Development and validation of predictive models of early immune effector cell–associated hematotoxicity

Immune effector cell-associated hematotoxicity (ICAHT) is associated with morbidity and mortality after chimeric antigen receptor (CAR) T-cell therapy. To date, the factors associated with ICAHT are poorly characterized, and there is no validated predictive model of ICAHT as defined by current consensus criteria. Therefore, we performed comprehensive univariate analyses to identify factors associated with severe (grade 3-4) early ICAHT (eICAHT) in 691 patients who received commercial or investigational CAR T-cell therapy for hematologic malignancies. In univariate logistic regression, preinfusion factors associated with severe eICAHT included disease type (acute lymphoblastic leukemia), prelymphodepletion (pre-LD) blood counts including absolute neutrophil count (ANC), lactate dehydrogenase (LDH), and inflammatory (C-reactive protein [CRP], ferritin, and interleukin-6 [IL-6]) and coagulopathy biomarkers (D-dimer). Postinfusion laboratory markers associated with severe eICAHT included early and peak levels of inflammatory biomarkers (CRP, ferritin, and IL-6), coagulopathy biomarkers (D-dimer), peak cytokine release syndrome grade, and peak neurotoxicity grade. We trained (n = 483) and validated (n = 208) 2 eICAHT prediction models (eIPMs): eIPMPre including preinfusion factors only (disease type and pre-LD ANC, platelet count, LDH, and ferritin) and eIPMPost containing both preinfusion (disease type and pre-LD ANC, platelet count, and LDH) and early postinfusion (day +3 ferritin) factors. Both models generated calibrated predictions and high discrimination (area under the receiver operating characteristic curve in test set, 0.87 for eIPMPre and 0.88 for eIPMPost), with higher net benefit in decision curve analysis for eIPMPost. Individualized predictions of severe eICAHT can be generated from both eIPMs using our online tool (available at https://eipm.fredhutch.org).

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Publication Details

Journal
Blood Advances
Published
2024-12-03
DOI
https://doi.org/10.1182/bloodadvances.2024014455
Citations
5
Primary Topic
CAR-T cell therapy research
Type
article
Field-Weighted Citation Impact
1.41

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article

Development and validation of predictive models of early immune effector cell–associated hematotoxicity

Laurel A. Thur, Ajay K. Gopal, Damian J. Green, Yein Jeon et al.
5 citations
Blood Advances
CAR-T cell therapy research
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article

Development and validation of predictive models of early immune effector cell–associated hematotoxicity

Laurel A. Thur, Ajay K. Gopal, Damian J. Green, Yein Jeon, Ryan Basom, Jordan Gauthier, Mohamed L. Sorror, Erik L. Kimble, David G. Maloney, Delaney R. Kirchmeier, Rahul Kumar Banerjee, Natalie Wuliji, Andrew J. Cowan, Aiko Torkelson, Qian Wu, Andrew J. Portuguese, Aude G. Chapuis, Brian G. Till, Alexandre V. Hirayama, Noam E. Kopmar, Valentín Ortiz‐Maldonado, Mazyar Shadman, Christina Poh, Filippo Milano, Lorenzo Iovino, Folashade Otegbeye, Aya Albittar, Ryan D. Cassaday, Emily C. Liang, Cameron J. Turtle, Abigail Chutnik, Jennifer J. Huang, Barbara S. Pender
article en
5 citations

Abstract

Immune effector cell-associated hematotoxicity (ICAHT) is associated with morbidity and mortality after chimeric antigen receptor (CAR) T-cell therapy. To date, the factors associated with ICAHT are poorly characterized, and there is no validated predictive model of ICAHT as defined by current consensus criteria. Therefore, we performed comprehensive univariate analyses to identify factors associated with severe (grade 3-4) early ICAHT (eICAHT) in 691 patients who received commercial or investigational CAR T-cell therapy for hematologic malignancies. In univariate logistic regression, preinfusion factors associated with severe eICAHT included disease type (acute lymphoblastic leukemia), prelymphodepletion (pre-LD) blood counts including absolute neutrophil count (ANC), lactate dehydrogenase (LDH), and inflammatory (C-reactive protein [CRP], ferritin, and interleukin-6 [IL-6]) and coagulopathy biomarkers (D-dimer). Postinfusion laboratory markers associated with severe eICAHT included early and peak levels of inflammatory biomarkers (CRP, ferritin, and IL-6), coagulopathy biomarkers (D-dimer), peak cytokine release syndrome grade, and peak neurotoxicity grade. We trained (n = 483) and validated (n = 208) 2 eICAHT prediction models (eIPMs): eIPMPre including preinfusion factors only (disease type and pre-LD ANC, platelet count, LDH, and ferritin) and eIPMPost containing both preinfusion (disease type and pre-LD ANC, platelet count, and LDH) and early postinfusion (day +3 ferritin) factors. Both models generated calibrated predictions and high discrimination (area under the receiver operating characteristic curve in test set, 0.87 for eIPMPre and 0.88 for eIPMPost), with higher net benefit in decision curve analysis for eIPMPost. Individualized predictions of severe eICAHT can be generated from both eIPMs using our online tool (available at https://eipm.fredhutch.org).

Blood AdvancesVol. 9(3)
The University of Sydney (AU), University of Miami (US), University of Washington (US), Fred Hutch Cancer Center (US), Hospital Clínic de Barcelona (ES), Sylvester Comprehensive Cancer Center (US)
Amgen, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, AstraZeneca, GlaxoSmithKline, Sanofi, Gilead Sciences, Fred Hutchinson Cancer Research Center, Teva Pharmaceutical Industries, Celgene, CSL Behring, Regeneron Pharmaceuticals, Vanda Pharmaceuticals, TG Therapeutics, MEI Pharma, Angiocrine Bioscience, Agios Pharmaceuticals, Adaptive Biotechnologies, Swim Across America, BeiGene, Incyte, Moderna, Seagen, Springworks Therapeutics, Servier, Swedish Orphan Biovitrum, MorphoSys, Grifols, National Institutes of Health, Genentech, Kite Pharma, Pharmacyclics, Juno Therapeutics, Legend Biotech, National Heart, Lung, and Blood Institute, National Cancer Institute, Janssen Biotech, Eurostars
Peace, Justice and strong institutions
Openalex Percentile: Top 15%
CAR-T cell therapy research
1.41
DOIOpen Access PDFOpenAlex
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