Chen, Yi‐Bin

Abstract Graft-versus-host disease (GVHD) is a major cause of nonrelapse mortality (NRM) after allogeneic hematopoietic cell transplantation. Algorithms containing either the gastrointestinal (GI) GVHD biomarker amphiregulin (AREG) or a combination of 2 GI GVHD biomarkers (suppressor of tumorigenicity-2 [ST2] + regenerating family member 3 alpha [REG3α]) when measured at GVHD diagnosis are validated predictors of NRM risk but have never been assessed in the same patients using identical statistical methods. We measured the serum concentrations of ST2, REG3α, and AREG by enzyme-linked immunosorbent assay at the time of GVHD diagnosis in 715 patients divided by the date of transplantation into training (2004-2015) and validation (2015-2017) cohorts. The training cohort (n = 341) was used to develop algorithms for predicting the probability of 12-month NRM that contained all possible combinations of 1 to 3 biomarkers and a threshold corresponding to the concordance probability was used to stratify patients for the risk of NRM. Algorithms were compared with each other based on several metrics, including the area under the receiver operating characteristics curve, proportion of patients correctly classified, sensitivity, and specificity using only the validation cohort (n = 374). All algorithms were strong discriminators of 12-month NRM, whether or not patients were systemically treated (n = 321). An algorithm containing only ST2 + REG3α had the highest area under the receiver operating characteristics curve (0.757), correctly classified the most patients (75%), and more accurately risk-stratified those who developed Minnesota standard-risk GVHD and for patients who received posttransplant cyclophosphamide-based prophylaxis. An algorithm containing only AREG more accurately risk-stratified patients with Minnesota high-risk GVHD. Combining ST2, REG3α, and AREG into a single algorithm did not improve performance.

PURPOSE Allogeneic hematopoietic cell transplantation (HCT) improves outcomes for patients with AML harboring an internal tandem duplication mutation of FLT3 ( FLT3-ITD) AML. These patients are routinely treated with a FLT3 inhibitor after HCT, but there is limited evidence to support this. Accordingly, we conducted a randomized trial of post-HCT maintenance with the FLT3 inhibitor gilteritinib (ClinicalTrials.gov identifier: NCT02997202 ) to determine if all such patients benefit or if detection of measurable residual disease (MRD) could identify those who might benefit. METHODS Adults with FLT3-ITD AML in first remission underwent HCT and were randomly assigned to placebo or 120 mg once daily gilteritinib for 24 months after HCT. The primary end point was relapse-free survival (RFS). Secondary end points included overall survival (OS) and the effect of MRD pre- and post-HCT on RFS and OS. RESULTS Three hundred fifty-six participants were randomly assigned post-HCT to receive gilteritinib or placebo. Although RFS was higher in the gilteritinib arm, the difference was not statistically significant (hazard ratio [HR], 0.679 [95% CI, 0.459 to 1.005]; two-sided P = .0518). However, 50.5% of participants had MRD detectable pre- or post-HCT, and, in a prespecified subgroup analysis, gilteritinib was beneficial in this population (HR, 0.515 [95% CI, 0.316 to 0.838]; P = .0065). Those without detectable MRD showed no benefit (HR, 1.213 [95% CI, 0.616 to 2.387]; P = .575). CONCLUSION Although the overall improvement in RFS was not statistically significant, RFS was higher for participants with detectable FLT3-ITD MRD pre- or post-HCT who received gilteritinib treatment. To our knowledge, these data are among the first to support the effectiveness of MRD-based post-HCT therapy.

Introduction: Risk stratification approaches using clinical criteria or biomarkers in acute graft-versus-host disease (GVHD) have traditionally been implemented at diagnosis or initiation systemic treatment with corticosteroids. For patients who require second-line treatment, the significance of biomarkers at salvage therapy and the relationship between biomarker risk and choice of therapy are unknown. Methods: We studied adult patients who received second-line treatment for acute GVHD between January 2016 and December 2021 in the Mount Sinai Acute GVHD Consortium (MAGIC) database, which collects clinical data and longitudinal serum samples from allogeneic HCT recipients using a rigorous PRoBE study design. Exclusion criteria included relapse of underlying malignant disease prior to second-line therapy, missing response data, or missing serum sample. Serum samples collected from 7 days prior to 3 days after initiation of second-line therapy met criteria for biomarker analysis. The MAGIC algorithm probability (MAP) was calculated as a single value based on concentrations of ST2 and REG3α and was stratified at a threshold of 0.290 to define high MAP and low MAP groups. The primary objective evaluated the association between MAP and survival for patients receiving second-line therapy for acute GVHD. The key secondary objective was to investigate the MAP and choice of second-line systemic agent on Day 28 overall response rate (ORR) and survival. Results: In total, 316 adult patients received second-line treatment for acute GVHD; 149 patients (47%) were excluded for disease relapse (n=27), missing response data (n=48), or missing sample (n=74).Of the 167 evaluable patients, most had steroid-refractory acute GVHD (n=146, 87%), rather than steroid-dependent (n=8, 5%) or steroid-sensitive (n=14, 8%) disease. 62 patients received ruxolitinib while 102 received other systemic agents (best available therapy: BAT). Baseline clinical characteristics of the study population according to treatment choice were similar, except for donor type (Rux: MRD 15%, MUD 74%, haplo 11%; BAT: MRD 30%, MUD 67%, haplo 3%; P=0.014) and median days from corticosteroids to second-line treatment (Rux: 18, BAT: 12; P=0.02).In total, 81 patients had high MAPs and 86 patients had low MAPs, with similar distribution in each treatment cohort (P=0.53). For the entire cohort, the median follow-up for survivors was 22 months (range, 1.5-27).The MAP separated patients into 2 groups (high vs low) with significantly different mortality (NRM at 2 years, 76% vs 29%, P<.0001) and survival (OS at 2 years, 12% vs 63%, P<.0001). Patients who received ruxolitinib as second-line therapy had lower mortality (NRM at 2 years, 35% vs 60%, P<.002) and improved survival (OS at 2 years, 51% vs 32%, P<.008), compared to those who received other systemic agents. However, the outcomes of patients with high MAP were poor, regardless of second-line treatment choice ( Figure 1A). The MAP (low vs high), time from corticosteroids to second-line treatment (≥14 days vs < 14 days), GVHD grade at second-line (0-2 vs 3-4), and choice of second-line therapy (Rux vs BAT) were all significant (P<0.05) predictors of lower NRM and higher OS in multivariate analysis. The MAP also separated patients into 2 groups with significantly different D28 ORR (low: 49%, high: 30%, P<.0001). In agreement with prospective trials, ruxolitinib resulted in higher D28 response rates compared to other systemic therapies (ORR 54.9% vs 30.5%, P=0.005), which was observed in both low MAP (ORR, 64.5% vs 38.5%, P=0.017) and high MAP cohorts (ORR, 42.9% vs 22.6%, P=0.06) ( Figure 1B). The MAP (low vs high), GVHD grade at second line (0-2 vs 3-4), and choice of second-line therapy (Rux vs BAT) were significant predictors (P<0.05) of higher D28 ORR in multivariate analysis. Conclusion: The MAP measured at the initiation of second-line systemic treatment for acute GVHD predicts NRM and OS, as well as treatment response. The outcomes of patients with high MAP are poor, regardless of second-line treatment choice, and the higher CR rate in low MAP patients may drive higher survival rates. Incorporation of MAP into clinical trials in this setting warrants investigation. The results also support the current use of ruxolitinib as second-line treatment for acute GVHD, particularly in patients with low MAP.

Background: BMT CTN 1506/MORPHO was a randomized study of the FLT3 inhibitor gilteritinib versus placebo as post-transplant (HCT) maintenance therapy for patients (pts) with FLT3-ITD acute myeloid leukemia (AML). Patients with FLT3-ITD AML in first remission underwent HCT and then were randomized, in double-blind fashion, to either gilteritinib or placebo for 24 months. The primary endpoint was relapse-free survival (RFS), and a pre-specified secondary endpoint was the effect of measurable residual disease (MRD) on survival as detected by a highly sensitive assay for FLT3-ITD mutations. In the primary analysis, while RFS was higher for pts randomized to gilteritinib, the difference did not reach the pre-determined threshold for significance (HR: 0.679; 95% CI: 0.459, 1.005; 2-sided p-value: 0.0518). However, in the secondary analysis, the 50.6% of pts who had MRD detectable pre- or post-HCT had significantly higher RFS with gilteritinib (HR of relapse or death=0.515, 95% CI: 0.316, 0.838, p = 0.0065). In this post-hoc analysis, we examined 1) the impact on RFS of different levels of FLT3-ITD variant allele frequency (VAF) pre-randomization (immediately before or after HCT but prior to randomization to gilteritinib or placebo); 2) the impact of the presence of multiple mutations detected as MRD pre-HCT; and 3) the eradication of FLT3-ITD clones detected post-HCT during follow up on gilteritinib or placebo. Methods: First-pull marrow aspirates were collected from pts at two time points pre-randomization (pre-HCT and between 30-90 days post-HCT), as well as at 3, 6, 12, 18, and 24 months post-randomization. For MRD detection (performed at Invivoscribe; San Diego, CA), 700 ng input DNA was amplified by polymerase chain-reaction (PCR) using 25 cycles and primers flanking exons 14 and 15 of FLT3, followed by next-generation sequencing (NGS) analysis of the amplicons. Variant allele frequency (VAF) was calculated as FLT3 mutant reads/total FLT3 reads. For pts with multiple FLT3-ITD mutations, the VAF used in analysis was the sum of the VAFs for each FLT3-ITD variant. The lower limit of blank (LOB) of the assay is estimated to be 1 x 10 -6 VAF. For terminology, VAF > 1 x 10 -6 and < 1 x 10 -5 is referred to as MRD6, VAF > 1 x 10 -5 and < 1 x 10 -4 is MRD5, VAF > 1 x 10 -4 or greater is MRD4, and MRD0 equals no detectable MRD. Results: MRD was evaluated in 350/356 (98.3%) pts pre-HCT and 347/356 (97.5%) pts post-HCT. MRD was detected in 46% of pts pre-HCT and 19.9% prior to randomization, including 4.5% who did not have detectable MRD pre-HCT. The variant allele frequency (VAF) of detectable MRD ranged from a low of 1.09 x 10 -6 to a high of 3.0 x 10 -1. More than a single mutation was detected in 51 pts pre-HCT. Most of these 51 pts had 2 clones, but the total ranged from 2-9. The presence of more than one mutation detected as MRD immediately pre-HCT was associated with worse RFS compared with all other pts (MRD-positive with only one clone and MRD-negative), irrespective of treatment arm (Figure 1A; HR=2.428, 95% CI: 1.555, 3.792, P < 0.001). There was no significant difference in age, mutation length, VAF, or karyotype between pts with more than one mutation and those with single mutations. However, if the VAFs of pts with multiple FLT3-ITD mutations were summed and treated as a single value, then the median VAF for pts with multiple mutations was higher than for those with single mutations (2.14 x 10 -4 vs. 3.12 x 10 -5). The VAF (including the summed VAFs of pts with multiple mutations) at multiple levels correlated very closely with RFS after HCT. To illustrate this quantitative effect of peri-HCT FLT3-ITD VAF on RFS, Kaplan-Meier analysis of pts on the placebo arm grouped by MRD level is displayed in Figure 1B. In the 71 pts with MRD detectable post-HCT, the MRD was eradicated in 69% of pts on gilteritinib versus 44% of pts on placebo. Conclusions Pts with multiple FLT3-ITD mutations have a worse prognosis, which may simply be a reflection of increased disease burden (VAF). The quantity of FLT3-ITD MRD appears to highly correlate with outcome. Gilteritinib appears to augment the effect of HCT, as evidenced by increased eradication of MRD post-HCT. These data illustrate the potential utility of the PCR-NGS FLT3-ITD MRD assay in the management of pts with FLT3-ITD AML.

Introduction Secondary central nervous system (CNS) involvement develops in 2-10% of large B-cell lymphoma (LBCL) cases. Current treatment approaches for relapsed or refractory CNS disease generally do not provide durable responses. Limited data suggest efficacy and feasibility of CAR-T therapy in SCNSL. We report here the largest multicenter retrospective analysis of the safety and efficacy of CD19-directed CAR-T therapy in SCNSL patients. Methods This study included SCNSL patients who received commercial CD19-directed CAR-T therapy at 9 academic institutions in the United States between 2016 and 2022. SCNSL was defined as history of parenchymal and/or leptomeningeal/cerebrospinal fluid (CSF) involvement by lymphoma at any time prior to receiving CAR-T therapy. Systemic response was assessed using the Lugano criteria while CNS response was assessed as per International PCNSL Collaborative Group criteria. Kaplan-Meier curves were generated for progression-free survival (PFS) and overall survival (OS) for entire cohort, as well as subsets of patients with and without active CNS disease at the time of CAR-T infusion. Results Ninety patients were included in the analysis, with baseline characteristics shown in Table 1. CAR-T products utilized include axicabtagene ciloleucel (n= 38, 42%), tisagenlecleucel (n=37, 41%) and lisocabtagene maraleucel (n= 15, 14%). Fludarabine/cyclophosphamide was used as lymphodepletion in 84 patients (93%). 28 patients received CNS directed radiation therapy (RT) prior to CAR-T infusion (31%) within a median time of 28.5 days (range 5 - 906) from last day of RT. Amongst all patients at the time of CAR-T infusion 82 (91.1%) had active CNS and/or systemic involvement while 8 (8.9%) had no evidence of disease; 68 (75.5%) had active CNS involvement while 22 (24.5%) had a prior history of CNS involvement but no active at the time of CAR-T infusion. ( Table 1) Median follow up all patients was 0.5 year (range 0.01 - 4.7). 71 patients (79%) developed cytokine release syndrome (CRS; median time to onset 3 days) with 3.3% patients developing Grade 3-4. Immune effector cell-associated neurotoxicity syndrome (ICANS; median time to onset 5 days) was reported in 55 patients (61%), with 28.8% developing Grade 3-4. No patients died due to CRS or ICANS. At 1-month post CAR-T, 80 patients were evaluable for CNS response and 71 patients in the entire cohort were evaluable for systemic response. Similarly, at 3-months these numbers were 66 and 60, respectively. Objective response rates (ORR) were 75% and 80% at 1-month for CNS and systemic disease respectively, while corresponding ORRs at 3-months were 68% and 76.7%. At 1- and 3-months timepoint 36 (45%) and 33 (50%) patients, respectively achieved CNS complete remission (CR), while 44 (62%) and 42 (70%) patients respectively achieved systemic CR. 1- and 2-year PFS for entire cohort were 25% (95%Cl 15% - 34%) and 16% (95%Cl 8.5% - 28%) respectively, while 1- and 2-year OS were 46% (95%Cl 36% - 59%) and 31% (95%Cl 22% - 46%). Non-relapse mortality (NRM) were 4.6% (95%CI, 1.8% -12%) and 7.2% (95%CI 2.9% - 18%) at 1- and 2-year. Cumulative incidence of relapse at 1- and 2-year were 73% (95%Cl 63% - 83%) and 77% (95%Cl 68% - 88%), respectively. ORRs for CNS response in patients with active CNS disease at 1-month and 3-month interval were 71% (n=45) and 60% (n=31). Similarly, ORR for systemic response with active CNS disease at 1-month and 3-month interval were 85% (n=43) and 74.3% (n=32).The 2-year PFS for patients with and without active CNS disease at CAR-T infusion were 12% (95%Cl 5.4% - 27%) and 28% (95%Cl 12% - 65%) respectively, with a corresponding OS of 25% (95%Cl 15% - 41%) and 58% (95%Cl 37% - 91%). ( Figure 1) The 2-year NRM rates for patients with and without active CNS disease at CAR-T infusion were 4.6% (95%Cl 1.5% - 14%) and 14% (95%Cl 3.6% - 53%) respectively, while the cumulative incidence of relapse in similar order were 83% (95%Cl 73% - 95%) and 58% (95%Cl 39% - 88%). Conclusion In this largest known case series to date, CAR-T therapy appeared safe and feasible in patients with SCNSL, but is associated with high rates of treatment failure, particularly in patients with active CNS disease at CAR-T infusion. This warrants further study of optimal CNS-directed treatment strategies prior to CAR-T, development of novel cellular therapy platforms or consideration of post CAR-T maintenance therapy in these high-risk patients.

[Background] The current standard first-line treatment for acute graft-versus-host disease (GVHD), systemic high-dose steroids, induces clinical responses in a majority of patients. Flares of GVHD after initial improvement often occur during tapering or discontinuation of immunosuppression. There is no consensus regarding the definition of GVHD flare and little has been published regarding its natural history. [Methods] We retrospectively evaluated clinical data and blood samples from 968 allogeneic hematopoietic cell transplantation (HCT) recipients from 23 Mount Sinai Acute GVHD International Consortium (MAGIC) transplant centers who achieved complete response (CR) or very good partial response (VGPR) within 4 weeks of acute GVHD treatment between 2014 and 2021. VGPR was defined as the complete resolution of acute GVHD manifestations except residual stage 1 skin disease. Flares were defined as a recurrence of acute GVHD after achievement of CR/VGPR if (1) patients had an increased symptom severity of at least 1 organ stage; (2) received intensified treatment (increase in steroid dose ≥ 0.25 mg/kg or initiation of additional systemic immunosuppression); and (3) had no prior history of primary disease relapse or donor lymphocyte infusion preceding the flare. Serum samples obtained at the time of CR/VGPR and at the time of flares were analyzed for ST2 and REG3α concentrations that generated MAGIC algorithm probabilities (MAPs) resulting in previously validated Ann Arbor (AA) scores (1, 2, and 3). [Results] The median recipient age at HCT was 55 years (range: 0 to 79); 18.6% of patients had grades III-IV acute GVHD before CR/VGPR. The median maximum daily dose of corticosteroids before CR/VGPR was 1 mg/kg methylprednisolone equivalent (range, 0.1 to 3.2 mg/kg). Flares developed within 6 months following CR/VGPR in 210/968 (21.7%) patients with a median onset of 28 days (range: 2 to 448). Symptom severity at the onset of flare symptoms varied widely (grade I: 22%; grade II: 38%; grade III-IV: 41%) and the development of a flare was associated with a five-fold increase in NRM (hazard ratio [HR], 4.84 [95% CI, 3.19-7.36], P < 0.001) when considered as a time-dependent covariate in a multivariate regression model. The large majority of non-relapse deaths after flares (54/71, 76%) were due to acute GVHD or complications from its treatment. The AA scores at the time of first CR/VGPR successfully stratified patients for risk of six-month NRM (AA1: 5%, AA2: 11%, AA3: 34%, P < 0.001) (Figure A). Increasing AA score at CR/VGPR was also associated with significantly increased risk of GVHD flares (Figure B). Not only did the risk of flare increase with each rising AA score, but the number of patients with severe (grade III/IV) symptoms at flare onset also increased (AA1: 34%, AA2: 43%, AA3: 54%). We next generated a multivariate regression model of risk factors for the development of flares. High AA scores at the time of CR/VGPR (AA2: HR, 1.81 [95% CI, 1.32-2.48], P = 0.001; AA3: HR, 3.14 [95% CI, 1.98-4.98], P < 0.001), HCT from HLA mismatched unrelated donor (HR, 1.74 [95% CI, 1.00-3.02], P = 0.049), and interestingly, rapid achievement of CR/VGPR from the time of initial treatment (≤14 days) (HR, 1.84 [95% CI, 1.21-2.80], P = 0.004) were all identified as significant risk factors. Meanwhile, no other transplant, GVHD, or treatment characteristics associated with the development of flares including maximum GVHD severity, maximum steroid dose, and use of additional immunosuppressive agents other than steroids before CR/VGPR. AA scores measured at the onset of flare symptoms in 98 patients also predicted six-month NRM (AA1, 6%; AA2, 19%; AA3 42%, P = 0.01). [Conclusion] Despite advances in treatment, flares of GVHD symptoms following excellent (CR/VGPR) responses still occur in over one fifth of patients in current practice and are associated with a five-fold increase in six-month NRM. AA scores from serum biomarkers predict outcomes despite the absence of symptoms, suggesting that MAGIC biomarkers detect subclinical damage to GI crypts that can drive later recrudescence of clinical GVHD. Measurement of the MAP at the time of response to GVHD treatment may thus help to risk-stratify tapering strategies of immunosuppressive therapy.

The overall response rate (ORR) 28 days (D28) after treatment has been adopted as the primary endpoint for clinical trials of acute graft versus host disease (GVHD). ORR combines complete response (CR) and partial response (PR) because CR and PR have very similar non relapse mortality (NRM). D28 ORR has some disadvantages: first, physicians usually decide to modify immunosuppression much earlier than D28, and second, NRM does not always correlate well with ORR at D28, particularly for patients who present with intermediate risk or low risk disease. MAGIC serum biomarkers at day 14 (D14) of GVHD treatment have been shown to correlate better with NRM than clinical symptom response (Srinagesh et al, Blood Advances, 2019). We therefore hypothesized that a combination of clinical symptom severity and biomarkers at D14 of treatment would predict NRM at least as well and possibly better than clinical response at D28. We studied 1144 patients from 23 MAGIC sites who were systemically treated with at least 0.25 mg/kg/day of systemic steroids (prednisone equivalents) and had clinical data and serum samples available in the MAGIC database and biorepository. We divided the patients into a training set (n=764) and a validation set (n=380). We used 12-month NRM from the time of acute GVHD onset as the primary outcome of interest. We first trained a recursive partitioning algorithm in the training set to create a response model (MAGIC D14 clinical response) according to overall GVHD grade at both onset and D14 that predicted 12-month NRM and then applied it to the validation set. Patients that either progressed to grade III/IV GVHD, continued having grade III/IV GVHD, or only improved to grade II at D14 from grade III/IV at D0 had high NRM and were classified as non-responders. Patients with grade I/II GVHD at day 0 who had grade 0-II GVHD at day 14 and patients who improved to grade 0/I at day 14 from grade III/IV at day 0 had low NRM and were classified as responders. Although counterintuitive, responders included patients whose GVHD remained at grade II because the 12 month NRM of this group was only 20%. The new clinical model predicted NRM as well as the D28 standard response model in the validation set. When we integrated the D14 MAP biomarker score (low: ≤ 0.290 vs high: >0.290) with the new D14 clinical response (D14 MAGIC integrated response), we observed three response groups of integrated response with strikingly different 12 month NRM (8%, 35%, 76%, p<0.001), in contrast to the D28 standard response (Figure 1A, 1B). D14 complete response required MAGIC clinical response with low MAP; D14 partial response required either MAGIC clinical response with high MAP or MAGIC clinical non-response with low MAP; and D14 non-response required MAGIC clinical non-response with high MAP. The D14 response groups also displayed significant differences in 12 month OS (82%, 58%, 14% respectively, p<0.001) We then compared the D14 integrated response with the D28 standard response for 12 month NRM prediction. This D14 integrated response model was superior for time-dependent AUC (0.78 vs 0.71, P=0.03), sensitivity (0.71 vs 0.54), positive predictive value (0.52 vs 0.48) and negative predictive value (0.92 vs 0.89), with minimal loss in specificity (0.85 vs 0.87) in the prediction of 12-month NRM compared to the D28 standard response model. Using decision curve analysis, the D14 integrated response displayed higher net benefit (correct identification of patients that will experience NRM by 12 months) over the whole range of threshold probabilities/preferences for changing immunosuppression when 12-month NRM was used as the outcome. We conclude first, that the definition of response that uses onset and D14 grades is as accurate as D28 ORR model; and second, that a model using clinical grades and biomarkers on D14 more accurately predicts long term NRM than the standard D28 definition and may be useful as a clinical trial endpoint.

Introduction: Detection of measurable residual disease (MRD) prior to allogeneic hematopoietic cell transplant (alloHCT) in patients with acute myeloid leukemia (AML) in remission is associated with increased relapse and inferior survival after transplant. We recently reported that next-generation sequencing (NGS) detection of mutated NPM1 or FLT3-ITD in first complete remission (CR1) blood prior to alloHCT is strongly associated with increased relapse and death (PMID: 36881031). However, the prognostic implications of detecting persistence of other common AML-associated mutations at this treatment landmark remain incompletely defined. Around 20% of patients diagnosed with AML have variants in isocitrate dehydrogenase ( IDH) genes (~7% for IDH1) and clinical outcomes are known to differ due to co-occurrence of other mutations, IDH subtypes, treatment strategies, and patient factors. Studies have examined the relationship between residual IDH1 variants ( IDH1m) in CR and subsequent clinical outcomes, but definitive standardized evidence to inform decision-making for the clinical utility of IDH1m as a target for AML MRD testing was not previously available. Methods: Adult patients undergoing alloHCT for IDH1 mutated AML in CR1 at CIBMTR sites in the USA between 2013-2019 were eligible for the study if remission blood sample collected within 100 days before alloHCT and outcome data were available. Ultrasensitive error-corrected NGS (NGS-MRD) targeting IDH1, NPM1, and FLT3 genes was performed on DNA from pre-conditioning blood to identify residual variants. Detected IDH1m were validated by digital droplet PCR (ddPCR). The day of transplant was considered as day 0. Median follow-up time was calculated for censored patients. Overall survival (OS) was estimated using Kaplan-Meier (log-rank tests) and Cox proportional hazards models (forward selection); cumulative incidence of relapse was examined using Fine-Gray regression models with non-relapse mortality as a competing risk. Results: A total of 148 patients were included in the study, with a median follow-up time of 24 months. Relapse was observed in 37 (25%) patients, with the majority occurring within 1 year after alloHCT (n = 28, 76%). Pre-transplant flow cytometry results were reported by the transplant centers for 97% of patients (n = 144), but no statistically significant differences in clinical outcomes were observed between the positive and negative groups (OS: p = 0.3; relapse: p = 0.07). 53 patients (36%) tested positive for IDH1m persistence in CR1, with a 100% validation rate by ddPCR for variants with an orthogonal assay available. Logistic regression indicated that IDH1m persistence in remission was more likely to occur in patients older than 40 years (OR: 1.02 with every 1-year increase after 40, p = 0.04). Clinical outcomes showed no statistically significant difference between the pre-alloHCT IDH1m positive and negative groups (Figure 1A), and this remained true after further subgroup analysis by age. The variant allele fraction (VAF) of the residual IDH1m ranged from 0.09% to 48.5% (median: 1.5%), and no differences in clinical outcomes were observed when stratifying by high (≥2.5%) or low VAF (<2.5%). Among patients with co-mutated NPM1 and/or FLT3-ITD at baseline (n=69), those with residual mutated NPM1 and/or FLT3-ITD in pre-transplant remission had significantly higher rates of relapse compared to those with residual IDH1m only or NGS-negative groups (p = 0.01, Figure 1B). The cohort excluding patients with co-mutated NPM1 and/or FLT3-ITD did not show any significant clinical outcome differences based on IDH1m persistence. Conditioning intensity did not show an association with clinical outcomes, and multivariable analysis for overall survival and relapse did not identify residual IDH1m as an important marker. Conclusion: Detection of persistent IDH1 variants in the blood of adult patients with AML in CR1 prior to first alloHCT is common, but not associated with increased relapse or death after transplant compared with those testing negative. For those patients with IDH1 mutated AML co-mutated with either NPM1 and/or FLT3-ITD, detection of persistent NPM1 and/or FLT3-ITD was associated with higher rates of relapse. These findings, from the largest study to date, do not support the detection of isolated IDH1 variants in CR1 blood prior to alloHCT as evidence of AML MRD or increased post-transplant relapse risk.

Introduction: Detection of measurable residual disease (MRD) in AML patients during remission is associated with adverse clinical outcomes after allogeneic hematopoietic cell transplant (alloHCT), including recent strong evidence from our group regarding residual NPM1 and/or FLT3-ITD variants (PMID: 36881031). Large studies examining the significance of other potential MRD targets, including isocitrate dehydrogenase isoform 2 ( IDH2), are needed. IDH2, which is mutated in approximately 12% of AML patients, is of particular interest due to the possibility of targeted clinical intervention. Methods: Patients over the age of 18 in first complete remission (CR1) with IDH2 mutated AML undergoing alloHCT transplant at a CIBMTR site between 2013-2019 with remission blood samples within 100 days of alloHCT and available clinical data were included in this study. Residual variants in IDH2, NPM1, and FLT3genes were detected by ultrasensitive error-corrected next-generation sequencing (NGS-MRD) on genomic DNA from pre-conditioning blood and validated by digital droplet PCR (ddPCR). The primary outcomes were overall survival (OS) and cumulative incidence of relapse with non-relapse mortality as a competing risk. The day of transplant was considered as time 0, and the median follow-up time was calculated for censored patients. Kaplan-Meier estimation (log-rank tests), Cox proportional hazards models, and Fine-Gray regression models were fitted to examine the clinical outcomes. Results: Among the 257 IDH2-mutated AML patients in this study, 57 (23%) experienced relapse, with 41 events occurring within 12 months after alloHCT. The median follow-up time was 25 months. Among 247 patients with pre-transplant remission flow cytometry results reported, 25% were positive, but no difference in rates of relapse or OS was observed between positive and negative patients. NGS MRD analysis detected residual IDH2 variants in remission samples of 130 patients (51%) with variant allele fraction (VAF) ranging from 0.05-56% (median: 3%), and 100% validation by ddPCR. NGS MRD IDH2 positive patients had increased rates of relapse (p = 0.03; 3yr: +11%, 95% CI: 0.2% to 22%) and decreased OS (p < 0.001; 3yr: -25%, 95% CI: -13% to -38%) compared to those who tested negative (Figure 1A). These OS differences were still observed between NGS MRD IDH2 positive and negative patients, regardless of age stratification (under 60yr p < 0.001, 3yr: -28%, 95% CI: -12% to -43%; over 60yr p = 0.04, 3yr: -19%, 95% CI: -1% to -40%); however, only patients over 60yrs had increased rates of relapse (p = 0.007; 3yr: +21, 95% CI: 6% to 36%). The impact of co-mutation status was examined by subdividing the cohort based on the presence of NPM1 or FLT3-ITD mutations at baseline. Residual IDH2 variants in patients without baseline NPM1 or FLT3-ITD co-mutations (n = 151) were associated with decreased OS and increased relapse ( IDH2+ vs IDH2-; OS p = 0.005, 3yr: -23%, 95% CI: -6% to -40%; Relapse p = 0.01, 3yr: +19, 95% CI: 6% to 32%; Figure 1B). In contrast, residual IDH2 variants were not predictive of relapse in co-mutated patients (n=106, p = 0.5). In these patients, the only prognostic marker for relapse was NPM1 and/or FLT3-ITD MRD, with similar relapse risk between IDH2 only positive and MRD negative groups (p < 0.001; 3yr: 83% vs. 11% vs. 15%; Figure 1B). In multivariable analysis, IDH2 MRD positivity was associated with decreased OS (HR 2.5, 95% CI: 1.5-4.2, p < 0.001) and increased rates of relapse (HR 2.1, 95% CI: 1.4-5.7, p = 0.003) after adjusting for other characteristics. Conclusion: In this study, we demonstrate that adult patients with IDH2-mutated AML who have IDH2 variants detected in CR1 prior to first alloHCT experienced increased relapse rates and decreased overall survival. However, this association is significant only in patients without baseline NPM1 and FLT3-ITD mutations. In co-mutated patients, NPM1 and/or FLT3-ITD MRD serve as superior prognostic markers. Subgroup analyses show the potential influence of factors such as conditioning intensity and age on clinical outcomes. Nevertheless, larger studies with balanced subgroups and more comprehensive baseline mutational information, including IDH2 mutation subtype, are needed to better define the clinical relevance of IDH2 MRD in this context.