Optimization and validation of the international metabolic prognostic index for CD19 CAR-T in large B-cell lymphoma

While CD19-directed CAR T-cell therapy represents a transformative immunotherapy for relapsed/refractory large B-cell lymphoma (r/r LBCL), more than 50% of patients ultimately progress or relapse. Recently, the International Metabolic Prognostic Index (IMPI) - incorporating age, stage, and metabolic tumor volume (MTV) - was shown to improve prognostication for LBCL frontline treatment. Here, we examine its utility to predict toxicity and survival in CAR-T recipients. This multicenter observational study spanning six international sites included 504 patients with available <sup>18</sup>FDG-PET/CT imaging at last response assessment prior to lymphodepletion. Optimal CAR-adapted MTV thresholds were identified in a development cohort (n = 256) and incorporated into a CAR-T-specific IMPI ("CAR-IMPI"). The prognostic performance of CAR-IMPI was validated in an independent cohort (n = 248). CAR-IMPI risk categories, defined by the median (1.35) and terciles (1.07, 1.58), demonstrated significant discrimination for progression-free survival (PFS; p < 0.0001) and overall survival (OS; p < 0.0001) in both cohorts. Multivariate Cox regression confirmed CAR-IMPI as an independent predictor of survival, accounting for pre-lymphodepletion LDH and CRP, performance status, treatment center, and CAR-T product. Patients in the CAR-IMPI high-risk category experienced increased severity of CRS and ICANS, and higher rates of intensive care unit (ICU) admissions. In an exploratory analysis, combining CAR-IMPI with established indices of high-risk systemic inflammation (CAR-HEMATOTOX, InflaMix) further enhanced survival stratification. The CAR-IMPI may provide a potent and validated PET-based tool for risk stratification of clinical outcomes in patients with r/r LBCL receiving CD19 CAR-T therapy. Our data highlight the utility of combining clinical and radiological modalities, with implications for patient selection and the anticipated level-of-care for toxicity management.

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Publication Details

Journal
Blood Cancer Journal
Published
2025-08-26
DOI
https://doi.org/10.1038/s41408-025-01338-1
Citations
4
Primary Topic
CAR-T cell therapy research
Type
article
Field-Weighted Citation Impact
4.18

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article

Optimization and validation of the international metabolic prognostic index for CD19 CAR-T in large B-cell lymphoma

Marion Subklewe, Michael David Jain, Heiko M. Schöder, Frederick Lundry Locke et al.
4 citations
Blood Cancer Journal
CAR-T cell therapy research
4.18
article

Optimization and validation of the international metabolic prognostic index for CD19 CAR-T in large B-cell lymphoma

Marion Subklewe, Michael David Jain, Heiko M. Schöder, Frederick Lundry Locke, Gunjan L. Shah, Magdalena Corona, Roni Shouval, Fabian Müller, Pere Barba, Akshay Bedmutha, Gloria Iacoboni, Veit Bücklein, Michael Winkelmann, Michael Scordo, Doris Leithner, Maria Lia Palomba, Kai Rejeski, Gabriel T. Sheikh, Khushali Jhaveri, Alexander P. Boardman, Sandeep S. Raj, Leo Hansmann, Wolfgang G. Kunz, Alejandro Luna, Miguel‐Angel Perales, Gilles Salles, Tobias Tix, Jae H. Park, Erin Dean, Turab Mohammad
article en
4 citations

Abstract

While CD19-directed CAR T-cell therapy represents a transformative immunotherapy for relapsed/refractory large B-cell lymphoma (r/r LBCL), more than 50% of patients ultimately progress or relapse. Recently, the International Metabolic Prognostic Index (IMPI) - incorporating age, stage, and metabolic tumor volume (MTV) - was shown to improve prognostication for LBCL frontline treatment. Here, we examine its utility to predict toxicity and survival in CAR-T recipients. This multicenter observational study spanning six international sites included 504 patients with available <sup>18</sup>FDG-PET/CT imaging at last response assessment prior to lymphodepletion. Optimal CAR-adapted MTV thresholds were identified in a development cohort (n = 256) and incorporated into a CAR-T-specific IMPI ("CAR-IMPI"). The prognostic performance of CAR-IMPI was validated in an independent cohort (n = 248). CAR-IMPI risk categories, defined by the median (1.35) and terciles (1.07, 1.58), demonstrated significant discrimination for progression-free survival (PFS; p < 0.0001) and overall survival (OS; p < 0.0001) in both cohorts. Multivariate Cox regression confirmed CAR-IMPI as an independent predictor of survival, accounting for pre-lymphodepletion LDH and CRP, performance status, treatment center, and CAR-T product. Patients in the CAR-IMPI high-risk category experienced increased severity of CRS and ICANS, and higher rates of intensive care unit (ICU) admissions. In an exploratory analysis, combining CAR-IMPI with established indices of high-risk systemic inflammation (CAR-HEMATOTOX, InflaMix) further enhanced survival stratification. The CAR-IMPI may provide a potent and validated PET-based tool for risk stratification of clinical outcomes in patients with r/r LBCL receiving CD19 CAR-T therapy. Our data highlight the utility of combining clinical and radiological modalities, with implications for patient selection and the anticipated level-of-care for toxicity management.

Blood Cancer JournalVol. 15(1)
Universitat Autònoma de Barcelona (ES), Siemens (Germany) (DE), Memorial Sloan Kettering Cancer Center (US), German Cancer Research Center (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Cornell University (US), Heidelberg University (DE), University of South Florida (US), University Hospital Heidelberg (DE), LMU Klinikum (DE), Moffitt Cancer Center (US), University Hospital Regensburg (DE), University of Florida (US), Universitätsklinikum Erlangen (DE), German Center for Infection Research (DE), Indiana University Bloomington (US), Vall d'Hebron Hospital Universitari (ES), Comprehensive Cancer Center Erlangen (DE), Vall d'Hebron Institute of Oncology (ES), Ludwig-Maximilians-Universität München (DE)
Memorial Sloan-Kettering Cancer Center, National Institutes of Health, National Cancer Institute
Openalex Percentile: Top 5%
CAR-T cell therapy research
4.18
DOIOpen Access PDFOpenAlex
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