, Konn ZJ, Gregory WM, Jackson GH, Child JA, Davies FE, Morgan GJ, Group NHOS (2011) Mapping of chromosome 1p deletions in myeloma identifies FAM46C at 1p12 and CDKN2C at 1p32.3 as being genes in regions associated with adverse survival. Clin Cancer Res 17(24):7776–7784. https://doi.org/10.1158/1078-0432.CCR-11-1791

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Korthals M, Sehnke N, Kronenwett R, Bruns I, Mau J, Zohren F, Haas R, Kobbe G, Fenk R (2012) The level of minimal residual disease in the bone marrow of patients with multiple myeloma before high-dose therapy and autologous blood stem cell transplantation is an independent predictive parameter. Biol Blood Marrow Transplant 18(3):423–431 e423. https://doi.org/10.1016/j.bbmt.2011.07.002

    Article  PubMed  Google Scholar 

  19. Paiva B, Vidriales MB, Cervero J, Mateo G, Perez JJ, Montalban MA, Sureda A, Montejano L, Gutierrez NC, Garcia de Coca A, de Las HN, Mateos MV, Lopez-Berges MC, Garcia-Boyero R, Galende J, Hernandez J, Palomera L, Carrera D, Martinez R, de la Rubia J, Martin A, Blade J, Lahuerta JJ, Orfao A, San Miguel JF, Groups GPCS (2008) Multiparameter flow cytometric remission is the most relevant prognostic factor for multiple myeloma patients who undergo autologous stem cell transplantation. Blood 112(10):4017–4023. https://doi.org/10.1182/blood-2008-05-159624

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Paiva B, Gutierrez NC, Rosinol L, Vidriales MB, Montalban MA, Martinez-Lopez J, Mateos MV, Cibeira MT, Cordon L, Oriol A, Terol MJ, Echeveste MA, de Paz R, de Arriba F, Palomera L, de la Rubia J, Diaz-Mediavilla J, Sureda A, Gorosquieta A, Alegre A, Martin A, Hernandez MT, Lahuerta JJ, Blade J, San Miguel JF, Groups PGCS (2012) 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 119(3):687–691. https://doi.org/10.1182/blood-2011-07-370460

    Article  CAS  PubMed  Google Scholar 

  21. Hu B, Thall P, Milton DR, Sasaki K, Bashir Q, Shah N, Patel K, Popat U, Hosing C, Nieto Y, Lin P, Delgado R, Jorgensen J, Manasanch E, Weber D, Thomas S, Orlowski RZ, Champlin R, Qazilbash MH (2018) High-risk myeloma and minimal residual disease postautologous-HSCT predict worse outcomes. Leuk Lymphoma:1–11. https://doi.org/10.1080/10428194.2018.1485908

  22. Chakraborty R, Muchtar E, Kumar SK, Jevremovic D, Buadi FK, Dingli D, Dispenzieri A, Hayman SR, Hogan WJ, Kapoor P, Lacy MQ, Leung N, Gertz MA (2017) Impact of post-transplant response and minimal residual disease on survival in myeloma with high-risk cytogenetics. Biol Blood Marrow Transplant 23(4):598–605. https://doi.org/10.1016/j.bbmt.2017.01.076

    Article  PubMed  Google Scholar 

  23. Dispenzieri A, Kyle R, Merlini G, Miguel JS, Ludwig H, Hajek R, Palumbo A, Jagannath S, Blade J, Lonial S, Dimopoulos M, Comenzo R, Einsele H, Barlogie B, Anderson K, Gertz M, Harousseau JL, Attal M, Tosi P, Sonneveld P, Boccadoro M, Morgan G, Richardson P, Sezer O, Mateos MV, Cavo M, Joshua D, Turesson I, Chen W, Shimizu K, Powles R, Rajkumar SV, Durie BG, International Myeloma Working G (2009) International Myeloma Working Group guidelines for serum-free light chain analysis in multiple myeloma and related disorders. Leukemia 23(2):215–224. https://doi.org/10.1038/leu.2008.307

    Article  CAS  PubMed  Google Scholar 

  24. Cordone I, Marchesi F, Masi S, Summa V, Pisani F, Merola R, Cigliana G, Orlandi G, Gumenyuk S, Palombi F, Romano A, Spadea A, Renzi D, Papa E, Canfora M, Conti L, Petti MC, Mengarelli A (2016) Flow cytometry remission by Ig light chains ratio is a powerful marker of outcome in multiple myeloma after tandem autologous transplant: a real-life study. J Exp Clin Cancer Res 35:49. https://doi.org/10.1186/s13046-016-0324-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Ross FM, Avet-Loiseau H, Ameye G, Gutierrez NC, Liebisch P, O'Connor S, Dalva K, Fabris S, Testi AM, Jarosova M, Hodkinson C, Collin A, Kerndrup G, Kuglik P, Ladon D, Bernasconi P, Maes B, Zemanova Z, Michalova K, Michau L, Neben K, Hermansen NE, Rack K, Rocci A, Protheroe R, Chiecchio L, Poirel HA, Sonneveld P, Nyegaard M, Johnsen HE, European Myeloma N (2012) Report from the European Myeloma Network on interphase FISH in multiple myeloma and related disorders. Haematologica 97(8):1272–1277. https://doi.org/10.3324/haematol.2011.056176

    Article  PubMed  PubMed Central  Google Scholar 

  26. Chng WJ, Van Wier SA, Ahmann GJ, Winkler JM, Jalal SM, Bergsagel PL, Chesi M, Trendle MC, Oken MM, Blood E, Henderson K, Santana-Davila R, Kyle RA, Gertz MA, Lacy MQ, Dispenzieri A, Greipp PR, Fonseca R (2005) A validated FISH trisomy index demonstrates the hyperdiploid and nonhyperdiploid dichotomy in MGUS. Blood 106(6):2156–2161. https://doi.org/10.1182/blood-2005-02-0761

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Munshi NC, Avet-Loiseau H, Rawstron AC, Owen RG, Child JA, Thakurta A, Sherrington P, Samur MK, Georgieva A, Anderson KC, Gregory WM (2017) Association of minimal residual disease with superior survival outcomes in patients with multiple myeloma: a meta-analysis. JAMA Oncol 3(1):28–35. https://doi.org/10.1001/jamaoncol.2016.3160

    Article  PubMed  PubMed Central  Google Scholar 

  28. Arroz M, Came N, Lin P, Chen W, Yuan C, Lagoo A, Monreal M, de Tute R, Vergilio JA, Rawstron AC, Paiva B (2016) Consensus guidelines on plasma cell myeloma minimal residual disease analysis and reporting. Cytometry B Clin Cytom 90(1):31–39. https://doi.org/10.1002/cyto.b.21228

    Article  CAS  PubMed  Google Scholar 

  29. Rawstron AC, Paiva B, Stetler-Stevenson M (2016) Assessment of minimal residual disease in myeloma and the need for a consensus approach. Cytometry B Clin Cytom 90(1):21–25. https://doi.org/10.1002/cyto.b.21272

    Article  PubMed  Google Scholar 

  30. Paiva B, van Dongen JJ, Orfao A (2015) New criteria for response assessment: role of minimal residual disease in multiple myeloma. Blood 125(20):3059–3068. https://doi.org/10.1182/blood-2014-11-568907

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. de Tute RM, Rawstron AC, Gregory WM, Child JA, Davies FE, Bell SE, Cook G, Szubert AJ, Drayson MT, Jackson GH, Morgan GJ, Owen RG (2016) Minimal residual disease following autologous stem cell transplant in myeloma: impact on outcome is independent of induction regimen. Haematologica 101(2):e69–e71. https://doi.org/10.3324/haematol.2015.128215

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Rosinol L, Oriol A, Teruel AI, Hernandez D, Lopez-Jimenez J, de la Rubia J, Granell M, Besalduch J, Palomera L, Gonzalez Y, Etxebeste MA, Diaz-Mediavilla J, Hernandez MT, de Arriba F, Gutierrez NC, Martin-Ramos ML, Cibeira MT, Mateos MV, Martinez J, Alegre A, Lahuerta JJ, San Miguel J, Blade J, Programa para el Estudio y la Terapeutica de las Hemopatias Malignas/Grupo Espanol de Mieloma g (2012) Superiority of bortezomib, thalidomide, and dexamethasone (VTD) as induction pretransplantation therapy in multiple myeloma: a randomized phase 3 PETHEMA/GEM study. Blood 120(8):1589–1596. https://doi.org/10.1182/blood-2012-02-408922

    Article  CAS  PubMed  Google Scholar 

  33. Reeder CB, Reece DE, Kukreti V, Chen C, Trudel S, Hentz J, Noble B, Pirooz NA, Spong JE, Piza JG, Zepeda VH, Mikhael JR, Leis JF, Bergsagel PL, Fonseca R, Stewart AK (2009) Cyclophosphamide, bortezomib and dexamethasone induction for newly diagnosed multiple myeloma: high response rates in a phase II clinical trial. Leukemia 23(7):1337–1341. https://doi.org/10.1038/leu.2009.26

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Paiva B, Martinez-Lopez J, Vidriales MB, Mateos MV, Montalban MA, Fernandez-Redondo E, Alonso L, Oriol A, Teruel AI, de Paz R, Larana JG, Bengoechea E, Martin A, Mediavilla JD, Palomera L, de Arriba F, Blade J, Orfao A, Lahuerta JJ, San Miguel JF (2011) Comparison of immunofixation, serum free light chain, and immunophenotyping for response evaluation and prognostication in multiple myeloma. J Clin Oncol 29(12):1627–1633. https://doi.org/10.1200/JCO.2010.33.1967

    Article  CAS  PubMed  Google Scholar 

  35. Liu H, Yuan C, Heinerich J, Braylan R, Chang M, Wingard J, Moreb J (2008) Flow cytometric minimal residual disease monitoring in patients with multiple myeloma undergoing autologous stem cell transplantation: a retrospective study. Leuk Lymphoma 49(2):306–314. https://doi.org/10.1080/10428190701813018

    Article  PubMed  Google Scholar 

  36. Paiva B, Cedena MT, Puig N, Arana P, Vidriales MB, Cordon L, Flores-Montero J, Gutierrez NC, Martin-Ramos ML, Martinez-Lopez J, Ocio EM, Hernandez MT, Teruel AI, Rosinol L, Echeveste MA, Martinez R, Gironella M, Oriol A, Cabrera C, Martin J, Bargay J, Encinas C, Gonzalez Y, Van Dongen JJ, Orfao A, Blade J, Mateos MV, Lahuerta JJ, San Miguel JF, Grupo Espanol de Mieloma/Programa para el Estudio de la Terapeutica en Hemopatias Malignas Cooperative Study G (2016) Minimal residual disease monitoring and immune profiling in multiple myeloma in elderly patients. Blood 127(25):3165–3174. https://doi.org/10.1182/blood-2016-03-705319

    Article  CAS  PubMed  Google Scholar 

  37. Martinez-Lopez J, Lahuerta JJ, Pepin F, Gonzalez M, Barrio S, Ayala R, Puig N, Montalban MA, Paiva B, Weng L, Jimenez C, Sopena M, Moorhead M, Cedena T, Rapado I, Mateos MV, Rosinol L, Oriol A, Blanchard MJ, Martinez R, Blade J, San Miguel J, Faham M, Garcia-Sanz R (2014) Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. Blood 123(20):3073–3079. https://doi.org/10.1182/blood-2014-01-550020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Perrot A, Lauwers-Cances V, Corre J, Robillard N, Hulin C, Chretien ML, Dejoie T, Maheo S, Stoppa AM, Pegourie B, Karlin L, Garderet L, Arnulf B, Doyen C, Meuleman N, Royer B, Eveillard JR, Benboubker L, Dib M, Decaux O, Jaccard A, Belhadj K, Brechignac S, Kolb B, Fohrer C, Mohty M, Macro M, Richardson PG, Carlton V, Moorhead M, Willis T, Faham M, Anderson KC, Harousseau JL, Leleu X, Facon T, Moreau P, Attal M, Avet-Loiseau H, Munshi N (2018) Minimal residual disease negativity using deep sequencing is a major prognostic factor in multiple myeloma. Blood 132:2456–2464. https://doi.org/10.1182/blood-2018-06-858613

    Article  CAS  PubMed  Google Scholar 

  39. van de Donk NW, van der Holt B, Minnema MC, Vellenga E, Croockewit S, Kersten MJ, von dem Borne PA, Ypma P, Schaafsma R, de Weerdt O, Klein SK, Delforge M, Levin MD, Bos GM, Jie KG, Sinnige H, Coenen JL, de Waal EG, Zweegman S, Sonneveld P, Lokhorst HM (2018) Thalidomide before and after autologous stem cell transplantation in recently diagnosed multiple myeloma (HOVON-50): long-term results from the phase 3, randomised controlled trial. Lancet Haematol 5(10):e479–e492. https://doi.org/10.1016/S2352-3026(18)30149-2

    Article  PubMed  Google Scholar 

  40. McCarthy PL, Holstein SA, Petrucci MT, Richardson PG, Hulin C, Tosi P, Bringhen S, Musto P, Anderson KC, Caillot D, Gay F, Moreau P, Marit G, Jung SH, Yu Z, Winograd B, Knight RD, Palumbo A, Attal M (2017) Lenalidomide maintenance after autologous stem-cell transplantation in newly diagnosed multiple myeloma: a meta-analysis. J Clin Oncol 35(29):3279–3289. https://doi.org/10.1200/JCO.2017.72.6679

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Fukumoto K, Fujisawa M, Suehara Y, Narita KT, Usui Y, Takeuchi M, Matsue K (2016) Prognostic impact of immunophenotypic complete response in patients with multiple myeloma achieving better than complete response. Leuk Lymphoma 57(8):1786–1792. https://doi.org/10.3109/10428194.2015.1121262

    Article  CAS  PubMed  Google Scholar 

  42. Mei J, Zhai Y, Li H, Li F, Zhou X, Song P, Zhao Q, Yu Y, An Z, Wang L (2018) Prognostic impact of hyperdiploidy in multiple myeloma patients with high-risk cytogenetics: a pilot study in China. J Cancer Res Clin Oncol 144(11):2263–2273. https://doi.org/10.1007/s00432-018-2732-3

    Article  CAS  PubMed  Google Scholar 

  43. Kumar S, Fonseca R, Ketterling RP, Dispenzieri A, Lacy MQ, Gertz MA, Hayman SR, Buadi FK, Dingli D, Knudson RA, Greenberg A, Russell SJ, Zeldenrust SR, Lust JA, Kyle RA, Bergsagel L, Rajkumar SV (2012) Trisomies in multiple myeloma: impact on survival in patients with high-risk cytogenetics. Blood 119(9):2100–2105. https://doi.org/10.1182/blood-2011-11-390658

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Pawlyn C, Melchor L, Murison A, Wardell CP, Brioli A, Boyle EM, Kaiser MF, Walker BA, Begum DB, Dahir NB, Proszek P, Gregory WM, Drayson MT, Jackson GH, Ross FM, Davies FE, Morgan GJ (2015) Coexistent hyperdiploidy does not abrogate poor prognosis in myeloma with adverse cytogenetics and may precede IGH translocations. Blood 125(5):831–840. https://doi.org/10.1182/blood-2014-07-584268

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

We sincerely thank all the doctors and nurses in the hematology department. In particular, we thank our colleagues who participated in this study. We thank all the patients who participated in this study and who sought care at our center.

Funding

This work is supported by projects from the National Natural Science Foundation of China for Young Scholars (grant number 81800126), the Six Talent Peak Project in Jiangsu Province (grant number 2015-WSN-011), and Hanqing Li received grant support from the Research Foundation of Jinling Hospital (grant number 2014017).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yongping Zhai.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical statement

This study was approved by the Clinical Research Ethics Committee of Jinling Hospital, Nanjing, China. Written consent was waived by the Ethics Committee.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, H., Li, F., Zhou, X. et al. Achieving minimal residual disease-negative by multiparameter flow cytometry may ameliorate a poor prognosis in MM patients with high-risk cytogenetics: a retrospective single-center analysis. Ann Hematol 98, 1185–1195 (2019). https://doi.org/10.1007/s00277-019-03609-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00277-019-03609-x

Keywords

Navigation