Pre-CAR-T GTE Scoring of Electroencephalogram Abnormalities as a Predictive Biomarker for ICANS

Pre-CAR-T GTE Scoring of Electroencephalogram Abnormalities as a Predictive Biomarker for ICANS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Pre-CAR-T GTE Scoring of Electroencephalogram Abnormalities as a Predictive Biomarker for ICANS Koji Kato, Hidetaka Nakagaki, Takuji Yamauchi, Takahiro Mukaino, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6087514/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Apr, 2025 Read the published version in Bone Marrow Transplantation → Version 1 posted 11 You are reading this latest preprint version Abstract CD19-targeted chimeric antigen receptor (CAR)-T cell therapy is an effective treatment for relapsed or refractory B-cell lymphoma but is associated with adverse events such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). The pathogenesis of ICANS remains unclear, and predictive biomarkers are needed for risk stratification. This study evaluates the Grand Total EEG (GTE) score, a comprehensive scoring system for electroencephalogram (EEG) abnormalities, as a predictive biomarker for ICANS. We retrospectively analyzed 55 patients who underwent CAR-T cell therapy. ICANS occurred in 29% of patients, with CRS (grade ≥ 2) and axicabtagene ciloleucel identified as significant risk factors. Higher GTE scores correlated with ICANS severity after ICANS onset. Furthermore, the GTE score before CAR-T therapy was already significantly higher in the ICANS group (mean: 4.94 ± 3.11) than in the non-ICANS group (mean: 2.44 ± 1.71) with an odds ratio of 1.78. Patients with a history of high-dose methotrexate treatment showed elevated GTE scores, suggesting an association between CNS-targeted therapies and baseline brain dysfunction without symptoms. The findings of this study illustrate the efficacy of the GTE score as a novel biomarker for ICANS prediction. The score enables early risk stratification and directs interventions in CAR-T therapy. Biological sciences/Immunology/Immunotherapy Health sciences/Risk factors Biological sciences/Cancer/Haematological cancer/Lymphoma/Non-hodgkin lymphoma/B-cell lymphoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction CD19-targeted chimeric antigen receptor (CAR)-T cell therapy has emerged as a promising treatment for refractory and relapsed B-cell lymphoma [ 1 ]. However, it is frequently associated with specific adverse events, such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), which occur in 21–64% of patients treated with CAR-T cells [ 2 , 3 , 4 ]. While CRS is relatively well understood as a cytokine-driven phenomenon, the pathogenesis of ICANS remains unclear, posing significant challenges for effective risk stratification and management [ 5 , 6 ]. Various risk factors for ICANS have been reported, including host factors such as age and vascular status, cell therapy-related factors such as the type of CAR-T product, and inflammatory mediators such as IL-1 and IL-6 [ 6 ]. Moreover, recent studies have highlighted the utility of electroencephalogram (EEG), a non-invasive and widely used tool for assessing brain activity, in diagnosing ICANS and assessing the severity [ 7 , 8 ]. Specifically, EEG abnormalities before CAR-T cell therapy have been proposed as potential risk factors for ICANS [ 9 , 10 ]. In this study, we investigated the role of pre-CAR-T EEG findings in predicting ICANS. The Grand Total EEG (GTE) score, a comprehensive scoring system for EEG abnormalities, was used in its pre-CAR-T form to assess its utility as a predictive biomarker for ICANS in patients undergoing CAR-T cell therapy. The GTE score has been applied in various neurological conditions, including dementia with Lewy bodies and atypical parkinsonian syndromes, demonstrating its effectiveness in quantifying disease-specific EEG abnormalities [ 11 , 12 ]. By leveraging this scoring system in the context of CAR-T cell therapy, we aim to identify high-risk patients, which could contribute to developing targeted prevention and early intervention strategies for ICANS. Methods Patients We conducted a retrospective study to evaluate 55 patients who received CD19-targeted CAR-T cell therapy at Kyushu University Hospital between November 2022 and December 2023. The study was approved by the Institutional Review Board of Kyushu University Hospital, and informed consent was obtained from all participants. Lymphodepleting chemotherapy was administered according to the guidelines specific to each CAR-T cell product. After CAR-T cell infusion, adverse events such as CRS and ICANS were prospectively graded based on the American Society for Transplantation and Cellular Therapy consensus grading system [ 13 ]. Patients who developed ICANS underwent additional evaluations, including EEG, as soon as possible. Toxicity management primarily involved tocilizumab and corticosteroids according to the National Comprehensive Cancer Network guidelines [ 14 ]. EEG Evaluation and GTE scoring EEG testing was performed using the International 10–20 system with bipolar longitudinal montages (Neurofax EEG-1200 System and QA-110AK Digital Video Software, Nihon Kohden, Japan). Pre-CAR-T EEG evaluations lasted approximately 30 minutes in a specialized laboratory. To accommodate patient severity, post-CAR-T EEG evaluations were primarily performed at the bedside upon ICANS onset. EEG findings were scored using the GTE scoring system. The score evaluates six parameters: rhythmic background activity frequency, diffuse slow-wave activity, reactivity of rhythmic background activity, paroxysmal activity, focal abnormalities, and sharp-wave activity. Each parameter is scored on a six-point scale, with total scores ranging from 1 to 31 [ 11 , 15 ]. ( Supplementary Fig. 1 ) Pre-CAR-T GTE scoring captured baseline EEG abnormalities, while post-CAR-T GTE scoring was applied to evaluate ICANS severity. Statistical Analysis The Wilcoxon signed-rank test was used to compare continuous or ordinal variables between patient groups, and Pearson’s chi-squared test was employed to assess associations between nominal variables. For comparisons among three groups, one-way ANOVA was utilized. A P-value of < 0.05 was considered statistically significant. Correlations between continuous variables were evaluated using Pearson’s correlation coefficient. Receiver operating characteristic (ROC) curves were constructed to assess the predictive ability of the GTE score for ICANS development. For multivariate analysis, nominal-ordinal logistic regression analysis was performed. Statistical analyses were performed using JMP Pro 17. Results Clinical Characteristics The patient cohort consisted of 55 individuals with a median age of 63 years (range 18–77), including 22 females (Table 1) . The most common primary disease was diffuse large B-cell lymphoma (DLBCL), observed in 37 patients (67%), followed by follicular lymphoma in 6 patients (11%). CAR-T cell products administered included axicabtagene ciloleucel (axi-cel) in 18 patients, tisagenlecleucel (tisa-cel) in 22 patients, and lisocabtagene maraleucel (liso-cel) in 15 patients. Before CAR-T cell therapy, 21 patients were in complete response (CR), and 28 had received treatment targeting the central nervous system (CNS), including prophylactic interventions. Incidence and Risk Factors of ICANS Among the cohort, 52 patients (95%) developed CRS, and 16 patients (29%) developed ICANS (Table 1) . Both adverse events had a grade 3 or higher incidence at less than 10%, making severe cases relatively rare. We investigated the risk factors for ICANS, including CRS presence, disease status, history of treatment targeting CNS, and the type of CAR-T cell product used. Although the sample size for patients who did not develop CRS was limited to just three individuals, it was observed that the incidence of ICANS was 30.8% among those who developed CRS, while none of the patients who did not develop CRS experienced ICANS ( Fig. 1 A ) . Regarding disease status, the incidence of ICANS was 28.6% in patients who achieved CR and 29.4% in those who did not, showing no significant difference between these groups. For patients with a history of CNS-targeted treatment, the incidence of ICANS was 31.0% in those without such a history and 26.9% in those with it, indicating no significant difference in ICANS occurrence. For CAR-T cell products, the incidence of ICANS was 18.2% in the tisa-cel group, 20.0% in the liso-cel group, and 50.0% in the axi-cel group, with the higher incidence in the axi-cel group aligning with previous reports ( Fig. 1 A ) [ 5 ]. GTE Score Predicts ICANS Development We scored the EEG records using the GTE scoring system to investigate whether abnormalities in pre-CAR-T EEG are a risk factor for developing ICANS. The mean GTE score for the cohort was 3.12 ± 2.46, which was comparable to the distribution in previously reported cohorts ( Fig. 1 B ) [ 16 ]. Notably, ICANS incidence increased with higher pre-CAR-T GTE scores, exceeding 35% for scores of 3 or higher, whereas scores of 2 or lower were associated with an ICANS incidence of less than 20% ( Fig. 1 C ) . The mean GTE score was significantly higher in the ICANS group (4.94 ± 3.11) than in the non-ICANS group (2.44 ± 1.71), with this difference becoming even more pronounced when focusing on the ICANS grade ≥ 2 group ( Fig. 2 A, 2 B ) . Additionally, we examined other known ICANS risk factors, such as age, CRS, and the EASIX score [ 17 ]. While age and the EASIX score did not show significant differences between the ICANS and non-ICANS groups, the grade of CRS was significantly higher in the ICANS group ( Fig. 2 C ) . Based on multivariate analysis, the risk factors for ICANS included axi-cel and CRS grade ≥ 2 with odds ratios of 8.14 and 5.31, respectively. These results were both consistent and significant in previous reports [ 5 , 6 ]. Of note, the GTE score was also significantly identified with an odds ratio of 1.78 ( Fig. 2 D ) . Furthermore, the GTE score was the only independent risk factor for moderate to severe ICANS (grade ≥ 2), with axi-cel and CRS grades not reaching statistical significance ( Fig. 2 E ) . GTE Scores Potentially Reflect Baseline Brain Dysfunction and CNS-Targeted Therapy History We next evaluated the factors influencing GTE scores by analyzing patient and treatment backgrounds, including age, gender, disease status, and CNS involvement. While GTE scores tended to increase with age, this association was not statistically significant ( Fig. 3 A ) . Patients with a history of high-dose methotrexate treatment had significantly higher GTE scores, and those with a history of intrathecal injections showed a trend toward elevated scores. These findings suggest that specific CNS-targeted therapies may contribute to baseline brain dysfunction, whether for therapeutic or preventive purposes ( Fig. 3 B ) . Predictive Value of GTE Score Items for ICANS To better understand the factors contributing to pre-CAR-T GTE scores, we analyzed each item of the GTE score to evaluate its importance in predicting ICANS. Items 1, 2, 4, and 5 showed significantly higher scores in the ICANS group than in the non-ICANS group, while item 3 was not statistically significant, and item 6 was uniformly zero in all cases ( Supplementary Fig. 2A ). ROC curve analysis further demonstrated that the total GTE score provided the highest predictive ability for ICANS, achieving an AUC of 0.78, followed by item 5 (AUC: 0.70) and other items (AUC: 0.56–0.66) (Supplementary Fig. 2B) ; this trend was consistent with the ROC curve for predicting ICANS grade ≥ 2, where the total GTE score achieved an AUC of 0.86 (Supplementary Fig. 2C) . These findings indicate that while individual GTE score items reflect varying degrees of brain impairment, integrating all items into the total GTE score provides the most effective tool for predicting ICANS. GTE Scores Reflect ICANS Severity and Progression Finally, we investigated how GTE scores change from pre-CAR-T EEG to post-CAR-T EEG at the onset of ICANS. Among the 16 patients who developed ICANS, post-CAR-T GTE scores were available for 13 patients. The mean post-CAR-T GTE score was 6.5 ± 3.35 in the ICANS grade 1 group, 11.33 ± 2.98 in the grade 2 group, and 13.67 ± 2.62 in the grade 3 group, with a clear trend toward higher GTE scores with increasing ICANS severity ( Fig. 4 A ) . The mean pre-CAR-T GTE score of these 13 patients was 5.23 ± 3.21, which increased significantly to 10.38 ± 4.09 in post-CAR-T GTE scoring ( Fig. 4 B ) . Discussion This study underscores the utility of pre-CAR-T GTE scoring as a novel predictive biomarker for ICANS in patients undergoing CD19-targeted CAR-T cell therapy. Our findings demonstrated that elevated pre-CAR-T GTE scores are significantly associated with an increased risk of developing ICANS, mainly in moderate to severe cases. By objectively quantifying pre-CAR-T EEG abnormalities, the GTE score offers a sensitive and practical tool for identifying high-risk patients and facilitating early intervention. ICANS risk factors are multifaceted, including host factors such as age, EASIX score, CAR-T product type, and CRS development [ 6 ]. In line with previous reports, our study confirmed that the use of axi-cel and the occurrence of grade ≥ 2 CRS are significant contributors to ICANS development, while traditional host factors such as age and the EASIX score did not show significant associations with ICANS in our cohort. Furthermore, the GTE score emerged as a robust independent predictor of ICANS, providing a new avenue for early detection and targeted prevention strategies. These findings align with those of Pensato et al. and Hernani et al., who demonstrated that EEG abnormalities predict ICANS onset and severity. The GTE score represents an improvement upon the subjective assessments used in earlier studies, offering a more nuanced and quantitative evaluation of brain dysfunction [ 9 , 10 , 18 ]. The correlation between elevated GTE scores of pre-CAR-T cell therapy and ICANS development reflects baseline neurological injury as a predisposing factor for neurotoxicity. This observation parallels findings by Schoeberl et al., who reported that pre-infusion neurofilament light chain (NfL) levels, a marker of neuroaxonal injury, are associated with ICANS severity [ 19 , 20 ]. While NfL testing requires specialized facilities, EEG is widely accessible and easily integrated into routine CAR-T management. Interestingly, we identified a significant association between high-dose methotrexate (HD-MTX) therapy and elevated GTE scores, suggesting that specific CNS-targeted treatments may contribute to baseline brain dysfunction without symptoms. Although HD-MTX itself is not a direct risk factor for ICANS, this finding underscores the necessity of considering individual susceptibility to iatrogenic neurological injury in high-risk subgroups. We also evaluated changes in GTE scores from pre-CAR-T cell therapy to ICANS onset (post-CAR-T GTE scores). Our results showed a significant increase in GTE scores at the onset of ICANS, with higher GTE scores correlating with greater ICANS severity. These findings reinforce the utility of the GTE score not only as a predictive marker but also as a tool for assessing ICANS severity and guiding early therapeutic interventions. However, EEG recordings after ICANS onset are often affected by noise, slow-wave activity, and non-convulsive status epilepticus (NCSE), which are not fully accounted for in the GTE scoring system [ 7 , 8 ]. Additionally, the subjectivity inherent in EEG interpretation and the relatively small sample size in this study highlight the need for further standardization and validation. Modifications to the GTE scoring system, such as adjusting weightings for specific items, may enhance its accuracy and applicability in clinical practice. Our findings establish a foundation for incorporating the GTE score into a comprehensive ICANS prediction model that integrates clinical, neurological, and inflammatory parameters. Such a model could refine patient risk stratification, facilitate the targeted use of prophylactic therapies, and ultimately improve the safety and efficacy of CAR-T cell therapy. By integrating GTE scoring into routine CAR-T protocols, clinicians can achieve earlier identification of high-risk patients and optimize treatment strategies, thereby contributing to safer and more effective CAR-T cell therapy. Declarations Acknowledgments We acknowledge the technical staff at the Department of Clinical Chemistry and Laboratory Medicine, Kyushu University Hospital, for the EEG test. We also thank the ward and transfusion center staff for supporting CAR-T cell therapy. Authorship H.N., T.Y., D.I., H.I., K.S., T.S., F.J., K.M., T.S., Y.K., Y.M., and K.K. performed CAR-T cell therapy and were involved in the clinical care of the patients. A.S., E.W., T.H., and Y.K. conducted the EEG tests. T.M., M.W., and H.S. analyzed the EEGs and calculated the GTE scores. H.N., T.Y., N.I., K.A., and K.K. wrote the manuscript with help from all authors. Competing interests Koji Kato; Honoraria: AbbVie, Bristol-Myers Squibb, Chugai, Dainippon-Sumitomo, Janssen, Kyowa Kirin, MSD, AbbVie, Ono, Gilead Sciences, Novartis; Consulting or Advisory Role: AbbVie, AstraZeneca, Chugai, Daiichi Sankyo, Eisai, Janssen, Bristol-Myers Squibb, Novartis, Gilead Sciences; Research Funding: AbbVie, Astellas, MSD, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Janssen, Kyowa Kirin, Novartis, Ono, Gilead Sciences. Data availability statement The datasets generated during the current study are available from the corresponding author on reasonable request. References Park JH, Geyer MB, Brentjens RJ. CD19-targeted CAR T-cell therapeutics for hematologic malignancies: interpreting clinical outcomes to date. Blood. 2016;127(26):3312-20. Schuster SJ, Bishop MR, Tam CS, Waller EK, Borchmann P, McGuirk JP, et al. Tisagenlecleucel in Adult Relapsed or Refractory Diffuse Large B-Cell Lymphoma. N Engl J Med. 2019;380(1):45-56. 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Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations Yes Supplementary Files BMTICANSTable.xlsx Table 1 BMTICANSFigFinal5.jpg Supplementary Figure 1 Diagrammatic explanation of the GTE scoring system. The GTE scoring system consists of six items. Each item is scored on a six-point scale, with a total score ranging from 1 to 31, where higher scores indicate more severe neurological injury. BMTICANSFigFinal6.jpg Supplementary Figure 2 A. GTE score item comparisons between non-ICANS and ICANS groups. B. ROC curves for ICANS prediction using the total GTE score and individual items. C. ROC curves for predicting ICANS grade ≥2. Cite Share Download PDF Status: Published Journal Publication published 28 Apr, 2025 Read the published version in Bone Marrow Transplantation → Version 1 posted Editorial decision: revise 10 Mar, 2025 Review # 3 received at journal 06 Mar, 2025 Review # 1 received at journal 04 Mar, 2025 Reviewer # 3 agreed at journal 03 Mar, 2025 Review # 2 received at journal 28 Feb, 2025 Reviewer # 2 agreed at journal 28 Feb, 2025 Reviewer # 1 agreed at journal 25 Feb, 2025 Reviewers invited by journal 24 Feb, 2025 Submission checks completed at journal 24 Feb, 2025 Editor assigned by journal 22 Feb, 2025 First submitted to journal 22 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Takahiro","middleName":"","lastName":"Shima","suffix":""},{"id":420300866,"identity":"4efe10b3-ff7d-4a07-a4a4-ba8eb82de1f9","order_by":14,"name":"Yoshikane Kikushige","email":"","orcid":"https://orcid.org/0000-0002-7721-1696","institution":"Kyushu University Graduate School of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Yoshikane","middleName":"","lastName":"Kikushige","suffix":""},{"id":420300867,"identity":"bdfb7b84-f998-4c1a-b33b-b74165ae0774","order_by":15,"name":"Yasuo Mori","email":"","orcid":"","institution":"Kyushu University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yasuo","middleName":"","lastName":"Mori","suffix":""},{"id":420300868,"identity":"2786f2ce-119b-4f04-944d-f4585fb6a538","order_by":16,"name":"Taeko Hotta","email":"","orcid":"","institution":"Kyushu University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Taeko","middleName":"","lastName":"Hotta","suffix":""},{"id":420300869,"identity":"6e1cee43-ea60-43de-baa4-0b13cdae450b","order_by":17,"name":"Yuya Kunisaki","email":"","orcid":"https://orcid.org/0000-0003-0141-7038","institution":"Kyushu University Graduate School of Medical Science","correspondingAuthor":false,"prefix":"","firstName":"Yuya","middleName":"","lastName":"Kunisaki","suffix":""},{"id":420300870,"identity":"0c857551-b090-4f05-bb59-d7a68969ab0c","order_by":18,"name":"Hiroshi Shigeto","email":"","orcid":"","institution":"Graduate School of Medical Sciences, Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Shigeto","suffix":""},{"id":420300871,"identity":"5db3bdad-cac6-4843-badb-5a58f55851cf","order_by":19,"name":"Noriko Isobe","email":"","orcid":"","institution":"Graduate School of Medical Sciences, Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Noriko","middleName":"","lastName":"Isobe","suffix":""},{"id":420300872,"identity":"07bb4486-55f8-4a28-bcbf-ecec48720bce","order_by":20,"name":"Koichi Akashi","email":"","orcid":"","institution":"Kyushu University","correspondingAuthor":false,"prefix":"","firstName":"Koichi","middleName":"","lastName":"Akashi","suffix":""}],"badges":[],"createdAt":"2025-02-22 22:30:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6087514/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6087514/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41409-025-02616-z","type":"published","date":"2025-04-28T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":77616679,"identity":"2ea1af11-f5e4-4c61-9200-e4e3264186ae","added_by":"auto","created_at":"2025-03-03 15:05:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":272015,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e. Incidence rates of ICANS by CRS grade, disease status (complete remission vs. non-complete remission), CNS treatment history, and type of CAR-T cell product (tisa-cel, liso-cel, axi-cel).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e. Distribution of pre-CAR-T GTE scores among all patients, presented as mean ± standard deviation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC.\u003c/strong\u003eICANS incidence rates stratified by pre-CAR-T GTE score.\u003c/p\u003e","description":"","filename":"BMTICANSFigFinal1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/3a164838eddfb7ad58417eb4.jpg"},{"id":77616681,"identity":"7ef6e700-014f-47d4-99f1-d8f1d83ce64a","added_by":"auto","created_at":"2025-03-03 15:05:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":533095,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e.\u003cstrong\u003e \u003c/strong\u003ePre-CAR-T GTE score comparison between non-ICANS and ICANS groups. Significant differences are indicated as ***p \u0026lt; 0.001, **p \u0026lt; 0.01, with p-values for non-significant results included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e. Pre-CAR-T GTE score comparison between ICANS ≤1 and ICANS ≥2 groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e. Comparisons of Age, CRS grade, and EASIX scores between non-ICANS and ICANS groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e. Nominal-ordinal logistic regression analysis showing odds ratios for ICANS development. Significant predictors included axi-cel (odds ratio: 8.14; 95% CI: 1.4–46.4; *p = 0.018), CRS grade ≥2 (odds ratio: 5.31; 95% CI: 1.1–25.7; *p = 0.038), and pre-CAR-T GTE score per point (odds ratio: 1.78; 95% CI: 1.2–2.7; ***p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e. Logistic regression analysis for moderate to severe ICANS (grade ≥2). The pre-CAR-T GTE score per point (odds ratio: 1.78; 95% CI: 1.2–2.6; ***p \u0026lt; 0.001) was the only significant predictor.\u003c/p\u003e","description":"","filename":"BMTICANSFigFinal2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/26357be482928b8cb0576a24.jpg"},{"id":77616685,"identity":"aa117eea-8828-400f-a63b-d922b0d17a38","added_by":"auto","created_at":"2025-03-03 15:05:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":220697,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e. Correlation coefficient between Age and pre-CAR-T GTE score is 0.22 (r = 0.22, p = 0.11).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e.\u003cstrong\u003e \u003c/strong\u003ePre-CAR-T GTE score comparisons based on CNS-oriented therapy, focusing on high-dose methotrexate (HD-MTX) and intrathecal chemotherapy (IT).\u003c/p\u003e","description":"","filename":"BMTICANSFigFinal3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/adf38ff4bf3663b48c0d9114.jpg"},{"id":77616683,"identity":"dfcd3254-06d7-4aef-a758-4beff952e72a","added_by":"auto","created_at":"2025-03-03 15:05:46","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":187491,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e. Post-CAR-T GTE scores stratified by ICANS grade.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e. Changes in GTE scores from pre-CAR-T cell therapy to post-CAR-T (ICANS onset) for each patient.\u003c/p\u003e","description":"","filename":"BMTICANSFigFinal4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/a5d8734db1e29d749dba3972.jpg"},{"id":81610541,"identity":"4ffc9e52-1917-49a1-8af2-1390f46e15ba","added_by":"auto","created_at":"2025-04-29 07:06:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1897257,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/365baa37-5df4-49bd-9e80-ec29fc61e453.pdf"},{"id":77616676,"identity":"a5ca1439-67b4-49be-9dbd-83e717bbde49","added_by":"auto","created_at":"2025-03-03 15:05:46","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10952,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"BMTICANSTable.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/eca103d3bdf9d07213990c10.xlsx"},{"id":77616680,"identity":"fb1223fa-0b9e-4586-b32e-2a78be0f7352","added_by":"auto","created_at":"2025-03-03 15:05:46","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":507267,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiagrammatic explanation of the GTE scoring system. The GTE scoring system consists of six items. Each item is scored on a six-point scale, with a total score ranging from 1 to 31, where higher scores indicate more severe neurological injury.\u003c/p\u003e","description":"","filename":"BMTICANSFigFinal5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/a915a24f5a42b995d602a192.jpg"},{"id":77618315,"identity":"67de6a25-f0b3-41fd-a730-365573b17abb","added_by":"auto","created_at":"2025-03-03 15:13:47","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":487919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e. GTE score item comparisons between non-ICANS and ICANS groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e. ROC curves for ICANS prediction using the total GTE score and individual items.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e. ROC curves for predicting ICANS grade ≥2.\u003c/p\u003e","description":"","filename":"BMTICANSFigFinal6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6087514/v1/b0b9095ae3357e059faf696d.jpg"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e","formattedTitle":"Pre-CAR-T GTE Scoring of Electroencephalogram Abnormalities as a Predictive Biomarker for ICANS","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCD19-targeted chimeric antigen receptor (CAR)-T cell therapy has emerged as a promising treatment for refractory and relapsed B-cell lymphoma [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, it is frequently associated with specific adverse events, such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), which occur in 21\u0026ndash;64% of patients treated with CAR-T cells [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. While CRS is relatively well understood as a cytokine-driven phenomenon, the pathogenesis of ICANS remains unclear, posing significant challenges for effective risk stratification and management [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVarious risk factors for ICANS have been reported, including host factors such as age and vascular status, cell therapy-related factors such as the type of CAR-T product, and inflammatory mediators such as IL-1 and IL-6 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, recent studies have highlighted the utility of electroencephalogram (EEG), a non-invasive and widely used tool for assessing brain activity, in diagnosing ICANS and assessing the severity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Specifically, EEG abnormalities before CAR-T cell therapy have been proposed as potential risk factors for ICANS [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we investigated the role of pre-CAR-T EEG findings in predicting ICANS. The Grand Total EEG (GTE) score, a comprehensive scoring system for EEG abnormalities, was used in its pre-CAR-T form to assess its utility as a predictive biomarker for ICANS in patients undergoing CAR-T cell therapy. The GTE score has been applied in various neurological conditions, including dementia with Lewy bodies and atypical parkinsonian syndromes, demonstrating its effectiveness in quantifying disease-specific EEG abnormalities [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. By leveraging this scoring system in the context of CAR-T cell therapy, we aim to identify high-risk patients, which could contribute to developing targeted prevention and early intervention strategies for ICANS.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective study to evaluate 55 patients who received CD19-targeted CAR-T cell therapy at Kyushu University Hospital between November 2022 and December 2023. The study was approved by the Institutional Review Board of Kyushu University Hospital, and informed consent was obtained from all participants.\u003c/p\u003e \u003cp\u003e Lymphodepleting chemotherapy was administered according to the guidelines specific to each CAR-T cell product. After CAR-T cell infusion, adverse events such as CRS and ICANS were prospectively graded based on the American Society for Transplantation and Cellular Therapy consensus grading system [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Patients who developed ICANS underwent additional evaluations, including EEG, as soon as possible. Toxicity management primarily involved tocilizumab and corticosteroids according to the National Comprehensive Cancer Network guidelines [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEEG Evaluation and GTE scoring\u003c/h3\u003e\n\u003cp\u003eEEG testing was performed using the International 10\u0026ndash;20 system with bipolar longitudinal montages (Neurofax EEG-1200 System and QA-110AK Digital Video Software, Nihon Kohden, Japan). Pre-CAR-T EEG evaluations lasted approximately 30 minutes in a specialized laboratory. To accommodate patient severity, post-CAR-T EEG evaluations were primarily performed at the bedside upon ICANS onset.\u003c/p\u003e \u003cp\u003eEEG findings were scored using the GTE scoring system. The score evaluates six parameters: rhythmic background activity frequency, diffuse slow-wave activity, reactivity of rhythmic background activity, paroxysmal activity, focal abnormalities, and sharp-wave activity. Each parameter is scored on a six-point scale, with total scores ranging from 1 to 31 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e) Pre-CAR-T GTE scoring captured baseline EEG abnormalities, while post-CAR-T GTE scoring was applied to evaluate ICANS severity.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe Wilcoxon signed-rank test was used to compare continuous or ordinal variables between patient groups, and Pearson\u0026rsquo;s chi-squared test was employed to assess associations between nominal variables. For comparisons among three groups, one-way ANOVA was utilized. A P-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant. Correlations between continuous variables were evaluated using Pearson\u0026rsquo;s correlation coefficient. Receiver operating characteristic (ROC) curves were constructed to assess the predictive ability of the GTE score for ICANS development. For multivariate analysis, nominal-ordinal logistic regression analysis was performed. Statistical analyses were performed using JMP Pro 17.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eClinical Characteristics\u003c/h2\u003e \u003cp\u003eThe patient cohort consisted of 55 individuals with a median age of 63 years (range 18\u0026ndash;77), including 22 females \u003cb\u003e(Table\u0026nbsp;1)\u003c/b\u003e. The most common primary disease was diffuse large B-cell lymphoma (DLBCL), observed in 37 patients (67%), followed by follicular lymphoma in 6 patients (11%). CAR-T cell products administered included axicabtagene ciloleucel (axi-cel) in 18 patients, tisagenlecleucel (tisa-cel) in 22 patients, and lisocabtagene maraleucel (liso-cel) in 15 patients. Before CAR-T cell therapy, 21 patients were in complete response (CR), and 28 had received treatment targeting the central nervous system (CNS), including prophylactic interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIncidence and Risk Factors of ICANS\u003c/h2\u003e \u003cp\u003eAmong the cohort, 52 patients (95%) developed CRS, and 16 patients (29%) developed ICANS \u003cb\u003e(Table\u0026nbsp;1)\u003c/b\u003e. Both adverse events had a grade 3 or higher incidence at less than 10%, making severe cases relatively rare. We investigated the risk factors for ICANS, including CRS presence, disease status, history of treatment targeting CNS, and the type of CAR-T cell product used. Although the sample size for patients who did not develop CRS was limited to just three individuals, it was observed that the incidence of ICANS was 30.8% among those who developed CRS, while none of the patients who did not develop CRS experienced ICANS \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Regarding disease status, the incidence of ICANS was 28.6% in patients who achieved CR and 29.4% in those who did not, showing no significant difference between these groups. For patients with a history of CNS-targeted treatment, the incidence of ICANS was 31.0% in those without such a history and 26.9% in those with it, indicating no significant difference in ICANS occurrence. For CAR-T cell products, the incidence of ICANS was 18.2% in the tisa-cel group, 20.0% in the liso-cel group, and 50.0% in the axi-cel group, with the higher incidence in the axi-cel group aligning with previous reports \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGTE Score Predicts ICANS Development\u003c/h3\u003e\n\u003cp\u003eWe scored the EEG records using the GTE scoring system to investigate whether abnormalities in pre-CAR-T EEG are a risk factor for developing ICANS. The mean GTE score for the cohort was 3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46, which was comparable to the distribution in previously reported cohorts \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Notably, ICANS incidence increased with higher pre-CAR-T GTE scores, exceeding 35% for scores of 3 or higher, whereas scores of 2 or lower were associated with an ICANS incidence of less than 20% \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. The mean GTE score was significantly higher in the ICANS group (4.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.11) than in the non-ICANS group (2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71), with this difference becoming even more pronounced when focusing on the ICANS grade\u0026thinsp;\u0026ge;\u0026thinsp;2 group \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Additionally, we examined other known ICANS risk factors, such as age, CRS, and the EASIX score [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. While age and the EASIX score did not show significant differences between the ICANS and non-ICANS groups, the grade of CRS was significantly higher in the ICANS group \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Based on multivariate analysis, the risk factors for ICANS included axi-cel and CRS grade\u0026thinsp;\u0026ge;\u0026thinsp;2 with odds ratios of 8.14 and 5.31, respectively. These results were both consistent and significant in previous reports [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Of note, the GTE score was also significantly identified with an odds ratio of 1.78 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Furthermore, the GTE score was the only independent risk factor for moderate to severe ICANS (grade\u0026thinsp;\u0026ge;\u0026thinsp;2), with axi-cel and CRS grades not reaching statistical significance \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eGTE Scores Potentially Reflect Baseline Brain Dysfunction and CNS-Targeted Therapy History\u003c/h3\u003e\n\u003cp\u003eWe next evaluated the factors influencing GTE scores by analyzing patient and treatment backgrounds, including age, gender, disease status, and CNS involvement. While GTE scores tended to increase with age, this association was not statistically significant \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Patients with a history of high-dose methotrexate treatment had significantly higher GTE scores, and those with a history of intrathecal injections showed a trend toward elevated scores. These findings suggest that specific CNS-targeted therapies may contribute to baseline brain dysfunction, whether for therapeutic or preventive purposes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePredictive Value of GTE Score Items for ICANS\u003c/h2\u003e \u003cp\u003eTo better understand the factors contributing to pre-CAR-T GTE scores, we analyzed each item of the GTE score to evaluate its importance in predicting ICANS. Items 1, 2, 4, and 5 showed significantly higher scores in the ICANS group than in the non-ICANS group, while item 3 was not statistically significant, and item 6 was uniformly zero in all cases (\u003cb\u003eSupplementary Fig.\u0026nbsp;2A\u003c/b\u003e). ROC curve analysis further demonstrated that the total GTE score provided the highest predictive ability for ICANS, achieving an AUC of 0.78, followed by item 5 (AUC: 0.70) and other items (AUC: 0.56\u0026ndash;0.66) \u003cb\u003e(Supplementary Fig.\u0026nbsp;2B)\u003c/b\u003e; this trend was consistent with the ROC curve for predicting ICANS grade\u0026thinsp;\u0026ge;\u0026thinsp;2, where the total GTE score achieved an AUC of 0.86 \u003cb\u003e(Supplementary Fig.\u0026nbsp;2C)\u003c/b\u003e. These findings indicate that while individual GTE score items reflect varying degrees of brain impairment, integrating all items into the total GTE score provides the most effective tool for predicting ICANS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGTE Scores Reflect ICANS Severity and Progression\u003c/h2\u003e \u003cp\u003eFinally, we investigated how GTE scores change from pre-CAR-T EEG to post-CAR-T EEG at the onset of ICANS. Among the 16 patients who developed ICANS, post-CAR-T GTE scores were available for 13 patients. The mean post-CAR-T GTE score was 6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35 in the ICANS grade 1 group, 11.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.98 in the grade 2 group, and 13.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.62 in the grade 3 group, with a clear trend toward higher GTE scores with increasing ICANS severity \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. The mean pre-CAR-T GTE score of these 13 patients was 5.23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.21, which increased significantly to 10.38\u0026thinsp;\u0026plusmn;\u0026thinsp;4.09 in post-CAR-T GTE scoring \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study underscores the utility of pre-CAR-T GTE scoring as a novel predictive biomarker for ICANS in patients undergoing CD19-targeted CAR-T cell therapy. Our findings demonstrated that elevated pre-CAR-T GTE scores are significantly associated with an increased risk of developing ICANS, mainly in moderate to severe cases. By objectively quantifying pre-CAR-T EEG abnormalities, the GTE score offers a sensitive and practical tool for identifying high-risk patients and facilitating early intervention.\u003c/p\u003e \u003cp\u003eICANS risk factors are multifaceted, including host factors such as age, EASIX score, CAR-T product type, and CRS development [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In line with previous reports, our study confirmed that the use of axi-cel and the occurrence of grade\u0026thinsp;\u0026ge;\u0026thinsp;2 CRS are significant contributors to ICANS development, while traditional host factors such as age and the EASIX score did not show significant associations with ICANS in our cohort. Furthermore, the GTE score emerged as a robust independent predictor of ICANS, providing a new avenue for early detection and targeted prevention strategies. These findings align with those of Pensato et al. and Hernani et al., who demonstrated that EEG abnormalities predict ICANS onset and severity. The GTE score represents an improvement upon the subjective assessments used in earlier studies, offering a more nuanced and quantitative evaluation of brain dysfunction [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe correlation between elevated GTE scores of pre-CAR-T cell therapy and ICANS development reflects baseline neurological injury as a predisposing factor for neurotoxicity. This observation parallels findings by Schoeberl et al., who reported that pre-infusion neurofilament light chain (NfL) levels, a marker of neuroaxonal injury, are associated with ICANS severity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. While NfL testing requires specialized facilities, EEG is widely accessible and easily integrated into routine CAR-T management. Interestingly, we identified a significant association between high-dose methotrexate (HD-MTX) therapy and elevated GTE scores, suggesting that specific CNS-targeted treatments may contribute to baseline brain dysfunction without symptoms. Although HD-MTX itself is not a direct risk factor for ICANS, this finding underscores the necessity of considering individual susceptibility to iatrogenic neurological injury in high-risk subgroups.\u003c/p\u003e \u003cp\u003eWe also evaluated changes in GTE scores from pre-CAR-T cell therapy to ICANS onset (post-CAR-T GTE scores). Our results showed a significant increase in GTE scores at the onset of ICANS, with higher GTE scores correlating with greater ICANS severity. These findings reinforce the utility of the GTE score not only as a predictive marker but also as a tool for assessing ICANS severity and guiding early therapeutic interventions. However, EEG recordings after ICANS onset are often affected by noise, slow-wave activity, and non-convulsive status epilepticus (NCSE), which are not fully accounted for in the GTE scoring system [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, the subjectivity inherent in EEG interpretation and the relatively small sample size in this study highlight the need for further standardization and validation. Modifications to the GTE scoring system, such as adjusting weightings for specific items, may enhance its accuracy and applicability in clinical practice.\u003c/p\u003e \u003cp\u003eOur findings establish a foundation for incorporating the GTE score into a comprehensive ICANS prediction model that integrates clinical, neurological, and inflammatory parameters. Such a model could refine patient risk stratification, facilitate the targeted use of prophylactic therapies, and ultimately improve the safety and efficacy of CAR-T cell therapy. By integrating GTE scoring into routine CAR-T protocols, clinicians can achieve earlier identification of high-risk patients and optimize treatment strategies, thereby contributing to safer and more effective CAR-T cell therapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the technical staff at the Department of Clinical Chemistry and Laboratory Medicine, Kyushu University Hospital, for the EEG test. We also thank the ward and transfusion center staff\u0026nbsp;for supporting CAR-T cell therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.N., T.Y., D.I., H.I., K.S., T.S., F.J., K.M., T.S., Y.K., Y.M., and K.K. performed CAR-T cell therapy and were involved in the clinical care of the patients. A.S., E.W., T.H., and Y.K. conducted the EEG tests. T.M., M.W., and H.S. analyzed the EEGs and calculated the GTE scores. H.N., T.Y., N.I., K.A., and K.K. wrote the manuscript with help from all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKoji Kato; Honoraria: AbbVie, Bristol-Myers Squibb, Chugai, Dainippon-Sumitomo, Janssen, Kyowa Kirin, MSD, AbbVie, Ono, Gilead\u0026nbsp;Sciences, Novartis; Consulting or Advisory Role: AbbVie, AstraZeneca, Chugai, Daiichi Sankyo, Eisai, Janssen, Bristol-Myers Squibb, Novartis, Gilead\u0026nbsp;Sciences; Research Funding: AbbVie, Astellas, MSD, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Janssen, Kyowa Kirin, Novartis, Ono, Gilead\u0026nbsp;Sciences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePark JH, Geyer MB, Brentjens RJ. CD19-targeted CAR T-cell therapeutics for hematologic malignancies: interpreting clinical outcomes to date. Blood. 2016;127(26):3312-20.\u003c/li\u003e\n\u003cli\u003eSchuster SJ, Bishop MR, Tam CS, Waller EK, Borchmann P, McGuirk JP, et al. Tisagenlecleucel in Adult Relapsed or Refractory Diffuse Large B-Cell Lymphoma. N Engl J Med. 2019;380(1):45-56.\u003c/li\u003e\n\u003cli\u003eAbramson JS, Palomba ML, Gordon LI, Lunning MA, Wang M, Arnason J, et al. Lisocabtagene maraleucel for patients with relapsed or refractory large B-cell lymphomas (TRANSCEND NHL 001): a multicentre seamless design study. Lancet. 2020;396(10254):839-52.\u003c/li\u003e\n\u003cli\u003eNeelapu SS, Locke FL, Bartlett NL, Lekakis LJ, Miklos DB, Jacobson CA, et al. Axicabtagene Ciloleucel CAR T-Cell Therapy in Refractory Large B-Cell Lymphoma. N Engl J Med. 2017;377(26):2531-44.\u003c/li\u003e\n\u003cli\u003eMorris EC, Neelapu SS, Giavridis T, Sadelain M. Cytokine release syndrome and associated neurotoxicity in cancer immunotherapy. Nat Rev Immunol. 2022;22(2):85-96.\u003c/li\u003e\n\u003cli\u003eButt OH, Zhou AY, Ances BM, DiPersio JF, Ghobadi A. A systematic framework for predictive biomarkers in immune effector cell-associated neurotoxicity syndrome. Front Neurol. 2023;14:1110647. https://doi.org/10.3389/fneur.2023.1110647.\u003c/li\u003e\n\u003cli\u003eMauget M, Lemercier S, Quelven Q, Maamar A, Lhomme F, De Guibert S, et al. Impact of diagnostic investigations in the management of CAR T-cell-associated neurotoxicity. Blood Adv. 2024;8(10):2491-8.\u003c/li\u003e\n\u003cli\u003eJones DK, Eckhardt CA, Sun H, Tesh RA, Malik P, Quadri S, et al. EEG-based grading of immune effector cell-associated neurotoxicity syndrome. Sci Rep. 2022;12(1):20011. https://doi.org/10.1038/s41598-022-24010-1.\u003c/li\u003e\n\u003cli\u003ePensato U, Amore G, Muccioli L, Sammali S, Rondelli F, Rinaldi R, et al. CAR t-cell therapy in BOlogNa-NEUrotoxicity TReatment and Assessment in Lymphoma (CARBON-NEUTRAL): proposed protocol and results from an Italian study. J Neurol. 2023;270(5):2659-73.\u003c/li\u003e\n\u003cli\u003eHernani R, Aiko M, Victorio R, Benzaqu\u0026eacute;n A, P\u0026eacute;rez A, Pi\u0026ntilde;ana JL, et al. EEG before chimeric antigen receptor T-cell therapy and early after onset of immune effector cell-associated neurotoxicity syndrome. Clin Neurophysiol. 2024;163:132-42.\u003c/li\u003e\n\u003cli\u003eRoks G, Korf ES, van der Flier WM, Scheltens P, Stam CJ. The use of EEG in the diagnosis of dementia with Lewy bodies. J Neurol Neurosurg Psychiatry. 2008;79(4):377-80.\u003c/li\u003e\n\u003cli\u003eBarcelon EA, Mukaino T, Yokoyama J, Uehara T, Ogata K, Kira JI, et al. Grand Total EEG Score Can Differentiate Parkinson\u0026apos;s Disease From Parkinson-Related Disorders. Front Neurol. 2019;10:398. https://doi.org/10.3389/fneur.2019.00398.\u003c/li\u003e\n\u003cli\u003eLee DW, Santomasso BD, Locke FL, Ghobadi A, Turtle CJ, Brudno JN, et al. ASTCT Consensus Grading for Cytokine Release Syndrome and Neurologic Toxicity Associated with Immune Effector Cells. Biol Blood Marrow Transplant. 2019;25(4):625-38.\u003c/li\u003e\n\u003cli\u003eThompson JA, Schneider BJ, Brahmer J, Zaid MA, Achufusi A, Armand P, et al. NCCN Guidelines\u0026reg; Insights: Management of Immunotherapy-Related Toxicities, Version 2.2024. J Natl Compr Canc Netw. 2024;22(9):582-92.\u003c/li\u003e\n\u003cli\u003eLee H, Brekelmans GJ, Roks G. The EEG as a diagnostic tool in distinguishing between dementia with Lewy bodies and Alzheimer\u0026apos;s disease. Clin Neurophysiol. 2015;126(9):1735-9.\u003c/li\u003e\n\u003cli\u003eClaus JJ, Strijers RL, Jonkman EJ, Ongerboer de Visser BW, Jonker C, et al. The diagnostic value of electroencephalography in mild senile Alzheimer\u0026apos;s disease. Clin Neurophysiol. 1999;110(5):825-832.\u003c/li\u003e\n\u003cli\u003eGreenbaum U, Strati P, Saliba RM, Torres J, Rondon G, Nieto Y, et al. CRP and ferritin in addition to the EASIX score predict CAR-T-related toxicity. Blood Adv. 2021;5(14):2799-806.\u003c/li\u003e\n\u003cli\u003eM\u0026ouml;hn N, Bonda V, Grote-Levi L, Panagiota V, Fr\u0026ouml;hlich T, Schultze-Florey C, et al. Neurological management and work-up of neurotoxicity associated with CAR T cell therapy. Neurol Res Pract. 2022;4(1):1. https://doi.org/10.1186/s42466-021-00166-5.\u003c/li\u003e\n\u003cli\u003eSchoeberl F, Tiedt S, Schmitt A, Blumenberg V, Karschnia P, Burbano VG, et al. Neurofilament light chain serum levels correlate with the severity of neurotoxicity after CAR T-cell treatment. Blood Adv. 2022;6(10):3022-6.\u003c/li\u003e\n\u003cli\u003eGust J, Rawlings-Rhea SD, Wilson AL, Tulberg NM, Sherman AL, Seidel KD, et al. GFAP and NfL increase during neurotoxicity from high baseline levels in pediatric CD19-CAR T-cell patients. Blood Adv. 2023;7(6):1001-10.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6087514/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6087514/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCD19-targeted chimeric antigen receptor (CAR)-T cell therapy is an effective treatment for relapsed or refractory B-cell lymphoma but is associated with adverse events such as cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). The pathogenesis of ICANS remains unclear, and predictive biomarkers are needed for risk stratification. This study evaluates the Grand Total EEG (GTE) score, a comprehensive scoring system for electroencephalogram (EEG) abnormalities, as a predictive biomarker for ICANS. We retrospectively analyzed 55 patients who underwent CAR-T cell therapy. ICANS occurred in 29% of patients, with CRS (grade ≥ 2) and axicabtagene ciloleucel identified as significant risk factors. Higher GTE scores correlated with ICANS severity after ICANS onset. Furthermore, the GTE score before CAR-T therapy was already significantly higher in the ICANS group (mean: 4.94 ± 3.11) than in the non-ICANS group (mean: 2.44 ± 1.71) with an odds ratio of 1.78. Patients with a history of high-dose methotrexate treatment showed elevated GTE scores, suggesting an association between CNS-targeted therapies and baseline brain dysfunction without symptoms. The findings of this study illustrate the efficacy of the GTE score as a novel biomarker for ICANS prediction. The score enables early risk stratification and directs interventions in CAR-T therapy.\u003c/p\u003e","manuscriptTitle":"Pre-CAR-T GTE Scoring of Electroencephalogram Abnormalities as a Predictive Biomarker for ICANS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-03 15:05:42","doi":"10.21203/rs.3.rs-6087514/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-03-10T16:35:01+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-03-07T01:12:41+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-03-04T15:06:01+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-03-03T16:38:11+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-02-28T11:30:04+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-02-28T08:41:02+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-02-25T08:10:00+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-02-24T17:24:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-24T12:25:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-22T22:27:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bone Marrow Transplantation","date":"2025-02-22T22:27:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b941ee01-d711-4f98-a22a-fa1ab75c9b51","owner":[],"postedDate":"March 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":44804752,"name":"Biological sciences/Immunology/Immunotherapy"},{"id":44804753,"name":"Health sciences/Risk factors"},{"id":44804754,"name":"Biological sciences/Cancer/Haematological cancer/Lymphoma/Non-hodgkin lymphoma/B-cell lymphoma"}],"tags":[],"updatedAt":"2025-04-29T07:06:27+00:00","versionOfRecord":{"articleIdentity":"rs-6087514","link":"https://doi.org/10.1038/s41409-025-02616-z","journal":{"identity":"bone-marrow-transplantation","isVorOnly":false,"title":"Bone Marrow Transplantation"},"publishedOn":"2025-04-28 04:00:00","publishedOnDateReadable":"April 28th, 2025"},"versionCreatedAt":"2025-03-03 15:05:42","video":"","vorDoi":"10.1038/s41409-025-02616-z","vorDoiUrl":"https://doi.org/10.1038/s41409-025-02616-z","workflowStages":[]},"version":"v1","identity":"rs-6087514","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6087514","identity":"rs-6087514","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}