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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.

572 Background: The DEFeNDR (Decreasing the burden of Febrile Neutropenia through Dynamic RPM) program leverages in-home technology and centralized nurse monitoring to facilitate ambulatory management as an alternative to hospital-based care for cancer patients with neutropenic fever (NF). The objective of this study is to assess 30-day care utilization outcomes and patient satisfaction at 12 months after program implementation. Methods: Adult cancer patients hospitalized with NF were assessed daily for DEFeNDR program eligibility including MASCC score ≥21 (per ASCO guidelines) and no cellular therapy (CAR-T, BMT) in the prior 100 days. Patients agreeing to participate in the 30-day program received a cellular-enabled tablet with pre-connected devices for twice-daily vital signs and symptom assessments. Patient generated data were EHR-integrated in real-time. Embedded decision trees facilitated alerts for adverse trends. Virtual RPM nurses responded to alerts and utilized predefined care pathways. The primary endpoint was the mean proportion of evaluable days spent inpatient (mPEDI) within 30 days of eligibility comparing those who participated in the program (RPM) with those who declined (no RPM). Results: Of 85 eligible patients, 62 were offered DEFeNDR participation. Of those, 34 (54.8%) participated and 28 (45.2%) declined. Baseline characteristics and care utilization outcomes are summarized in Table 1. RPM patients experienced significantly lower mPEDI compared with unmonitored patients [5.1% (Standard Error [SE], 1.9%) vs 12.4% (SE, 2.1%); Wilcoxon Rank Sums p-value, 0.032]. RPM patients also experienced a trend toward fewer total hospital days and lower 30-day readmission rate, as well as shorter mean length of stay and lower rate of ICU utilization when readmitted. Non-visit care activities (EHR clinical communications, documentation, and patient messaging) were decreased from pre-hospital baseline for 58.8% of RPM patients versus 46.6% of those unmonitored. All RPM patients completing a patient satisfaction survey (n=9) indicated that they would recommend the program to patients with a similar condition. Conclusions: Cancer patients with NF participating in the DEFeNDR program experienced a significant reduction in mPEDI and care utilization compared with those who declined. Further studies are warranted to assess comparative effectiveness of this model vs usual care.[Table: see text]

AbstractThe World Health Organization (WHO) classification system categorizes advanced systemic mastocytosis (SM‐Adv) into aggressive SM (ASM), mast cell leukemia (MCL), and SM with associated hematological neoplasm (SM‐AHN). By contrast, the International Consensus Classification (ICC) requires “immature” MC cytomorphology for the diagnosis of MCL and limits SM‐AHN to myeloid neoplasms (SM‐AMN). The current study includes 329 patients with SM‐Adv (median age 65 years, range 18–88; males 58%): WHO subcategories SM‐AHN (N = 212; 64%), ASM (N = 99; 30%), and MCL (N = 18; 6%); ICC subcategories SM‐AMN (N = 190; 64%), ASM (N = 99; 33%), and MCL (N = 9; 3%); WHO‐defined MCL with “mature” MC cytomorphology and SM‐AHN associated with lymphoid neoplasms were operationally labeled as “MCL‐mature” (N = 9) and SM‐ALN (N = 22), respectively, and distinguished from ICC‐defined MCL and SM‐AMN. Multivariable analysis that included the Mayo alliance risk factors for survival in SM (age >60 years, anemia, thrombocytopenia, increased alkaline phosphatase) revealed more accurate survival prediction with the ICC versus WHO classification order: (i) survival was significantly worse with MCL‐immature versus MCL‐mature (hazard ratio [HR] 15; p < .01), (ii) prognostic distinction between MCL and SM‐AHN/AMN was confirmed in the context of ICC (HR 9.3; p < .01) but not WHO classification order (p = .99), (iii) survival was similar between MCL‐mature and SM‐AMN (p = .18), and (iv) SM‐AMN (HR 1.7; p < .01) but not SM‐ALN (p = .37) was prognostically distinct from ASM. The current study provides evidence for the independent prognostic contribution of both the ICC system for SM‐Adv and the Mayo alliance risk factors for survival in SM.

SummaryVenetoclax (VEN) is an FDA‐approved selective inhibitor of B‐cell leukaemia/lymphoma‐2 (BCL‐2), used for treating elderly or unfit acute myeloid leukaemia (AML) patients unable to undergo intensive chemotherapy. Combining VEN with hypomethylating agents (HMAs) has shown impressive response rates in high‐risk myelodysplastic syndromes (MDS) and relapsed/refractory AML. However, the efficacy of VEN and HMAs in treating DDX41‐mutated (mDDX41) MDS/AML patients remains uncertain. Despite the favourable prognostic nature of mDDX41 MDS/AML patients, there is a lack of clinical experience regarding their response to different treatment regimens, leading to an unknown optimal therapeutic approach.

Abstract We examined the individual prognostic contribution of absolute neutrophil (ANC), lymphocyte (ALC), and monocyte (AMC) counts, on overall (OS), leukemia‐free (LFS), and myelofibrosis‐free (MFFS) survival in essential thrombocythemia (ET). Informative cases ( N = 598; median age 59 years; females 62%) were retrospectively accrued from a Mayo Clinic database: JAK2 59%, CALR 27%, triple‐negative 11%, and MPL 3%; international prognostic scoring system for ET (IPSET) risk high 21%, intermediate 42%, and low 37%; 7% (37/515) had abnormal karyotype and 10% (21/205) adverse mutations ( SF3B1/SRSF2/U2AF1/TP53 ). At median 8.4 years, 163 (27%) deaths, 71 (12%) fibrotic, and 20 (3%) leukemic transformations were recorded. Multivariable analysis resulted in HR (95% CI) of 16.5 (9.9–27.4) for age > 70 years, 3.7 (2.3–6.0) for age 50–70 years, 2.4 (1.7–3.3) for ANC ≥8 × 10 9 /L, and 1.9 (1.4–2.6) for ALC <1.7 × 10 9 /L. The corresponding HR‐based scores were 4, 2, 1, and 1, resulting in an new 4‐tiered AgeAncAlc (AAA; triple A) risk model: high (5–6 points; median survival 8 years; HR 30.1, 95% CI 17.6–54), intermediate‐2 (4 points; median 13.5 years; HR 12.7, 95% CI 7.1–23.0), intermediate‐1 (2–3 points; median 20.7 years; HR 3.8, 95% CI 2.3–6.4) and low (0–1 points; median 47 years). The AAA model (Akaike Information Criterion [AIC] 621) performed better than IPSET (AIC 647) and was subsequently validated by an external University of Florence ET cohort ( N = 485). None of the AAA variables predicted LFS while ALC <1.7 × 10 9 /L was associated with inferior MFFS ( p = .01). Adverse mutations ( p < .01) and karyotype ( p < .01) displayed additional prognostic value without disqualifying the prognostic integrity of the AAA model. This study proposes a simple and globally applicable survival model for ET, which can be used as a platform for further molecular refinement. This study also suggests a potential role for immune‐related biomarkers, as a prognostic tool in myeloproliferative neoplasms.