Standardized assay for assessment of minimal residual disease in blood, bone marrow and apheresis from patients with plasma cell myeloma

[1]  A. Porwit,et al.  Visualization of Cell Composition and Maturation in the Bone Marrow Using 10‐Color Flow Cytometry and Radar Plots , 2018, Cytometry. Part B, Clinical cytometry.

[2]  A. Órfão,et al.  MRD detection in multiple myeloma: comparison between MSKCC 10-color single-tube and EuroFlow 8-color 2-tube methods. , 2017, Blood advances.

[3]  N. Puig,et al.  Analytical and clinical validation of a novel in-house deep-sequencing method for minimal residual disease monitoring in a phase II trial for multiple myeloma , 2017, Leukemia.

[4]  A Orfao,et al.  Next Generation Flow for highly sensitive and standardized detection of minimal residual disease in multiple myeloma , 2017, Leukemia.

[5]  H. Goldschmidt,et al.  International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma. , 2016, The Lancet. Oncology.

[6]  P. Wallace,et al.  Flow cytometry quality requirements for monitoring of minimal disease in plasma cell myeloma , 2016, Cytometry. Part B, Clinical cytometry.

[7]  M. Stetler-Stevenson,et al.  Assessment of minimal residual disease in myeloma and the need for a consensus approach , 2016, Cytometry. Part B, Clinical cytometry.

[8]  B. Paiva,et al.  Consensus guidelines on plasma cell myeloma minimal residual disease analysis and reporting , 2016, Cytometry. Part B, Clinical cytometry.

[9]  A. Órfão,et al.  Consensus guidelines for myeloma minimal residual disease sample staining and data acquisition , 2016, Cytometry. Part B, Clinical cytometry.

[10]  E. Ocio,et al.  Treatment for patients with newly diagnosed multiple myeloma in 2015. , 2015, Blood reviews.

[11]  A. Lesokhin,et al.  Minimal residual disease in multiple myeloma: bringing the bench to the bedside , 2015, Nature Reviews Clinical Oncology.

[12]  G. Morgan,et al.  Minimal residual disease in myeloma by flow cytometry: independent prediction of survival benefit per log reduction. , 2015, Blood.

[13]  H. Kantarjian,et al.  Multiple myeloma and chronic leukaemias in 2014: Improved understanding of disease biology and treatment , 2015, Nature Reviews Clinical Oncology.

[14]  G. Marti,et al.  Flow cytometry detection of minimal residual disease in multiple myeloma: Lessons learned at FDA‐NCI roundtable symposium , 2014, American journal of hematology.

[15]  P. Mäntymaa,et al.  Comparative analysis of minimal residual disease detection by multiparameter flow cytometry and enhanced ASO RQ-PCR in multiple myeloma , 2014, Blood Cancer Journal.

[16]  T. Cedena,et al.  Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma. , 2014, Blood.

[17]  M. Stetler-Stevenson,et al.  Minimal residual disease: what are the minimum requirements? , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[18]  N. Puig,et al.  Critical evaluation of ASO RQ-PCR for minimal residual disease evaluation in multiple myeloma. A comparative analysis with flow cytometry , 2014, Leukemia.

[19]  J. Besalduch,et al.  Clinical applicability and prognostic significance of molecular response assessed by fluorescent‐PCR of immunoglobulin genes in multiple myeloma. Results from a GEM/PETHEMA study , 2013, British journal of haematology.

[20]  James A. Hutchinson,et al.  Standardization of whole blood immune phenotype monitoring for clinical trials: panels and methods from the ONE study , 2013, Transplantation research.

[21]  M. Stetler-Stevenson,et al.  Minimal residual disease testing in multiple myeloma by flow cytometry: major heterogeneity. , 2013, Blood.

[22]  G. Morgan,et al.  Minimal residual disease assessed by multiparameter flow cytometry in multiple myeloma: impact on outcome in the Medical Research Council Myeloma IX Study. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[23]  E. Montserrat,et al.  Improving efficiency and sensitivity: European Research Initiative in CLL (ERIC) update on the international harmonised approach for flow cytometric residual disease monitoring in CLL , 2013, Leukemia.

[24]  M. Terol,et al.  High-risk cytogenetics and persistent minimal residual disease by multiparameter flow cytometry predict unsustained complete response after autologous stem cell transplantation in multiple myeloma. , 2012, Blood.

[25]  B. Barlogie,et al.  Diagnostic usefulness and prognostic impact of CD200 expression in lymphoid malignancies and plasma cell myeloma. , 2012, American journal of clinical pathology.

[26]  R. Hoffman Treatment of patients with cocaine-induced arrhythmias: bringing the bench to the bedside. , 2010, British journal of clinical pharmacology.

[27]  J. Byrd,et al.  International standardized approach for flow cytometric residual disease monitoring in chronic lymphocytic leukaemia , 2007, Leukemia.

[28]  D. Dingli,et al.  Flow cytometric detection of circulating myeloma cells before transplantation in patients with multiple myeloma: a simple risk stratification system. , 2005, Blood.

[29]  Viswanath Devanarayan,et al.  Fit-for-Purpose Method Development and Validation for Successful Biomarker Measurement , 2006, Pharmaceutical Research.

[30]  M. Altfeld,et al.  Standardization of cytokine flow cytometry assays , 2005, BMC Immunology.

[31]  A. Barclay,et al.  CD200 and membrane protein interactions in the control of myeloid cells. , 2002, Trends in immunology.

[32]  D. Carey,et al.  Syndecans: multifunctional cell-surface co-receptors. , 1997, The Biochemical journal.

[33]  F. Malavasi,et al.  Human CD38, a cell‐surface protein with multiple functions , 1996, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[34]  D. Fearon,et al.  Activation of B lymphocytes: integrating signals from CD19, CD22 and FcγRIIb1 , 1996 .

[35]  D. Fearon,et al.  Activation of B lymphocytes: integrating signals from CD19, CD22 and Fc gamma RIIb1. , 1996, Current opinion in immunology.

[36]  H. Schneider Failure mode and effect analysis : FMEA from theory to execution , 1996 .

[37]  C. Morimoto,et al.  The 1A4 molecule (CD27) is involved in T cell activation. , 1991, Journal of immunology.

[38]  P. Hoffman,et al.  Antibody-induced antigenic modulation is antigen dependent: characterization of 22 proteins on a malignant human B cell line. , 1986, Journal of immunology.

[39]  J. Griffin,et al.  Characterization of an antigen expressed by human natural killer cells. , 1983, Journal of immunology.