Metareview-informed Explainable Cytokine Storm Detection during CAR-T
cell Therapy
- URL: http://arxiv.org/abs/2206.10612v1
- Date: Mon, 20 Jun 2022 12:45:57 GMT
- Title: Metareview-informed Explainable Cytokine Storm Detection during CAR-T
cell Therapy
- Authors: Alex Bogatu, Magdalena Wysocka, Oskar Wysocki, Holly Butterworth,
Donal Landers, Elaine Kilgour, Andre Freitas
- Abstract summary: Cytokine release syndrome (CRS) is one of the most consequential adverse effects of chimeric antigen receptor therapies.
CRS could be identified by the analysis of specific cytokine and chemokine profiles that tend to exhibit similarities across patients.
- Score: 0.6332429219530602
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Cytokine release syndrome (CRS), also known as cytokine storm, is one of the
most consequential adverse effects of chimeric antigen receptor therapies that
have shown promising results in cancer treatment. When emerging, CRS could be
identified by the analysis of specific cytokine and chemokine profiles that
tend to exhibit similarities across patients. In this paper, we exploit these
similarities using machine learning algorithms and set out to pioneer a
meta--review informed method for the identification of CRS based on specific
cytokine peak concentrations and evidence from previous clinical studies. We
argue that such methods could support clinicians in analyzing suspect cytokine
profiles by matching them against CRS knowledge from past clinical studies,
with the ultimate aim of swift CRS diagnosis. During evaluation with
real--world CRS clinical data, we emphasize the potential of our proposed
method of producing interpretable results, in addition to being effective in
identifying the onset of cytokine storm.
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