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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.
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1 Massachusetts General Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); MGH, Clinical Data Animation Center (CDAC), Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Brigham Young University, Provo, USA (GRID:grid.253294.b) (ISNI:0000 0004 1936 9115)
2 Massachusetts General Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); MGH, Clinical Data Animation Center (CDAC), Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Brigham and Women’s Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294)
3 Massachusetts General Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); MGH, Clinical Data Animation Center (CDAC), Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924)
4 Washington University School of Medicine, Department of Neurology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002)
5 Massachusetts General Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X)
6 Brigham and Women’s Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294); Dana Farber Cancer Institute (DFCI), Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910)
7 Massachusetts General Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Dana Farber Cancer Institute (DFCI), Boston, USA (GRID:grid.65499.37) (ISNI:0000 0001 2106 9910)
8 Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); Brigham and Women’s Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.62560.37) (ISNI:0000 0004 0378 8294)
9 Massachusetts General Hospital (MGH), Department of Neurology, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); Harvard Medical School, Boston, USA (GRID:grid.38142.3c) (ISNI:000000041936754X); MGH, Clinical Data Animation Center (CDAC), Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924); MGH Cancer Center for Brain Health, Boston, USA (GRID:grid.32224.35) (ISNI:0000 0004 0386 9924)