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INTRODUCTION: African-Americans (blacks) have higher risk of stroke and coronary heart disease (CHD) - collectively referred to here as cardiovascular disease (CVD), than Caucasian-Americans (whites). Though partly explained by traditional cardiovascular risk factors, half of the excess risk in blacks is not explained by known risk factors. Recent data suggest increased risk of CVD and mortality in individuals with clonal hematopoiesis, which often presents as cytopenia. Using peripheral blood cytopenia as a marker of clonal hematopoiesis, we examined the association between cytopenia and risk of CVD and mortality in blacks and whites. METHODS: The REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study enrolled 30,239 US black and white adults between 2003 and 2007 (41% black). Socio-demographics and medical history were obtained by telephone interview, and laboratory studies (including complete blood count [CBC]) and physical exam from an in-home visit at baseline. Participants or their proxies were contacted every 6 months to ascertain CVD events, hospitalizations or deaths, and medical records were reviewed to confirm these events. Cytopenia was defined using thresholds in Table 1 as presence of 2 or more of the following: i) hemoglobin in age-, sex-, and race-specific lowest 5th percentile; ii) white cell count in race-specific lowest 5th percentile; iii) platelet count in lowest 5th percentile, and iv) macrocytosis (MCV >98fL). Participants with pre-baseline history of stroke (for analyses including stroke or CVD mortality) or CHD (for analyses including CHD or CVD mortality) and those with missing CBC were excluded. Cox proportional hazards models were used to calculate hazard ratios (HRs) of incident CVD and mortality associated with cytopenia. Models adjusted for socio-demographics (Model 1), Framingham stroke or CHD risk factors (Model 2), and estimated glomerular filtration rate and C-reactive protein (Model 3) were used. Differences in the association of cytopenia with outcomes by race were tested using cross-product interaction terms, using a p of <0.1 for interaction. RESULTS: The study included 19,544 participants who were followed for a median of ~9 years. There were 798 (4.3% of those at risk) incident stroke cases and 727 (4.3%) incident CHD cases; 1033 (5.3%) died of CVD, and 3933 (20.1%) died of all-causes. Cytopenia was present in 378 (1.9%) participants, ranging from 0.9% to 3.5% in blacks, 1.4 to 3.9% in whites, 1.6 to 3.9% in men, and 0.9 to 1.8% in women, with increasing prevalence by age. There was no association between cytopenia and stroke or CHD risk in any model. However, cytopenia was associated with increased risk of all-cause mortality (HR=1.73, 95%CI: 1.34-2.22), and CVD mortality (HR=1.56, 95% CI: 1.11-2.19) in the extended risk factor Model 3 and also in CVD risk factor adjusted model (Model 2), with little evidence of confounding (Table 2). While the race by cytopenia interaction term was not significant in any model for incident CHD or mortality, the interaction for cytopenia by race for stroke was statistically significant (p-interaction=0.08) in Model 2. The HR of stroke for cytopenia in blacks was 0.86 (95%CI: 0.46-1.61), and for whites was 1.96 (95%CI: 1.0-3.82). CONCLUSION: In this large biracial cohort, cytopenia was associated with increased all-cause and CVD mortality. Cytopenia was a race-specific risk factor for stroke affecting white Americans but not black Americans. With growing knowledge on the role of clonal hematopoiesis in CVD risk and mortality, further work is needed to determine if our phenotype of cytopenia is accurate in classifying clonal hematopoiesis and for determining the mortality risk. Given these findings, assessing clonal hematopoiesis and outcomes related to clonal hematopoiesis in diverse populations is critical to understanding the interactions between somatic mutations in hematopoietic cells and CVD/mortality risk. Disclosures Safford: Amgen: Research Funding.

Background: Lymphoma patients exposed to chest RT during adolescence/young adulthood are at increased risk for BC; the cumulative incidence exceeds 20% by age 45 and the BC risk is comparable to that in women with BRCA1 mutations. These findings present an urgent yet unmet need to reduce the risk of BC in RT-exposed lymphoma survivors. The risk of BC is 50% lower in chest RT-exposed survivors who also receive ovarian radiation, suggesting a critical role of endogenous estrogens in RT-related breast carcinogenesis, making tamoxifen (a selective estrogen receptor modulator) an attractive risk-reducing option. Tamoxifen administered at 20 mg/d is effective in BC prevention in other high risk populations, but severe adverse events (SAE: venous thromboembolism, endometrial cancer) have limited its broad use. Previous biomarker trials in the general population have shown that LDTam (5mg/d) is not inferior to tamoxifen at 20 mg/d in reducing BC risk, and is associated with a safer AE profile. Mammographic breast density (MBD) is an established biomarker of BC risk; high MBD is associated with a 4-fold higher risk of BC. We hypothesized that LDTam would be effective in reducing BC risk (using MBD as a primary endpoint) in chest RT-exposed lymphoma survivors. We used an investigator-initiated, multi-institutional, randomized phase IIb, double blind, placebo controlled trial (FDA IND 107367) to test this hypothesis. Methods: Female patients from 13 sites were ≥25y at enrollment, with a history of exposure to chest RT at ≥12 Gy by age 40 for their primary cancer, and were off therapy for ≥6 mo. Subjects with a prior history of BC/DCIS, B/L mastectomy, or baseline MBD <25% in both breasts were excluded. Tamoxifen 5mg or identical placebo tablets were provided by Sharp Clinical Services (Allentown, PA) under good manufacturing practice. Subjects were randomized 1:1 in a double-blinded fashion by a Web-based system to receive LDTam or placebo daily for 2y. MBD (in both breasts) was measured centrally on digital scans independently by 3 radiologists at baseline, 1y and 2y. Using an intention-to-treat analysis, the efficacy of LDTam in reducing MBD was compared between the LDTam and placebo arms by applying a linear mixed effects model for bivariate normally distributed data with random intercept and time*treatment arm effects. Correlations between the left and right breasts and within radiologists were accounted for in the model. Treating clinicians and all research staff were blinded to the treatment arm. Results: A total of 72 patients (LDTam: n=34; placebo: n=38) participated in the trial; primary diagnosis: Hodgkin lymphoma (86%); non-Hodgkin lymphoma (10%); other (3%); median age at diagnosis of primary cancer: 21.5y (IQR, 16-28), and at trial enrollment: 43.8y (35-49); median time from diagnosis of primary cancer to study: 17.0y (12-26). Median chest RT dose: 30.3 Gy (21-37.3); 11% had received pelvic radiation; 39% were post-menopausal at study. Participant characteristics were comparable between the two treatment arms, as was the mean baseline MBD (LDTam: 52.6% vs. placebo: 50.4%, p=0.6). The time*treatment arm effect was statistically significant (LDTam vs. placebo: estimate = -1.7, SE = 0.5, p = 0.001), indicating a significantly lower mean fitted MBD for LDTam (43.9%) vs. placebo (47.3%) at 2y (Figure). This represented a 16.5% relative reduction in MBD on the LDTam arm, corresponding to an estimated 33% lower risk of BC (assuming that reductions in MBD have the same benefit in lymphoma survivors as they do in the general population). There were no grade 3 or 4 AEs related to LDTam. Grade 2 AEs did not differ between treatment arms (LDTam: 44.1% vs. placebo: 36.8%, p=0.6). There was no difference in the prevalence of moderate-to-severe patient-reported outcomes between the treatment arms (Table). Conclusion: Low-dose tamoxifen was associated with a significantly steeper decline in MBD in chest RT-exposed lymphoma survivors, when compared with placebo, and was safe and well-tolerated. This is the first trial demonstrating efficacy of a pharmacologic intervention in reducing a biomarker strongly associated with breast cancer risk in lymphoma survivors with a past history of chest radiation. Disclosures Palomares: Covance: Other: Medical monitoring. Henderson:Seattle Genetics: Research Funding. OffLabel Disclosure: The drug is a low-dose tamoxifen, a selective estrogen receptor modulator. Tamoxifen in standard doses is used to reduce the risk of breast cancer in high risk populations. Tamoxifen in standard or low doses have not been tested before for chest-irradiated cancer survivors to reduce the risk of radiation-related breast cancer.

Gestational trophoblastic neoplasia (GTN), a subset of gestational trophoblastic disease (GTD), occurs when tumors develop in the cells that would normally form the placenta during pregnancy. The NCCN Guidelines for Gestational Trophoblastic Neoplasia provides treatment recommendations for various types of GTD including hydatidiform mole, persistent post-molar GTN, low-risk GTN, high-risk GTN, and intermediate trophoblastic tumor.

The NCCN Guidelines for Kidney Cancer provide multidisciplinary recommendations for the clinical management of patients with clear cell and non–clear cell renal cell carcinoma, and are intended to assist with clinical decision-making. These NCCN Guidelines Insights summarize the NCCN Kidney Cancer Panel discussions for the 2020 update to the guidelines regarding initial management and first-line systemic therapy options for patients with advanced clear cell renal cell carcinoma.

Changes in pituitary-ovarian hormones across the menopausal transition have multiple physiological consequences. However, little is known about how the major types of postmenopausal hormone therapy (HT) affect pituitary-ovarian hormonal relationships. This study evaluated these relationships in recently menopausal women (52.45 ± 2.49 yr of age) in the Kronos Early Estrogen Prevention Study (KEEPS) who were compliant to randomized, double-blinded treatment with oral conjugated equine estrogen (o-CEE; n = 109), transdermal 17β-estradiol (t-E2; n = 107), or placebo ( n = 146). Androstenedione, testosterone, 17β-estradiol, estrone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were measured in serum before (baseline) and 48 mo after randomization to treatment. Descriptive summaries of hormone levels were performed, and multiple regression analyses were used to examine the effects of o-CEE, t-E2, and placebo on these hormone levels at 48 mo, adjusting for baseline levels. A network analysis examined the covariance of changes in hormone levels over the 48 mo within treatment groups. As expected, at 48 mo of treatment, hormone levels differed between women in the two active treatment groups compared with placebo, and network analysis indicated stronger relationships among hormone levels in the t-E2 and o-CEE groups compared with placebo. Associations among testosterone, 17β-estradiol, FSH, and LH differed between the o-CEE group compared with t-E2 and placebo groups. Thus, two common HT regimens differentially alter pituitary-ovarian hormone levels, altering feedback cycles and interhormonal associations in recently menopausal women. These interactions provide the basis for future studies investigating the impact of hormonal modulation of aging, including cognitive decline in women.

15 Background: CPG are evidence-based guidelines, which serve as a standard of care in practice, quality improvement, and reimbursement. The extent of financial conflicts of Interest (FCOI) in NCCN guidelines has not been recently evaluated. Our study evaluated the extent of FCOI in the NCCN CPG among the 10 most common malignancies in the US. Methods: We examined the latest 2019 version of the NCCN CPG for the 10 most common cancers by incidence in the US. Using disclosure lists, we catalogued the FCOIs for the panelists under various categories outlined in the CPG. We also tabulated the companies/institutions involved in each disclosure. An “episode” describes 1 instance of participation of a panelist in 1 company in 1 category of each guideline. “Affiliation” describes a commercial, industry, or institute affiliation reported by a panelist in each episode. Results: Of the 491 panelists on the CPG, 483 (98.3%) completed FCOI disclosures. 224 (46.38%) reported at least 1 FCOI. A total of 1,103 episodes were disclosed with an average of 4.9 episodes per panelist with FCOI. Being a part of scientific advisory boards, consultant, or expert witness was the most common FCOI category (19.9%). A total of 191 companies were associated with 1,103 episodes of FCOI. The top companies were Bristol Myers Squibb, Merck, Genentech and AstraZeneca. Among the top 10 cancers, the prevalence of FCOI were lung (56%), bladder (52%), pancreatic (52%), non-Hodgkin lymphoma (50%), kidney (49%), colorectal (43%), breast (42%), melanoma (40%), prostate (38%), and uterine (32%). Among the panelists with FCOI, 26%, 17%, and 57% reported 1, 2, and > 3 episodes, respectively. There were 127 episodes among the CPG chairs/vice chairs who reported FCOI (mean 6.4). The chairs/vice chairs of uterine, pancreatic, melanoma, and prostate cancer CPG did not have any FCOI. Conclusions: FCOI are very prevalent among the top 10 NCCN CPG panelists. In almost half of the CPG, the majority of the panelists had at least 1 FCOI. Over half of the CPG chairs/vice chairs reported multiple FCOI. Further studies are necessary to determine the impact of these FCOI.

14 Background: National Comprehensive Cancer Network (NCCN) guidelines are the most comprehensive and widely used standard for clinical care in oncology by clinicians and payors in the US. The level of scientific evidence in NCCN guidelines has not been studied since it’s last review in 2010. We describe the categories of evidence and consensus (EC) among the 10 most common cancers in the US as of 2019 and compare them with 2010 guidelines. Methods: We obtained the 2019 version of NCCN guidelines. The definitions for various categories of EC used were: Category 1 (high level evidence such as randomized controlled trials with uniform consensus), 2A (lower level of evidence with uniform consensus), 2B (lower level of evidence without a uniform consensus but with no major disagreement) and 3 (any level of evidence but with major disagreement). We compared our results with previously published results from 2010 guidelines. Results: Total recommendations increased by 77% from 1023 (2010) to 1818 (2019). Of the 1818 recommendations, Category 1, 2A, 2B and 3 EC were 7%, 87%, 6% and 0% while in 2010 they were 5%, 85%, 9% and 1% respectively. Recommendations with category 1 EC were found in lung (13%), prostate (11%), melanoma (8%), breast (7%), NHL (5%), kidney (2%), bladder (2%) and colorectal (2%) guidelines. Pancreatic and uterine cancer guidelines had no recommendations with category 1 EC. 19% of therapeutic recommendations were category 1 EC with the majority (65%) pertaining to initial therapy. Guidelines with highest proportions of therapeutic recommendations with category 1 EC were breast (30%), lung (10%), and kidney (10%) cancers. No category 1 EC recommendations existed in screening or surveillance. Although we found an increase in the total number of recommendations, the distribution of different types of categories of EC are largely similar to 2010. Conclusions: Recommendations in 2019 NCCN guidelines are largely derived from lower levels of evidence with uniform expert opinion. Despite the major advances in oncology in the past decade, this is largely unchanged. Our study underscores the urgent need and available opportunities to expand the current evidence base in oncology which forms the platform for clinical practice guidelines.

Abstract Introduction: Monoclonal antibodies (MoAbs) have shown activity in relapsed and refractory multiple myeloma (MM). Elotuzumab is an anti-SLAMF7 MoAb that synergizes with immunomodulatory agents (IMiDs) and is approved for treatment of relapsed and refractory MM. Anti-CD38 MoAbs (daratumumab, FDA approved and isatuximab, in clinical trials) have also entered the therapeutic MM landscape but little is known about how to best sequence MoAbs and the existence of cross resistance between different classes of MoAbs. We analyzed outcomes of patients who become refractory to elotuzumab with emphasis on the activity of anti-CD38 MoAbs in the post-elotuzumab setting. Methods: We identified patients from 14 academic institutions within the US who were refractory to elotuzumab administered alone or in combination with other agents. Patients were considered refractory to elotuzumab if treated with at least 4 weeks of therapy and had evidence of progressive disease (PD) within 60 days of last dose. Time zero (T0) was defined as point when myeloma became refractory to elotuzumab-containing regimen. Data were collected with an electronic platform and submitted to peer-based quality check for completeness and internal consistency. We analyzed demographics, characteristics of their myeloma and prior therapy including number and type of therapy prior to elotuzumab, duration of elotuzumab therapy, and outcome after becoming refractory to elotuzumab. We performed a multi-variable analysis of these factors to determine significant factors associated with survival post T0. We subsequently identified a subset of patients who received an anti-CD38 MoAb alone or in combination as next or subsequent line of therapy after T0 and report their outcomes. Results: Eighty-nine patients were evaluated. Eighty-six (96.6%) had progression on elotuzumab in combination with IMiD (N=82) or another agent (N=4). Median age at T0 was 65 years (range 28-90), 51% of patients were males, 65% were White, 54% had IgG subtype, 27% had ISS stage III at diagnosis, and 27% had high-risk cytogenetics. Patients received a median of 4 prior lines of treatment (range 1-11) prior to elotuzumab-containing regimen, including 66% who underwent autologous transplant. Sixty-one patients (69%) were refractory to at least one IMiD and one proteasome inhibitor (PI) at T0, classified as double-refractory. Twenty-one (23.6%) were quad-refractory, i.e. refractory to 2 IMiDs and 2 PIs. Twenty-eight patients (31.5%) were refractory to prior anti-CD38 MoAb. The median time from diagnosis to T0 was 59.5 months and duration of elotuzumab therapy was 3 months (range 0.4 - 59.5). Median OS from T0 for the entire cohort was 15.1 months (95% C.I. 9.3-20.9). In multivariate analysis, the only factors affecting OS after T0 were high-risk cytogenetics (HR 3.31, 95% C.I. 1.74-6.27, P<0.001) and refractoriness to prior anti-CD38 MoAb (HR 4.22, 95% C.I. 2.22-8.01, P<0.001). Interestingly, median OS for patients not refractory to anti-CD38 MoAb was 33.1 months vs. 4.5 months for anti-CD38 MoAb-refractory patients (Figure 1). After T0, 45 patients (50.6%) received an anti-CD38 MoAb in the next (N=28, 62.5%) or subsequent regimens (N=17, 37.8%). Median time between T0 and initiation of anti-CD38 MoAb was 1.2 months (0-15.0). Anti-CD38 MoAbs employed were: isatuximab in 4 (8.9%) and daratumumab in 41 patients (91.1%). In most cases, the anti-CD38 MoAb was administered in combination with IMiD (N=30, 66.6%) or bortezomib (N=7, 15.6%). The overall response rate (ORR) for anti-CD38 MoAb regimens was 35.6%; responses to specific combinations are outlined in the Table. Median PFS for elotuzumab-refractory patients receiving therapy with anti-CD38 MoAbs was 4.6 months (95% C.I. 1.6-7.6), while median OS was 15.3 months (95% C.I. 8.2-22.4) (Figure 2). Conclusion: Patient who become refractory to elotuzumab have guarded prognosis, particularly dismal among patients also refractory to anti-CD38 MoAb, defining a population with great need for novel therapies. Failure of elotuzumab-based therapy does not preclude disease control with anti-CD38 MoAb, particularly in combination. Disclosures Paul: Bristol Myer Squibb: Other: Stock and pension plan (past employee). Amarendra:Amgen: Consultancy; Celgene: Consultancy. Liedtke:Caelum: Membership on an entity's Board of Directors or advisory committees; celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech/Roche: Research Funding; BlueBirdBio: Research Funding; Prothena: 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, Research Funding; Amgen/Onyx: Consultancy, Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding. Hari:Kite Pharma: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; Janssen: Honoraria; Bristol-Myers Squibb: Consultancy, Research Funding; Amgen Inc.: Research Funding; Spectrum: Consultancy, Research Funding. Vij:Karyopharm: Honoraria; Jazz Pharmaceuticals: Honoraria; Janssen: Honoraria; Amgen: Honoraria; Takeda: Honoraria, Research Funding; Bristol Myer Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Usmani:Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy; Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding. Costa:Karyopharm: Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Research Funding; Sanofi: Honoraria; Janssen: Research Funding.

Abstract Introduction Development of anti-CD38 monoclonal antibody therapies (MoABs), including daratumumab and isatuximab, have drastically changed the therapeutic landscape for management of relapsed and/or refractory multiple myeloma (RRMM). However, there is a paucity of information regarding response to treatment after progression on CD38 MoABs. This collaborative research study (MAMMOTH: Monoclonal Antibodies in Multiple Myeloma: Outcomes after Therapy Failure) investigates the therapeutic choices and outcomes of subsequent treatments after refractoriness to MoABs. Methods Patients from 14 US academic institutions with diagnosis of MM and refractory to daratumumab or isatuximab, administered alone or in combination, were evaluated. Patients were considered refractory to a CD38 MoAB if treated with at least 4 weeks of therapy and had evidence of progressive disease (PD) while on therapy or within 60 days after last dose. Time of progression was defined as time zero (T0). Data was collected by electronic platform and submitted to peer-based quality check for completeness and internal consistency. Results Two hundred and seventy-five patients with MM refractory to CD38 MoAB were evaluated; 249 (90.5%) of those patients who received at least one subsequent line of therapy were included in this analysis. The median age at T0 was 65 years (range 27-90) and 54% were male. At the time of diagnosis, 28% had ISS stage III disease and 29% had high-risk cytogenetics. Patients were heavily pre-treated at T0 with a median of 5 lines of therapy (range 2-17); most (74%) underwent a prior autologous stem cell transplant. The majority of patients were refractory to other anti-myeloma therapies including lenalidomide (78%), pomalidomide (65%), bortezomib (69%) and carfilzomib (45%). In total, 97.1% of patients were exposed to at least one immunomodulatory agent (IMiD) and one proteasome inhibitor (PI), 79.3% were ≥ triple-refractory (refractory to 1 IMiD, 1 PI and 1 CD38 MoAB), while 25.3% were penta-refractory (refractory to 2 IMiDs, 2 PIs and 1 CD38 MoAB). Responses to the next subsequent line of therapy after progression with CD38 MoAB are shown (Table). The overall response rate (ORR; ≥PR) of first regimen post-T0 was 31% with a median progression free survival (PFS) of 3.4 mo and median overall survival (OS) of 9.3 mo. Carfilzomib-based therapy resulted in an ORR of 32% with median PFS 4.2 mo and overall OS of 10.9 mo. The addition of an IMiD to daratumumab yielded an ORR of 37% with median PFS 4.5 mo and OS 12.6 mo. The addition of a PI to daratumumab yielded no responses. Elotuzumab-based therapy had an ORR of 21% with median PFS 2.6 mo and OS 8.3 mo. By multivariate analysis, alkylator-based therapies were found to have the highest ORR (OR 3.1, 95% CI 1.8-5.7, p<0.001), however, resulted in median PFS of only 3 mo and OS of 7.7 mo. Multivariate analysis evaluating for PFS and adjusting for refractoriness to prior therapies found lower risk of progression with carfilzomib-based therapy (HR 0.60, 95% CI 0.42-0.85, p=0.004, Figure 1) and with the addition of an IMiD to daratumumab (HR 0.64, 95% CI 0.43-0.94, p=0.02). The benefit of IMiD + daratumumab was essentially restricted to patients previously refractory to CD38 MoAB as monotherapy. These patients demonstrated improved PFS with subsequent daratumumab-combination therapy at time of progression compared with patients refractory to CD38 MoAB combination therapy (log-rank p=0.02, Figure 2). No particular regimen was associated with improved OS compared with the rest. Conclusions After progression on CD38 MoAB, treatment with carfilzomib-based regimens and the addition of an IMiD to daratumumab-monotherapy resulted in a higher ORR and PFS compared with other regimens. Alkylating agents resulted in the highest ORR but relatively short PFS and OS. The use of elotuzumab and the addition of a PI to daratumumab monotherapy resulted in relatively low response rates. Overall, progression after CD38 MoAB therapy is associated with a poor prognosis and innovative therapeutic strategies are needed. Disclosures Malek: Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau. Paul:Bristol Myer Squibb: Other: Stock and pension plan (past employee). Neppalli:Celgene: Consultancy; Amgen: Consultancy. Liedtke:Amgen/Onyx: Consultancy, Honoraria, Research Funding; Caelum: Membership on an entity's Board of Directors or advisory committees; Genentech/Roche: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; celgene: Research Funding; BlueBirdBio: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Hari:Takeda: Consultancy, Honoraria, Research Funding; Spectrum: Consultancy, Research Funding; Kite Pharma: Consultancy, Honoraria; Sanofi: Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Amgen Inc.: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Janssen: Honoraria. Vij:Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansson: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Costa:Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; BMS: Research Funding; Abbvie: Research Funding; Janssen: Research Funding; Karyopharm: Research Funding; Sanofi: Honoraria. Kumar:Roche: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.