Current Activity Trends and Outcomes in Hematopoietic Cell Transplantation and Cellular Therapy – A report from the CIBMTR

Stephen R Spellman; Ke Xu; Temitope Oloyede; Kwang Woo Ahn; Othman Akhtar; Yung-Tsi Bolon; Larisa Broglie; Jenni Bloomquist; Caitrin Bupp; Min Chen; Steven M Devine; Najla El-Jurdi; Mehdi Hamadani; Mary Hengen; Anna H Huppler; Samantha Jaglowski; Michelle Kuxhausen; Stephanie J Lee; Amy Moskop; Kristin M Page; Marcelo Pasquini; Waleska Perez; Rachel Phelan; Doug Rizzo; Wael Saber; Heather Stefanski; Patricia Steinert; Eileen Tuschl; Alexis Visotcky; Rebecca Vogel; Jeffery J Auletta; Bronwen E Shaw; Mariam Allbee-Johnson

doi:10.1016/j.jtct.2025.05.014

. Author manuscript; available in PMC: 2026 May 19.

Published in final edited form as: Transplant Cell Ther. 2025 May 19;31(8):505–532. doi: 10.1016/j.jtct.2025.05.014

Current Activity Trends and Outcomes in Hematopoietic Cell Transplantation and Cellular Therapy – A report from the CIBMTR

Stephen R Spellman ¹, Ke Xu ², Temitope Oloyede ², Kwang Woo Ahn ², Othman Akhtar ², Yung-Tsi Bolon ¹, Larisa Broglie ^2,³, Jenni Bloomquist ¹, Caitrin Bupp ¹, Min Chen ², Steven M Devine ¹, Najla El-Jurdi ^2,⁴, Mehdi Hamadani ^2,⁵, Mary Hengen ¹, Anna H Huppler ², Samantha Jaglowski ², Michelle Kuxhausen ¹, Stephanie J Lee ^2,⁶, Amy Moskop ^2,⁴, Kristin M Page ², Marcelo Pasquini ², Waleska Perez ², Rachel Phelan ^2,⁴, Doug Rizzo ², Wael Saber ², Heather Stefanski ¹, Patricia Steinert ², Eileen Tuschl ², Alexis Visotcky ², Rebecca Vogel ², Jeffery J Auletta ^1,⁷, Bronwen E Shaw ², Mariam Allbee-Johnson ²

PMCID: PMC12302970 NIHMSID: NIHMS2094936 PMID: 40398621

Abstract

The Center for International Blood and Marrow Transplant Research (CIBMTR) compiles annual summary slides describing trends in hematopoietic cell transplantation (HCT) and cellular therapy (CT) practice and outcomes. This year’s report includes all patients receiving their first autologous and/or allogeneic HCT/CT in the United States between 2013 and 2023 or chimeric antigen receptor T-cell (CAR-T) from 2016 and 2023, reported to CIBMTR. Relative proportion of allogeneic and autologous HCT/CT was generated as percentage of total for donor type and for patient age, disease indication, graft-versus-host disease (GVHD) prophylaxis, and race and ethnicity. Causes of death were summarized using frequencies, and the Kaplan-Meier estimator was used for estimating overall survival. New for this year, disease risk stratification reflects European LeukemiaNet cytogenetic risk score for acute myeloid leukemia (AML) and the Revised International Prognostic Scoring System for myelodysplastic syndromes (MDS).

Use of allogeneic HCT increased substantially in 2023, recovering from a decline in activity during the COVID-19 pandemic, with growth predominately in the 65–74 year-old age group. Overall, matched unrelated donors (MUD) continue as the most common allogeneic donor source (45%) followed by haploidentical related donors (Haplo) (21%), matched related donors (MRD) (18%), mismatched unrelated donors (MMUD) (12%) and cord blood (Cord) (3%). These trends hold in the adult patient population with a notable doubling of MMUD utilization since 2020 driven by the rapid shift to post-transplant cyclophosphamide based GVHD prophylaxis (PTCy) in this setting. In the pediatric setting, Haplo was the most common donor source surpassing MRD use in 2023 followed by MUD, Cord and MMUD. Autologous HCT continued to decline slightly while use of CAR-T therapy has rapidly increased since commercial approval in 2017 with lymphoma and multiple myeloma reaching 45% and 16%, respectively in 2023.

Significant recent changes in GVHD prophylaxis in the adult allogeneic HCT setting have occurred. PTCy is most common in Haplo HCT with >90% since 2016. Among other donor sources, the most rapid adoption is in MMUD HCT at 82% in 2023. In MRD and MUD, PTCy use differs by conditioning intensity with RIC/NMA higher (58% and 64%, respectively), reflecting the standard of care established by BMT CTN 1703, compared to MAC (43% and 46%, respectively). In pediatrics, calcineurin inhibitor +/− others remains the most common GVHD prevention strategy for MRD (88%) and MUD (68%). Although common in the pediatric Haplo HCT setting at 68% in 2023, use of PTCy is less common across other mismatched donor types where use of abatacept or ex-vivo T cell depletion/CD34 selection accounts for 28% and 17% in MMUD, respectively.

Three-year overall survival continues to significantly improve among patients receiving allogeneic (62.1% vs 55.8%) and autologous (82.6% vs 79.6%) HCT when comparing HCT from 2017–2022 versus 2012–2016 (p<0.001), respectively. In both the adult and pediatric settings, primary cause of mortality after 100 days post-HCT remains primary disease in both allogeneic (47% and 45%, respectively) and autologous (60% and 79%, respectively). HCT/CT and CAR-T use continues to grow. Relapse remains the primary cause of death in the malignant setting supporting further efforts to mitigate risk.

Figure 1. — The annual numbers of 1^st allogeneic and 1^st autologous transplants and first CAR-T therapy in the US were compiled according to the number of first transplants or CAR-T for recipients registered with the CIBMTR.

Figure 2. — Upon further stratifying the number of 1^st allogeneic transplants in the US by donor type, matched unrelated donor (MUD) transplants represent the largest group, which continues to grow. The number of matched related donor (MRD) transplants has been decreasing for several years. The number of haplo procedures surpassed matched related donor (MRD) transplants in 2020 but declined in 2022 before increasing again in 2023. There is steady growth in mismatched unrelated donor (MMUD) transplants since 2020.

Figure 3. — This figure shows the relative proportion of 1^st allogeneic transplants performed by donor type annually, 2013–2023. The percentage of each is represented on the bar graph.

Figure 4. — This is a subset of the previous slide, looking specifically at adult patients. The trends of donor type used for adult patients reflect the general overall trends on the previous slide.

Figure 5. — In pediatric 1^st allogeneic transplants (recipients younger than 18), haploidentical related donor (Haplo) transplants represent the largest donor group, followed by matched related donor (MRD) and matched unrelated (MUD) donors. Haplo transplants show steady increases over the last 10 years, while the number of cord blood donor (UCB) transplants shows steady decreases. The use of MMUD has varied over time, with increases since 2020.

Figure 6. — Haplo donor use is increasing in pediatric recipients across all indications, most notably in ALL.

Figure 7. — This figure shows the relative proportion of 1^st allogeneic transplants by donor type performed for different recipient age groupings, 2019–2023. The percentage of each is represented on the bar graph.

Figure 8. — This figure shows the relative proportion of recipient age groups for 1^st allogeneic HCT recipients, 2013–2023. The percentage of each is represented on the bar graph. The percentage of recipients younger than 40 remains relatively constant. The percentage of patients aged 65 and older is increasing substantially over time.

Figure 9. — This figure shows the relative proportion of recipient age groups for 1^st autologous HCT recipients, 2013–2023. The percentage of each is represented on the bar graph.

Figure 10. — This figure shows the relative proportion of 1^st allogeneic transplants performed by Hematopoietic Cell Transplantation Comorbidity Index group (HCT-CI) in the different age groups between 2019–2023.

Figure 11. — The percentage of 1^st allogeneic recipients by Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI) index group receiving myeloablative (MAC) or non-myeloablative/reduced-intensity conditioning (NMA/RIC), 2019–2023. There were a higher percentage of HCT-CI = 3–4 and HCT-CI = 5+ in the NMA/RIC group.

Figure 12. — This figure shows the number of 1^st allogeneic procedures by graft source in adult patients since 2013. Peripheral blood stem cells (PBSC) represents the largest graft source consistently by year.

Figure 13. — This figure shows the number of 1^st allogeneic procedures by graft sources among pediatric recipients, 2013–2023. Bone marrow (BM) represents the largest graft source consistently each year.

Figure 14. — While calcineurin inhibitor (CNI) based graft-versus-host disease (GVHD) prophylaxis remains the most commonly used approach in adult matched related donor (MRD) recipients in the MAC setting, the use of post-transplant cyclophosphamide (PTCy) continues to increase, especially in recent years.

Figure 15. — The use of post-transplant cyclophosphamide (PTCy) became the most common GVHD prophylaxis approach in the reduced intensity/non-myeloablative (RIC/NMA) setting in 2023.

Figure 16. — While calcineurin inhibitor (CNI) -based GVHD prophylaxis remains the most commonly used in adult matched unrelated donor recipients in the myeloablative conditioning (MAC) setting, the use of post-transplant cyclophosphamide (PTCy) continues to increase, especially in recent years.

Figure 17. — The use of post-transplant cyclophosphamide (PTCy) became the most common GVHD prophylaxis approach in the reduced intensity/non-myeloablative (RIC/NMA) setting in 2023.

Figure 18. — GVHD prophylaxis for adults receiving haplo donor HCT is almost exclusively with PTCy.

Figure 19. — Since 2019, GVHD prophylaxis for adults receiving MMUD HCT with PTCy is > 50%, and this continues to increase.

Figure 20. — CNI and MMF is the most common GVHD prophylaxis group within the PTCy GVHD prophylaxis setting for adults in 2023.

Figure 21. — CNI-based GVHD prophylaxis remains the most commonly used in pediatric matched related donor recipients using myeloablative conditioning (MAC).

Figure 22. — CNI-based GVHD prophylaxis remains the most commonly used in pediatric MRD recipients using reduced intensity/non-myeloablative (RIC/NMA) conditioning. There is a notable increase in the use of abatacept since 2020.

Figure 23. — CNI-based GVHD prophylaxis remains the most commonly used in pediatric MUD recipients using myeloablative conditioning (MAC). There is a notable increase in the use of abatacept since 2020.

Figure 24. — CNI-based GVHD prophylaxis remains the most commonly used in pediatric matched unrelated donor (MUD) recipients using reduced intensity/non-myeloablative (RIC/NMA) conditioning. There is a notable increase in the use of abatacept since 2020.

Figure 25. — GVHD prophylaxis for pediatric patients receiving haplo donor HCT is predominantly with PTCy, though ex-vivo T-cell depletion is also used commonly. The use of CD34 selection has significantly decreased, particularly after 2016.

Figure 26. — GVHD prophylaxis has become quite variable in recent years in the pediatric MMUD transplant setting. There is a notable increase in the use of abatacept and PTCy based approaches since 2020.

Figure 27. — The most common indications are AML for 1^st allogeneic HCT and MM/PCD for 1^st autologous HCT in the US in 2023 for adult patients. 22 gene therapies for other non-malignant disease were reported for treatment of sickle cell disease, thalassemia and Scheie syndrome.

Figure 28. — The most common treatment type for multiple myeloma is autologous HCT, accounting for majority of the cases with an increase in the use of CAR-T therapies seen since 2021.

Figure 29. — The most common treatment type for lymphoma remains autologous HCT although this has substantially decreased since 2018, following the increase in the number of CAR-T therapies. The percentage of allogeneic HCT remains approximately stable.

Figure 30. — The most common indications are ALL for 1^st allogeneic HCT and neuroblastoma for 1^st autologous HCT in the US in 2023 for pediatric patients. A total of 22 gene therapies were reported for treatment of primary immune deficiency, sickle cell disease, thalassemia and other non-malignant disease.

Figure 31. — Diffuse large B-cell lymphoma is the most common indication among patients receiving CAR-T, increasing in number from 2016 to 2023.

Figure 32. — The percentage of patients receiving CAR-T with no prior HCT increased from 2016 to 2021 but remains approximately stable thereafter.

Figure 33. — The percentage of patients receiving 1^st alloHCT with no prior CAR-T decreased in 2019 but remains approximately stable thereafter.

Figure 34. — Large B Cell Lymphoma (LBCL) was the most common commercial CAR-T cell indication during 2016–2023, accounting for 56% of all cases. LBCL was also the most common non-commercial CAR-T cell indication during 2016–2023, accounting for 35% of all cases for the same time interval.

Figure 35. — Number of commercial CAR-T cell product by disease, 2016–2023. Axicabtagene ciloleucel accounts for 82% of follicular lymphoma cases, and Brexucabtagene autoleucel accounts for 98% of mantle cell lymphoma cases.

Figure 36. — Approximately half of deaths for recipients of 1^st allogeneic transplants are due to disease relapse after 100 days, in both adults and pediatric patients. Within the first 100 days, disease relapse, organ failure, and infection are the three most common causes of death.

Figure 37. — The primary cause of death for recipients of 1^st autologous transplants is disease relapse, though organ failure and infection are common in the first 100 days

Figure 38. — This figure shows a breakdown of commonly used conditioning regimens for myeloablative (MAC) and reduced-intensity/non-myeloablative (RIC/NMA) conditioning in adult patients with acute myeloid leukemia (AML) or myelodysplastic syndromes/myeloproliferative neoplasms (MDS/MPN). MAC: regimens with total body irradiation doses of ≥500 cGY, single fractionated doses of ≥ 800 cGY, busulfan doses of > 9mg/kg oral or Bu ≥ 7.2 mg/kg IV, or melphalan doses of >150 mg/m² given as single agents or in combination with other drugs¹. RIC/NMA: regimens with lower doses of total body irradiation, fractionated radiation therapy, busulfan, and melphalan than those used to define a MAC (above)².

Figure 39. — This slide shows a breakdown of commonly used conditioning regimens for MAC and RIC/NMA conditioning in adult patients with ALL.

Figure 40. — Percentage of center-reported race and ethnicity for 1^st allogeneic HCT recipients, 2013–2023.

Figure 41. — Percentage of donor type for 1^st allogeneic HCT recipients by race and ethnicity.

Figure 42. — Percentage of center-reported recipient race and ethnicity for 1^st autologous HCT recipients, 2013–2023.

Figure 43. — Percentage of center-reported recipient by race and ethnicity for 1^st autologous HCT recipients, 2013–2023

Figure 44. — Percentage of center-reported recipient by race and ethnicity for 1^st autologous HCT recipients, 2013–2023.

Figure 45. — The percentage of patient center-reported by race and ethnicity for commercial CAR-T cell product types.

Figure 46. — The percentage of patient center-reported data for adults by race and ethnicity for commercial CAR-T cell product types.

Figure 47. — The percentage of patient center-reported data for pediatrics by race and ethnicity for commercial CAR-T cell product types.

Figure 48. — Among the 144,996 patients receiving 1^st allogeneic HCT in US during 2002–2022, the 3-year probabilities (95% CI) of survival after allogeneic HCT during 2002–2022 in US are: 2017–2022 62.1% (61.7–62.6%); 2012–2016 55.8% (55.3–56.2%); 2007–2011 50.2% (49.7–50.8%) and 2002–2006 45.3% (44.7–46.0%). Two-group comparison: 2017–2022 vs 2012–2016 p-value: <.0001. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 49. — Among the 188,693 patients receiving 1^st autologous HCT in US during 2002–2022, the 3-year probabilities (95% CI) of survival after autologous HCT during 2002–2022 in US are: 2017–2022 82.6% (82.2–82.9%); 2012–2016 79.6% (79.3–80.0%); 2007–2011 76.1% (75.7–76.6%) and 2002–2006 66.9% (66.3–67.5%). Two-group comparison: 2017–2022 vs 2012–2016 p-value: <.0001. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 50. — Among 3,648 adult patients with AML receiving MRD transplant during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to ELN cytogenetic risk score are: Normal 67.1% (58.6–76.8%); Favorable 71.3% (68.1–74.6%); Intermediate 65.2% (62.3–68.2%) and Poor 49.5% (47.0–52.2%). Two-group comparison p-values: MRD Normal vs Favorable p-value: 0.4500; MRD Normal vs Intermediate p-value: 0.5381; MRD Normal vs Poor p-value: 0.0004. Among 8,022 adult patients with AML receiving MUD transplant during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to ELN cytogenetic risk score are: Normal 60.7% (55.0–67.0%); Favorable 67.8% (65.5–70.1%); Intermediate 62.0% (59.9–64.2%) and Poor 48.2% (46.5–50.0%). Two-group comparisons: MUD Normal vs Favorable p-value: 0.0052; MUD Normal vs Intermediate p-value: 0.3227 and MUD Normal vs Poor p-value: 0.0004. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 51. — Among 3,261 adult patients with AML receiving haplo donor transplant during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to ELN cytogenetic risk score are: Normal 65.3% (56.4–75.7%); Favorable 70.1% (66.6–73.7%); Intermediate 61.9% (58.6–65.3%) and Poor 46.0% (43.4–48.8%). Two-group comparisons: Haplo Normal vs Favorable p-value: 0.1278; Haplo Normal vs Intermediate p-value: 0.9378 and Haplo Normal vs Poor p-value: 0.0019. Among 1,157 adult patients with AML receiving MMUD transplant during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to ELN cytogenetic risk score are: Normal 69.4% (56.7–84.9%); Favorable 68.7% (62.4–75.7%); Intermediate 60.3% (54.9–66.1%) and Poor 43.7% (39.2–48.8%). Two-group comparisons: MMUD Normal vs Favorable p-value: 0.9542; MMUD Normal vs Intermediate p-value: 0.3206 and MMUD Normal vs Poor p-value: 0.0029. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 52. — Among 1,302 pediatric patients with AML receiving 1^st allogeneic transplant during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to ELN cytogenetic risk score are: Normal 72.1% (62.2–83.6%); Favorable 72.3% (66.6–78.6%); Intermediate 68.4% (63.0–74.4%) and Poor 65.0% (61.3–69.0%). Two-group comparisons: Normal vs Favorable p-value: 0.9645; Normal vs Intermediate p-value: 0.4114 and Normal vs Poor p-value: 0.0769. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 53. — Among 973 patients with a MRD allotransplants performed during 2017–2022 in recipients with early and advanced disease MDS, the 3-year probabilities (95% CI) of survival following transplant according to IPSS-R Score are: Very low 69.0% (61.2–77.7%); Low 69.0% (62.9–75.6%); Intermediate 51.9% (46.1–58.5%); High 48.8% (41.8–56.9%) and Very high 27.2% (20.6–35.9%). Two-group comparisons: MRD Very low vs Low p-value: 0.7932; MRD Very low vs Intermediate p-value: 0.0010; MRD Very low vs High p-value: 0.0001 and MRD Very low vs Very high p-value: <.0001. The 3-year probabilities (95% CI) of survival following transplant among 2,886 patients with a MUD according to IPSS-R Score are: Very low 64.2% (59.3–69.5%); Low 59.9% (56.3–63.7%); Intermediate 47.3% (43.8–51.1%); High 43.9% (39.7–48.6%) and Very high 34.4% (29.6–40.0%). Two-group comparisons: MUD Very low vs Low p-value: 0.0947; MUD Very low vs Intermediate p-value: <.0001; MUD Very low vs High p-value: <.0001and MUD Very low vs Very high p-value: <.0001. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 54. — Among 876 adult patients with a donor receiving 1^st transplant for early and advanced MDS performed during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to IPSS-R Score are: Very low 54.1% (44.8–65.2%); Low 57.7% (51.4–64.7%); Intermediate 39.2% (33.2–46.2%); High 36.7% (29.7–45.4%) and Very high 25.7% (18.6–35.4%). Two-group comparisons: Haplo Very low vs Low p-value: 0.4785; Haplo Very low vs Intermediate p-value: 0.0102; Haplo Very low vs High p-value: 0.0030 and Haplo Very low vs Very high p-value: <.0001. Among 332 adult patients with a MMUD, the 3-year probabilities (95% CI) of survival following transplant according to IPSS-R Score are: Very low 66.4% (54.5–81.0%); Low 61.2% (50.9–73.5%); Intermediate 46.7% (36.7–59.5%); High 27.6% (17.1–44.5%) and Very high 40.3% (28.3–57.6%). Two-group comparisons: MMUD Very low vs Low p-value: 0.9953; MMUD Very low vs Intermediate p-value: 0.1128; MMUD Very low vs High p-value: 0.0030 and MMUD Very low vs Very high p-value: 0.0223. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 55. — Among 740 adult patients with a matched related donor, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Myelofibrosis 67.4% (62.9–72.3%) and Other MPN 59.3% (53.8–65.4%). Among 1,877 adult patients with a matched unrelated donor, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Myelofibrosis 59.1% (56.0–62.5%) and Other MPN 53.0% (49.4–56.7%). Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 56. — Among 566 adult patients with a Haplo donor, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Myelofibrosis 58.7% (53.0–65.0%) and Other MPN 55.7% (49.9–62.2%). Among 233 adult patients with a mismatched unrelated donor, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Myelofibrosis 54.5% (45.4–65.4%) and Other MPN 46.2% (36.5–58.5%). Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 57. — Among 1,607 adult patients with a matched related donor (MRD), the 3-year probabilities (95% CI) of survival following transplant according to disease status are: CR1 72.2% (69.5–75.0%); CR2+ (2nd or subsequent complete remission); 54.9% (49.5–60.8%) and Relapse/never in CR (includes primary induction failure) 55.1% (43.3–70.1%). Two-group comparisons: MRD CR1 vs CR2+ p-value: <.0001 and MRD CR2+ vs Rel p-value: 0.5301. Among the 2,305 adult recipients of matched unrelated donor (MUD), the 3-year probabilities (95% CI) of survival following transplant according to disease status are: CR1 68.5% (66.2–70.8%); CR2+ (2nd or subsequent complete remission) 55.7% (51.2–60.7%) and Relapse/never in CR (includes primary induction failure) 36.6% (27.7–48.5%). Two-group comparisons: MUD CR1 vs CR2+ p-value: <.0001 and MUD CR2+ vs Rel p-value: 0.0006. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 58. — Among 1,395 adult patients receiving a haplo donor transplant for ALL during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: CR1 72.5% (69.5–75.6%); CR2+ (2nd or subsequent complete remission) 50.8% (45.7–56.4%) and Relapse/never in CR (includes primary induction failure) 38.8% (27.4–54.9%). Two-group comparisons: CR1 vs CR2+ p-value: <.0001 and CR2+ vs Rel p-value: 0.0211. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 59. — Among 1,696 pediatric patients receiving 1^st allogeneic transplant for ALL during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: CR1 80.5% (77.2–84.0%); CR2+ (2nd or subsequent complete remission) 71.9% (69.2–74.8%) and Relapse/never in CR (includes primary induction failure) 66.0% (52.0–83.7%). Two-group comparisons: CR1 vs CR2+ p-value: 0.0003 and CR2+ vs Rel p-value: 0.1628. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 60. — Allogeneic HCT is the treatment of choice for young patients with severe aplastic anemia (SAA) who have an HLA-matched related donor (MRD). Among 810 pediatric patients who underwent transplantation for SAA during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according by donor type are: MRD 98.2% (96.7–99.8%); matched unrelated donor (MUD) 93.0% (90.1–96.0%); mismatched unrelated donor (MMUD) 89.9% (83.4–96.9%) and Haplo donors 89.1% (84.0–94.5%). Two-group comparisons: Pediatrics MRD vs MUD p-value: 0.0021; Pediatrics MRD vs MMUD p-value: 0.0008 and Pediatrics MRD vs Haplo p-value: <.0001. Among 1,158 adult patients who underwent transplantation for SAA during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according by donor type are: MRD 89.4% (86.1–92.8%); Haplo donors 84.4% (79.7–89.4%); MUD 79.1% (75.4–82.9%) and MMUD 76.4% (66.5–87.7%). Two-group comparisons: Adults MRD vs MUD p-value: 0.0001; Adults MRD vs MMUD p-value: 0.0049 and Adults MRD vs Haplo p-value: 0.1315. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 61. — Among 603 pediatric patients receiving 1^st allogeneic transplant for sickle cell disease during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant is: matched related donor (MRD) 98.9% (97.8–100.0%); Haploidentical donor (Haplo) 92.0% (87.4–96.8%); matched unrelated donor (MUD) 91.3% (83.6–99.9%) and mismatched unrelated donor (MMUD) 87.0% (74.2–100.0%). Two-group comparisons: MRD vs MUD p-value: <.0001; MRD vs MMUD p-value: <.0001 and MRD vs Haplo p-value: 0.0003. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 62. — Among 792 pediatric patients receiving 1^st allogeneic transplant for primary immune deficiency during 2016–2021, the 3-year probabilities (95% CI) of survival following transplant is: matched related donors (MRD) 93.0% (89.5–96.6%); matched unrelated donors (MUD) 81.4% (77.2–85.8%); Haploidentical donors (Haplo) 76.7% (70.4–83.6%) and mismatched unrelated donor (MMUD) 73.1% (63.5–84.0%). Two-group comparisons: MRD vs MUD p-value: 0.0001; MRD vs MMUD p-value: <.0001 and MRD vs Haplo p-value: <.0001. Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 63. — Among the 4,979 patients receiving 1^st autologous HCT for Hodgkin lymphoma (HL) during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Chemosensitive disease 92.9% (92.0–93.8%) and Chemoresistant disease 88.7% (84.3–93.3%). Among the 655 patients receiving 1^st allogeneic HCT for HL during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Chemosensitive disease 75.7% (72.0–79.5%) and Chemoresistant disease 58.5% (49.1–69.8%). Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done

Figure 64. — Among the 818 patients receiving 1^st autologous HCT for Follicular Lymphoma (FL) during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Chemosensitive disease 85.8% (83.1–88.6%) and Chemoresistant disease 60.2% (41.1–88.2%). Among the 245 patients receiving 1^st allogeneic HCT for FL during 2017–2022, the 3-year probabilities (95% CI) of survival following transplant according to disease status are: Chemosensitive disease 78.2% (72.8–84.1%) and Chemoresistant disease 79.1% (66.4–94.2%). Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 65. — Among the 44,576 patients receiving 1^st autologous HCT for multiple myeloma and amyloidosis during 2017–2022, the 3-year probabilities (95% CI) of survival after their autologous HCT are: Amyloidosis 90.0% (88.4–91.7%) and Multiple Myeloma 85.3% (84.9–85.7%) Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 66. — Among 6119 patients receiving CAR-T infusion for Diffuse large B-cell lymphoma (DLBCL) during 2017–2022 in US, the 3-year probabilities (95% CI) of survival is 43.5% (42.1–45.0%). Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

Figure 67. — The 3-year probabilities (95% CI) of survival for 1,418 patients who received first CAR-T infusion during 2017–2022 in US for ALL, by age groups are: Pediatrics 65.5% (62.1–69.0%) and Adults 48.6% (44.0–53.8%). Caution interpreting these univariate curves is important, as adjustment for other relevant factors using multivariable analyses has not been done.

ACKNOWLEDGEMENTS

CIBMTR is supported primarily by the Public Health Service U24CA076518 from the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI), and the National Institute of Allergy and Infectious Diseases (NIAID); 75R60222C00011 from the Health Resources and Services Administration (HRSA); and N00014-24-1-2057 and N00014-25-1-2146 from the Office of Naval Research. Support is also provided by the Medical College of Wisconsin, NMDP, Gateway for Cancer Research, Pediatric Transplantation and Cellular Therapy Consortium and from the following commercial entities: AbbVie; Actinium Pharmaceuticals, Inc.; Adaptimmune LLC; Adaptive Biotechnologies Corporation; ADC Therapeutics; Adienne SA; Alexion; AlloVir, Inc.; Amgen, Inc.; Astellas Pharma US; AstraZeneca; Atara Biotherapeutics; Autolus Limited; BeiGene; BioLineRX; Blue Spark Technologies; bluebird bio, inc.; Blueprint Medicines; Bristol Myers Squibb Co.; CareDx Inc.; Caribou Biosciences, Inc.; CSL Behring; CytoSen Therapeutics, Inc.; DKMS; Editas Medicine; Elevance Health; Eurofins Viracor, DBA Eurofins Transplant Diagnostics; Gamida-Cell, Ltd.; Gift of Life Biologics; Gift of Life Marrow Registry; HistoGenetics; In8bio, Inc.; Incyte Corporation; Iovance; Janssen Research & Development, LLC; Janssen/Johnson & Johnson; Jasper Therapeutics; Jazz Pharmaceuticals, Inc.; Karius; Kashi Clinical Laboratories; Kiadis Pharma; Kite, a Gilead Company; Kyowa Kirin; Labcorp; Legend Biotech; Mallinckrodt Pharmaceuticals; Med Learning Group; Medac GmbH; Merck & Co.; Mesoblast, Inc.; Millennium, the Takeda Oncology Co.; Miller Pharmacal Group, Inc.; Miltenyi Biotec, Inc.; MorphoSys; MSA-EDITLife; Neovii Pharmaceuticals AG; Novartis Pharmaceuticals Corporation; Omeros Corporation; Orca Biosystems, Inc.; OriGen BioMedical; Ossium Health, Inc.; Pfizer, Inc.; Pharmacyclics, LLC, An AbbVie Company; Registry Partners; Rigel Pharmaceuticals; Sanofi; Sarah Cannon; Seagen Inc.; Sobi, Inc.; Sociedade Brasileira de Terapia Celular e Transplante de Medula Ossea (SBTMO); Stemcell Technologies; Stemline Technologies; STEMSOFT; Takeda Pharmaceuticals; Talaris Therapeutics; Vertex Pharmaceuticals; Vor Biopharma Inc.; Xenikos BV.

Our co-author, colleague, and friend Kristin Page, MD (June 7, 1974 - September 5, 2024) died during the drafting of this report. This report is dedicated to her memory.

Footnotes

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REFERENCES

1.Bacigalupo A, Ballen K, Rizzo D, et al. : Defining the intensity of conditioning regimens: working definitions. Biol Blood Marrow Transplant 15:1628–33, 2009 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Giralt S, Ballen K, Rizzo D, et al. : Reduced-intensity conditioning regimen workshop: defining the dose spectrum. Report of a workshop convened by the center for international blood and marrow transplant research. Biol Blood Marrow Transplant 15:367–9, 2009 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.CIBMTR Summary slides: https://cibmtr.org/Files/Summary-Slides--Reports/CIBMTR-Summary-Slides-2024-5.12.2025-WEB.pptx accessed 22 May 2025

[R1] 1.Bacigalupo A, Ballen K, Rizzo D, et al. : Defining the intensity of conditioning regimens: working definitions. Biol Blood Marrow Transplant 15:1628–33, 2009 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R2] 2.Giralt S, Ballen K, Rizzo D, et al. : Reduced-intensity conditioning regimen workshop: defining the dose spectrum. Report of a workshop convened by the center for international blood and marrow transplant research. Biol Blood Marrow Transplant 15:367–9, 2009 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] 3.CIBMTR Summary slides: https://cibmtr.org/Files/Summary-Slides--Reports/CIBMTR-Summary-Slides-2024-5.12.2025-WEB.pptx accessed 22 May 2025

PERMALINK

Current Activity Trends and Outcomes in Hematopoietic Cell Transplantation and Cellular Therapy – A report from the CIBMTR

Stephen R Spellman

Ke Xu

Temitope Oloyede

Kwang Woo Ahn

Othman Akhtar

Yung-Tsi Bolon

Larisa Broglie

Jenni Bloomquist

Caitrin Bupp

Min Chen

Steven M Devine

Najla El-Jurdi

Mehdi Hamadani

Mary Hengen

Anna H Huppler

Samantha Jaglowski

Michelle Kuxhausen

Stephanie J Lee

Amy Moskop

Kristin M Page

Marcelo Pasquini

Waleska Perez

Rachel Phelan

Doug Rizzo

Wael Saber

Heather Stefanski

Patricia Steinert

Eileen Tuschl

Alexis Visotcky

Rebecca Vogel

Jeffery J Auletta

Bronwen E Shaw

Mariam Allbee-Johnson

Abstract

Figure 1. Number of 1st Cellular Therapies Reported to CIBMTR in the US.

Figure 2. Number of Allogeneic HCTs in the US by Donor Type.

Figure 3. Relative Proportion of Allogeneic HCTS in the US by Donor Type.

Figure 4. Number of Allogeneic HCTS in the US by Donor Type, Adults.

Figure 5. Number of Allogeneic HCTs in the US by Donor Type, Pediatrics.

Figure 6. Number of Haplo HCTs in the US by Disease Type, Pediatrics.

Figure 7. Relative Proportion of Allogeneic HCTs by Donor Types in the US by Recipient Age, 2019–2023.

Figure 8. Recipient Age of Allogeneic HCTs in the US.

Figure 9. Recipient Age of Autologous HCTs in the US.

Figure 10. Comorbidity Index in Allogeneic HCTs in the US by Recipient Age, 2019–2023.

Figure 11. Comorbidity Index in the Allogeneic HCTs in the US by Conditioning Intensity.

Figure 12. Number of Allogeneic HCTs in the US by Graft Source, Adults.

Figure 13. Number of Allogeneic HCTs in the US by Graft Source, Pediatrics.

Figure 14. GVHD Prophylaxis of Matched Related Donor HCTs in the US, Adults, Myeloablative Conditioning (MAC).

Figure 15. GVHD Prophylaxis of Matched Related Donor HCTs in the US, Adults, Reduced Intensity Conditioning/Non-myeloablative (RIC/NMA).

Figure 16. GVHD Prophylaxis of Matched Unrelated Donor HCTs in the US, Adults, MAC.

Figure 17. GVHD Prophylaxis of Matched Unrelated Donor HCTs in the US, Adults, RIC/NMA.

Figure 18. GVHD Prophylaxis of Haplo Donor HCTs in the US, Adults.

Figure 19. GVHD Prophylaxis of Mismatched Unrelated Donor HCTs in the US, Adults.

Figure 20. PTCy and other GVHD Prophylaxis, 2023, Adults.

Figure 21. GVHD Prophylaxis of Matched Related Donor HCTs in the US, Pediatrics, MAC.

Figure 22. GVHD Prophylaxis of Matched Related Donor HCTs in the US, Pediatrics, RIC/NMA.

Figure 23. GVHD Prophylaxis of Matched Unrelated Donor HCTs in the US, Pediatrics, MAC.

Figure 24. GVHD Prophylaxis of Matched Unrelated Donor HCTs in the US, Pediatrics, RIC/NMA.

Figure 25. GVHD Prophylaxis of Haplo Donor HCTs in the US, Pediatrics.

Figure 26. GVHD Prophylaxis of Mismatched Unrelated Donor HCTs in the US, Pediatrics.

Figure 27. Number of HCTs by Indications in the US, 2023, Adult.

Figure 28. Relative Proportion of Multiple Myeloma Treatment by Type in the US.

Figure 29. Relative Proportion of Lymphoma Treatment by Type in the US.

Figure 30. Number of HCTs by Indication in the US, 2023, Pediatrics.

Figure 31. Number of CAR-T Infusions by Indication in the US Annually.

Figure 32. Trends in the use of CAR-T after alloHCT for ALL.

Figure 33. Trends in the alloHCT for ALL patients after CAR-T.

Figure 34. CAR-T indications 2016–2023.

Figure 35. Infusions with Commercial CAR-T Cell Products in the US, 2016–2023.

Figure 36. Causes of Death after Allogeneic HCTs in the US, 2019–2023.

Figure 37. Causes of Death after Autologous HCTs in the US, 2019–2023.

Figure 38. Common Conditioning Regimens in Acute Myeloid Leukemia and Myelodysplastic Syndromes/Myeloproliferative Neoplasms Allogeneic HCTs in the US, in Adults, 2019–2023.

Figure 39. Common Conditioning Regimens in Acute Lymphoblastic Leukemia Allogeneic HCTs in the US, in Adults, 2019–2023.

Figure 40. Allogeneic HCTs in the US by Race and Ethnicity.

Figure 41. Allogeneic HCTs in the US by Race and Ethnicity and Donor Type, 2019–2023.

Figure 42. Autologous HCTs in the US by Race and Ethnicity.

Figure 43. Autologous HCTs in the US by Race and Ethnicity, Adults.

Figure 44. Autologous HCTs in the US by Race and Ethnicity, Pediatrics.

Figure 1. Number of 1^st Cellular Therapies Reported to CIBMTR in the US.