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    Predicting Risk of Infection in Patients with Newly Diagnosed Multiple Myeloma: Utility of Immune Profiling

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    Author
    Teh, BW; Harrison, SJ; Allison, CC; Slavin, MA; Spelman, T; Worth, LJ; Thursky, KA; Ritchie, D; Pellegrini, M
    Date
    2017-10-05
    Source Title
    Frontiers in Immunology
    Publisher
    FRONTIERS MEDIA SA
    University of Melbourne Author/s
    Pellegrini, Marc; Harrison, Simon; Allison, Cody; Slavin, Monica; Spelman, Timothy; Worth, Leon; Thursky, Karin; Ritchie, David; Teh, Benjamin
    Affiliation
    Medicine and Radiology
    Medical Biology (W.E.H.I.)
    Sir Peter MacCallum Department of Oncology
    Surgery (St Vincent's)
    Medical Education
    Metadata
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    Document Type
    Journal Article
    Citations
    Teh, B. W., Harrison, S. J., Allison, C. C., Slavin, M. A., Spelman, T., Worth, L. J., Thursky, K. A., Ritchie, D. & Pellegrini, M. (2017). Predicting Risk of Infection in Patients with Newly Diagnosed Multiple Myeloma: Utility of Immune Profiling. FRONTIERS IN IMMUNOLOGY, 8 (OCT), https://doi.org/10.3389/fimmu.2017.01247.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/255400
    DOI
    10.3389/fimmu.2017.01247
    Abstract
    BACKGROUND: A translational study in patients with myeloma to determine the utility of immune profiling to predict infection risk in patients with hematological malignancy was conducted. METHODS: Baseline, end of induction, and maintenance peripheral blood mononuclear cells from 40 patients were evaluated. Immune cell populations and cytokines released from 1 × 106 cells/ml cultured in the presence of a panel of stimuli (cytomegalovirus, influenza, S. pneumoniae, phorbol myristate acetate/ionomycin) and in media alone were quantified. Patient characteristics and infective episodes were captured from clinical records. Immunological variables associated with increased risk for infection in the 3-month period following sample collection were identified using univariate analysis (p < 0.05) and refined with multivariable analysis to define a predictive immune profile. RESULTS: 525 stimulant samples with 19,950 stimulant-cytokine combinations across three periods were studied, including 61 episodes of infection. Mitogen-stimulated release of IL3 and IL5 were significantly associated with increased risk for subsequent infection during maintenance therapy. A lower Th1/Th2 ratio and higher cytokine response ratios for IL5 and IL13 during maintenance therapy were also significantly associated with increased risk for infection. On multivariable analysis, only IL5 in response to mitogen stimulation was predictive of infection. The lack of cytokine response and numerical value of immune cells were not predictive of infection. CONCLUSION: Profiling cytokine release in response to mitogen stimulation can assist with predicting subsequent onset of infection in patients with hematological malignancy during maintenance therapy.

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