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ACUTE MYELOID LEUKEMIA

Association of hematologic response and assay sensitivity on the prognostic impact of measurable residual disease in acute myeloid leukemia: a systematic review and meta-analysis

Leukemia volume 36, pages 2817–2826 (2022)Cite this article

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Abstract

Measurable residual disease (MRD) is associated with relapse and survival in acute myeloid leukemia (AML). We aimed to quantify the impact of MRD on outcomes across clinical contexts, including its association with hematologic response and MRD assay sensitivity. We performed systematic literature review and meta-analysis of 48 studies that reported the association between MRD and overall survival (OS) or disease-free survival (DFS) in AML and provided information on the MRD threshold used and the hematologic response of the study population. Among studies limited to patients in complete remission (CR), the estimated 5-year OS for the MRD-negative and MRD-positive groups was 67% (95% Bayesian credible interval [CrI], 53–77%) and 31% (95% CrI, 18–44%), respectively. Achievement of an MRD-negative response was associated with superior DFS and OS, regardless of MRD threshold or analytic sensitivity. Among patients in CR, the benefit of MRD negativity was highest in studies using an MRD cutoff less than 0.1%. The beneficial impact of MRD negativity was observed across MRD assays and timing of MRD assessment. In patients with AML in morphological remission, achievement of MRD negativity is associated with superior DFS and OS, irrespective of hematologic response or the MRD threshold used.

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Fig. 1: Flow diagram of the study selection process.
Fig. 2: Estimated survival curves according to MRD response for the entire study population and for only studies reporting patients in CR.
Fig. 3: Estimated survival curves according to MRD response for the entire study population, stratified by MRD threshold.
Fig. 4: Hazard ratios (HRs) by MRD threshold for studies that only included patients in CR.
Fig. 5: Hazard ratios (HRs) by subgroups for the entire study population, stratified by MRD threshold.
Fig. 6: Hazard ratios (HRs) by subgroups for the entire study population, stratified by inclusion of only patients in CR versus inclusion of patients with lesser responses.

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Data availability

Data may be shared upon reasonable request to the corresponding author.

References

  1. Short NJ, Rytting ME, Cortes JE. Acute myeloid leukaemia. Lancet. 2018;392:593–606.

    Article  PubMed  Google Scholar 

  2. 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  Google Scholar 

  3. Walter RB, Kantarjian HM, Huang X, Pierce SA, Sun Z, Gundacker HM, et al. Effect of complete remission and responses less than complete remission on survival in acute myeloid leukemia: a combined Eastern Cooperative Oncology Group, Southwest Oncology Group, and M. D. Anderson Cancer Center Study. J Clin Oncol: Off J Am Soc Clin Oncol. 2010;28:1766–71.

    Article  Google Scholar 

  4. Chen X, Xie H, Wood BL, Walter RB, Pagel JM, Becker PS, et al. Relation of clinical response and minimal residual disease and their prognostic impact on outcome in acute myeloid leukemia. J Clin Oncol: Off J Am Soc Clin Oncol. 2015;33:1258–64.

    Article  Google Scholar 

  5. Short NJ, Rafei H, Daver N, Hwang H, Ning J, Jorgensen JL, et al. Prognostic impact of complete remission with MRD negativity in patients with relapsed or refractory AML. Blood Adv. 2020;4:6117–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Aitken MJL, Ravandi F, Patel KP, Short NJ. Prognostic and therapeutic implications of measurable residual disease in acute myeloid leukemia. J Hematol Oncol. 2021;14:137.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Short NJ, Zhou S, Fu C, Berry DA, Walter RB, Freeman SD, et al. Association of measurable residual disease with survival outcomes in patients with acute myeloid leukemia: a systematic review and meta-analysis. JAMA Oncol. 2020;6:1890–9.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gui G, Hourigan CS. Measurable residual disease assessment as a Surrogate Marker in new drug development in acute myeloid leukemia. Cancer J. 2022;28:73–7.

    Article  CAS  PubMed  Google Scholar 

  9. Przepiorka D, de Claro RA, Pazdur R. The role of acute myeloid leukemia minimal Residual Disease in regulatory decision-making. JAMA Oncol. 2021;7:784.

    Article  PubMed  Google Scholar 

  10. Schuurhuis GJ, Heuser M, Freeman S, Bene MC, 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 

  11. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  12. San Miguel JF, Vidriales MB, Lopez-Berges C, Diaz-Mediavilla J, Gutierrez N, Canizo 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 

  13. Feller N, van der Pol MA, van Stijn A, Weijers GW, Westra AH, Evertse BW, et al. MRD parameters using immunophenotypic detection methods are highly reliable in predicting survival in acute myeloid leukaemia. Leukemia. 2004;18:1380–90.

    Article  CAS  PubMed  Google Scholar 

  14. Perea G, Lasa A, Aventin A, Domingo A, Villamor N, Queipo de Llano MP, et al. Prognostic value of minimal residual disease (MRD) in acute myeloid leukemia (AML) with favorable cytogenetics [t(8;21) and inv(16)]. Leukemia. 2006;20:87–94.

    Article  CAS  PubMed  Google Scholar 

  15. Laane E, Derolf AR, Bjorklund E, Mazur J, Everaus H, Soderhall 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 

  16. 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: Off J Am Soc Clin Oncol. 2006;24:3686–92.

    Article  Google Scholar 

  17. Maurillo L, Buccisano F, Spagnoli A, Del Poeta G, Panetta P, Neri B, et al. Monitoring of minimal residual disease in adult acute myeloid leukemia using peripheral blood as an alternative source to bone marrow. Haematologica. 2007;92:605–11.

    Article  PubMed  Google Scholar 

  18. Al-Mawali A, Gillis D, Lewis I. The use of receiver operating characteristic analysis for detection of minimal residual disease using five-color multiparameter flow cytometry in acute myeloid leukemia identifies patients with high risk of relapse. Cytom Part B, Clin Cytom. 2009;76:91–101.

    Article  Google Scholar 

  19. 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 

  20. Corbacioglu A, Scholl C, Schlenk RF, Eiwen K, Du J, Bullinger L, et al. Prognostic impact of minimal residual disease in CBFB-MYH11-positive acute myeloid leukemia. J Clin Oncol: Off J Am Soc Clin Oncol. 2010;28:3724–9.

    Article  CAS  Google Scholar 

  21. van der Velden VH, van der Sluijs-Geling A, Gibson BE, te Marvelde JG, Hoogeveen PG, Hop WC, 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 

  22. Inoue D, Maruoka H, Takahashi T. Clinical analysis and optimization of postremission therapy for acute myeloid leukemia patients with minimal residual disease as determined by flow cytometry. Mediterranean J Hematol Infect Dis. 2010;2:e2010020.

    Article  Google Scholar 

  23. Kronke J, Schlenk RF, Jensen KO, Tschurtz F, Corbacioglu A, Gaidzik VI, et al. Monitoring of minimal residual disease in NPM1-mutated acute myeloid leukemia: a study from the German-Austrian acute myeloid leukemia study group. J Clin Oncol: Off J Am Soc Clin Oncol. 2011;29:2709–16.

    Article  Google Scholar 

  24. Chen Y, Cortes J, Estrov Z, Faderl S, Qiao W, Abruzzo L, et al. Persistence of cytogenetic abnormalities at complete remission after induction in patients with acute myeloid leukemia: prognostic significance and the potential role of allogeneic stem-cell transplantation. J Clin Oncol: Off J Am Soc Clin Oncol. 2011;29:2507–13.

    Article  Google Scholar 

  25. Terwijn M, Kelder A, Snel AN, Rutten AP, Scholten WJ, Oussoren YJ, et al. Minimal residual disease detection defined as the malignant fraction of the total primitive stem cell compartment offers additional prognostic information in acute myeloid leukaemia. Int J Lab Hematol. 2012;34:432–41.

    Article  CAS  PubMed  Google Scholar 

  26. 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: Off J Am Soc Clin Oncol. 2012;30:3625–32.

    Article  Google Scholar 

  27. Xu XJ, Feng JH, Tang YM, Shen HQ, Song H, Yang SL, et al. Prognostic significance of flow cytometric minimal residual disease assessment after the first induction course in Chinese childhood acute myeloid leukemia. Leuk Res. 2013;37:134–8.

    Article  PubMed  Google Scholar 

  28. Zhang L, Li Q, Li W, Liu B, Wang Y, Lin D, et al. Monitoring of minimal residual disease in acute myeloid leukemia with t(8;21)(q22;q22). Int J Hematol. 2013;97:786–92.

    Article  CAS  PubMed  Google Scholar 

  29. Shayegi N, Kramer M, Bornhauser M, Schaich M, Schetelig J, Platzbecker U, et al. The level of residual disease based on mutant NPM1 is an independent prognostic factor for relapse and survival in AML. Blood. 2013;122:83–92.

    Article  CAS  PubMed  Google Scholar 

  30. Marani C, Clavio M, Grasso R, Colombo N, Guolo F, Kunkl A, et al. Integrating post induction WT1 quantification and flow-cytometry results improves minimal residual disease stratification in acute myeloid leukemia. Leuk Res. 2013;37:1606–11.

    Article  PubMed  Google Scholar 

  31. 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: Off J Am Soc Clin Oncol. 2013;31:3889–97.

    Article  Google Scholar 

  32. 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: Off J Am Soc Clin Oncol. 2013;31:4123–31.

    Article  Google Scholar 

  33. Rossi G, Minervini MM, Melillo L, di Nardo F, de Waure C, Scalzulli PR, et al. Predictive role of minimal residual disease and log clearance in acute myeloid leukemia: a comparison between multiparameter flow cytometry and Wilm’s tumor 1 levels. Ann Hematol. 2014;93:1149–57.

    CAS  PubMed  Google Scholar 

  34. Hubmann M, Kohnke T, Hoster E, Schneider S, Dufour A, Zellmeier E, et al. Molecular response assessment by quantitative real-time polymerase chain reaction after induction therapy in NPM1-mutated patients identifies those at high risk of relapse. Haematologica. 2014;99:1317–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Kohnke T, Sauter D, Ringel K, Hoster E, Laubender RP, Hubmann M, et al. Early assessment of minimal residual disease in AML by flow cytometry during aplasia identifies patients at increased risk of relapse. Leukemia. 2015;29:377–86.

    Article  CAS  PubMed  Google Scholar 

  36. Zhang L, Cao Z, Ruan M, Zeng Q, Zhao L, Li Q, et al. Monitoring the AML1/ETO fusion transcript to predict outcome in childhood acute myeloid leukemia. Pediatr Blood Cancer. 2014;61:1761–6.

    Article  CAS  PubMed  Google Scholar 

  37. Hirsch P, Labopin M, Viguie F, Perot C, Isnard F, Mamez AC, et al. Interest of cytogenetic and FISH evaluation for prognosis evaluation in 198 patients with acute myeloid leukemia in first complete remission in a single institution. Leuk Res. 2014;38:907–12.

    Article  CAS  PubMed  Google Scholar 

  38. Lambert J, Lambert J, Nibourel O, Pautas C, Hayette S, Cayuela JM, et al. MRD assessed by WT1 and NPM1 transcript levels identifies distinct outcomes in AML patients and is influenced by gemtuzumab ozogamicin. Oncotarget. 2014;5:6280–8.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Terwijn M, Zeijlemaker W, Kelder A, Rutten AP, Snel AN, Scholten WJ, et al. Leukemic stem cell frequency: a strong biomarker for clinical outcome in acute myeloid leukemia. PloS One. 2014;9:e107587.

    Article  PubMed  PubMed Central  Google Scholar 

  40. 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 

  41. Klco JM, Miller CA, Griffith M, Petti A, Spencer DH, Ketkar-Kulkarni S, et al. Association between mutation clearance after induction therapy and outcomes in acute myeloid leukemia. Jama. 2015;314:811–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zeijlemaker W, Kelder A, Oussoren-Brockhoff YJ, Scholten WJ, Snel AN, Veldhuizen D, et al. Peripheral blood minimal residual disease may replace bone marrow minimal residual disease as an immunophenotypic biomarker for impending relapse in acute myeloid leukemia. Leukemia. 2016;30:708–15.

    Article  CAS  PubMed  Google Scholar 

  43. Willekens C, Blanchet O, Renneville A, Cornillet-Lefebvre P, Pautas C, Guieze R, et al. Prospective long-term minimal residual disease monitoring using RQ-PCR in RUNX1-RUNX1T1-positive acute myeloid leukemia: results of the French CBF-2006 trial. Haematologica. 2016;101:328–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Keino D, Kinoshita A, Tomizawa D, Takahashi H, Ida K, Kurosawa H, et al. Residual disease detected by multidimensional flow cytometry shows prognostic significance in childhood acute myeloid leukemia with intermediate cytogenetics and negative FLT3-ITD: a report from the Tokyo Children’s Cancer Study Group. Int J Hematol. 2016;103:416–22.

    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. Kim Y, Lee GD, Park J, Yoon JH, Kim HJ, Min WS, et al. Quantitative fragment analysis of FLT3-ITD efficiently identifying poor prognostic group with high mutant allele burden or long ITD length. Blood Cancer J. 2015;5:e336.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Tierens A, Bjorklund E, Siitonen S, Marquart HV, Wulff-Juergensen G, Pelliniemi TT, 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 

  48. Othus M, Wood BL, Stirewalt DL, Estey EH, Petersdorf SH, Appelbaum FR, et al. Effect of measurable (‘minimal’) residual disease (MRD) information on prediction of relapse and survival in adult acute myeloid leukemia. Leukemia. 2016;30:2080–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Ravandi F, Jorgensen J, Borthakur G, Jabbour E, Kadia T, Pierce S, et al. Persistence of minimal residual disease assessed by multiparameter flow cytometry is highly prognostic in younger patients with acute myeloid leukemia. Cancer. 2017;123:426–35.

    Article  CAS  PubMed  Google Scholar 

  50. Buldini B, Rizzati F, Masetti R, Fagioli F, Menna G, Micalizzi C, et al. Prognostic significance of flow-cytometry evaluation of minimal residual disease in children with acute myeloid leukaemia treated according to the AIEOP-AML 2002/01 study protocol. Br J Haematol. 2017;177:116–26.

    Article  PubMed  Google Scholar 

  51. Parkin B, Londono-Joshi A, Kang Q, Tewari M, Rhim AD, Malek SN. Ultrasensitive mutation detection identifies rare residual cells causing acute myelogenous leukemia relapse. J Clin Investig. 2017;127:3484–95.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Boddu P, Jorgensen J, Kantarjian H, Borthakur G, Kadia T, Daver N, et al. Achievement of a negative minimal residual disease state after hypomethylating agent therapy in older patients with AML reduces the risk of relapse. Leukemia. 2018;32:241–4.

    Article  CAS  PubMed  Google Scholar 

  53. Lacombe F, Campos L, Allou K, Arnoulet C, Delabarthe A, Dumezy F, et al. Prognostic value of multicenter flow cytometry harmonized assessment of minimal residual disease in acute myeloblastic leukemia. Hematological Oncol. 2018;36:422–8.

    Article  CAS  Google Scholar 

  54. Ferret Y, Boissel N, Helevaut N, Madic J, Nibourel O, Marceau-Renaut A, et al. Clinical relevance of IDH1/2 mutant allele burden during follow-up in acute myeloid leukemia. A study by the French ALFA group. Haematologica. 2018;103:822–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Freeman SD, Hills RK, Virgo P, Khan N, Couzens S, Dillon R, et al. Measurable residual disease at induction redefines partial response in acute myeloid leukemia and stratifies outcomes in patients at standard risk without NPM1 mutations. J Clin Oncol: Off J Am Soc Clin Oncol. 2018;36:1486–97.

    Article  CAS  Google Scholar 

  56. Morita K, Kantarjian HM, Wang F, Yan Y, Bueso-Ramos C, Sasaki K, et al. Clearance of Somatic mutations at remission and the risk of relapse in acute myeloid leukemia. J Clin Oncol: Off J Am Soc Clin Oncol. 2018;36:1788–97.

    Article  CAS  Google Scholar 

  57. Boddu P, Gurguis C, Sanford D, Cortes J, Akosile M, Ravandi F, et al. Response kinetics and factors predicting survival in core-binding factor leukemia. Leukemia. 2018;32:2698–701.

    Article  CAS  PubMed  Google Scholar 

  58. Onecha E, Linares M, Rapado I, Ruiz-Heredia Y, Martinez-Sanchez P, Cedena T, et al. A novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia. Haematologica. 2019;104:288–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Ok CY, Loghavi S, Sui D, Wei P, Kanagal-Shamanna R, Yin CC, et al. Persistent IDH1/2 mutations in remission can predict relapse in patients with acute myeloid leukemia. Haematologica. 2019;104:305–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Wierda WG, Rawstron A, Cymbalista F, Badoux X, Rossi D, Brown JR, et al. Measurable residual disease in chronic lymphocytic leukemia: expert review and consensus recommendations. Leukemia. 2021;35:3059–72.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Short NJ, Jabbour E, Albitar M, de Lima M, Gore L, Jorgensen J, et al. Recommendations for the assessment and management of measurable residual disease in adults with acute lymphoblastic leukemia: a consensus of North American experts. Am J Hematol. 2019;94:257–65.

    Article  PubMed  Google Scholar 

  62. Heuser M, Freeman SD, Ossenkoppele GJ, Buccisano F, Hourigan CS, Ngai LL, et al. 2021 Update on MRD in acute myeloid leukemia: a consensus document from the European LeukemiaNet MRD Working Party. Blood. 2021;138:2753–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Norsworthy KJ, Gao X, Ko CW, Pulte ED, Zhou J, Gong Y, et al. Response rate, event-free survival, and overall survival in newly diagnosed acute myeloid leukemia: US Food and Drug Administration Trial-Level and Patient-Level Analyses. J Clin Oncol: Off J Am Soc Clin Oncol. 2022;40:847–54.

    Article  CAS  Google Scholar 

  64. U.S. Department of Health and Human Services. Hematologic malignancies: regulatory considerations for use of minimal residual disease in development of drug and biological products for treatment—guidance for industry. [cited 18 April 2022]; Available from: https://www.fda.gov/vaccines-blood-biologics/guidance-compliance-regulatory-information-biologics/biologics-guidances.

  65. Gokbuget N, Dombret H, Bonifacio M, Reichle A, Graux C, Faul C, et al. Blinatumomab for minimal residual disease in adults with B-cell precursor acute lymphoblastic leukemia. Blood. 2018;131:1522–31.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Jen EY, Xu Q, Schetter A, Przepiorka D, Shen YL, Roscoe D, et al. FDA approval: Blinatumomab for patients with B-cell precursor acute lymphoblastic leukemia in morphologic remission with minimal residual disease. Clin Cancer Res: Off J Am Assoc Cancer Res. 2019;25:473–7.

    Article  CAS  Google Scholar 

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Funding

Supported by an MD Anderson Cancer Center Support Grant (CA016672) and SPORE. NJS is supported by the K12 Paul Calabresi Clinical Oncology Scholar Award and the American Society of Hematology Junior Faculty Scholar Award in Clinical Research. Supported in part by the Intramural Research Program of the National Heart, Lung, and Blood Institute of the National Institutes of Health (CSH). The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

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Author notes

  1. These authors contributed equally: Nicholas J. Short, Chenqi Fu.

  2. These authors jointly supervised this work: Shouhao Zhou, Farhad Ravandi.

Authors and Affiliations

  1. Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Nicholas J. Short, Hagop Kantarjian & Farhad Ravandi

  2. Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA

    Chenqi Fu & Shouhao Zhou

  3. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Donald A. Berry, Xuelin Huang, Graciela Nogueras Gonzalez, Hyunsoo Hwang & Xinyue Qi

  4. Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA

    Roland B. Walter

  5. Institute of Infection and Immunity, University of Birmingham, Birmingham, UK

    Sylvie D. Freeman

  6. Laboratory of Myeloid Malignancies, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

    Christopher S. Hourigan

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Contributions

NJS and CF conceptualized the study design, analyzed the data, and wrote the first draft of the manuscript; RBW, SDF and CSH selected studies for inclusion the meta-analysis, XH, GNG, HH and XQ performed statistical analyses; DAB, HK, SZ and FR conceptualized the study design and supervised the analyses. All authors reviewed and approved the final version of the manuscript.

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Correspondence to Shouhao Zhou or Farhad Ravandi.

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Short, N.J., Fu, C., Berry, D.A. et al. Association of hematologic response and assay sensitivity on the prognostic impact of measurable residual disease in acute myeloid leukemia: a systematic review and meta-analysis. Leukemia 36, 2817–2826 (2022). https://doi.org/10.1038/s41375-022-01692-0

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