Mangaonkar, Abhishek A.

Introduction Atrial fibrillation/flutter (Afib) contributes independently to the hematopoietic cell transplant comorbidity index (HCTCI) and is a known complication of allogeneic hematopoietic transplantation (AlloHCT) which has been linked to inferior outcomes, particularly in older patients. An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm to predict Afib and cardiac contractile dysfunction risk has been validated (Lancet 394:861, 2019). We hypothesized that assessment of pre-transplant Afib risk using the AI algorithm may predict future development of Afib and help identify patients at higher risk for this complication. Methods 191 consecutive MDS patients undergoing AlloHCT with curative intent using myeloablative (28.3%) or reduced intensity conditioning (62.3%) in the Mayo Clinic Comprehensive Cancer Center (Rochester, Jacksonville, Phoenix) between November 2015 and January 2022 were included in this retrospective analysis. Primary outcome was Afib within 100 days and 365 days of transplantation, and we also assessed the outcomes of Death and Relapse. Revised IPSS (IPSS-R) and HCTCI scores were included for all patients. Elevated Afib risk score using the AI algorithm was calculated from pre-transplant ECG, performed during vital organ testing at AlloHCT clearance. In addition to left ventricular (LV) ejection fraction (EF) we evaluated detailed echocardiographic (Echo) parameters including LV volume and mass indices, left atrial volume index (LAVI), maximum trans mitral flow velocities during LV filling (E velocity) and during the diastolic phase due to atrial contraction (A velocity), the velocity of the annulus away from the apex during the protodiastolic phase (e' velocity), E/A and E/e' ratios, the presence of valvular disease, and right ventricular systolic pressure (RVSP). We performed an analysis using a Cox proportional hazards regression models (adjusting for age and sex) to evaluate associations with Afib risk, Relapse, and Overall Survival. Results The median age was 64 years (18-75), 58.6% were male, 6.9% non-white race, and 3.7% Hispanic/Latino ethnicity. Most patients had an HCTCI score of 0-3 (76.3%). GVHD prophylaxis was predominantly with calcineurin inhibitor-based regimes plus/minus methotrexate or mycophenolate mofetil (83.8%). 5.2% of patients had a history of Afib before transplant. Non-relapse mortality was 7.9% at 100 days, and 18.3% at 365 days. N=25 patients (13.1%) developed Afib within 100 days, and n=28 (14.7%) within 1-year after AlloHCT. On multivariable analysis, Age [Hazard Ratio (HR) 2.83, 95% Confidence Interval (CI) 1.36-5.89, p=0.0055] and Echo parameters [including LAVI (HR 2.10, CI 1.23-3.58, p=0.0067), E velocity (HR 3.28, CI 1.29-8.80, p=0.013), E/A ratio (HR 3.74, CI 1.75-7.97, p=0.0006), E/e ' ratio (HR 1.81, CI 1.07-3.07, p=0.026) and RVSP (HR 1.68, CI 1.04-2.70, p=0.032)] were significantly associated with Afib risk; elevated AI risk score was significant in the univariate model (HR 2.74, CI 1.15-6.53, p=0.023) but was borderline in the multivariate model (HR 2.34, CI 0.98-5.60, p=0.056) ( Table 1). Based on previous observations we evaluated the association of AI and Echo parameters with Relapse and Death after AlloHCT ( Table 1). Age (HR 1.32, CI 1.01-1.71, p=0.041) and IPSS-R (HR 1.20, CI 1.08-1.33, p=0.0009) were significantly associated with Death after AlloHCT, while HCTCI (HR 1.10, CI 1.00-1.22, p=0.052) and higher LV EF (HR 0.63, CI 0.38-1.06, p=0.084) were borderline. For Relapse, only IPSS-R (HR 1.52, CI 1.31-1.75, p=1.22E-08) was significant, while increase Echo E velocity was of borderline significance (HR 0.45, CI 0.20-1.02, p=0.057). Conclusions Afib is a common post-AlloHCT complication and is more frequent with increasing Age. Echo parameters (specifically E/A ratio) predict significantly higher Afib risk, while the baseline ECG AI algorithm was of borderline significance. The selection of patients with lower HCTCI scores, and the low background prevalence of Afib in this cohort (i.e., selection of patients with lower baseline cardiac morbidity) are possible explanations for non-significance of the AI algorithm. As anticipated Age and IPSS-R are the greatest predictors of Death after AlloHCT, although the suggestion of an association with baseline Echo parameters highlights the importance of identifying those who may benefit from preemptive Cardiology intervention.

Introduction HMAs are the only approved therapy for CMML. In order to improve response rates and survival, the addition of VEN has been utilized in both CMML and after blast transformation (CMML-BT) with conflicting results in small single center studies. To clarify the role of upfront HMA+VEN in CMML and CMML-BT, we performed a large multicenter analysis. Methods We included patients with HMA-naïve CMML and CMML-BT treated with combination HMA and VEN from 4 academic centers. The primary outcome was overall survival (OS) with secondary outcomes including overall response rate (ORR) by 2015 MDS/MPN IWG criteria for CMML and 2022 ELN criteria for CMML-BT. To better appreciate the benefit of adding VEN to HMA treatment, we also performed 1:1 propensity score matched (PSM) analysis of patients treated with HMA alone as upfront therapy for CMML or CMML-BT. Matching was based on age, sex, ECOG performance status, CPSS-Mol, blood counts, peripheral and bone marrow blasts. Results Eighty-nine patients were treated with frontline HMA+VEN, 51 CMML and 38 CMML-BT (5 had received HMA alone for prior CMML). The median age was 71 years, 70% were male, and 83% had ECOG 0-1. Among CMML patients, 55% had MP-CMML subtype, 65% had CMML-2 and 12%, 30%, 58% were CPSS-mol intermediate-1, intermediate-2 and high risk, respectively. In the entire cohort, ASXL1 (63%), TET2 (47%), SRSF2 (39%) and RUNX1 (27%) were the most commonly mutated genes and 55% of patients harbored a RAS mutation ( KRAS [20%], NRAS [18%], CBL [13%], NF1 [11%], PTPN11 [9%]). For HMA combination partner, 46 (52%) were treated with azacitidine, 35 (39%) with decitabine, and 8 (9%) with both during their VEN course. During a median follow-up time of 15.8 months (mos) 52 patients (58%) died: 23 (45%) with CMML and 29 (76%) with CMML-BT. Among CMML patients, the ORR was 90%, including complete remission (CR) in 22%, complete cytogenic remission (CCR) in 4%, optimal marrow response (CMR) in 50%, and partial marrow response (PMR) in 6%. The OS of CMML patients was 25.1 mo (95% CI 15.7 - NR). A PSM population of HMA patients matched to HMA+VEN treated patients showing similar baseline characteristics. ORR was significantly higher with HMA+VEN (95%) as compared those treated with HMA alone (46%), p < 0.001. However, there was no significant OS difference between HMA+VEN vs HMA alone (19.1 mos vs 19.1 mos, p = 0.85, Figure 1). For CMML-BT patients, the ORR of HMA+VEN was 81% including CR in 17%, CR with partial hematologic recover (CRh) in 3%, CR with incomplete hematologic recovery (CRi) in 28%, morphologic leukemia-free state (MLFS) in 22% and partial response (PR) in 11%. The OS of CMML-BT patients was 8 mos (95% CI 4.6 - 26.2). A PSM population of CMML-BT patients treated with HMA alone showed a significantly increased ORR with HMA+VEN (82% vs 40%, p = 0.039). However, there was no difference in OS (7.49 mos vs 9.26 mos, p = 0.83, Figure 2). Among HMA-VEN treated patients, achievement of a CR was associated with an improved OS in the CMML (HR 0.31, 95% CI 0.13 - 0.75) and CMML-BT (HR 0.37, 95% CI 0.19 - 0.74). No predictors of response were identified, including the presence of a RAS mutation. In terms of safety, 7 patients (7.9%) had a grade 3/4 (G3/4) neutropenic infection and 2 patients (2.2%) had a G3/4 hemorrhagic event while being treated with HMA+VEN. A total of 29 patients went on to receive allogeneic transplant (alloSCT): 22 (43%) with CMML and 7 (18%) with CMML-BT. CMML patients who underwent alloSCT after HMA+VEN were younger as compared to non-transplanted patients (64 vs 74 years, p < 0.0001), but had otherwise similar baseline characteristics including stage, CPSS-mol category and prevalence of RAS mutations. Similarly, CMML-BT patients bridged to alloSCT were younger (66 vs 74 years, p < 0.002) and had a better ECOG performance status (p = 0.047). Of patients who received alloSCT, 10 patients (34%) died, 5 with CMML and 5 with CMML-BT. The median OS after alloSCT was 26.7 mo. Conclusions Although the use of VEN with HMA in the upfront treatment of CMML and AML secondary to CMML results in higher response rates compared to HMA alone, this combination does not improve survival based on this multi-center PSM analysis. The current sample size of CMML-BT may limit detection of OS differences between treatment groups. The role of VEN to reduce blasts and serve as a bridge to alloSCT, particularly after HMA failure, requires further investigation in larger studies in both the CMML and CMML-BT populations.

Introduction: Fludarabine combined with melphalan 140 mg/m2 (FluMel140) is a commonly used reduced-intensity conditioning (RIC) regimen in patients undergoing matched related (MRD) and unrelated donor (MUD) allogeneic stem cell transplant (alloSCT). Ciurea et al Blood 2020, described outcomes of Flu 160 mg/m2 and Mel 100 mg/m2. In this study, we describe our experience of attenuated melphalan dosing 100-120 mg/m2 versus 140 mg/m2 with fludarabine 125 mg/m2 (attenuated FluMel versus regular dose FluMel). Methods: We retrospectively reviewed patients from November 2016 to April 2023 with AML, ALL or MDS undergoing alloSCT who received fludarabine and melphalan. Patients who received the lower dose of melphalan were considered to be the attenuated FluMel cohort, whereas patients receiving the melphalan 140 mg/m2 were considered to be the control cohort. Kaplan-Meier and log-rank tests were used to estimate OS. NRM and relapse incidence (RI) was calculated using competing risk analysis. R 4.2.0 (R Foundation for Statistical Computing) was used for statistical analyses. Results: A total of 134 patients [92 (68.7%) males] were evaluated. Thirty-seven (27.6%) patients received attenuated FluMel and 97 (72.4%) patients received regular dose FluMel (controls). Among the patients in the attenuated FluMel cohort, 5 (13.5%) patients also received fludarabine at doses less than 125 mg/m 2 [median 20 mg/m 2 (range 87.5-112.5 mg/m 2]. Median age at transplant was 65 years (range 30 - 76 years). The most common disease was AML [75 (56.0%) patients] ( Table 1). Patients in the attenuated FluMel group had comparable iothalamate clearance compared to control cohort (clearance <65 ml/min/1.73 m2: 18.9% vs. 12.4%, P = 0.52). Patients in the attenuated FluMel group had comparable rates of high/very high DRI to those in control cohort (51.4% vs. 43.3%, P = 0.91). Compared to the control cohort, patients in the attenuated FluMel group were less likely to have a matched related donor (21.6% vs. 45.4%, P = 0.02) and were more likely to receive PTCy for GVHD prophylaxis (37.8% vs. 16.5%, P = 0.02). Among the patients receiving attenuated FluMel, the median melphalan dose administered was 100 mg/m2. The median time to neutrophil engraftment was 19 days (IQR 16-21 days), and median time to platelet engraftment was 18 days (range 12-25 days). Eleven (29.7%) patients developed post-alloSCT mucositis, and 3 (8.1%) patients developed grade 3-4 mucositis. All the patients in the attenuated FluMel group achieved 100% CD33 donor chimerism at day +30 (n=35) and day +100 (n=28) after alloSCT. Similarly, 26 (74.3%, n = 35) patients achieved ≥ 95% CD3 donor chimerism at day +30 after alloSCT and 23 (82.1%, n = 28) patients achieved ≥ 95% CD3 donor chimerism at day +100 after alloSCT. Median follow-up of the entire cohort after alloSCT was 2.3 years (95% CI 2.1-2.5 years). Median follow-up was 1.5 years in the attenuated FluMel cohort and 2.5 years for the control cohort ( P<0.001) . Survival was similar among patients receiving attenuated FluMel vs. control cohort (2-year OS 74.7% vs. 65.0%, P = 0.28). At 2 years post-alloSCT, the attenuated FluMel and control cohort had similar non-relapse mortality (19.9% vs. 24.4%, P=0.58) and relapse (22% vs. 15.2%, P=0.51). The attenuated FluMel was not associated with an increased incidence of relapse (HR 1.36, 95% CI 0.50-3.73, P=0.55) or NRM (HR 0.74, 95% CI 0.28-1.95, P = 0.55). GVHD-free relapse free (GRFS) survival was also similar among the attenuated Flu/Mel and control cohort (1-year GRFS rate 41.1% vs. 45.6%, P = 0.8). Among the patients receiving PTCy for GVHD prophylaxis, the 2-year OS in patients receiving attenuated FluMel was higher than the control group, but it was not statistically significant (2-year OS rate: 90% vs. 55%, P=0.37, Figure 1). Compared to the control group, the attenuated FluMel group had similar rates of NRM at 100 days (10% vs. 12.5%), 1 year (NA vs. 25%) and at 2 years after alloSCT (NA vs. 25%, P=0.54). GRFS at 1 year was also similar between the attenuated FluMel and control group (68.6% vs. 43.8%, P = 0.69). Conclusion: The attenuated dosed FluMel conditioning is a safe and effective regimen for elderly patients with acute leukemia and MDS, and is non-inferior to regular dose FluMel. Among patients receiving PTCy for GVHD prophylaxis, the lower dose of melphalan was non-inferior to regular dose FluMel for survival outcomes. Larger studies are needed to confirm our findings.

Introduction: Germline DEAD-box RNA helicase-1 mutant (DDX41) predisposition syndrome ( DDX41-MT-GPS) is one of the most frequent hereditary predisposition syndromes in adults with myeloid neoplasms (MN-2-5%). Somatic mosaicism involving the unmutated DDX41 allele (e.g., R525H) as a potential mechanism for myeloid evolution has been reported in 39-50% of patients (pts). In addition, given the later age of onset, somatic mosaic states composed of age-related clonal hematopoiesis (ARCH) (e.g., DNMT3A, ASXL1, TET2, and TP53), with reported frequencies less than expected in MDS and AML, have been documented. We conducted this study to define the somatic mosaic landscape in DDX41-MT-GPS . Methods: After approval from the Mayo Clinic IRB the prospective GPS database was queried for pts with DDX41-MT GPS. Germline confirmation was conducted on skin fibroblast-, or hair follicle-derived DNA. Somatic CH testing was conducted using a targeted NGS panel as previously described. Given the high frequency of variants of undetermined significance (VUS), comparisons were made between pathogenic ( DDX41path) and DDX41VUS. Results: We identified 106 pts with DDX41-MT-GPS, of which 83 (78%) met criteria for MN, 16 (15%) for CH/CCUS (clonal cytopenias of undetermined significance), while 7 (6%) were unaffected carriers. Somatic mosaicism in DDX41-GPS patients without MN Sixteen DDX41-MT pts without MN met criteria for CH/CCUS ( DDX41path [n=4] and DDX41VUS [n=12]; median age 69 years (yrs) (range [R], 19-78) ( DDX41path [69 yrs] and DDX41VUS [67 yrs], p=0.85), with a male predilection (75%). Four (25%) pts had somatic DDX41 MT (R525H [n=3] and A376T [n=1]) with median variant allele frequency (VAF) 10.5% (R, 5-27); 2 (50%) pts with germline DDX41path had R525H (VAF; 5% and 13%) and 1 (8%) pt each with germline DDX41VUS had R525H (VAF 5%) and A376T (VAF 27%) somatic variants, respectively. Abnormal cytogenetics (CG) were observed in 2/13 evaluable (15%) pts ([+8 and del20q]) in the germline DDX41path group only (p= 0.05). ARCH co-mutations were observed in 11 (69%) pts, not significantly (NS) different between DDX41path (75%) and DDX41VUS (75%), p= 0.66. Individual co-mutations: DNMT3A (25% vs 16%, p= > 0.99), ASXL1 (25% vs 8%, p=0.71), TET2 (25% vs 8%, p= >0.99), and JAK2 (0% vs 8%, p= >0.99) were NS different between the two groups. Somatic mosaicism in DDX41-GPS patients with MN Eight-three pts met criteria for MN ( DDX41path [n=43] and DDX41VUS [n=40]; median age 67 yrs (range [R], 27-92), with a male predilection (58%). Fifty-four (65%) pts had MDS ( DDX41path [55%] and DDX41VUS [45%], p=0.55) and 29 (35%) had AML ( DDX41path [41%] and DDX41VUS [59%], p=0.65). Overall, 15 (18%) pts had somatic DDX41 MT; 12 (80%) pts with DDX41path and 3 (20%) pts with DDX41VUS (p= 0.003). The median VAF of somatic DDX41 MT was 12% (R, 5-37), NS different between DDX41path (10.5%) and DDX41VUS (12%) (p=0.08). The most common somatic DDX41 MT was R525H (66% [n=10]), significantly associated with DDX41path (9/10 [90%]), p=0.01. ARCH was observed in 17 (20%) pts, significantly higher in DDX41path (76%) compared to DDX41VUS (24%), p= 0.03. Abnormal CG were observed in 10/73 evaluable (14%) pts (-Y [n=2], del 20 [n=3], del 5q [n=2], del 7q [n=1], t (3;8) [n=1] and complex CG [n=1]), higher in DDX41path (70%) compared to DDX41VUS (30%) with p value >0.99. We compared the spectrum of CH between DDX41 MT CH/CCUS and MN pts ( Table 1) and found no difference in the proportion of pts with somatic DDX41 MT (p= 0.52) and ARCH/myeloid MT (p= 0.56). The individual occurrences of DNMT3A (p= 0.49), ASXL1 (p= 0.71), TET2 (p=0.59), JAK2 (p>0.99) and TP53 (p= 0.56) mutations were NS different between the two groups ( Figure 1). Conclusion: We define the somatic mosaic landscape in DDX41-MT GPS and demonstrate that somatic mutations involving the other allele, especially R525H, are seen in ~20% of pts (>80% of R525H present in MN). The frequency and composition of ARCH and myeloid driver mutations was lower than expected for the age of presentation, in comparison to de novo and secondary MDS/AML and occurred more frequently in DDX41path compared to DDX41VUS. Forty-two % (n=41), including 37% with MN, did not have somatic mosaicism, underscoring the fact that mechanisms of leukemia progression remain to be defined in subsets of affected pts.

Introduction Truncating ASXL1 mutations in chronic myelomonocytic leukemia (CMML) are associated with inferior overall survival (OS) and leukemia free survival (LFS). Conversely, loss-of-function mutations in TET2 are associated with better outcomes, with the ASXL1wt/ TET2mut genotype being associated with the best OS and LFS-rates (Coltro G, et al. Leukemia. 2020). Contemporary CMML prognostic scoring systems - such as the Mayo Molecular Model (MMM; Patnaik MM, et al. Leukemia. 2014) and the CPSS-Molecular Model (CMM; Elena C, et al. Blood. 2016) - do not consider concomitant ASXL1/ TET2 mutational status or mutational VAF. We hypothesized that the ASXL1/ TET2 genotype would better risk stratify patients in comparison to ASXL1 mutations alone, and that this effect would be proportional to the underlying mutational VAF. Methods After IRB approval, we compiled a large (n = 888), molecularly annotated database of CMML patients seen at two US medical centers (Mayo Clinic and MD Anderson) via retrospective chart review. All statistical analyses considered the clinical and laboratory parameters obtained at the time of presentation to the respective institution. Categorical variables were compared by Fisher exact or Pearson χ 2 tests and continuous variables by Mann-Whitney U tests. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Survival was assessed via the Kaplan-Meier method. P-values < 0.05 were considered significant. All statistical calculations were performed using the BlueSky Statistics (v10.3.1) interface for R. Results The median age of the cohort was 71 years (range 20 - 94), 67% were male, 46% had proliferative CMML (pCMML), and 19% had CMML-2. The distribution of low, intermediate-1, intermediate-2, and high-risk patients was 15%, 11%, 32%, and 42% by the MMM and 9%, 23%, 40%, and 28% by the CMM, respectively. The most frequently mutated genes were ASXL1 (45%), TET2 (43%), SRSF2 (41%), and RUNX1 (17%), while 40% harbored at least one RAS pathway mutation ( NRAS 16%, CBL 15%, KRAS 8%, PTPN11 4%, FLT3 2%). The median OS and LFS of the entire cohort were 31.8 months (95% CI 28.4 - 33.5 months) and 28.4 months (95% CI 24.6 - 32.1 months), respectively. Patients were stratified into ASXL1wt/ TET2wt (28%), ASXL1mut/ TET2wt (29%), ASXL1wt/ TET2mut (26%), and ASXL1mut/ TET2mut (17%) genotypes. Those with isolated TET2 mutations had the longest median OS (53.6 months; p < 0.02 for all comparisons) whereas those with isolated ASXL1 mutations had the shortest median OS (20.9 months; p < 0.04 for all comparisons); mutations in neither or both genes performed similarly (p = 0.9224; Figure 1A). The same trend was seen for LFS. We further hypothesized that the ASXL1 or TET2 mutation VAF would be more predictive of outcomes than a binary metric. The respective median VAFs were 37% (quartiles 28% - 45%) and 45% (quartiles 40% - 49%). When treated as a continuous variable, however, there was no correlation between either VAF and OS or LFS by both Pearson linear regression and Cox proportional hazard modeling. Unlike the overall cohort, the ASXL1/ TET2 genotypes did not further stratify patients with pCMML, CMML-2, or those considered high risk by the CMM in Kaplan-Meier analyses, suggesting that the high-risk features inherent in these subgroups outweigh the benefits of the TET2 mutation. In contrast, patients considered high-risk by the MMM were further stratified by the ASXL1/ TET2 genotypes. Incorporating TET2 mutations into the MMM as a protective factor (worth -1.5 points) improved detection of low- (≤ 1 point) and high-risk (≥ 4 points) patients, while intermediate-1 and intermediate-2 coalesced into a single intermediate risk category ( Figure 1B). A similar phenomenon was observed when TET2 was incorporated into the CMM (worth -1 point, yielding low- (0 points), intermediate- (1-2 points), and high-risk (≥ 3 points) groups with median OS of 83 months (95% CI 66.2 - 104.2), 34.3 months (95% CI 31.6 - 38.7), and 17.7 months (95% CI 15.7 - 20.2), respectively. Conclusions Truncating and hypomorphic TET2 mutations are associated with better outcomes in CMML, with the ASXL1mut/ TET2wt genotype being associated with improved risk stratification in comparison to ASXL1 mutational status alone. Counterintuitively, in our data set, this stratification was not impacted by mutational VAF, supporting binary mutational assessments in prognostic models.

BACKGROUND: Recently proposed World Health Organization (WHO, 5 th edition) and International Consensus Classification (ICC) recognized myeloid neoplasms (MN) harboring TP53-mutated ( TP53mut) as a separate entity. However, there are critical differences between the two classifications regarding allelic-status, variance allele frequency (VAF) cut-off and blast categories, that may lead to under- or overestimation of the risk. METHODS: We analyzed MN harboring TP53mut (VAF ≥2%, n=536) managed at Mayo Clinic (USA) and South Australia Health Network (Australia). ICC (Arber et al, Blood 2022) and WHO (Bluebook, Beta v2) definitions were used to stratify MN harboring TP53mut. RESULTS: Of 536 cases, 379 (71%) had myelodysplastic syndromes (MDS) (<20% blasts) and 157 (29%) had acute myeloid leukemia (AML). Using WHO, 160 (42%) of 379 were classified as MDS-bi TP53 as they harbored 2 TP53mut (n=115; 30%) or 1 TP53mut plus confirmed loss of heterozygosity (LOH) or copy neutral LOH (cnLOH) of TP53 locus (n=45; 12%). Sixty-two (16%) TP53mut MDS with VAF >49% were classified as presumptive MDS-bi TP53. Of the 157 cases with 1 TP53mut VAF ≤49%, 17 confirmed to have an intact wild-type TP53 copy and were classified as monoallelic. While 140 (89%) cases did not have copy number variation (CNV) analysis. We next evaluated the number of TP53mut cases classified differently by WHO and ICC. As WHO does not recognize TP53mut AML as a separate entity, 157 (29%) TP53mut AML were not classifiable. 46% (174/379) of the TP53mut MDS including 48 (30%), 12 (19%) and 79 (65%) of bi TP53, presumptive bi TP53 and monoallelic TP53mut MDS according to WHO were classified differently by ICC ( Figure 1A). Discordance between the two classifications were predominantly driven by: (i) The difference in VAF cut-off. Sixty patients (11%) with TP53mut VAF <10% were excluded from the ICC classification of TP53mut MN as it mandates TP53mut VAF cut-off ≥10%. 11 (18%) and 41 (68%) of these had bi TP53, monoallelic TP53mut MDS by WHO criteria while 8 (13%) had AML. Importantly, within the VAF <10% cohort, median overall survival (OS) of 2 TP53mut or 1 TP53mut with 17p13.1 (hereafter 17p) deletion or complex karyotype (CK, n=30) was significantly poor compared to 1 TP53mut VAF <10% (11.6 vs 32.4 months; P =0.002, Figure 1B), suggesting that ICC may underestimate the poor prognosis of multi-hit or multi-hit equivalent TP53mut MN with VAF <10%. (ii) The difference in bone marrow blast cut-off. The underlying assumption by WHO is that prognosis of bi TP53mut MDS is poor irrespective of blast percentage category (0-9% vs 10-19%). In contrast, ICC considers that TP53mut MDS/AML (blasts 10-19%) is associated with poor prognosis irrespective of TP53 allelic status. Median OS of TP53mut MDS with 10-19% blasts was significantly poor compared to blast 0-9% (6.4 vs 11.6 months, P <0.0001). Second, median OS of bi TP53mut was significantly poor than monoallelic TP53mut in MDS- blast 0-9% (10.1 vs 15.9 months; P =0.0001) but not in blasts 10-19% (6.8 vs 6.2 months; P =0.19). Hence, exclusion of monoallelic TP53mut MDS with blast 10-19% as TP53mut MN from the WHO classification may underestimate the poor prognosis. (iii) The difference in the definition of biallelic and multi-hit TP53 loss. 35 cases with 1 TP53mut VAF ≤49%, had 17p deletion but did not have CNV analysis to confirm the loss of TP53 locus and could not be classified further using WHO. ICC classified 18 (50%) of these cases as multi-hit. Median OS of 1 TP53mut VAF ≤49%, and 17p deletion on karyotype was significantly poor than 1 TP53mut (VAF ≤49%without 17p deletion on karyotype (6.4 vs 14.6 months, P =0.001). (iv) The difference in the definition of multi-hit equivalent. 32% (33/104) WHO defined monoallelic cases without available CNV data, were classified as multi-hit-equivalent by ICC as they harbored CK. However, WHO does not consider CK as presumptive evidence of bi TP53. Median OS of 1 TP53mut VAF ≤49% with CK was significantly poor compared to 1 TP53mut without CK (8.2 vs 26.9 months, P =0.0008). CONCLUSION: Our study provides evidence that poor prognosis of ‘multi-hit’ TP53 with VAF <10% is underestimated by ICC. On the other hand, poor prognosis of monoallelic TP53 MDS with 10-19% blasts as well as 1 TP53mut VAF ≤49% in the presence of CK is underestimated by WHO. These data suggest that both classifications can be further refined.

Abstract VEXAS (Vacuoles, E1 enzyme, X‐linked, Autoinflammatory, Somatic) syndrome is a newly identified disease caused by somatic alterations in UBA1 which produce a recalcitrant inflammatory state along with hematologic disturbances. Patients with VEXAS can have a wide spectrum of clinical symptoms and providers should be familiar with the heterogeneity of associated clinical features. While hematologic parameters may be generally non‐specific, peripheral blood features of macrocytosis, monocytopenia, and/or thrombocytopenia coupled with bone marrow vacuolization of erythroid or myeloid precursors should raise suspicion for this condition. Due to an increased mortality, prompt recognition and accurate diagnosis is paramount. Access to testing for confirmation of UBA1 variants is not yet universally available but clinicians should understand the current available options for genetic confirmation of this disease. Treatment options are limited due to lack of prospective clinical trials but cytokine directed therapies such as interleukin‐6 inhibitors and JAK–STAT inhibitors as well as hypomethylating agents such as azacitidine have shown evidence of partial effect. Though cases are limited, allogeneic stem cell transplantation holds promise for durable response and potential cure. The intent of this review is to outline the pathophysiology of VEXAS syndrome and to provide a practical approach to diagnosis and treatment.