Pretransplantation risk factors for MRD after allogeneic stem cell transplantation in AML patients: A prospective study

Pretransplantation risk factors for MRD after allogeneic stem cell transplantation in AML patients: A prospective study | 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 Pretransplantation risk factors for MRD after allogeneic stem cell transplantation in AML patients: A prospective study Ying-Jun Chang, Si-Qi Li, Chunzi Yu, Lan-Ping Xu, Yu Wang, Xiao-hui Zhang, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4438416/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Nov, 2024 Read the published version in Bone Marrow Transplantation → Version 1 posted 11 You are reading this latest preprint version Abstract We aimed to explore the risk factors for measurable residual disease (MRD) positivity after allogeneic stem cell transplantation (allo-SCT) in AML patients. A total of 478 AML patients receiving allo-SCT were prospectively enrolled. The cumulative incidences of post-SCT MRD positivity at 100 days, 360 days and 3 years were 4.6%, 12.1% and 18.3%, respectively. Positive pre-SCT MRD was a risk factor for post-SCT MRD positivity at both 360 days and 3 years ( P < 0.001). European LeukemiaNet (ELN) 2022 and 2017 risk stratification was a risk factor for positive post-SCT MRD at 100 days and 360 days ( P = 0.020 and 0.047, respectively). A scoring system for predicting post-SCT MRD positivity at 360 days was established by using pre-SCT MRD and ELN 2017 risk stratification. The cumulative incidence of positive post-SCT MRD at 3 years was 13.2%, 23.6%, and 43.9% for patients with scores of 0, 1, and 2, respectively ( P < 0.001). Multivariate analysis demonstrated that the scoring system was associated with a higher cumulative incidence of post-SCT MRD positivity, leukemia relapse and inferior survival. Our data indicate that positive pre-SCT MRD status, ELN 2022 risk stratification and 2017 risk stratification are independent risk factors for positive post-SCT MRD status in AML patients. Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia Health sciences/Risk factors Acute myeloid leukemia Measurable residual disease Risk factors ELN 2017 risk stratification Figures Figure 1 Figure 2 Introduction Allogeneic stem cell transplantation (allo-SCT) is a curative treatment for patients with acute myeloid leukemia (AML). [ 1 – 3 ] However, posttransplantation relapse remains the main cause of treatment failure. [ 4 – 5 ] Although various methods, including targeted drugs, chemotherapy, immune checkpoint inhibitors, donor lymphocyte infusion (DLI), and secondary allogeneic transplantation, are used to treat relapsed AML patients post-SCT, the 5-year overall survival (OS) of these patients is only approximately 10–20%. [ 4 – 7 ] Increasing evidence indicates that peri-transplantation measurable residual disease (MRD), especially post-SCT MRD, is the root cause of relapse in AML patients receiving allo-SCT. [ 8 – 10 ] Compared to patients with persistent negative MRD after transplantation, AML patients with persistent MRD at any time posttransplantation have a greater cumulative incidence of relapse (CIR) and poorer leukemia-free survival (LFS). [ 8 – 9 ] More importantly, post-SCT MRD-guided preemptive interventions, such as DLI, can significantly reduce the CIR and improve the survival of AML patients. [ 10 ] Therefore, it is crucial to identify patients who are at a high risk of developing post-SCT MRD and select appropriate therapeutic regimens to improve their prognosis. Unfortunately, to our knowledge, only a few studies have suggested an association between pre-SCT MRD positivity and post-SCT MRD positivity in patients with AML. [ 8 , 11 – 12 ] However, the reported studies possessed a number of limitations: first, the studies had a retrospective nature; [ 8 , 12 ] second, the number of patients included in the studies was relatively small, and the only AML patients who were involved were patients with a specific risk type; [ 11 ] and third, these studies did not investigate the association of other variables, such as remission status and ELN 2017 or ELN 2022 risk stratifications, with positive post-SCT residual disease. [ 8 , 11 – 12 ] Therefore, we performed this large-sample, prospective study to explore the risk factors for positive posttransplantation MRD in AML patients who underwent allo-SCT. The results showed that positive pre-SCT MRD and ELN risk stratification were risk factors for positive post-SCT MRD after allogeneic transplantation in patients with AML. Methods Patients In this study, we prospectively enrolled 478 consecutive patients with AML who underwent allo-HSCT (including haploidentical hematopoietic stem cell transplantation [haplo-HSCT] [n = 375], HLA-matched sibling donor transplantation [MSDT] [n = 92] and HLA-matched unrelated donor transplantation [MUDT] [n = 11]) between July 2018 and December 2019 at the Peking University Institute of Hematology. MSDT was the first choice for allo-HSCT. If the HLA-matched sibling donor was unavailable, subjects without a suitable closely HLA-matched unrelated donor (> 8 of 10 matching HLA-A, B, C, DR, and DQloci and > 5 of 6 matching HLA-A, B, and DR loci) were eligible for haplo-HSCT. [ 3 ] All of the patients who were included in the study provided signed informed consent. The study was performed in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of Peking University. Trial registration #ChiCTR1800016458 at http://www.chictr.org.cn/showproj.aspx?proj527944 Transplantation Protocol The transplantation procedure was performed as previously described. [ 3 , 13 – 15 ] For MUDT patients and the majority of patients in the haplo-HSCT group, the conditioning regimen was a standard myeloablative conditioning (MAC) regimen consisting of the following: cytarabine (4 g/m 2 /day intravenously on Days − 10 and − 9), busulfan (9.6 mg/kg intravenously in 12 doses on Days − 8 to -6), cyclophosphamide (1.8 g/m 2 /day intravenously on Days − 5 and − 4), semustine (250 mg/m 2 /d orally once on Day − 3), and antithymocyte globulin (ATG) (2.5 mg/kg/day, Sang Stat, intravenously on Days − 5 to -2). For MSDT, patients received hydroxycarbamide (80 mg/kg orally on Day − 10) or a lower dose of cytarabine (2 g/m 2 /d on Day − 9); otherwise, the previously mentioned identical regimen without ATG was used. In addition, a small portion of haplo-HSCT patients were conditioned with total body irradiation (TBI, 770 cGy on Day − 6) and the MAC regimen on Days − 5 to -3. Granulocyte colony-stimulating factor (G-CSF, 5 µk/kg/d subcutaneously for 5 or 6 consecutive days) was administered to healthy donors to mobilize the bone marrow (G-BM) and peripheral blood (G-PB). The target mononuclear cell (MNC) count was 6×10 8 /kg of the recipient weight. Unmanipulated BM (harvested on Day 4 after G-CSF) and/or PB stem cells (PBSCs, harvested on Day 5 after G-CSF; if the MNC count did not reach the target value, they were harvested again on Day 6 after G-CSF) were infused into the corresponding recipient on the day of collection. [ 3 , 13 – 15 ] All of the patients received graft-versus-host disease (GVHD) prophylaxis consisting of cyclosporine A (CsA) and mycophenolate mofetil (MMF), as well as short-term methotrexate, as described previously. [ 13 – 15 ] Detection of MRD Eight-color multiparameter flow cytometry (MFC) was used as a routine clinical test to detect MRD in all of the enrolled patients, with a sensitivity ranging from 10 − 4 to 10 − 5 for bone marrow aspirate samples. Bone marrow samples were obtained before allo-HSCT; at 1, 2, 3, 4.5, 6, 9, and 12 months after allo-HSCT, as well as every 6 months after transplantation. In addition, posttransplantation MRD was evaluated at any time according to changes in the patient's condition. [ 16 ] A panel of eight antibody combinations that recognize CD7, CD11b, CD13, CD14, CD16, CD19, CD33, CD34, CD38, CD41, CD45, CD56, CD61, CD64, CD71, CD117, CD123, and HLA-DR was used for MRD evaluation. A total of 0.2–1 million events per tube were collected on a FACSCant II. MRD positivity was considered when a cluster of more than twenty-five cells with leukemia-associated immunophenotype (LAIP) and side scatter (SSC) characteristics was observed, and these cells were identified in all of the plots of interest and carried at least two LAIP markers that were identified at diagnosis. For those without LAIP markers at the time of diagnosis, MRD was identified as a cell population that exhibited deviation from normal antigen expression patterns on specific cell lineages at specific stages of maturity (compared to either normal or regenerated bone marrow). [ 16 – 17 ] The targeted lower limit of detection (LOD) was 0.01%. When abnormal cells were identified, the cells were quantified as the percentage of total CD45-positive leukocytes. Any measurable level of MRD was considered to be positive, and the results of the MFC assessment of MRD were provided to the transplant team. Standardized assays and quality controls were performed according to previous reports. [ 18 ] Interventions for Posttransplantation MRD To prevent relapse, patients with posttransplantation MRD were treated with immunosuppressants, such as reducing or discontinuing immunosuppressants, interferon-α (IFNα), and/or preemptive G-CSF-mobilized DLI. IFNα was used as previously described; according to previous research, IFNα or DLI showed comparable efficacy. [ 19 ] Preemptive G-CSF-mobilized DLI was allowed in patients without active GVHD when donor lymphocytes were available. [ 11 ] Short-term immunosuppressants were used after DLI to prevent GVHD. Detailed information on preemptive G-CSF-mobilized DLI has been previously published. [ 10 , 20 ] The treatments for GVHD following DLI or IFNα include methylprednisolone, prednisone, and CsA, among other treatments. [ 11 ] In addition, sorafenib or nilotinib are used as preemptive treatments for patients with FLT3-ITD mutations or BCR-ABL mutations, respectively. Definitions The definitions of engraftment, OS, LFS, nonrelapse mortality (NRM), and relapse were used as described previously. [ 4 , 13 , 21 ] Acute GVHD was diagnosed and graded based on published criteria by evaluating the pattern and severity of organ involvement. [ 22 ] Chronic GVHD was defined and graded as mild, moderate, or severe, in accordance with the National Institute of Health criteria. [ 23 ] Relapse was defined by morphological evidence of disease in the peripheral blood, bone marrow, or extramedullary sites. [ 11 ] Patients who had a prior history of myeloproliferative neoplasm (MPN) or myelodysplastic syndrome (MDS) were diagnosed with secondary AML. [ 24 ] The risk stratification of AML patients was assessed by using both European LeukemiaNet (ELN) 2017 and ELN 2022. The determination of risk categories for ELN 2017 and ELN 2022 was based on the ELN 2017 guidelines [ 25 ] and the ELN 2022 guidelines, [ 26 ] respectively. Evaluation Endpoints The primary endpoint of the study was the cumulative incidence of posttransplantation MRD. The secondary endpoints were the cumulative incidence of relapse and NRM, the probabilities of OS and LFS, the incidence of acute and chronic GVHD, and the engraftment rate. Statistical Analysis Patient characteristics were compared by using Pearson's chi-square test for categorical variables and the Kruskal‒Wallis test for continuous variables. The competing risk setting was used to evaluate cumulative incidence, with relapse treated as a competing event for NRM and with death from any cause as a competing risk for GVHD and relapse. The probabilities of OS and LFS were estimated by using the Kaplan‒Meier method. Variables in Table 1 were included in the univariate analysis. Only the characteristics with P < 0.1 were selected for multivariate analysis by using a Cox proportional hazard model that was built for time-to-event outcomes, and a forward selection procedure was implemented. Two-sided P values < 0.05 were considered to indicate statistical significance. The analysis was performed with SPSS 22.0 (Mathsoft, Seattle, WA, USA) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). Table 1 Patient and donor characteristics Characteristics All patients Posttransplantation MRDpos Patient number 478 65 Patient age, yr (median, range) 33 (1–64) 37 (1–59) Patient sex, n (%) Male 262 (54.8) 35 (53.8) Female 216 (45.2) 30 (46.2) Patient height, cm (median, range) 165 (73–190) 165 (76–186) Patient weight, kg (median, range) 62 (8-115) 63 (8-109) Disease type, n (%) Primary AML 450 (94.1) 60 (92.3) Secondary AML 28 (5.9) 5 (7.7) ELN 2017, n (%) Favorable 127 (26.6) 12 (18.5) Intermediate 249 (52.1) 35 (53.8) Adverse 102 (21.3) 18 (27.7) ELN 2022, n (%) Favorable 129 (27.0) 17 (26.2) Intermediate 203 (42.5) 23 (35.4) Adverse 146 (30.5) 25 (38.5) Time from diagnosis to transplant, month (median, range) 6.0 (2-55.5) 6.0 (2.5–18.5) Disease status, n (%) CR1 405 (84.7) 49 (75.4) ≥CR2 45 (9.4) 6 (9.2) NR 28 (5.9) 10 (15.4) Pretransplantation MRDpos, n (%) 120 (25.1) 36 (55.4) Transplant modality, n (%) Haplo-HSCT 375 (78.5) 53 (81.5) MSDT 92 (19.2) 12 (18.5) MUDT 11 (2.3) 0 (0.0) Donor-recipient relationship, n (%) Parent‒child 171 (35.8) 21 (32.3) Sibling-sibling 180 (37.7) 21 (32.3) Child‒parent 110 (23.0) 23 (35.4) Others 17 (3.6) 0 (0.0) Donor-recipient sex match, n (%) Male‒male 190 (39.7) 25 (38.5) Male‒female 142 (29.7) 18 (27.7) Female‒male 77 (16.1) 9 (13.8) Female‒female 69 (14.4) 13 (20.0) HLA-A, B, DR mismatched loci, n (%) 0 102 (21.3) 12 (18.5) 1 9 (1.9) 1 (1.5) 2 42 (8.8) 6 (9.2) 3 325 (68.0) 46 (70.8) Donor-recipient ABO match, n (%) Matched 276 (57.7) 36 (55.4) Major mismatch 91 (19.0) 16 (24.6) Minor mismatch 92 (19.2) 10 (15.4) Bidirectional mismatch 19 (4.0) 3 (4.6) Mononuclear cells per graft, ×10 8 /kg (median, range) 8.8 (3.3–19.5) 8.6 (3.9–19.2) CD34 + cells per graft, ×10 6 /kg (median, range) 2.4 (0.2–13.3) 2.6 (0.2–13.3) Interventions for posttransplantation MRDpos, n (%) Chemotherapy combined with DLI 11 (16.9) 11 (16.9) IFNα 12 (18.5) 12 (18.5) Targeted drug (Sorafenib or Nilotinib) 3 (4.6) 3 (4.6) Reduce or discontinue immunosuppressants 10 (15.4) 10 (15.4) Two or more interventions mentioned above 20 (30.8) 20 (30.8) No intervention 4 (6.2) 4 (6.2) Unknown 5 (7.7) 5 (7.7) Follow-up, d (median, range) 542 (23-1738) 491 (65-1588) Follow-up of survivors, d (median, range) 583 (144–1738) 694 (202–1588) Abbreviations : MRD=minimal residual disease; pos=positive; AML=acute myeloid leukemia; ELN=European LeukemiaNet; CR=complete remission; NR=nonremission; HLA=human leukocyte antigen; Haplo-HSCT=haploidentical hematopoietic stem cell transplantation; MSDT=HLA-matched sibling donor transplantation; MUDT=HLA-matched unrelated donor transplantation; DLI=donor lymphocyte infusion; IFNα= interferon-α. Results Patient Characteristics A total of 478 eligible patients were enrolled in this study. Patient and donor clinical characteristics are summarized in Table 1 . The median age of the patients was 33 years. The patients were either diagnosed with primary AML (94.1%) or secondary AML (5.9%). The majority of patients were in CR1 before allo-SCT (n = 405, 84.7%). Most patients underwent haplo-SCT (78.5%), followed by MSDT (19.2%) and MUDT (2.3%). One hundred and twenty patients had positive pre-SCT MRD (25.1%), and the median pre-SCT MRD was 0.79% (range: 0.01–43.01%). Sixty-five patients developed post-SCT MRD (13.6%). The median value of the first post-SCT MRD was 0.15% (range: 0.01–5.30%), and the median time for the emergence of positive MRD after allo-SCT was 139 days (range: 24-1141 days) posttransplantation. Hematopoietic Engraftment and Transplantation Outcomes All but one patient achieved myeloid engraftment by 30 days after allo-HSCT. Among the 477 evaluable patients, the median times of neutrophil and platelet engraftment were 13 (range: 9–27) days and 14 (range: 6-215) days posttransplantation, respectively. The median follow-up times for all of the patients and for those who survived were 542 (range: 23-1738) days and 583 (range: 144–1738) days after allo-SCT, respectively (Table 1 ). The 3-year OS and LFS were 76.2% (95% confidence interval [CI]: 70.8–82.1%) and 73.1% (95% CI: 67.6–79.2%), respectively. The cumulative incidences of relapse and NRM at 3 years were 20.0% (95% CI: 14.5–25.5%) and 6.9% (95% CI: 4.5–9.3%), respectively. The 100-day cumulative incidence of Grade II-IV acute GVHD and the 3-year cumulative incidence of chronic GVHD were 21.1% (95% CI: 17.4–24.8%) and 51.0% (95% CI: 45.4–56.6%), respectively. Positive post-SCT MRD was observed in 65 patients. The cumulative incidences of positive post-SCT MRD at 100 days, at 360 days and at 3 years following allo-SCT were 4.6% (95% CI: 2.7–6.5%), 12.1% (95% CI: 9.1–15.1%) and 18.3% (95% CI: 12.8–23.8%), respectively. Patients with positive post-SCT MRD status had a greater CIR and lower LFS, as well as OS, than did those with negative post-SCT MRD status (all P < 0.001) (Fig. 1 A-C). Patients with positive post-SCT MRD at 360 days experienced a greater CIR and lower LFS and OS than did those without detectable post-SCT MRD ( P < 0.001 for all); moreover, they had a shorter OS than did patients with positive post-SCT MRD after 360 days ( P = 0.014, Fig. 1 D-F). Patients with positive post-SCT MRD after 360 days had a greater CIR ( P = 0.017) but comparable survival to those with negative post-SCT MRD (Fig. 1 D-F). Risk Factors for Positive Posttransplantation MRD in All Patients In the total population, patients who were positive for pre-SCT MRD were more likely to have positive post-SCT MRD and CIR, as well as lower LFS and OS, than were those who were negative for pre-SCT MRD (all P < 0.001) ( Figure S1 A-D ). Multivariate analysis demonstrated that positive pre-SCT MRD (hazard ratio: [HR] 4.479, 95% CI: 2.744–7.310, P < 0.001) was associated with post-SCT MRD positivity. At 360 days after transplantation, the cumulative incidence of positive post-SCT MRD was significantly greater in patients with positive pre-SCT MRD than in those with negative pre-SCT MRD ( P < 0.001) ( Figure S2A ). The cumulative incidence of post-SCT MRD positivity was significantly greater in patients with adverse prognoses than in those with favorable or intermediate prognoses according to the ELN 2017 risk stratification ( P = 0.031) ( Figure S2B ). The associations of the ELN 2017 risk stratification with other transplant outcomes are shown in Figure S2C-E . Multivariate analysis demonstrated that positive pre-SCT MRD (HR: 4.449, 95% CI: 2.598–7.617, P < 0.001) and the ELN 2017 risk stratification (adverse versus favorable combined with intermediate: HR: 1.790, 95% CI: 1.008–3.180, P = 0.047) were related to positive post-SCT MRD. At 100 days after allo-SCT, the cumulative incidence of positive post-SCT MRD was significantly greater in patients with positive pre-SCT MRD than in patients with negative pre-SCT MRD ( P < 0.001) ( Figure S3A ). The cumulative incidence of post-SCT MRD positivity was significantly greater in patients with adverse prognoses than in patients with favorable or intermediate prognoses according to the ELN 2022 risk stratification ( P = 0.011) (Figure S3B ). Patients with an adverse prognosis according to the ELN 2022 risk stratification had a greater CIR but comparable LFS and OS compared with those with a favorable prognosis combined with an intermediate prognosis according to the ELN 2022 risk stratification ( P = 0.021, 0.108, and 0.155, respectively). Multivariate analysis indicated that pre-SCT MRD (HR: 8.197, 95% CI: 3.206–20.957, P < 0.001) and ELN 2022 (adverse versus favorable combined with intermediate: HR: 2.709, 95% CI: 1.170–6.274, P = 0.020) were associated with post-SCT MRD positivity. However, ELN 2022 risk stratification had no significant impact on post-SCT MRD positivity at 360 days or overall post-SCT MRD positivity ( P = 0.221 and 0.098, respectively) ( Figure S3C-D ). A Scoring System for Post-SCT MRD and Transplant Outcomes in All Patients When considering the association of positive pre-SCT MRD and ELN 2017 risk stratification with positive post-SCT MRD, we established a scoring system based on pre-SCT MRD and ELN 2017 risk stratification for predicting post-SCT MRD at 360 days after allo-HSCT. The scoring system utilized negative and positive pre-SCT MRD scores of 0 and 1, respectively. Favorable combined with intermediate prognosis and adverse prognosis in the ELN 2017 risk stratification were scored as 0 and 1, respectively. According to the scoring system, patients were stratified into three groups, including the low-risk group, with a score of 0 (n = 286, 59.8%); the medium-risk group, with a score of 1 (n = 162, 33.9%); and the high-risk group, with a score of 2 (n = 30, 6.3%). The cumulative incidence of positive post-SCT MRD at 3 years was 13.2%, 23.6%, and 43.9% for patients in the low-risk, medium-risk, and high-risk groups, respectively ( P < 0.001). The cumulative incidence of post-SCT MRD positivity at 360 days was 6.0%, 19.2%, and 34.6% for patients in the low-risk, medium-risk, and high-risk groups, respectively ( P < 0.001) (Fig. 2 A-B). Multivariate analysis demonstrated that the scoring system was associated with post-SCT MRD positivity at 360 days and 3 years after allo-SCT (Table 2 ). Moreover, patients in the medium-risk and high-risk groups experienced a greater CIR and lower LFS and OS than patients in the low-risk group, whereas patients in the high-risk group had a greater CIR and a trend toward lower LFS and OS than did those in the medium-risk group according to the scoring system (Fig. 2 C-E). Multivariate analysis indicated that the risk score was associated with leukemia relapse and LFS (Table 2 ). Table 2 Univariate and multivariate analysis of the associations between posttransplantation MRD and transplant outcomes Univariate analysis Multivariate analysis Covariates HR 95% CI P value HR 95% CI P value Posttransplantation MRD at 360 days after allo-HSCT The scoring system < 0.001 < 0.001 The low-risk group (risk score 0) 1 1 The medium-risk group (risk score 1) 3.541 1.923–6.520 < 0.001 3.541 1.923–6.520 < 0.001 The high-risk group (risk score 2) 7.673 3.386–17.385 < 0.001 7.673 3.386–17.385 < 0.001 Disease status 0.004 CR1 1 ≥CR2 1.407 0.597–3.320 0.435 NR 3.628 1.697–7.756 0.001 Posttransplantation MRD The scoring system < 0.001 < 0.001 The low-risk group (risk score 0) 1 1 The medium-risk group (risk score 1) 3.085 1.790–5.317 < 0.001 3.085 1.790–5.317 < 0.001 The high-risk group (risk score 2) 6.187 2.907–13.170 < 0.001 6.187 2.907–13.170 < 0.001 Disease status 0.001 CR1 1 ≥CR2 1.211 0.519–2.829 0.658 NR 3.627 1.830–7.187 < 0.001 Relapse The scoring system < 0.001 0.002 The low-risk group (risk score 0) 1 1 The medium-risk group (risk score 1) 2.146 1.290–3.570 0.003 1.681 0.977–2.892 0.061 The high-risk group (risk score 2) 5.033 2.536–9.989 < 0.001 3.821 1.832–7.970 < 0.001 ELN 2022 0.031 Favorable 1 Intermediate 1.715 0.860–3.420 0.126 Adverse 2.486 1.245–4.966 0.010 Disease status < 0.001 < 0.001 CR1 1 1 ≥CR2 2.189 1.104–4.339 0.025 2.291 1.152–4.555 0.018 NR 5.405 2.998–9.744 < 0.001 3.541 1.866–6.723 < 0.001 Leukemia-free survival The scoring system 0.001 0.035 The low-risk group (risk score 0) 1 1 The medium-risk group (risk score 1) 1.690 1.122–2.544 0.012 1.413 0.914–2.184 0.120 The high-risk group (risk score 2) 2.904 1.535–5.493 0.001 2.366 1.208–4.635 0.012 ELN 2022 0.209 Favorable 1 Intermediate 1.235 0.739–2.065 0.420 Adverse 1.586 0.938–2.683 0.085 Disease status < 0.001 0.001 CR1 1 1 ≥CR2 1.919 1.083–3.401 0.026 1.955 1.102–3.470 0.022 NR 3.622 2.098–6.254 < 0.001 2.732 1.511–4.941 0.001 Overall survival The scoring system 0.002 The low-risk group (risk score 0) 1 The medium-risk group (risk score 1) 1.689 1.086–2.626 0.020 The high-risk group (risk score 2) 2.992 1.530–5.850 0.001 Disease status < 0.001 < 0.001 CR1 1 1 ≥CR2 1.894 1.020–3.515 0.043 1.894 1.020–3.515 0.043 NR 4.088 2.344–7.131 < 0.001 4.088 2.344–7.131 < 0.001 Abbreviations : MRD=minimal residual disease; HR=hazard ratio; CI=confidence interval; allo-HSCT=allogeneic hematopoietic stem cell transplantation; CR=complete remission; NR=nonremission; ELN=European LeukemiaNet. * Variables in Table 1 were first included in the univariate analysis, and only the variables with P < 0.1 were selected for multivariate analysis by using a Cox proportional hazard model. Discussion In this large-sample prospective study, we provided further evidence indicating that positive pre-SCT MRD was an independent risk factor for post-SCT MRD positivity in patients with AML, which has been previously reported by other researchers. [ 8 , 11 – 12 ] In addition to pretransplant MRD, the ELN 2017 risk stratification and the ELN 2022 stratification were identified for the first time as being two risk factors for positive posttransplantation residual disease. Furthermore, we developed a novel scoring system based on pre-SCT MRD and ELN 2017 risk stratification, which could stratify transplant recipients with AML into three subgroups with different cumulative incidences of post-SCT MRD positivity. Therefore, our study provides a new risk factor and scoring system for positive post-SCT residual disease in AML patients who received allogeneic transplantations. In agreement with previous studies, [ 8 , 11 – 12 ] we further confirmed the strong association of positive pre-SCT MRD with posttransplant MRD positivity in recipients with AML. In a retrospective study reported by Zhou et al., 279 adults with AML, including HLA-matched siblings (n = 114) and unrelated donor transplantations (n = 165), received myeloablative allogeneic HCT. They showed that the percentages of post-MRD positivity in 216 patients who had no MFC evidence of MRD before transplantation and those with MFC evidence of residual disease pre-SCT were 0.7% and 5%, respectively. [ 8 ] In another retrospective study, 146 patients with AML who received allografts from sibling, unrelated, or hapolidentical donors were enrolled. Kim et al. reported that the percentages of patients with positive NGS evidence of residual disease in a group of patients who were pre-MRD-positive and those who were MRD-negative before transplantation were 1.5% and 15.9%, respectively. [ 12 ] The results reported by others [ 8 , 11 – 12 ] , as well as our data, suggest that positive pre-SCT MRD determined by either MFC, Q-PCR, or NGS is a risk factor for posttransplantation residual disease positivity in AML patients who either receive HLA-matched or mismatched allo-SCT. Several studies have suggested that the contribution of positive pre-SCT residual disease to post-SCT residual disease positivity could be related to HLA loss or decreased expression of HLA class II antigens, which results in evasion from donor immune cells. [ 27 – 30 ] However, further studies are warranted to elucidate the underlying mechanisms that contribute to drug resistance and immune escape of pre-SCT residual AML cells in allo-SCT settings. Consistent with previous studies, [ 31 – 34 ] in the present study, we confirmed the association of the ELN 2017 risk stratification and the ELN 2022 risk stratification with leukemia relapse. Impressively, we identified ELN 2022 risk stratification and ELN 2017 risk stratification as being risk factors for post-SCT MRD positivity on Day 100 and day 360 following transplantation, respectively. When considering that the onset of residual disease after transplantation contributes to subsequent hematological relapse and that MRD-directed therapy can decrease the CIR and improve survival, as reported by others and our group, [ 8 – 12 ] our results provide new evidence suggesting that the ability of ELN risk stratification to predict the onset of post-SCT MRD may provide us with an opportunity to identify high-risk patients who will experience positive MRD. Thus, they can adopt maintenance or prophylaxis therapy before hematological relapse. In this study, we developed a new scoring system for post-SCT MRD positivity to help physicians in identifying AML patients at high risk of relapse. The system combined pre-SCT MRD and ELN 2017 risk stratification to classify patients into different risk categories (statistically and clinically) with respect to the cumulative incidence of post-SCT residual disease, CIR, LFS, and OS (Fig. 2 ). However, this novel scoring system should be interpreted with caution. First, these data were obtained from unmanipulated allografts, and further studies regarding other transplant modalities, such as haplo-SCT with PT-Cy, [ 35 ] allo-SCT with T-cell depletion [ 36 ] and cord blood transplantation [ 37 ] , are needed to confirm the effects of the scoring system on posttransplant MRD positivity and other outcomes. Second, further prospective, multicenter studies should be performed on older transplant recipients and those with different ethnic origins (nonoriental). This research, although it was prospective and included a large number of patients, was limited by its single-center nature. The small number of patients with positive posttransplantation MRD results made it difficult to perform subgroup analysis, such as grouping pretransplantation MRD according to different values or grouping patients based on different transplant modalities. Therefore, prospective, multicenter studies with larger sample sizes are needed in the future to answer the abovementioned questions. In summary, our results indicated that pre-SCT residual disease as well as ELN 2017 risk stratification and ELN 2022 risk stratification were useful for predicting posttransplantation MRD in AML transplant recipients. The novel risk score system based on pre-SCT MRD and ELN 2017 risk stratification can predict posttransplantation MRD positivity and refine the risk stratification. The results of our study provide single or combination variables that can identify a specific population of patients who are candidates for prophylaxis or early preemptive therapy to decrease posttransplant relapse. Declarations Acknowledgments We thank all of the faculty members who participated in these studies. We would also like to thank the American Journal Experts (www.aje.com) for assistance in editing this manuscript. Funding This work was partly supported by grants from the National Natural Science Foundation of China (82293630 and 82293633); the Beijing Municipal Science and Technology Commission (Z221100007422008). Contributions Contribution: Y.-J.C. designed the study; Y.-J.C., C.-Z. Y., and S.-Q. L. collected data; Y.-J.C., S.-Q. L., and C.-Z. Y. analyzed the data and drafted the manuscript; all authors contributed to data interpretation, manuscript preparation, and approval of the final version. Competing interests The authors declare that they have no competing interests. Data Availability Statement The data supporting the conclusions of this article is available from the corresponding author (please contact [email protected] ) upon reasonable request. 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Supplementary Files SupplementaryMaterials.pdf Cite Share Download PDF Status: Published Journal Publication published 16 Nov, 2024 Read the published version in Bone Marrow Transplantation → Version 1 posted Editorial decision: revise 12 Jun, 2024 Review # 1 received at journal 10 Jun, 2024 Review # 2 received at journal 09 Jun, 2024 Review # 3 received at journal 27 May, 2024 Reviewer # 3 agreed at journal 26 May, 2024 Reviewer # 2 agreed at journal 21 May, 2024 Reviewer # 1 agreed at journal 21 May, 2024 Reviewers invited by journal 21 May, 2024 Submission checks completed at journal 20 May, 2024 First submitted to journal 17 May, 2024 Editor assigned by journal 17 May, 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. 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19:25:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4438416/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4438416/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41409-024-02466-1","type":"published","date":"2024-11-16T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57937724,"identity":"cb20b74f-45e4-4c78-a647-e9084a1b750d","added_by":"auto","created_at":"2024-06-07 17:43:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1224677,"visible":true,"origin":"","legend":"\u003cp\u003eEstimates of (A) CIR, (B) probability of LFS, and (C) probability of OS according to posttransplantation MRD. Estimates of (D) CIR, (E) probability of LFS, and (F) probability of OS among patients with positive posttransplantation MRD within and after 360 days following allo-HSCT, as well as patients with negative posttransplantation MRD.\u003c/p\u003e","description":"","filename":"Figure1BMT.png","url":"https://assets-eu.researchsquare.com/files/rs-4438416/v1/2eb57170cb430d3b05d89dbb.png"},{"id":57937727,"identity":"f2cbdb55-6d9e-44d6-b0c6-d448116752e9","added_by":"auto","created_at":"2024-06-07 17:43:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3123763,"visible":true,"origin":"","legend":"\u003cp\u003eEstimates of (A) cumulative incidence of positive posttransplantation MRD within 360 days following allo-HSCT, (B) cumulative incidence of positive posttransplantation MRD, (C) CIR, (D) probability of LFS, and (E) probability of OS according to the scoring system.\u003c/p\u003e","description":"","filename":"Figure2BMT.png","url":"https://assets-eu.researchsquare.com/files/rs-4438416/v1/e1df0090487a8e5ae5931dc1.png"},{"id":69171993,"identity":"878ae57f-e908-49d1-bfbf-7d9a95efa715","added_by":"auto","created_at":"2024-11-17 08:07:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3671846,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4438416/v1/d5a89904-d2bb-43f7-94e6-30e9884bfdb6.pdf"},{"id":57937725,"identity":"a3f3977b-3175-4003-8609-39beb3f95ff4","added_by":"auto","created_at":"2024-06-07 17:43:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":797509,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryMaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4438416/v1/49dc6040759891463a3057d3.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Pretransplantation risk factors for MRD after allogeneic stem cell transplantation in AML patients: A prospective study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAllogeneic stem cell transplantation (allo-SCT) is a curative treatment for patients with acute myeloid leukemia (AML). \u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e However, posttransplantation relapse remains the main cause of treatment failure. \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e Although various methods, including targeted drugs, chemotherapy, immune checkpoint inhibitors, donor lymphocyte infusion (DLI), and secondary allogeneic transplantation, are used to treat relapsed AML patients post-SCT, the 5-year overall survival (OS) of these patients is only approximately 10\u0026ndash;20%. \u003csup\u003e[\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIncreasing evidence indicates that peri-transplantation measurable residual disease (MRD), especially post-SCT MRD, is the root cause of relapse in AML patients receiving allo-SCT. \u003csup\u003e[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e Compared to patients with persistent negative MRD after transplantation, AML patients with persistent MRD at any time posttransplantation have a greater cumulative incidence of relapse (CIR) and poorer leukemia-free survival (LFS). \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e More importantly, post-SCT MRD-guided preemptive interventions, such as DLI, can significantly reduce the CIR and improve the survival of AML patients. \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e Therefore, it is crucial to identify patients who are at a high risk of developing post-SCT MRD and select appropriate therapeutic regimens to improve their prognosis.\u003c/p\u003e \u003cp\u003eUnfortunately, to our knowledge, only a few studies have suggested an association between pre-SCT MRD positivity and post-SCT MRD positivity in patients with AML. \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e However, the reported studies possessed a number of limitations: first, the studies had a retrospective nature;\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e second, the number of patients included in the studies was relatively small, and the only AML patients who were involved were patients with a specific risk type;\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e and third, these studies did not investigate the association of other variables, such as remission status and ELN 2017 or ELN 2022 risk stratifications, with positive post-SCT residual disease. \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e Therefore, we performed this large-sample, prospective study to explore the risk factors for positive posttransplantation MRD in AML patients who underwent allo-SCT. The results showed that positive pre-SCT MRD and ELN risk stratification were risk factors for positive post-SCT MRD after allogeneic transplantation in patients with AML.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eIn this study, we prospectively enrolled 478 consecutive patients with AML who underwent allo-HSCT (including haploidentical hematopoietic stem cell transplantation [haplo-HSCT] [n\u0026thinsp;=\u0026thinsp;375], HLA-matched sibling donor transplantation [MSDT] [n\u0026thinsp;=\u0026thinsp;92] and HLA-matched unrelated donor transplantation [MUDT] [n\u0026thinsp;=\u0026thinsp;11]) between July 2018 and December 2019 at the Peking University Institute of Hematology. MSDT was the first choice for allo-HSCT. If the HLA-matched sibling donor was unavailable, subjects without a suitable closely HLA-matched unrelated donor (\u0026gt;\u0026thinsp;8 of 10 matching HLA-A, B, C, DR, and DQloci and \u0026gt;\u0026thinsp;5 of 6 matching HLA-A, B, and DR loci) were eligible for haplo-HSCT. \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e All of the patients who were included in the study provided signed informed consent. The study was performed in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of Peking University. Trial registration #ChiCTR1800016458 at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.chictr.org.cn/showproj.aspx?proj527944\u003c/span\u003e\u003cspan address=\"http://www.chictr.org.cn/showproj.aspx?proj527944\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTransplantation Protocol\u003c/h2\u003e \u003cp\u003eThe transplantation procedure was performed as previously described. \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e For MUDT patients and the majority of patients in the haplo-HSCT group, the conditioning regimen was a standard myeloablative conditioning (MAC) regimen consisting of the following: cytarabine (4 g/m\u003csup\u003e2\u003c/sup\u003e/day intravenously on Days \u0026minus;\u0026thinsp;10 and \u0026minus;\u0026thinsp;9), busulfan (9.6 mg/kg intravenously in 12 doses on Days \u0026minus;\u0026thinsp;8 to -6), cyclophosphamide (1.8 g/m\u003csup\u003e2\u003c/sup\u003e/day intravenously on Days \u0026minus;\u0026thinsp;5 and \u0026minus;\u0026thinsp;4), semustine (250 mg/m\u003csup\u003e2\u003c/sup\u003e/d orally once on Day \u0026minus;\u0026thinsp;3), and antithymocyte globulin (ATG) (2.5 mg/kg/day, Sang Stat, intravenously on Days \u0026minus;\u0026thinsp;5 to -2). For MSDT, patients received hydroxycarbamide (80 mg/kg orally on Day \u0026minus;\u0026thinsp;10) or a lower dose of cytarabine (2 g/m\u003csup\u003e2\u003c/sup\u003e/d on Day \u0026minus;\u0026thinsp;9); otherwise, the previously mentioned identical regimen without ATG was used. In addition, a small portion of haplo-HSCT patients were conditioned with total body irradiation (TBI, 770 cGy on Day \u0026minus;\u0026thinsp;6) and the MAC regimen on Days \u0026minus;\u0026thinsp;5 to -3.\u003c/p\u003e \u003cp\u003eGranulocyte colony-stimulating factor (G-CSF, 5 \u0026micro;k/kg/d subcutaneously for 5 or 6 consecutive days) was administered to healthy donors to mobilize the bone marrow (G-BM) and peripheral blood (G-PB). The target mononuclear cell (MNC) count was 6\u0026times;10\u003csup\u003e8\u003c/sup\u003e/kg of the recipient weight. Unmanipulated BM (harvested on Day 4 after G-CSF) and/or PB stem cells (PBSCs, harvested on Day 5 after G-CSF; if the MNC count did not reach the target value, they were harvested again on Day 6 after G-CSF) were infused into the corresponding recipient on the day of collection. \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAll of the patients received graft-versus-host disease (GVHD) prophylaxis consisting of cyclosporine A (CsA) and mycophenolate mofetil (MMF), as well as short-term methotrexate, as described previously. \u003csup\u003e[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDetection of MRD\u003c/h2\u003e \u003cp\u003eEight-color multiparameter flow cytometry (MFC) was used as a routine clinical test to detect MRD in all of the enrolled patients, with a sensitivity ranging from 10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e for bone marrow aspirate samples. Bone marrow samples were obtained before allo-HSCT; at 1, 2, 3, 4.5, 6, 9, and 12 months after allo-HSCT, as well as every 6 months after transplantation. In addition, posttransplantation MRD was evaluated at any time according to changes in the patient's condition. \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eA panel of eight antibody combinations that recognize CD7, CD11b, CD13, CD14, CD16, CD19, CD33, CD34, CD38, CD41, CD45, CD56, CD61, CD64, CD71, CD117, CD123, and HLA-DR was used for MRD evaluation. A total of 0.2\u0026ndash;1\u0026nbsp;million events per tube were collected on a FACSCant II. MRD positivity was considered when a cluster of more than twenty-five cells with leukemia-associated immunophenotype (LAIP) and side scatter (SSC) characteristics was observed, and these cells were identified in all of the plots of interest and carried at least two LAIP markers that were identified at diagnosis. For those without LAIP markers at the time of diagnosis, MRD was identified as a cell population that exhibited deviation from normal antigen expression patterns on specific cell lineages at specific stages of maturity (compared to either normal or regenerated bone marrow). \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e The targeted lower limit of detection (LOD) was 0.01%. When abnormal cells were identified, the cells were quantified as the percentage of total CD45-positive leukocytes. Any measurable level of MRD was considered to be positive, and the results of the MFC assessment of MRD were provided to the transplant team. Standardized assays and quality controls were performed according to previous reports. \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eInterventions for Posttransplantation MRD\u003c/h2\u003e \u003cp\u003eTo prevent relapse, patients with posttransplantation MRD were treated with immunosuppressants, such as reducing or discontinuing immunosuppressants, interferon-α (IFNα), and/or preemptive G-CSF-mobilized DLI. IFNα was used as previously described; according to previous research, IFNα or DLI showed comparable efficacy. \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e Preemptive G-CSF-mobilized DLI was allowed in patients without active GVHD when donor lymphocytes were available. \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e Short-term immunosuppressants were used after DLI to prevent GVHD. Detailed information on preemptive G-CSF-mobilized DLI has been previously published. \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e The treatments for GVHD following DLI or IFNα include methylprednisolone, prednisone, and CsA, among other treatments. \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e In addition, sorafenib or nilotinib are used as preemptive treatments for patients with FLT3-ITD mutations or BCR-ABL mutations, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDefinitions\u003c/h2\u003e \u003cp\u003eThe definitions of engraftment, OS, LFS, nonrelapse mortality (NRM), and relapse were used as described previously. \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e Acute GVHD was diagnosed and graded based on published criteria by evaluating the pattern and severity of organ involvement. \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e Chronic GVHD was defined and graded as mild, moderate, or severe, in accordance with the National Institute of Health criteria. \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e Relapse was defined by morphological evidence of disease in the peripheral blood, bone marrow, or extramedullary sites. \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e Patients who had a prior history of myeloproliferative neoplasm (MPN) or myelodysplastic syndrome (MDS) were diagnosed with secondary AML. \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e The risk stratification of AML patients was assessed by using both European LeukemiaNet (ELN) 2017 and ELN 2022. The determination of risk categories for ELN 2017 and ELN 2022 was based on the ELN 2017 guidelines \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e and the ELN 2022 guidelines, \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation Endpoints\u003c/h2\u003e \u003cp\u003eThe primary endpoint of the study was the cumulative incidence of posttransplantation MRD. The secondary endpoints were the cumulative incidence of relapse and NRM, the probabilities of OS and LFS, the incidence of acute and chronic GVHD, and the engraftment rate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003ePatient characteristics were compared by using Pearson's chi-square test for categorical variables and the Kruskal‒Wallis test for continuous variables. The competing risk setting was used to evaluate cumulative incidence, with relapse treated as a competing event for NRM and with death from any cause as a competing risk for GVHD and relapse. The probabilities of OS and LFS were estimated by using the Kaplan‒Meier method. Variables in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were included in the univariate analysis. Only the characteristics with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1 were selected for multivariate analysis by using a Cox proportional hazard model that was built for time-to-event outcomes, and a forward selection procedure was implemented. Two-sided \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered to indicate statistical significance. The analysis was performed with SPSS 22.0 (Mathsoft, Seattle, WA, USA) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).\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 and donor characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosttransplantation MRDpos\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient age, yr (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (1\u0026ndash;64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (1\u0026ndash;59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient sex, n (%)\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 \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\u003e262 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (53.8)\u003c/p\u003e \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\u003e216 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (46.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient height, cm (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165 (73\u0026ndash;190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165 (76\u0026ndash;186)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient weight, kg (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (8-115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (8-109)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease type, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary AML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e450 (94.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (92.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary AML\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eELN 2017, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.5)\u003c/p\u003e \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\u003e249 (52.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (53.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (27.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eELN 2022, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFavorable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (26.2)\u003c/p\u003e \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\u003e203 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (35.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (38.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime from diagnosis to transplant, month (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0 (2-55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0 (2.5\u0026ndash;18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e405 (84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (75.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;CR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePretransplantation MRDpos, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (25.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (55.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransplant modality, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaplo-HSCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e375 (78.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (81.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSDT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUDT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDonor-recipient relationship, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParent‒child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSibling-sibling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild‒parent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (35.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDonor-recipient sex match, n (%)\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 \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\u003e190 (39.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (38.5)\u003c/p\u003e \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\u003e142 (29.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (27.7)\u003c/p\u003e \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\u003e77 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (13.8)\u003c/p\u003e \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\u003e69 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (20.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA-A, B, DR mismatched loci, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (9.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e325 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (70.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDonor-recipient ABO match, n (%)\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 \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\u003e276 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (55.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor mismatch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (24.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinor mismatch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBidirectional mismatch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMononuclear cells per graft, \u0026times;10\u003csup\u003e8\u003c/sup\u003e/kg (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8 (3.3\u0026ndash;19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6 (3.9\u0026ndash;19.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD34\u003csup\u003e+\u003c/sup\u003e cells per graft, \u0026times;10\u003csup\u003e6\u003c/sup\u003e/kg (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.4 (0.2\u0026ndash;13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6 (0.2\u0026ndash;13.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterventions for posttransplantation MRDpos, n (%)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy combined with DLI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (16.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFNα\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTargeted drug (Sorafenib or Nilotinib)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReduce or discontinue immunosuppressants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo or more interventions mentioned above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (30.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.2)\u003c/p\u003e \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\u003e5 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (7.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up, d (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e542 (23-1738)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e491 (65-1588)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up of survivors, d (median, range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e583 (144\u0026ndash;1738)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e694 (202\u0026ndash;1588)\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\n\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: MRD=minimal residual disease; pos=positive; AML=acute myeloid leukemia; ELN=European LeukemiaNet; CR=complete remission; NR=nonremission; HLA=human leukocyte antigen; Haplo-HSCT=haploidentical hematopoietic stem cell transplantation; MSDT=HLA-matched sibling donor transplantation; MUDT=HLA-matched unrelated donor transplantation; DLI=donor lymphocyte infusion; IFN\u0026alpha;= interferon-\u0026alpha;.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eA total of 478 eligible patients were enrolled in this study. Patient and donor clinical characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age of the patients was 33 years. The patients were either diagnosed with primary AML (94.1%) or secondary AML (5.9%). The majority of patients were in CR1 before allo-SCT (n\u0026thinsp;=\u0026thinsp;405, 84.7%). Most patients underwent haplo-SCT (78.5%), followed by MSDT (19.2%) and MUDT (2.3%). One hundred and twenty patients had positive pre-SCT MRD (25.1%), and the median pre-SCT MRD was 0.79% (range: 0.01\u0026ndash;43.01%). Sixty-five patients developed post-SCT MRD (13.6%). The median value of the first post-SCT MRD was 0.15% (range: 0.01\u0026ndash;5.30%), and the median time for the emergence of positive MRD after allo-SCT was 139 days (range: 24-1141 days) posttransplantation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHematopoietic Engraftment and Transplantation Outcomes\u003c/h2\u003e \u003cp\u003eAll but one patient achieved myeloid engraftment by 30 days after allo-HSCT. Among the 477 evaluable patients, the median times of neutrophil and platelet engraftment were 13 (range: 9\u0026ndash;27) days and 14 (range: 6-215) days posttransplantation, respectively.\u003c/p\u003e \u003cp\u003eThe median follow-up times for all of the patients and for those who survived were 542 (range: 23-1738) days and 583 (range: 144\u0026ndash;1738) days after allo-SCT, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The 3-year OS and LFS were 76.2% (95% confidence interval [CI]: 70.8\u0026ndash;82.1%) and 73.1% (95% CI: 67.6\u0026ndash;79.2%), respectively. The cumulative incidences of relapse and NRM at 3 years were 20.0% (95% CI: 14.5\u0026ndash;25.5%) and 6.9% (95% CI: 4.5\u0026ndash;9.3%), respectively. The 100-day cumulative incidence of Grade II-IV acute GVHD and the 3-year cumulative incidence of chronic GVHD were 21.1% (95% CI: 17.4\u0026ndash;24.8%) and 51.0% (95% CI: 45.4\u0026ndash;56.6%), respectively. Positive post-SCT MRD was observed in 65 patients. The cumulative incidences of positive post-SCT MRD at 100 days, at 360 days and at 3 years following allo-SCT were 4.6% (95% CI: 2.7\u0026ndash;6.5%), 12.1% (95% CI: 9.1\u0026ndash;15.1%) and 18.3% (95% CI: 12.8\u0026ndash;23.8%), respectively. Patients with positive post-SCT MRD status had a greater CIR and lower LFS, as well as OS, than did those with negative post-SCT MRD status (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-C). Patients with positive post-SCT MRD at 360 days experienced a greater CIR and lower LFS and OS than did those without detectable post-SCT MRD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all); moreover, they had a shorter OS than did patients with positive post-SCT MRD after 360 days (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-F). Patients with positive post-SCT MRD after 360 days had a greater CIR (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017) but comparable survival to those with negative post-SCT MRD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-F).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRisk Factors for Positive Posttransplantation MRD in All Patients\u003c/h2\u003e \u003cp\u003eIn the total population, patients who were positive for pre-SCT MRD were more likely to have positive post-SCT MRD and CIR, as well as lower LFS and OS, than were those who were negative for pre-SCT MRD (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-D\u003c/b\u003e). Multivariate analysis demonstrated that positive pre-SCT MRD (hazard ratio: [HR] 4.479, 95% CI: 2.744\u0026ndash;7.310, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was associated with post-SCT MRD positivity.\u003c/p\u003e \u003cp\u003eAt 360 days after transplantation, the cumulative incidence of positive post-SCT MRD was significantly greater in patients with positive pre-SCT MRD than in those with negative pre-SCT MRD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eFigure S2A\u003c/b\u003e). The cumulative incidence of post-SCT MRD positivity was significantly greater in patients with adverse prognoses than in those with favorable or intermediate prognoses according to the ELN 2017 risk stratification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031) (\u003cb\u003eFigure S2B\u003c/b\u003e). The associations of the ELN 2017 risk stratification with other transplant outcomes are shown in \u003cb\u003eFigure S2C-E\u003c/b\u003e. Multivariate analysis demonstrated that positive pre-SCT MRD (HR: 4.449, 95% CI: 2.598\u0026ndash;7.617, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and the ELN 2017 risk stratification (adverse versus favorable combined with intermediate: HR: 1.790, 95% CI: 1.008\u0026ndash;3.180, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047) were related to positive post-SCT MRD.\u003c/p\u003e \u003cp\u003eAt 100 days after allo-SCT, the cumulative incidence of positive post-SCT MRD was significantly greater in patients with positive pre-SCT MRD than in patients with negative pre-SCT MRD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (\u003cb\u003eFigure S3A\u003c/b\u003e). The cumulative incidence of post-SCT MRD positivity was significantly greater in patients with adverse prognoses than in patients with favorable or intermediate prognoses according to the ELN 2022 risk stratification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011) \u003cb\u003e(Figure S3B\u003c/b\u003e). Patients with an adverse prognosis according to the ELN 2022 risk stratification had a greater CIR but comparable LFS and OS compared with those with a favorable prognosis combined with an intermediate prognosis according to the ELN 2022 risk stratification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021, 0.108, and 0.155, respectively). Multivariate analysis indicated that pre-SCT MRD (HR: 8.197, 95% CI: 3.206\u0026ndash;20.957, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and ELN 2022 (adverse versus favorable combined with intermediate: HR: 2.709, 95% CI: 1.170\u0026ndash;6.274, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020) were associated with post-SCT MRD positivity. However, ELN 2022 risk stratification had no significant impact on post-SCT MRD positivity at 360 days or overall post-SCT MRD positivity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.221 and 0.098, respectively) (\u003cb\u003eFigure S3C-D\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eA Scoring System for Post-SCT MRD and Transplant Outcomes in All Patients\u003c/h2\u003e \u003cp\u003eWhen considering the association of positive pre-SCT MRD and ELN 2017 risk stratification with positive post-SCT MRD, we established a scoring system based on pre-SCT MRD and ELN 2017 risk stratification for predicting post-SCT MRD at 360 days after allo-HSCT. The scoring system utilized negative and positive pre-SCT MRD scores of 0 and 1, respectively. Favorable combined with intermediate prognosis and adverse prognosis in the ELN 2017 risk stratification were scored as 0 and 1, respectively. According to the scoring system, patients were stratified into three groups, including the low-risk group, with a score of 0 (n\u0026thinsp;=\u0026thinsp;286, 59.8%); the medium-risk group, with a score of 1 (n\u0026thinsp;=\u0026thinsp;162, 33.9%); and the high-risk group, with a score of 2 (n\u0026thinsp;=\u0026thinsp;30, 6.3%).\u003c/p\u003e \u003cp\u003eThe cumulative incidence of positive post-SCT MRD at 3 years was 13.2%, 23.6%, and 43.9% for patients in the low-risk, medium-risk, and high-risk groups, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The cumulative incidence of post-SCT MRD positivity at 360 days was 6.0%, 19.2%, and 34.6% for patients in the low-risk, medium-risk, and high-risk groups, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B). Multivariate analysis demonstrated that the scoring system was associated with post-SCT MRD positivity at 360 days and 3 years after allo-SCT (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, patients in the medium-risk and high-risk groups experienced a greater CIR and lower LFS and OS than patients in the low-risk group, whereas patients in the high-risk group had a greater CIR and a trend toward lower LFS and OS than did those in the medium-risk group according to the scoring system (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-E). Multivariate analysis indicated that the risk score was associated with leukemia relapse and LFS (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analysis of the associations between posttransplantation MRD and transplant outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCovariates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePosttransplantation MRD at 360 days after allo-HSCT\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe scoring system\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe low-risk group (risk score 0)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe medium-risk group (risk score 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.923\u0026ndash;6.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.923\u0026ndash;6.520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe high-risk group (risk score 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.386\u0026ndash;17.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.386\u0026ndash;17.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status\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 \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;CR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.597\u0026ndash;3.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.697\u0026ndash;7.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePosttransplantation MRD\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe scoring system\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe low-risk group (risk score 0)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe medium-risk group (risk score 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.790\u0026ndash;5.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.790\u0026ndash;5.317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe high-risk group (risk score 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.907\u0026ndash;13.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.907\u0026ndash;13.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status\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 \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;CR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.519\u0026ndash;2.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.830\u0026ndash;7.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRelapse\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe scoring system\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe low-risk group (risk score 0)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe medium-risk group (risk score 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.290\u0026ndash;3.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.977\u0026ndash;2.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe high-risk group (risk score 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.536\u0026ndash;9.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.832\u0026ndash;7.970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eELN 2022\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 \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFavorable\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\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\u003e1.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.860\u0026ndash;3.420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.245\u0026ndash;4.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;CR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.104\u0026ndash;4.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.152\u0026ndash;4.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.998\u0026ndash;9.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.866\u0026ndash;6.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeukemia-free survival\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe scoring system\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 \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe low-risk group (risk score 0)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe medium-risk group (risk score 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.122\u0026ndash;2.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.914\u0026ndash;2.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe high-risk group (risk score 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.535\u0026ndash;5.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.208\u0026ndash;4.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eELN 2022\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 \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFavorable\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\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\u003e1.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.739\u0026ndash;2.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdverse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.938\u0026ndash;2.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;CR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.083\u0026ndash;3.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.102\u0026ndash;3.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.098\u0026ndash;6.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.511\u0026ndash;4.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall survival\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe scoring system\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 \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe low-risk group (risk score 0)\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe medium-risk group (risk score 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.086\u0026ndash;2.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe high-risk group (risk score 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.530\u0026ndash;5.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease status\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;CR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.020\u0026ndash;3.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.020\u0026ndash;3.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.344\u0026ndash;7.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.344\u0026ndash;7.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\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\u003cp\u003e\u003cstrong\u003eAbbreviations\u003c/strong\u003e: MRD=minimal residual disease; HR=hazard ratio; CI=confidence interval; allo-HSCT=allogeneic hematopoietic stem cell transplantation; CR=complete remission;\u0026nbsp;NR=nonremission; ELN=European LeukemiaNet.\u003c/p\u003e\n\u003cp\u003e* Variables in Table 1 were first included in the univariate analysis,\u0026nbsp;and\u0026nbsp;only the\u0026nbsp;variables\u0026nbsp;with \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.1 were selected for multivariate analysis by using a Cox proportional hazard model.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large-sample prospective study, we provided further evidence indicating that positive pre-SCT MRD was an independent risk factor for post-SCT MRD positivity in patients with AML, which has been previously reported by other researchers. \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e In addition to pretransplant MRD, the ELN 2017 risk stratification and the ELN 2022 stratification were identified for the first time as being two risk factors for positive posttransplantation residual disease. Furthermore, we developed a novel scoring system based on pre-SCT MRD and ELN 2017 risk stratification, which could stratify transplant recipients with AML into three subgroups with different cumulative incidences of post-SCT MRD positivity. Therefore, our study provides a new risk factor and scoring system for positive post-SCT residual disease in AML patients who received allogeneic transplantations.\u003c/p\u003e \u003cp\u003eIn agreement with previous studies, \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e we further confirmed the strong association of positive pre-SCT MRD with posttransplant MRD positivity in recipients with AML. In a retrospective study reported by Zhou et al., 279 adults with AML, including HLA-matched siblings (n\u0026thinsp;=\u0026thinsp;114) and unrelated donor transplantations (n\u0026thinsp;=\u0026thinsp;165), received myeloablative allogeneic HCT. They showed that the percentages of post-MRD positivity in 216 patients who had no MFC evidence of MRD before transplantation and those with MFC evidence of residual disease pre-SCT were 0.7% and 5%, respectively. \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e In another retrospective study, 146 patients with AML who received allografts from sibling, unrelated, or hapolidentical donors were enrolled. Kim et al. reported that the percentages of patients with positive NGS evidence of residual disease in a group of patients who were pre-MRD-positive and those who were MRD-negative before transplantation were 1.5% and 15.9%, respectively. \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e The results reported by others \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e, as well as our data, suggest that positive pre-SCT MRD determined by either MFC, Q-PCR, or NGS is a risk factor for posttransplantation residual disease positivity in AML patients who either receive HLA-matched or mismatched allo-SCT. Several studies have suggested that the contribution of positive pre-SCT residual disease to post-SCT residual disease positivity could be related to HLA loss or decreased expression of HLA class II antigens, which results in evasion from donor immune cells. \u003csup\u003e[\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e However, further studies are warranted to elucidate the underlying mechanisms that contribute to drug resistance and immune escape of pre-SCT residual AML cells in allo-SCT settings.\u003c/p\u003e \u003cp\u003eConsistent with previous studies, \u003csup\u003e[\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e in the present study, we confirmed the association of the ELN 2017 risk stratification and the ELN 2022 risk stratification with leukemia relapse. Impressively, we identified ELN 2022 risk stratification and ELN 2017 risk stratification as being risk factors for post-SCT MRD positivity on Day 100 and day 360 following transplantation, respectively. When considering that the onset of residual disease after transplantation contributes to subsequent hematological relapse and that MRD-directed therapy can decrease the CIR and improve survival, as reported by others and our group, \u003csup\u003e[\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e our results provide new evidence suggesting that the ability of ELN risk stratification to predict the onset of post-SCT MRD may provide us with an opportunity to identify high-risk patients who will experience positive MRD. Thus, they can adopt maintenance or prophylaxis therapy before hematological relapse.\u003c/p\u003e \u003cp\u003eIn this study, we developed a new scoring system for post-SCT MRD positivity to help physicians in identifying AML patients at high risk of relapse. The system combined pre-SCT MRD and ELN 2017 risk stratification to classify patients into different risk categories (statistically and clinically) with respect to the cumulative incidence of post-SCT residual disease, CIR, LFS, and OS (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, this novel scoring system should be interpreted with caution. First, these data were obtained from unmanipulated allografts, and further studies regarding other transplant modalities, such as haplo-SCT with PT-Cy, \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e allo-SCT with T-cell depletion \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e and cord blood transplantation \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e, are needed to confirm the effects of the scoring system on posttransplant MRD positivity and other outcomes. Second, further prospective, multicenter studies should be performed on older transplant recipients and those with different ethnic origins (nonoriental).\u003c/p\u003e \u003cp\u003eThis research, although it was prospective and included a large number of patients, was limited by its single-center nature. The small number of patients with positive posttransplantation MRD results made it difficult to perform subgroup analysis, such as grouping pretransplantation MRD according to different values or grouping patients based on different transplant modalities. Therefore, prospective, multicenter studies with larger sample sizes are needed in the future to answer the abovementioned questions.\u003c/p\u003e \u003cp\u003eIn summary, our results indicated that pre-SCT residual disease as well as ELN 2017 risk stratification and ELN 2022 risk stratification were useful for predicting posttransplantation MRD in AML transplant recipients. The novel risk score system based on pre-SCT MRD and ELN 2017 risk stratification can predict posttransplantation MRD positivity and refine the risk stratification. The results of our study provide single or combination variables that can identify a specific population of patients who are candidates for prophylaxis or early preemptive therapy to decrease posttransplant relapse.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all of the faculty members who participated in these studies. We would also like to thank the American Journal Experts (www.aje.com) for assistance in editing this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was partly supported by grants from the National Natural Science Foundation of China (82293630 and 82293633); the Beijing Municipal Science and Technology Commission (Z221100007422008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContribution: Y.-J.C. designed the study; Y.-J.C., C.-Z. Y., and S.-Q. L. collected data; Y.-J.C., S.-Q. L., and C.-Z. Y. analyzed the data and drafted the manuscript; all authors contributed to data interpretation, manuscript preparation, and approval of the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors\u0026nbsp;declare\u0026nbsp;that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the conclusions of this article is available from the corresponding author (please contact [email protected]) upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eXu LP, Lu PH, Wu DP, Sun ZM, Liu QF, Han MZ, et al. Hematopoietic stem cell transplantation activity in China 2019: a report from the Chinese Blood and Marrow Transplantation Registry Group. \u003cem\u003eBone Marrow Transplant\u003c/em\u003e. 2021;56(12):2940-2947.\u003c/li\u003e\n\u003cli\u003ePassweg JR, Baldomero H, Chabannon C, Basak GW, de la C\u0026aacute;mara R, Corbacioglu S, et al. Hematopoietic cell transplantation and cellular therapy survey of the EBMT: monitoring of activities and trends over 30 years. \u003cem\u003eBone Marrow Transplant\u003c/em\u003e. 2021;56(7):1651-1664.\u003c/li\u003e\n\u003cli\u003eXu L, Chen H, Chen J, Han M, Huang H, Lai Y, et al. The consensus on indications, conditioning regimen, and donor selection of allogeneic hematopoietic cell transplantation for hematological diseases in China-recommendations from the Chinese Society of Hematology. \u003cem\u003eJ Hematol Oncol\u003c/em\u003e. 2018;11(1):33.\u003c/li\u003e\n\u003cli\u003eWang Y, Chen H, Chen J, Han M, Hu J, Jiong Hu, et al. 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Cord blood transplant for acute myeloid leukaemia. \u003cem\u003eBr J Haematol\u003c/em\u003e. 2016;173(1):25-36.\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":"Acute myeloid leukemia, Measurable residual disease, Risk factors, ELN 2017 risk stratification","lastPublishedDoi":"10.21203/rs.3.rs-4438416/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4438416/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe aimed to explore the risk factors for measurable residual disease (MRD) positivity after allogeneic stem cell transplantation (allo-SCT) in AML patients. A total of 478 AML patients receiving allo-SCT were prospectively enrolled. The cumulative incidences of post-SCT MRD positivity at 100 days, 360 days and 3 years were 4.6%, 12.1% and 18.3%, respectively. Positive pre-SCT MRD was a risk factor for post-SCT MRD positivity at both 360 days and 3 years (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). European LeukemiaNet (ELN) 2022 and 2017 risk stratification was a risk factor for positive post-SCT MRD at 100 days and 360 days (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020 and 0.047, respectively). A scoring system for predicting post-SCT MRD positivity at 360 days was established by using pre-SCT MRD and ELN 2017 risk stratification. The cumulative incidence of positive post-SCT MRD at 3 years was 13.2%, 23.6%, and 43.9% for patients with scores of 0, 1, and 2, respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariate analysis demonstrated that the scoring system was associated with a higher cumulative incidence of post-SCT MRD positivity, leukemia relapse and inferior survival. Our data indicate that positive pre-SCT MRD status, ELN 2022 risk stratification and 2017 risk stratification are independent risk factors for positive post-SCT MRD status in AML patients.\u003c/p\u003e","manuscriptTitle":"Pretransplantation risk factors for MRD after allogeneic stem cell transplantation in AML patients: A prospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-07 17:42:57","doi":"10.21203/rs.3.rs-4438416/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-06-12T10:43:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-06-10T16:23:57+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-06-10T03:51:15+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-05-27T05:54:52+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-05-27T03:57:10+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-05-21T13:41:19+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-05-21T12:19:15+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-05-21T11:15:36+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-20T11:10:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bone Marrow Transplantation","date":"2024-05-17T19:21:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-17T19:21:59+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":"c475eb76-a088-47c9-b482-20b378591f6e","owner":[],"postedDate":"June 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32200626,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Leukaemia/Acute myeloid leukaemia"},{"id":32200627,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-11-17T08:07:08+00:00","versionOfRecord":{"articleIdentity":"rs-4438416","link":"https://doi.org/10.1038/s41409-024-02466-1","journal":{"identity":"bone-marrow-transplantation","isVorOnly":false,"title":"Bone Marrow Transplantation"},"publishedOn":"2024-11-16 05:00:00","publishedOnDateReadable":"November 16th, 2024"},"versionCreatedAt":"2024-06-07 17:42:57","video":"","vorDoi":"10.1038/s41409-024-02466-1","vorDoiUrl":"https://doi.org/10.1038/s41409-024-02466-1","workflowStages":[]},"version":"v1","identity":"rs-4438416","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4438416","identity":"rs-4438416","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}