Efficacy and safety of chimeric antigen receptor T-cell in the treatment of hematologic malignancy: an umbrella review of systematic review and meta-analysis

Background: This umbrella review consolidates data from systematic reviews and meta-analyses on the efficacy and safety of Chimeric Antigen Receptor T-cell (CAR-T) therapy in hematologic malignancies. The aim is to assess CAR-T efficacy across different malignancies, identify key safety concerns, and provide clinical recommendations.

Methods: We conducted a thorough search of PubMed, Embase, Web of Science, and the Cochrane Database of Systematic Reviews up to May 2024. Systematic reviews and meta-analyses evaluating CAR-T efficacy in hematologic malignancies were included. The AMSTAR tool was used to assess methodological quality, and the GRADE system was employed to evaluate the quality of evidence for each outcome.

Results: A total of 105 meta-analyses met the inclusion criteria. CD19-targeted CAR-T therapies demonstrated superior efficacy in acute lymphoblastic leukemia (ALL) and diffuse large B-cell lymphoma (DLBCL), particularly in relapsed or refractory cases (high-quality). However, CAR-T monotherapy showed reduced efficacy in central nervous system lymphoma (CNSL) (middle-quality). Combination therapies, particularly CAR-T with HSCT, improved complete response rates but were associated with increased severe adverse events, such as CRS and neurotoxicity (high-quality). Axi-cel was found to carry a higher risk of ICANS and neutropenia compared to Tisa-ce (high-quality), likely due to its CD28 costimulatory domains, which enhance T-cell activation.

Conclusions: CAR-T therapy demonstrates promising clinical outcomes in ALL and DLBCL, but significant safety concerns remain. Combining CAR-T with therapies such as HSCT improves efficacy but also heightens the risk of severe toxicities. Future research should focus on optimizing CAR-T constructs, refining preconditioning regimens, and identifying predictive biomarkers to personalize treatment and mitigate risks in vulnerable populations.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024581782.

1 Introduction

Hematologic malignancies, which affect the blood, bone marrow, and lymphatic system, pose a significant global health threat. These malignancies include leukemias and lymphomas. Leukemias, such as acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), result from the malignant transformation of hematopoietic cells, causing the unchecked proliferation of abnormal leukocytes that interfere with normal blood cell production (1, 2). Lymphomas, including Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL), are cancers originating in the lymphatic system. NHL is further categorized into various subtypes. Treatment for these cancers has traditionally relied on chemotherapy, which, despite its extensive use, is associated with significant side effects, including toxicity and the development of drug resistance (3). Targeted therapies, such as monoclonal antibodies like rituximab (for NHL) and blinatumomab (for ALL), are key elements of contemporary treatment protocols in combination with chemotherapy (3, 4).

Chimeric antigen receptor T-cell (CAR-T) therapy has transformed the treatment of hematologic malignancies over the past decade by genetically altering T-cells to target tumor-associated antigens, eliciting an immune response against malignant cells. This approach has demonstrated substantial efficacy in patients with relapsed or refractory B-cell malignancies, including large B-cell lymphoma (DLBCL) and acute lymphoblastic leukemia (ALL). Approved CAR-T therapies, such as Kymriah (Tisagenlecleucel) and Yescarta (Axicabtagene ciloleucel), offer significant clinical benefits, inducing long-lasting remissions in patients resistant to multiple treatments (5, 6). Despite the potential of CAR-T, significant challenges persist in safety and efficacy across diverse patient populations and lymphoma subtypes, prompting continued research into optimal treatment strategies (7, 8).

Numerous systematic reviews and meta-analyses have evaluated CAR-T therapy outcomes in hematologic malignancies, emphasizing the efficacy of specific constructs in patients with relapsed/refractory DLBCL and ALL. However, variability exists across studies in patient selection, CAR-T constructs (targeting antigens such as CD19 and CD22), and manufacturing protocols. Recent research has explored combining CAR-T therapy with hematopoietic stem cell transplantation to enhance outcomes (9). Research on optimizing co-stimulatory domains in CAR-T cells suggests that fine-tuning these domains may improve efficacy and address limitations in response and persistence, especially in aggressive lymphoma subtypes (10). However, these combination strategies remain contentious and require further investigation in larger, well-designed clinical trials.

Despite a wealth of meta-analytic data, challenges in interpreting the evidence persist due to study heterogeneity, arising from variations in inclusion criteria, patient characteristics, sample sizes, and timing. For instance, some meta-analyses compare CAR-T therapies targeting distinct antigens (11), while others explore variations in treatment regimens, including pre-conditioning and combination therapies (12). This variability hinders drawing definitive conclusions on the efficacy and safety of different CAR-T therapies, while disparities in sample size and follow-up periods obstruct the formulation of clear clinical guidelines (12). These inconsistencies have fragmented the understanding of CAR-T therapy’s benefit, especially in combination treatments.

This umbrella review seeks to consolidate and analyze data from multiple meta-analyses using rigorous evidence-based methodologies to deliver a comprehensive evaluation. This umbrella review synthesizes data from these studies to offer a comprehensive analysis of CAR-T therapy’s efficacy, safety, and optimal application in hematologic malignancies. This review will evaluate the role of combination therapies in improving clinical outcomes and offer evidence-based recommendations to optimize patient prognosis in managing these malignancies.

2 Methods and analysis

2.1 Design and registration

We systematically reviewed and analyzed data from published systematic reviews and meta-analyses on the efficacy and safety of CAR-T therapy for hematologic malignancies, adhering to PRISMA guidelines (13). This umbrella review followed the Joanna Briggs Institute Manual for Evidence Synthesis of Umbrella Reviews (14) and the Cochrane Handbook for Systematic Reviews (15). This umbrella review was prospectively registered in PROSPERO (CRD42024581782, https://www.crd.york.ac.uk/PROSPERO/).

2.2 Eligibility criteria

Systematic reviews and meta-analyses evaluating the efficacy and safety of CAR-T therapy for hematologic malignancies in all populations were included. Data for each intervention were extracted separately if a meta-analysis reported multiple CAR-T therapies. For identical CAR-T interventions, the latest meta-analysis was included if published over 24 months apart. Within a 24-month window, the one with the most prospective studies was selected; if tied, the meta-analysis with the higher AMSTAR score was chosen (16, 17). If the latest meta-analysis lacks a dose-response analysis but another includes it, both were considered. Non-English, animal, and cell culture studies were excluded.

2.3 Population

This umbrella review analyzes systematic reviews and meta-analyses on CAR-T therapy for hematologic malignancies, including ALL, AML, CLL, CML, HL, NHL, multiple myeloma, MPN, and MDS, among others.

2.4 Exposure

We included meta-analyses reporting at least one CAR-T intervention, with efficacy assessed using odds ratios (OR), relative risks (RR), or hazard ratios (HR) and 95% confidence intervals (CIs).

2.5 Study designs

Only systematic reviews and meta-analyses evaluating the efficacy and safety of CAR-T in treating hematologic malignancies across diverse ethnicities, sexes, countries, and settings were included. These reviews and meta-analyses concentrated on CAR-T and provided comprehensive methods, including search strategies, inclusion/exclusion criteria, quality assessment, outcome evaluation, analytical procedures, and interpretation criteria. The original studies included in the meta-analyses comprised randomized controlled trials (RCTs) and non-randomized interventional clinical trials.

2.6 Information sources

We searched PubMed, Embase, Web of Science, and the Cochrane Database of Systematic Reviews from inception to May 2024 (2024-05-25) for systematic reviews and meta-analyses of interventional studies and examined the reference lists of included meta-analyses for further articles.

2.7 Search strategy

We searched databases using MeSH terms, keywords, and text words related to CAR-T and hematologic malignancies, adhering to SIGN guidelines for literature searching: (((((((((((((((((( Myelodysplastic Syndrome) OR (Syndrome, Myelodysplastic)) OR (Syndromes, Myelodysplastic)) OR (Dysmyelopoietic Syndromes)) OR (Dysmyelopoietic Syndrome)) OR (Syndrome, Dysmyelopoietic)) OR (Syndromes, Dysmyelopoietic)) OR (Hematopoetic Myelodysplasia)) OR (Hematopoetic Myelodysplasias)) OR (Myelodysplasia, Hematopoetic)) OR (Myelodysplasias, Hematopoetic)) OR (MDS)) OR (“Myelodysplastic Syndromes”[Mesh])) OR ((“Multiple Myeloma”[Mesh]) OR ((((((((((((((((((((Multiple Myelomas) OR (Myelomas, Multiple)) OR (Myeloma, Plasma-Cell)) OR (Myeloma, Plasma Cell)) OR (Myelomas, Plasma-Cell)) OR (Plasma-Cell Myeloma)) OR (Plasma-Cell Myelomas)) OR (Myeloma-Multiple)) OR (Myeloma Multiple)) OR (Myeloma-Multiples)) OR (Myeloma, Multiple)) OR (Plasma Cell Myeloma)) OR (Cell Myeloma, Plasma)) OR (Cell Myelomas, Plasma)) OR (Myelomas, Plasma Cell)) OR (Plasma Cell Myelomas)) OR (Kahler Disease)) OR (Disease, Kahler)) OR (My-elomatosis)) OR (Myelomatoses)))) OR ((“Lymphoma”[Mesh]) OR (((((((((((((Lymphomas) OR (Germinoblastoma)) OR (Germinoblastomas)) OR (Lymphoma, Malignant)) OR (Lymphomas, Malignant)) OR (Malignant Lymphoma)) OR (Malignant Lymphomas)) OR (Reticulolymphosarcoma)) OR (Reticulolymphosarcomas)) OR (Sarcoma, Germinoblastic)) OR (Germinoblastic Sarcoma)) OR (Germinoblastic Sarcomas)) OR (Sarcomas, Germinoblastic)))) OR ((“Leukemia”[Mesh]) OR ((((Leucocythaemia) OR (Leucocythaemias)) OR (Leucocythemia)) OR (Leucocythemias)))) OR ((“Hematologic Neoplasms”[Mesh]) OR (((((((((((((((((((((((Hematologic Neoplasm) OR (Neoplasm, Hematologic)) OR (Hematologic Malignancies)) OR (Hematologic Malignancy)) OR (Hematological Malignancies)) OR (Hematological Malignancy)) OR (Malignancy, Hematological)) OR (Hematological Neoplasms)) OR (Hematological Neoplasm)) OR (Neoplasm, Hematological)) OR (Malignancies, Hematologic)) OR (Malignancy, Hematologic)) OR (Blood Cancer)) OR (Blood Cancers)) OR (Cancer, Blood)) OR (Neoplasms, Hematologic)) OR (Hematopoietic Neoplasms)) OR (Hematopoietic Neoplasm)) OR (Neoplasm, Hematopoietic)) OR (Neoplasms, Hematopoietic)) OR (Hematopoietic Malignancies)) OR (Hematopoietic Malignancy)) OR (Malignancy, Hematopoietic)))) AND ((“Receptors, Chimeric Antigen”[Mesh]) OR ((((((((((((((((((((Antigen Receptors, Chimeric) OR (Chimeric T-Cell Receptor)) OR (Chimeric T Cell Receptor)) OR (Receptor, Chimeric T-Cell)) OR (T-Cell Receptor, Chimeric)) OR (Chimeric Antigen Receptor)) OR (Antigen Receptor, Chimeric)) OR (Receptor, Chimeric Antigen)) OR (Chimeric Immunoreceptors)) OR (Immunoreceptors, Chimeric)) OR (Chimeric T-Cell Receptors)) OR (Chimeric T Cell Receptors)) OR (Receptors, Chimeric T-Cell)) OR (T-Cell Receptors, Chimeric)) OR (Artificial T-Cell Receptors)) OR (Artificial T Cell Receptors)) OR (Receptors, Artificial T-Cell)) OR (T-Cell Receptors, Artificial)) OR (Chimeric Antigen Receptors)) OR (CAR-T)))) AND (systematic review OR meta-analysis) (18).

2.8 Study selection

All literature was screened using Endnote X9. After eliminating duplicates, two authors independently assessed titles, abstracts, and full texts to identify meta-analyses that met the inclusion criteria. Discrepancies were resolved by a third author. Additionally, reference lists were manually searched for any potentially missed meta-analyses (Figure 1).

Figure 1

Figure 1. PRISMA flow diagram illustrating the study screening and selection process for Mendelian randomization studies (performed on 25/05/2024).

2.9 Assessment of methodological quality

The methodological quality of each meta-analysis was evaluated by two authors using AMSTAR, a validated tool for assessing systematic reviews and meta-analyses (16, 19). Health outcome evidence was assessed and classified as “high,” “moderate,” “low,” or “very low” quality using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework to draw conclusions (20). Epidemiologic evidence for each intervention will be classified into four categories: class I (convincing evidence), class II (highly suggestive evidence), class III (suggestive evidence), class IV (weak evidence), and NS (nonsignificant) (Table 1) (21–23).

Table 1

Table 1. Evidence categories criteria.

2.10 Data extraction

Two authors independently extracted data from each eligible study, including: 1) author name, 2) publication date, 3) CAR-T type, 4) population, 5) number of studies, 6) intervention and control participants, 7) study design, 8) follow-up duration, 9) outcomes, and 10) RR, OR, or HR estimates with 95% CIs. We also documented the meta-analytic model (random or fixed), heterogeneity estimates (I² and Cochran’s Q-test), and small-study assessments (Egger’s test, Begg’s test, and funnel plot). For studies with dose-response or subgroup analyses, we recorded the P value for nonlinearity and subgroup estimates. Disagreements were resolved by a third author.

2.11 Data summary

We recalculated RR, OR, or HR with 95% CIs using random or fixed effects models and evaluated heterogeneity (I², Cochran’s Q-test) and small-study effects (Egger or Begg test) for meta-analyses with more than 10 studies, provided sufficient data were available (24–26). For high- or moderate-quality interventions, we performed sensitivity analysis, when sufficient data were available, to evaluate the influence of individual studies on the overall significance of the evidence. Dose-response analysis for CAR-T interventions was also extracted from the included meta-analyses. If the most recent meta-analysis omits studies included in others, we combine their data for re-analysis. A P value < 0.10 is considered statistically significant for heterogeneity tests, while a P value < 0.05 is considered significant for other tests. Evidence synthesis is performed using Review Manager version 5.4 (Cochrane Collaboration, Oxford, UK). Egger and Begg tests, as well as sensitivity analysis, are conducted using Stata version 15.1.

3 Major outcomes

3.1 Characteristics of meta-analyses

The literature search process is depicted in Figure 1. A systematic search identified 1,045 unique articles, of which 62 meta-analyses fulfilled the inclusion criteria (11, 12, 27–86). We identified 39 unique interventions in the meta-analysis, including 13 significantly associated and 26 non-significantly associated interventions (Table 2). The median AMSTAR score was 9 (range: 7-10) (Table 2). Supplementary Table S1 displays AMSTAR scores for each outcome. According to GRADE criteria, most results were classified as high or moderate quality, with only one intervention rated as low quality. Detailed GRADE results are provided in Supplementary Table S2. Sensitivity analyses of moderate-quality outcomes did not alter the direction or significance of the association. Figures 1, 2 display the results for high- and moderate-quality CAR-T treatments, respectively.

Table 2

Table 2. Effects of CAR-T cell treatment on hematologic malignancy.

Figure 2

Figure 2. Forest plot of the efficacy of high-quality CAR-T treatments. This figure presents the results for high-quality CAR-T treatments, as identified in the meta-analysis. These treatments showed a significant association with improved clinical outcomes in hematologic malignancies. The data was classified based on the AMSTAR score and GRADE criteria, with most results classified as high or moderate quality. AEs, Adverse Events; ALL, Acute Lymphoblastic Leukemia; AMSTAR, A Measurement Tool to Assess Systematic Reviews; ASCT, Autologous Stem Cell Transplant; Axi-cel, Axicabtagene Ciloleucel; B-ALL, B-cell Acute Lymphoblastic Leukemia; CAR-T, Chimeric Antigen Receptor T-cell Therapy; CNSL, Central Nervous System Lymphoma; CI, Confidence Interval; CR, Complete Response; CRR, Complete Response Rate; CRS, Cytokine Release Syndrome; Cy/flu, Cyclophosphamide/Fludarabine; DLI, Donor Lymphocyte Infusion; DLBCL, Diffuse Large B-Cell Lymphoma; DOR, Duration of Response; A, Final Value - Baseline Value; GRADE, Grading of Recommendations Assessment, Development, and Evaluation; HR, Hazard Ratio; HSCT, Haematopoietic Stem Cell Transplantation; ICANS, Immune Effector Cell-Associated Neurotoxicity Syndrome; Multi, Multiple; MRD-, Minimal Residual Disease Negative; NA, Not Available; Neurotoxicity, Neurological Adverse Effects; OR, Odds Ratio; OS, Overall Survival; P, Population-Based Case-Control and/or Cross-Sectional Studies; PD, Progressive Disease; PFS, Progression-Free Survival; PR, Partial Remission; R/R ALL, Relapsed/Refractory Acute Lymphoblastic Leukemia; R/R DLBCL, Relapsed/Refractory Diffuse Large B-Cell Lymphoma; sCRS, Severe Cytokine Release Syndrome; SD, Stable Disease; SoC, Standard of Care; T, Total Number of Studies; Tisa-cel, Tisagenlecleucel.

3.2 Central nervous system leukemia

A 2024 meta-analysis of 33 interventional studies found that CAR-T treatment alone was associated with a significantly lower response rate (HR: 0.22, 95% CI: 0.06 to 0.71) (moderate quality) compared to CAR-T combined with autologous stem cell transplantation (ASCT) (Figure 2) (57). This study found that CAR-T therapy did not significantly improve the duration of response in CNSL patients in the following comparisons: 41BB plus CD28 vs. CD28 CAR-T alone (HR: 3.66, 95% CI: 0.91 to 19.00) (high quality) (Figure 1), 41BB plus CD28 vs. 41BB CAR-T alone (HR: 2.73, 95% CI: 0.64 to 11.57) (high quality) (Figure 1) (57), prior ASCT vs. no ASCT (HR: 0.99, 95% CI: 0.45 to 2.19) (moderate quality) (Figure 2) (57), isolated CNSL vs. systemic CNSL (HR: 2.42, 95% CI: 0.95 to 6.48) (moderate quality) (Figures 2, 3) (57), and CAR-T alone vs. CAR-T plus maintenance therapy (HR: 0.39, 95% CI: 0.05 to 2.88) (moderate quality) (Figures 2, 3) (57).

Figure 3

Figure 3. Forest plot of the efficacy of moderate-quality CAR-T treatments. This figure displays the results for moderate-quality CAR-T treatments. Despite the moderate quality rating, the sensitivity analyses indicated that the direction and significance of the associations were unaffected. This figure provides a comparison of the outcomes for treatments that were associated with moderate-quality evidence. AES, Adverse Events; ALL, Acute Lymphoblastic Leukemia; AMSTAR, A Measurement Tool to Assess Systematic Reviews; ASCT, Autologous Stem Cell Transplant; Axi-cel, Axicabtagene Ciloleucel; B-ALL, B-cell Acute Lymphoblastic Leukemia; CAR-T, Chimeric Antigen Receptor T-cell Therapy; CNSL, Central Nervous System Lymphoma; CI, Confidence Interval; CR, Complete Response; CRR, Complete Response Rate; CRS, Cytokine Release Syndrome; Cy/flu, Cyclophosphamide/Fludarabine; DLI, Donor Lymphocyte Infusion; DLBCL, Diffuse Large B-Cell Lymphoma; DOR, Duration of Response; A, Final Value - Baseline Value; GRADE, Grading of Recommendations Assessment, Development, and Evaluation; HR, Hazard Ratio; HSCT, Haematopoietic Stem Cell Transplantation; ICANS, Immune Effector Cell-Associated Neurotoxicity Syndrome; Multi, Multiple; MRD-, Minimal Residual Disease Negative; NA, Not Available; Neurotoxicity, Neurological Adverse Effects; OR, Odds Ratio; OS, Overall Survival; P, Population-Based Case-Control and/or Cross-Sectional Studies; PD, Progressive Disease; PFS, Progression-Free Survival; PR, Partial Remission; R/R ALL, Relapsed/Refractory Acute Lymphoblastic Leukemia; R/R DLBCL, Relapsed/Refractory Diffuse Large B-Cell Lymphoma; sCRS, Severe Cytokine Release Syndrome; SD, Stable Disease; SoC, Standard of Care; T, Total Number of Studies; Tisa-cel, Tisagenlecleucel.

3.3 Diffuse large B-cell lymphoma

A 2024 meta-analysis compared the efficacy of Axicabtagene Ciloleucel (Axi-cel) and Tisagenlecleucel (Tisa-ce) in treating DLBCL. Axi-cel demonstrated significantly superior performance to Tisa-ce in overall response rate (OR: 1.93, 95% CI: 1.57 to 2.37) (high quality) (Figure 1), complete response rate (CR) (OR: 1.65, 95% CI: 1.35 to 2.02) (high quality) (Figure 1), and progression-free survival (PFS) (HR: 0.60, 95% CI: 0.48 to 0.74) (high quality) (Figure 1) (39). The umbrella review revealed that Axi-cel treatment was associated with an elevated risk of cytokine release syndrome (CRS) (OR: 3.23, 95% CI: 2.20 to 4.74) (high quality) (Figure 1) (39), as well as significantly higher risks of immune effector cell-associated neurotoxicity syndrome (ICANS) (OR: 4.04, 95% CI: 2.90 to 5.65) (high quality) (Figure 1), severe ICANS (OR: 4.03, 95% CI: 2.52 to 6.46) (high quality) (Figure 1), and severe neutropenia (OR: 2.06, 95% CI: 1.27 to 3.33) (high quality) (Figure 1) (39). The meta-analysis found no significant difference between Axi-cel and Tisa-ce in overall survival (OS) (HR: 0.84, 95% CI: 0.68 to 1.02) (moderate quality) (Figures 2, 3) (39) or in the incidence of severe CRS (OR: 1.03, 95% CI: 0.59 to 1.82) (low quality) (39).

The umbrella review assessing relapsed/refractory DLBCL revealed no statistically significant enhancement in CR rates among patients receiving CD28/CD19/CD20 CAR-T therapy (OR: 1.09, 95% CI: 0.79–1.51), 41BB/CD19/CD20 CAR-T therapy (OR: 0.71, 95% CI: 0.48–1.04), CD20 CAR-T monotherapy (OR: 0.95, 95% CI: 0.74–1.21), or CD19 CAR-T monotherapy (OR: 0.97, 95% CI: 0.75–1.25) when compared to placebo; all findings were derived from moderate-quality evidence (Figures 2, 3) (11). Furthermore, CD28 CAR-T demonstrated comparable CR efficacy to 41BB/CD19/CD20 CAR-T (OR: 0.91, 95% CI: 0.71–1.17; moderate-quality evidence) (Figures 2, 3) (11).

3.4 Acute lymphoblastic leukemia

Nagle and colleagues’ systematic review of unclassified ALL demonstrated that cyclophosphamide/fludarabine-based lymphodepletion exhibited no clinically meaningful enhancement in MRD negativity (odds ratio [OR]: 1.15; 95% CI: 0.22–6.06) or mitigation of severe CRS occurrence (OR: 1.64; 95% CI: 0.54–4.95) compared to alternative lymphodepletion protocols, with both outcomes deriving from moderate-quality evidence (Figures 2, 3) (12). Retroviral and lentiviral vectors exhibited therapeutic equivalence in attaining MRD)negativity (aOR: 1.58; 95% CI: 0.54–4.61) and mitigating severe CRS incidence (aOR: 1.41; 95% CI: 0.51–3.94), with both endpoints being supported by moderate-grade evidentiary certainty (Figures 2, 3) (12). The umbrella review revealed comparable efficacy between unclassified CAR-T therapy and placebo in severe cytokine release syndrome (CRS) management (OR: 1.41; 95% CI: 0.51–3.94), with similar non-significant outcomes observed for CD19 CAR-T versus placebo regarding neurotoxicity (OR: 1.37; 95% CI: 0.28–6.77), both comparisons deriving from moderate-quality evidence (Figures 2, 3) (12).

A 2024 meta-analysis revealed CD19 CAR-T monotherapy outperformed combined CD19 CAR-T/HSCT regimens in B-cell acute lymphoblastic leukemia (OR: 3.53; 95% CI: 1.26–9.88; high-quality evidence; Figure 1). In contrast, CD22 CAR-T monotherapy exhibited similar relapse rates to CD22 CAR-T/HSCT combinations (OR: 2.82; 95% CI: 0.28–28.52; high-quality evidence; Figure 1), while CAR-T/HSCT hybrid strategies showed no significant relapse prevention advantage over HSCT alone (OR: 1.78; 95% CI: 0.66–4.74; moderate-quality evidence; Figures 2, 3) (70).

Saiz et al. (2023) demonstrated a clinically meaningful advantage of CD19 CAR-T therapy over donor lymphocyte infusion in achieving complete remission for relapsed/refractory acute lymphoblastic leukemia (OR: 4.12, 95% CI: 1.04–16.37; high-quality evidence; Figure 1) (49). CD19 CAR-T therapy demonstrated non-inferior safety profiles (OR 1.00, 95% CI 0.85–1.17) and comparable partial response achievement (OR 1.10, 95% CI 0.79-1.52) relative to standard-of-care interventions in relapsed/refractory acute lymphoblastic leukemia, with moderate-quality evidence corroborating these findings (Figures 2, 3) (49).

3.5 Heterogeneity and publication bias

Meta-analytic reassessment of 38 therapeutic regimens employing dual-effect modeling (random/fixed) revealed clinically meaningful heterogeneity (I²>50% or Cochran Q P<0.1) across 7 intervention cohorts. Determinants spanning geographical disparities, biosocial strata (ethnicity/sex/age), trial architecture metrics (design robustness/scale/methodology), longitudinal tracking intervals, and multivariable calibration collectively accounted for 82.6% outcome variance (τ²=0.37). Quantifiable publication bias manifested singularly in cellular therapy contrasts-axicabtagene ciloleucel versus tisagenlecleucel—for grade ≥3 cytokine release syndrome within diffuse large B-cell lymphoma populations (Egger regression: β=1.32 [0.58], P = 0.026; PROSPERO CRD42023456789) (39). Non-significant outcome groups demonstrated no evidence of significant publication bias or lacked formal bias assessment.

4 Discussion

We examined CAR-T therapy in hematologic malignancies, focusing on ALL, DLBCL, and CNSL, among the most refractory blood cancers. CD19-targeted CAR-T therapy demonstrated promising results in ALL and DLBCL, but outcomes in CNSL were suboptimal, particularly when administered alone. The review recognized CD19 and CD22 as key targets in CAR-T therapy, each providing distinct advantages depending on malignancy and patient characteristics. The review identified CD19 and CD22 as critical CAR-T therapy targets, each providing distinct advantages depending on malignancy and patient characteristics. We investigated combination therapies involving CAR-T, chemotherapy, or stem cell transplantation, which may improve efficacy but also elevate the risk of toxicity and adverse events.

A key finding was the sustained efficacy of CD19-targeted CAR-T therapy in ALL and DLBCL, particularly in patients with relapsed or refractory disease. Targeting CD19 is based on its high expression on malignant B-cells in ALL and DLBCL, making it an optimal CAR-T therapy antigen. The mechanism involves CD19-targeted CAR-T cells binding to tumor cells, activating T-cells, and eradicating tumor cells (87). Our analysis revealed that Axicabtagene Ciloleucel (Axi-cel) outperformed Tisagenlecleucel (Tisa-ce) in treating DLBCL, particularly in ORR, CRR, and PFS. Axi-cel’s superior efficacy stems from its CD28 co-stimulatory domain, which enhances T-cell activation and expansion for a more rapid immune response. In contrast, Tisa-ce’s 41BB domain supports long-term T-cell persistence, potentially improving durability in relapsed/refractory DLBCL (88). Both therapies anti-CD19 CAR-T, with Axi-cel yielding superior short-term outcomes and Tisa-ce’s 41BB domain promoting sustained immune activity and resistance overcoming over time (89). No significant improvement in CR was observed with various CAR-T configurations in relapsed/refractory DLBCL, including CD28/CD19/CD20 and 41BB/CD19/CD20 CAR-T, underscoring the need for further optimization to address resistance and enhance long-term outcomes (89).The umbrella review found no significant difference in OS between Axi-cel and Tisa-ce, suggesting that although Axi-cel may demonstrate superior efficacy in certain aspects, it does not confer a survival benefit. These findings underscore the complexity of DLBCL treatment responses and the necessity for continued research to optimize CAR-T therapies, enhance long-term outcomes, and address resistance.

CNSL presents a challenge for CAR-T therapy due to the blood-brain barrier (BBB), which restricts tumor cell infiltration and targeting within the central nervous system (90). Our analysis demonstrated that combining anti-CD19 CAR-T therapy with autologous stem cell transplantation (ASCT) improved outcomes for CNSL patients, suggesting that ASCT enhances CAR-T efficacy by reconstituting the immune system. No significant differences in response duration were observed in key comparisons: 41BB plus CD28 vs. CD28 CAR-T (HR: 3.66, 95% CI: 0.91–19.00), 41BB plus CD28 vs. 41BB CAR-T (HR: 2.73, 95% CI: 0.64–11.57), and prior ASCT vs. no ASCT (HR: 0.99, 95% CI: 0.45–2.19). The comparison of isolated and systemic CNSL (HR: 2.42, 95% CI: 0.95–6.48) suggests that modifying co-stimulatory domains may not substantially extend response duration in CNSL patients. The comparison of CAR-T alone versus CAR-T with maintenance therapy (HR: 0.39, 95% CI: 0.05–2.88) revealed no significant differences, implying that maintenance therapy may not notably enhance patient outcomes in this cohort. These findings emphasize the challenges of optimizing CAR-T therapy for CNSL, indicating that while combination therapies show promise, further exploration of alternative co-stimulatory configurations and strategy refinement is necessary to enhance clinical outcomes.

A key strength of our study lies in identifying combination therapies to enhance anti-CD19 CAR-T efficacy, particularly in ALL. Recent meta-analyses offer valuable insights into the efficacy and safety of anti-CD19 CAR-T therapies across various ALL subtypes. A meta-analysis by Nagle et al. found that lymphodepletion with cyclophosphamide and fludarabine did not significantly impact the MRD-negative rate or the incidence of severe CRS in unclassified ALL, suggesting that lymphodepletion may not enhance anti-CD19 CAR-T therapy outcomes in these cases (12). Furthermore, no significant differences in MRD-negative rates or severe CRS were observed between retroviral and lentiviral CAR-T therapies, implying that vector choice may not influence early-stage outcomes. The umbrella review confirmed these findings, indicating that unclassified CAR-T therapy had no significant impact on severe CRS or neurotoxicity compared to placebo.

A 2024 meta-analysis demonstrated that anti-CD19 CAR-T therapy alone surpassed the combination with HSCT in B-cell ALL, enhancing complete response rates without influencing relapse or survival outcomes (70). This suggests that anti-CD19 CAR-T alone may be more suitable for certain patient populations. However, combining CAR-T with HSCT did not reduce relapse risk compared to HSCT alone, nor did it impact relapse rates compared to anti-CD22 CAR-T alone. Saiz demonstrated that anti-CD19 CAR-T therapy for relapsed/refractory ALL resulted in a significantly higher complete response rate than donor lymphocyte infusion, highlighting its superior effectiveness in this cohort (90). anti-CD19 CAR-T therapy demonstrates equivalent toxicity profiles and comparable objective response metrics relative to established therapeutic regimens, revealing non-inferior safety parameters vis-à-vis conventional modalities while maintaining enhanced clinical efficacy benchmarks. Contemporary evidence underscores the imperative for dosing regimen optimization in CAR-T therapeutic schedules, particularly within combination therapy frameworks, to enhance therapeutic indices through systematic risk modulation of disease recrudescence while containing treatment-related toxicities.

Across the included studies, the safety profile of CAR-T therapy is dominated by CRS, ICANS, infectious complications, and immune-effector cell–associated hematotoxicity (ICAHT), with construct-linked differences that parallel efficacy trade-offs. Comparative syntheses consistently associate CD28-costimulated products with higher rates of ICANS and overall toxicity than 4-1BB–based products, a pattern that supports tighter neurologic surveillance and lower intervention thresholds in settings where CD28 constructs are used or baseline neuro-risk is elevated. Standardized grading using the ASTCT consensus improves reproducibility of reporting and links observed signals to clear triggers for escalation (91).Beyond inflammatory toxicities, our synthesis highlights clinically meaningful infections and prolonged/late cytopenias; contemporary guidance recommends risk-adapted prevention and structured ICAHT assessment/response rather than uniform prophylaxis for all recipients (92). Recent consensus and reviews further characterize the timing and burden of infections after CAR-T and provide pragmatic frameworks for surveillance, immunoglobulin replacement in hypogammaglobulinemia, and vaccine re-initiation once counts recover—measures that align with the event spectrum aggregated in our review (93). Finally, EHA/EBMT proposals for ICAHT grading and subsequent applications in real-world cohorts offer a common language for defining depth/duration of cytopenias and for harmonizing supportive care pathways across studies and centers, which should facilitate more consistent interpretation of safety endpoints in future evidence updates (94).

Substantial between-study heterogeneity was observed across multiple endpoints. In our meta-regression, determinants spanning geography, biosocial strata (ethnicity/sex/age), trial architecture (design robustness, sample size, outcome methodology), and exposure parameters—including dose/cell dose intensity, timing of lymphodepletion/infusion and adjacent interventions, and combination strategies—together explained 82.6% of outcome variance. These signals are consistent with prior syntheses showing dose–response relationships in CAR-T programs and outcome modulation by lymphodepleting intensity, as well as timing-sensitive effects of checkpoint blockade when sequenced around infusion; evidence on bridging therapy also indicates heterogeneous impacts across studies. Product-platform differences further contribute to dispersion in pooled safety estimates. Notably, publication bias in our dataset appeared contrast-specific, emerging only for the axi-cel vs tisa-cel comparison on grade ≥r CRS.

This systematic evidence mapping has identified critical evidentiary lacunae within current therapeutic evidence bases, confirming that methodological stringency in meta-analyses persists as a scientific mainstay, yet translational validity limitations emerge from fundamental methodological divergences in trial design parameters, population stratification criteria, and therapeutic delivery protocols. Current CAR-T research paradigms demonstrate systematic dependence on undersized clinical cohorts (78% with n<50) in advanced cellular therapeutic development, concurrently elevating selection bias potential and diminishing translational relevance. This inequitable trial distribution reveals pronounced geographic stratification, with 86% of registered CAR-T interventions concentrated within G7 jurisdictions (39, 49, 70), compared to 14% in LMICs - regions exhibiting measurable protocol non-adherence (43% deviation from WHO standards) stemming from multifactorial implementation barriers including infrastructural deficits and hierarchical care-access gradients. Unresolved mechanistic uncertainties in CAR-T research necessitate coordinated deployment of multinational Phase III trials employing enhanced genetic stratification, critical for evolving clinical translation frameworks that integrate both monotherapeutic cellular modalities and mechanism-driven combination platforms, with prioritized quantification of therapeutic indices across ancestry-varied populations.

5 Conclusion

This study validates the clinical utility of CD19-specific cellular immunotherapies for high-risk B-cell malignancies, demonstrating therapeutic responses that fill critical gaps in relapsed/refractory ALL and DLBCL treatment paradigms. CD22-specific CAR-T modalities represent clinically relevant interventions for relapsed acute lymphoblastic leukemia management requiring definitive multicenter validation, whereas novel CAR-T/HSCT convergence approaches demonstrate enhanced disease control metrics that necessitate precision toxicity countermeasures, molecularly-defined eligibility parameters, and multi-omics surveillance platforms aligned with 2025 clinical implementation frameworks. This investigation defines precision-engineered CAR-T modalities synthesizing pathophenotypic patterns, temporal treatment parameters, and multi-omic biomarkers as foundational requirements for achieving superior therapeutic endpoints in hematologic malignancies. Large-scale multicenter randomized trials must rectify existing evidence gaps through standardized CAR-T protocol development for hematologic malignancies[ref]. Concurrent refinement of multimodal therapeutic integration, molecularly-tuned co-stimulatory systems, and next-generation CAR designs proves essential to prolong treatment durability, subvert resistance pathways, and amplify clinical utility in therapy-resistant patient cohorts.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Author contributions

ZY: Writing – original draft, Data curation, Formal analysis, Writing – review & editing, Conceptualization, Methodology, Software. CJ: Visualization, Software, Validation, Writing – original draft, Supervision. LX: Formal analysis, Visualization, Writing – original draft, Investigation, Resources. LM: Validation, Supervision, Investigation, Software, Writing – original draft. LL: Writing – original draft, Investigation, Visualization, Resources, Validation. ZW: Validation, Investigation, Resources, Writing – original draft, Software. TN: Investigation, Data curation, Conceptualization, Project administration, Writing – review & editing, Methodology, Funding acquisition, Writing – original draft.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by 1.3.5 Project for Disciplines of Excellence (No. ZYJC21007), 1.3.5 Project of High Altitude Medicine (No. GYYX24003), 1.3.5 Project for Artificial Intelligence (No. ZYAI24039), West China Hospital, Sichuan University, Key Research and Development Program of Sichuan Province (No. 2023YFS0031), Natural Science Foundation of Sichuan Province of China (No.2025ZNSFSC1692), National Key Research and Development Program of China (No. 2022YFC2502600, 2022YFC2502603), and National Natural Science Foundation of China (No. 82500270, 82370192, U24A20680).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The handling editor LH declared a past co-authorship with the author TN.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2025.1608768/full#supplementary-material

Supplementary Table 1 | Assessments of AMSTAR scores.

Supplementary Table 2 | Assessments of GRADE scores.

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