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BackgroundSystematic evaluation of complex flow in the true lumen and false lumen (TL, FL) is needed to better understand which patients with chronic descending aortic dissection (DAD) are predisposed to complications.PurposeTo develop quantitative hemodynamic maps from 4D flow MRI for evaluating TL and FL flow characteristics.Study TypeRetrospective.PopulationIn all, 20 DAD patients (age = 60 ± 11 years; 12 male) (six medically managed type B AD [TBAD], 14 repaired type A AD [rTAAD] now with ascending aortic graft [AAo] or elephant trunk [ET1] repair) and 21 age‐matched controls (age = 59 ± 10 years; 13 male) were included.Field Strength/Sequence1.5T, 3T, 4D flow MRI.Assessment4D flow MRI was acquired in all subjects. Data analysis included 3D segmentation of TL and FL and voxelwise calculation of forward flow, reverse flow, flow stasis, and kinetic energy as quantitative hemodynamics maps.Statistical TestsAnalysis of variance (ANOVA) or Kruskal–Wallis tests were performed for comparing subject groups. Correlation and Bland–Altman analysis was performed for the interobserver study.ResultsPatients with rTAAD presented with elevated TL reverse flow (AAo repair: P = 0.004, ET1: P = 0.018) and increased TL kinetic energy (AAo repair: P = 0.0002, ET1: P = 0.011) compared to controls. In addition, TL kinetic energy was increased vs. patients with TBAD (AAo repair: P = 0.021, ET1: P = 0.048). rTAAD was associated with higher FL kinetic energy and lower FL stasis compared to patients with TBAD (AAo repair: P = 0.002, ET1: P = 0.024 and AAo repair: P = 0.003, ET1: P = 0.048, respectively).Data ConclusionQuantitative maps from 4D flow MRI demonstrated global and regional hemodynamic differences between DAD patients and controls. Patients with rTAAD vs. TBAD had significantly altered regional TL and FL hemodynamics. These findings indicate the potential of 4D flow MRI‐derived hemodynamic maps to help better evaluate patients with DAD.Level of Evidence: 3Technical Efficacy Stage: 1J. Magn. Reson. Imaging 2020;51:1357–1368.

Objective: To describe the incidence and risk factors for mortality and morbidity in patients with cirrhosis undergoing elective or emergent abdominal surgeries. Background: Postoperative morbidity and mortality are higher in patients with cirrhosis; variation by surgical procedure type and cirrhosis severity remain unclear. Methods: We analyzed prospectively-collected data from the Veterans Affairs (VA) Surgical Quality Improvement Program for 8193 patients with cirrhosis, 864 noncirrhotic controls with chronic hepatitis B infection, and 5468 noncirrhotic controls without chronic liver disease, who underwent abdominal surgery from 2001 to 2017. Data were analyzed using random-effects models controlling for potential confounders. Results: Patients with cirrhosis had significantly higher 30-day mortality than noncirrhotic patients with chronic hepatitis B [4.4% vs 1.3%, adjusted odds ratio (aOR) 2.80, 95% confidence interval (CI) 1.57–4.98] or with no chronic liver disease (0.8%, aOR 4.68, 95% CI 3.27–6.69); mortality difference was highest in patients with Model for End-stage Liver Disease (MELD) score ≥10. Among patients with cirrhosis, postoperative mortality was almost 6 times higher after emergent rather than elective surgery (17.2% vs. 2.1%, aOR 5.82, 95% CI 4.66–7.27). For elective surgeries, 30-day mortality was highest after colorectal resection (7.0%) and lowest after inguinal hernia repair (0.6%). Predictors of postoperative mortality included cirrhosis-related characteristics (high MELD score, low serum albumin, ascites, encephalopathy), surgery-related characteristics (emergent vs elective, type of surgery, intraoperative blood transfusion), comorbidities (chronic obstructive pulmonary disease, cancer, sepsis, ventilator dependence, functional status), and age. Conclusions: Accurate preoperative risk assessments in patients with cirrhosis should account for cirrhosis severity, comorbidities, type of procedure, and whether the procedure is emergent versus elective.

With its first administration of an Objective Structured Clinical Examination (OSCE) in 2018, the American Board of Anesthesiology (ABA) became the first US medical specialty certifying board to incorporate this type of assessment into its high-stakes certification examination system. The fundamental rationale for the ABA’s introduction of the OSCE is to include an assessment that allows candidates for board certification to demonstrate what they actually “do” in domains relevant to clinical practice. Inherent in this rationale is that the OSCE will capture competencies not well assessed in the current written and oral examinations—competencies that will allow the ABA to judge whether a candidate meets the standards expected for board certification more properly. This special article describes the ABA’s journey from initial conceptualization through first administration of the OSCE, including the format of the OSCE, the process for scenario development, the standardized patient program that supports OSCE administration, examiner training, scoring, and future assessment of reliability, validity, and impact of the OSCE. This information will be beneficial to both those involved in the initial certification process, such as residency graduate candidates and program directors, and others contemplating the use of high-stakes summative OSCE assessments.

Abstract Background The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian Randomisation (MR) framework to examine if lifestyle, cardiometabolic and inflammatory factors influence the risk of glioma. This methodology reduces bias from confounding and is not affected by reverse causation. Methods We identified genetic instruments for 37 potentially modifiable risk factors and evaluated their association with glioma risk using data from a genome-wide association study of 12,488 glioma patients and 18,169 controls. We used the estimated odds ratio of glioma associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures: lifestyle and dietary factors (height, plasma IGF-1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamin [A1, B12, B6, E and 25-hydroxyvitamin D], fatty acids levels [mono-unsaturated, omega-3 and omega-6] and circulating fetuin-A); cardiometabolic factors (birth weight, HDL cholesterol, LDL cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, HbA1C levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio) were included; inflammatory factors (C-reactive protein (CRP), plasma IL-6 sRa and serum IgE). Results After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism (SNP) no significant association with glioma risk was observed (i.e. PCorrected > 0.05). Conclusions This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk.

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: Axi-cel is a US FDA-approved, autologous anti-CD19 chimeric antigen receptor (CAR) T cell therapy for the treatment of patients with relapsed or refractory large B cell lymphoma with ≥ 2 prior systemic therapies. This report focuses on high-risk patient populations as well as long-term durability of response, and B cell recovery. Methods: In ZUMA-1, eligible patients with refractory large B cell lymphoma (diffuse large B cell lymphoma, primary mediastinal B cell lymphoma, transformed follicular lymphoma) underwent leukapheresis and received low-dose conditioning followed by a target dose of 2 × 106 anti-CD19 CAR T cells/kg (Neelapu and Locke et al. NEJM. 2017; NCT02348216). Outcomes in patients with double-expressor B cell lymphoma (MYC [≥ 40%] and BCL-2 [≥ 50%] protein expression by immunohistochemistry [IHC]) or high-grade B cell lymphoma (HGBCL), defined as double- or triple-hit (MYC+ and BCL2+ and/or BCL6+ by fluorescence in situ hybridization) or not otherwise specified (MYC- and > 70% Ki67 by IHC) were examined by independent pathology review. Exploratory analyses, including normal B cell levels in peripheral blood over time and frequency of use of safety interventions of interest, were also performed. A long-term follow-up analysis will be conducted with a data cutoff of August 11, 2018 for all 108 patients, including the HGBCL subgroup. Results: As of August 11, 2017, all 108 patients had at least 1 year of follow-up, with a median follow-up of 15.4 months. The objective response rate (ORR) was 82% with a complete response (CR) rate or 58%. The CR rate was 53% (29/55) in patients with disease refractory to ≥ 2 consecutive prior lines of therapy and 72% (18/25) in patients who had relapsed within 12 months after autologous stem cell transplantation. High-risk genetics were assessed in the 47 evaluable pre-treatment tumor samples: 37 patients (79%) had HGBCL or double-expressor B cell lymphoma and had an ORR of 89% (33/37) including a CR rate of 68% (25/37). Forty-two percent of patients overall had ongoing responses with a median follow-up of 15.4 months including 49% (18/37) of patients with high-risk genetics. To investigate the relationship between B cell recovery and ongoing response, B cell levels were assessed over time. Overall, of the 87 evaluable patients, 47% had no detectable B cells at baseline, and the remainder had levels close to or below the lower level of quantification of the assay. In patients with ongoing responses at 12 months post axi-cel infusion, 19 of the 35 (54%) patients with evaluable samples had detectable B cells at 12 months. This suggests B cell recovery in some patients with ongoing response as only 6 of 40 (15%) patients with evaluable samples had detectable B cells at 3 months after axi-cel infusion. Grade ≥ 3 cytokine release syndrome (CRS) and neurologic events (NE) were generally reversible and reported for 12% and 31% of patients, respectively. Tocilizumab (45%) and/or steroids (28%) were used for the management of CRS and NE. The use of vasopressors, dialysis, and intubation were minimal, used in only 17%, 3%, and 3% of patients, respectively. Thirty-four percent of patients (37/108) had either no CRS/NE (6%) or only Grade 1 CRS with (12%) or without (16%) Grade 1 NE. For these 37 patients, the median onset of CRS and NE was 2 and 7 days after infusion, respectively. Patients with Grade 0 - 1 CRS/NE had similar efficacy (ORR, 86%; CR, 65%) but lower peak/AUC CAR T cell levels vs the overall population. Updated safety and efficacy results will be presented with a minimum follow-up of 2 years and a median follow-up of 27.1 months. Conclusion: High rates of durable response were observed in patients with HGBCL and double-expressor B cell lymphoma, with approximately half of these patients (18/37) maintaining CR at ≥ 1 year. Efficacy in these high-risk populations was comparable to the overall patient population in ZUMA-1. At 12 months, B-cell recovery was observed in over half the patients with ongoing remission. About one-third of patients had only Grades 0 - 1 CRS/NE yet showed comparable efficacy with the overall patient population. High-grade CRS/NE were largely managed with tocilizumab and steroids with very low use of intensive or invasive interventions. Updated outcomes with a minimum of 2 years of follow-up will be presented. Disclosures Neelapu: Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cellectis: Research Funding; Poseida: Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta: Research Funding; Karus: Research Funding; Bristol-Myers Squibb: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees; Unum Therapeutics: Membership on an entity's Board of Directors or advisory committees; Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Miklos:Adaptive Biotechnologies: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pharmacyclics - Abbot: Consultancy, Research Funding; Kite - Gilead: Consultancy, Research Funding; Genentech: Research Funding; Janssen: Consultancy, Research Funding. Hill: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; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Seattle Genetics: 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; Abbvie: 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; 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; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees. Deol:Novartis: Consultancy; Kite Pharmaceuticals: Consultancy. Reagan:Seattle Genetics: Research Funding. Flinn:Agios: Research Funding; Forty Seven: Research Funding; Celgene: Research Funding; Calithera: Research Funding; Portola: Research Funding; Kite: Research Funding; Forma: Research Funding; Genentech: Research Funding; Verastem: Research Funding; BeiGene: Research Funding; Incyte: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Janssen: Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; ArQule: Research Funding; Constellation: Research Funding; Infinity: Research Funding; Novartis: Research Funding; Gilead: Research Funding; Curis: Research Funding; Pharmacyclics: Research Funding; Verastem: Consultancy, Research Funding; Takeda: Research Funding; Pfizer: Research Funding. McSweeney:Kite, a Gilead Company: Honoraria, Membership on an entity's Board of Directors or advisory committees. Munoz:Alexion: Consultancy; Genentech: Consultancy, Honoraria; Juno: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria; Janssen: Consultancy; Kite: Consultancy, Honoraria, Speakers Bureau; Bayer: Consultancy, Speakers Bureau; Gilead: Speakers Bureau; Pfizer: Consultancy; Bristol-Myers Squibb: Consultancy. Siddiqi:Juno Therapeutics: Other: Steering committee. Herrera:Bristol-Myers Squibb: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Seattle Genetics: Research Funding; Pharmacyclics: Consultancy, Research Funding; AstraZeneca: Research Funding; Gilead Sciences: Research Funding; Merck, Inc.: Consultancy, Research Funding; KiTE Pharma: Consultancy, Research Funding; Immune Design: Research Funding. Xue:Kite, a Gilead Company: Employment. Jiang:Kite, a Gilead Company: Employment. Bot:KITE: Employment. Rossi:KITE: Employment. Kim:Kite, a Gilead Company: Employment. Go:KITE: Employment. Locke:Cellular BioMedicine Group Inc.: Consultancy; Novartis Pharmaceuticals: Other: Scientific Advisor; Kite Pharma: Other: Scientific Advisor.

Background: There is intense interest and speculation in the application of artificial intelligence (AI) to radiology. The goals of this investigation were (1) to assess thoracic radiologists’ perspectives on the role and expected impact of AI in radiology, and (2) to compare radiologists’ perspectives with those of computer science (CS) experts working in the AI development. Methods: An online survey was developed and distributed to chest radiologists and CS experts at leading academic centers and societies, comparing their expectations of AI’s influence on radiologists’ jobs, job satisfaction, salary, and role in society. Results: A total of 95 radiologists and 45 computer scientists responded. Computer scientists reported having read more scientific journal articles on AI/machine learning in the past year than radiologists (mean [95% confidence interval]=17.1 [9.01-25.2] vs. 7.3 [4.7-9.9], P=0.0047). The impact of AI in radiology is expected to be high, with 57.8% and 73.3% of computer scientists and 31.6% and 61.1% of chest radiologists predicting radiologists’ job will be dramatically different in 5 to 10 years, and 10 to 20 years, respectively. Although very few practitioners in both fields expect radiologists to become obsolete, with 0% expecting radiologist obsolescence in 5 years, in the long run, significantly more computer scientists (15.6%) predict radiologist obsolescence in 10 to 20 years, as compared with 3.2% of radiologists reporting the same (P=0.0128). Overall, both chest radiologists and computer scientists are optimistic about the future of AI in radiology, with large majorities expecting radiologists’ job satisfaction to increase or stay the same (89.5% of radiologists vs. 86.7% of CS experts, P=0.7767), radiologists’ salaries to increase or stay the same (83.2% of radiologists vs. 73.4% of CS experts, P=0.1827), and the role of radiologists in society to improve or stay the same (88.4% vs. 86.7%, P=0.7857). Conclusions: Thoracic radiologists and CS experts are generally positive on the impact of AI in radiology. However, a larger percentage, but still small minority, of computer scientists predict radiologist obsolescence in 10 to 20 years. As the future of AI in radiology unfolds, this study presents a historical timestamp of which group of experts’ perceptions were closer to eventual reality.

Abstract Introduction This phase 1/2 study evaluated the safety and antitumor activity of brentuximab vedotin (BV) administered in combination with nivolumab (Nivo) in adult patients (pts) with relapsed/refractory classic Hodgkin lymphoma (R/R cHL) who have failed frontline therapy (NCT02572167). Results from Parts 1 & 2 have been previously reported, wherein safety, efficacy, and biomarkers consistent with immune activation were observed in pts with R/R cHL (Herrera et al., Blood 2018). In Part 3, patients were treated with BV + Nivo on Day 1 of each cycle. In contrast, pts in Parts 1 & 2 received BV on C1D1 and Nivo on C1D8 with concurrent admin on subsequent cycles. Herein we present safety, efficacy, and biomarker results for Part 3 and updated progression free survival (PFS) from Parts 1 & 2. Methods Pts in Parts 1 & 2 received up to four 21-day cycles of staggered dosing (day 1 BV 1.8 mg/kg, day 8 Nivo 3 mg/kg in Cycle 1) and concurrent thereafter, with steroid and antihistamine premedication. Pts in Part 3 received up to four 21-day cycles of concurrent BV + Nivo on Day 1 with antihistamine premedication. Following Cycle 4 response assessment (Lugano Classification Revised Staging System with the incorporation of the Lymphoma Response to Immunomodulatory Therapy Criteria [LYRIC, 2016]) responding pts were eligible to undergo autologous stem cell transplant (ASCT). Results 30 pts were treated in Part 3 and all were evaluable for efficacy. Pt characteristics included the following: median age 31.5 yrs (range; 20 - 66), 63% female, 93% prior ABVD, 37% primary refractory HL, 30% relapsed within 1year of frontline therapy, 30% with extranodal disease and 17% with bulky disease at enrollment. 28 pts completed all 4 cycles. 1 pt discontinued treatment (tx) due to an adverse event (AE; Grade 3 [G3] elevated Gamma-Glutamyltransferase) and 1 pt due to progressive disease (PD). The latter pt eventually died due to PD. All pts are off tx and have been observed through the safety reporting period. 37% of pts experienced a G3 or higher tx emergent AE prior to ASCT. 30% of the pts experienced infusion related reactions (IRRs), which occurred most frequently during Cycle 2. Potential G3 or higher immune-related AEs (IRAEs), excluding IRRs, occurred in 2 pts, one of whom required steroids for G4 pneumonitis, which subsequently resolved. Among the 30 efficacy evaluable pts, the complete response (CR) rate was 80% (24/30), with an objective response rate (ORR) of 93%. 47% of pts (14) had a Deauville ≤2, and 17% (5) had Deauville 3. 5 pts with CR had a Deauville >3 and met LYRIC criteria for IR-2. 4/5 pts had a negative follow-up biopsy that confirmed CR and in 1 pt the PET finding was considered to be a false positive as contrast enhanced CT did not reveal any abnormality. All 5 pts proceeded directly to ASCT and remain in CR at follow-up. Among all treated patients, 25 went directly to ASCT after completing BV + Nivo tx with a median 6.8 x 106 CD34+ cells/kg (range 1-20) collected. Median times to neutrophil and platelet engraftment were 12 and 14 days, respectively. 4 pts required additional salvage therapy subsequent to study tx. Patients were followed for a median of 6 months from ASCT (N=25, range 0.8-8.8) and 10 months from first dose (N=30, range 1.8-12.7). The estimated 9-month PFS rate in all-treated pts was 88%. This is comparable to all-treated pts in Parts 1 & 2, whose estimated 9 and 15 month PFS were 86% and 82%, respectively (Fig 2). Biomarker testing was performed on peripheral blood samples, included immunophenotyping, serum cytokine analysis, and TCRβ sequencing. Concurrent dosing of BV+ Nivo resulted in increased levels of both activated and dividing CD4+ and CD8+ T cells, as well as increased regulatory T-cells and circulating plasmablasts. Cytokines and chemokines associated with innate and adaptive immune activation, including Type I and Type II interferons, IL-18, and IP-10, were significantly upregulated following BV + Nivo, while TARC levels were significantly diminished following therapy. TCRβ sequencing revealed clonal expansion in the periphery following BV + Nivo. Conclusion A concurrent dosing schedule of BV + Nivo was well tolerated with a high CR rate of 80%. Biomarkers evaluated in Part 3 indicate immune activation in the periphery following BV + Nivo. Cumulatively, the results in Part 3, along with the durable remissions noted in Parts 1 & 2, support BV + Nivo combination as an encouraging first salvage therapy prior to ASCT in pts with R/R cHL. Disclosures Advani: Forty Seven: Research Funding; Infinity: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Merck: Research Funding; Agensys: Research Funding; Millenium: Research Funding; Janssen: Research Funding; Celgene: Research Funding; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Regeneron: Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding. Moskowitz:Bristol Myers-Squibb: Consultancy, Research Funding; Incyte: Research Funding; Takeda: Honoraria; Merck: Research Funding; ADC Therapeutics: Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding. Bartlett:Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees. Vose:Celgene: Research Funding; Legend Pharmaceuticals: Honoraria; Bristol Myers Squibb: Research Funding; Merck Sharp & Dohme Corp.: Research Funding; Incyte Corp.: Research Funding; Roche: Honoraria; Novartis: Honoraria, Research Funding; Seattle Genetics, Inc.: Research Funding; Acerta Pharma: Research Funding; Abbvie: Honoraria; Epizyme: Honoraria; Kite Pharma: Research Funding. Ramchandren:Merck: Research Funding; Bristol-Myers Squibb: Consultancy; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics LLC an AbbVie Company: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Feldman:Johnson and Johnson: Speakers Bureau; Celgene: Speakers Bureau; Pharmacyclics: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau; Portola: Research Funding; Janssen: Speakers Bureau; KITE: Speakers Bureau. LaCasce:Seattle Genetics: Consultancy, Honoraria; Bristol-Myers Squibb: Other: Data safety and monitoring board; Research to Practice: Speakers Bureau; Humanigen: Consultancy, Honoraria. Christian:Acerta: Research Funding; Merck: Research Funding; Bristol-Myers Squibb: Research Funding; Immunomedics: Research Funding; Celgene: Research Funding; Seattle Genetics: Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees, Research Funding. Ansell:LAM Therapeutics: Research Funding; Pfizer: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding; Celldex: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Takeda: Research Funding. Moskowitz:Celgene: Consultancy; Merck & Co: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Consultancy, Research Funding. Fenton:Seattle Genetics, Inc.: Employment, Equity Ownership. Ogden:Seattle Genetics, Inc: Employment, Equity Ownership. Taft:Seattle Genetics: Employment, Equity Ownership. Zak:Seattle Genetics: Employment, Equity Ownership. Sacchi:Bristol-Myers Squibb: Employment, Equity Ownership. Galderisi:Seattle Genetics: Employment, Equity Ownership. Herrera:Immune Design: Research Funding; Merck, Inc.: Consultancy, Research Funding; KiTE Pharma: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Seattle Genetics: Research Funding; AstraZeneca: Research Funding; Pharmacyclics: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Gilead Sciences: Research Funding.