Dear Editor,
The introduction of chimeric antigen receptor T-cell (CAR-T) therapies has significantly transformed the treatment landscape for patients with relapsed/refractory (r/r) multiple myeloma (MM). BCMA-directed CAR-T cell therapies, idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel), have revolutionized the field by demonstrating remarkable efficacy in pivotal clinical trials [1, 2]. With a median age at diagnosis of 69 years, older adults ( ≥ 70 years) represent a substantial proportion of the r/r MM population [3]. However, with a median age of 63 years and 61.5 years for KarMMa-3 and CARTITUDE-4, r/r MM patients aged ≥70 years are underrepresented in these trials [1, 2]. This age group is more likely to have additional comorbidities and a higher frailty index, raising questions about the efficacy and safety of CAR-T therapies in this more vulnerable population [4–6].
In the present study, we sought to evaluate differences in clinical outcomes and toxicity profiles between elderly patients aged 70 years and older and their younger counterparts. By identifying age-related differences, we aim to provide insights that could inform patient selection, risk stratification, and supportive care strategies for optimizing the use of CAR-T therapies in clinical practice.
This retrospective study enrolled 148 r/r MM patients treated with idecabtagene vicleucel (ide-cel) (n = 140/148) and ciltacabtagene autoleucel (cilta-cel) (n = 8/148) between March 2022 and September 2024 in seven German and one Swiss hospitals. Clinical data were retrospectively extracted from the medical records and electronic patient files and informed consent was obtained. The study was approved by the Ethics Committee of the University Hospital Münster (approval number 2024-068-f-S) and was performed in accordance with the Declaration of Helsinki. The details on definitions and statistical analysis are presented in Supplementary Information. Age 70 years was used as the prespecified cutoff for age-stratified analyses based on exploratory spline modeling (Supplementary Fig. 1). Based on this, 96 patients (64.9%) were <70 years and 52 patients (35.1%) were ≥70 years of age at the time of CAR-T infusion. The participating centers contributed between 8 and 40 patients each, with the proportion of patients aged ≥70 years ranging from 20% to 53% across all seven centers.
Baseline characteristics by age group ( < 70 vs. ≥70 years) are summarized in Table 1. Elderly patients had significantly higher comorbidity (CCI ≥ 4: 71.2% vs. 28.1%; p < 0.001) and frailty (IMWG simplified frailty: 84.0% vs. 55.6%) compared with younger patients. In contrast, prior treatment exposure, disease risk stratification using the MyCARe score [7], number of prior therapy lines, and response status at CAR-T infusion were comparable between groups.
Table 1.
Baseline characteristics of all patients.
| Variable | Total cohort (N = 148) | < 70 years (N = 96) | ≥ 70 years (N = 52) | P-value |
|---|---|---|---|---|
| Median age at CAR-T infusion in years [Min, Max] | 65.0 [37.0, 82.6] | 61.0 [37.0, 69.3] | 73.0 [70.0, 82.6] | <0.001 |
| Age at CAR-T infusion in categories | <0.001 | |||
| <60 years | 44 (29.7%) | 44 (45.8%) | 0 (0%) | |
| 60–69 years | 52 (35.1%) | 52 (54.2%) | 0 (0%) | |
| ≥ 70 years | 52 (35.1%) | 0 (0%) | 52 (100%) | |
| <75 years | 36 (69.2%) | |||
| ≥75 years | 16 (30.8%) | |||
| Female | 56 (37.8%) | 40 (41.7%) | 16 (30.8%) | 0.217 |
| ECOG | 0.544 | |||
| 0–1 | 119 (90.8%) | 77 (89.5%) | 42 (93.3%) | |
| >1 | 12 (9.2%) | 9 (10.5%) | 3 (6.7%) | |
| Missing | 17 | 10 | 7 | |
| Charlson Comorbidity Index (CCI) | <0.001 | |||
| 0–1 | 14 (9.5%) | 13 (13.5%) | 1 (1.9%) | |
| 2–3 | 70 (47.3%) | 56 (58.3%) | 14 (26.9%) | |
| ≥4 | 64 (43.2%) | 27 (28.1%) | 37 (71.2%) | |
| Simplified frailty score | <0.001 | |||
| Frail | 92 (65.7%) | 50 (55.6%) | 42 (84.0%) | |
| Non-frail | 48 (34.3%) | 40 (44.4%) | 8 (16.0%) | |
| Missing | 8 | 6 | 2 | |
| Myeloma Type | 0.209 | |||
| IgG | 85 (57.8%) | 51 (53.7%) | 34 (65.4%) | |
| IgA | 28 (19.0%) | 23 (24.2%) | 5 (9.6%) | |
| IgM | 3 (2.0%) | 1 (1.1%) | 2 (3.8%) | |
| Kappa | 14 (9.5%) | 8 (8.4%) | 6 (11.5%) | |
| Lambda | 14 (9.5%) | 10 (10.5%) | 4 (7.7%) | |
| asecretory | 3 (2.0%) | 2 (2.1%) | 1 (1.9%) | |
| Missing | 1 | 1 | 0 | |
| R-ISS Stage at Diagnosis | 0.119 | |||
| I | 30 (24.0%) | 19 (23.8%) | 11 (24.4%) | |
| II | 47 (37.6%) | 35 (43.8%) | 12 (26.7%) | |
| III | 48 (38.4%) | 26 (32.5%) | 22 (48.9%) | |
| Missing | 23 | 16 | 7 | |
| High-Risk Cytogenetics (17p deletion, t(4;14), t(14;16), t(14;20)) | 64 (48.1%) | 47 (52.8%) | 17 (38.6%) | 0.143 |
| CAR-T Product | 0.452 | |||
| Ide-cel | 140 (94.6%) | 92 (95.8%) | 48 (92.3%) | |
| Cilta-cel | 8 (5.4%) | 4 (4.2%) | 4 (7.7%) | |
| Plasma cell leukemia | 1 (0.7%) | 1 (1.0%) | 0 (0%) | 1 |
| Extramedullary disease | 56 (37.8%) | 40 (41.7%) | 16 (30.8%) | 0.217 |
| MyCARe score | 0.293 | |||
| low (0-1) | 40 (27.0%) | 24 (25.0%) | 16 (30.8%) | |
| intermediate (2–3) | 88 (59.5%) | 56 (58.3%) | 32 (61.5%) | |
| high (4) | 20 (13.5%) | 16 (16.7%) | 4 (7.7%) | |
| Prior treatment lines (Median, Min, Max) | 5.00 [3.00, 15.0] | 5.00 [3.00, 15.0] | 5.00 [3.00, 12.0] | 0.316 |
| Lenalidomide refractory | 123 (83.1%) | 80 (83.3%) | 43 (82.7%) | 1 |
| Triple refractory | 136 (91.9%) | 89 (92.7%) | 47 (90.4%) | 0.754 |
| Penta refractory | 80 (54.1%) | 48 (50.0%) | 32 (61.5%) | 0.227 |
| Previous BCMA-directed Therapy | 21 (14.3%) | 14 (14.7%) | 7 (13.5%) | 1 |
| Prior HDCT/autoSCT | 134 (90.5%) | 90 (93.8%) | 44 (84.6%) | 0.0828 |
| Prior alloSCT | 9 (6.1%) | 7 (7.3%) | 2 (3.8%) | 0.494 |
| Response status at CAR-T infusion | 0.367 | |||
| CR/VGPR/PR | 52 (35.9%) | 31 (33.0%) | 21 (41.2%) | |
| nonPR | 93 (64.1%) | 63 (67.0%) | 30 (58.8%) | |
| Missing | 3 | 2 | 1 | |
| Holding/Bridging therapy prior to CAR-T | 0.729 | |||
| Holding therapy | 36 (24.3%) | 21 (21.9%) | 15 (28.8%) | |
| Bridging therapy | ||||
| Conventional anti-CD38/PI/IMiD regimens | 83 (56.1%) | 54 (56.3%) | 29 (55.8%) | |
| Chemotherapy-based | 21 (14.2%) | 15 (15.6%) | 6 (11.5%) | |
| Bispecific antibodies | 8 (5.4%) | 6 (6.3%) | 2 (3.8%) | |
| Number of applied bridging therapies | ||||
| 1 | 103 (70.1%) | 68 (71.6%) | 35 (67.3%) | 0.526 |
| 2 | 8 (5.4%) | 6 (6.3%) | 2 (3.8%) | |
| 3 | 2 (1.4%) | 2 (2.1%) | 0 (0%) | |
| Missing | 1 | 1 | 0 | |
| Median time apheresis-CAR-T (days) | 58.0 [2.00, 252] | 58.5 [43.0, 200] | 58.0 [2.00, 252] | 0.94 |
| Median time diagnosis-CAR-T (years) | 7.00 [0, 26.2] | 6.75 [0, 26.2] | 7.90 [0, 19.5] | 0.94 |
| Median follow-up of survivors in months post-CAR-T | 8.65 [0.400, 26.5] | 9.25 [0.400, 24.4] | 7.20 [0.400, 26.5] | 0.202 |
CAR-T chimeric antigen receptor T-cell, ECOG Eastern Cooperative Oncology Group performance status, CCI Charlson Comorbidity Index, R-ISS, Revised International Staging System, BCMA B-cell maturation antigen, Ide-cel idecabtagene vicleucel, Cilta-cel ciltacabtagene autoleucel, HDCT high-dose chemotherapy, autoSCT autologous stem cell transplantation, alloSCT allogeneic stem cell transplantation, PI proteasome inhibitor, IMiD immunomodulatory drugs, CR complete response, VGPR very good partial response, PR partial response, nonPR less than partial response.
Bold values just highlight a statistical significance.
The use and type of holding or bridging therapy prior to CAR-T were comparable between both groups (Table 1). Overall, 24.3% of patients received holding therapy, while the remainder required bridging therapy. Among bridged patients, conventional anti-CD38/PI/IMiD regimens were most frequently used, accounting for 56.1% of all cases. Chemotherapy-based regimens were administered in 14.2%, and bispecific antibodies in 5.4% as bridging therapy. Most patients received one line of bridging therapy (70.1%); 5.4% and 1.4% received two and three distinct bridging regimens, respectively.
Outcomes after CAR-T cell therapy are shown in Supplementary Table 1 and Fig. 1.
Fig. 1. Age-stratified efficacy and safety outcomes.
Age-stratified outcomes comparing patients <70 years (red) and ≥70 years (blue). A Overall survival (OS) and (B) progression-free survival (PFS) were compared using the log-rank test. C Relapse incidence (RI) and (D) non-relapse mortality (NRM) was compared using Gray’s test. Numbers at risk are shown below each plot. E Best response before and after CAR-T therapy by age group; p-values indicate within-group paired comparisons of CR rates before versus after CAR-T. F Distribution of cytokine release syndrome (CRS) and immune effector cell–associated neurotoxicity syndrome (ICANS) grades according to age.
With a median follow-up of 8.7 months among survivors (range: 0.4–27 months), the cumulative incidence of relapse at 12 months was comparable between age groups - 41.4% (95% CI: 22.3–59.5%) in patients aged ≥70 years versus 48.3% (95% CI: 35.6–59.9%) in those <70 years (Fig. 1A). In contrast, the cumulative incidence of non-relapse mortality (NRM) was numerically higher in the older cohort, reaching 17.1% (95% CI: 7.1–30.8%) compared to 6.7% (95% CI: 2.3–14.1%) in younger patients (Fig. 1B) (p = 0.10). The estimated 12-month PFS rates were 43.5% (95% CI: 32.7–57.8%) and 47.8% (95% CI: 32.8–69.7%) for patients <70 and ≥70 years, respectively, while the corresponding 12-month OS rates were 74.4% (95% CI: 64.8–85.6%) and 68.4% (95% CI: 54.3–86.1%) (both p > 0.05) (Fig. 1C, D). The overall response rate, indicated by achieving a CR or (VG)PR as the best response, was 78.7% ( < 70 years) and 94.1% ( ≥ 70 years) for both age groups (p = 0.002), respectively. In both age groups, response depth significantly improved post-infusion, with a higher CR-rate observed among older patients (58.8% vs. 42.6%) (Fig. 1E).
Figure 1F and Supplementary Table 1 summarize treatment-related toxicities, hematologic recovery, and early outcomes after CAR-T therapy stratified by age group. Severe cytokine release syndrome (CRS; grade >2) occurred in 7.5% of patients overall (7.4% vs. 7.7% in those; p = 1.0). Grade >2 immune effector cell-associated neurotoxicity syndrome (ICANS) occurred in 3.2% of younger patients and in none of the older cohort. Hematologic recovery and immunoglobulin nadirs were comparable between age groups.
After propensity score matching (n = 47 per group), baseline characteristics were largely balanced, although extramedullary disease remained more frequent in younger patients (Supplementary Table 2). In the matched cohort, age-stratified OS and RI/NRM patterns remained comparable (Supplementary Fig. 2). Univariable and multivariable competing-risks regression identified factors associated with relapse incidence and NRM (Supplementary Fig. 3A; Supplementary Table 3). For RI, extramedullary disease, intermediate/high MyCARe (both p < 0.05), and a higher number of prior therapy lines were associated with increased risk in univariable analyses; in multivariable analysis, high-risk MyCARe [4] remained associated with RI (HR = 3.30, p = 0.012). For NRM, prior HDCT/ASCT was associated with reduced risk (HR = 0.19, p = 0.004), whereas age group, simplified frailty, and prior therapy lines were not significant after adjustment. In multivariable Cox models for OS and PFS (Supplementary Fig. 3B; Supplementary Table 4), high-risk MyCARe [4] was associated with inferior PFS (HR = 3.63, p = 0.004) and OS (HR = 3.46, p = 0.041). Frailty was associated with reduced OS (HR = 2.45, p = 0.039), while prior HDCT/ASCT was favorable (HR = 0.29, p = 0.009). A higher number of prior therapy lines was associated with decreased PFS (HR = 1.11 per line, p = 0.030); other covariates, including age group, were not significant after adjustment.
Beyond efficacy, our analyses highlight the persistent risk of non-relapse mortality, predominantly driven by infections in patients treated with CAR-T. Our data is consistent with the fatal infections reported in large meta-analyses underscoring the importance of structured follow-up and preventive strategies, particularly in elderly and comorbid patients. Immune monitoring, including serial immunoglobulin assessment and markers of immune may help identify patients at increased risk for severe infections. Preventive measures should include immunoglobulin substitution when indicated, antibacterial and antiviral prophylaxis, and vaccination strategies to reduce infectious complications. Despite being a multicenter study, the sample size, particularly for the ≥70 years subgroup, was limited, which may reduce the power to detect differences in less frequent outcomes such as NRM. The possible bias such analyses like presented here is patient selection. Younger patients may represent a more unfavorable group due to more aggressive disease characteristics, while elderly patients are evaluated more thoroughly in terms of eligibility to CAR-T cell therapy. Additionally, limited follow-up time limits the ability to assess long-term outcomes and durability of response. The retrospective design and the predominance of ide-cel patients also introduce potential bias in patient selection and data completeness.
Limited data exist on cilta-cel outcomes in elderly and frail patients. Recent conference abstracts by Velayati et al. found no age-related differences in efficacy or toxicity among 64 patients aged ≥75 versus 128 younger patients receiving cilta-cel [8], while Mian et al. reported that frailty ( ≥ 2 points on simplified frailty index) was not associated with response or CRS grade ≥2 risk in 183 frail versus 358 non-frail cilta-cel recipients [9], though overall survival was inferior. These findings are consistent with our predominantly ide-cel cohort results. As such, larger cilta-cel-specific studies are warranted given its increasing use and distinct toxicity profile. Importantly, a strength of our analysis is that most elderly patients (84%) were frail, supporting the feasibility of CAR-T in a clinically vulnerable real-world population.
However, despite a significantly higher prevalence of frailty and comorbidities in patients aged ≥70 years, we observed comparable clinical outcomes after BCMA-directed CAR-T therapy in older and younger patients, with similar overall response rates exceeding 80% and no significant differences in PFS or OS. Second, treatment-related toxicities, including high-grade CRS, ICANS, infections, and hematologic recovery, were not increased in the elderly cohort, supporting the feasibility of CAR-T therapy in this population. Notably, comparable findings have been observed in other real-world studies analyzing the efficacy and safety of CD19- or BCMA-directed CAR-T cell therapy in patients with aggressive B-cell lymphoma [10–13] or multiple myeloma [8, 14] (Supplementary Table 5A and 5B).
Third, after propensity score matching for relevant clinical variables, survival outcomes remained comparable between age groups, reinforcing that age alone should not be a barrier to CAR-T eligibility. Finally, multivariable analyses highlighted that risk factors such as high MyCARe score, comorbidity burden represented by the simplified frailty scoring (which incorporates the CCI) were more strongly associated with adverse outcomes, including relapse incidence, NRM, and OS, than an age cutoff of 70 years. These findings should encourage clinicians to offer BCMA targeted CAR-T cell therapies to elderly patients with a clear indication and support a more individualized approach to CAR-T selection. Furthermore, they underscore the importance of integrating frailty and disease biology into treatment decision-making.
Supplementary information
Author contributions
PB, TP, and ES conceived the study. PB and ES performed data analysis and wrote the manuscript. TP and ES jointly supervised the work. All authors contributed data, critically revised the manuscript, and approved the final version.
Data availability
The data supporting the findings of this study are available from the corresponding author upon reasonable request, subject to data protection restrictions.
Competing interests
GL received research grants not related to this manuscript from AGIOS, AQUINOX, AstraZeneca, Bayer, Celgene, Gilead, Janssen, MorphoSys, Novartis, F. Hoffmann-La Roche Ltd, and Verastem. GL received honoraria not related to this study from ADC Therapeutics, AbbVie, Amgen, AstraZeneca, Bayer, BeiGene, BMS, Celgene, Constellation, Genase, Genmab, Gilead, Hexal/Sandoz, Immagene, Incyte, Janssen, Karyopharm, Lilly, Miltenyi, MorphoSys, MSD, NanoString, Novartis, PentixaPharm, Pierre Fabre, F. Hoffmann-La Roche Ltd, and Sobi. MM received honoraria from AbbVie, AstraZeneca, Gilead and Lilly and congress/travel support from AbbVie, Gilead, Stemline therapeutics, Incyte, Sobi and Johnson & Johnson. RWK received honoraria from BMS, Gilead, Hexal, Roche, and Sobi. AB received honoraria from GSK, AstraZeneca, Menarini StemLine, Johnson and Johnson, Pfizer Oncopeptides, BMS; Advisory Board: GSK, AstraZeneca, Menarini StemLine, Johnson and Johnson, Pfizer Oncopeptides; and has received travel support from Pfizer, AstraZeneca, Johnson and Johnson, BMS. MS has served as a consultant for Pfizer, MSD, Bristol-Myers Squibb (BMS), Incyte, Takeda, Astellas, Autolus, Sanofi and Amgen; as a speaker for Pfizer, Medac, MSD, Astellas, Jazz Pharmaceuticals, Amgen, Novartis, Gilead, Celgene, BMS, AbbVie, and Incyte; has received research funding from Pfizer; and has received travel support from Medac, Sanofi and Pfizer. FHH is a consultant for BMS/Celgene, AOP, Novartis, CTI, Janssen, AbbVie, GSK, Merck, CTI, Kartos, Telios, Silence Therapeutics, Prelude Therapeutics, Geron and Sumitomo and received research funding from: Novartis, BMS/Celgene and CTI. ES received honoraria not related to this manuscript from Amgen, BMS, Sanofi, Oncopeptides, Gilead, Incyte, Lilly, Roche, Abbvie and Takeda.
Footnotes
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These authors contributed equally: Thomas Pabst, Evgenii Shumilov.
Supplementary information
The online version contains supplementary material available at 10.1038/s41408-026-01531-w.
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Associated Data
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Supplementary Materials
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request, subject to data protection restrictions.