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Background The American Registry for Migraine Research (ARMR) is a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository that collects clinical data, electronic health record (EHR) data, blood samples, and brain imaging data from individuals with migraine or other headache types. In this manuscript, we outline ARMR research methods and report baseline data describing an initial cohort of ARMR participants. Methods Adults with any International Classification of Headache Disorders (ICHD) diagnosis were prospectively enrolled from one of the 8 participating headache specialty centers. At baseline, ARMR participants complete web‐based questionnaires, clinicians enter the participant’s ICHD diagnoses, an optional blood specimen is collected, and neuroimaging data are uploaded to the ARMR neuroimaging repository. Participants maintain the ARMR daily headache diary longitudinally and follow‐up questionnaires are completed by participants every 3 months. EHR data are integrated into the ARMR database from a subset of ARMR sites. Herein, we describe the ARMR methodology and report the summary data from ARMR participants who had, from February 2016 to May 2019, completed at least 1 baseline questionnaire from which data are reported in this manuscript. Descriptive statistics are used to provide an overview of patient’s sociodemographics, headache diagnoses, headache characteristics, most bothersome symptoms other than headache, headache‐related disability, comorbidities, and treatments. Results Data were available from 996 ARMR participants, enrolled from Mayo Clinic Arizona, Dartmouth‐Hitchcock Medical Center, University of Utah, University of Colorado, Thomas Jefferson University, University of Texas Health Science Center at Houston, Georgetown University Medical Center, and DENT Neurological Institute. Among ARMR participants, 86.7% (n = 864) were female and the mean age at the time of enrollment was 48.6 years (±13.9; range 18‐84). The most common provider‐reported diagnosis was chronic migraine (n = 622), followed by migraine without aura (n = 327), migraine with aura (n = 196), and medication overuse headache (n = 65). Average headache frequency was 19.1 ± 9.2 days per month (n = 751), with 68% reporting at least 15 headache days per month. Sensitivity to light was the most frequent (n = 222) most bothersome symptom overall, other than headache, but when present, cognitive dysfunction was most frequently (n = 157) the most bothersome symptom other than headache. Average migraine disability assessment (MIDAS) score was 52 ± 49 (n = 760), (very severe headache‐related disability); however, 17% of the ARMR population had MIDAS scores suggesting “no” or “mild” disability. The most common non‐headache health issues were allergies (n = 364), back pain (n = 296), neck pain (n = 296), depression (n = 292), and anxiety (n = 278). Nearly 85% (n = 695) of patients were using preventive medications and 24.7% were using non‐medication preventive therapy (eg, vitamins and neuromodulation). The most common preventive medication classes were neurotoxins, anticonvulsants, antidepressants, vitamins/supplements, and anticalcitonin gene‐related peptide ligand or receptor‐targeted monoclonal antibodies. Nearly 90% (n = 734) of ARMR participants was taking medications to treat migraine attacks, with the most common classes being triptans, non‐steroidal anti‐inflammatory drugs, antiemetics, acetaminophen, and combination analgesics. Conclusions ARMR is a source of real‐world patient data, biospecimens, and brain neuroimaging data that provides comprehensive insight into patients with migraine and other headache types being seen in headache specialty clinics in the United States. ARMR data will allow for longitudinal and advanced analytics that are expected to lead to a better characterization of patient heterogeneity, healthcare resource utilization, identification of endophenotypes, factors that predict treatment outcomes and clinical course, and ultimately advance the field toward precision headache medicine.

Studies utilizing a systems perspective show that individual work system elements impact surgeon workload. However, limited work has shown how multiple elements together can affect perceived workload in the healthcare domain. Using NASA-Task Load Index (NASA-TLX), this study aimed to compare operating room workload across two work system factors (surgical specialty and case number of the day) using a large set of self-reported surgeon workload data. Thirty-two surgeons completed 545 workload surveys across a three month period. Surgeons reported significant differences in composite workload scores across the surgical specialties (F(7,544)=3.622, p=0.001). Significant interactions were identified between surgical specialty and case number for composite workload, F(20,534)=1.72, p=0.027. While such findings are promising, future work is needed across multiple institutions to establish baseline workload values across specialties with different patient characteristics and work systems.

There is a growing awareness of the physical demands of performing surgery and the need for ergonomic education and training, extending beyond the primary surgeon to other members of the surgical team who are also at risk for musculoskeletal injury. In this study, nine Surgical First Assistants received knowledge-based ergonomic education before their body postures were evaluated using inertial measurement units in an anatomy training lab setting and again in the operating room (OR). Five of those trainees comprised the intervention group, receiving a personalized report detailing their level of ergonomic risk, while the other four did not receive this individual feedback. The intervention group significantly improved their neck and left arm posture during the anatomy lab training with carryover into the OR, indicating some retention of ergonomic concepts, while the control group did not. The integration of wearable technology and individualized feedback into traditional educational settings helped trainees learn about their own behaviors and practice strategies for reducing risks in the OR with greater retention compared to knowledge-based education alone.

Abstract Pediatric large B-cell lymphomas (LBCLs) share morphological and phenotypic features with adult types but have better prognosis. The higher frequency of some subtypes such as LBCL with IRF4 rearrangement (LBCL-IRF4) in children suggests that some age-related biological differences may exist. To characterize the genetic and molecular heterogeneity of these tumors, we studied 31 diffuse LBCLs (DLBCLs), not otherwise specified (NOS); 20 LBCL-IRF4 cases; and 12 cases of high-grade B-cell lymphoma (HGBCL), NOS in patients ≤25 years using an integrated approach, including targeted gene sequencing, copy-number arrays, and gene expression profiling. Each subgroup displayed different molecular profiles. LBCL-IRF4 had frequent mutations in IRF4 and NF-κB pathway genes (CARD11, CD79B, and MYD88), losses of 17p13 and gains of chromosome 7, 11q12.3-q25, whereas DLBCL, NOS was predominantly of germinal center B-cell (GCB) subtype and carried gene mutations similar to the adult counterpart (eg, SOCS1 and KMT2D), gains of 2p16/REL, and losses of 19p13/CD70. A subset of HGBCL, NOS displayed recurrent alterations of Burkitt lymphoma–related genes such as MYC, ID3, and DDX3X and homozygous deletions of 9p21/CDKN2A, whereas other cases were genetically closer to GCB DLBCL. Factors related to unfavorable outcome were age >18 years; activated B-cell (ABC) DLBCL profile, HGBCL, NOS, high genetic complexity, 1q21-q44 gains, 2p16/REL gains/amplifications, 19p13/CD70 homozygous deletions, and TP53 and MYC mutations. In conclusion, these findings further unravel the molecular heterogeneity of pediatric and young adult LBCL, improve the classification of this group of tumors, and provide new parameters for risk stratification.

Abstract Background: Adult acute myeloid leukemia (AML) patients with high-risk cytogenetics have a significantly worse survival compared to similarly treated intermediate- or favorable-risk patients. Although prior studies suggest better outcome in high-risk AML patients in first complete remission (CR1) who undergo allogeneic hematopoietic cell transplantation (HCT) compared with consolidation chemotherapy, only 40% of patients proceed to HCT. The lack of a matched sibling donor (available in about 33%) should not be a barrier to HCT since alternative donors are available for the large majority of high-risk AMLpatients and recent data suggest outcomes after allogeneic HCT from fully matched unrelated donors are similar to those following matched related donor transplantation. We sought to determine if a prospective organized effort could rapidly identify alternative donors to improve the historical 40% allogeneic HCT rate in high-risk CR1 AML patients ≤ age 61. Secondly, we hypothesized that transplanting significantly more adults with high-risk AML in CR1 would lead to an improved outcome compared with the historical relapse-free survival (RFS) of 22%. Patients and Methods: Adult patients between ages 18 and 60 years with untreated AML were randomized to receive induction therapy with standard cytarabine plus daunorubicin (7+3; n=261), idarubicin with high-dose cytarabine (IA; n=261), or IA with vorinostat (IA+V; n=216). Conventional cytogenetics were obtained at time of enrollment and used to determine risk classification by standard criteria. All patients with high-risk cytogenetics underwent expedited HLA-typing. High-risk patientswere encouraged tobe referred for consultation with a transplant team with the goal of conducting an allogeneic HCT in CR1. Results: Of 738 eligible patients (median age, 49 years; range, 18-60), 159 (22%) had high-risk cytogenetics, of whom 60 (38%), 61 (38%), and 38 (24%) received induction with 7+3, IA, or IA+V, respectively. A total of 107 of the 159 high-risk patients achieved CR/CRi (67%). HCT was performed in 317 of all 738 patients (43%) and 68 (64%) of the high-risk patients received a transplant in CR1 (p<0.001 compared to historical rate of 40%). Twenty-five (37%) had a matched related donor, 31 (45%) had a matched unrelated donor, 3 (4%) had a mismatched related donor, 8 (12%) had a mismatched unrelated donor, and 1 (1%) received an umbilical cord blood transplant. Sixty-six high-risk patients transplanted in CR/CRi have detailed data. Median time to HCT from CR1 was 76 days (range, 20-365). Fifty-seven patients (86%) received a myeloablative regimen and 9 (14%) reduced-intensity conditioning. Reasons for 39 high-risk CR1 patients not receiving a transplant in CR1 were: co-morbidities (n=1), death (n=6), no insurance (n=1), no donor (n=1), physician decision (n=3), patient decision (n=3), relapse (n=6), other (n=10), or unknown (n=8). The 2-year RFS estimate in the entire high-risk cohort is 32%, significantly higher than the 22% historical rate (p=0.05). Median RFS in the high-risk CR1 cohort (n=107) was 10 months [range, 1-32* (censored) months]. RFS and OS were similar among HCT patients using matched related [1 year estimates: 40% (95% CI 27%, 74%) and 56% (37%, 74%), respectively] and matched unrelated [1 year estimates: 52% (37%, 75%) and 56% (37%, 74%), respectively] donors in CR1. The HR (reference = unrelated) for RFS was 0.67 (0.32, 1.37) and for OS was 0.88 (0.41, 1.90). Median overall survival (OS) among all patients in the high-risk cohort (n=159) was 12 months [range, 1-33* (censored) months] and was 18 months [range 3-33* (censored) months] for those transplanted in CR1 (Fig. 1). Conclusions: In newly diagnosed adults with AML age 18-60, early cytogenetic testing with an organized effort to identify a suitable allogeneic HCT donorled to a CR1 transplant rate of 64% in the high-risk group, which in turn led to a significant improvement in RFS over historical controls. Better outcomes in poor prognosis AML patients may be achieved simply by rapidly finding unrelated donors and performing allogeneic HCT in CR1 as soon as possible. Clinical Trials Registry: NCT #0180233; Support: NIH/NCI grants: CA180888, CA180819, CA18020, CA180821, CA180863, CA077202; CCSRI #021039 Figure 1 Overall Survival (OS) among all patients in the high-risk cohort, all high-risk patients achieving CR1, and in those high-risk patients transplanted in CR1. Figure 1. Overall Survival (OS) among all patients in the high-risk cohort, all high-risk patients achieving CR1, and in those high-risk patients transplanted in CR1. Disclosures Othus: Glycomimetics: Consultancy; Celgene: Consultancy. Radich:Novartis: Consultancy, Other: laboratory contract; ARIAD: Consultancy; Pfizer: Consultancy; TwinStrand: Consultancy; Bristol-MyersSquibb: Consultancy. Strickland:Alexion Pharmaceuticals: Consultancy; Ambit: Consultancy; Baxalta: Consultancy; Boehringer Ingelheim: Consultancy, Research Funding; CTI Biopharma: Consultancy; Daiichi Sankyo: Consultancy; Sunesis Pharmaceuticals: Consultancy, Research Funding; Abbvie: Research Funding; Astellas Pharma: Research Funding; Celator: Research Funding; Cyclacel: Research Funding; GlaxoSmithKline: Research Funding; Karyopharm Therapeutica: Research Funding; Sanofi: Research Funding. Savoie:AbbVie: Consultancy; Lundbeck: Consultancy; BMS: Consultancy, Honoraria; Velgene: Consultancy; Pfizer: Consultancy; Amgen: Consultancy; Novartis: Consultancy, Honoraria; Jazz: Consultancy. Sekeres:Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Stone:Amgen: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Xenetic Biosciences: Consultancy; Jansen: Consultancy; Pfizer: Consultancy; ONO: Consultancy; Juno Therapeutics: Consultancy; Merck: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Sunesis Pharmaceuticals: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy; Novartis: Consultancy; Celator: Consultancy; Karyopharm: Consultancy. Erba:Seattle Genetics: Consultancy, Research Funding; Pfizer: Consultancy; Jannsen: Consultancy, Research Funding; Juno: Research Funding; Celator: Research Funding; Ariad: Consultancy; Agios: Research Funding; Amgen: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Millennium Pharmaceuticals, Inc.: Research Funding; Incyte: Consultancy, DSMB, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Gylcomimetics: Other: DSMB; Sunesis: Consultancy; Daiichi Sankyo: Consultancy; Astellas: Research Funding.

(Text above this line is not copy/pasted in the abstract body) INTRODUCTION Allogeneic HCT using RIC regimens is the standard treatment for patients with relapsed/refractory cHL, however there is significant heterogeneity amongst the different regimens and a lack of data supporting a preferred RIC regimen. Using the CIBMTR database we evaluate the outcomes of the 3 most commonly used RIC regimens for cHL. METHODS In the CIBMTR registry, 492 adult patients underwent a first alloHCT using either a matched related or unrelated donor for cHL between 2008-2016, utilizing a RIC regimen with either fludarabine/ i.v. busulfan (6.4mg/kg) (Flu/Bu, n=102), fludarabine/melphalan 140mg/m^2 (Flu/Mel140, n=318) or fludarabine/cyclophosphamide (Flu/Cy, n=72). Graft-versus-host disease (GVHD) prophylaxis was calcineurin inhibitor (CNI) plus methotrexate, mycophenolate mofitil (MMF) or other agents, however post transplantation cyclophosphamide (post-CY) was excluded. The primary endpoint was overall survival (OS). Secondary endpoints included acute (a) and chronic (c) GVHD, non-relapse mortality (NRM), relapse/progression and progression-free survival (PFS). Probabilities of OS and PFS were calculated using the Kaplan-Meier estimator. Multivariable regression analysis was performed for GVHD, relapse/progression, NRM, PFS, and OS. Covariates with a p<0.01 were considered significant. RESULTS Baseline characteristics are shown in Table 1. The median patient age of the complete study cohort was only 33 years, with more than 80% receiving a prior autologous HCT. On multivariate analysis (Table 2), the 3 conditioning regimen cohorts were not statistically different in either risk of cGVHD nor risk of grade 3-4 aGVHD. No significant differences were seen in the NRM risk between the three regimens (p=0.54). Similarly, the risk of relapse (p=0.02) and PFS was comparable between regimens (p=0.14). Flu/Cy conditioning was associated with decreased risk of mortality in first 11months after alloHCT (OR 0.28, 95% CI 0.10-0.73, p=0.009, but beyond 11 months post alloHCT it was associated with a significantly higher risk of mortality, (OR 2.46, 95% CI 0.1.32-4.61, p=0.005; Figure 1) [11months post alloHCT cutoff chosen on the basis of the maximum likelihood value in the Cox model]. Four year adjusted PFS and OS were similar across the three regimens at 29% for Flu/Bu, 37% for Flu/Mel140 and 25% for Flu/Cy (p=0.07) for PFS and 62% for Flu/Bu, 59% for Flu/Mel140 and 55% for Flu/Cy (p=0.64) for OS, respectively. Relapse was the most common cause of death across all the regimens, followed by organ failure and GVHD. CONCLUSIONS The most commonly used RIC regimen in alloHCT for cHL is Flu/Mel140, which was compared to Flu/Bu and Flu/Cy, the next most frequently used regimens. The choice of conditioning regimen, in these young cHL patients (median age 33 years) did not confer any benefit in terms of the risk of relapse, decrease in NRM or improvement in PFS. There was no OS benefit between, Flu/Bu and Flu/Mel 140, but Flu/Cy was associated with a significantly higher risk of mortality in patients beyond 11 months from allo-HCT. Novel approaches are still needed to decrease post-HCT relapse risk and improve overall results. Figure 1 Disclosures Ghosh: Seattle Genetics: Consultancy, Speakers Bureau; Genentech: Research Funding; Gilead/Kite: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; Celgene: Consultancy, Research Funding, Speakers Bureau; Forty Seven Inc: Research Funding; Spectrum: Consultancy, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau; Astra Zeneca: Speakers Bureau. Kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy. Sureda:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Gilead: Honoraria; Novartis: Honoraria; Amgen: Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria; Roche: Honoraria; Sanofi: Honoraria; Takeda: Consultancy, Honoraria, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Hamadani:Merck: Research Funding; Janssen: Consultancy; Otsuka: Research Funding; Takeda: Research Funding; Medimmune: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Research Funding; Celgene: Consultancy; Sanofi Genzyme: Research Funding, Speakers Bureau; Pharmacyclics: Consultancy.

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: Less-fit patients with acute myeloid leukemia (AML) or high-risk myelodysplasia (MDS) age 60 years and older constitute the majority of patients with AML/MDS but are not well represented in clinical trials. DNA-methyltransferase inhibitor (HMA) monotherapy (e.g. azacitidine or decitabine) is usual. Overall response rates (ORR) are low; improvement in overall survival relative to supportive care alone is modest, highlighting the critical need for efficient identification of effective novel therapies. Blocking programed cell death protein-1 (PD-1) signaling with nivolumab may increase the sensitivity of AML cells to azacitidine and improve outcomes and is the focus of one arm of the S1612 trial. Signaling through PD-1 contributes to tumor immune evasion and growth in AML [Chen, Cancer Biol Ther 2008]. Increased expression of PD-1 (~40% of AML), is associated with poor HMA response [Ørskov, Oncotarget 2015]. A single center azacitidine/nivolumab non-randomized phase II study in relapsed/refractory AML reported ORR of 33% (23/70), including 22% complete remission/complete remission with incomplete hematologic recovery [Daver, Cancer Discovery 2018]. About 25% of the patients developed grade 2-4 immune toxicities; nivolumab immune-related adverse events led to treatment discontinuation in nearly 1 in 7 patients. Study Design and Methods:The S1612 trial [NCT03092674] is a platform randomized phase II/III clinical trial with a common azacitidine control arm (CA) and two currently active experimental arms (EA). Therapy is intended for community setting: azacitidine/nivolumab; and azacitidine/midostaurin. The innovative design utilizes a phase II go/no-go decision comparing each EA with the CA independently when there are 100 pts/arm and 104 deaths on the EA and CA combined. EAs will proceed to phase III if the null hypothesis (HR=1) is rejected in favor of the EA (15% one-sided alpha). When the two currently active EAs complete phase II accrual, a third EA (decitabine/cytarabine) will open. The CA stays open the entire length of the trial and only concurrently randomized patients will be compared across arms. If an EA proceeds to phase III, 200 additional patients (300 total patients) will be accrued. Phase III analysis occurs 1.5 years after accrual or at 414 deaths (in the respective EA and CA), whichever comes first. The phase III tests the null hypothesis with 4.5% two-sided alpha and 83% power for each EA to detect an improvement in median OS from 10.4 to 15.6 months. Eligible pts are age ≥60 years, newly diagnosed AML with ≥ 20% blasts or myelodysplastic syndrome with excess blasts-2 (MDS-EB-2); deemed by the treating physician unfit for standard cytotoxic chemotherapy; and no prior HMA permitted. Trial in Progress Issues:Between December 2017 and October 2018, 113 patients were screened and 78 randomized to study treatment (median/range age: 75/61-86 years; median/range performance status 1/0-3). Two concerns challenged this trial: 1) required administration of 7-day azacitidine at the enrolling sites created a burden for this population and 2) an early excess grade 5 toxicity signal in the azacitidine/nivolumab arm compared with the control arm. Without a control comparison, this safety signal likely would have been missed. Strategies to address these concerns were developed by the study team. Discussion with the sponsor and US Food and Drug Administration (FDA) focused on allowance of standard-of-care protocol-directed azacitidine administration in the patient's primary care doctor's office rather than at the oncology center. Because of the toxicity concern, the trial was placed on partial clinical hold for further evaluation and possible nivolumab-arm eligibility changes, along with new surveillance and pre-emptive action including prompt steroid initiation for suspected immune-related toxicities. The S1612 trial highlights special concerns when enrolling vulnerable populations onto leukemia clinical trials, and the importance of collaborative strategies including with the FDA to preserve clinical trial integrity for patient benefit. It also demonstrates the efficiency this novel platform design has for therapeutic investigation and, importantly, very early identification of serious toxicity. Updates on accrual and resolution and of these issues will be presented. Disclosures Hay: Kite: Research Funding; Gilead: Research Funding; AbbVie: Research Funding; Janssen: Research Funding; MorphoSys: Research Funding; Seattle Genetics: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Roche: Research Funding; Novartis: Research Funding. Assouline:Janssen: Consultancy, Honoraria, Speakers Bureau; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Speakers Bureau; Abbvie: Consultancy, Honoraria. Walter:Pfizer: Consultancy, Research Funding; Race Oncology: Consultancy; New Link Genetics: Consultancy; Agios: Consultancy; Amphivena Therapeutics: Consultancy, Equity Ownership; Seattle Genetics: Research Funding; Aptevo Therapeutics: Consultancy, Research Funding; Argenx BVBA: Consultancy; Astellas: Consultancy; BioLineRx: Consultancy; BiVictriX: Consultancy; Boehringer Ingelheim: Consultancy; Boston Biomedical: Consultancy; Covagen: Consultancy; Daiichi Sankyo: Consultancy; Jazz Pharmaceuticals: Consultancy; Kite Pharma: Consultancy; Amgen: Consultancy. Foran:Agios: Honoraria, Research Funding. Radich:TwinStrand Biosciences: Research Funding; Novartis: Other: RNA Sequencing. Othus:Celgene: Other: Data Safety and Monitoring Committee; Glycomimetics: Other: Data Safety and Monitoring Committee. Erba:Astellas Pharma: Consultancy; Amgen: Consultancy; Amgen: Consultancy; ImmunoGen: Consultancy, Research Funding; Novartis: Consultancy, Research Funding, Speakers Bureau; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; Pfizer: Consultancy; Pfizer: Consultancy; ImmunoGen: Consultancy, Research Funding; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; Astellas Pharma: Consultancy; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; Seattle Genetics: Consultancy; Seattle Genetics: Consultancy; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Daiichi Sankyo: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau. Michaelis:Pfizer: Equity Ownership, Research Funding; Incyte: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; TG Therapeutics: Consultancy, Research Funding; JAZZ: Other: Data Safety Monitoring Board, uncompensated, Research Funding; BMS: Research Funding; Bioline: Research Funding; ASTEX: Research Funding; Janssen: Research Funding; Millenium: Research Funding; Macrogeneics: Research Funding. OffLabel Disclosure: Off label experimental combination therapies in newly diagnosed AML/MDS will be discussed, including nivolumab and azacitidine.

Introduction: Most patients with newly diagnosed FL treated with rituximab (R) alone or R + chemotherapy will experience prolonged progression-free survival and overall survival (OS), but it remains unclear what factors have the greatest influence on FL-associated and other causes of death in this patient population. We utilized individual patient data from 13 first-line randomized clinical trials from the FLASH database to perform a comprehensive multistate survival analysis to examine and quantify the relationships between clinical characteristics, treatment response, and early, intermediate, and late FL outcomes. Methods: The multistate survival analysis model defined states for "Alive after beginning Induction Treatment (TX)", "Alive after beginning Maintenance TX", "Death due to FL", and "Death from Other Causes" (Figure 1). We used the Aalen-Johansen estimator, a generalization of the Kaplan-Meier estimator, to calculate the likelihood of being in each model state and estimate the course of FL over time. Making no assumptions on the probability distributions and capable of coping with censored observations, the Aalen-Johansen estimator is a convenient and reliable nonparametric estimator for clinical data. Results: Among 7,465 FL patients with median age 56 (range 18-90) years, 49.2% were female; 28.7% Stage I-III, 71.3% Stage IV, and FLIPI was 0-1 (20.0%), 2 (36.8%), ≥ 3 (43.2%). Following initiation of induction treatment, 2-, 5- and 10-year death rates were 1.7%, 3.8%, and 5.8% due to FL, and 0.7%, 2.1%, and 4.8% from other causes (Figure 2). Death rates at 2, 5, and 10 years due to FL and other causes for subgroups based on clinical characteristics and treatment response are shown in Table 1. Notably, patients > 70 years and patients with FLIPI ≥ 3 had worse outcomes and patients achieving CR at 18, 24, and 30 months experienced improved outcomes. Conclusion: This is the largest study using data from randomized trials to quantify the impact of clinical factors on early, intermediate and late mortality by cause of death. We demonstrated that age > 70 years and FLIPI ≥ 3 were linked to increased FL-associated death and response to TX distinguished patients with favorable and poor outcomes. Future analyses should quantify the impact of predictors on the rate/time of FL outcomes in multivariable models. Disclosures Salles: Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. Hoster:Janssen: Research Funding; Roche Pharma AG: Other: Travel Support. Hiddemann:Bayer: Research Funding; Gilead: Consultancy, Honoraria; Vector Therapeutics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria. Herold:Roche: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Gilead: Honoraria; Celgene: Honoraria. Morschhauser:Servier: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Roche/Genentech: Consultancy; BMS: Honoraria; Celgene: Honoraria. Rummel:Roche Pharma AG: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Honoraria; Sandoz: Honoraria. Kimby:AbbVie,: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Gilead: Other: educational lectures. Vitolo:Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gyan:Pfizer: Honoraria. Ladetto:Celgene: Honoraria; Roche: Honoraria; Janssen: Honoraria; Abbvie: Honoraria; Acerta: Honoraria; Sandoz: Honoraria. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Flowers:AstraZeneca: Consultancy; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Optimum Rx: Consultancy; V Foundation: Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding; Denovo Biopharma: Consultancy; Acerta: Research Funding; National Cancer Institute: Research Funding; Millenium/Takeda: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Spectrum: Consultancy;