Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

MINIMAL RESIDUAL DISEASE

Impact of measurable residual disease by decentralized flow cytometry: a PETHEMA real-world study in 1076 patients with acute myeloid leukemia

Leukemia volume 35, pages 2358–2370 (2021)Cite this article

Subjects

Abstract

The role of decentralized assessment of measurable residual disease (MRD) for risk stratification in acute myeloid leukemia (AML) remains largely unknown, and so it does which methodological aspects are critical to empower the evaluation of MRD with prognostic significance, particularly if using multiparameter flow cytometry (MFC). We analyzed 1076 AML patients in first remission after induction chemotherapy, in whom MRD was evaluated by MFC in local laboratories of 60 Hospitals participating in the PETHEMA registry. We also conducted a survey on technical aspects of MRD testing to determine the impact of methodological heterogeneity in the prognostic value of MFC. Our results confirmed the recommended cutoff of 0.1% to discriminate patients with significantly different cumulative-incidence of relapse (-CIR- HR:0.71, P < 0.001) and overall survival (HR: 0.73, P = 0.001), but uncovered the limited prognostic value of MFC based MRD in multivariate and recursive partitioning models including other clinical, genetic and treatment related factors. Virtually all aspects related with methodological, interpretation, and reporting of MFC based MRD testing impacted in its ability to discriminate patients with different CIR. Thus, this study demonstrated that “real-world” assessment of MRD using MFC is prognostic in patients at first remission, and urges greater standardization for improved risk-stratification toward clinical decisions in AML.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Prognostic value of decentralized MRD assessment using MFC.
Fig. 2: Prognostic value according to MRD threshold levels.
Fig. 3: MRD performance in a recursive partitioning model with other prognostic factors.
Fig. 4: Heterogeneity in MRD testing using MFC in Hospitals participating in the PETHEMA LMA 1999, 2007 and 2010 protocols.
Fig. 5: Impact of technical heterogeneity in MRD testing using MFC and its ability to predict outcome.

Similar content being viewed by others

Data availability

Data supporting the conclusions of this manuscript will be made available upon reasonable request to the Corresponding Author.

References

  1. Schuurhuis GJ, Heuser M, Freeman S, Béné M-C, Buccisano F, Cloos J, et al. Minimal/measurable residual disease in AML: a consensus document from the European LeukemiaNet MRD Working Party. Blood. 2018;131:1275–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Cornelissen JJ, Blaise D. Hematopoietic stem cell transplantation for patients with AML in first complete remission. Blood. 2016;127:62–70.

    Article  CAS  PubMed  Google Scholar 

  3. Dohner H, Estey E, Grimwade D, Amadori S, Appelbaum FR, Buchner T, et al. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood. 2017;129:424–47.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Walter RB, Buckley SA, Pagel JM, Wood BL, Storer BE, Sandmaier BM, et al. Significance of minimal residual disease before myeloablative allogeneic hematopoietic cell transplantation for AML in first and second complete remission. Blood. 2013;122:1813–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Araki D, Wood BL, Othus M, Radich JP, Halpern AB, Zhou Y, et al. Allogeneic hematopoietic cell transplantation for acute myeloid leukemia: time to move toward a minimal residual disease-based definition of complete remission? J Clin Oncol. 2016;34:329–36.

    Article  PubMed  Google Scholar 

  6. Maurillo L, Buccisano F, Del Principe MI, Del Poeta G, Spagnoli A, Panetta P, et al.Toward optimization of postremission therapy for residual disease-positive patients with acute myeloid leukemia.J Clin Oncol. 2008;26:4944–51.

    Article  PubMed  Google Scholar 

  7. van der Velden VHJ, van der Sluijs-Geling A, Gibson BES, te Marvelde JG, Hoogeveen PG, Hop WCJ, et al. Clinical significance of flowcytometric minimal residual disease detection in pediatric acute myeloid leukemia patients treated according to the DCOG ANLL97/MRC AML12 protocol. Leukemia. 2010;24:1599–606.

    Article  PubMed  Google Scholar 

  8. Buccisano F, Maurillo L, Piciocchi A, Del Principe MI, Sarlo C, Cefalo M, et al. Minimal residual disease negativity in elderly patients with acute myeloid leukemia may indicate different postremission strategies than in younger patients. Ann Hematol. 2015;94:1319–26.

    Article  CAS  PubMed  Google Scholar 

  9. Rubnitz JE, Inaba H, Dahl G, Ribeiro RC, Bowman WP, Taub J, et al. Minimal residual disease-directed therapy for childhood acute myeloid leukaemia: results of the AML02 multicentre trial. Lancet Oncol. 2010;11:543–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Walter RB, Gyurkocza B, Storer BE, Godwin CD, Pagel JM, Buckley SA, et al. Comparison of minimal residual disease as outcome predictor for AML patients in first complete remission undergoing myeloablative or nonmyeloablative allogeneic hematopoietic cell transplantation. Leukemia. 2015;29:137–44.

    Article  CAS  PubMed  Google Scholar 

  11. Inaba H, Coustan-Smith E, Cao X, Pounds SB, Shurtleff SA, Wang KY, et al. Comparative analysis of different approaches to measure treatment response in acute myeloid leukemia.J Clin Oncol. 2012;30:3625–32.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Terwijn M, van Putten WL, Kelder A, van der Velden VH, Brooimans RA, Pabst T, et al. High prognostic impact of flow cytometric minimal residual disease detection in acute myeloid leukemia: data from the HOVON/SAKK AML 42A study. J Clin Oncol. 2013;31:3889–97.

    Article  PubMed  Google Scholar 

  13. Vidriales M-B, Perez-Lopez E, Pegenaute C, Castellanos M, Perez J-J, Chandia M, et al. Minimal residual disease evaluation by flow cytometry is a complementary tool to cytogenetics for treatment decisions in acute myeloid leukaemia. Leuk Res. 2016;40:1–9.

    Article  PubMed  Google Scholar 

  14. San Miguel JF, Martinez A, Macedo A, Vidriales MB, Lopez-Berges C, Gonzalez M, et al. Immunophenotyping investigation of minimal residual disease is a useful approach for predicting relapse in acute myeloid leukemia patients. Blood. 1997;90:2465–70.

    Article  CAS  PubMed  Google Scholar 

  15. San Miguel JF, Vidriales MB, López-Berges C, Díaz-Mediavilla J, Gutiérrez N, Cañizo C, et al. Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification. Blood. 2001;98:1746–51.

    Article  CAS  PubMed  Google Scholar 

  16. Venditti A, Buccisano F, Del Poeta G, Maurillo L, Tamburini A, Cox C, et al. Level of minimal residual disease after consolidation therapy predicts outcome in acute myeloid leukemia. Blood. 2000;96:3948–52.

    Article  CAS  PubMed  Google Scholar 

  17. Sievers EL, Lange BJ, Alonzo TA, Gerbing RB, Bernstein ID, Smith FO, et al. Immunophenotypic evidence of leukemia after induction therapy predicts relapse: results from a prospective Children’s Cancer Group study of 252 patients with acute myeloid leukemia. Blood. 2003;101:3398–406.

    Article  CAS  PubMed  Google Scholar 

  18. Kern W, Voskova D, Schoch C, Hiddemann W, Schnittger S, Haferlach T. Determination of relapse risk based on assessment of minimal residual disease during complete remission by multiparameter flow cytometry in unselected patients with acute myeloid leukemia. Blood. 2004;104:3078–85.

    Article  CAS  PubMed  Google Scholar 

  19. Kern W, Voskova D, Schoch C, Schnittger S, Hiddemann W, Haferlach T. Prognostic impact of early response to induction therapy as assessed by multiparameter flow cytometry in acute myeloid leukemia. Haematologica. 2004;89:528–40.

    PubMed  Google Scholar 

  20. Loken MR, Alonzo TA, Pardo L, Gerbing RB, Raimondi SC, Hirsch BA, et al. Residual disease detected by multidimensional flow cytometry signifies high relapse risk in patients with de novo acute myeloid leukemia: a report from Children’s Oncology Group. Blood. 2012;120:1581–8.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Buccisano F, Maurillo L, Gattei V, Del Poeta G, Del Principe MI, Cox MC, et al. The kinetics of reduction of minimal residual disease impacts on duration of response and survival of patients with acute myeloid leukemia. Leukemia. 2006;20:1783–9.

    Article  CAS  PubMed  Google Scholar 

  22. Freeman SD, Virgo P, Couzens S, Grimwade D, Russell N, Hills RK, et al. Prognostic relevance of treatment response measured by flow cytometric residual disease detection in older patients with acute myeloid leukemia. J Clin Oncol. 2013;31:4123–31.

    Article  PubMed  Google Scholar 

  23. Langebrake C, Creutzig U, Dworzak M, Hrusak O, Mejstrikova E, Griesinger F, et al. Residual disease monitoring in childhood acute myeloid leukemia by multiparameter flow cytometry: the MRD-AML-BFM Study Group. J Clin Oncol 2006;24:3686–92.

    Article  PubMed  Google Scholar 

  24. Tierens A, Bjørklund E, Siitonen S, Marquart HV, Wulff-Juergensen G, Pelliniemi T-T, et al. Residual disease detected by flow cytometry is an independent predictor of survival in childhood acute myeloid leukaemia; results of the NOPHO-AML 2004 study. Br J Haematol. 2016;174:600–9.

    Article  PubMed  Google Scholar 

  25. Buckley SA, Wood BL, Othus M, Hourigan CS, Ustun C, Linden MA, et al. Minimal residual disease prior to allogeneic hematopoietic cell transplantation in acute myeloid leukemia: a meta-analysis. Haematologica. 2017;102:865–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Grubovikj RM, Alavi A, Koppel A, Territo M, Schiller GJ. Minimal residual disease as a predictive factor for relapse after allogeneic hematopoietic stem cell transplant in adult patients with acute myeloid leukemia in first and second complete remission. Cancers. 2012;4:601–17.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Leung W, Pui C-H, Coustan-Smith E, Yang J, Pei D, Gan K, et al. Detectable minimal residual disease before hematopoietic cell transplantation is prognostic but does not preclude cure for children with very-high-risk leukemia. Blood. 2012;120:468–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Laane E, Derolf AR, Björklund E, Mazur J, Everaus H, Söderhäll S, et al. The effect of allogeneic stem cell transplantation on outcome in younger acute myeloid leukemia patients with minimal residual disease detected by flow cytometry at the end of post-remission chemotherapy. Haematologica. 2006;91:833–6.

    PubMed  Google Scholar 

  29. Bleyzac N, Cuzzubbo D, Rénard C, Garnier N, Dubois V, Domenech C, et al. Improved outcome of children transplanted for high-risk leukemia by using a new strategy of cyclosporine-based GVHD prophylaxis. Bone Marrow Transpl. 2016;51:698–704.

    Article  CAS  Google Scholar 

  30. Zheng C, Zhu X, Tang B, Zhang L, Geng L, Liu H, et al. The impact of pre-transplant minimal residual disease on outcome of intensified myeloablative cord blood transplant for acute myeloid leukemia in first or second complete remission. Leuk Lymphoma. 2016;57:1398–405.

    Article  CAS  PubMed  Google Scholar 

  31. Ustun C, Courville EL, DeFor T, Dolan M, Randall N, Yohe S, et al. Myeloablative, but not reduced-intensity, conditioning overcomes the negative effect of flow-cytometric evidence of leukemia in acute myeloid leukemia. Biol Blood Marrow Transpl. 2016;22:669–75.

    Article  Google Scholar 

  32. Rossi G, Carella AM, Minervini MM, di Nardo F, Waure C, de, Greco MM, et al. Optimal time-points for minimal residual disease monitoring change on the basis of the method used in patients with acute myeloid leukemia who underwent allogeneic stem cell transplantation: a comparison between multiparameter flow cytometry and Wilms’ t. Leuk Res. 2015;39:138–43.

    Article  PubMed  Google Scholar 

  33. Kanakry CG, Tsai H-L, Bolaños-Meade J, Smith BD, Gojo I, Kanakry JA, et al. Single-agent GVHD prophylaxis with posttransplantation cyclophosphamide after myeloablative, HLA-matched BMT for AML, ALL, and MDS. Blood. 2014;124:3817–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Anthias C, Dignan FL, Morilla R, Morilla A, Ethell ME, Potter MN, et al. Pre-transplant MRD predicts outcome following reduced-intensity and myeloablative allogeneic hemopoietic SCT in AML. Bone Marrow Transpl. 2014;49:679–83.

    Article  CAS  Google Scholar 

  35. Bastos-Oreiro M, Perez-Corral A, Martínez-Laperche C, Bento L, Pascual C, Kwon M, et al. Prognostic impact of minimal residual disease analysis by flow cytometry in patients with acute myeloid leukemia before and after allogeneic hemopoietic stem cell transplantation. Eur J Haematol. 2014;93:239–46.

    Article  PubMed  Google Scholar 

  36. Wang Y, Liu D-H, Liu K-Y, Xu L-P, Zhang X-H, Han W, et al. Impact of pretransplantation risk factors on post transplantation outcome of patients with acute myeloid leukemia in remission after haploidentical hematopoietic stem cell transplantation. Biol Blood Marrow Transpl. 2013;19:283–90.

    Article  Google Scholar 

  37. Brooimans RA, van der Velden VHJ, Boeckx N, Slomp J, Preijers F, Te Marvelde JG, et al. Immunophenotypic measurable residual disease (MRD) in acute myeloid leukemia: Is multicentric MRD assessment feasible? Leuk Res. 2019;76:39–47.

    Article  PubMed  Google Scholar 

  38. Swerdlow, SH WHO classification of tumours of haematopoietic and lymphoid tissues. WHO Classif tumours [Internet]. 2008 [cited 2020 May 19];22008:439. http://ci.nii.ac.jp/naid/20001195667/en/

  39. Grimwade D, Hills RK, Moorman AV, Walker H, Chatters S, Goldstone AH, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood. 2010;116:354–65.

    Article  CAS  PubMed  Google Scholar 

  40. Cheson BD, Cassileth PA, Head DR, Schiffer CA, Bennett JM, Bloomfield CD, et al. Report of the National Cancer Institute-sponsored workshop on definitions of diagnosis and response in acute myeloid leukemia.J Clin Oncol. 1990;8:813–9.

    Article  CAS  PubMed  Google Scholar 

  41. Epstein-Peterson ZD, Devlin SM, Stein EM, Estey E, Tallman MS. Widespread use of measurable residual disease in acute myeloid leukemia practice. Leuk Res. 2018;67:92–8.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Venditti A, Peter Gale R, Buccisano F, Ossenkoppele G. Should persons with acute myeloid leukemia (AML) in 1st histological complete remission who are measurable residual disease (MRD) test positive receive an allotransplant? Leukemia. 2020;34:963–5.

    Article  PubMed  Google Scholar 

  43. Hourigan CS, Dillon LW, Gui G, Logan BR, Fei M, Ghannam J, et al. Impact of conditioning intensity of allogeneic transplantation for acute myeloid leukemia with genomic evidence of residual disease. J Clin Oncol. 2020;38:1273–83.

    Article  CAS  PubMed  Google Scholar 

  44. Gilleece MH, Labopin M, Yakoub-Agha I, Volin L, Socié G, Ljungman P, et al. Measurable residual disease, conditioning regimen intensity, and age predict outcome of allogeneic hematopoietic cell transplantation for acute myeloid leukemia in first remission: a registry analysis of 2292 patients by the Acute Leukemia Working Party. Am J Hematol. 2018;93:1142–52.

    Article  PubMed  Google Scholar 

  45. Ivey A, Hills RK, Simpson MA, Jovanovic JV, Gilkes A, Grech A, et al. Assessment of minimal residual disease in standard-risk AML. N Engl J Med. 2016;374:422–33.

    Article  CAS  PubMed  Google Scholar 

  46. Buccisano F, Maurillo L, Spagnoli A, Del Principe MI, Fraboni D, Panetta P, et al. Cytogenetic and molecular diagnostic characterization combined to postconsolidation minimal residual disease assessment by flow cytometry improves risk stratification in adult acute myeloid leukemia. Blood. 2010;116:2295–303.

    Article  CAS  PubMed  Google Scholar 

  47. Walter RB, Gooley TA, Wood BL, Milano F, Fang M, Sorror ML, et al. Impact of pretransplantation minimal residual disease, as detected by multiparametric flow cytometry, on outcome of myeloablative hematopoietic cell transplantation for acute myeloid leukemia.J Clin Oncol. 2011;29:1190–7.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Grimwade D, Freeman SD. Defining minimal residual disease in acute myeloid leukemia: which platforms are ready for “prime time”? Blood. 2014;124:3345–55.

    Article  CAS  PubMed  Google Scholar 

  49. Hourigan CS, Gale RP, Gormley NJ, Ossenkoppele GJ, Walter RB. Measurable residual disease testing in acute myeloid leukaemia. Leukemia. 2017;31:1482–90.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge all investigators involved in the PETHEMA 99, 2007 and 2010 protocols (named in the Supplemental Annex). This study was supported by the Centro de Investigación Biomédica en Red – Área de Oncología - del Instituto de Salud Carlos III (CIBERONC; CB16/12/00369, CB16/12/00233, CB16/12/00284 and CB16/12/00400), Instituto de Salud Carlos III/Subdirección General de Investigación Sanitaria (FIS No. PI16/01661, PI16/00517 and PI18/01946), Gerencia Regional de Salud de CyL (GRS 1346/A/16) and the Plan de Investigación de la Universidad de Navarra (PIUNA 2014-18). This study was supported internationally by the Cancer Research UK, FCAECC and AIRC under the Accelerator Award Program EDITOR.

Author information

Author notes

  1. These authors contributed equally: B Paiva, M-B Vidriales, A Sempere

Authors and Affiliations

  1. Clínica Universidad de Navarra, Centro de Investigación Médica Aplicada (CIMA), IDISNA, CIBER-ONC number CB16/12/00369, Pamplona, Spain

    Bruno Paiva, Juan-Jose Garces, Catia Simoes & Jesús F. San Miguel

  2. Department of Hematology, University Hospital of Salamanca (HUS/IBSAL), CIBERONC (CB16/12/002333) and Center for Cancer Research-IBMCC (USAL-CSIC), Salamanca, Spain

    María-Belen Vidriales & Marcos González-Díaz

  3. Hospital Universitario y Politécnico La Fe, CIBER-ONC number CB16/12/00284, Valencia, Spain

    Amparo Sempere, Lourdes Cordón, David Martínez-Cuadrón, Miguel-Ángel Sanz & Pau Montesinos

  4. Hospital General Universitario de Alicante, Alicante, Spain

    Fabián Tarín & Carmen Botella

  5. Hospital Universitario Central de Asturias, Instituto de Investigación Sanitaria y Universitario Oncológico del Principado de Asturias (ISPA / IUOPA), Oviedo, Spain

    Enrique Colado & Teresa Bernal

  6. Hospital Clínico San Carlos, Madrid, Spain

    Celina Benavente

  7. Hospital Universitario 12 de Octubre, Madrid, Spain

    María-Teresa Cedena & Joaquín Martínez-López

  8. Hospital Reina Sofía, Córdoba, Spain

    Joaquín Sánchez & Josefina Serrano

  9. Hopsital Universitario Virgen del Rocío, Instituto de Biomedicina (IBIS / CSIC / CIBERONC), Universidad de Sevilla, Sevilla, Spain

    Teresa Caballero-Velazquez & José A. Pérez-Simón

  10. Hospital de Clinicas. Montevideo, Uruguay, Spain

    Sofia Grille

  11. Hospital Universitario de Gran Canaria Doctor Negrin, Las Palmas, Spain

    Carlos Rodríguez-Medina

  12. Hospital General de Albacete, Albacete, Spain

    Lorenzo Algarra

  13. Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain

    Juan-Manuel Alonso-Domínguez

  14. Hospital Morales Messeguer, Murcia, Spain

    María-Luz Amigo

  15. Hospital Regional Universitario de Málaga, Malaga, Spain

    Manuel Barrios

  16. Hospital General Universitario de Castellón, Castellón de la Plana, Spain

    Raimundo García-Boyero

  17. Hospital Universitario Marqués de Valdecilla, Santander, Spain

    Mercedes Colorado

  18. Hospital HM Madrid, Madrid, Spain

    Jaime Pérez-Oteyza

  19. Hospital Clinico de Santiago de Compostela, Santiago de Compostela, Spain

    Manuel Pérez-Encinas

  20. Hospital Miguel Servet, Zaragoza, Spain

    Lisette Costilla-Barriga

  21. Hospital Universitario Dr. Peset, Valencia, Spain

    María-José Sayas

  22. Hospital Universitario Virgen Macarena, Sevilla, Spain

    Olga Pérez

  23. Clinica FOSCAL, Santander, Colombia

    Claudia Sossa

  24. Cancer Research Center (IBMCC-CSIC/USAL-IBSAL); Cytometry Service (NUCLEUS) and Department of Medicine, University of Salamanca, Salamanca, Spain

    Alberto Orfao

  25. (USAL) Centro de Investigación Biomédica en Red de Cáncer, Instituto Carlos III, Salamanca, Spain

    Alberto Orfao

  26. CIBER-ONC number CB16/12/00400, Salamanca, Spain

    Alberto Orfao

Authors
  1. Bruno Paiva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. María-Belen Vidriales
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amparo Sempere
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fabián Tarín
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Enrique Colado
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Celina Benavente
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. María-Teresa Cedena
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Joaquín Sánchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Teresa Caballero-Velazquez
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Lourdes Cordón
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Juan-Jose Garces
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Catia Simoes
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. David Martínez-Cuadrón
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Teresa Bernal
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Carmen Botella
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Sofia Grille
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Josefina Serrano
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Carlos Rodríguez-Medina
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Lorenzo Algarra
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Juan-Manuel Alonso-Domínguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. María-Luz Amigo
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Manuel Barrios
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Raimundo García-Boyero
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Mercedes Colorado
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Jaime Pérez-Oteyza
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Manuel Pérez-Encinas
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Lisette Costilla-Barriga
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. María-José Sayas
    View author publications

    You can also search for this author in PubMed Google Scholar

  29. Olga Pérez
    View author publications

    You can also search for this author in PubMed Google Scholar

  30. Marcos González-Díaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  31. José A. Pérez-Simón
    View author publications

    You can also search for this author in PubMed Google Scholar

  32. Joaquín Martínez-López
    View author publications

    You can also search for this author in PubMed Google Scholar

  33. Claudia Sossa
    View author publications

    You can also search for this author in PubMed Google Scholar

  34. Alberto Orfao
    View author publications

    You can also search for this author in PubMed Google Scholar

  35. Jesús F. San Miguel
    View author publications

    You can also search for this author in PubMed Google Scholar

  36. Miguel-Ángel Sanz
    View author publications

    You can also search for this author in PubMed Google Scholar

  37. Pau Montesinos
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

PETHEMA (Programa para el Estudio de la Terapéutica en Hemopatías Malignas) cooperative study group

Corresponding author

Correspondence to Pau Montesinos.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

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

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Paiva, B., Vidriales, MB., Sempere, A. et al. Impact of measurable residual disease by decentralized flow cytometry: a PETHEMA real-world study in 1076 patients with acute myeloid leukemia. Leukemia 35, 2358–2370 (2021). https://doi.org/10.1038/s41375-021-01126-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41375-021-01126-3

This article is cited by

Search

Advanced search

Quick links