Tilly, Hervé

PURPOSE Although most patients with follicular lymphoma (FL) can expect an indolent course, progressive lymphoma remains the primary cause of death during the first decade after diagnosis. Progression of disease within 24 months (POD24) of starting first-line (1L) immunochemotherapy defines a high-risk population with poor survival, but better risk stratification at diagnosis is needed. METHODS The FLIPI24 model was developed and internally validated to predict 24-month event rates using individual data from 4,485 patients treated with 1L immunochemotherapy from 10 observational cohorts of FL. Overall and cause-specific survival was further evaluated in FLIPI24 risk groups. External validation in the 1L immunochemotherapy setting was performed using the prospective observational Lymphoma Epidemiology of Outcomes (LEO) cohort (N = 565) and three randomized phase III trials (N = 3,192); extension to all patients with FL (any 1L therapy) was performed in the LEO cohort (N = 1,445) and its Molecular Epidemiology Resource subcohort (N = 1,074). RESULTS The FLIPI24 model uses age and four blood-based variables (hemoglobin, lactate dehydrogenase, beta-2 microglobulin, and WBC count). FLIPI24 showed consistent performance across validation and extension data sets, which was superior to existing prognostic tools. Across the four external immunochemotherapy validation data sets, patients with high-risk FLIPI24 (23%-32% of patients) had significantly higher 24-month event rates (22%-35%) and inferior 5-year overall survival (77%-83%) compared with patients with low-risk FLIPI24 (29%-31% of patients, 24-month event rates: 10%-12%; 5-year OS: 96%-97%). Results were consistent when evaluating lymphoma-related death and when extended to all patients with FL. CONCLUSION The FLIPI24 model robustly stratifies, at diagnosis, patients with FL at increased risk of lymphoma-related death versus patients with very low lymphoma-related mortality during the first decade after diagnosis. FLIPI24 can be used to enrich future clinical trial designs in newly diagnosed FL.

Abstract Diffuse large B-cell lymphoma (DLBCL) poses a challenge in hematology given its varied symptoms, and the complex interplay between disease and treatment effects on health-related quality of life (HRQoL). The phase 3 POLARIX study demonstrated superior progression-free survival and a similar safety profile with polatuzumab vedotin plus rituximab, cyclophosphamide, doxorubicin, and prednisone (Pola-R-CHP) vs R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) in patients with previously untreated DLBCL. Here, we evaluate HRQoL through patient-reported outcome (PRO) instruments to fully characterize the patient experience in the POLARIX study. Changes from baseline in HRQoL, lymphoma symptoms, and gastrointestinal (GI) symptoms were assessed, as well as incidence and severity of common symptoms by PROs vs clinician-reported adverse events (AEs). Baseline characteristics of PRO-evaluable patients (N = 874) were consistent. Comparison between PROs and clinician-reported AEs revealed a notable discordance; patients generally reported a higher incidence of symptoms than clinicians, emphasizing the need for patient-centric tools to accurately capture the patient experience. Both treatments exhibited rapid and sustained improvements in HRQoL and lymphoma symptoms, with the most substantial improvements seen in global health status/QoL, lymphoma symptoms, fatigue, role, emotional, and social functioning. GI symptoms (diarrhea, constipation, nausea, and vomiting) were generally similar between treatment arms and returned to baseline levels after treatment completion. These HRQoL data underscore the complementarity of PROs, as an adjunct to clinician-reported AEs, in evaluating the efficacy and tolerability of new treatments, including Pola-R-CHP, which may represent a new benchmark for patient-reported HRQoL in previously untreated DLBCL. This trial was registered at www.clinicaltrials.gov as NCT03274492.

12100 Background: The safety profiles of novel agents are mainly based on clinician-reported adverse events (AEs) from clinical trials. Patient-reported outcomes (PROs) may better represent the treatment burden experienced by patients (pts) compared with clinician-reported AEs. Using data from POLARIX, a double-blind, placebo-controlled, randomized Phase 3 international study (NCT03274492), we previously presented PRO and clinician-reported data showing similar rates of neuropathy (Trněný et al. 2022). Here, we evaluate the reporting of other common symptoms using PRO and clinician-reported data in POLARIX. Methods: POLARIX methods were previously described (Tilly et al. 2022); this analysis included all pts with PRO data. PRO and clinician-reported data described the incidence and severity of fatigue, constipation, diarrhea, nausea, and vomiting. Clinician-reported severity grading was based on the NCI Common Terminology Criteria for Adverse Events (NCI-CTCAE) v4.0. PROs were collected using the European Organisation Research and Treatment of Cancer Quality of Life-Core 30 questionnaire (EORTC QLQ-C30), which was administered to pts at clinic visits on Day 1 of Cycles 1 (baseline), 2, 3, and 5, and end of treatment (EOT). PRO severity scores included ‘A little’, ‘Quite a bit’, and ‘Very much’. Results: Overall, 825 pts were evaluable. From baseline to EOT, PROs showed a higher incidence of symptoms compared with clinicians for fatigue (98% vs 27%), constipation (68% vs 29%), diarrhea (56% vs 26%), nausea (58% vs 40%), and vomiting (24% vs 15%). PRO severity scores of ‘Quite a bit’ or ‘Very much’ were reported in 33% of pts for fatigue, 29% for constipation, 17% for diarrhea, 19% for nausea, and 7% for vomiting. Clinicians reported Grade ≥2 symptoms in 11% of pts for fatigue, 11% for constipation, 11% for diarrhea, 14% for nausea, and 6% for vomiting. Conclusions: In POLARIX, pts reported a higher incidence and severity of symptoms compared with clinicians. Although distinct scales were used, the differences in symptom rates reported by pts and clinicians were clinically meaningful. These data may have implications for symptom management, including physician evaluation and communication of symptom expectations for pts. Reporting of symptoms by PROs should be incorporated into clinical trials as an adjunct to standard AE reporting to better characterize the patient experience. Clinical trial information: NCT03274492 . [Table: see text]

Abstract Introduction: Plamotamab (XmAb13676) is a humanized bispecific antibody that binds both CD20 and CD3 to recruit cytotoxic T cells to kill CD20 expressing malignant cells. Interim results of an ongoing first-in-human (FIH), dose-escalation study (XmAb13676-01; NCT02924402) in subjects with relapsed/refractory (R/R) non-Hodgkin's lymphoma (NHL) are reported. Methods: The study is an FIH, multi-center, open-label, phase 1, dose-escalation study in subjects with R/R NHL with a standard 3 + 3 design. The primary objectives are to determine safety, tolerability, and the maximum tolerated dose (MTD) or recommended dose of plamotamab. Secondary objectives include preliminary anti-tumor activity and pharmacokinetics/pharmacodynamics of plamotamab. This study has 3 Parts: Part A, escalating dose cohorts that establish an initial priming dose as part of repeated weekly infusions at a fixed, weight-based dose in a 28-day cycle; Part B, with a dosing schedule consisting of a priming dose on Cycle 1 Day 1, established in Part A, followed by step-up dosing (SUD) on subsequent weeks; and Part C is an SUD regimen with flat and less frequent dosing. Cytokine release syndrome (CRS) prophylaxis with dexamethasone, antihistamine, and acetaminophen was mandated prior to each administration of plamotamab. Treatment was continued for 2 cycles or longer if there was evidence of therapeutic benefit. Results: At data cut-off (01Jul2021), 80 subjects with NHL have been treated. Subjects had a median age of 62 years (range 32-89), a median of 4 prior therapies (range 1-10), and had been diagnosed a median of 28 months (range 6-353) prior to treatment in the study. The most common treatment-related adverse event was CRS. Overall, 50 subjects (62.5%) experienced CRS, with 4 (5.0%) experiencing Grade ≥ 3 CRS. No related neurotoxicity >Grade 2 has been observed. Treatment responses for NHL were assessed by the Lugano criteria or International Working Group criteria for Waldenström Macroglobulinemia. There have been 23 objective responses (43.4% overall response rate [ORR]) and 13 (38.2%) at doses of ≥ 80 µg/kg or flat dosing in all evaluable subjects with NHL and diffuse large cell B-cell lymphoma, respectively. In the efficacy-evaluable, follicular lymphoma population, at doses of 80-360 µg/kg or flat dosing, objective responses were observed in 8/10 (80%) subjects. After implementation of flat dosing, as opposed to weight-based dosing, a 50% ORR (4/8 evaluable subjects) has been observed in NHL subjects in that cohort. An MTD has not been reached, and dose escalation is ongoing. Overall, 4 out of 16 (25%) evaluable subjects with prior CAR-T therapy responded to plamotamab. Conclusions: Plamotamab demonstrated evidence of clinical activity in heavily pretreated subjects with R/R NHL. CRS was generally manageable with premedication. The study is ongoing with further optimization of dose and schedule. Figure 1 Figure 1. Disclosures Patel: Kite Pharma: Consultancy, Speakers Bureau; Genentech: Consultancy; Morphosys: Consultancy; Bristol Myers Squibb: Consultancy, Speakers Bureau; BeiGene: Consultancy; Janssen: Consultancy; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; Pharmacyclics: Consultancy; Abbvie: Consultancy; TG Therapeutics: Consultancy, Speakers Bureau; MEI Pharma: Consultancy; ADC Therapeutics: Consultancy; Lilly: Consultancy. Michot: GSK: Honoraria; Celgene: Honoraria; MSD: Consultancy, Honoraria; Innate Pharma: Research Funding; Incyte: Research Funding; H3 biomedecine: Research Funding; GSK: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Gamamabs: Research Funding; Forma: Research Funding; Exelixis: Research Funding; Eos: Research Funding; Eisai: Research Funding; Debiopharm: Research Funding; Daiichi Sankyo,: Research Funding; Clovis: Research Funding; Chugai: Research Funding; Boeringer Ingelheim: Research Funding; Celgene: Research Funding; Blueprint: Research Funding; Beigene: Research Funding; Bayer: Research Funding; Argen-x: Research Funding; Amgen: Research Funding; Agios: Research Funding; Aduro: Research Funding; Abbvie: Research Funding; ASTEX: Research Funding, Speakers Bureau; Astra Zeneca: Honoraria, Research Funding; Roche: Honoraria; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding. Chanan-Khan: Alpha2 Pharmaceuticals, NonoDev, Starton: Current holder of stock options in a privately-held company; Ascentage: Research Funding; Cellectar: Current equity holder in publicly-traded company; Alpha2 Pharmaceuticals: Patents & Royalties: Tabi; Ascentage, Starton, Cellectar, NonoDev, Alpha2 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; BeiGene, Jansen, Ascentage: Honoraria; BieGene, Jansen, Ascentage: Consultancy. Ghesquieres: Janssen: Honoraria; Mundipharma: Consultancy, Honoraria; Roche: Consultancy; Celgene: Consultancy, Honoraria; Gilead Science: Consultancy, Honoraria. Byrd: Vincerx Pharmaceuticals: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Novartis, Trillium, Astellas, AstraZeneca, Pharmacyclics, Syndax: Consultancy, Honoraria; Newave: Membership on an entity's Board of Directors or advisory committees. Cartron: Roche, Celgene-BMS: Consultancy; Danofi, Gilead, Novartis, Jansen, Roche, Celgene-BMS, Abbvie, Takeda: Honoraria. Portell: Acerta/AstraZeneca: Research Funding; Xencor: Research Funding; SeaGen: Research Funding; Targeted Oncology: Honoraria; Aptitude Health: Honoraria; Abbvie: Research Funding; Pharmacyclics: Honoraria; Kite: Honoraria, Research Funding; Merck: Honoraria, Research Funding; BeiGene: Honoraria, Research Funding; Morphosys: Honoraria; TG Therapeutics: Honoraria, Research Funding; Genentech: Research Funding; VelosBio: Research Funding. Solh: Jazz Pharmaceuticals: Consultancy; Partner Therapeutics: Research Funding; BMS: Consultancy; ADCT Therapeutics: Consultancy, Research Funding. Wierda: Loxo Oncology, Inc.: Research Funding; GSK/Novartis: Research Funding; Pharmacyclics LLC, an AbbVie Company: Research Funding; Miragen: Research Funding; Sunesis: Research Funding; Gilead Sciences: Research Funding; KITE Pharma: Research Funding; Genentech: Research Funding; Janssen: Research Funding; Juno Therapeutics: Research Funding; Acerta Pharma Inc.: Research Funding; Xencor: Research Funding; AstraZeneca: Research Funding; Cyclacel: Research Funding; Oncternal Therapeutics, Inc.: Research Funding; Karyopharm: Research Funding; Genzyme Corporation: Consultancy; AbbVie: Research Funding. Johnson: Xencor: Current equity holder in publicly-traded company, Divested equity in a private or publicly-traded company in the past 24 months, Ended employment in the past 24 months. Garcha: Xencor: Current Employment, Current equity holder in publicly-traded company, Current holder of stock options in a privately-held company; Promedim: Ended employment in the past 24 months. Ribrag: AstraZeneca: Membership on an entity's Board of Directors or advisory committees; GSK: Research Funding; MSD Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Servier: Consultancy, Membership on an entity's Board of Directors or advisory committees; Argen-X: Research Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Astex Pharmaceuticals: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees; Nanostring: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; PharmaMar: Honoraria, Membership on an entity's Board of Directors or advisory committees; Epizyme: Honoraria, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees. Liebowitz: Xencor: Current Employment, Current equity holder in publicly-traded company, Divested equity in a private or publicly-traded company in the past 24 months. Phillips: Incyte: Consultancy, Other: received travel expenses from Incyte, Research Funding; ADCT, BeiGene, Bristol Myers Squibb, Cardinal Health, Incyte, Karyopharm, Morphosys, Pharmacyclics, Seattle Genetics: Consultancy; AbbVie: Consultancy, Research Funding; AstraZeneca: Consultancy; BMS: Consultancy, Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Consultancy, Research Funding.

Abstract Disease progression after frontline therapy for Diffuse large B‐cell lymphoma (DLBCL) is a clinically significant event. Patients who experience early progression or have refractory disease have especially poor outcomes. Simple, clinically applicable prognostic tools are needed for selecting patients for consideration for novel therapies and prognostication in the relapsed/refractory (R/R) setting. Model building was performed in patients from the Surrogate endpoints in aggressive lymphoma (SEAL) consortium with disease progression after frontline immunochemotherapy. The primary endpoint was overall survival (OS) measured from date of progression. Validation was performed in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and Danish National Lymphoma Register (LYFO) cohorts. Model performance was assessed using time‐dependent concordance indices (c‐statistic) and calibration with metrics evaluated at 2 years from progression. Note, 1234 of 5112 patients treated with frontline immunochemotherapy in the SEAL consortium developed progressive disease. Time to progression on immunochemotherapy and age at progression were strongly associated with post‐progression OS (both p < 0.001). A prognostic model was developed incorporating spline fit for both variables. The model had good concordance in the discovery (0.67) and validation sets (LYFO c = 0.64, MER c = 0.68) with generally good calibration. Time to progression on frontline therapy is strongly associated with post‐progression OS in DLBCL. We developed and validated a simple to apply clinical prognostic tool in the R/R setting. The useful prediction of expected outcomes in R/R DLBCL and can inform treatment decisions such as considerations for CAR‐T therapy as well as trial designs. The model is available in smartphone‐based point of care applications.

Abstract Great heterogeneity in survival exists for patients newly diagnosed with diffuse large B-cell lymphoma (DLBCL). Three scoring systems incorporating simple clinical parameters (age, lactate dehydrogenase, number/sites of involvement, stage, performance status) are widely used: the International Prognostic Index (IPI), revised IPI (R-IPI), and National Comprehensive Cancer Network IPI (NCCN-IPI). We evaluated 2124 DLBCL patients treated from 1998 to 2009 with frontline rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP; or variant) across 7 multicenter randomized clinical trials to determine which scoring system best discriminates overall survival (OS). Median age was 63 years, and 56% of patients were male. Five-year OS estimates ranged from 54% to 88%, from 61% to 93%, and from 49% to 92% using the IPI, R-IPI, and NCCN-IPI, respectively. The NCCN-IPI had the greatest absolute difference in OS estimates between the highest- and lowest-risk groups and best discriminated OS (concordance index = 0.632 vs 0.626 [IPI] vs 0.590 [R-IPI]). For each given IPI risk category, NCCN-IPI risk categories were significantly associated with OS (P ≤ .01); the reverse was not true, and the IPI did not provide additional significant prognostic information within all NCCN-IPI risk categories. Collectively, the NCCN-IPI outperformed the IPI and R-IPI. Patients with low-risk NCCN-IPI had favorable survival outcomes with little room for further improvement. In the rituximab era, none of the clinical risk scores identified a patient subgroup with long-term survival clearly &lt;50%. Integrating molecular features of the tumor and microenvironment into the NCCN-IPI or IPI might better characterize a high-risk group for which novel treatment approaches are most needed.

7544 Background: Great heterogeneity in survival exists for patients (pts) newly diagnosed with aggressive BCL. Three scoring systems based on simple clinical parameters (age, lactate dehydrogenase, number/sites of involvement, stage, performance status) are widely used: the international prognostic index (IPI), revised-IPI (R-IPI), and National Comprehensive Cancer Network IPI (NCCN-IPI). We studied BCL pts treated with R-CHOP to determine which scoring systems best identifies subgroups with poor outcomes that might benefit from new approaches. Methods: Individual pt data from 7 multicenter trials (1998-2009) of pts with BCL (86% DLBCL) treated front-line with R-CHOP (or variant) were analyzed to determine whether IPI, R-IPI, or NCCN-IPI best discriminated overall survival (OS). The concordance index (c-index) from a proportional hazards model, stratifying on trial and induction therapy, quantified predictive accuracy of each scoring system. Results: 2561 pts (median age 63 yrs, 56% male) were classified into IPI, R-IPI, and NCCN-IPI risk groups (Table). With a median follow-up of 5 yrs, NCCN-IPI had the greatest absolute difference in OS estimates between the highest and lowest risk groups at 1, 3, and 5 yrs, and best discriminated OS (c-index = 0.631, Table). Conclusions: In an independent and large cohort of pts, NCCN-IPI performs best in risk-stratifying pts with aggressive BCL, readily distinguishing pts at high and low risk for treatment failure using clinical parameters (5-yr OS between 48 and 92%). Improvement over the simpler IPI appears incremental, and IPI may remain a valuable alternative. Work integrating molecular features of the tumor into the (NCCN-) IPI is in progress to define high risk groups where targeted novel approaches are needed most. [Table: see text]

Background: Disease progression (PD) after frontline IC therapy for DLBCL is a clinically significant event and only 20-40% of patients achieve durable remissions with salvage chemotherapy. Patients who experience early PD or have disease refractory to IC have especially poor outcomes. Chimeric antigen receptor T-cell therapy has emerged as a novel effective therapy for selected cases of relapsed or refractory (r/r) DLBCL, although its availability is limited by cost and logistic challenges. Simple, clinically applicable prognostic tools would be useful for selecting patients for consideration for novel therapies vs those who are more likely to be successfully managed by conventional therapies, but few have been developed for r/r DLBCL. Methods: Model building was performed in patients with PD after IC from 13 frontline, multicenter, randomized DLBCL clinical trials from the SEAL Consortium. All patients received rituximab and an anthracycline-based combination IC and were followed systematically; however therapy received, clinical, and laboratory data at progression were not available. OS was defined as time from first progression until death from any cause. Associations between variables and OS were evaluated using Cox models; splines were used to model functional forms. Validation was performed in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and Danish LYFO cohorts. Model performance was assessed using time-dependent concordance indices (c-stat), Brier scores, and calibration with metrics evaluated at two years from progression. Results: Model Development (SEAL): 1125 of 5112 patients had PD after IC. Median time to PD (TTP) was 11.8 months (IQR 6.6-23.5); median age at PD was 68 years (IQR 60-73). At a median follow-up of 21 months from PD (IQR 7-43), 732 patients (65%) had died and 24 month overall survival after PD (OS24) was 35% (95% CI: 32-38). TTP was strongly associated with post PD OS (spline p-value&lt;0.0001) with OS24 ranging from 18% in patients with TTP &lt;6 months compared to 69% in patients with TTP &gt; 36 months (Figure A). Additionally, age at PD (spline p-value&lt;0.0001) was associated with post PD OS. A model consisting of age at PD including patients 40-80 years and TTP ranging 0-60 months was created (n=1011, Figure B) due to sparse data outside these intervals. C-stat was 0.67, and the model was well calibrated (predicted OS24 = 34% vs. actual OS24 = 34%). External Validation (MER): The model was validated in 290 patients with DLBCL who initiated 2nd line therapy after PD to IC. Median age at PD was younger than the SEAL cohort at 62 years (IQR 57-70). Patients with biopsy proven indolent histology at relapse were excluded. Median TTP was 8.2 months (IQR 5.1-17.0). At a median follow-up of 87 months from PD, 201 patients (69%) had died. OS24 was 47% (95% CI: 41-53). The model showed similar concordance (c-stat=0.65), but underestimated OS24 (predicted =33% vs. 47% actual, Figure C). External Validation (LYFO): The model was validated in 599 patients with DLBCL and PD after frontline IC. Median age at PD was 67 years (IQR 60-73). Median TTP was 10.1 months (IQR 6.0-19.4). At a median follow-up of 82 months from PD, 435 patients (73%) had died. OS24 was 38% (95% CI: 34-42). The model showed similar concordance (c-stat=0.67) when applied to the LYFO cohort, but again underestimated OS24 (predicted =32% vs. 38% actual, Figure D). Case vignettes: A 74 year old patient who progressed 9 months after diagnosis would have a predicted OS24 of 20%. A 58 year old patient who progressed 32 months after diagnosis would have a predicted OS24 of 65% Conclusions: TTP to following IC is strongly associated with post-progression survival in DLBCL. We developed a model from the largest frontline clinical trial dataset in DLBCL and validated a simple to apply clinical prognostic tool in the r/r setting. The model allows better understanding of expected outcomes in r/r DLBCL and can aid design and interpretation of trial results in this setting. The model underestimated the actual survival probability when applied to non-trial validation cohorts. Recalibration of the model for transplant eligible patients and development of smartphone based point-of-care application of the model is ongoing. Figure Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees. Schmitz:Riemser: Consultancy, Honoraria; Celgene: Equity Ownership; Gilead: Honoraria; Novartis: Honoraria. Farooq:Kite Pharma: Research Funding; Celgene: Honoraria. Flowers:Optimum Rx: Consultancy; Burroughs Wellcome Fund: Research Funding; BeiGene: Consultancy, Research Funding; Karyopharm: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Bayer: Consultancy; TG Therapeutics: Research Funding; Acerta: Research Funding; Celgene: Consultancy, Research Funding; National Cancer Institute: Research Funding; Denovo Biopharma: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy; Millenium/Takeda: Research Funding; AbbVie: Consultancy, Research Funding; V Foundation: Research Funding. Frederiksen:Alexion: Research Funding; Gilead: Research Funding; Abbvie: Research Funding; Janssen Pharmaceuticals: Research Funding; Novartis: Research Funding. Cunningham:Eli Lilly: Research Funding; 4SC: Research Funding; Bayer: Research Funding; MedImmune: Research Funding; Celgene: Research Funding; AstraZeneca: Research Funding; Merrimack: Research Funding; Sanofi: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Merck: Research Funding; Clovis: Research Funding. Jørgensen:Gilead: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Poeschel:Amgen: Other: Travel, accommodations, expenses; Abbvie: Other: Travel, accomodations, expenses; Hexal: Speakers Bureau; Roche: Other: Travel, accomodations, expenses. Nowakowski:F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Seymour:Takeda: Consultancy; Celgene: Consultancy, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Acerta: Consultancy; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding, Speakers Bureau. Merli:Takeda: Honoraria, Other: Travel Expenses; Gilead: Honoraria; Mundipharma: Honoraria; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; Janssen: Honoraria. Haioun:novartis: Honoraria; celgene: Honoraria; roche: Consultancy; celgene: Consultancy; gilead: Consultancy; takeda: Consultancy; janssen cilag: Consultancy; amgen: Honoraria; servier: Honoraria. Tilly:roche: Membership on an entity's Board of Directors or advisory committees; servier: Honoraria; merck: Honoraria; Gilead: Honoraria; Janssen: Honoraria; BMS: Honoraria; Karyopharm: Consultancy; Astra-Zeneca: Consultancy; Celgene: Consultancy, Research Funding; Roche: Consultancy. Salles:Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. El-Galaly:Roche: Employment, Other: Travel support; Takeda: Other: Travel support.