Haploidentical vs Mismatched Unrelated Donor Transplants with Posttransplant Cyclophosphamide-based GVHD Prophylaxis

Haploidentical vs Mismatched Unrelated Donor Transplants with Posttransplant Cyclophosphamide-based GVHD Prophylaxis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Haploidentical vs Mismatched Unrelated Donor Transplants with Posttransplant Cyclophosphamide-based GVHD Prophylaxis Dipenkumar Modi, Seongho Kim, Maya Shatta, Abhinav Deol, Andrew Kin, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3944455/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 May, 2024 Read the published version in Bone Marrow Transplantation → Version 1 posted 11 You are reading this latest preprint version Abstract Post-transplant cyclophosphamide (PTcy) as a GVHD prevention strategy has provided encouraging results in haploidentical and mismatched unrelated donor (MMUD) transplants. We sought to determine overall survival and GVHD-free relapse-free survival (GRFS) between haploidentical and MMUD using PTcy-contaning GVHD prophylaxis. We retrospectively compared outcomes of 144 adult patients who underwent either haploidentical or MMUD transplants using peripheral blood stem cells, and PTcy, tacrolimus, and mycophenolate for GVHD prophylaxis. Between January 2013 and December 2021, 89 patients received haploidentical and 55 received MMUD transplants. Among MMUD, 87% (n=48) were 7/8 HLA-matched and 13% (n=7) were 6/8 HLA-matched. Median age of the population was 62.5 years, 24% (n=35) were African American, 73% (n=105) had AML, and 20% (n=29) received myeloablative conditioning regimen. Median time to neutrophil engraftment was prolonged in the haploidentical group (18 vs 15 days, p<0.001), while platelet engraftment was similar (23 vs 21 days, p=0.15). Using propensity score-based covariate adjustment, no difference in overall survival and GRFS was noted between both groups. Our study demonstrated that transplant outcomes did not differ between haploidentical and MMUD when PTcy was used for GVHD prophylaxis. In the absence of HLA-matched donors, haploidentical and MMUD appear to provide equivalent outcomes. Biological sciences/Stem cells/Haematopoietic stem cells Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia Health sciences/Medical research/Stem-cell research Post-transplant Cyclophosphamide Haploidentical donor Mismatched unrelated donor Acute myeloid leukemia Myelodysplastic syndrome Allogeneic stem cell transplant Figures Figure 1 Figure 2 Figure 3 Introduction The median age of patients undergoing allogeneic transplantation has increased dramatically over the past few years ( 1 ). However, finding sibling donors for these patients has become more difficult, as older sibling donors have more comorbidities and greater difficulty with mobilizing stem cells. As a result, the number of HLA-matched related donor (MRD) transplants have declined with a corresponding rise of HLA-matched unrelated donor (MUD) transplants ( 2 ). HLA-MUD have shown to provide transplant outcomes comparable to MRD ( 3 – 8 ). Finding an HLA-MUD in the current donor registries depends on the ethnic and racial background of the patient, with the highest possibility among whites of European descent (75%) and the lowest possibility among blacks of South or Central American descent (16%) ( 9 ). Thus, patients from ethnic minorities or those without HLA-matched donors rely on haploidentical donors, mismatched unrelated donors (MMUD), or umbilical cord blood (UCB). Post-transplant cyclophosphamide (PTcy), when given on days + 3 and + 4, selectively depletes rapidly proliferating alloreactive T cells and spares memory T cells ( 10 – 12 ). PTcy significantly reduced rates of acute and chronic GVHD and improved non-relapse mortality (NRM) and overall survival (OS) in haploidentical donor transplants ( 12 , 13 ). Survival following haploidentical transplants with PTcy were comparable to matched donor transplants for acute leukemia and lymphoma in several single-center and multicenter studies ( 14 – 26 ). Given its encouraging activity, PTcy is being increasingly used in MMUD transplants. We along with others have previously shown that the rates of engraftment, GVHD, NRM, and OS with PTcy were comparable to conventional GVHD prophylaxis agents in MMUD transplants ( 27 – 34 ). Promising activity of PTcy in multiple HLA-mismatched related (haploidentical) and unrelated donors (MMUD) raises important questions; in the absence of an HLA-matched donor, is there a preferred donor between haploidentical and MMUD when PTcy is used for GVHD prophylaxis? Do outcomes of haploidentical or MMUD transplants differ when using PTcy-based GVHD prophylaxis? The information on the comparison of haploidentical and MMUD using PTcy-based GVHD prophylaxis is very limited ( 34 , 35 ). The EBMT study compared outcomes of haploidentical and 9/10 MMUD transplants for AML in complete remission (CR) and reported higher NRM, and lower leukemia-free survival (LFS) and OS in haploidentical transplants compared to MMUD ( 34 ). Herein, we conducted a retrospective review comparing outcomes of haploidentical and MMUD transplants for patients with AML and MDS who received PTcy, tacrolimus, and mycophenolate for GVHD prophylaxis. Materials and Methods All patients received peripheral blood stem cells. Molecular typing was performed at allele level for HLA-A, -B, -C and -DRB1. Our institution preference is to select donors younger than 40 years. Patients who did not have matched donors received haploidentical or MMUD transplant. While searching for an HLA-matched unrelated donor through the NMDP registry, we simultaneously screen for MMUD as well. Thus, we could quickly proceed with MMUD instead conducting an HLA-typing of the related donors to identify suitable haploidentical donors when HLA-matched donors are not available. Cytokine release syndrome (CRS) was graded per the ASTCT consensus grading criteria ( 36 ). The Wayne State University Institutional Review Board approved this study. This research work was carried out in accordance with the code of ethics of the Declaration of Helsinki for experiments involving humans. GVHD prophylaxis Cyclophosphamide 50 mg/kg/day was administered on days + 3 and + 4. Tacrolimus (0.03 mg/kg/day) was administered intravenously starting on day + 5. Tacrolimus was given orally when patient tolerated oral intake at fourfold the IV dose to maintain at therapeutic level, and tapered beginning around day + 60 in the absence of active GVHD, with a goal of tapering off completely by day + 180. Mycophenolate 15 mg/kg twice daily was given from day + 5 through day + 30. Acute and chronic GVHD were graded using the consensus criteria ( 37 – 39 ). Conditioning regimen Conditioning regimen was selected based on the age and comorbidities of the patient, and physician preferences. Myeloablative conditioning (MAC) regimen consisted of busulfan 130 mg/m 2 (days − 6 to − 3) and fludarabine 30 mg/m 2 (days − 6 to − 2) (Bu/Flu). Reduced intensity conditioning (RIC) regimens included ( 1 ) busulfan 130 mg/ m 2 (days − 6 and − 5), fludarabine 30 mg/ m 2 (days − 6 to -2), and TBI 200 cGy (day 0) (Bu/Flu/TBI) and ( 2 ) fludarabine 30 mg/ m 2 (days − 6 to -2), melphalan 140 mg/m 2 (day − 2), and TBI 200 cGy (day 0) (Flu/Mel/TBI). Busulfan was dosed pharmacokinetically to achieve an AUC of 5000 µmolar × minute for each dose. Endpoints The primary objective was to estimate OS and GRFS between haploidentical and MMUD transplants. Secondary objectives were to assess acute and chronic GVHD incidence rates, relapse rate, NRM, and RFS between both groups. Statistical methods Baseline patient characteristics were summarized using count and percentage for categorical variables and median and range for continuous variables. Fisher’s exact test and Wilcoxon rank sum tests were used to compare between groups for categorical and continuous variables, respectively. Kaplan-Meier estimates were used to summarize the distributions of RFS, OS and GRFS. The cumulative incidences of acute GVHD (aGVHD) and chronic GVHD (cGVHD) were calculated with relapse or death without GVHD as competing risks. The cumulative incidences of relapse and NRM were calculated with death without relapse for relapse and death with relapse for NRM, respectively, as competing risks. Multivariable Cox and subdistribution proportional hazard regression analyses were carried out to estimate adjusted HR and SHR, respectively, by propensity score-based covariate adjustment (PSCA). The propensity score was estimated using a multivariable logistic regression model with group as a response variable and age, Karnofsky performance score (KPS), HCT-CI, diagnosis, conditioning regimen, disease status at transplantation, cytomegalovirus (CMV) serotype, donor/recipient sex mismatch, and donor age as nine covariates. These covariates were included because of known clinical confounding factors. Then both estimated propensity score and group were included as covariates into multivariable Cox and subdistribution proportional hazard models, respectively. The proportional hazard assumption was checked and no violation was found. The follow-up time was calculated using the reverse Kaplan-Meier estimate. Results Patient Characteristics From January 2013 through December 2021, 89 patients underwent haploidentical and 55 received MMUD transplants (Table 1 ). Among the MMUD group, 48 patients (87%) were 7/8 HLA-matched and 7 (13%) were 6/8 HLA-matched. The median age of the population at transplant was 62.5 years. Thirty-five patients (24%) were of African American (AA) race and 4 (3%) were of Middle Eastern ethnicity. One hundred five patients (73%) had AML. MAC regimen (Bu/Flu) was used in 29 patients (20%). Among RIC regimens, Bu/Flu/TBI was used in 100 patients (87%). When compared to the haploidentical donor group, median age of the donor was significantly younger (35 vs 27 days, p < 0.001) and the median time from diagnosis to transplant was significantly shorter for the MMUD group (8.2 vs 4.8 months, p = 0.04). Table 1 Patient characteristics Haploidentical (N = 89) MMUD (N = 55) All (N = 144) p Age, median (range) 62 (22,78) 64 (31,76) 62.5 (22,78) 0.534 Sex, no. (%) 0.229 Male 52 (58) 26 (47) 78 (54) Female 37 (42) 29 (53) 66 (46) Race, no. (%) 0.095 Caucasian 60 (67) 45 (82) 105 (73) African American 25 (28) 10 (18) 35 (24) Middle eastern 4 (4) 0 (0) 4 (3) Prior allogeneic transplant, no. (%) 12 (13) 3 (5) 15 (10) 0.164 KPS, median (range) 80 (60,100) 70 (60,100) 80 (60,100) 0.022 Comorbidity score, median (range) 3 (0,8) 2 (0,9) 3 (0,9) 0.796 Disease, no. (%) 0.177 AML 61 (69) 44 (80) 105 (73) MDS 28 (31) 11 (20) 39 (27) AML subtype, no. (%) 0.525 De-novo 44 (72) 29 (66) 73 (70) Secondary 17 (28) 15 (34) 32 (30) MDS subtype, no. (%) a 0.898 Single lineage dysplasia 1 (4) 0 (0) 1 (3) Multi lineage dysplasia 5 (18) 1 (10) 6 (16) MDS with ring sideroblasts 1 (4) 0 (0) 1 (3) EB-1 9 (32) 5 (50) 14 (37) EB-2 10 (36) 3 (30) 13 (34) Other 2 (7) 1 (10) 3 (8) Unknown 0 1 1 IPSS: MDS, no. (%) b 0.673 Low 2 (7) 1 (12) 3 (9) Intermediate 8 (30) 2 (25) 10 (29) High 8 (30) 1 (12) 9 (26) Very high 9 (33) 4 (50) 13 (37) Unknown 1 3 4 Disease status AML, no. (%) 0.002 First complete remission 19 (31) 31 (70) 50 (48) Second complete remission 15 (25) 4 (9) 19 (18) Third complete remission 1 (2) 0 (0) 1 (1) Primary induction failure 11 (18) 3 (7) 14 (13) Relapse disease 15 (25) 6 (14) 21 (20) MDS, no. (%) > 0.99 Complete remission 1 (4) 0 (0) 1 (3) Active disease 27 (96) 11 (100) 38 (97) Disease risk index, no. (%) 0.063 Low 1 (1) 1 (2) 2 (1) Intermediate 43 (48) 35 (64) 78 (54) High 39 (44) 13 (24) 52 (36) Very high 6 (7) 6 (11) 12 (8) Conditioning regimens Myeloablative regimens, no. (%) > 0.99 Bu/Flu 20 (100) 9 (100) 29 (100) Reduced-intensity regimens, no. (%) 0.397 Bu/Flu/TBI 58 (84) 42 (91) 100 (87) Flu/MEL/TBI 11 (16) 4 (9) 15 (13) Graft type, no. (%) > 0.99 Peripheral blood stem cells 89 (100) 55 (100) 144 (100) Infused CD34, median (range) 7.91 (1.19,26.2) 7.24 (3.1,20.75) 7.645 (1.19,26.2) 0.584 CMV serostatus, no. (%) 0.284 +/+ 32 (36) 14 (25) 46 (32) +/- 8 (9) 2 (4) 10 (7) -/+ 28 (31) 22 (40) 50 (35) -/- 21 (24) 17 (31) 38 (26) Donor/recipient sex mismatch, no. (%) 0.381 Male-Male 39 (44) 21 (38) 60 (42) Male-Female 23 (26) 19 (35) 42 (29) Female-Male 15 (17) 5 (9) 20 (14) Female-Female 12 (13) 10 (18) 22 (15) Donor age, median (range) 35 (17,64) 27 (19,41) 31 (17,64) < 0.001 Year of transplant, median (range) 2018 (2013,2021) 2019 (2014,2021) 2019 (2013,2021) 0.001 ABO matching, no. (%) 0.008 Matched 53 (60) 21 (38) 74 (51) Mismatch 36 (40) 32 (58) 68 (47) Bidirectional 0 (0) 2 (4) 2 (1) GVHD prophylaxis, no. (%) > 0.99 PTcy/Tacrolimus/Mycophenolate 89 (100) 55 (100) 144 (100) HLA matching, no. (%) < 0.001 4/8 59 (66) 0 (0) 59 (41) 5/8 21 (24) 0 (0) 21 (15) 6/8 8 (9) 7 (13) 15 (10) 7/8 1 (1) 48 (87) 49 (34) HLA-A, no. (%) 80 (91) 23 (42) 103 (72) < 0.001 HLA-B, no. (%) 80 (91) 23 (42) 103 (72) < 0.001 HLA-C, no. (%) 76 (86) 23 (42) 99 (69) < 0.001 DRB1, no. (%) 71 (81) 23 (42) 94 (66) < 0.001 a Data is not available for one patient; b Data is not available for four patients; Engraftment, Acute and Chronic GVHD Median time to neutrophil engraftment was 18 days for haploidentical and 15 days for MMUD transplants (p < 0.001). The median time to platelet engraftment was 23 days for haploidentical and 21 days for MMUD transplants (p = 0.15). Three haploidentical patients and one MMUD transplant experienced graft failure. Median duration of hospitalization was 33 days for haploidentical and 30 days for MMUD transplants (p = 0.06). The cumulative incidence of grade III-IV aGVHD at day + 100 was 3.4% for haploidentical and 7.3% for MMUD transplants (Gray’s p = 0.30). The cumulative incidence of cGVHD at 1-year was 28% for haploidentical and 14.2% for MMUD transplants (Gray’s p = 0.05) (Fig. 1 a-b), and chronic extensive GVHD was 17.5% for haploidentical and 12.3% for MMUD transplants (Gray’s p = 0.38). Multivariable analysis by PSCA to adjust for age, KPS, HCT-CI, diagnosis, conditioning regimen, DRI, CMV serotype, donor age, and donor/recipient sex mismatch did not demonstrate any difference in acute (SHR 0.82; 95% CI, 0.42–1.61; p = 0.57) and chronic GVHD (SHR 1.14; 95% CI, 0.32–4.06; p = 0.84) between both groups. Cytokine release syndrome and post-transplant infections CRS occurred in 69 patients (78%) in haploidentical and 21 (38%) in MMUD transplants (p < 0.001). Median time of onset of CRS was at day + 1 (range, 0–4) post-transplant in both groups, and median duration of CRS was three days in both groups. Majority of CRS were grade 1–2 (n = 66, 96% in haploidentical and n = 21, 100% in MMUD transplants). Three patients (4%) in the haploidentical group experienced grade 3–4 CRS. Thirty patients (43%) in the haploidentical group and 9 (43%) in MMUD transplants received tocilizumab at a median of 1 day following onset of CRS. There was no neurotoxicity and no deaths related to CRS. The rate of CMV reactivation was 30% for haploidentical and 29% for MMUD transplants (p > 0.99). Median time to CMV reactivation was 34 days post-transplant for haploidentical and 35 days for MMUD transplants (p = 0.77). Two patients in the haploidentical group developed GI CMV disease as did one in the MMUD transplant group. The rate of EBV reactivation was 1% for haploidentical and 7% for MMUD transplants (p = 0.07). Overall Survival and Relapse-free survival The median follow-up of surviving patients was 2.9 years for haploidentical and 2.1 years for MMUD transplants. At 1-year, OS was 66.7% for haploidentical and 69.5% for MMUD transplants (HR 0.81; 95% CI, 0.45–1.44; p = 0.47); and RFS was 59.0% for haploidentical and 61.8% for MMUD transplants (HR, 0.83; 95% CI, 0.49–1.40; p = 0.47) (Fig. 2 ). Among MMUD transplants, 1-year OS was not different according to HLA-match (67% for 7/8 HLA-match vs 85.7% for < 7/8 HLA-match). Multivariable cox proportional hazard analysis by PSCA did not reveal any difference in OS (HR 0.59; 95% CI, 0.28–1.25; p = 0.17) and RFS (HR 0.68; 95% CI, 0.34–1.36; p = 0.28). Relapse, NRM and GRFS At one-year, the relapse rate was 18.3% for haploidentical and 25% for MMUD transplants (Gray’s p = 0.49); the NRM was 22.7% for haploidentical and 13.2% for MMUD transplants (Gray’s p = 0.11); and the GRFS was 37.5% for haploidentical and 46.0% for MMUD transplants (HR 0.81; 95% CI, 0.52–1.26; p = 0.35) (Fig. 3 ). After PSCA, no difference in relapse (SHR 0.98; 95% CI, 0.34–2.82; p = 0.97), NRM (SHR 0.53; 95% CI, 0.22–1.29; p = 0.17), and GRFS (HR 0.95; 95% CI, 0.52–1.75; p = 0.88) was observed between both groups. We performed a separate analysis after removing 15 patients who received Flu/MEL/TBI regimen in both groups and did not notice any difference in OS, relapse, RFS, and NRM in multivariable analysis. The cause of death for patients undergoing haploidentical and MMUD transplants, respectively, included disease relapse (n = 8, 26% vs n = 8, 50%), infection (n = 13, 42% vs n = 4, 25%), GVHD (0% vs n = 2, 12%), multi-organ failure (n = 2, 6% vs n = 1, 6%), acute respiratory failure (n = 7, 23% vs 0%), and CNS infarction (n = 1, 3% vs n = 1, 6%). Subgroup analysis of African American patients At one-year, OS was 71.2% and 50% (HR 2.39; 95% CI, 0.82–6.97; p = 0.11), and RFS was 63.5% and 40% (HR 2.33; 95% CI, 0.87–6.29; p = 0.09), for haploidentical and MMUD transplants, respectively. At 1-year, cGVHD was 52.7% and 10% (Gray’s p = 0.04), relapse rate was 20.2% and 60% (Gray’s p = 0.02), and NRM was 16.2% and 0% (Gray’s p = 0.60), for haploidentical and MMUD transplants, respectively. No patients experienced grade III-IV aGVHD in both groups. Discussion There remains a critical need to identify the additional source of stem cells for patients with advanced age or those from ethnic minorities who do not have suitable HLA matched donors. Both haploidentical and MMUD are now being used in these settings. The use of PTcy in the haploidentical setting has shown to be an effective GVHD prevention strategy which allows engraftment without excess GVHD with outcomes similar to fully matched donor transplants. MMUD transplants were previously limited by high rates of graft failure, GVHD, and NRM ( 40 – 48 ). However, usage of PTcy for GVHD prevention appears to overcome multiple HLA-mismatches and improve MMUD transplant outcomes ( 27 – 34 ). There is a growing interest in exploring PTcy usage with the hope of abrogating transplant-related toxicity and mortality. Ours is one of the largest single-center studies comparing outcomes of haploidentical and MMUD transplants using PTcy, tacrolimus, and mycophenolate for GVHD prophylaxis and PBSC allografts. The results of this study could provide insight into selection of optimal donors. Our study did not report any difference in grade 3–4 aGVHD and cGVHD between haploidentical and MMUD transplants. These rates were in line with prior studies reporting outcomes of HLA-MRD and MUD transplants using conventional GVHD prophylaxis agents. The EBMT study evaluating haploidentical and 9/10 MMUD for AML reported grade 3–4 aGVHD rate of 6% for haploidentical bone marrow grafts compared to 12% for haploidentical PBSC grafts and MMUD ( 34 ). Increased use of MAC regimen (54–58% vs 20%) and various PTcy-based GVHD regimens might have contributed to higher aGVHD rates compared to our study. Our GVHD results appear favorable compared to prior studies of MMUD transplants using PTcy for GVHD prophylaxis ( 27 – 29 , 31 , 32 ). In the NMDP study evaluating MMUD transplants using bone marrow allografts and PTcy, sirolimus, and mycophenolate for GVHD prophylaxis, the rate of grade 3–4 aGVHD was 18% and 0%, and rate of 1-year cGVHD was 36% and 18% for MAC and RIC regimens, respectively ( 31 ). Our GVHD rates for MMUD transplants differed from the NMDP study, which may have resulted from several notable differences between both studies. In the NMDP analysis, MAC regimen was more commonly used (50% vs 16.3%), a higher proportion of patients received ≥ 6/8 HLA-match (43% vs 13%), and bone marrow was the source of stem cells (vs PBSC) compared to our study. The EBMT study evaluated PTcy and ATG outcomes of 9/10 MMUD transplants for AML using BM and PBSC allografts and reported grade 3–4 aGVHD rate of 9% for PTcy and 19% for ATG, while 2-year cGVHD rate was 39% for PTcy and 36% for ATG ( 27 ). The EBMT study used MAC regimen in 50% of patients (vs 16.3% in MMUD transplants) and various combinations of GVHD regimen were used which might have affected GVHD rates. All patients received bone marrow allografts which might have resulted in lower GVHD rates compared to our study. We observed rapid engraftment of neutrophil and platelet in the MMUD group compared to the haploidentical donor group. The rate of graft failure was similar in both groups. Our neutrophil and platelet engraftment times were shorter when compared to the NMDP study of MMUD transplants using PTcy and bone marrow allografts ( 31 ). This likely was related to use of peripheral blood stem cells in our study. The incidence and severity of CRS was higher in haploidentical compared to MMUD transplants (78% vs 38%, p < 0.001). This might be related to greater HLA-mismatches in the haploidentical group. Despite its common occurrence, no deaths were attributed to CRS. Our CMV reactivation rate was 30% and 29%, and EBV reactivation rate was 1% and 7% for haploidentical and MMUD transplants, respectively, which was consistent with prior studies reporting CMV reactivation among haploidentical transplants with PTcy ( 49 – 54 ). The CIBMTR study reported significantly higher rate of CMV reactivation among haploidentical donor with PTcy, matched sibling donor (MSD) with PTcy, compared to MSD with calcineurin inhibitors (42%, 37%, and 23%, p < 0.001). CMV reactivation was highest among CMV-seropositive recipients and was significantly higher in PTcy recipients ( 55 ). In our study, one-year relapse rate was 18.3% and 25% for haploidentical and MMUD transplants, respectively. More than half of the patients in our cohort had intermediate risk DRI, and approximately one third had high DRI. Our relapse rate was comparable to prior studies of HLA-matched donors, haploidentical donors, as well as MMUD for AML and MDS ( 27 , 31 , 34 ). We noted 1-year survival of 66.74% and 69.54% for haploidentical and MMUD transplants, respectively. The NMDP study reported 1-year survival of 72.3% and 78.9% for MAC and RIC regimens, respectively ( 31 ). This study reported significantly lower NRM than our study, which might have resulted in improved survival. Older median age and a relatively higher incidence of CMV reactivation rate in our study may have influenced the NRM. In the EBMT study, 9/10 MMUD was associated with higher 2-year OS (72% vs 62% and 60% for haploidentical bone marrow and haploidentical PBSC, respectively) and LFS (67% vs 56% and 55% for haploidentical bone marrow and haploidentical PBSC, respectively) for AML in CR ( 34 ). Our survival rates were lower compared to the EBMT study. Patients with racial or ethnic minorities are underrepresented in clinical trials and thus the information on alloSCT outcomes is limited. Since the odds of finding HLA-matched donor are very low in ethnic minority patients ( 9 ), new strategies to improve MMUD outcomes are warranted. The CIBMTR study evaluated association of race with myeloablative HLA-MUD alloSCT outcomes for acute and chronic leukemia and MDS. AA patients had worse OS (relative risk (RR) for mortality 1.47, p < 0.01), and disease-free survival (DFS) (RR 1.48, p < 0.01) and higher risks of transplant-related mortality (RR 1.56, p < 0.01) compared with Whites ( 56 ). Conversely, black race was independently associated with better OS (HR 0.47, p = 0.003), DFS (HR 0.49; P = 0.003), and relapse (HR 0.49; P = 0.01) following PTcy-based haploidentical donor transplants compared to Whites ( 57 ). One of the important findings of our study was that it included 24% patients with AA race and 3% with middle eastern ethnicity, and outcomes of AA patients were not different in both groups. This may indicate that MMUD could serve as a viable donor option when HLA-matched or haploidentical donors are not available. Possible selection bias involved in conditioning regimen and donor could be considered weaknesses of our study. In the absence of prospective randomized trial, results from retrospective study like ours could be used to guide clinical practice. The use of PSCA allowed us to negate confounding effects of some of these clinically relevant variables. In addition, all patients received uniform care in terms of intensity of conditioning regimen, GVHD prophylaxis, graft source, and supportive care, which could be considered strengths of this study. In conclusion, our study demonstrates acceptable safety and feasibility of PTcy in MMUD and haploidentical transplants. Haploidentical and MMUD transplants provide equivalent rates of GVHD, disease relapse, and survival for AML and MDS with PTcy-containing GVHD prophylaxis. Rates of graft failure and opportunistic infections were similar. Our results indicate that when an HLA-matched donor is not available, either haploidentical or MMUD may be used. Further randomized studies involving large patient population are warranted to validate these results. Declarations Funding: None. Competing interest : Dr. Modi serves in the advisory board in the MorphoSys and Seagen. He receives research funding from Genentech, MorphoSys, Genmab, and ADC Therapeutics, and honorarium from AstraZeneca, Beigene, Genmab, ADC therapeutics, and Seagen. Dr. Deol serves as a Consultant/Advisory board for Adicet, Kite/Gilead and Janssen. Acknowledgement : None Authorship Contributions: D.M., S.K., and J.U designed research; D.M., M.S. collected data; D.M., and S.K. analyzed the data; D.M. wrote the first draft of the manuscript; D.M., S.K., M.S., A.K., A.D., L.A., V.R., and J.U. reviewed the manuscript and provided their feedback Competing interest: Dr. Modi receives research funding from Karyophram, Genmab, ADC therapeutics, Genentech. He served in the advisory board for MorphoSys, ADC therapeutics, Genmab, and Seagen and received financial fees. He received fees for speaker bureau for Beigene. Dr. Deol serves as a Consultant/Advisory board for Adicet, Kite/Gilead and Janssen. Other authors have no existing or potential financial conflict of interest to disclose. We presented the abstract at American Society of Hematology (ASH) annual meeting 2022 at New Orleans, LA. The abstract was published in Blood supplement issue in December 2022. References Auletta J.J. KJ, Chen M., Shaw B.E. 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Jones RJ. Haploidentical transplantation: repurposing cyclophosphamide. Biol Blood Marrow Transplant. 2012;18(12):1771-2. Luznik L, Bolanos-Meade J, Zahurak M, Chen AR, Smith BD, Brodsky R, et al. High-dose cyclophosphamide as single-agent, short-course prophylaxis of graft-versus-host disease. Blood. 2010;115(16):3224-30. Luznik L, O'Donnell PV, Symons HJ, Chen AR, Leffell MS, Zahurak M, et al. HLA-haploidentical bone marrow transplantation for hematologic malignancies using nonmyeloablative conditioning and high-dose, posttransplantation cyclophosphamide. Biol Blood Marrow Transplant. 2008;14(6):641-50. Brunstein CG, Fuchs EJ, Carter SL, Karanes C, Costa LJ, Wu J, et al. Alternative donor transplantation after reduced intensity conditioning: results of parallel phase 2 trials using partially HLA-mismatched related bone marrow or unrelated double umbilical cord blood grafts. Blood. 2011;118(2):282-8. Ghosh N, Karmali R, Rocha V, Ahn KW, DiGilio A, Hari PN, et al. 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Jorge AS, Suarez-Lledo M, Pereira A, Gutierrez G, Fernandez-Aviles F, Rosinol L, et al. Single Antigen-Mismatched Unrelated Hematopoietic Stem Cell Transplantation Using High-Dose Post-Transplantation Cyclophosphamide Is a Suitable Alternative for Patients Lacking HLA-Matched Donors. Biol Blood Marrow Transplant. 2018;24(6):1196-202. Rashidi A, DiPersio JF, Westervelt P, Vij R, Schroeder MA, Cashen AF, et al. Comparison of Outcomes after Peripheral Blood Haploidentical versus Matched Unrelated Donor Allogeneic Hematopoietic Cell Transplantation in Patients with Acute Myeloid Leukemia: A Retrospective Single-Center Review. Biol Blood Marrow Transplant. 2016;22(9):1696-701. Slade M, DiPersio JF, Westervelt P, Vij R, Schroeder MA, Romee R. Haploidentical Hematopoietic Cell Transplant with Post-Transplant Cyclophosphamide and Peripheral Blood Stem Cell Grafts in Older Adults with Acute Myeloid Leukemia or Myelodysplastic Syndrome. Biol Blood Marrow Transplant. 2017;23(10):1736-43. Battipaglia G, Labopin M, Kroger N, Vitek A, Afanasyev B, Hilgendorf I, et al. Posttransplant cyclophosphamide vs antithymocyte globulin in HLA-mismatched unrelated donor transplantation. Blood. 2019;134(11):892-9. Mehta RS, Saliba RM, Chen J, Rondon G, Hammerstrom AE, Alousi A, et al. Post-transplantation cyclophosphamide versus conventional graft-versus-host disease prophylaxis in mismatched unrelated donor haematopoietic cell transplantation. Br J Haematol. 2016;173(3):444-55. Soltermann Y, Heim D, Medinger M, Baldomero H, Halter JP, Gerull S, et al. Reduced dose of post-transplantation cyclophosphamide compared to ATG for graft-versus-host disease prophylaxis in recipients of mismatched unrelated donor hematopoietic cell transplantation: a single-center study. Ann Hematol. 2019;98(6):1485-93. Modi D, Kondrat K, Kim S, Deol A, Ayash L, Ratanatharathorn V, et al. Post-transplant Cyclophosphamide Versus Thymoglobulin in HLA-Mismatched Unrelated Donor Transplant for Acute Myelogenous Leukemia and Myelodysplastic Syndrome. Transplant Cell Ther. 2021;27(9):760-7. Shaw BE, Jimenez-Jimenez AM, Burns LJ, Logan BR, Khimani F, Shaffer BC, et al. National Marrow Donor Program-Sponsored Multicenter, Phase II Trial of HLA-Mismatched Unrelated Donor Bone Marrow Transplantation Using Post-Transplant Cyclophosphamide. J Clin Oncol. 2021;39(18):1971-82. Kasamon YL, Ambinder RF, Fuchs EJ, Zahurak M, Rosner GL, Bolanos-Meade J, et al. Prospective study of nonmyeloablative, HLA-mismatched unrelated BMT with high-dose posttransplantation cyclophosphamide. Blood Adv. 2017;1(4):288-92. Al Malki MM, Tsai NC, Palmer J, Mokhtari S, Tsai W, Cao T, et al. Posttransplant cyclophosphamide as GVHD prophylaxis for peripheral blood stem cell HLA-mismatched unrelated donor transplant. Blood Adv. 2021;5(12):2650-9. Battipaglia G, Galimard JE, Labopin M, Raiola AM, Blaise D, Ruggeri A, et al. Post-transplant cyclophosphamide in one-antigen mismatched unrelated donor transplantation versus haploidentical transplantation in acute myeloid leukemia: a study from the Acute Leukemia Working Party of the EBMT. Bone Marrow Transplant. 2022;57(4):562-71. Gaballa S, Ge I, El Fakih R, Brammer JE, Kongtim P, Tomuleasa C, et al. Results of a 2-arm, phase 2 clinical trial using post-transplantation cyclophosphamide for the prevention of graft-versus-host disease in haploidentical donor and mismatched unrelated donor hematopoietic stem cell transplantation. Cancer. 2016;122(21):3316-26. Lee DW, Santomasso BD, Locke FL, Ghobadi A, Turtle CJ, Brudno JN, et al. ASTCT Consensus Grading for Cytokine Release Syndrome and Neurologic Toxicity Associated with Immune Effector Cells. Biol Blood Marrow Transplant. 2019;25(4):625-38. Lee SJ. Classification systems for chronic graft-versus-host disease. Blood. 2017;129(1):30-7. Lee SJ, Klein JP, Barrett AJ, Ringden O, Antin JH, Cahn JY, et al. Severity of chronic graft-versus-host disease: association with treatment-related mortality and relapse. Blood. 2002;100(2):406-14. Przepiorka D, Weisdorf D, Martin P, Klingemann HG, Beatty P, Hows J, et al. 1994 Consensus Conference on Acute GVHD Grading. Bone Marrow Transplant. 1995;15(6):825-8. Anasetti C, Beatty PG, Storb R, Martin PJ, Mori M, Sanders JE, et al. Effect of HLA incompatibility on graft-versus-host disease, relapse, and survival after marrow transplantation for patients with leukemia or lymphoma. Hum Immunol. 1990;29(2):79-91. Petersdorf EW, Anasetti C, Martin PJ, Gooley T, Radich J, Malkki M, et al. Limits of HLA mismatching in unrelated hematopoietic cell transplantation. Blood. 2004;104(9):2976-80. Petersdorf EW, Gooley TA, Anasetti C, Martin PJ, Smith AG, Mickelson EM, et al. Optimizing outcome after unrelated marrow transplantation by comprehensive matching of HLA class I and II alleles in the donor and recipient. Blood. 1998;92(10):3515-20. Savani BN, Labopin M, Kroger N, Finke J, Ehninger G, Niederwieser D, et al. Expanding transplant options to patients over 50 years. Improved outcome after reduced intensity conditioning mismatched-unrelated donor transplantation for patients with acute myeloid leukemia: a report from the Acute Leukemia Working Party of the EBMT. Haematologica. 2016;101(6):773-80. Woolfrey A, Klein JP, Haagenson M, Spellman S, Petersdorf E, Oudshoorn M, et al. HLA-C antigen mismatch is associated with worse outcome in unrelated donor peripheral blood stem cell transplantation. Biol Blood Marrow Transplant. 2011;17(6):885-92. Flomenberg N, Baxter-Lowe LA, Confer D, Fernandez-Vina M, Filipovich A, Horowitz M, et al. Impact of HLA class I and class II high-resolution matching on outcomes of unrelated donor bone marrow transplantation: HLA-C mismatching is associated with a strong adverse effect on transplantation outcome. Blood. 2004;104(7):1923-30. Lee SJ, Klein J, Haagenson M, Baxter-Lowe LA, Confer DL, Eapen M, et al. High-resolution donor-recipient HLA matching contributes to the success of unrelated donor marrow transplantation. Blood. 2007;110(13):4576-83. Finke J, Bethge WA, Schmoor C, Ottinger HD, Stelljes M, Zander AR, et al. Standard graft-versus-host disease prophylaxis with or without anti-T-cell globulin in haematopoietic cell transplantation from matched unrelated donors: a randomised, open-label, multicentre phase 3 trial. Lancet Oncol. 2009;10(9):855-64. Bacigalupo A, Lamparelli T, Bruzzi P, Guidi S, Alessandrino PE, di Bartolomeo P, et al. Antithymocyte globulin for graft-versus-host disease prophylaxis in transplants from unrelated donors: 2 randomized studies from Gruppo Italiano Trapianti Midollo Osseo (GITMO). Blood. 2001;98(10):2942-7. Ciurea SO, Mulanovich V, Saliba RM, Bayraktar UD, Jiang Y, Bassett R, et al. Improved early outcomes using a T cell replete graft compared with T cell depleted haploidentical hematopoietic stem cell transplantation. Biol Blood Marrow Transplant. 2012;18(12):1835-44. Raiola AM, Dominietto A, Ghiso A, Di Grazia C, Lamparelli T, Gualandi F, et al. Unmanipulated haploidentical bone marrow transplantation and posttransplantation cyclophosphamide for hematologic malignancies after myeloablative conditioning. Biol Blood Marrow Transplant. 2013;19(1):117-22. Shmueli E, Or R, Shapira MY, Resnick IB, Caplan O, Bdolah-Abram T, et al. High rate of cytomegalovirus drug resistance among patients receiving preemptive antiviral treatment after haploidentical stem cell transplantation. J Infect Dis. 2014;209(4):557-61. Tischer J, Engel N, Fritsch S, Prevalsek D, Hubmann M, Schulz C, et al. Virus infection in HLA-haploidentical hematopoietic stem cell transplantation: incidence in the context of immune recovery in two different transplantation settings. Ann Hematol. 2015;94(10):1677-88. Jamy O, Hebert C, Dunn-Valadez S, Magnusson T, Watts N, McGwin G, et al. Risk of Cytomegalovirus Infection with Post-Transplantation Cyclophosphamide in Haploidentical and HLA-Matched Unrelated Donor Transplantation. Transplant Cell Ther. 2022;28(4):213 e1- e6. Mariotti J, Legrand F, Furst S, Giordano L, Magri F, Richiardi L, et al. Risk Factors for Early Cytomegalovirus Reactivation and Impact of Early Cytomegalovirus Reactivation on Clinical Outcomes after T Cell-Replete Haploidentical Transplantation with Post-Transplantation Cyclophosphamide. Transplant Cell Ther. 2022;28(3):169 e1- e9. Goldsmith SR, Abid MB, Auletta JJ, Bashey A, Beitinjaneh A, Castillo P, et al. Posttransplant cyclophosphamide is associated with increased cytomegalovirus infection: a CIBMTR analysis. Blood. 2021;137(23):3291-305. Baker KS, Davies SM, Majhail NS, Hassebroek A, Klein JP, Ballen KK, et al. Race and socioeconomic status influence outcomes of unrelated donor hematopoietic cell transplantation. Biol Blood Marrow Transplant. 2009;15(12):1543-54. Solomon SR, Zhang X, Holland HK, Morris LE, Solh M, Bashey A. Superior Survival of Black Versus White Patients Following Post-Transplant Cyclophosphamide-Based Haploidentical Transplantation for Adults with Hematologic Malignancy. Biol Blood Marrow Transplant. 2018;24(6):1237-42. Additional Declarations The authors have declared there is NO conflict of interest to disclose. Cite Share Download PDF Status: Published Journal Publication published 22 May, 2024 Read the published version in Bone Marrow Transplantation → Version 1 posted Editorial decision: revise 11 Mar, 2024 Review # 1 received at journal 07 Mar, 2024 Review # 3 received at journal 25 Feb, 2024 Review # 2 received at journal 14 Feb, 2024 Reviewer # 3 agreed at journal 14 Feb, 2024 Reviewer # 2 agreed at journal 14 Feb, 2024 Reviewer # 1 agreed at journal 14 Feb, 2024 Reviewers invited by journal 14 Feb, 2024 Submission checks completed at journal 12 Feb, 2024 First submitted to journal 09 Feb, 2024 Editor assigned by journal 09 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3944455","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":272838587,"identity":"a9bbcd36-ad5b-4d50-9d4c-ba96ce855f0a","order_by":0,"name":"Dipenkumar 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risks\u003c/p\u003e","description":"","filename":"Fig1abv3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3944455/v1/1e024812319584f88f6540d5.jpg"},{"id":51236972,"identity":"df8aafb1-2650-4c3e-880e-212748f8ef92","added_by":"auto","created_at":"2024-02-16 16:43:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":131246,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Kaplan-Meier survival curves for overall survival (OS)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Kaplan-Meier survival curves for relapse-free survival (RFS)\u003c/p\u003e","description":"","filename":"Fig2abv3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3944455/v1/10a10e480f318266c84cd5c5.jpg"},{"id":51236973,"identity":"a6f218e4-eeb7-4fb8-b9cc-7e173c187774","added_by":"auto","created_at":"2024-02-16 16:43:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":184336,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Cumulative incidence curves for relapse with death without relapse as a competing risk\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Cumulative incidence curves for non-relapse mortality (NRM) with death with relapse as a competing risk\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c)\u003c/strong\u003e Kaplan-Meier survival curves for GVHD-free relapse-free survival (GRFS)\u003c/p\u003e","description":"","filename":"Fig3abcv3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3944455/v1/f1cd293ee5012c4bb2f65530.jpg"},{"id":56994688,"identity":"c1550bed-2c28-4b5c-a880-4f64c5b22c4c","added_by":"auto","created_at":"2024-05-23 07:11:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1301898,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3944455/v1/24e586ed-8e20-4de6-88fd-6d5877cffec3.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Haploidentical vs Mismatched Unrelated Donor Transplants with Posttransplant Cyclophosphamide-based GVHD Prophylaxis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe median age of patients undergoing allogeneic transplantation has increased dramatically over the past few years (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). However, finding sibling donors for these patients has become more difficult, as older sibling donors have more comorbidities and greater difficulty with mobilizing stem cells. As a result, the number of HLA-matched related donor (MRD) transplants have declined with a corresponding rise of HLA-matched unrelated donor (MUD) transplants (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). HLA-MUD have shown to provide transplant outcomes comparable to MRD (\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Finding an HLA-MUD in the current donor registries depends on the ethnic and racial background of the patient, with the highest possibility among whites of European descent (75%) and the lowest possibility among blacks of South or Central American descent (16%) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Thus, patients from ethnic minorities or those without HLA-matched donors rely on haploidentical donors, mismatched unrelated donors (MMUD), or umbilical cord blood (UCB).\u003c/p\u003e \u003cp\u003ePost-transplant cyclophosphamide (PTcy), when given on days\u0026thinsp;+\u0026thinsp;3 and +\u0026thinsp;4, selectively depletes rapidly proliferating alloreactive T cells and spares memory T cells (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). PTcy significantly reduced rates of acute and chronic GVHD and improved non-relapse mortality (NRM) and overall survival (OS) in haploidentical donor transplants (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Survival following haploidentical transplants with PTcy were comparable to matched donor transplants for acute leukemia and lymphoma in several single-center and multicenter studies (\u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Given its encouraging activity, PTcy is being increasingly used in MMUD transplants. We along with others have previously shown that the rates of engraftment, GVHD, NRM, and OS with PTcy were comparable to conventional GVHD prophylaxis agents in MMUD transplants (\u003cspan additionalcitationids=\"CR28 CR29 CR30 CR31 CR32 CR33\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePromising activity of PTcy in multiple HLA-mismatched related (haploidentical) and unrelated donors (MMUD) raises important questions; in the absence of an HLA-matched donor, is there a preferred donor between haploidentical and MMUD when PTcy is used for GVHD prophylaxis? Do outcomes of haploidentical or MMUD transplants differ when using PTcy-based GVHD prophylaxis? The information on the comparison of haploidentical and MMUD using PTcy-based GVHD prophylaxis is very limited (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The EBMT study compared outcomes of haploidentical and 9/10 MMUD transplants for AML in complete remission (CR) and reported higher NRM, and lower leukemia-free survival (LFS) and OS in haploidentical transplants compared to MMUD (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Herein, we conducted a retrospective review comparing outcomes of haploidentical and MMUD transplants for patients with AML and MDS who received PTcy, tacrolimus, and mycophenolate for GVHD prophylaxis.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eAll patients received peripheral blood stem cells. Molecular typing was performed at allele level for HLA-A, -B, -C and -DRB1. Our institution preference is to select donors younger than 40 years. Patients who did not have matched donors received haploidentical or MMUD transplant. While searching for an HLA-matched unrelated donor through the NMDP registry, we simultaneously screen for MMUD as well. Thus, we could quickly proceed with MMUD instead conducting an HLA-typing of the related donors to identify suitable haploidentical donors when HLA-matched donors are not available. Cytokine release syndrome (CRS) was graded per the ASTCT consensus grading criteria (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The Wayne State University Institutional Review Board approved this study. This research work was carried out in accordance with the code of ethics of the Declaration of Helsinki for experiments involving humans.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGVHD prophylaxis\u003c/h2\u003e \u003cp\u003eCyclophosphamide 50 mg/kg/day was administered on days\u0026thinsp;+\u0026thinsp;3 and +\u0026thinsp;4. Tacrolimus (0.03 mg/kg/day) was administered intravenously starting on day\u0026thinsp;+\u0026thinsp;5. Tacrolimus was given orally when patient tolerated oral intake at fourfold the IV dose to maintain at therapeutic level, and tapered beginning around day\u0026thinsp;+\u0026thinsp;60 in the absence of active GVHD, with a goal of tapering off completely by day\u0026thinsp;+\u0026thinsp;180. Mycophenolate 15 mg/kg twice daily was given from day\u0026thinsp;+\u0026thinsp;5 through day\u0026thinsp;+\u0026thinsp;30. Acute and chronic GVHD were graded using the consensus criteria (\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eConditioning regimen\u003c/h2\u003e \u003cp\u003eConditioning regimen was selected based on the age and comorbidities of the patient, and physician preferences. Myeloablative conditioning (MAC) regimen consisted of busulfan 130 mg/m\u003csup\u003e2\u003c/sup\u003e (days \u0026minus;\u0026thinsp;6 to \u0026minus;\u0026thinsp;3) and fludarabine 30 mg/m\u003csup\u003e2\u003c/sup\u003e (days \u0026minus;\u0026thinsp;6 to \u0026minus;\u0026thinsp;2) (Bu/Flu). Reduced intensity conditioning (RIC) regimens included (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) busulfan 130 mg/ m\u003csup\u003e2\u003c/sup\u003e (days \u0026minus;\u0026thinsp;6 and \u0026minus;\u0026thinsp;5), fludarabine 30 mg/ m\u003csup\u003e2\u003c/sup\u003e (days \u0026minus;\u0026thinsp;6 to -2), and TBI 200 cGy (day 0) (Bu/Flu/TBI) and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) fludarabine 30 mg/ m\u003csup\u003e2\u003c/sup\u003e (days \u0026minus;\u0026thinsp;6 to -2), melphalan 140 mg/m\u003csup\u003e2\u003c/sup\u003e (day \u0026minus;\u0026thinsp;2), and TBI 200 cGy (day 0) (Flu/Mel/TBI). Busulfan was dosed pharmacokinetically to achieve an AUC of 5000 \u0026micro;molar \u0026times; minute for each dose.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEndpoints\u003c/h2\u003e \u003cp\u003eThe primary objective was to estimate OS and GRFS between haploidentical and MMUD transplants. Secondary objectives were to assess acute and chronic GVHD incidence rates, relapse rate, NRM, and RFS between both groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eBaseline patient characteristics were summarized using count and percentage for categorical variables and median and range for continuous variables. Fisher\u0026rsquo;s exact test and Wilcoxon rank sum tests were used to compare between groups for categorical and continuous variables, respectively. Kaplan-Meier estimates were used to summarize the distributions of RFS, OS and GRFS. The cumulative incidences of acute GVHD (aGVHD) and chronic GVHD (cGVHD) were calculated with relapse or death without GVHD as competing risks. The cumulative incidences of relapse and NRM were calculated with death without relapse for relapse and death with relapse for NRM, respectively, as competing risks. Multivariable Cox and subdistribution proportional hazard regression analyses were carried out to estimate adjusted HR and SHR, respectively, by propensity score-based covariate adjustment (PSCA). The propensity score was estimated using a multivariable logistic regression model with group as a response variable and age, Karnofsky performance score (KPS), HCT-CI, diagnosis, conditioning regimen, disease status at transplantation, cytomegalovirus (CMV) serotype, donor/recipient sex mismatch, and donor age as nine covariates. These covariates were included because of known clinical confounding factors. Then both estimated propensity score and group were included as covariates into multivariable Cox and subdistribution proportional hazard models, respectively. The proportional hazard assumption was checked and no violation was found. The follow-up time was calculated using the reverse Kaplan-Meier estimate.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eFrom January 2013 through December 2021, 89 patients underwent haploidentical and 55 received MMUD transplants (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the MMUD group, 48 patients (87%) were 7/8 HLA-matched and 7 (13%) were 6/8 HLA-matched. The median age of the population at transplant was 62.5 years. Thirty-five patients (24%) were of African American (AA) race and 4 (3%) were of Middle Eastern ethnicity. One hundred five patients (73%) had AML. MAC regimen (Bu/Flu) was used in 29 patients (20%). Among RIC regimens, Bu/Flu/TBI was used in 100 patients (87%). When compared to the haploidentical donor group, median age of the donor was significantly younger (35 vs 27 days, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the median time from diagnosis to transplant was significantly shorter for the MMUD group (8.2 vs 4.8 months, p\u0026thinsp;=\u0026thinsp;0.04).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHaploidentical\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;89)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMUD\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;144)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, median (range)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (22,78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (31,76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.5 (22,78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaucasian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105 (73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle eastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior allogeneic transplant, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKPS, median (range)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (60,100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (60,100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80 (60,100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity score, median (range)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0,8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0,9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0,9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105 (73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAML subtype, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDe-novo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMDS subtype, no. (%)\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle lineage dysplasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMulti lineage dysplasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS with ring sideroblasts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEB-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEB-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIPSS: MDS, no. (%)\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAML, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst complete remission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond complete remission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThird complete remission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary induction failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelapse disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMDS, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete remission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease risk index, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConditioning regimens\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMyeloablative regimens, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBu/Flu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReduced-intensity regimens, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBu/Flu/TBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlu/MEL/TBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGraft type, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral blood stem cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfused CD34, median (range)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.91 (1.19,26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.24 (3.1,20.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.645 (1.19,26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCMV serostatus, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e+/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDonor/recipient sex mismatch, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale-Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale-Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale-Male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale-Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDonor age, median (range)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (17,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (19,41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (17,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear of transplant, median (range)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018 (2013,2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2019 (2014,2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019 (2013,2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABO matching, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatched\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74 (51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMismatch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBidirectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGVHD prophylaxis, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTcy/Tacrolimus/Mycophenolate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHLA matching, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHLA-A, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHLA-B, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHLA-C, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99 (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDRB1, no. (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eData is not available for one patient; \u003csup\u003eb\u003c/sup\u003eData is not available for four patients;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEngraftment, Acute and Chronic GVHD\u003c/h2\u003e \u003cp\u003eMedian time to neutrophil engraftment was 18 days for haploidentical and 15 days for MMUD transplants (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The median time to platelet engraftment was 23 days for haploidentical and 21 days for MMUD transplants (p\u0026thinsp;=\u0026thinsp;0.15). Three haploidentical patients and one MMUD transplant experienced graft failure. Median duration of hospitalization was 33 days for haploidentical and 30 days for MMUD transplants (p\u0026thinsp;=\u0026thinsp;0.06).\u003c/p\u003e \u003cp\u003eThe cumulative incidence of grade III-IV aGVHD at day\u0026thinsp;+\u0026thinsp;100 was 3.4% for haploidentical and 7.3% for MMUD transplants (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.30). The cumulative incidence of cGVHD at 1-year was 28% for haploidentical and 14.2% for MMUD transplants (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-b), and chronic extensive GVHD was 17.5% for haploidentical and 12.3% for MMUD transplants (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.38). Multivariable analysis by PSCA to adjust for age, KPS, HCT-CI, diagnosis, conditioning regimen, DRI, CMV serotype, donor age, and donor/recipient sex mismatch did not demonstrate any difference in acute (SHR 0.82; 95% CI, 0.42\u0026ndash;1.61; p\u0026thinsp;=\u0026thinsp;0.57) and chronic GVHD (SHR 1.14; 95% CI, 0.32\u0026ndash;4.06; p\u0026thinsp;=\u0026thinsp;0.84) between both groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eCytokine release syndrome and post-transplant infections\u003c/h2\u003e \u003cp\u003eCRS occurred in 69 patients (78%) in haploidentical and 21 (38%) in MMUD transplants (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Median time of onset of CRS was at day\u0026thinsp;+\u0026thinsp;1 (range, 0\u0026ndash;4) post-transplant in both groups, and median duration of CRS was three days in both groups. Majority of CRS were grade 1\u0026ndash;2 (n\u0026thinsp;=\u0026thinsp;66, 96% in haploidentical and n\u0026thinsp;=\u0026thinsp;21, 100% in MMUD transplants). Three patients (4%) in the haploidentical group experienced grade 3\u0026ndash;4 CRS. Thirty patients (43%) in the haploidentical group and 9 (43%) in MMUD transplants received tocilizumab at a median of 1 day following onset of CRS. There was no neurotoxicity and no deaths related to CRS.\u003c/p\u003e \u003cp\u003eThe rate of CMV reactivation was 30% for haploidentical and 29% for MMUD transplants (p\u0026thinsp;\u0026gt;\u0026thinsp;0.99). Median time to CMV reactivation was 34 days post-transplant for haploidentical and 35 days for MMUD transplants (p\u0026thinsp;=\u0026thinsp;0.77). Two patients in the haploidentical group developed GI CMV disease as did one in the MMUD transplant group. The rate of EBV reactivation was 1% for haploidentical and 7% for MMUD transplants (p\u0026thinsp;=\u0026thinsp;0.07).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOverall Survival and Relapse-free survival\u003c/h2\u003e \u003cp\u003eThe median follow-up of surviving patients was 2.9 years for haploidentical and 2.1 years for MMUD transplants. At 1-year, OS was 66.7% for haploidentical and 69.5% for MMUD transplants (HR 0.81; 95% CI, 0.45\u0026ndash;1.44; p\u0026thinsp;=\u0026thinsp;0.47); and RFS was 59.0% for haploidentical and 61.8% for MMUD transplants (HR, 0.83; 95% CI, 0.49\u0026ndash;1.40; p\u0026thinsp;=\u0026thinsp;0.47) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among MMUD transplants, 1-year OS was not different according to HLA-match (67% for 7/8 HLA-match vs 85.7% for \u0026lt;\u0026thinsp;7/8 HLA-match). Multivariable cox proportional hazard analysis by PSCA did not reveal any difference in OS (HR 0.59; 95% CI, 0.28\u0026ndash;1.25; p\u0026thinsp;=\u0026thinsp;0.17) and RFS (HR 0.68; 95% CI, 0.34\u0026ndash;1.36; p\u0026thinsp;=\u0026thinsp;0.28).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRelapse, NRM and GRFS\u003c/h2\u003e \u003cp\u003eAt one-year, the relapse rate was 18.3% for haploidentical and 25% for MMUD transplants (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.49); the NRM was 22.7% for haploidentical and 13.2% for MMUD transplants (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.11); and the GRFS was 37.5% for haploidentical and 46.0% for MMUD transplants (HR 0.81; 95% CI, 0.52\u0026ndash;1.26; p\u0026thinsp;=\u0026thinsp;0.35) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). After PSCA, no difference in relapse (SHR 0.98; 95% CI, 0.34\u0026ndash;2.82; p\u0026thinsp;=\u0026thinsp;0.97), NRM (SHR 0.53; 95% CI, 0.22\u0026ndash;1.29; p\u0026thinsp;=\u0026thinsp;0.17), and GRFS (HR 0.95; 95% CI, 0.52\u0026ndash;1.75; p\u0026thinsp;=\u0026thinsp;0.88) was observed between both groups. We performed a separate analysis after removing 15 patients who received Flu/MEL/TBI regimen in both groups and did not notice any difference in OS, relapse, RFS, and NRM in multivariable analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe cause of death for patients undergoing haploidentical and MMUD transplants, respectively, included disease relapse (n\u0026thinsp;=\u0026thinsp;8, 26% vs n\u0026thinsp;=\u0026thinsp;8, 50%), infection (n\u0026thinsp;=\u0026thinsp;13, 42% vs n\u0026thinsp;=\u0026thinsp;4, 25%), GVHD (0% vs n\u0026thinsp;=\u0026thinsp;2, 12%), multi-organ failure (n\u0026thinsp;=\u0026thinsp;2, 6% vs n\u0026thinsp;=\u0026thinsp;1, 6%), acute respiratory failure (n\u0026thinsp;=\u0026thinsp;7, 23% vs 0%), and CNS infarction (n\u0026thinsp;=\u0026thinsp;1, 3% vs n\u0026thinsp;=\u0026thinsp;1, 6%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis of African American patients\u003c/h2\u003e \u003cp\u003eAt one-year, OS was 71.2% and 50% (HR 2.39; 95% CI, 0.82\u0026ndash;6.97; p\u0026thinsp;=\u0026thinsp;0.11), and RFS was 63.5% and 40% (HR 2.33; 95% CI, 0.87\u0026ndash;6.29; p\u0026thinsp;=\u0026thinsp;0.09), for haploidentical and MMUD transplants, respectively. At 1-year, cGVHD was 52.7% and 10% (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.04), relapse rate was 20.2% and 60% (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.02), and NRM was 16.2% and 0% (Gray\u0026rsquo;s p\u0026thinsp;=\u0026thinsp;0.60), for haploidentical and MMUD transplants, respectively. No patients experienced grade III-IV aGVHD in both groups.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere remains a critical need to identify the additional source of stem cells for patients with advanced age or those from ethnic minorities who do not have suitable HLA matched donors. Both haploidentical and MMUD are now being used in these settings. The use of PTcy in the haploidentical setting has shown to be an effective GVHD prevention strategy which allows engraftment without excess GVHD with outcomes similar to fully matched donor transplants. MMUD transplants were previously limited by high rates of graft failure, GVHD, and NRM (\u003cspan additionalcitationids=\"CR41 CR42 CR43 CR44 CR45 CR46 CR47\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). However, usage of PTcy for GVHD prevention appears to overcome multiple HLA-mismatches and improve MMUD transplant outcomes (\u003cspan additionalcitationids=\"CR28 CR29 CR30 CR31 CR32 CR33\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). There is a growing interest in exploring PTcy usage with the hope of abrogating transplant-related toxicity and mortality. Ours is one of the largest single-center studies comparing outcomes of haploidentical and MMUD transplants using PTcy, tacrolimus, and mycophenolate for GVHD prophylaxis and PBSC allografts. The results of this study could provide insight into selection of optimal donors.\u003c/p\u003e \u003cp\u003eOur study did not report any difference in grade 3\u0026ndash;4 aGVHD and cGVHD between haploidentical and MMUD transplants. These rates were in line with prior studies reporting outcomes of HLA-MRD and MUD transplants using conventional GVHD prophylaxis agents. The EBMT study evaluating haploidentical and 9/10 MMUD for AML reported grade 3\u0026ndash;4 aGVHD rate of 6% for haploidentical bone marrow grafts compared to 12% for haploidentical PBSC grafts and MMUD (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Increased use of MAC regimen (54\u0026ndash;58% vs 20%) and various PTcy-based GVHD regimens might have contributed to higher aGVHD rates compared to our study. Our GVHD results appear favorable compared to prior studies of MMUD transplants using PTcy for GVHD prophylaxis (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). In the NMDP study evaluating MMUD transplants using bone marrow allografts and PTcy, sirolimus, and mycophenolate for GVHD prophylaxis, the rate of grade 3\u0026ndash;4 aGVHD was 18% and 0%, and rate of 1-year cGVHD was 36% and 18% for MAC and RIC regimens, respectively (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Our GVHD rates for MMUD transplants differed from the NMDP study, which may have resulted from several notable differences between both studies. In the NMDP analysis, MAC regimen was more commonly used (50% vs 16.3%), a higher proportion of patients received \u0026ge; 6/8 HLA-match (43% vs 13%), and bone marrow was the source of stem cells (vs PBSC) compared to our study. The EBMT study evaluated PTcy and ATG outcomes of 9/10 MMUD transplants for AML using BM and PBSC allografts and reported grade 3\u0026ndash;4 aGVHD rate of 9% for PTcy and 19% for ATG, while 2-year cGVHD rate was 39% for PTcy and 36% for ATG (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The EBMT study used MAC regimen in 50% of patients (vs 16.3% in MMUD transplants) and various combinations of GVHD regimen were used which might have affected GVHD rates. All patients received bone marrow allografts which might have resulted in lower GVHD rates compared to our study.\u003c/p\u003e \u003cp\u003eWe observed rapid engraftment of neutrophil and platelet in the MMUD group compared to the haploidentical donor group. The rate of graft failure was similar in both groups. Our neutrophil and platelet engraftment times were shorter when compared to the NMDP study of MMUD transplants using PTcy and bone marrow allografts (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This likely was related to use of peripheral blood stem cells in our study. The incidence and severity of CRS was higher in haploidentical compared to MMUD transplants (78% vs 38%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This might be related to greater HLA-mismatches in the haploidentical group. Despite its common occurrence, no deaths were attributed to CRS. Our CMV reactivation rate was 30% and 29%, and EBV reactivation rate was 1% and 7% for haploidentical and MMUD transplants, respectively, which was consistent with prior studies reporting CMV reactivation among haploidentical transplants with PTcy (\u003cspan additionalcitationids=\"CR50 CR51 CR52 CR53\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). The CIBMTR study reported significantly higher rate of CMV reactivation among haploidentical donor with PTcy, matched sibling donor (MSD) with PTcy, compared to MSD with calcineurin inhibitors (42%, 37%, and 23%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). CMV reactivation was highest among CMV-seropositive recipients and was significantly higher in PTcy recipients (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, one-year relapse rate was 18.3% and 25% for haploidentical and MMUD transplants, respectively. More than half of the patients in our cohort had intermediate risk DRI, and approximately one third had high DRI. Our relapse rate was comparable to prior studies of HLA-matched donors, haploidentical donors, as well as MMUD for AML and MDS (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). We noted 1-year survival of 66.74% and 69.54% for haploidentical and MMUD transplants, respectively. The NMDP study reported 1-year survival of 72.3% and 78.9% for MAC and RIC regimens, respectively (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This study reported significantly lower NRM than our study, which might have resulted in improved survival. Older median age and a relatively higher incidence of CMV reactivation rate in our study may have influenced the NRM. In the EBMT study, 9/10 MMUD was associated with higher 2-year OS (72% vs 62% and 60% for haploidentical bone marrow and haploidentical PBSC, respectively) and LFS (67% vs 56% and 55% for haploidentical bone marrow and haploidentical PBSC, respectively) for AML in CR (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Our survival rates were lower compared to the EBMT study.\u003c/p\u003e \u003cp\u003ePatients with racial or ethnic minorities are underrepresented in clinical trials and thus the information on alloSCT outcomes is limited. Since the odds of finding HLA-matched donor are very low in ethnic minority patients (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), new strategies to improve MMUD outcomes are warranted. The CIBMTR study evaluated association of race with myeloablative HLA-MUD alloSCT outcomes for acute and chronic leukemia and MDS. AA patients had worse OS (relative risk (RR) for mortality 1.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and disease-free survival (DFS) (RR 1.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and higher risks of transplant-related mortality (RR 1.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared with Whites (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Conversely, black race was independently associated with better OS (HR 0.47, p\u0026thinsp;=\u0026thinsp;0.003), DFS (HR 0.49; P\u0026thinsp;=\u0026thinsp;0.003), and relapse (HR 0.49; P\u0026thinsp;=\u0026thinsp;0.01) following PTcy-based haploidentical donor transplants compared to Whites (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). One of the important findings of our study was that it included 24% patients with AA race and 3% with middle eastern ethnicity, and outcomes of AA patients were not different in both groups. This may indicate that MMUD could serve as a viable donor option when HLA-matched or haploidentical donors are not available.\u003c/p\u003e \u003cp\u003ePossible selection bias involved in conditioning regimen and donor could be considered weaknesses of our study. In the absence of prospective randomized trial, results from retrospective study like ours could be used to guide clinical practice. The use of PSCA allowed us to negate confounding effects of some of these clinically relevant variables. In addition, all patients received uniform care in terms of intensity of conditioning regimen, GVHD prophylaxis, graft source, and supportive care, which could be considered strengths of this study.\u003c/p\u003e \u003cp\u003eIn conclusion, our study demonstrates acceptable safety and feasibility of PTcy in MMUD and haploidentical transplants. Haploidentical and MMUD transplants provide equivalent rates of GVHD, disease relapse, and survival for AML and MDS with PTcy-containing GVHD prophylaxis. Rates of graft failure and opportunistic infections were similar. Our results indicate that when an HLA-matched donor is not available, either haploidentical or MMUD may be used. Further randomized studies involving large patient population are warranted to validate these results.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e None.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e: Dr. Modi serves in the advisory board in the MorphoSys and Seagen. He receives research funding from Genentech, MorphoSys, Genmab, and ADC Therapeutics, and honorarium from AstraZeneca, Beigene, Genmab, ADC therapeutics, and Seagen. Dr. Deol serves as a Consultant/Advisory board for Adicet, Kite/Gilead and Janssen.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e: None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship Contributions:\u0026nbsp;\u003c/strong\u003eD.M., S.K., and J.U designed research; D.M., M.S. collected data; D.M., and S.K. analyzed the data;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eD.M. wrote the first draft of the manuscript; D.M., S.K., M.S., A.K., A.D., L.A., V.R., and J.U. reviewed the manuscript and provided their feedback\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u003c/strong\u003e Dr. Modi receives research funding from Karyophram, Genmab, ADC therapeutics, Genentech. He served in the advisory board for MorphoSys, ADC therapeutics, Genmab, and Seagen and received financial fees. He received fees for speaker bureau for Beigene. Dr. Deol serves as a Consultant/Advisory board for Adicet, Kite/Gilead and Janssen.\u003c/p\u003e\n\u003cp\u003eOther authors have no existing or potential financial conflict of interest to disclose.\u003c/p\u003e\n\u003cp\u003eWe presented the abstract at American Society of Hematology (ASH) annual meeting 2022 at New Orleans, LA. The abstract was published in Blood supplement issue in December 2022.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAuletta J.J. KJ, Chen M., Shaw B.E. Current use and outcome of hematopoietic stem cell transplantation: CIBMTR US summary slides: CIBMTR; 2021 [\u003c/li\u003e\n\u003cli\u003eAuletta J.J. KJ, Chen M., Shaw B.E. Current use and outcome of hematopoietic stem cell transplantation: CIBMTR US summary slides, 2021. 2021.\u003c/li\u003e\n\u003cli\u003eAlousi AM, Le-Rademacher J, Saliba RM, Appelbaum FR, Artz A, Benjamin J, et al. 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Transplant Cell Ther. 2022;28(4):213 e1- e6.\u003c/li\u003e\n\u003cli\u003eMariotti J, Legrand F, Furst S, Giordano L, Magri F, Richiardi L, et al. Risk Factors for Early Cytomegalovirus Reactivation and Impact of Early Cytomegalovirus Reactivation on Clinical Outcomes after T Cell-Replete Haploidentical Transplantation with Post-Transplantation Cyclophosphamide. Transplant Cell Ther. 2022;28(3):169 e1- e9.\u003c/li\u003e\n\u003cli\u003eGoldsmith SR, Abid MB, Auletta JJ, Bashey A, Beitinjaneh A, Castillo P, et al. Posttransplant cyclophosphamide is associated with increased cytomegalovirus infection: a CIBMTR analysis. Blood. 2021;137(23):3291-305.\u003c/li\u003e\n\u003cli\u003eBaker KS, Davies SM, Majhail NS, Hassebroek A, Klein JP, Ballen KK, et al. Race and socioeconomic status influence outcomes of unrelated donor hematopoietic cell transplantation. Biol Blood Marrow Transplant. 2009;15(12):1543-54.\u003c/li\u003e\n\u003cli\u003eSolomon SR, Zhang X, Holland HK, Morris LE, Solh M, Bashey A. Superior Survival of Black Versus White Patients Following Post-Transplant Cyclophosphamide-Based Haploidentical Transplantation for Adults with Hematologic Malignancy. Biol Blood Marrow Transplant. 2018;24(6):1237-42.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Post-transplant Cyclophosphamide; Haploidentical donor, Mismatched unrelated donor, Acute myeloid leukemia, Myelodysplastic syndrome, Allogeneic stem cell transplant","lastPublishedDoi":"10.21203/rs.3.rs-3944455/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3944455/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePost-transplant cyclophosphamide (PTcy) as a GVHD prevention strategy has provided encouraging results in haploidentical and mismatched unrelated donor (MMUD) transplants. We sought to determine overall survival and GVHD-free relapse-free survival (GRFS) between haploidentical and MMUD using PTcy-contaning GVHD prophylaxis. We retrospectively compared outcomes of 144 adult patients who underwent either haploidentical or MMUD transplants using peripheral blood stem cells, and PTcy, tacrolimus, and mycophenolate for GVHD prophylaxis. Between January 2013 and December 2021, 89 patients received haploidentical and 55 received MMUD transplants. Among MMUD, 87% (n=48) were 7/8 HLA-matched and 13% (n=7) were 6/8 HLA-matched. Median age of the population was 62.5 years, 24% (n=35) were African American, 73% (n=105) had AML, and 20% (n=29) received myeloablative conditioning regimen. Median time to neutrophil engraftment was prolonged in the haploidentical group (18 vs 15 days, p\u0026lt;0.001), while platelet engraftment was similar (23 vs 21 days, p=0.15). Using propensity score-based covariate adjustment, no difference in overall survival and GRFS was noted between both groups. Our study demonstrated that transplant outcomes did not differ between haploidentical and MMUD when PTcy was used for GVHD prophylaxis. In the absence of HLA-matched donors, haploidentical and MMUD appear to provide equivalent outcomes.\u003c/p\u003e","manuscriptTitle":"Haploidentical vs Mismatched Unrelated Donor Transplants with Posttransplant Cyclophosphamide-based GVHD Prophylaxis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-16 16:43:45","doi":"10.21203/rs.3.rs-3944455/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-03-11T12:24:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-03-07T21:08:40+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-02-25T21:36:14+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-02-15T01:44:17+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-15T00:29:12+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-14T16:12:00+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-14T15:50:55+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-02-14T13:35:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-02-12T11:21:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bone Marrow Transplantation","date":"2024-02-09T23:46:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-09T23:46:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5a2b64de-55c4-4262-ad60-6d382e43c891","owner":[],"postedDate":"February 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28759044,"name":"Biological sciences/Stem cells/Haematopoietic stem cells"},{"id":28759045,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia"},{"id":28759046,"name":"Health sciences/Medical research/Stem-cell research"}],"tags":[],"updatedAt":"2024-05-23T07:11:10+00:00","versionOfRecord":{"articleIdentity":"rs-3944455","link":"https://doi.org/10.1038/s41409-024-02309-z","journal":{"identity":"bone-marrow-transplantation","isVorOnly":false,"title":"Bone Marrow Transplantation"},"publishedOn":"2024-05-22 04:00:00","publishedOnDateReadable":"May 22nd, 2024"},"versionCreatedAt":"2024-02-16 16:43:45","video":"","vorDoi":"10.1038/s41409-024-02309-z","vorDoiUrl":"https://doi.org/10.1038/s41409-024-02309-z","workflowStages":[]},"version":"v1","identity":"rs-3944455","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3944455","identity":"rs-3944455","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}