Scientific Reports (Nov 2022)

EEG-based grading of immune effector cell-associated neurotoxicity syndrome

  • Daniel K. Jones,
  • Christine A. Eckhardt,
  • Haoqi Sun,
  • Ryan A. Tesh,
  • Preeti Malik,
  • Syed Quadri,
  • Marcos Santana Firme,
  • Meike van Sleuwen,
  • Aayushee Jain,
  • Ziwei Fan,
  • Jin Jing,
  • Wendong Ge,
  • Fábio A. Nascimento,
  • Irfan S. Sheikh,
  • Caron Jacobson,
  • Matthew Frigault,
  • Eyal Y. Kimchi,
  • Sydney S. Cash,
  • Jong Woo Lee,
  • Jorg Dietrich,
  • M. Brandon Westover

DOI
https://doi.org/10.1038/s41598-022-24010-1
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 13

Abstract

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Abstract CAR-T cell therapy is an effective cancer therapy for multiple refractory/relapsed hematologic malignancies but is associated with substantial toxicity, including Immune Effector Cell Associated Neurotoxicity Syndrome (ICANS). Improved detection and assessment of ICANS could improve management and allow greater utilization of CAR-T cell therapy, however, an objective, specific biomarker has not been identified. We hypothesized that the severity of ICANS can be quantified based on patterns of abnormal brain activity seen in electroencephalography (EEG) signals. We conducted a retrospective observational study of 120 CAR-T cell therapy patients who had received EEG monitoring. We determined a daily ICANS grade for each patient through chart review. We used visually assessed EEG features and machine learning techniques to develop the Visual EEG-Immune Effector Cell Associated Neurotoxicity Syndrome (VE-ICANS) score and assessed the association between VE-ICANS and ICANS. We also used it to determine the significance and relative importance of the EEG features. We developed the Visual EEG-ICANS (VE-ICANS) grading scale, a grading scale with a physiological basis that has a strong correlation to ICANS severity (R = 0.58 [0.47–0.66]) and excellent discrimination measured via area under the receiver operator curve (AUC = 0.91 for ICANS ≥ 2). This scale shows promise as a biomarker for ICANS which could help to improve clinical care through greater accuracy in assessing ICANS severity.