Warlick, Erica D.

Abstract Background: Hypomethylating agents (HMA) are well established standard of care for patients (pts) with higher-risk MDS (HR-MDS). However, approximately half of the pts do not respond to HMA therapy and most of the responders eventually lose response (HMA failure). There is no standard of care for pts after HMA failure and median overall survival (OS) post HMA failure is around 6 months (Jabbour et al. 2015). While the mutational landscapes and their role in prognosis are increasingly becoming apparent in pts with HR-MDS at diagnosis, mutational profiles at the time of HMA failure and their impact on clinical outcomes are not well understood. Here, using samples collected from a global Phase 3 trial randomizing HR-MDS pts post HMA failure to I.V. rigosertib (RGS) or physician's choice (PC) (INSPIRE: NCT02562443), we analyzed the landscape of driver mutations in HR-MDS after HMA failure and investigated the association with the clinical outcomes. Since RGS is a non-ATP-competitive small molecule RAS mimetic (Athuluri-Divakar 2016), the study also offered an opportunity to test the hypothesis whether HR-MDS pts with oncogenic RAS pathway mutations benefit from RGS. Methods: HR-MDS pts after HMA failure were randomized 2:1 to RGS or PC. All pts failed to respond to or progressed on prior HMA therapy. Bone marrow samples or peripheral blood samples were collected at the time of trial screening. Genomic DNA was sequenced by the targeted capture deep sequencing of 295 genes (median 500x). Results: 372 pts were enrolled in INSPIRE trial (248 to RGS and 124 to PC). The median age of the trial participants was 73 (range: 40-85). All pts were previously treated and with an HMA with the median duration of prior HMA therapy of 6.7 months. 64% and 28% of the pts were classified as IPSS-R very high risk or high risk, respectively, at the time of randomization. Among the 372 participants, DNA sequencing of pre-treatment samples was performed in 188 pts (51% of the participants, N = 122 in RGS arm, N = 66 in PC arm). The most frequently identified driver mutations involved ASXL1 (36%) followed by RUNX1 (24%), TET2 (23%), STAG2 (22%) and TP53 (21%). Mutations in splicing pathway genes were found in 36% of the pts. Oncogenic RAS pathway mutations were detected in 15% of the pts (NRAS = 3 %, KRAS = 2%, CBL = 4%, NF1 = 5%, PTPN11 = 3%, and 1% had multi-hit mutations). Compared to the previously untreated MDS pts (N = 446, Papaemmanuil et al. Blood 2013), mutations in ASXL1 (36% vs. 18%, P < 0.0001), BCOR (9% vs. 3%, P = 0.002), CEBPA (4% vs. 0.2%, P = 0.001), NF1 (5% vs. 0.9%, P = 0.003), RUNX1 (25% vs. 11%, P < 0.0001), STAG2 (22% vs. 5%, P < 0.0001), TP53 (21% vs. 6%, P < 0.0001), and IDH1/2 (13% vs. 7%, P =0.016) were significantly more enriched in pts with HMA failure, whereas mutations in SF3B1 (7% vs. 37%, P < 0.0001), TET2 (23% vs. 35%, P = 0.006), and splicing pathway genes (36% vs. 68%, P < 0.0001) were significantly less frequent in HMA failure pts. These results are consistent with the high-risk profiles of HMA failure pts. Frequency of oncogenic RAS pathway mutations were similar between HMA failure and previously untreated MDS pts (15% vs. 13%, P = 0.612). Correlation analysis between the types of HMA failure and gene mutations showed that TP53 mutations were significantly enriched in pts who relapsed after initial response to HMA (P = 0.001), whereas oncogenic RAS pathway mutations were significantly enriched in pts who progressed during the HMA therapy (P = 0.03). Overall, RGS did not significantly improve the overall survival (OS) of HMA failure pts compared to PC. Survival difference between RGS arm and PC arm was not observed in any subgroups stratified by the gene mutations. The only subgroup that showed improved OS with RGS compared to PC was pts with RAEB-t (median OS 7.5 vs. 3.9 months, P = 0.049). Of note, among pts with oncogenic RAS pathway mutations, no survival difference was observed between RGS and PC arms. Conclusion: High-risk gene mutations, such as TP53, ASXL1, RUNX1, and STAG2 (Ogawa. Blood 2019). were significantly enriched in MDS pts with HMA failure, suggesting their role in HMA resistance and disease progression. Identifying the mutations present de novo and with HMA failure offers the opportunity to determine prognosis based on these mutations as well as potential strategies to target these mutations with new medical entities. Disclosures Takahashi: GSK: Consultancy; Celgene/BMS: Consultancy; Novartis: Consultancy; Symbio Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Luger: Syros: Honoraria; Agios: Honoraria; Daiichi Sankyo: Honoraria; Jazz Pharmaceuticals: Honoraria; Brystol Myers Squibb: Honoraria; Acceleron: Honoraria; Astellas: Honoraria; Pfizer: Honoraria; Onconova: Research Funding; Celgene: Research Funding; Biosight: Research Funding; Hoffman LaRoche: Research Funding; Kura: Research Funding. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Diez-Campelo: BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. OffLabel Disclosure: Rigosertib for MDS patients after HMA failure

Lay Summary People who have advanced myelodysplastic syndromes (MDS) may live longer if they get a bone marrow transplant (BMT) instead of other therapies. However, only 15% of people with MDS actually get BMT. Experts say community physicians and transplant physicians should team up with insurance companies and patient advocacy groups to 1) spread this news about lifesaving advances in BMT, 2) ensure that everyone can afford health care, 3) provide emotional support for patients and families, 4) help patients and families get transportation and housing if they need to travel for transplant, and 5) improve care for people of under‐represented racial and ethnic backgrounds.

Background: Patients with HR-MDS have a dismal prognosis after failure of hypomethylating agents (HMAs) (Zeidan 2014), with median overall survival (OS) of less than 6 months (Prebet 2011) and currently no approved second-line therapy (Garcia-Manero 2016). Targeted therapies with novel mechanisms of action, combination strategies, as well as innovative study designs, are all needed to expedite and address the high unmet medical need in patients with HMA refractory HR-MDS. Rigosertib is a unique targeted therapy that inhibits PI3K and PLK signaling pathways by binding directly to the Ras-binding domain (Athuluri-Divakar 2016) and in vitro cytotoxicity studies have demonstrated synergy with azacitidine (Cosenza 2015). INSPIRE study is an example of a study with a novel compound and unique mechanism of action as well as an innovative study design. Methods: INSPIRE (NCT02562443) is a global randomized Phase 3 trial in patients with HR-MDS after HMA failure. Patients are randomized in a 2:1 fashion to rigosertib or physician's choice of treatment. Key inclusion criteria: age <82 years; MDS classified as RAEB-1, RAEB-2 or RAEB-t; ≥1 cytopenia; patient must demonstrate one of the following: progression any time after initiation of HMA treatment, intolerance to HMA, failure to achieve complete remission (CR), partial remission (PR), or hematologic improvement (HI) after six 4-week cycles of AZA or either four 4-week or four 6-week cycles of DAC, or relapse after initial CR, PR or HI; duration of prior HMA ≤9 cycles within 12 months; last dose of HMA ≤6 months before enrollment; and ECOG score 0-2. The primary endpoint of overall survival (OS) will be tested in a sequential fashion in the intention to treat (ITT) population and the IPSS-R very high risk (VHR) subgroup. Secondary endpoints include OS in patients with monosomy 7 or trisomy 8, overall response, quality-of-life, and HI. The initial sample size was 225 patients with a pre-planned interim analysis (IA) after 88 deaths. INSPIRE featured an adaptive trial design with a pre-planned Sample Size Re-estimation (Cui 1999) to 360 patients and 288 OS events as one option that the Independent Data Monitoring Committee (IDMC) could implement at IA. The adaptive sample size modification of an on-going two-arm, group sequential clinical trial is used to categorize the results for each population into three zones of Unfavorable, Promising, and Favorable. This adaptive design is advantageous as it allows study sample size to be adjusted when there is high variance in estimating the true effect of the drug under investigation which could otherwise result in underpowering of the study. The IDMC had several options following the interim analysis, including continuation of the study as initially planned, discontinuation for futility or safety, trial expansion using pre-planned sample size re-estimation, and continuation for only the pre-defined VHR subgroup. The investigators remain blinded to the specific interim analysis results. Enrollment in the trial is ongoing with topline data expected in 2020. Conclusions: Based on the results of interim analysis, the IDMC recommended continuation of the trial based on ITT result in promising zone with one-time expansion in enrollment, using a pre-planned sample size re-estimation, the sample size for the study was increased from 225 to 360 with unchanged eligibility criteria. The Adaptive Design used real time data from the IA to modify sample size and mitigate the risk of underpowering without undermining its validity and integrity, while preserving type-1 error. The study design used in INSPIRE may be advantageous for other novel agents in rare hematological diseases during the transition from phase 2 to phase 3 studies. Clinical trial information: (NCT02562443). Disclosures Luger: Agios: Honoraria; Ariad: Research Funding; Biosight: Research Funding; Celgene: Research Funding; Cyslacel: Research Funding; Daichi Sankyo: Honoraria; Genetech: Research Funding; Jazz: Honoraria; Kura: Research Funding; Onconova: Research Funding; Pfizer: Honoraria; Seattle Genetics: Research Funding. Al-Kali:Astex Pharmaceuticals, Inc.: Research Funding. Woodman:Onconova Therapeutics, Inc.: Employment. Adesanya:Onconova Therapeutics, Inc.: Employment. Azarnia:Onconova Therapeutics, Inc.: Employment. Parris:Onconova Therapeutics, Inc.: Employment. Jedrzejczak:Roche: Other: travel support for hematology meetings (ASH, EBMT, EHA) ; Novartis: Research Funding; Takeda: Consultancy; Amgen: Consultancy, Other: travel support for hematology meetings (ASH, EBMT, EHA) ; Celgene: Other: travel support for hematology meetings (ASH, EBMT, EHA) . Díez-Campelo:Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding.

Background: More than 45 mutations have been identified in association with HR-MDS. In the majority of patients with MDS (80%) co-mutations are present and the prognostic contribution of each individual mutation remains elusive, especially after adjusting for clinical variables such as IPSS-R score. N-RAS and K-RAS mutations as well as regulators of the Ras pathway (e.g. PTPN11, NF1) are frequently observed (15-20%) in HR-MDS, however their clinical impact is unclear, especially in de novo MDS. Rigosertib (RGS) is a non-ATP-competitive small molecule RAS mimetic that has the potential to block RAS-RAF-MEK-ERK and PI3K-AKT-mTOR signaling pathways (Athuluri-Divakar 2016). Rigosertib has the potential to also inhibit wildtype upregulation of RAS. We report here genomic profiling at the time of study entry in the ongoing phase 3 randomized global study (known as INSPIRE) in patients with HR-MDS after failure of HMA therapy. Methods: INSPIRE (NCT02562443) is a global randomized Ph3 trial in pts with HR-MDS after HMA failure with an overall target enrollment of 360 pts with currently 298 pts randomized. Pts are randomized 2:1 to rigosertib or physician's choice of treatment. The primary endpoint is overall survival (OS). All pts failed to respond or progressed on HMA therapy. Key inclusion criteria includes: age < 82 years, RAEB-1, RAEB-2 or RAEB-t; intermediate risk (IR), high risk (HR) and very high risk (VHR) per IPSS-R; ≥ 1 cytopenia; duration of prior HMA ≤ 9 cycles within 12 months; last dose of HMA ≤ 6 months before enrollment; baseline blast counts between 5-29% and one of the following: progression any time after initiation of HMA treatment, intolerance to HMA, failure to achieve complete remission (CR), partial remission (PR), or hematologic improvement (HI) after six 4-week cycles of AZA or either four 4-week or four 6-week cycles of DAC, or relapse after initial CR, PR or HI. Bone marrow samples were collected at study baseline and throughout the study for mutational analysis as an exploratory endpoint. Baseline blast counts are described as % reported in bone marrow aspirate at screening. Genomic DNA was extracted from diagnostic bone marrow or peripheral blood samples and targeted capture deep sequencing of 295 genes were performed (median sequencing depth 500x) using Agilent's SureSelect custom panel. Modified Mutect and Pindel were used to identify high-confidence somatic mutations. Results: All data is presented as blinded aggregate results for both arms of the study. Baseline mutations are presented for 114 pts; 92 pts were randomized and 22 pts were screen failures. Median age is 72 years (59-81). The IPSS-R scores for the pts randomized were: Intermediate 5(5%), High 30 (32%) and VHR 56 (60%). In total 48 different mutations were identified at baseline prior to pts receiving study treatment. The most common mutations identified in pts were ASXL1 40%, STAG2 26%, TP53 24%, RUNX1 22%, SRSF2 and TET2 each 18%. Average number of mutations per pt was 3.06. At baseline, 4 pts (4%) had no mutations, 17 pts (18%) had only 1 mutation while 17 pts (18%) had between 6-8 mutations. N-RAS and K-RAS mutations occurred in 4 pts each (7% of pts) and all in the presence of other mutations. Mutations involving regulators of the Ras pathway (N-RAS, K-RAS, PTPN11, NF1) occurred in 12 (13%) of patients. Of note, 23 pts (25%) had IDH1 (6 pts) or IDH2 (17 pts) and the majority of these pts (68%) were High/VHR with an average blast count of 15% (range 5-27%) at study entry. The high proportion of IDH1/2 mutations observed is most likely due to inclusion of patients with RAEB-t. These results will be updated at the meeting with blinded baseline mutational analyses for all pts randomized into the study. Conclusion: The baseline mutational analyses from the INSPIRE study provides important initial insights into the genomic profile of pts with HMA failure, especially for the subset with VHR. Following analysis of the primary endpoint, it is anticipated that correlation of overall survival and clinical response with mutational status will be possible, including changes in mutations following therapy. Given the number of mutations involving the Ras pathway the efficacy of rigosertib in patients with this group of mutations will also be examined. Figure Disclosures Garcia-Manero: Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Luger:Agios: Honoraria; Jazz: Honoraria; Kura: Research Funding; Onconova: Research Funding; Pfizer: Honoraria; Seattle Genetics: Research Funding; Daichi Sankyo: Honoraria; Genetech: Research Funding; Cyslacel: Research Funding; Ariad: Research Funding; Biosight: Research Funding; Celgene: Research Funding. Al-Kali:Astex Pharmaceuticals, Inc.: Research Funding. Jedrzejczak:Amgen: Consultancy, Other: travel support for hematology meetings (ASH, EBMT, EHA) ; Celgene: Other: travel support for hematology meetings (ASH, EBMT, EHA) ; Takeda: Consultancy; Novartis: Research Funding; Roche: Other: travel support for hematology meetings (ASH, EBMT, EHA) . Díez-Campelo:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Zbyszewski:Onconova Therapeutics, Inc.: Employment. Cavanaugh:Onconova Therapeutics, Inc.: Employment. Woodman:Onconova Therapeutics, Inc.: Employment. Fruchtman:Onconova Therapeutics, Inc.: Employment. Takahashi:Symbio Pharmaceuticals: Consultancy.

Background With the exception of therapy related MDS due to treatment with alkylating agents and/or radiation or with a topoisomerase II inhibitor, little is known about the etiology of myelodysplastic syndromes (MDS). A few studies have evaluated pre-existing medical conditions as risk factors for MDS, with evidence suggesting that autoimmune disease is associated with an increased risk of MDS. Here, we evaluated associations between history of autoimmune disease, overall and by individual disease subtype, and risk of MDS in a population-based case control study. Methods MDS cases were identified by rapid case ascertainment through the population-based Minnesota Cancer Surveillance System (MCSS). Participants were recruited if they were diagnosed with MDS between April 1, 2010 and October 31, 2014. Eligibility criteria included residence in Minnesota, age at diagnosis between 20 and 85 years, and ability to understand English or Spanish. Centralized pathology and cytogenetics review were conducted to confirm diagnosis and classify by subtypes. Controls were identified through the Minnesota State driver's license/identification card list. History of autoimmune disease was reported using a self-administered questionnaire; proxy interviews were not conducted. Unconditional logistic regression with adjustment for age, sex and confounders (education, NSAID use, benzene exposure, BMI) was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CI) for autoimmune disease and MDS. Results A total of 399 cases with a confirmed diagnosis of MDS and 1399 controls were included. Cases were significantly more likely to report a diagnosis of any autoimmune disease when compared with controls (OR=1.49, 95% CI 1.13-1.97). As illustrated in Figure 1, specific associations were observed for hypothyroidism (OR=2.07, 95% CI 1.39-3.08), ulcerative colitis (OR=2.26, 95% CI 1.09-4.69), Crohn's disease (OR=3.88, 95% CI 1.23-12.2), and systemic lupus erythematosus (SLE; OR=7.52, 95% CI 1.98-28.6). Autoimmune conditions were more commonly reported in both female cases and female controls when compared with males; however, associations for hypothyroidism and ulcerative colitis were significantly associated with MDS in males in an analysis stratified by sex. Associations between autoimmune disease and MDS remained statistically significant after exclusion of therapy-related MDS cases. Discussion Our results validate previous findings of an association between autoimmune disease and MDS risk from population-based registry studies and case-control studies. In addition, our results provide additional evidence to suggest that this association is largely driven by hypothyroidism, inflammatory bowel disease, and SLE. This increased MDS risk following a diagnosis for an autoimmune condition is hypothesized to be due to shared genetic or environmental risk factors, treatment for autoimmune diseases, altered immune surveillance or damage to the bone marrow caused by the autoimmune condition. Further studies are required to confirm which of these is the most plausible explanation. Disclosures No relevant conflicts of interest to declare.

Although some data (Scott, JCO 2017) suggest that myeloablative conditioning (MAC) is preferred for allogeneic hematopoietic cell transplantation (HCT) in acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS), these data were not informed by analysis of disease specific risk factors. We analyzed AML and MDS HCT outcomes stratified by the disease risk index (DRI) in order to identify the preferred transplant conditioning intensity (reduced-intensity conditioning [RIC] vs. MAC). In this large CIBMTR registry study we identified 4387 adult patients (age 40-65 years) who received HCT for AML (68%) or MDS (32%) between 2009 and 2015. DRI was stratified as low/ intermediate risk (1539 MAC and 999 RIC) and high/ very high risk (1121 MAC and 728 RIC). Examining the low/ intermediate risk DRI cohort (Table), RIC was associated with lower risk of TRM (HR=0.74, 95% CI 0.62-0.88; p<0.001) but significantly higher risk of relapse (HR=1.54, 95% CI 1.35-1.76; p<0.001). As a result, RFS in this cohort was significantly worse with RIC (HR=1.19, 95% CI 1.07-1.33; p=0.001). In the high/ very high risk DRI cohort, RIC resulted in similar TRM (HR=0.83, 95% CI 0.68-1.00; p=0.051) but again significantly higher risk of relapse (HR=1.23, 95% CI 1.08-1.41; p=0.002). RFS in high/ very high risk DRI cohort was similar between RIC and MAC. Adjusted outcome curves for the 3 endpoints are shown in the Figure. In this large study of HCT for AML or MDS stratified by DRI, RIC was independent predictor of lower TRM, but significantly higher risk of relapse. The MAC was an independent predictor of lower relapse in both low/ intermediate and high/very high DRI groups. However, MAC only resulted in RFS benefit in the low/ intermediate group where the magnitude of impact on relapse was not offset by the higher TRM. In adults with AML or MDS aged 40-65 years, these data support MAC as the preferred conditioning intensity for low/ intermediate risk DRI, whereas MAC does not provide significant benefit in those with high/ very high risk DRI. Safer, yet still potent MAC regimens could benefit this higher risk group. Disclosures Bejanyan: Kiadis Pharma: Other: advisory board. Brunstein:Gamida: Research Funding; Astex: Research Funding; Magenta: Research Funding. Kebriaei:Amgen: Research Funding; Jazz: Consultancy; Pfizer: Honoraria; Kite: Honoraria; Pfizer: Honoraria; Kite: Honoraria. Weisdorf:Fate Therapeutics: Consultancy; Pharmacyclics: Consultancy; Incyte: Research Funding.

Background Maintenance of telomere length has long been established to play a role in the biology of cancer, and several lines of evidence suggest that it may be especially important in myeloid malignancy. Measuring leukocyte telomere length (LTL) directly in case control studies is problematic because telomere length is likely to be influenced by the disease process. Recent studies have led to the identification of a robust genetic predictor of LTL, which we have used to compare differences in predicted telomere length in case control studies of myeloid leukemia and myelodysplastic syndromes (MDS) using Mendelian randomization (MR). MR is a method used to measure the association between a trait (e.g. telomere length) and an outcome (e.g. myeloid malignancy) that can't be measured directly by utilizing genetic variants known to be associated with the trait as instrumental variables. The use of genetic predictors of telomere length reduces the possibility that the association is explained by reverse causation and confounding likely to be relevant in case-control studies where telomere length is measured directly because genotypes in the general population should be randomly distributed. Additionally, predicted telomere length has the added advantage of representing telomere length over the lifetime of the individual while measuring LTL directly will represent only one time point in an individual's life. Methods Myeloid leukemia (AML and CML) and MDS cases were identified by rapid case ascertainment through the Minnesota Cancer Surveillance System (MCSS). Centralized pathology and cytogenetics reviews were conducted to confirm diagnosis and classify by subtypes. Controls were identified through the Minnesota State driver's license/identification card list. We used the Sequenom platform to genotype seven SNPs that were validated predictors of LTL in a recently published meta-analysis. We estimated associations between individual SNPs and myeloid malignancy using multivariable logistic regression. Mendelian randomization was used to evaluate the association between predicted LTL and risk of myeloid malignancy. Results We included 253 AML cases, 353 MDS cases, 145 CML cases, and 1,042 controls. We observed a significant association between longer predicted telomere length and AML in analyses adjusted for sex and age (OR 4.82 per additional kilobase of average telomere length, 95% CI 1.32-17.63). The individual SNP analyses suggest that the association is largely driven by rs10936599, located in TERC (OR 1.47 per allele, 95% CI 1.14-1.90; Figure). We did not observe statistically significant associations between predicted LTL and MDS or CML. Discussion In this analysis of predicted telomere length and myeloid malignancy, we identified a significant association between longer predicted leukocyte telomere length and AML. In contrast, no significant association was observed for MDS or CML although we did observe an elevated OR for longer predicted telomere length and MDS that did not reach statistical significance. Figure Disclosures No relevant conflicts of interest to declare.

Abstract Myelodysplastic syndromes (MDS) are a heterogeneous collection of clonal disorders of hematopoietic stem cells characterized by ineffective hematopoiesis, dysplasia, and risk of progression to secondary acute myeloid leukemia (AML). Despite the development of numerous prognostic scoring systems (MDS Comorbidity Index (MDS-CI),International Prognostic Scoring System (IPSS) and IPSS-R, updated WHO classifications, and WHO prognostic scoring system (WPSS)), little prospective data regarding the influence of these and other factors on patient outcomes is available. To better elucidate the features of early mortality in MDS we compare characteristics of patients dying within one year of MDS diagnosis with those surviving longer in our Adults in Minnesota with MDS (AIMMS) population based case-control study. The AIMMS study is a statewide prospective population-based case-control study (R01 CA142714) conducted by the University of Minnesota (UMN), Mayo Clinic, and the Minnesota Department of Health. Adults (age 20-85 years) with a new diagnosis of MDS between April 2010 and October 2014 were recruited through the Minnesota Cancer Surveillance System. Patients completed a comprehensive questionnaire to capture retrospective epidemiologic data. All cases went through central medical review including pathology review by two independent hematopathologists, cytogenetic analyses, and oncologist medical record review with assignment of IPSS, IPSS-R, WPSS 1.2 noting past medical history, exposures, and treatment history and response. Annual clinical review of all patient cases for four years after initial enrollment is ongoing in a batched, non-real time manner. Three hundred and ninety-nine patients with a confirmed diagnosis of MDS based on central review and one year of clinical follow-up review were included in the analysis. For the entire group, we observed early mortality in those with abnormal cytogenetics, three or greater cytogenetic abnormalities, treatment at a community medical center only (versus academic), and with 2-3 concurrent medical comorbidities (Table 1). Treatment with hypomethylating agents also correlated with early mortality but when adjusted for WPSS and IPSS-R, this association was no longer significant. To investigate varied impact of disease and patient characteristics within different groups of MDS patients, we did multivariable regression analysis within the following categories: High/Very High Risk IPSS-R; Very low/Low/Intermediate Risk IPSS-R; Treated Patients; Supportive Care Only Patients. In patients with high or very high risk IPSS-R, the presence of 3 or more cytogenetic abnormalities was the only significant predictor early mortality in a multivariable adjusted model (OR: 3.66, 95% CI: 1.57-8.53). Similarly, in those with very low, low, or intermediate IPSS-R, abnormal cytogenetics was the only significant predictor of early mortality in an adjusted model (OR: 3.71, 95% CI 1.49-9.26). In patients receiving supportive care only, early mortality was seen in those who had diabetes (OR: 3.06, 95% CI 1.11-8.42), had complex cytogenetics (OR for ≥ 3 abnormalities: 4.94, 95% CI 1.25-19.46), and had very high or high IPSS-R (OR: 4.20, 95% CI 1.43-12.34). Likewise, complex cytogenetics remained the sole significant predictor of early mortality in treated patients (OR: 4.84, 95% CI 1.43-16.37). Complex cytogenetics and prognostic risk category (either by WPSS or IPSS-R) have previously been associated with higher risk disease and early mortality without intervention. Our data confirm this association in a large prospectively followed MDS cohort and highlight the significance of cytogenetic abnormalities and complexity regardless of IPSS-R risk categorization or treatment. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction Expanding treatment options for MDS have changed therapeutic decision-making for clinicians. To better characterize therapeutic choices in newly diagnosed MDS, we report the practice patterns captured during the first year of MDS diagnosis for patients enrolled in our statewide population-based study. We highlight a comparison of treatment in community and academic centers. Methods Adults in Minnesota with MDS (AIMMS) is a statewide prospective population-based study conducted by the University of Minnesota (UMN), Mayo Clinic, and Minnesota Department of Health. Starting in April 2010, all newly diagnosed adult cases (ages 20+) of MDS were invited to participate. After patient enrollment, central review was performed consisting of independent hematopathology and cytogenetic review coupled with oncologist chart review assigning prognostic risk scores [International Prognostic Scoring System (IPSS) and IPSS-R (Revised)] and abstracting treatment exposures. All enrolled patients with one year follow-up were included in this analysis. Treatment was divided into supportive, active, transplant, or other. Supportive care included observation, growth factors, and transfusions. Active care included azacitidine, decitabine, lenalidomide, or 7+3 chemotherapy. Academic centers were defined as the UMN and Mayo Clinic; all other centers were designated as community based practices. Results The median patient age was 73 years, with 68% males. IPSS and IPSS-R risk scores were calculated for 100% and 97% of patients, respectively. Treatment choices stratified by IPSS risk group showed 89% low risk, 53% INT-1, 31% INT-2, and 13% high risk with supportive care; active and transplant strategies were utilized for 9% low risk, 44% INT-1, 64% INT-2, and 88% high risk. INT-1 in the community received 70% supportive treatment, in academic 35%. Active treatment for INT-1 was 30% in community and 45% in academic. Community INT-2 received supportive care in 45% of cases, in academic 23%. Transplants were limited to academic centers, with the highest rate in INT-2 at 34%. Among community diagnoses, 100% of high risk, 52% INT-2, 26% INT-1, and 13% low risk were referred to an academic center. Comparison of age <65 and 65+ years showed 83% of transplants occurred in those <65. INT-2/high risk group patients <65 received 95% active therapy or transplant, compared to 51% of those 65+. Discussion This prospective, population based study provides a well-defined patient cohort based on central review of pathologic and clinical data. Evaluation of practice patterns during the first year after diagnosis showed higher utilization of active and transplant treatment strategies as IPSS risk score increased. Further, compared to community, higher utilization occurred for patients at academic centers, suggesting more aggressive treatment in these settings. Age was also a predictor of treatment choice. In addition, referral patterns followed IPSS score. Whether these treatment differences are driven by patient preference and/or translate into improved disease control and decreased mortality requires continued prospective analysis and will be detailed in future reports. Disclosures No relevant conflicts of interest to declare.