Citations

Abstract Objective To design, develop, and evaluate a scalable clinical data normalization pipeline for standardizing unstructured electronic health record (EHR) data leveraging the HL7 Fast Healthcare Interoperability Resources (FHIR) specification. Methods We established an FHIR-based clinical data normalization pipeline known as NLP2FHIR that mainly comprises: (1) a module for a core natural language processing (NLP) engine with an FHIR-based type system; (2) a module for integrating structured data; and (3) a module for content normalization. We evaluated the FHIR modeling capability focusing on core clinical resources such as Condition, Procedure, MedicationStatement (including Medication), and FamilyMemberHistory using Mayo Clinic’s unstructured EHR data. We constructed a gold standard reusing annotation corpora from previous NLP projects. Results A total of 30 mapping rules, 62 normalization rules, and 11 NLP-specific FHIR extensions were created and implemented in the NLP2FHIR pipeline. The elements that need to integrate structured data from each clinical resource were identified. The performance of unstructured data modeling achieved F scores ranging from 0.69 to 0.99 for various FHIR element representations (0.69–0.99 for Condition; 0.75–0.84 for Procedure; 0.71–0.99 for MedicationStatement; and 0.75–0.95 for FamilyMemberHistory). Conclusion We demonstrated that the NLP2FHIR pipeline is feasible for modeling unstructured EHR data and integrating structured elements into the model. The outcomes of this work provide standards-based tools of clinical data normalization that is indispensable for enabling portable EHR-driven phenotyping and large-scale data analytics, as well as useful insights for future developments of the FHIR specifications with regard to handling unstructured clinical data.

Pontocerebellar hypoplasia (PCH) is a group of neurological disorders that affect the development of the brain, in particular, the pons and cerebellum. Homozygous mutations of TBC1D23 have been found recently to lead to PCH; however, the underlying molecular mechanisms remain unclear. Here, we show that the crystal structure of the TBC1D23 C-terminal domain adopts a Pleckstrin homology domain fold and selectively binds to phosphoinositides, in particular, PtdIns(4)P, through one surface while binding FAM21 via the opposite surface. Mutation of key residues of TBC1D23 or FAM21 selectively disrupts the endosomal vesicular trafficking toward the Trans-Golgi Network. Finally, using the zebrafish model, we show that PCH patient-derived mutants, impacting either phosphoinositide binding or FAM21 binding, lead to abnormal neuronal growth and brain development. Taken together, our data provide a molecular basis for the interaction between TBC1D23 and FAM21, and suggest a plausible role for PtdIns(4)P in the TBC1D23-mediating endosome-to-TGN trafficking pathway. Defects in this trafficking pathway are, at least partially, responsible for the pathogenesis of certain types of PCH.

44 Background: A noninvasive cfDNA blood test detecting multiple cancers at earlier stages could decrease cancer mortality. In earlier discovery work, whole-genome bisulfite sequencing outperformed whole-genome and targeted sequencing approaches for multi-cancer detection across stages at high specificity. Here, multi-cancer detection and TOO localization using bisulfite sequencing of plasma cfDNA to identify methylomic signatures was evaluated in preparation for clinical validation, utility, and implementation studies. Methods: 2301 analyzable participants (1422 cancer [ > 20 tumor types, all stages], 879 non-cancer) were included in this prespecified substudy from the Circulating Cell-free Genome Atlas (CCGA) (NCT02889978) study - a prospective, multi-center, observational, case-control study with longitudinal follow-up. Plasma cfDNA was subjected to a targeted methylation sequencing assay using high-efficiency methylation chemistry to enrich for methylation targets, and a machine learning classifier determined cancer status and tissue of origin (TOO). Observed methylation fragments characteristic of cancer and TOO were combined across targeted regions and assigned a relative probability of cancer and of a specific TOO. Results: Performance is reported at 99% specificity (ie, a combined false positive rate across all cancer types of 1%), a level required for population-level screening. Across cancer types, sensitivity ranged from 59 to 86%. Combined cancer detection (sensitivity [95% CI]) was 34% (27-43%) in stage I (n = 151), 77% (70-83%) in stage II (n = 171), 84% (79-89%) in stage III (n = 204), and 92% (88-95%) in stage IV (n = 281). TOO was provided for 94% of all cancers detected; of these, TOO was correct in > 90% of cases. Conclusions: Detection of multiple deadly cancers across stages using methylation signatures in plasma cfDNA was achieved with a single, fixed, low false positive rate, and simultaneously provided accurate TOO localization. This targeted methylation assay is undergoing validation in preparation for prospective clinical investigation as a cancer detection diagnostic. Clinical trial information: NCT02889978.

Abstract Background: It has been known for approximately 19 years that germline mutations in RUNX1, lead to familial platelet disorder with predisposition to myeloid malignancy (FPD-MM, OMIM 601399). Since that time researchers have identified a broad range of different RUNX1 mutations, in over 100 families. In large families, the diagnosis of malignancy shows variable penetrance among family members with the same mutation; some carriers of RUNX1 mutations do not develop malignancy. The causes of this heterogeneity are currently not known, complicating counselling and risk analysis for individual carriers. Recent advances in genetic sequencing technology applied by many FPD-MM research groups around the world have highlighted their value in understanding the somatic genetic changes that are associated with development of malignancies in germline RUNX1 mutation carriers. Collectively this information could lead to powerful insights essential for more precise risk assessment, monitoring, and therapeutic intervention. Specifically, a growing catalogue of somatic mutations associated with germline RUNX1 malignancy offers the opportunity for informed monitoring of asymptomatic RUNX1 carriers for additional high-risk somatic mutations, in turn providing the possibility for early therapeutic intervention to arrest the leukemic process. The challenge in advancing these goals for FPD-MM is the relative rarity of the disorder in individual populations. Global data sharing in a highly interactive FPD-MM research community offers a solution to this problem that benefits all patients world-wide. Aims: To create a global RUNX1 network through identifying and contacting researchers and clinicians with known and novel germline RUNX1 families, seeking their collaboration to share genomics data. To create a RUNX1.db portal to collectively house and analyse genomics data from germline RUNX1 carriers, with associated phenotype and clinical information, such that researchers have an ongoing means by which to combine their data with those generated by other groups around the world. Methods: RUNX1 network : Through existing collaborative networks, a systematic review of the literature, and referrals from initial contacts, we have identified a global network of researchers managing FPD-MM cases and families. RUNX1.db: We have adapted a custom-built variant analysis platform, VariantGrid, that is a visual web application and database designed to help scientists manage and analyse DNA variants that can be used to aggregate and analyse multiple datasets. Results: Preliminary analysis of aggregated data from the literature suggests there are features of germline RUNX1 syndrome that can be ascertained. These include frequent somatic mutation of RUNX1 in malignancy development, as well as mutations in genes associated with clonal hematopoiesis that may precede development of overt leukemia. This analysis also suggests that different types of germline RUNX1 mutations may be associated with different combinations of somatic mutations in the tumour. To further this analysis, we have identified over 70 groups internationally that either manage RUNX1 families or have identified potential germline carriers through genomics initiatives. This represents a large and growing resource for both scientific studies and clinical programs to benefit individuals with FPD-MM. Many of these groups have generated NGS data sets from patient samples which will be available for analysis through this portal. Further details and activities of the network, and results from the genomics aggregation database will be presented. Conclusion: We have created a global RUNX1 network, aggregated their data, and generated a RUNX1.db genomics portal for the continuous curation of genomics data from germline RUNX1 carriers. A preliminary analysis has already identified specific features of germline RUNX1 mutated malignancies that have clinical importance. Ongoing scientific and clinical studies through the RUNX1 network will enhance the power of aggregated data analysis, with RUNX1.db providing a central link, driving new insights that benefit patients. Disclosures Natsoulis: Imago BioSciences, Inc.: Consultancy, Equity Ownership. Guzman:Cellectis: Research Funding. DiNardo:Bayer: Honoraria; Karyopharm: Honoraria; Celgene: Honoraria; Agios: Consultancy; Medimmune: Honoraria; Abbvie: Honoraria. Borate:Novartis: Consultancy; Agios: Consultancy. Wei:Amgen: Honoraria, Other: Advisory committee, Research Funding; Pfizer: Honoraria, Other: Advisory committee; Celgene: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau. Dokal:MRC, Bloodwise, Telomerase Activator Sciences: Research Funding; The Gary Woodward Dyskeratosis Congenita Trust: Membership on an entity's Board of Directors or advisory committees; Action Medical Research, European School of Haematology: Membership on an entity's Board of Directors or advisory committees; Barts and The London School of Medicine and Dentistry, Queen Mary University of London,: Employment, Research Funding; Telomerase Activator Sciences: Research Funding; Barts and The London, Queen Mary University of London: Employment; Gary Woodward Dyskeratois Congenita Trust: Membership on an entity's Board of Directors or advisory committees. Hiwase:Novartis: Research Funding; Celgene: Research Funding. Branford:Cepheid: Honoraria; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Qiagen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Kramer:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Research Funding; Daiichi Sankyo: Consultancy. Owen:Merck: Honoraria; Teva: Honoraria; AbbVie: Research Funding; Pharmacyclics: Research Funding; Janssen: Honoraria, Research Funding; Celgene: Research Funding; AstraZeneca: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Honoraria, Research Funding. Fitzgibbon:Epizyme: Consultancy, Research Funding; Gilead: Consultancy. Rienhoff:Imago BioSciences, Inc.: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Kurokawa:Astellas Pharma: Research Funding; Sumitomo Dainippon Pharma: Research Funding; Nippon Sinyaku: Honoraria, Research Funding; Kyowa Hakko Kirin: Honoraria, Research Funding; Eizai: Research Funding; MSD: Honoraria, Research Funding; Ono Pharmaceutical: Honoraria, Research Funding; Pfizer: Research Funding; Takeda Pharmaceutical: Research Funding; Otsuka Pharmaceutical: Research Funding; Teijin Pharma: Research Funding; Chugai Pharmaceutical: Research Funding.

Abstract Background: Bendamustine and rituximab (BR) is a commonly chosen frontline treatment for grade 1-2 (G 1-2) follicular lymphoma (FL). This regimen resulted in significantly longer progression-free survival (PFS) and less toxicity compared to R-CHOP in the STiL trial [Rummel et al., 2013] and similar results were observed when comparing BR vs. R-CHOP/R-CVP in the confirmatory BRIGHT trial [Flinn et al., 2014, updated ASCO 2017]. Importantly, patients (pts) with grade 3A (G 3A) FL were excluded from these studies, yet the conclusions are often extrapolated to the treatment of G 3A pts. Notably, G 3A pts were included in the GALLIUM trial which used both bendamustine as well as CHOP backbones. Several retrospective studies of FL pts treated with frontline R-CHOP have demonstrated equivalent or improved overall survival (OS) for G 3A relative to G 1-2 FL (Koch et al., 2016, Mustafa et al., 2017, Yuan et al., 2017, Maeshima et al., 2013). Early disease progression after diagnosis and treatment with frontline R-CHOP has been identified as a strong predictor of poor OS in FL pts [Casulo et al. 2015], but has not been assessed in pts treated with frontline BR. We retrospectively evaluated outcomes of a large cohort of FL pts treated with frontline BR and stratified the results based on histologic grade and early vs. late progression. Methods: We reviewed medical records of adult (age >18) pts with FL treated with frontline BR at 18 US cancer centers. There was no central pathology review; each academic institution confirmed the diagnosis and grade of FL. Pts with unknown grade, grade 3B, or cutaneous FL were excluded. Baseline characteristics between grades were evaluated with the Chi-Square test for categorical variables and the Mann-Whitney U for continuous variables. Outcomes were calculated from time of initiation of BR. Patients were grouped according to whether or not they had progression of disease within 24 months of BR initiation (POD24). OS and PFS were estimated using the Kaplan-Meier method and compared using the log-rank test. Results: 687 pts were included (616 G 1-2, 71 G 3A). Median age at diagnosis was 60 years (range 21-94) with 53% men. The median time from diagnosis to treatment with BR was 1 month (range 0-139). The median duration of follow up for the entire cohort was 39 months. Characteristics including age, gender, ethnicity, ECOG, stage, LDH, and FLIPI are shown in the Table, and did not significantly differ between G 1-2 and G 3A pts. Rates of complete response (CR) and partial response (PR) to BR were similar between G 1-2 and G 3A (72%/22% vs. 66%/21%, respectively, p=0.114) but progressive disease (PD) was higher in G 3A pts (11.9%) relative to G 1-2 (4.8%, p=0.025). As shown in the Figure (A and B), 3-year PFS and OS was significantly longer for G 1-2 vs. G 3A pts (75% vs. 65%, log rank p= 0.035 and 90% vs. 86%, log rank p=0.007, respectively). Seventy-six (12.3%) of the 616 G 1-2 pts and 13 (18.3%) of the 71 G 3A pts experienced POD24 (p=0.19). For pts with both G 1-2 and G 3A FL, POD24 was associated with inferior OS (3-year OS 95% vs. 57% for G 1-2 pts, log rank p<0.0001 and 3-year OS 93% vs. 37% for G 3A pts, log rank p<0.0001) compared to patients without POD24. Conclusions: G 3A FL pts have an inferior OS and are significantly more likely to have PD to frontline BR compared to G 1-2, which differs from the published experience with R-CHOP. Similar to outcomes after frontline treatment with R-CHOP, POD24 after frontline BR for FL is associated with very poor OS. Future studies are needed to address optimal frontline management of pts with G3A as well as for pts with any grade FL with POD24 after frontline BR. Disclosures Nastoupil: Novartis: Honoraria; Genentech: Honoraria, Research Funding; Gilead: Honoraria; Celgene: Honoraria, Research Funding; TG Therappeutics: Research Funding; Karus: Research Funding; Merck: Honoraria, Research Funding; Spectrum: Honoraria; Janssen: Research Funding; Juno: Honoraria. Cerhan:Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding; Nanostring: Research Funding. Maurer:Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Smith:Genentech: Research Funding; Incyte Corporation: Research Funding; Portola Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Merck Sharp and Dohme Corp.: Consultancy, Research Funding; Acerta Pharma BV: Research Funding; Seattle Genetics: Research Funding. Lossos:Affimed: Research Funding. Portell:TG therapeutics: Research Funding; Amgen: Consultancy; Kite: Research Funding; AbbVie: Research Funding; BeiGene: Research Funding; Acerta: Research Funding; Genentech/Roche: Consultancy, Research Funding; Infinity: Research Funding. Calzada:Seattle Genetics: Research Funding. Cohen:Bristol-Myers Squibb: Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; BioInvent: Consultancy. Ghosh:Spectrum: Consultancy; SGN: Consultancy, Research Funding, Speakers Bureau; Pharmacyclics, an Abbvie Company: Consultancy, Research Funding, Speakers Bureau; TG Therapeutics: Honoraria, Research Funding; Celgene: Consultancy; Juno: Consultancy, Research Funding; Abbvie: Consultancy, Speakers Bureau; Genentech: Research Funding; F. Hoffman-La Roche Ltd: Research Funding; PCYC: Consultancy, Research Funding, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Forty seven Inc: Research Funding. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Caimi:Kite Pharma: Other: Advisory Board Participation; Genentech: Other: Advisory Board PArticipation, Research Funding; Celgene: Speakers Bureau; Kite Pharma: Other: Advisory Board Participation. Danilov:Gilead Sciences: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; Astra Zeneca: Consultancy; Genentech: Consultancy, Research Funding; Takeda Oncology: Research Funding; TG Therapeutics: Consultancy; Verastem: Consultancy, Research Funding. Martin:AstraZeneca: Consultancy; Seattle Genetics: Consultancy; Janssen: Consultancy; Kite: Consultancy; Gilead: Consultancy; Bayer: Consultancy. Kamdar:Seattle Genetics: Speakers Bureau; Genentech: Consultancy. Kahl:AstraZeneca: Consultancy; Acerta: Consultancy; Juno: Consultancy; CTI: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Seattle Genetics: Consultancy; Abbvie: Consultancy; Genentech: Consultancy; ADC Therapeutics: Consultancy. Hill:Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Allogeneic hematopoietic stem cell transplantation (HCT) is the only curative therapy for myelofibrosis (MF). Consideration of HCT is recommended by international working groups and national guidelines for MF patients (pts) age <70 with intermediate-1 with adverse indicators, intermediate-2 or high-risk disease by the Dynamic International Prognostic Scoring System (DIPSS) for MF- a recommendation made in the absence of clear data indicating the optimal timing of HCT for MF. In this large multicenter retrospective study, we analyze overall survival in MF pts treated with and without HCT. Methods: Disease characteristics, treatments, and outcome data from MF pts receiving non-transplant therapy at 14 US academic medical centers between 2000-2014 were retrospectively collected. MF pts who underwent HCT were identified from the Center for International Blood and Marrow Transplant Research (CIBMTR). The Cox proportional hazards model was used. The reference time point (time zero) was time of referral for the non-transplant (non-HCT) arm and the time of transplant for the HCT arm. The main effect variable (HCT vs. non-HCT) violated the proportionality assumption where comparing to non-HCT, mortality was higher with HCT in early time period from time zero but then was lower in late time period; therefore, the comparison is presented as early time period and late time period. The Cox model identified 14 months from time zero as the ideal cut point to define early and late time periods. The proportionality assumption is satisfied within each of these two periods. Results: A total of 1377 and 551 pts were included in the non-HCT and HCT arms, respectively (Table 1). In the overall cohort, survival was higher with non-HCT vs. HCT in early time period (relative risk [RR]: 0.34, P< .0001, Figure 1D), but in late time period survival was lower with non-HCT vs. HCT (RR: 2.37, P< 0.001) (Table 2). In the DIPSS low-risk MF group, while survival was higher with non-HCT vs. HCT in the early time period (RR: 0.19, P=0.007, Figure 1A), survival was lower with non-HCT in the late time period, but the latter did not reach statistical significance (RR: 1.45, P=0.39). In the DIPSS intermediate-1 risk group, a survival advantage was present with non-HCT treatments vs. HCT in the early time period (RR: 0.27, P < .0001, Figure 1B), however survival was lower with non-HCT in the late time period (RR: 3.13, P < .0001). Similarly, in those with DIPSS intermediate-2 and high-risk MF, survival advantage was observed with non-HCT in the early time period (RR: 0.41, P< .0001, Figure IC), but survival was lower with non-HCT in the late time period (RR: 2.82, P < .0001). Conclusion: A long-term survival advantage with transplant was observed for pts with intermediate-1 or higher risk MF, but at the cost of potential early mortality. The magnitude of benefit increased as DIPSS risk score increased. Although this retrospective study has limitations, the results have an impact on clinical practice by suggesting that transplantation could be considered earlier in the disease course and supports the recommendation for consideration of HCT in the setting of intermediate-1 risk MF. Disclosures Gowin: Incyte: Consultancy, Other: Scientific Advisory Board, Speakers Bureau. Verstovsek:Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Incyte: Consultancy; Italfarmaco: Membership on an entity's Board of Directors or advisory committees. Ali:Incyte Corporation: Membership on an entity's Board of Directors or advisory committees. Gupta:Novartis: Consultancy, Honoraria, Research Funding; Incyte: Research Funding. Gerds:Celgene: Consultancy; Apexx Oncology: Consultancy; CTI Biopharma: Consultancy; Incyte: Consultancy.

Abstract Introduction: In the ASPIRE and ENDEAVOR trials, multiple myeloma (MM) patients treated with carfilzomib (K) had significantly improved progression‐free survival and overall survival compared with standard of care. The incidence of all-grade adverse cardiovascular events (ACVE) was 26.6% and 24.5% in the K treated groups in ASPIRE and ENDEAVOR respectively. The atherosclerotic cardiovascular disease (ASCVD) score is a risk stratification tool used by cardiologists to classify patients with a score ≥7.5% as high risk for the incidence of ASCVD events. To date, there are no clinically relevant models that predict the likelihood of ACVE in MM patients treated with K nor are we aware of any protective factors against ACVE. Our study aims to identify factors which can predict and mitigate the incidence of ACVE. Methods: A retrospective chart review of 372 MM patients who were treated with K between 2011 and 2018 at our institution was performed.Data were summarized using descriptive statistics; Chi-square tests of association and Kruskal-Wallis tests were employed to test for differences across groups, where appropriate. Logistic regression was performed to examine the risk factors associated with ACVE. Results: Of the 372 patients, 243 (65%) were Durie-Salmon Stage (DSS) III, 70 (19%) were International Staging System (ISS) III; 186 (50%) were men. There were a total of 102 (27%) ACVE and 33 (9%) ≥grade 3 events. The most common ACVE were congestive heart failure (29%), asymptomatic elevations in pulmonary arterial systolic pressure (PASP) (27%), and hypertension (HTN) (16%). Sixty-eight (66%) Caucasians, 14 (14%) African Americans and 17 (17%) Hispanics developed ACVE. Aspirin (ASA) (64%), beta blockers (BB) (51%), calcium channel blockers (CCB) (43%) and statins (37%) were the most common cardiac medications patients were taking at the time of K initiation. Regardless of cardiac history, patients who were taking a CCB had higher odds of experiencing an ACVE compared to patients who were not taking a CCB (CCB + Cardiac history: OR=1.9; CI=1.0-3.7; CCB, no Cardiac history: OR=6.3; CI= 2.1-18.4) (Table 1). Patients with an ASCVD score ≥7.5% did not have an increased incidence of ACVE but did have an increased incidence of ≥grade 3 vs. grade 1-2 ACVE (100% vs. 78%, p=0.092). Prior cardiac history, including history of HTN, was common (59%) but not associated with incidence or severity of ACVE. Those with type 2 diabetes had a higher rate of ≥grade 3 vs. grade 1-2 ACVE (33% vs. 10%, p=0.004). Patients on certain CV medications while receiving K-based treatment had a higher incidence of ACVE compared to those not on these medications, including BB (51% vs. 34%, p=0.002), CCB (43% vs. 26%, p=0.002), aldosterone antagonists (AA) (8% vs. 3%, p=0.024) and statins (37% vs. 25%, p=0.022). Patients on ASA were more likely to experience ≥grade 3 compared to grade 1-2 ACVE (78% vs. 53%, p=0.016). ACE inhibitors or angiotensin receptor blockers (ACE/ARB) were not associated with increased incidence or severity of ACVE. The use of K in relapsed, as opposed to induction setting, was associated with a higher incidence of ACVE (31% vs. 20%, p=0.035). Maximum dose and number of K doses were not associated with ACVE. There was no relationship between PASP elevation and age >75, use of BB, CCB, AA, ACE/ARB, number of K treatments or maximum dose of K. Factors that were associated with increased odds of ACVE in multivariate analysis included patients who received K in the relapsed setting (OR= 1.7; CI=0.94-3.0) and use of an AA (OR= 4.5; CI=1.4-14.1) (Table 1). Conclusion: In line with prior studies, 28% of MM patients treated with K at our institution developed an ACVE, with 9% grade 3 or above. Use of CCB and AA were particularly associated with increased risk of ACVE, while use of ACE/ARB were not. ASCVD score ≥7.5% was associated with an increased incidence of ≥grade 3 ACVE in K-treated patients and should perhaps be evaluated as a predictive tool in prospective studies. Disclosures Siegel: Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Merck: Consultancy, Honoraria, Speakers Bureau. Biran:Merck: Research Funding; Amgen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Honoraria, Speakers Bureau; BMS: Research Funding.

PurposeTo clinically implement and comprehensively evaluate two independent methods for beam monitor calibration of scanning proton beam.MethodsSeven proton energies that represent the lowest to highest energy proton beams were selected. Single energy layer circular fields of diameter 15 cm with 2.5 mm spot spacing and 10 times of repainting (FS15cm) were designed for all energies. The effective measurement points of Bragg peak chamber (BPC), advanced Markus chamber (AMC) and farmer chamber (FC) were all aligned to 2 cm depth in water using SSD setup. The BPC and AMC were cross‐calibrated with farmer chamber (FC) using the field FS15cm. In order to evaluate BPC's lateral response uniformity, a collimated narrow proton beam (5.8 mm diameter) was delivered to the active area and edge of the BPC. The dose area product (DAP) was measured using two methods by two BPCs, one AMC and one FC. For method 1, a single spot proton beam was delivered to the geometric center of the BPC. For method 2, the fields FS15cm were delivered to FC and AMC, respectively. Accumulated charges by these chambers were converted to DAPs, and the quantitative difference of DAPs between both methods was calculated. The causes of the uncertainties were discussed, and the advantages of the two methods were compared.ResultsThe two BPCs showed different lateral response uniformity. BPC1 has a uniform response from the center up to a radius of 3.5 cm. BPC2 has a uniform response only to 2 cm and the response dropped 1% to 2% at 3.5 cm from center. BPC2 also has significant over‐response compared to BPC1. A 2.2% systematic error would be transferred to DAP if the over‐response from BPC2 was not considered. The DAPs measured by method 1 with two BPCs and by method 2 with FC and AMC were consistent to 0.5%. The major uncertainty component of method 1 is from the cross‐calibration of the BPC.ConclusionsThe two independent methods for DAP were shown to give consistent results, given the sources of uncertainties were carefully addressed in the measurements. Direct measurement of DAP with BPC is very efficient, but it may be subject to more than 2% systematic error if the BPC lateral response is not carefully evaluated.

Abstract BACKGROUND: Recurrent mutations in isocitrate dehydrogenase 1 (IDH1) are observed in approximately 4% of patients with myelodysplastic syndrome (MDS) and have been linked with increased transformation to acute myeloid leukemia. Ivosidenib (AG-120), an oral, potent, targeted, small-molecule inhibitor of the mutant IDH1 protein (mIDH1), is a therapeutic candidate for the treatment of patients with mIDH1 MDS. Through inhibition of mIDH1, ivosidenib suppresses the production of the oncometabolite 2-hydroxyglutarate (2-HG), leading to clinical responses via differentiation of malignant cells. AIM: To report safety and efficacy data from patients with relapsed or refractory (R/R) MDS enrolled in the first-in-human, phase 1, dose escalation and expansion study of ivosidenib in patients with mIDH1 advanced hematologic malignancies (NCT02074839). METHODS: This ongoing study is evaluating the safety, maximum tolerated dose (MTD), pharmacokinetics, pharmacodynamics, and clinical activity of ivosidenib. Trial enrollment was completed on 08May2017. In dose escalation, patients received single-agent ivosidenib orally once daily (QD) or twice daily in 28-day cycles. The MTD was not reached and 500 mg QD was selected as the dose to be tested in expansion. Expansion Arm 3 enrolled patients with mIDH1 advanced hematologic malignancies, including MDS. The overall response rate (ORR) for MDS was defined as complete remission (CR) + partial remission + marrow CR. Exploratory biomarker assessments included baseline co-occurring mutations (next-generation sequencing panel for hematologic malignancies) and mIDH1 variant allele frequency (VAF) in bone marrow mononuclear cells (BEAMing Digital PCR; lower limit of detection for mIDH1, 0.02-0.04%). Here, we present safety and efficacy data for patients with MDS in expansion Arm 3 and in dose escalation whose starting dose was 500 mg QD. RESULTS: In all, 258 patients (78 in dose escalation, 180 in expansion) received ivosidenib, including 12 patients with MDS (9 from expansion and 3 from escalation) whose starting dose was 500 mg QD. Baseline characteristics for these 12 patients were: 9 men/3 women; median age, 72.5 years (range, 52-78) and 42% were ≥75 years of age; median number of prior therapies, 1 (range, 1-3). As of 10Nov2017, 7 of 12 (58.3%) patients remained on treatment and 5 (41.7%) had discontinued (one for allogeneic stem cell transplantation). The median duration of exposure to ivosidenib was 11.0 months (range, 3.3-31.1). The most common adverse events (AEs) of any grade, irrespective of causality, occurring in ≥20% of the 12 patients were back pain (n=4, 33.3%) and anemia, decreased appetite, diarrhea, dyspnea, fatigue, hypokalemia, pruritus, and rash (n=3, 25.0% each). The majority of these AEs were grade 1-2 and reported as unrelated to treatment. No AEs led to permanent discontinuation of treatment. IDH differentiation syndrome (IDH-DS) was observed in 2 of 12 (16.7%) patients; the events were grade 1 and 2, respectively. Of the 12 patients with MDS receiving ivosidenib 500 mg QD, 5 achieved CR (41.7%; 95% CI 15.2%, 72.3%) and 6 achieved marrow CR (50.0%), resulting in an ORR of 91.7% (95% CI 61.5%, 99.8%). The median durations of CR and overall response were not estimable at the time of the data cutoff. The percentages of patients who remained in CR and response at 12 months were 60.0% and 61.4%, respectively. Among 5 patients who were transfusion dependent at baseline, 4 became transfusion independent for at least 56 days on treatment. Baseline co-occurring mutations and changes in mIDH1 VAF levels on ivosidenib therapy will be presented. CONCLUSION: In patients with mIDH1 R/R MDS, ivosidenib monotherapy was well tolerated and induced durable remissions and transfusion independence. These findings support the role of ivosidenib as an effective, oral, targeted treatment for patients with mIDH1 R/R MDS. Disclosures DiNardo: Karyopharm: Other: Advisory role; Medimmune: Other: Advisory role; Celgene: Other: Advisory role; Bayer: Other: Advisory role; Agios: Consultancy, Other: Advisory role; AbbVie: Consultancy, Other: Advisory role. Watts:Jazz Pharma: Consultancy, Speakers Bureau; Takeda: Research Funding. Stein:Celgene: Consultancy; Daiichi Sankyo: Consultancy; Agios: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Bayer: Consultancy. de Botton:Agios: Research Funding; Celgene: Honoraria, Research Funding. Fathi:Takeda: Consultancy, Honoraria; Jazz: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Boston Biomedical: Consultancy, Honoraria; Astellas: Honoraria; Seattle Genetics: Consultancy, Honoraria; Agios: Honoraria, Research Funding. Stein:Amgen: Speakers Bureau; Celgene: Speakers Bureau. Foran:Agios: Research Funding; Xencor, Inc.: Research Funding. Stone:AbbVie: Consultancy; Agios: Consultancy, Research Funding; Cornerstone: Consultancy; Orsenix: Consultancy; Fujifilm: Consultancy; Sumitomo: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Ono: Consultancy; Novartis: Consultancy, Research Funding; Otsuka: Consultancy; Jazz: Consultancy; Merck: Consultancy; Astellas: Consultancy; Arog: Consultancy, Research Funding; Argenx: Other: Data and Safety Monitoring Board; Amgen: Consultancy. Patel:France Foundation: Honoraria; Dava Oncology: Honoraria; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Tallman:Cellerant: Research Funding; BioSight: Other: Advisory board; ADC Therapeutics: Research Funding; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board; AROG: Research Funding; Orsenix: Other: Advisory board. Choe:Agios: Employment, Equity Ownership. Wang:Agios: Employment, Equity Ownership. Zhang:Agios: Employment, Equity Ownership. Dai:Agios: Employment, Equity Ownership. Fan:Agios: Employment, Equity Ownership. Yen:Agios: Employment, Equity Ownership. Kapsalis:Agios: Employment, Equity Ownership. Hickman:Agios: Employment, Equity Ownership. Agresta:Agios: Employment, Equity Ownership. Liu:Agios: Employment, Equity Ownership. Wu:Agios: Employment, Equity Ownership, Patents & Royalties. Attar:Agios: Employment, Equity Ownership.

Abstract Background Survival rates for older pts with advanced HL (aged ≥60 yrs) were historically poor with doxorubicin, bleomycin, vinblastine and dacarbazine (ABVD). Reasons may include decreased tolerance of therapy, increased toxicity (particularly with bleomycin), comorbidities, and disease biology. The pivotal phase 3 ECHELON-1 study demonstrated superior 2-yr modified progression-free survival (mPFS) with frontline brentuximab vedotin + doxorubicin, vinblastine and dacarbazine (A+AVD) vs ABVD in pts with stage III/IV cHL (Connors JM et al, NEJM 2018). The study allowed entry of older pts, with no upper age limit. Alternative dosing schedules of the A+AVD regimen have been studied (e.g., sequential brentuximab vedotin before and after AVD; NCT01476410, Evens AM et al, J Clin Oncol 2018). We report efficacy and safety results from ECHELON-1 for older pts with cHL and compare these with those for pts aged <60 yrs. Methods mPFS per independent review facility (IRF) for pts ≥60 years was a prespecified subgroup analysis of ECHELON-1. Additional exploratory safety and efficacy analyses were also assessed and compared with younger pts (<60 yrs). The study was not powered for age-based subgroup analyses; p-values are descriptive without multiplicity adjustment. Results 14% (186/1334) of pts in the intent-to-treat (ITT) population were aged ≥60 yrs (A+AVD, n=84; ABVD, n=102) and included in the sub analyses. Median age (range) of older pts was: A+AVD, 68.0 yrs (60-82); ABVD, 66.0 yrs (60-83). Baseline pt and disease characteristics in older pts were similar in both arms. ECOG PS scores were 0 (36% vs 36%), 1 (52% vs 54%), and 2 (12% vs 10%) in A+AVD and ABVD arms, respectively. Pts received a median of 6 cycles with mean relative dose intensities for each drug (%) in older pts of: A+AVD, 92.3, 96.6, 93.3, and 97.9; ABVD, 97.3, 88.7, 93.3, and 95.9. With median follow-up of ~25 months, 2-yr mPFS per IRF was similar in both arms for older ITT pts (A+AVD 70.3% [95% CI: 58.4, 79.4] vs ABVD 71.4% [95% CI: 60.5, 79.8]; HR=1.00 [95% CI: 0.58, 1.72]; p=0.993). An exploratory analysis of standard PFS per investigator (INV) showed HR=0.85 ([95% CI: 0.49, 1.48]; p=0.576) (Table 1). For older pts with stage IV cHL (A+AVD n=51; ABVD n=67), there was an increase in 2-yr PFS per INV with A+AVD vs ABVD (74.0% [95% CI: 59.5, 84.0] vs 59.9% [95% CI: 45.6, 71.5]; HR, 0.66 [95% CI: 0.34, 1.26]; p=0.20); mPFS per IRF improvement with A+AVD in older stage IV pts was lower (HR=0.80; [95% CI: 0.42, 1.53]). In younger stage III/IV pts (<60 yrs) 2-yr mPFS per IRF and PFS per INV were also higher compared with older pts in both arms (Table 1). 66 of 83 older A+AVD pts required ≥1 dose modification of brentuximab vedotin, reasons were: dose reduction (n=27), dose held (n=4), dose delayed (n=51), brentuximab vedotin discontinued (n=17). In older pts, grade (G) 3/4 AEs occurred in 88% of A+AVD pts vs 80% ABVD pts; for younger pts, rates were 82% (A+AVD) vs 63% (ABVD) (Table 2). In older pts there were 3 (4%) on-study deaths in the A+AVD arm (1 each: hemophagocytosis, neutropenic sepsis, and myocardial infarction) and 5 (5%) with ABVD (all pulmonary-related). In pts <60 yrs, there were 6 on-study deaths (1%) with A+AVD vs 8 (1%) with ABVD. G3 neutropenia in older pts was (70%) A+AVD pts vs (59%) ABVD pts, and febrile neutropenia (FN) in 31 (37%) vs 17 (17%) pts. In older pts who had G-CSF primary prophylaxis (PP) neutropenia was seen in 4/10 (40%) A+AVD pts vs 1/9 (11%) ABVD pts (on-study FN in 3 [30%] vs 2 [22%] pts). In older pts, treatment-emergent peripheral neuropathy (PN) was reported in 54 (65%) of A+AVD pts vs 42 (43%) of ABVD pts (G≥3 in 15 [18%] vs 3 [3%] pts), respectively. In pts <60 yrs PN was reported in 388 (67%) A+AVD pts vs 244 (43%) ABVD pts (G≥3 in 55 [9%] vs 8 [1%] pts), respectively. In older pts at last follow-up, 65% (35/54) of A+AVD pts and 60% (25/42) of ABVD pts had complete resolution (A+AVD, 39%; ABVD, 38%) or improvement (A+AVD, 26%; ABVD, 21%) of PN events. 2% older A+AVD pts had pulmonary AEs (both G1/2 pulmonary infiltration) vs 13% older ABVD pts. Conclusions For older ECHELON-1 pts, mPFS and PFS were similar in both arms. In the larger subgroup of younger pts, mPFS and PFS were improved vs older pts. As expected, incidence of treatment-emergent AEs was higher in older pts, with regimen-specific AEs seen, including fatal pulmonary events in ABVD pts. The high incidence of FN in older A+AVD pts points to the need for G-CSF PP. Disclosures Evens: Acerta: Consultancy; Pharmacyclics International DMC: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Affimed: Consultancy; Janssen: Consultancy; Abbvie: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy; Tesaro: Research Funding; Novartis: Consultancy. Connors:Merck: Research Funding; Amgen: Research Funding; Takeda: Research Funding; Roche Canada: Research Funding; NanoString Technologies: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Seattle Genetics: Honoraria, Research Funding; Janssen: Research Funding; F Hoffmann-La Roche: Research Funding; Bayer Healthcare: Research Funding; Cephalon: Research Funding; Bristol Myers-Squibb: Research Funding; Lilly: Research Funding; Genentech: Research Funding. Younes:Sanofi: Honoraria; Merck: Honoraria; Astra Zeneca: Research Funding; Celgene: Honoraria; Incyte: Honoraria; Seattle Genetics: Honoraria; Bayer: Honoraria; Novartis: Research Funding; Curis: Research Funding; J&J: Research Funding; Genentech: Research Funding; Takeda: Honoraria; Roche: Honoraria, Research Funding; Abbvie: Honoraria; Janssen: Honoraria, Research Funding; Pharmacyclics: Research Funding; BMS: Honoraria, Research Funding. Ansell:Merck & Co: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Takeda: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Bristol-Myers Squibb: Research Funding. Radford:Takeda: Consultancy, Research Funding, Speakers Bureau; GlaxoSmithKline: Equity Ownership; AstraZeneca: Equity Ownership; Seattle Genetics: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Research Funding; Novartis: Consultancy, Speakers Bureau; Pfizer: Research Funding; Celgene: Research Funding; BMS: Consultancy, Speakers Bureau. Feldman:Seattle Genetics: Research Funding, Speakers Bureau; Janssen: Speakers Bureau; Pharmacyclics: Speakers Bureau; Johnson and Johnson: Speakers Bureau; Celgene: Speakers Bureau; Portola: Research Funding; KITE: Speakers Bureau. Tuscano:Takeda: Research Funding; Genentech: Consultancy, Research Funding; Amgen: Honoraria, Speakers Bureau; Seattle Genetics: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding, Speakers Bureau; Pharmacyclics: Research Funding. Oki:Seattle Genetics: Research Funding; Takeda Millenium: Honoraria, Research Funding; Jazz Pharmaceuticals: Employment. Grigg:Roche: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Pocock:Kent & Canterbury Hospital: Employment. Dlugosz-Danecka:Roche: Consultancy; Servier: Consultancy. Fenton:Seattle Genetics, Inc.: Employment, Equity Ownership. Engley:Seattle Genetics: Employment. Liu:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Miao:Millennium Pharmaceuticals Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Jolin:Takeda Pharmaceuticals International Co.: Employment. Gautam:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Gallamini:Takeda: Consultancy, Speakers Bureau.