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A systematic review and meta-analysis of nonrelapse mortality after CAR T cell therapy

Abstract

Although chimeric antigen receptor (CAR) T cell therapy represents a transformative immunotherapy, it is also associated with distinct toxicities that contribute to morbidity and mortality. In this systematic review and meta-analysis, we searched MEDLINE, Embase and CINAHL (Cochrane) for reports of nonrelapse mortality (NRM) after CAR T cell therapy in lymphoma and multiple myeloma up to March 2024. After extraction of causes and numbers of death, we analyzed NRM point estimates using random-effect models. We identified 7,604 patients across 18 clinical trials and 28 real-world studies. NRM point estimates varied across disease entities and were highest in patients with mantle-cell lymphoma (10.6%), followed by multiple myeloma (8.0%), large B cell lymphoma (6.1%) and indolent lymphoma (5.7%). Entity-specific meta-regression models for large B cell lymphoma and multiple myeloma revealed that axicabtagene ciloleucel and ciltacabtagene autoleucel were independently associated with increased NRM point estimates, respectively. Of 574 reported nonrelapse deaths, over half were attributed to infections (50.9%), followed by other malignancies (7.8%) and cardiovascular/respiratory events (7.3%). Conversely, the CAR T cell-specific side effects, immune effector cell-associated neurotoxicity syndrome/neurotoxicity, cytokine release syndrome and hemophagocytic lymphohistiocytosis, represented only a minority of nonrelapse deaths (cumulatively 11.5%). Our findings underline the critical importance of infectious complications after CAR T cell therapy and support the comprehensive reporting of NRM, including specific causes and long-term outcomes.

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Fig. 1: Study retrieval and identification for meta-analysis.
Fig. 2: Forest plot of NRM point estimates across all study cohorts and stratified by treatment setting.
Fig. 3: CAR T cell products impact NRM point estimates in a disease-specific manner.
Fig. 4: Distribution of causes of nonrelapse deaths across treatment settings and disease entities.

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Data availability

All data needed to evaluate the conclusions in the paper are present in the paper and/or Supplementary Information. Data from primary studies are publicly available within the databases and search algorithms described in Supplementary Information (MEDLINE, Embase and CINAHL (Cochrane)). Original output data can be accessed under https://github.com/DMCDS/CART_NRM_Metaanalysis. In case of further questions, please contact the corresponding author.

Code availability

All codes were adapted using R software, v.4.3.1 (meta package 7.0-0, metafor package 4.4-0). Data sheets were created using Microsoft Excel. The underlying R code for the present study can be accessed in a GitHub repository: https://github.com/DMCDS/CART_NRM_Metaanalysis. For further questions, please contact the corresponding author.

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Acknowledgements

First and foremost, we acknowledge the many patients whose data were incorporated into the present study as well as the research personnel who advanced this rapidly moving field. In addition, we thank all first and corresponding authors who took the time to answer our queries about their studies for their efforts. We particularly thank M. Pasquini (CIBMTR), S. Ahmed (MD Anderson Cancer Center), D. Hansen (Moffitt Cancer Center), S. Giralt (Memorial Sloan Kettering Cancer Center) and P. Berning (Yale Cancer Center). T.T., D.M.C.D.S. and K.R. received a fellowship from the School of Oncology of the German Cancer Consortium. D.M.C.D.S. received the Walter Benjamin Fellowship from Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). K.R. acknowledges funding from the Else Kröner Forschungskolleg within the Munich Clinician Scientist Program. This work was supported by a grant from the Bruno and Helene Jöster Foundation (to S.T., K.R. and M.S.). We further acknowledge support from the Bavarian Cancer Research Center (‘CAR-T Control’ translational group, to M.S. and K.R.). This work was in part supported by DFG: Collaborative Research grants (no. SFB-TRR 388/1 2021–452881907 to M.S. and S.T.) and individual research grants (no. 451580403 to M.S. and no. 391587558 to S.T. and M.V.B.-B.). E.R.S.C. received research funding from Arnold Ventures. R.S., K.R. and M.-A.P. were supported by a Memorial Sloan Kettering Cancer Center Core grant (no. P30 CA008748) from the National Institutes of Health (NIH)/National Cancer Institute. R.S. was supported by an NIH/National Cancer Institute K-award (no. K08CA282987). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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Authors and Affiliations

Authors

Contributions

K.R. conceived the project. D.M.C.D.S., T.T., R.S., E.R.S.C., S.T., M.V.B.-B., I.M.G., M.-A.P., M.S. and K.R. carried out the investigations. D.M.C.D.S. and T.T. did the formal analysis and visualization. D.M.C.D.S., T.T., A.G.-G., J.-B.A. and K.R. provided the methodology. D.M.C.D.S., T.T. and K.R. wrote the original draft of the paper. D.M.C.D.S., T.T., R.S., A.G.-G., J.-B.A., E.R.S.C., S.T., M.V.B.-B., I.M.G., M.-A.P., M.S. and K.R. reviewed and edited the paper. All authors read and approved the final paper.

Corresponding author

Correspondence to Kai Rejeski.

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Competing interests

A.G.-G. received honoraria from/had a consultancy with Pfizer, Bayer, Novartis, Neopharm, Roche, Medison, Sanofi, AstraZeneca and Boehringer-Ingelheim. S.T. received honoraria from/had a consultancy with Amgen, BMS/Celgene, GSK, Janssen, Pfizer, Sanofi, Takeda, Stemline and Kyowa Kirin. M.V.B.-B. had a consultancy and received research funding and honoraria from MSD Sharp & Dohme, Novartis, Roche, Kite/Gilead, Bristol-Myers Squibb, Astellas, Mologen and Miltenyi. I.M.G. received honoraria from Celgene, Bristol-Myers-Squibb, Takeda, Amgen, Janssen and Vor Biopharma, and had a consultancy/advisory role with Bristol-Myers-Squibb, Novartis, Amgen, Takeda, Celgene, Cellectar, Sanofi, Janssen, Pfizer, Menarini Silicon Biosystems, Oncopeptides, The Binding Site, GSK, Abbvie, Adaptive and 10X Genomics. M.S. receives industry research support from Amgen, BMS/Celgene, Gilead, Janssen, Miltenyi Biotec, Novartis, Roche, Seattle Genetics and Takeda, and serves as a consultant/advisor to AvenCell, CDR-Life, Ichnos Sciences, Incyte Biosciences, Janssen, Miltenyi Biotec, Molecular Partners, Novartis, Pfizer and Takeda. She serves on the speakers’ bureau at Amgen, AstraZeneca, BMS/Celgene, Gilead, GSK, Janssen, Novartis, Pfizer, Roche and Takeda. M.-A.P. reports honoraria from Adicet, Allogene, Allovir, Caribou Biosciences, Celgene, Bristol-Myers Squibb, Equilium, Exevir, ImmPACT Bio, Incyte, Karyopharm, Kite/Gilead, Merck, Miltenyi Biotec, MorphoSys, Nektar Therapeutics, Novartis, Omeros, OrcaBio, Sanofi, Syncopation, VectivBio AG and Vor Biopharma. He serves on data and safety monitoring boards for Cidara Therapeutics, Medigene and Sellas Life Sciences, and on the scientific advisory board of NexImmune. He has ownership interests in NexImmune, Omeros and OrcaBio and has received institutional research support for clinical trials from Allogene, Incyte, Kite/Gilead, Miltenyi Biotec, Nektar Therapeutics and Novartis. K.R. has received research funding, consultancy, honoraria and travel support from Kite/Gilead; honoraria from Novartis; consultancy and honoraria from BMS/Celgene; and travel support from Pierre-Fabre. The other authors declare no competing interests. None of the mentioned conflicts of interest was related to financing of this study.

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Extended data

Extended Data Fig. 1 NRM cumulative incidence rates are comparable to NRM point estimates.

A Left: Paired comparison of reported cumulative incidence rates of NRM and the calculated NRM point estimates. Two-sided Mann-Whitney test was used to explore statistical significance. Right: Difference between NRM point estimates and reported NRM in percent. Only studies reporting a 1-year NRM rate were included into the comparison with NRM point estimates (n = 13). B Correlation between NRM point estimates and cohort follow up times, which was primarily driven by clinical trial cohorts (light grey = clinical trials, dark grey = real-world studies). The Pearson correlation coefficient from the linear regression analysis is depicted together with the 95% confidence interval (orange line and shading). A total of 49 studies were included. Two-side p value was calculated using Pearson’s correlation coefficient. Abbreviations: CT = clinical trials, NRM = non-relapse mortality, RW = real-world.

Extended Data Fig. 2 NRM point estimates are similar between treatment settings but clinical trials show extended follow-up times.

A Bubble plot demonstrating NRM point estimates in relation to follow-up times for clinical trial cohorts (light blue) and real-world cohorts (dark grey). Each bubble represents one cohort. Bubble size indicates the total number of patients per cohort. The aggregated NRM point estimate for all cohorts within each treatment setting is encircled in black. B NRM point estimates with 95% CIs are shown for RWs (n = 34) and CT (n = 18, middle) and follow-up times (right). The p-value for the comparison of NRM point estimates was derived from the test for subgroup differences (random effects model). Two-sided Mann-Whitney test was used for statistical testing of FU times. Data is presented as point estimate proportion with error bars showing 95% CI. For box-plots, box represent interquartile range (IQR) and whiskers extend no further than 1.5 times the IQR from the uper/lower hinge. Data beyond whiskers are plotted as individual outliers. Horizontal line is the median. Abbreviations: CT = clinical trial, NRM = non-relapse mortality, RW = real-world.

Extended Data Fig. 3 Subgroup analysis of NRM point estimates stratified by disease entity.

Forest plot illustrating NRM point estimates and 95% confidence intervals (95% CI) stratified by disease entity. The results of the random effects model and measures of heterogeneity are shown for each disease entity. Data is presented as point estimate proportion with error bars showing 95% CI. The p-value for the comparison of subgroups was derived from a two-sided test for subgroup differences (random effects model). Abbreviations: IL = indolent lymphoma, LBCL = large B-cell lymphoma, MCL = mantle cell lymphoma, MM = multiple myeloma, NRM = non-relapse mortality.

Extended Data Fig. 4 Subgroup analysis of NRM point estimates stratified by CAR T-cell products.

Forest plot illustrating NRM point estimates and 95% confidence intervals (95% CI) stratified by the administered CAR T-cell product. The results of the random effects model and measures of heterogeneity are depicted for each disease entity. Only NRM point estimates that were attributable to a single CAR T-cell product were analyzed. Data is presented as point estimate proportion with error bars showing 95% CI. The p-value for the comparison of subgroups was derived from a two-sided test for subgroup differences (random effects model). NRM = non-relapse mortality.

Extended Data Fig. 5 NRM point estimates and follow-up times for individual CAR T-cell products.

A Comparison of NRM point estimates with 95% confidence intervals (95% CIs) across all studied CAR T-cell products. Data is presented as point estimate proportion with error bars showing 95% CI. P-value for the comparison of NRM point estimates was derived from the test for subgroup differences (random effects model). B Box plots indicating the median follow-up times (with 95% Cis) in months across all studied CAR T-cell products. Only NRM point estimates and follow-up times that were attributable to a single CAR T-cell product were included (cilta-cel: n = 4, brexu-cel: n = 5, axi-cel: n = 18, ide-cel: n = 8, tisa-cel: n = 9, liso-cel: n = 3). Two-sided Mann-Whitney test was used for statistical testing of FU times. The box represent interquartile range (IQR) and whiskers extend no further than 1.5 times the IQR from the uper/lower hinge. Data beyond whiskers are plotted as individual outliers. Horizontal line is the median. Abbreviations: FU = follow-up, NRM = non-relapse mortality.

Extended Data Fig. 6 Reported 1-year NRM rates in LBCL studies are higher in axi-cel compared to tisa-cel.

Reported 1-year NRM rates based on cumulative incidence functions were extracted from LBCL studies and compared between the CAR T-cell products axi-cel (n = 4) and tisa-cel (n = 5). Reported NRM rates for liso-cel were not available. Two-sided Mann-Whitney test was used for statistical testing. The box represent interquartile range (IQR) and whiskers extend no further than 1.5 times the IQR from the uper/lower hinge. Data beyond whiskers are plotted as individual outliers. Horizontal line is the median. Abbreviations: LBCL = large B-cell lymphoma, NRM = non-relapse mortality.

Extended Data Fig. 7 LBCL-specific subgroup analyses of NRM point estimates.

Comparison of LBCL-specific aggregated NRM point estimates with 95% CIs for treatment setting (CT n = 9, RW n = 22), follow-up time, treatment line and era. To compare follow-up times, studies were classified using the median follow-up of 13.0 months determined for LBCL studies (FU ≤ 13 n = 15, FU > 13 n = 11). For the comparison of treatment lines, we examined studies using CD19 CAR-T cells in first or second line (earlier, n = 6) versus third line and beyond (later, n = 25). Treatment era was defined based on an inclusion end date before versus after 01/2020 (before n = 7, after n = 24). P-values for the comparison of NRM point estimates were derived from the test for subgroup differences (random effects model). Abbreviations: CT = clinical trial, FU = follow-up, LBCL = large B-cell lymphoma, NRM = non-relapse mortality, RW = real-world.

Extended Data Fig. 8 MM-specific subgroup analyses of NRM point estimates.

Comparison of MM-specific aggregated NRM point estimates with 95% CIs for treatment setting (CT n = 6, RW n = 7), follow-up time, treatment line and era. To compare follow-up times, studies were classified using the median follow-up of 13.3 months determined for MM studies (FU ≤ 13.3 n = 6, FU > 13.3 n = 7). For the comparison of treatment lines, we examined studies using BCMA CAR-T cells in an earlier indication (CARTITUDE-4 and KarMMA-3, ‘earlier’, n = 2) versus later indication (other studies, ‘later’, n = 11). Treatment era was defined based on an inclusion end date before versus after 01/2020 (before n = 3, after n = 9). P-values for the comparison of NRM point estimates were derived from the test for subgroup differences (random effects model). Abbreviations: CT = clinical trial, FU = follow-up, MM = multiple myeloma, NRM = non-relapse mortality, RW = real-world.

Extended Data Fig. 9 Causes of death are similar between entity-specific CAR T-cell products.

Causes of death were compared across CAR T-cell products for lymphoma (left), MM (middle) and mantle cell lymphoma patients (right). The number of cases for each product is depicted at the bottom of the graph. Only NRM-related deaths that were attributable to a single CAR T-cell product were used. The relative distribution of the different causes of death is depicted across the different CAR T-cell products. Two-sided Chi-square distribution test was used for statistical testing. Abbreviations: CRS = cytokine release syndrome, HLH = hemophagocytic lymphohistiocytosis, ICANS = immune effector cell-associated neurotoxicity syndrome.

Extended Data Table 1 Sensitivity analyses

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Tables 1–4, study protocol and PRISMA checklist.

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Cordas dos Santos, D.M., Tix, T., Shouval, R. et al. A systematic review and meta-analysis of nonrelapse mortality after CAR T cell therapy. Nat Med (2024). https://doi.org/10.1038/s41591-024-03084-6

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