Abstract
Background:
Data for outcomes after autologous hematopoietic cell transplant (auto-HCT) in DLBCL patients ≥70 years are limited.
Objectives:
Auto-HCT is feasible on older DLBCL patients.
Study Design:
Using the CIBMTR database, we compared outcomes of auto-HCT in DLBCL patients aged 60-69 years (n=363) versus ≥70 years (n=103) between 2008 and 2019. Non-relapse mortality (NRM), relapse/progression (REL), progression-free survival (PFS), and overall survival (OS) were modeled using Cox proportional hazards models.
Results:
All patients received BEAM conditioning. On univariate analysis, in the 60-69 years versus ≥70 years cohorts, 100-day NRM was 3% versus 4%, 5-year REL was 47% versus 45%, 5-year PFS 40% versus 38% and 5-year OS 55% versus 41% respectively. On multivariate analysis, patients ≥70 had no significant difference in NRM (HR 1.43, 95% CI 0.85-2.39), REL (HR 1.11, 95% CI 0.79-1.56), PFS (HR 1.23, 95% CI 0.92-1.63) compared to patients 60-69 years. Patients ≥70 years had a higher mortality (HR 1.39, 95% CI 1.05-1.85, p=0.02), likely due to inferior post-relapse OS in this cohort (HR 1.82, 95% CI 1.27-2.61, p=0.001). DLBCL was the major cause of death in both cohorts (62% vs. 59%).
Conclusion:
Older patients should not be denied auto-HCT solely based on chronological age.
Keywords: autologous transplant, older, diffuse large B cell lymphoma, relapse, BEAM
Introduction
Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin lymphoma (NHL), has a poor prognosis in the relapsed or refractory (R/R) setting. The risk of developing NHL increases throughout life, with more than half of patients ≥65 years at the time of diagnosis (1). Following the overall survival (OS) benefit demonstrated by the PARMA study in 1995, dose intense chemotherapy followed by consolidative autologous hematopoietic cell transplant (auto-HCT) became the current standard of care (2) in transplant eligible relapsed patients with chemosensitive disease. Yet many older patients will not be offered this potentially curative treatment due to perceived high risk of toxicity from the myeloablative conditioning regimen (3). With no strict guidelines on patient selection for auto-HCT (4), clinician bias to exclude older patients from receiving this treatment deprives them of an opportunity for potentially curative therapy. Many older studies showed a high treatment related mortality (TRM) from auto-HCT, potentially due to the use of high-dose total body irradiation (5). With better supportive care and less toxic conditioning regimens, these resulting morbidities could be mitigated. Still, many older patients (empirically defined as ≥60 years) are susceptible to increased cardiovascular and gastro-intestinal toxicities of conditioning and sub-groups of older patients may continue to have modest increase in TRM compared to their younger counterparts (6, 7). Thus, many older DLBCL patients with R/R disease may not be considered for consolidative auto-HCT based solely on age.
Several single center studies have shown feasibility and safety of auto-HCT in older NHL patients (6-8). Patients ≥70 years remain under-represented in these studies. Moreover, these included all subtypes of lymphoma patients receiving an auto-HCT. Therefore, using the CIBMTR database, we report outcomes of consolidative auto-HCT in relapsed DLBCL patients 60-69 years compared to those ≥70 years.
Materials and Methods
Data Source
The CIBMTR is a collaborative research program managed by Medical College of Wisconsin (MCW) and The National Marrow Donor Program (NMDP) that collects data from >380 transplant centers worldwide. Participating sites are required to report detailed data on both autologous and allogeneic HCT with frequent updates gathered during the longitudinal follow-up of transplant patients and the compliance is monitored by on-site audits. Computerized checks for discrepancies, physicians’ review of submitted data, and on-site audits of participating centers ensure data quality. Observational studies conducted by the CIBMTR are performed in compliance with all applicable federal regulations pertaining to the protection of human research participants. The MCW and NMDP institutional review boards approved this study.
Patients
Adult DLBCL patients aged 60 years and older, who received an auto-HCT between 2008-2019 and were reported to the CIBMTR were included in this analysis. All patients received rituximab-containing, anthracycline based chemoimmunotherapy in the first-line setting. Conditioning for auto-HCT was limited to BEAM (carmustine, etoposide, cytosine arabinoside and melphalan) with or without rituximab (9, 10).
Definitions and Endpoints:
Response to frontline chemoimmunotherapy and disease status prior to auto-HCT were determined using the International Working Group criteria, (11, 12) applicable to the era of these transplants. Chemosensitive disease is defined as achieving either a complete response (CR) or partial response (PR) to treatment before auto-HCT.
The primary endpoint was OS. Death from any cause was considered an event and surviving patients were censored at last follow-up. Secondary outcomes included non-relapse mortality (NRM), relapse/progression, and progression-free survival (PFS). NRM was defined as death without evidence of prior lymphoma progression/relapse; relapse was considered a competing risk. Relapse/progression was defined as progressive lymphoma after auto-HCT or lymphoma recurrence after a CR; NRM was considered a competing risk. For PFS, a patient was considered a treatment failure at the time of progression/relapse or death from any cause. Patients alive without evidence of disease relapse or progression were censored at last follow-up. Early chemoimmunotherapy failure (ECF) was defined as not achieving a CR after first line chemoimmunotherapy or relapse/progression within 1 year of initial diagnosis, as previously reported (13, 14).
Neutrophil engraftment represented the time to achieve an absolute neutrophil count >0.5 × 109 /L that is sustained for 3 consecutive days post-transplantation. Platelet engraftment is time to achieve a platelet count of >20 × 109 /L post-transplantation without any platelet transfusions for 7 consecutive days. Death prior to engraftment was considered a competing risk. All outcomes are calculated relative to the transplantation date.
Statistical Analysis:
All endpoints were compared between age groups 60-69 years and ≥70 years. Patient-, disease- and transplant-related variables were compared between the two cohorts using the Chi-square test for categorical variables and the Wilcoxon two-sample test for continuous variables. The distribution of OS and PFS were estimated using the Kaplan-Meier method. The cumulative incidence method was used to estimate NRM, relapse/progression while accounting for competing events. Cox proportional hazard analysis was used to identify prognostic factors for relapse/progression, NRM, PFS, and OS using forward stepwise variable selection. No covariates violated the proportional hazards assumption. No significant interactions between the main effect and significant covariates were found. Results were reported as hazard ratio (HR), 95% confidence interval (CI) for HR and p-value. Covariates with a p-value <0.05 were considered statistically significant. The variables considered in multivariate analysis are shown in Table 3S. All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).
Results
Baseline Characteristics
A total of 466 DLBCL patients were identified who received an auto-HCT during the study period; 363 patients were between 60-69 years and 103 patients ≥70 years of age. The oldest patient included in this analysis was 79 years at the time of auto-HCT. All patients received BEAM with or without rituximab as the conditioning regimen (dosing details in Table 1S). Patients who received non-BEAM conditioning (n=232) were excluded (details in Table 2S). Baseline characteristics are summarized in Table 1. For patients in the 60-69 years versus ≥70 years cohorts Karnofsky performance status (KPS) ≥90 was report in 54% vs. 45% (P=0.04) patients, respectively. There were no significant differences between the 60-69 and ≥70 years cohorts in CR status before auto-HCT (CR: 61% vs 72%; P=0.05), median number of lines of therapy (2 vs 2; P=0.58) prior to auto-HCT, median time from diagnosis to auto-HCT (20 vs 21 months; P=0.3), or ECF (49% vs 49%, P=0.98).
Table 1.
Baseline Characteristics of DLBCL patients 60-69 years versus ≥70 years receiving auto-HCT
| 60-69 years | ≥ 70 years | P-value | |
|---|---|---|---|
| Patients, n | 363 | 103 | |
| Median age, y (range) | 65 (60-69) | 72 (70-79) | <0.001a |
| Male sex | 213 (59) | 73 (71) | 0.02b |
| Race | 0.35b | ||
| Caucasian | 299 (82) | 93 (90) | |
| African American | 32 (9) | 4 (4) | |
| Asian | 24 (7) | 5 (5) | |
| Other1 | 3 (1) | 0 | |
| Missing | 5 (1) | 1 (1) | |
| Karnofsky Performance Score | 0.04b | ||
| ≥90 | 195 (54) | 46 (45) | |
| HCT-CI | |||
| 3+ | 132 (36) | 38 (37) | 0.97b |
| Remission Status | 0.05b | ||
| CR | 223 (61) | 74 (72) | |
| PR | 140 (39) | 29 (28) | |
| Stage at diagnosis | 0.88b | ||
| Stage III-IV | 245 (67) | 72 (70) | |
| LDH at diagnosis | 0.84b | ||
| High | 52 (14) | 15 (15) | |
| Missing | 216 (60) | 64 (62) | |
| Number of Lines of Chemotherapy | 0.86b | ||
| Median (range) | 2 (1-5) | 2 (1-5) | |
| Bone marrow involvement at diagnosis | 0.57b | ||
| Yes | 74 (20) | 26 (25) | |
| CNS involvement pre-HCT | 0.56b | ||
| Yes | 2 (0) | 1 (1) | |
| Extranodal involvement at diagnosis | 0.14b | ||
| Yes | 203 (56) | 70 (68) | |
| Time from diagnosis to transplant | 0.38b | ||
| Median, d (range) | 20 (3-161) | 21 (4-138) | 0.30a |
| Pre-HCT radiation | 0.44b | ||
| Yes | 71 (20) | 15 (15) | |
| Early Chemoimmunotherapy Failure | 0.98b | ||
| No | 173 (48) | 49 (48) | |
| Yes | 178 (49) | 51 (49) | |
| Missing | 12 (3) | 3 (3) | |
| Conditioning Regimen | 0.12b | ||
| BEAM | 291 (80) | 74 (72) | |
| ;Rituximab-BEAM | 72 (20) | 29 (28) | |
| Response to first line of therapy | 0.69b | ||
| No | 228 (63) | 68 (66) | |
| Yes | 114 (31) | 28 (27) | |
| Missing | 21 (6) | 7 (7) |
3 American Indian or Alaska Native
Kruskal-Wallis test
Pearson chi-square test
Except for the number of patients, median age, number of lines of chemotherapy, time from diagnosis to transplant, all data are n (%).
Abbreviations: BEAM: carmustine, etoposide, cytosine arabinoside and melphalan; CNS: Central Nervous System; CR: complete remission; HCT: hematopoietic cell transplant; HCT-CI: hematopoietic cell transplant comorbidity index; LDH: lactate dehydrogenase; n: number; PR: partial remission; y: years
Non-relapse Mortality and Relapse/Progression
On univariate analysis (Table 2), the 100-day cumulative incidence of NRM was 3% (95% CI, 2-6%) in the 60-69 years and 4% (95% CI, 1-9%) in ≥70 years cohorts (P=0.77). The 1-year NRM (Table 2, Figure 1A) was 6% (95% CI, 3-8) and 8% (95% CI, 3-13) respectively. The 5-year cumulative incidence of relapse/progression (REL) (Table 2, Figure 1B) was 47% (95% CI, 41-52%) in 60-69 years and 45% (95% CI, 35-55%) in ≥70 years (P=0.63) cohorts. On multivariate analysis, there were no statistically significant difference in the risk of NRM (HR 1.43, 95% CI 0.85-2.39, P=0.18), or REL (HR 1.11, 95% CI 0.79-1.56, P=0.56) between the two age cohorts (Table 3).
Table 2:
Univariate analysis of outcomes in DLBCL patients treated with Autologous HCT
| 60-69 years (N=363) | >=70yr (N = 103) | ||||
|---|---|---|---|---|---|
| Outcomes | N eval | Prob (95% CI) | N eval |
Prob (95% CI) | p-value |
| Non-relapse Mortality | 357 | 98 | |||
| 100-day | 3 (1-5)% | 4 (0-8)% | 0.77 | ||
| 1-year | 6 (3-8)% | 8 (3-13)% | 0.41 | ||
| 3-year | 7 (4-10)% | 11 (5-17)% | 0.23 | ||
| 5-year | 9 (6-12)% | 12 (6-19)% | 0.31 | ||
| Relapse/Progression | 357 | 98 | |||
| 1-year | 30 (26-35)% | 36 (27-46)% | 0.26 | ||
| 3-year | 37 (32-42)% | 40 (30-50)% | 0.61 | ||
| 5-year | 39 (34-44)% | 42 (32-52)% | 0.63 | ||
| Progression-free survival | 357 | 98 | |||
| 1-year | 64 (59-69)% | 54 (44-64)% | 0.09 | ||
| 3-year | 56 (51-61)% | 48 (38-58)% | 0.14 | ||
| 5-year | 52 (47-57)% | 44 (34-54)% | 0.16 | ||
| Overall survival | 363 | 103 | |||
| 1-year | 78 (74-82)% | 70 (61-79)% | 0.09 | ||
| 3-year | 71 (66-75)% | 58 (49-68)% | 0.02 | ||
| 5-year | 65 (60-70)% | 50 (41-60)% | 0.01 | ||
Abbreviations: N eval: number evaluated; Prob: probability; auto-HCT: autologous hematopoietic cell transplantation; CAR-T: chimeric antigen receptor T-cells; PR: partial remission
Figure 1A-D: Outcomes for DLBCL patients undergoing autologous HCT: 60-69 years versus ≥70 years.
1A: Non-Relapse Mortality; 1B: Relapse/Progression; 1C: Progression-Free Survival; 1D: Overall Survival
Table 3.
Multivariate analysis of Outcomes in DLBCL patients treated with Autologous HCT
| Non-relapse mortality | N | HR (95% CI) | p-value | Overall p- value |
|---|---|---|---|---|
| 60-69 years old | 3357 | 1 | 0.18 | |
| >=70 years old | 998 | 1.43 (0.85-2.39) | 0.18 | |
| NRM adjusted for significant covariates: Remission status, Sex | ||||
| Progression/relapse | N | HR (95% CI) | p-value | Overall p- value |
| 60-69 years old | 3357 | 1 | 0.56 | |
| >=70 years old | 998 | 1.11 (0.79-1.56) | 0.56 | |
| Progression/relapse adjusted for significant covariates: Remission status, Early chemoimmunotherapy failure | ||||
| Progression free survival | N | HR (95% CI) | p-value | Overall p- value |
| 60-69 years old | 3357 | 1 | 0.16 | |
| >=70 years old | 998 | 1.23 (0.92-1.63) | 0.16 | |
| Progression free survival adjusted for significant covariates: Remission status, Early chemoimmunotherapy failure | ||||
| Overall Survival | N | HR (95% CI) | p-value | Overall p- value |
| 60-69 years old | 3363 | 1 | 0.02 | |
| >=70 years old | 1103 | 1.39 (1.05-1.85) | 0.02 | |
| Overall survival adjusted for significant covariates: Remission status, Number of lines of chemotherapy , Early chemoimmunotherapy failure | ||||
| Post-relapse OS | N | HR (95% CI) | p-value | Overall p- value |
| 60-69 years old | 1173 | 1 | 0.001 | |
| >=70 years old | 448 | 1.82 (1.27-2.61) | 0.001 | |
| Post-relapse OS adjusted for significant covariates: Number of lines of chemotherapy | ||||
Progression-free and Overall Survival
Five-year PFS in the ≥70-year age group was 38% (95% CI, 28%-49%) compared with 40% (95% CI, 35%-46%) in the 60-69 years age group (P=0.70; Table 2, Figure 1C). On multivariate analysis patients ≥70 years did not have a significantly different PFS compared to patients in the 60-69 years age group (HR 1.23, 95% CI 0.92-1.63, P=0.16).
Five-year OS (Figure 1D) was 55% (95% CI, 50-60%) in 60-69 years versus 41% (95% CI, 31-52%) in ≥70 years cohort (P=0.02). On multivariate analysis patients ≥70 years had a significantly higher mortality risk (HR 1.39, 95% CI 1.05-1.85, P=0.02) compared to patients in the 60-69 years age group. Since the two cohorts did not have significantly different risk of NRM, REL, or PFS, we analyzed post-relapse OS to investigate the reason for the difference in mortality risk. Post-relapse OS of patients in the ≥70 years cohort was significantly inferior to those in the 60-69 years cohort (HR 1.82, 95% CI 1.27-2.61, P=0.001) (Table 3).
Cause of Death
A total of 256 deaths were seen amongst the entire cohort of 466 patients. The leading cause of death was DLBCL in 62% of patients 60-69 years and 59% of patients ≥ 70 years. Second leading cause of death is organ failure (8%, 60-69 years and 6%, ≥70 years) and infection (6%, 60-69 years and 5%, ≥70 years), (details in Table 4S).
Discussion
Older DLBCL patients with chemosensitive R/R disease are often not considered for auto-HCT due to concerns of increased toxicity based on age alone. Given the limited data on auto-HCT in R/R DLBCL patients ≥70 years in the contemporary era, we compared safety and outcomes in those ≥70 years versus those 60-69 years of age. Our analysis shows similar NRM, relapse/progression and PFS in both age cohorts and supports the feasibility of auto-HCT in select patients ≥70 years. Both cohorts enjoyed a prolonged 5-year PFS (Table 2) indicating that auto-HCT can still be curative in some older patients. Inferior 3- and 5-year OS was seen in patients ≥70 years, despite a lack of difference in other outcome measures. This OS difference was driven primarily by inferior post-relapse OS. It is important to consider that age-appropriate life expectancy is relatively lower in patients ≥70 years compared to those a decade younger and therefore increased mortality is not unexpected. Lower OS may be further explained in part by the fact that older patients are prone to more toxicities of treatment (6) and with potential debility from treatment or disease, are less likely to receive aggressive therapies following relapse. Older patients are also less likely to be enrolled on clinical trials (15-17). Overall, older patients are at risk of receiving sub-optimal therapies (9, 18, 19) thereby potentially affecting their outcomes. It is noteworthy to mention that older age groups are enriched for the presence of clonal hematopoiesis of indeterminate potential (CHIP). It was previously demonstrated that CHIP at the time of auto-HCT has poor outcomes for lymphoma patients (20) and this should be studied in future trials. We acknowledge that disease evolution occurs with each relapse (21), increasing resistance to conventional treatments (22) and may account for poor OS in these patients (21-23). Advances in targeted therapies for relapsed refractory DLBCL are changing the scope of practice for these patients (24).
A limitation of this data set was that quality-of-life (QoL) data and treatment toxicities were not captured. A recent study demonstrated increased rates of grade ≥3 toxicities in lymphoma patients ≥70 years versus 60-69 years receiving BEAM conditioning (100% vs 92%) (6). In our analysis we report no differences in infection and organ failure as causes of death in both age groups. Still, patient co-morbidities and frailty should be considered when evaluating an older patient for auto-HCT. Although there are objective methods to measure frailty and physiologic age, this is not commonly employed in routine practice (25). Comprehensive geriatric assessments are validated in clinical practice to describe physiologic age and if used effectively, can be predictive of outcomes after auto-HCT (26, 27). For example, in one series, a history of in-hospital falls was predictive of inferior NRM and OS in patients undergoing auto-HCT (7). Our data set is limited in that it does not include measures of frailty and physiologic age which would help in patient selection. Unfortunately, measures of function such as the Karnofsky performance status (KPS) and the hematopoietic cell transplant comorbidity index (HCT-CI) are not ideal measures of frailty in older patients. A Canadian study evaluating long-term quality of life in older lymphoma auto-HCT survivors demonstrated that functional well-being was more variable for ≥65-year-old patients and impacted relapse while conditioning regimen, age, gender, or HCT-CI did not impact outcomes (28). Other similar studies of auto-HCT in older patients did not find an association between HCT-CI and incidence of NRM (6, 7, 29, 30). Therefore, for older DLBCL patients, frailty specific prognostic tools are necessary when evaluating patients for auto-HCT. In our study, we could not address for these correlations between HCT-CI and outcomes.
Our analysis reflects similar outcomes to prior studies of older patients receiving auto-HCT (29-33). However, there are several key differences that make this analysis distinct. Firstly, most of these studies save one (31) included heterogenous lymphoma populations, while this analysis focuses on solely on patients with DLBCL. Second, this study represents a homogeneous population receiving BEAM conditioning in the rituximab era. Lastly, compared to prior studies, this analysis comprises the largest sample size of patients ≥70 years (n=103), albeit age group 75 and older were expectedly low (n=17). Our study also observed a significant racial disparity in DLBCL patients receiving an auto-HCT. This may be on account of poor referrals for older auto-HCT (34), socio-economic (35, 36) or disease-related factors (37) and is unfortunately a recurring problem in other disease groups (38, 39).
Our study showcases the largest number of older relapsed DLBCL patients, all receiving a uniform conditioning regimen for salvage auto-HCT. Results from our study are confirmatory as observed in other similar prospective (40) and retrospective reports (8, 30, 31). Notwithstanding the limitations inherent to the retrospective nature of our study, we extrapolate, that in this contemporary data set of older DLBCL patients with R/R chemosensitive disease, select patients ≥70 years could still benefit from consolidative auto-HCT. In addition to limitations mentioned already, other limitations include an inherent bias in patient selection ≥70 years, as similar rates of NRM and PFS for both age cohorts can be interpreted as proof of appropriate patient selection. Our analysis was further limited by the smaller number of patients ≥75 years (n=17). Therefore, much of our conclusions are focused on patients in their early 70s.
In summary, advanced age is a known risk factor for relapse and poor outcomes (2) and therefore auto-HCT should not be withheld based on age alone. Chimeric antigen receptor (CAR) T-cell therapies are now available to older DLBCL patients ineligible for or relapsing following auto-HCT (41-43), but are limited with their own unique toxicities. Whether CAR T-cell therapy or auto-HCT is better tolerated in otherwise fit, older adults is unknown but research is gaining traction (44). With the knowledge that older age predisposes to more aggressive disease biology and with recent data from the Zuma 7 trial (45) showing a superior event free survival benefit of CAR T-cell versus standard-of-care in the second line setting for primary refractory and DLBCL relapsing within 12 months from initial diagnosis, we may see a decline in the use of auto-HCT for older lymphoma patients in the future.
In conclusion, consolidative auto-HCT for R/R DLBCL fit older patients continues to provide durable benefit and should be offered after careful evaluation of co-morbidities, physiologic age and toxicity impact.
Data Sharing:
CIBMTR supports accessibility of research in accord with the National Institutes of Health (NIH) Data Sharing Policy and the National Cancer Institute (NCI) Cancer Moonshot Public Access and Data Sharing Policy. The CIBMTR only releases de-identified datasets that comply with all relevant global regulations regarding privacy and confidentiality.
Supplementary Material
Highlights:
DLBCL patients ≥70 years undergoing auto-HCT have similar D100 NRM and 5-year PFS/Relapse risk compared to 60-69 years.
Patients ≥70 years had worse OS if relapsing following auto-HCT.
Auto-HCT is feasible and effective in select older DLBCL chemosensitive patients and should not be denied based on chronological age.
Footnotes
Disclosure of conflict of interest
P. Munshi reports: Consultancy: Incyte Corporation. Speaker’s Bureau: Incyte Corporation, Kite.
M. Hamadani reports: Consultancy: Incyte Corporation, ADC Therapeutics, Pharmacyclics, Omeros, Verastem, Genmab, Morphosys, Kite, Novartis, Kadmon. Speaker’s Bureau: Sanofi Genzyme, AstraZeneca, BeiGene, ADC Therapeutics.
P. Shaughnessy reports: Speakers Bureau: Sanofi Genzyme, Kite, BMS. Advisory Board: Sanofi Genzyme, Novartis.
M. Shadman reports: Consulting, Advisory Boards, steering committees, or data safety monitoring committees: Abbvie, Genentech, AstraZeneca, Sound Biologics, Pharmacyclics, Beigene, Bristol Myers Squibb, Morphosys/Incyte, TG Therapeutics, Innate Pharma, Kite Pharma, Adaptive Biotechnologies, Epizyme, Eli Lilly, Adaptimmune, Mustang Bio, Regeneron, Merck and Atara Biotherapeutics . Research Funding: Mustang Bio, Celgene, Bristol Myers Squibb, Pharmacyclics, Gilead, Genentech, AbbVie, TG Therapeutics, Beigene, AstraZeneca, Sunesis, Atara Biotherapeutics, Genmab
F. Locke reports: Consulting or advisory role with ecoR1, Emerging Therapy Solutions Gerson Lehman Group, Allogene, Amgen, Bluebird Bio, BMS/Celgene, Calibr, Iovance, Kite, a Gilead Company, Janssen, Legend Biotech, Novartis, Umoja, Cowen, Cellular Biomedicine Group, GammaDelta Therapeutics, Wugen; research funding from Kite, a Gilead Company, Allogene and Novartis; and patents, royalties, other intellectual property from several patents held by the institution in his name (unlicensed) in the field of cellular immunotherapy.
A. Goodman reports: Consulting: Seattle Genetics and EUSA Pharma
G. Shouse reports: Speaker’s Bureau: Kite; Honorarium: Beigene
FT. Awan reports: Consultancy: Genentech, Astrazeneca, Abbvie, Janssen, Pharmacyclics, Gilead sciences, Kite pharma, Celgene, Karyopharm, MEI Pharma, Verastem, Incyte, Beigene, Johnson and Johnson, Dava Oncology, BMS, Merck, Cardinal Health, ADCT therapeutics, Epizyme.
C. Sauter reports: Consultancy on advisory boards: Juno Therapeutics, Sanofi-Genzyme, Spectrum Pharmaceuticals, Novartis, Genmab, Precision Biosciences, Kite/a Gilead Company, Celgene/BMS, Gamida Cell, Karyopharm Therapeutics and GSK; Research funds: Juno Therapeutics, Celgene/BMS, Bristol-Myers Squibb, Precision Biosciences and Sanofi-Genzyme.
S. Jaglowski reports: Advisory Boards: Kite Therapeutics, Novartis, Juno/BMS, Takeda Inc, CRISPR Therapeutics; Research funding: Kite Therapeutics, Novartis.
A. Herrera reports: Consultancy: BMS, Genentech, Merck, AstraZeneca, Karyopharm, ADC Therapeutics, Takeda, Tubulis, Regeneron, Genmab. Research Funding: BMS, Genentech, Merck, Seattle Genetics, Kite, Gilead Sciences, AstraZeneca, ADC Therapeutics.
Following authors have no conflicts of interest to disclose
KW. Ahn, A. Cashen, MA. Kharfan-Dabaja, J. Zurko, JC. Villasboas Bisneto, G. Meyers
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