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Acute Leukemias

Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center

Leukemia volume 29, pages 312–320 (2015)Cite this article

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Abstract

Therapeutic resistance remains the principal problem in acute myeloid leukemia (AML). We used area under receiver-operating characteristic curves (AUCs) to quantify our ability to predict therapeutic resistance in individual patients, where AUC=1.0 denotes perfect prediction and AUC=0.5 denotes a coin flip, using data from 4601 patients with newly diagnosed AML given induction therapy with 3+7 or more intense standard regimens in UK Medical Research Council/National Cancer Research Institute, Dutch–Belgian Cooperative Trial Group for Hematology/Oncology/Swiss Group for Clinical Cancer Research, US cooperative group SWOG and MD Anderson Cancer Center studies. Age, performance status, white blood cell count, secondary disease, cytogenetic risk and FLT3-ITD/NPM1 mutation status were each independently associated with failure to achieve complete remission despite no early death (‘primary refractoriness’). However, the AUC of a bootstrap-corrected multivariable model predicting this outcome was only 0.78, indicating only fair predictive ability. Removal of FLT3-ITD and NPM1 information only slightly decreased the AUC (0.76). Prediction of resistance, defined as primary refractoriness or short relapse-free survival, was even more difficult. Our limited ability to forecast resistance based on routinely available pretreatment covariates provides a rationale for continued randomization between standard and new therapies and supports further examination of genetic and posttreatment data to optimize resistance prediction in AML.

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Acknowledgements

Research reported in this publication was supported by grants from the National Cancer Institute/National Institutes of Health (NCI/NIH; R21-CA182010 to RBW and MO, and R01-CA090998-09 to MO). SWOG trials were supported in part by the following PHS Cooperative Agreement grant numbers awarded by the NCI/NIH: U10-CA032102, U10-CA038926 and U10-CA105409. RBW is a Leukemia & Lymphoma Society Scholar in Clinical Research.

Author information

Authors and Affiliations

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

    R B Walter, F R Appelbaum & E H Estey

  2. Division of Hematology, Department of Medicine, University of Washington, Seattle, WA, USA

    R B Walter & E H Estey

  3. Department of Epidemiology, University of Washington, Seattle, WA, USA

    R B Walter

  4. SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    M Othus

  5. Department of Haematology, School of Medicine, Cardiff University, Cardiff, UK

    A K Burnett, R K Hills & A Evans

  6. Department of Hematology, Erasmus University Medical Center, Rotterdam, The Netherlands

    B Löwenberg

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

    H M Kantarjian, F Ravandi & S R Pierce

  8. Division of Hematology, VU University Medical Center, Amsterdam, The Netherlands

    G J Ossenkoppele

  9. Department of Medical Oncology, University Hospital, Bern, Switzerland

    T Pabst

  10. Department of Hematology, Cliniques Universitaires Saint-Luc UCL, Brussels, Belgium

    M-C Vekemans

  11. Department of Medicine, Division of Medical Oncology, University of Washington, Seattle, WA, USA

    F R Appelbaum

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  1. R B Walter
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Correspondence to R B Walter.

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Additional information

Presented in part at the 55th Annual Meeting of the American Society of Hematology, December 7–10, 2013, New Orleans, LA Version: July 23, 2014.

Supplementary Information accompanies this paper on the Leukemia website

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Walter, R., Othus, M., Burnett, A. et al. Resistance prediction in AML: analysis of 4601 patients from MRC/NCRI, HOVON/SAKK, SWOG and MD Anderson Cancer Center. Leukemia 29, 312–320 (2015). https://doi.org/10.1038/leu.2014.242

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