The Center for International Blood & Marrow Transplant Research, or CIBMTR, is a research facility that focuses on hematopoietic cell transplantation and cellular therapy research. The center operates a combined research program of the National Marrow Donor Program and the Medical College of Wisconsin.
Abstract Background Ciltacabtagene autoleucel (cilta‐cel), an anti–B‐cell maturation antigen (BCMA) chimeric antigen receptor T‐cell (CAR‐T) therapy, is approved for relapsed/refractory multiple myeloma (RRMM). Methods Using the Center for International Blood and Marrow Transplant Research registry, this study evaluated outcomes of frail patients receiving commercial cilta‐cel from March 2022 to December 2023. Frailty was defined by an adapted simplified score incorporating age, performance status, and comorbidities. Results Among 541 patients with available frailty status, 183 (33.8%) were frail and 358 (66.2%) were nonfrail. Overall response rates were comparable (frail 82.8% vs. nonfrail 88.5%). However, frail patients had inferior progression‐free survival (PFS) (12‐month PFS, 62.7% [95% confidence interval (CI), 53.6%–71.3%] vs. 75.9% [95% CI, 70.4%–81.1%]; p < .01) and overall survival (OS) (12‐month OS 72.8% [95% CI, 64.9%–80.0%] vs. 90.4% [95% CI, 86.6%–93.7%]; p < .01). Twelve‐month treatment‐related mortality in frail patients was 6.8% (95% CI, 3.4%–11.2%) versus 3.6% (95% CI, 1.8%–6.1%), p = .12. Cytokine release syndrome (grade ≥2) occurred in 22.4% of frail versus 17.9% of nonfrail patients ( p = .05), and immune effector cell–associated neurotoxicity (ICANS) of any grade was reported in 32.2% versus 17.6% ( p < .01). Rates of cranial nerve palsies and Parkinsonism were comparable. Prolonged cytopenia (>day 30) was more common in frail patients (30.6% vs. 21.2%; p < .01). On multivariable analysis, frailty independently predicted worse PFS (hazard ratio [HR], 1.67; 95% CI, 1.16–2.40), OS (HR, 2.46; 95% CI, 1.57–3.87), and higher odds of any‐grade ICANS (odds ratio, 2.01; 95% CI, 1.32–3.08) (all p < .01). Conclusions Cilta‐cel remains effective in frail RRMM, but frailty is associated with reduced survival and increased toxicity, supporting tailored CAR‐T strategies.
Chimeric antigen receptor T cell (CAR-T) therapy is being increasingly used as a cutting-edge treatment for blood cancers. Although the number of scientific articles focused on its outcomes is increasing, there is limited literature providing guidance on appropriate statistical analysis methods for CAR-T therapy studies. Statistical approaches applied to CAR-T therapy outcome analysis often use methods adopted from hematopoietic cell transplantation (HCT); however, there are important differences between these therapies that must be accounted for in the outcomes analysis. Additionally, much of the literature on CAR-T therapy outcomes is focused on clinical trials, which differ from real-world settings in the long-term follow-up of these patients. There are some statistical challenges in analyzing CAR-T therapy data, such as defining patients' response to therapy and quantifying the duration of response. Although some outcomes, such as overall survival and treatment-related mortality, are seen in both HCT and CAR-T therapy studies, some post-therapy complications are unique to CAR-T cell therapies, and their statistical analysis should be given careful consideration. Other challenges include establishing the appropriate time origin for each outcome, determining censoring time, and defining competing risks. Here we propose to define common CAR-T therapy outcomes, describe appropriate statistical approaches for their analyses, and address these critical statistical challenges based on the observational data collected by the Center for International Blood and Marrow Transplant Research. We used observational data to illustrate these statistical methods for analyzing CAR-T therapy outcomes. © 2026 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.
ABSTRACT:The benefit of extended phased (∼) HLA class I∼class III∼class II haplotypes in reducing the mortality after hematopoietic cell transplantation is unknown and requires information on functional class III variation. We identified a robust class III single-nucleotide polymorphism (SNP), rs915654, informative for mortality and relapse in 1436 patients and their haploidentical related donors through multivariable regression analysis of 26 candidate class III SNPs. Three-marker haplotypes, as defined by 1 class I locus, 1 class II locus, and rs915654 were determined in patients separately from donors. Inclusion of rs915654 into relapse and mortality models already containing patient HLA-E∼DRB1 and donor HLA-B∼DRB1 improved each model (likelihood ratio test P = .06 and P = .004, respectively, for relapse; P = .10 and P = .01, respectively, for mortality). The risks of mortality and relapse increased with decreasing numbers of favorable patient and donor markers. Retesting in an independent cohort of 1141 haploidentical transplants yielded similar results. The number of unfavorable markers additionally increased nonrelapse mortality. HLA-A∼C∼B∼DRB1∼DQB1 haplotypes were defined according to their expected numbers of favorable markers, and the theoretical utility for selecting donors was explored. In summary, extended HLA class I∼class III∼class II haplotypes influence the success of transplantation and inform the biology of the major histocompatibility complex in health and disease. The selection of haploidentical donors for future patients may be optimized with knowledge of donor HLA haplotypes.
BACKGROUND:Large population-based databases are increasingly used to study access to hematopoietic cell transplantation (HCT) and chimeric antigen receptor T-cell (CAR-T) therapy. METHODS:We conducted a systematic scoping review of studies using US databases (1/2008-2/2025) to examine access to HCT or CAR-T therapy for hematologic malignancies to identify limitations and explain differences in reported disparities. RESULTS:Thirty-five studies met inclusion criteria, and 46% used linked databases. Across data sources, older age, racial and ethnic minoritized status, lower neighborhood socioeconomic status, and non-private insurance were associated with lower likelihood of HCT and CAR-T receipt. However, disparities varied substantially by databases due to differences in eligible populations, data availability, and ability to identify treatment candidacy. CONCLUSION:No single database adequately characterizes disparities in access to cellular therapies. Equity-focused research requires deliberate alignment of research questions with database strengths and greater investment in data standardization and inclusion of social determinants of health.
