Lindsley, R Coleman

ABSTRACT The epidemiology of myelodysplastic syndromes/neoplasms (MDS) is challenging to define due to inconsistent reporting, complex diagnostic procedures, and evolving diagnostic criteria. Using the National MDS Natural History Study—a prospective cohort with centrally adjudicated histopathology and genetic variant review—we characterized the landscape of MDS across the United States and identified differences across demographics. Among 2115 participants, 64% (1346) had an MDS spectrum condition, including MDS (24%), MDS/myeloproliferative neoplasm (5%) and precursor conditions—clonal cytopenia of undetermined significance (22%) and idiopathic cytopenia/dysplasia of undetermined significance (13%). The median age was 74 years, and participants were predominantly male (66%), White (91%), and Non‐Hispanic (92%). Myeloid‐associated variants were detected in 68% of participants, most commonly in TET2, DNMT3A, ASXL1, SF3B1, and SRSF2 . Black, compared to White, participants were younger at diagnosis (69 vs. 74 years, p = 0.01), had equal or increased prevalence of higher‐risk MDS, lower hemoglobin, and higher peripheral blood blasts, yet were less likely to receive MDS‐directed therapy (14% vs. 42%, p = 0.008). Black and Hispanic participants had fewer detectable gene mutations than White participants. Females had lower variant allele frequencies and fewer RNA splicing gene mutations than males. After multivariable adjustment, TP53 mutations, MDS diagnosis, and higher‐risk disease were associated with worse progression‐free and overall survival; age was also associated with overall survival. Black race trended toward improved progression‐free survival. These findings highlight the need for enhanced understanding of MDS pathogenesis across patient groups and refined prognostic tools to improve personalized management of MDS spectrum conditions. Trial Registration: ClinicalTrials.gov identifier: NCT02775383

Abstract Patients at risk for progression from myeloid precursor states (idiopathic cytopenia of undetermined significance [ICUS] and clonal cytopenia of undetermined significance [CCUS]) to myelodysplastic syndrome (MDS) are not well defined. Epidemiologic risk factors, clonal changes for MDS development, and evolution from one MDS state to another were available in the MDS Natural History Study (NHS), a prospective cohort enrolled at diverse US sites. Extensive clinical data and biospecimens were collected at baseline and follow-up. A total of 1177 (56%) individuals with MDS or MDS-related precursor conditions (ICUS/idiopathic dysplasia of undetermined significance [IDUS], CCUS, and MDS/myeloproliferative neoplasm overlap) were enrolled and diagnosed in the MDS NHS. The median age was 74 years, with 89% aged ≥60 years, and most were male patients. Median follow-up time was 1.6 years and was similar among ICUS/IDUS, CCUS, and MDS. During follow-up period, 68% of participants terminated the study, 35% died, and 38% had disease progression. Using a refined clinical definition of progression, the greatest proportion of progression was observed among higher-risk-MDS (116 [73%]), followed by lower-risk-MDS (170 [52%]); fewer progression events were observed among participants with CCUS (65 [22%]) and ICUS/IDUS (46 [17%]). Predictors of progression are delineated, including female sex, higher quantity of mutations, the presence of TP53 mutation, and poor/very poor cytogenetic score. Based on these prospective data, guidelines for clinical management including monitoring and surveillance are outlined. The MDS NHS provides real-world data to illustrate how clinical and genotypic differences inform the classification, disease course, and approach to therapy, with informed monitoring guidelines for patients. This trial was registered at www.ClinicalTrials.gov as NCT02775383.

Abstract Introduction: Standardized reporting of clinical trials results for MDS is essential to improve clinical interpretation and cross-study comparison. However, reporting of patient characteristics, response criteria, and endpoints in publications is often inconsistent; there is no systemic analysis of MDS trial reporting available. We conducted a systematic review of published MDS trial manuscripts on behalf of the international consortium for MDS (icMDS) to assess variability in reporting practices. Methods We searched ClinicalTrials.gov to identify all clinical trials registered for adults (≥18 years) with MDS that reported results between 2015-2024. Clinical trials that included acute myeloid leukemia (AML) or MDS/myeloproliferative neoplasms (MPN) were included if they enrolled ≥5 MDS patients. We excluded trials without an MDS cohort; non-therapeutic trials; trials focused on transplant interventions; or those which enrolled solid malignancies or other hematologic malignancies (chronic myeloid leukemia or lymphoid diseases). Finally, trials were required to have a manuscript available on Larvol, PubMed, or Google Scholar. Trials were categorized by disease risk (lower-risk [LR] vs. higher-risk [HR]) and trial phase (early phase [EP] vs. late phase [LP]). Results We identified 502 MDS trials on ClinicalTrials.gov, of which 351 did not meet inclusion criteria and 79 lacked a manuscript. A total of 72 trials (32 EP, 40 LP) with 80 publications (34 EP, 46 LP) were analyzed. Frequently reported baseline characteristics included age (100% EP, 100% LP), disease risk (74% EP, 74% LP), Eastern Cooperative Oncology Group performance status (85% EP, 72% LP), prior treatments (71% EP, 67% LP), and RBC transfusion dependency (32% EP, 70% LP). Less frequently reported characteristics included blood counts (hemoglobin [Hb; 38% EP, 54% LP], platelet count [38% EP, 54% LP], neutrophil count [24% EP and LP]) and bone marrow blasts (29% EP, 43% LP). Although disease risk was widely reported, definitions varied: IPSS and IPSS-R were each reported in 54% of manuscripts, while IPSS-M appeared in only 3%. Cytogenetic risk was separately reported in 39% of manuscripts (38% EP, 39% LP), and mutational data in 45% (47% EP, 43% LP). Responses per IWG 2006 criteria were reported in 84% of manuscripts. The primary endpoint involved safety/tolerability in 85% of EP manuscripts, though definitions were variable; recommended phase 2 dose was the most common (26% of EP manuscripts). In LP trials, primary endpoints were risk-specific: transfusion independence (TI) in 77% of LR, overall response rate (ORR) in 28% of HR, and complete remission (CR) or overall survival (OS) in 22% of HR. In HR manuscripts, CR was reported in 100%, ORR in 73%, hematologic improvement (HI) in 48%, RBC-TI in 23%, and OS in 80%. However, seven different definitions were used for ORR: CR + marrow CR + partial remission + HI per IWG 2006 was most common (35%). Event-free survival was reported in 25%; progression-free survival and relapse-free survival in 13%; and leukemia-free survival in 5%. Early mortality rate was reported in 35% (18% EP, 56% LP) and transplant rate in 58% (50% EP, 67% LP). Only 47% of HR and 90% of LR manuscripts identified HI-eligible patients. In LR-MDS, RBC-TI was reported in 72% of manuscripts but used six definitions. The most common were RBC-TI ≥8 weeks at any time during treatment (24%), ≥8 weeks within 28 weeks of treatment (13%), ≥8 weeks with Hb increase ≥1.0 (4%), ≥12 weeks with Hb increase ≥1.5 (4%), and ≥16 weeks within 24 weeks of treatment (12%). The remainder did not report RBC-TI, did not define it, or used a custom definition not used in another trial. HI was reported in 80% of LR papers with most of those reporting HI using IWG 2006 criteria (90%). Conclusion Reporting of baseline characteristics, response criteria, and outcomes is inconsistent in MDS clinical trials, with wide variability in response definitions, including ORR and TI. This heterogeneity limits interpretability, hampers historical comparisons and may obscure efficacy signals. Our findings highlight the need for standardized reporting guidelines to ensure clarity and consistency in MDS trial publications. As a next phase of this effort, we will conduct a formal Delphi process among icMDS experts to establish consensus recommendations for minimal and optimal MDS clinical trial reporting in manuscripts by disease risk (LR/HR) and trial phase (EP/LP).

Abstract Background Myelodysplastic syndromes (MDS) develop from the acquisition of somatic mutations over years or decades. While some mutations are random stochastic events, others derive from extrinsic agents that promote genomic instability, including environmental exposures. Agent Orange (AO) is a phenoxy herbicide used by the U.S. military as a defoliant during the Vietnam War (1962-71), often diluted with gasoline to promote aerosolization, contaminated with the carcinogen dioxin during the manufacturing process, and linked to various cancers. We studied AO as a risk factor for MDS. Methods The prospective National Heart, Lung, and Blood Institute National MDS Natural History Study includes patients (pts) with suspected or recently diagnosed MDS enrolled from 6/2016-6/2024. Bone marrow samples underwent central pathology review, resulting in diagnoses including MDS, MDS/myeloproliferative neoplasm overlap (MDS/MPN), or clonal cytopenia of undetermined significance (CCUS). Pts completed detailed assessment for AO exposure and other risk factors for MDS development. Associations between AO exposure, mutation prevalence, and key covariates (demographics, diagnosis, military service, clinical history, cytogenetics and smoking) were assessed using univariate tests of association, multivariable regression and Cox regression models for survival and progression. Results Among 2115 enrolled pts, 1191 (56%) had a myeloid malignancy or precursor condition and 130 (6.1%) reported AO exposure, the majority (96%) male. Compared to unexposed pts, AO exposed pts were more likely to derive from the 1945-54 birth cohort (p<.001), of age to serve in Vietnam, and to have an ultimate diagnosis of MDS or CCUS vs. a non-clonal diagnosis (57% vs. 44%, p=.046). AO exposure was more common among Blacks (12% vs 6%, p=.02), specifically Black males (21% vs 9%, p=.006). AO exposure was marginally associated with International Prognostic Scoring System (IPSS)-R poor-risk cytogenetics (p=.066) and lower baseline platelet count (p=.072). In multiple regression analyses, risk of AO exposure was significantly higher for the 1945-1954 birth cohort (OR [95% CI]=10.3 [4.4-30.6], p<.001), among those with military service (OR=24.1 [11.9-55.8], p<.0001), and for Blacks vs Whites (OR=2.6 [1.2-5.5], p=.017). The crude risk of AO exposure trended higher for patients with MDS compared to idiopathic cytopenia of undetermined significance (ICUS; OR=2.1 [0.9-6.0],p=.13), but not in multivariable analysis (OR=1.3 [0.5-4.4, p=.60]). AO exposure trended toward an association with younger age at MDS diagnosis (p=.06) and toward having a prior primary malignancy (49% vs. 41%, p=.09): Compared to non-AO exposed pts, AO exposed pts had higher rates of prior prostate cancer (16% vs. 8%), notable given its documented association with AO exposure. AO exposure was not associated with a history of or intensity of cigarette smoking (p=.67). After accounting for age, diagnosis, sex, and military service, AO exposure was significantly associated with increased numbers of pathogenic variants in 53 genes (OR=1.2 [1.0-1.4], p=.02) and with having Very Poor/Poor risk IPSS-R cytogenetics (OR=3.7 [1.2-11.1], p=.02). AO exposed and non-exposed pts had similar overall survival (HR=1.1 [0.8-1.7], p=.50), but those exposed to AO had a higher risk of disease progression in the first two years following diagnosis (HR =1.9 [1.2-2.8], p=.004). AO exposed pts appeared more likely to have del (5q) (15% vs. 8%) and del (20q) (13% vs. 5%) karyotypic abnormalities, and TP53 (7.7% vs. 4.5%), STAG2 (5.1% vs. 2.8%), and NRAS mutations (3.4% vs. 1.7%), although sample sizes were small. Focusing on gene pathways, AO exposed pts appeared more likely to have abnormalities in RAS signaling (10.3% vs. 5.7%), cell cycle (7.7% vs. 4.5%), and cohesion complex pathways (6.0% vs. 3.1%), but less likely to have abnormalities in cytokine receptor pathways (0% vs. 4.5%). ConclusionsIn our representative national cohort of pts with at least one cytopenia, and for the first time, we demonstrated that AO exposure is associated with younger age at MDS diagnosis, ultimate MDS diagnosis, genetic complexity of MDS, increased risk of disease progression, and with Black race, despite Black individuals comprising just 16% of men who served in the Vietnam War and being less likely to have MDS than white individuals. AO should formally be recognized as a risk factor for the development of MDS.

Abstract Lineage switch (LS), defined as the immunophenotypic transformation of acute leukemia, has emerged as a mechanism of relapse after antigen-targeted immunotherapy, which is associated with dismal outcomes. Through an international collaborative effort, we identified cases of LS after a host of antigen-targeted therapies (eg, CD19, CD22, CD38, and CD7), described how LS was diagnosed, reviewed treatment approaches, and analyzed overall outcomes for this form of postimmunotherapy relapse. Collectively, 75 cases of LS were evaluated, including 53 (70.7%) cases of B-cell acute lymphoblastic leukemia (B-ALL) transforming to acute myeloid leukemia (AML), 17 (22.7%) cases of B-ALL transforming to mixed phenotypic acute leukemia (MPAL)/acute leukemias of ambiguous lineage (ALAL), and 5 (6.7%) cases of rare LS presentation (ie, T-cell ALL to AML). An additional 10 cases with incomplete changes in immunophenotype, referred to as “lineage drift” were also described. With a primary focus on the 70 cases of LS from B-ALL to AML or MPAL/ALAL, LS emerged at a median of 1.5 months (range, 0-36.5) after immunotherapy, with 81.4% presenting with LS within the first 6 months from the most proximal immunotherapy. Although most involved KMT2A rearrangements (n = 45, 64.3%), other rare cytogenetic and/or molecular alterations were uniquely observed. Treatment outcomes were generally poor, with remission rates of <40%. The median overall survival after LS diagnosis was 4.8 months. Outcomes were similarly poor for those with rare immunophenotypes of LS or lineage drift. This global initiative robustly categorizes lineage changes after immunotherapy and, through enhanced understanding, establishes a foundation for improving outcomes of LS.

Introduction Knowledge of epidemiologic risk factors, clonal changes associated with MDS development from precursor states, and evolution from one MDS state to another (lower- (LR) or higher-risk (HR) disease or leukemia (AML)) are largely limited to retrospective studies, which may not reflect the true MDS spectrum. The MDS NHS is an established prospective cohort of patients (pts) with suspected MDS enrolled at diverse US sites. Extensive clinical data and biospecimens are collected at baseline and throughout follow-up (F/U), in real time, as pts are followed for life. Here, we assess rates and potential predictors of progression providing a foundation for precise stratification across the MDS spectrum, which may ultimately guide intervention. Methods At baseline, all MDS NHS pts have central pathology review and those assigned to MDS, MDS/MPN overlap, AML<30% blasts, or at-risk of MDS (AR-MDS: CCUS and other at-risk) are followed prospectively. We compared AR-MDS with LR-MDS (MDS and MDS/MPN overlap with IPSS-R ≤ 3.5) and HR-MDS (MDS and MDS/MPN overlap with IPSS-R > 3.5). We defined disease progression as any F/U diagnosis of worsening disease or documented disease-related death. Rates of disease progression were compared between groups using survival analysis methods for cumulative incidence incorporating non-disease death as a competing risk. Associations between progression and predictor variables were explored using univariate tests of association and multivariable survival (Cox regression) models for time-to-progression and logistic models for probability of progression (yes/no). Results The MDS NHS enrolled 2051 pts during June 2016-February 2024, with 54% (1111, above categories) followed prospectively. Median F/U is 1.7 yrs (IQR: 0.8-3.1 yrs, max: 7.9 yrs). For the current analysis, 582 MDS and 505 AR-MDS pts were included. Compared to AR-MDS, MDS patients were more often male (70% v 61%, p<0.01), older (median age: 75 v 72 years, p<0.01), and had lower baseline hemoglobin (median: 10.1 v 11.9 g/dL, p<0.001), platelets (median: 124 x109 v 146 x109 cells/L, p<0.001), and absolute neutrophil counts (median: 1.9 x109 vs 2.8 x109 cells/L, p<0.001). F/U time was similar among AR-MDS and MDS (median: 1.9 vs 1.6 yrs), with both groups having a 75th percentile of 3 yrs and maximum of 7 yrs. A total of 331 deaths were observed (30%), with 145 (44%) of these due to causes related to MDS (myeloid disease and/or cardiovascular disease). Overall, 18.5% had disease progression, with annual rates of 8% (MDS) and 2% (AR-MDS) (p<0.01). Among HR-MDS, progression rates were greatest in the 1st year following diagnosis (33%) and declined thereafter, whereas progression rates remained between 5-8% for LR-MDS and 1-3% for AR-MDS over 5 yrs of F/U. AR-MDS had similar rates of progression within the first 3 yrs from diagnosis as MDS with the lowest IPSS-R category. Among AR-MDS, low hemoglobin (hazard ratio, HR [95% CI]=3.2 [1.4-7.3], p<0.01) was significantly associated with progression. Among MDS, low hemoglobin (HR=4.0 [2.2-7.0], p<0.001), low platelet count (HR=3.1 [1.7-5.6], p<0.001) and higher numbers of mutations (HR=1.13 [1.0-1.2], p<0.01) were significantly associated with progression. Due to the low rate of progression in AR-MDS, meaningful comparisons of mutations could not be completed. In MDS, univariate analyses showed that somatic mutation prevalence in gene pathways for transcription, cell cycle and RAS signaling, and in genes TP53, BCOR, SF3B1, DDX41, PTPN11, SETBP1, and JAK2 were significantly associated with the probability of progression (p<0.05 in all). In multivariable models, adjusting for patient age, sex, and MDS risk level, the probability of progression (PP) was significantly higher among those with vs without somatic mutations in BCOR (PP=63% vs 29%, p=0.004), PTPN11 (PP=67% vs 29%, p=0.009), SETBP1 (PP=61% vs 30%, p=0.02), JAK2 (PP=59% vs 30%, p=0.02), DDX41 (PP=56% vs 30%, p=0.03) and TP53 (PP=43% vs 29%, p=0.04). Conclusions In this large prospective cohort of MDS and pts at risk for MDS, the annual rate of any disease progression was 8% among MDS and 2% among AR-MDS, lower than some retrospective series. Specific cytopenias and genetic factors associated with progression were identified. The MDS NHS provides an incomparable opportunity to address the critical clinical challenges of management and prevention of MDS progression across its spectrum.

Introduction: Myelodysplastic syndromes (MDS) occur due to the acquisition of mutational events over time. Tobacco smoking is a risk factor for MDS and has been associated with distinct genetic mutations in solid cancers. We investigated the association between smoking intensity and duration and the number and types of genetic mutations in MDS using a large prospective cohort. Methods: The prospective NHLBI/NCI National MDS Natural History Study includes individuals with suspected or recently diagnosed MDS enrolled between June 2016-August 2023. Patient (Pt) bone marrow samples underwent central pathology review, resulting in diagnoses including MDS, MDS/myeloproliferative neoplasm overlap (MDS/MPN), or precursor conditions, such as clonal cytopenia of undetermined significance (CCUS). Self-reported smoking data were collected at enrollment. Smoking intensity (i.e., light, medium, and heavy) was defined per CDC definitions. Included mutations were those manually annotated to be pathogenic for MDS. Mutation frequency and prevalence, as well as associations with smoking history and other key covariates, were assessed using univariate tests of association and multivariable regression models for counts and proportions. Rates of disease progression were compared between groups using survival analysis methods for cumulative incidence incorporating non-disease death as a competing risk. Results: Of 1898 evaluable pts, 52% (N=979) had a history of cigarette smoking [MDS: 58% (252/436), MDS/MPN: 57% (52/91), CCUS: 57% (230/405)], and 18% still smoked at diagnosis. The mean ± SD cigarettes per day was 15.8 ± 12.5 and the mean ± SD smoking years was 29.8 ± 16.9 years. Compared to non-smokers, smokers were more often males (68% v 54%, p<0.001) in the 70-79 year age group (45% v 34%, p<0.001). Similar proportions of those with and without a smoking history had MDS (41% v 37%, respectively). Within MDS, there was no association between smoking and MDS prognostic risk per revised international prognostic scoring system. Compared to light smokers [1-10 pack-years (PY)], heavy smokers (30+ PY) were more often male (81% v 62%, p<0.001) and had higher rates of cardiovascular disease (38% v 20%, p<0.001). In univariate analyses, smokers and non-smokers had similar numbers of mutations (mean ± SD: 2.0 ± 2.7 in both groups). Pts with CCUS had the least number of mutations (1.5 ± 1.2), followed by MDS (2.3 ± 1.8), and MDS/MPN overlap (3.3 ± 1.8). Within disease groups, smokers and non-smokers had similar numbers of mutations. Mutation prevalence was higher among smokers v non-smokers in gene pathways for chromatin modification (15% v 11%, p<0.01) and RNA splicing (26% v 19%, p<0.001) and for individual genes ASXL1 (12% v 8%, p<0.01), SF3B1 (9% v 6%, p<0.05), U2AF1 (6% v 3%, p<0.05) and ZRSR2 (2% v 1%, p<0.05). In multivariable regression models, after adjustment for sex, age and disease group, smokers had significantly more mutations on average than non-smokers (2.0 v. 1.4, p=0.04). Moreover, the number of mutations increased significantly with PY smoked (p=0.006), and those at the 75th and 90th percentiles of PY had 1.8 and 3.5 times the number of mutations, respectively, compared to non-smokers, indicating a dose-response relationship. After adjustment, mutation prevalence increased with PY smoked in the gene pathways for chromatin modification and RNA splicing (p<0.03 for both) and for the genes ASXL1 and ETNK1 (p<0.05 in both cases). The five-year cumulative incidence of disease progression was significantly higher among long-term smokers compared to non-smokers/those with shorter smoking history (mean [95% CI] proportion progressed, 20+ years vs <20 years smoking: 27% [19%-36%] vs 18% [13%-24%], p < 0.05). Overall survival was significantly lower for smokers compared to non-smokers for CCUS pts [HR 1.91, 95% CI (1.03-3.55), p=0.04] but not for MDS [HR 1.21, 95% CI (0.53-1.30), p=0.41]. Conclusions: In this prospective, national cohort, tobacco smoking was associated with distinct genetic mutations related to MDS, suggesting smoking potentially contributes to its multi-step molecular pathogenesis. A dose-response relationship was also demonstrated, as was an association with progression and survival. Our data suggest that pts with a new MDS diagnosis who are also smokers should be counseled to stop smoking, as it appears to contribute to the acquisition of new genetic mutations that can lead to progression.

Introduction: The NHLBI National MDS Study (NCT02775383) is a prospective cohort study conducted at 92 community hospitals and 29 academic centers. It enrolls patients undergoing work up for suspected MDS to understand the genetic, epigenetic, and biological factors associated with the initiation and progression of the disease. Previously untreated, cytopenic participants undergo both local and centralized pathology review and are assigned a diagnosis, including MDS, MDS/MPN, AML with blasts < 30%, and "Other". Emerging data suggests that Next Generation Sequencing (NGS), along with cytogenetics and clinical variables, may improve MDS diagnostic precision. Given that our study relies on central review (with additional tertiary pathology review used to adjudicate disagreements), we examined whether targeted gene sequencing data could be used to increase the agreement between local and central pathologic diagnosis of MDS vs. Other. Methods: Peripheral blood and bone marrow (BM) biopsy specimens from cytopenic patients, along with clinical history, CBC, and other results including karyotyping, FISH and pathology reports from local pathologists were reviewed by central pathologists. The updated 2016 WHO classifications were used to diagnose MDS. Targeted exon sequencing of 96 genes was performed using BM specimens. A subset of 648 individuals that were classified as MDS (n=212) or Other (n=436, including 90 CCUS and 89 individuals with other cancers) by pathology assessments were selected. A mean coverage of 1,317X was achieved and variants had a minimum variant allele frequency (VAF) of 2% (except FLT3). Variants for 596 subjects were manually reviewed to retain likely disease-causing variants to build a binary classifier (MDS vs. Other) using the maximum VAF per gene as input (Figure 1). Subjects diagnosed with MDS or Other by both central and local pathology were used for training, validation, and testing, and were considered "gold standard" (GS) cases (n=546). These subjects were split into 4 random groups with equal proportions of MDS cases. 75% of the GS cases were used to train and validate lasso-regularized logistic regression models using 3-fold cross validation. ROC curve analysis was carried out using the remaining 25% of GS cases (Test Set 1) on the best model to identify an optimal probability cut off point for classifying subjects as MDS. Model performance was then tested on 50 subjects for which the central and local pathology diagnosis disagreed (Test Set 2), as well as on 52 additional subjects irrespective of agreement (Test Set 3). Results : The best performing logistic regression model retained 7 genes as most informative in a discriminating diagnosis of MDS from Other based on their VAFs, in order of impact: TP53, SF3B1, U2AF1, ASXL1, TET2,STAG2, and SRSF2. We used this model to assign probabilities for each of the subjects in Test Set 1 and to estimate the performance using ROC analysis (Figure 1), resulting in a high area under the curve (AUC) of 0.89. We chose a probability cut-off of ≥0.17, being associated with a high percentage of correct classification of MDS with a sensitivity and specificity of 0.90 and 0.81, respectively. Among the cohort of 50 subjects with a discordant local and central pathology diagnosis (Test Set 2), the classifier accurately reassigned 37 subjects (accuracy = 74%) from the local to the central pathology. The blinded tertiary pathology reviewer agreed with central in all Test Set 2 cases. This included 24/34 MDS cases that had been labeled as Other by local pathology (positive predictive value [PPV]=0.89). 3/16 final pathology-classified Other cases were mis-classified as MDS by the local pathologist (negative predictive value [NPV] = 0.57). Next, we assessed the ability of the model to predict MDS vs. Other for 52 additional independent subjects using the third pathologist's diagnosis to break any ties (Test Set 3). The classifier correctly predicted 15/21 MDS cases (PPV=0.83) and misclassified 6/31 Others as MDS (NPV=0.82). The overall accuracy was 83%. Conclusions: We identified that VAFs for 7 genes can correctly re-classify subjects as either MDS or Other in 74% of cases that were misclassified between local and central pathology review. Further assessment on an independent cohort showed an accuracy of 83% of the model. Taken together, these data suggest that complementing pathology reviews with targeted sequencing of 7 genes could improve MDS diagnosis. Disclosures Lindsley: MedImmune: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Bluebird Bio: Consultancy; Takeda Pharmaceuticals: Consultancy. Bejar:Aptose Biosciences: Current Employment; AbbVie/Genentech: Honoraria; Astex/Otsuka: Honoraria; Takeda: Honoraria, Research Funding; Celgene/BMS: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria; Forty-Seven/Gilead: Honoraria; Genoptix/NeoGenomics: Honoraria. DeZern:MEI: Consultancy; Astex: Research Funding; Abbvie: Consultancy; Celgene: Consultancy, Honoraria. Foran:H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Revolution Medicine: Consultancy; Xencor: Research Funding; Agios: Honoraria, Research Funding; Aprea: Research Funding; Actinium: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Komrokji:Acceleron: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Jazz: Honoraria, Speakers Bureau; Geron: Honoraria; Novartis: Honoraria. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria. Padron:Novartis: Honoraria; BMS: Research Funding; Incyte: Research Funding; Kura: Research Funding. Starczynowski:Captor Therapeutics: Consultancy; Tolero Therapeutics: Research Funding; Kurome Therapeutics: Consultancy, Current equity holder in private company, Research Funding. Sekeres:BMS: Consultancy; Takeda/Millenium: Consultancy; Pfizer: Consultancy.