ALBERT

Description: Background Measurable residual disease (MRD) is associated with inferior outcomes in patients with acute myeloid leukemia (AML). MRD monitoring enhances risk stratification and may guide therapeutic intervention. Post-induction MRD is frequently cleared with further therapy and the clearance may lead to better outcomes. In contrast, persistent MRD is associated with poor outcomes. At present it is not possible to predict which patients are likely to clear MRD with further therapy. Here we report a simple, objective, widely applicable and quantitative MFC approach using the ratio of blast/PDC to predict persistent MRD and poor outcomes in AML. Patients and Methods A cohort of 136 adult patients with a confirmed diagnosis of AML by WHO criteria who underwent standard induction therapy at a single center between 4/2014 and 9/2017 was initially included. 69 patients achieved complete morphologic remission (36 MRD-neg. and 33 MRD-pos.). MRD status was assessed by MFC using a different from normal (DfN) approach. PDC were quantified as the percent of total WBC by flow cytometry based on low side scatter, moderate CD45, CD303, bright CD123 and HLA-DR expression. Results The proportion of PDC was markedly decreased in patients with AML (≥20% blasts) (N=136) with a median of 0.016% (interquartile range IQR: 0.0019%-0.071%, Figure 1A), more than 10-fold lower than observed in normal controls (median 0.23%, IQR 0.17%-0.34%) (N=20). While there was no difference between MRD-neg. and normal control groups (median 0.31%, IQR: 0.17%-0.49%; vs. 0.28%, IQR: 0.17%-0.34%), MRD-pos. group had significantly reduced PDC proportion compared to the control (median 0.074%, IQR: 0.022%-0.33%, Wilcoxon rank sum, p=0.019). In an attempt to achieve better separation and to eliminate possible effects of hemodilution, the ratio of blast/PDC was calculated by using the proportions of blasts and PDCs out of total WBCs as quantitated by flow cytometry. A cut-off threshold of the blast/PDC ratio of 10 was chosen to separate each group (Figure 1B). Importantly, a ratio cut-off of 10 had a corresponding specificity of 97.4% for predicting MRD positivity status. MRD positivity was significantly associated with inferior overall survival (OS) and relapse-free survival (RFS) in our study cohort (OS HR 4.11 (95% CI: 1.30-13.03), p=0.016; RFS HR 4.20 (95% CI: 1.49-11.82), p=0.007, Figure 1C and D). The 2-year cumulative incidence of relapse in the MRD-neg. group compared to MRD-pos. group was 10% (95% CI: 2-24%) vs. 37% (95% CI: 18-56%, p=0.014). Importantly, blast/PDC ratio ≥10 was also strongly associated with inferior OS and RFS (OS HR 3.12 (95% CI: 1.13-8.60), p= 0.028; RFS HR 4.05 (95% CI: 1.63-10.11), p=0.003, Figure 1E and F), which is similar in magnitude to MRD positivity. Furthermore, MRD-pos. patients with blast/PDC ratio

Description: Introduction: Mutations localized in the tyrosine kinase domain activation loop of FLT3 (FLT3-TKD), representing point mutations in codon D835/I836 and rarely deletions of codon I836, induce constitutive tyrosine phosphorylation and activation of the receptor tyrosine kinase similarly to FLT3 internal tandem duplication (ITD) mutations. However, the prognostic role of FLT3-TKD in AML, particularly in the presence of NPM1 mutations, is not well established. The phase 3 RATIFY trial [NCT00651261; Stone et al. N Engl J Med. 2017] showed that in combination with standard chemotherapy, midostaurin (PKC412) improved survival outcomes across all 3 FLT3 stratification subgroups (ITD high allelic ratio [≥ 0.7], ITD low allelic ratio [〈 0.7], and TKD) vs placebo in patients with newly diagnosed FLT3-mutated AML. Here, we evaluated the prognostic impact of FLT3-TKD and NPM1 mutations in a post hoc analysis from the RATIFY trial. Methods: In RATIFY, newly diagnosed patients with AML 18-60 years old were randomly assigned to receive midostaurin or placebo together with standard induction and consolidation therapy followed by 12 28-day cycles of maintenance therapy with midostaurin or placebo. FLT3-TKD mutation was detected by PCR and capillary electrophoresis at 9 reference laboratories. Patients were categorized as NPM1 mutated (mut) or NPM1 wild-type (WT) using PCR. Efficacy outcomes included complete remission (CR), overall survival (OS), event-free survival (EFS) and disease-free survival (DFS). EFS and DFS analyses were performed considering CR within a 60-day window. P values presented have not been adjusted for multiplicity. Results: Of the total randomized 162 FLT3-TKD patients, 134 with available NPM1 data had consented for exploratory analysis and thus were included in this study (see Table for subgroup distribution). Overall, 47.8% of patients were male, and the median age was 49 years (95% CI, 45.5-51.1 years). The median white blood cell (WBC) count was higher in patients with NPM1-mut than in patients with NPM1-WT (34.1 vs 15.5 × 109/L, P = .0011). CR rates (during the first 60 days) were higher in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT (66% vs 53%); however, this was driven by the higher rate of CR in the midostaurin arm (76% NPM1-mut vs 44% NPM1-WT) rather than the placebo arm (53% NPM1-mut vs 60% NPM1-WT). The overall CR rate (regardless of NPM1 genotype) was 64% for midostaurin and 56% for placebo in FLT3-TKD patients. The prognostic effect of the NPM1 mutation concurrent with FLT3-TKD was seen for all endpoints consistently with hazard ratios (HRs) around 0.50 or lower (Figures 1 and 2 and Table). Overall (regardless of treatment) OS, EFS, and DFS estimates at 3 years were 73% vs 52%, 48% vs 25%, and 74% vs 47%, respectively, in patients with FLT3-TKD/NPM1-mut vs FLT3-TKD/NPM1-WT. Whereas the HRs for midostaurin vs placebo were 0.73 for both OS and EFS, the impact of treatment on outcomes varied between the individual NPM1/TKD subgroups and was not consistently observed when endpoints were censored at stem cell transplant (SCT) (Table). It should be noted that the number of patients in each subgroup was small and therefore the HRs with 95% CIs should be interpreted with caution. Multivariate analyses in these FLT3-TKD patients revealed that NPM1 genotype was an independent prognostic factor for OS, EFS and DFS (2-sided P 〈 .05), whereas study drug, age, sex, WBC at baseline and SCT (no/yes) did not reach this level of significance in the Cox model. Conclusions: This post hoc analysis of the FLT3-TKD patient subset in the RATIFY trial showed the high prognostic value of NPM1 mutational status. Whereas midostaurin showed an overall benefit in the FLT3-TKD patients for OS, EFS, CR and DFS, the impact of treatment on outcome varied between the individual NPM1 subgroups within these FLT3-TKD patients and was not consistently observed.Further analyses using additional endpoints and additional multivariate analyses are planned. Support: U10CA180821, U10CA180882, U10CA180820, U10CA180791, U10CA180888, U10CA180863, (CCSRI) #704970, U24CA196171; ClinicalTrials.gov Identifier: NCT00651261 Disclosures Voso: Celgene: Research Funding, Speakers Bureau. Larson:Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Heuser:Janssen: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; StemLine Therapeutics: Consultancy; Astellas: Research Funding; BergenBio: Research Funding; Karyopharm: Research Funding; Bayer Pharma AG: Consultancy, Research Funding; Tetralogic: Research Funding; Sunesis: Research Funding; Daiichi Sankyo: Research Funding. Wei:Novartis: Honoraria, Other: Advisory committee, Research Funding, Speakers Bureau; Pfizer: Honoraria, Other: Advisory committee; Amgen: Honoraria, Other: Advisory committee, Research Funding; Abbvie: Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Servier: Consultancy, Honoraria, Other: Advisory committee, Research Funding; Celgene: Honoraria, Other: Advisory committee, Research Funding. Brandwein:Lundbeck: Consultancy; Celgene: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Boehringer Ingelheim: Consultancy, Research Funding. de Witte:Novartis: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Honoraria, Research Funding. Medeiros:Celgene: Consultancy, Research Funding; Genentech: Employment. Tallman:Cellerant: Research Funding; Orsenix: Other: Advisory board; BioSight: Other: Advisory board; ADC Therapeutics: Research Funding; AROG: Research Funding; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board. Schlenk:Pfizer: Research Funding, Speakers Bureau. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Cheng:Novartis: Employment. Gathmann:Novartis: Employment. Tiecke:Novartis: Employment. Thiede:AgenDix: Other: Ownership; Novartis: Honoraria, Research Funding. Döhner:AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Celator: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Agios: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Pfizer: Research Funding; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Stone:Otsuka: Consultancy; Argenx: Other: Data and Safety Monitoring Board; Amgen: Consultancy; Agios: Consultancy, Research Funding; Orsenix: Consultancy; Ono: Consultancy; Novartis: Consultancy, Research Funding; Astellas: Consultancy; Arog: Consultancy, Research Funding; Merck: Consultancy; Cornerstone: Consultancy; Fujifilm: Consultancy; Jazz: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee; Pfizer: Consultancy; Sumitomo: Consultancy; AbbVie: Consultancy.

Description: Background: High-dose chemotherapy and autologous hematopoietic cell transplantation (HDT-AHCT) is an established treatment for non-Hodgkin lymphoma (NHL). Incidence of NHL is highest in patients over 60 years of age, however, limited data is available on long-term effects of HDT-AHCT in older patients. This study is conducted to evaluate the late cardiopulmonary effects and overall outcomes of HDT-AHCT in older patients. Methods: This is a single-center, retrospective study examining late cardiopulmonary effects, and overall outcomes of HDT-AHCT in 41 patients age 70 years and older, with NHL, between January 2000 and December 2016. Clinical data and comorbidities were correlated with outcomes. Pre- and post-transplant pulmonary function tests (PFT) and echocardiograms were compared. Overall survival (OS) and progression-free survival (PFS) were analyzed according to age, gender, disease histology, disease stage at diagnosis, number of lines of treatment, Karnofsky Performance Status (KPS), hemoglobin adjusted diffusing capacity of lungs for carbon monoxide (DLCO), left ventricular ejection fraction (LVEF), and hematopoietic cell transplantation comorbidity index (HCT-CI) at the time of HDT-AHCT. Results: A total of 41 patients underwent HDT-AHCT for follicular or diffuse large B-cell lymphoma (FL / DLBCL n=18 44%), mantle cell lymphoma (MCL n=15 37%) and T-cell or other NHL subtypes (n=8 19%). The median age was 72 (range 70-77). Eight (19%), 6 (15%) and 27 (66%) patients had a low (0), intermediate (1-2) and high (≥3) HCT-CI score, respectively, at transplant. All patients except 1, had received anthracycline as part of initial treatment. BEAM and RR-BEAM were the most common conditioning regimens (n=38 93%). Pre-transplant LVEF was within normal range in all patients except 1 (45%). The median (range) pre- and post-transplant LVEF was 63% (45-74%) and 64% (39-71%), respectively. Of the 23 patients who had a post-transplant echocardiogram (median time between the pre- and post-transplant echocardiogram was 423 days), a mild decrease in LVEF was noted in 3. Only 1 patient had a significant decline of 19% in LVEF. Pulmonary artery pressure (PAP) was within normal range pre- and post-transplant in all. The median (range) of pre-transplant DLCO, FEV1 and FVC were 70% (48-125%), 97% (83-141%), and 98% (57-123%), respectively. Of the 10 patients who underwent post-transplant PFT (median time between the pre- and post-transplant PFT was 405 days), DLCO decline of 〉10% was the most common abnormality, and developed in 4 out of 10 patients. In 5 patients DLCO improvement of 〉10% was observed. A greater than 15% improvement in FEV1 and FVC was observed in 5 of 10 and 4 of 10 patients respectively. The median improvements in FVC, FEV1 and DLCO were 4%, 6% and 10%, respectively. With a median follow-up of 58 months (range 5-123) for survivors, PFS and OS at 3 years were 84% (95% CI, 67-92%) and 94% (95% CI, 80-99%), respectively. In a univariate analysis, age, gender, histology, disease stage, number of lines of treatment, DLCO, LVEF, and HCT-CI score did not affect OS or PFS. However, KPS ≥90 was associated with worse OS (p=0.008). The small sample size may have been a contributor to this unexpected finding. Relapse occurred in 11 patients (27%), 8 of whom died. Median time to relapse was 38 months (range 26-100). Secondary malignancies developed in 4 patients (8%) which included acute myeloid leukemia in 2, melanoma in 1, and esophageal cancer in 1, and led to death in 3. Conclusion: In this cohort of elderly patients with NHL who underwent HDT-AHCT, the late declines in cardiopulmonary function were minimal, and none resulted in mortality. Secondary malignancy was the only cause of non-relapse mortality. This can be explained by age being the biggest single risk factor for cancer development in general, in addition to the effects of HDT. We show that the most common cause of long-term mortality after HDT-AHCT continues to be lymphoma recurrence. Our data though limited by small number of patients and its retrospective nature, suggest that age alone is not predictive of post-transplant late effects and outcomes, and therefore should not be used to preclude HDT-AHCT in elderly. While prospective studies with larger number of patients are needed to evaluate long-term effects of HDT-AHCT on different organ functions in older adults, strategies to mitigate risk of relapse remain the most important area to improve outcomes. Disclosures Sauter: Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Novartis: Consultancy; Precision Biosciences: Consultancy; Kite: Consultancy.

Description: Introduction: Acute undifferentiated leukemia (AUL) is a rare type of acute leukemia that shows no evidence of differentiation along any lineage. Clinical, immunophenotypic and genetic data is limited: the largest study to date reported 16 AUL cases but did not use the current WHO classification and included limited genetic data on 5 cases (Ann Hematol 2013 92:747-758). Moreover, it is uncertain if AUL is biologically distinct from acute myeloid leukemia with minimal differentiation (AML MD), which also shows limited myeloid marker expression and has been reported to have a poor prognosis. Methods: A total of 95 cases (36 AUL cases 59 AML MD) were identified from pathology databases of eight academic institutions with available diagnostic flow cytometric data, cytogenetic findings, and clinical data by searching for diagnoses of "AUL" or "AML MD". Diagnosis of AUL required absence of any lineage-defining markers including MPO, CD19 and CD3. Using the WHO classification, diagnosis of AML with MD required expression of at least 2 myeloid markers (CD117, CD13 or CD33), absence of myeloid maturation (CD15) or monocytic markers (CD64, CD11b, lysozyme or non-specific esterase). Next generation sequencing with extensive mutational panel data was available in 78 cases. Outcome analysis for overall survival (OS) and relapse-free survival (RFS) and were performed using Kaplan Meier and log rank test for patients who received induction chemotherapy. Results: Based on cytogenetic abnormalities (N=27) or history of MDS (N=2), according to the 2016 WHO Classification, 28 cases (6 AUL and 22 AML MD) were re-classified as AML with myelodysplasia related changes (AML MRC). The remaining 30 AUL patients presented with similar age, blood counts, bone marrow cellularity, and blast percentage as the 37 AML MD patients (all p 〉 0.05). Comparison of immunophenotype in the two groups showed that AUL blasts had more frequent expression of TdT (p=0.0003) and lacked myeloid markers (CD117, CD13 or CD33 p0.05) were seen between these two groups. The frequency of abnormal karyotype was similar between AUL and AML MD (16/30 [53%] vs 15/37 [41%], respectively). The most common mutations identified in AUL were PHF6 (7/18), SRSF2 (7/18), RUNX1 (7/23), ASXL1 (6/23) and BCOR (5/16). Compared to AML MD, AUL cases were characterized by frequent mutations in PHF6 (7/18 vs 1/23, p=0.013) and SRSF2 (7/18 vs 2/22 p=0.028). Limiting AUL cases to only those with 1 myeloid marker or less also showed similar findings with more frequent mutations in PHF6 (7/16 vs 1/25, p=0.0031), SRSF2 (6/15 vs 3/26 p= 0.018) and trend towards higher BCOR frequency (5/15 vs 2/26, p=0.078) in AUL patients as compared to AML MD. RUNX1 mutation was seen in 7/23 AUL and 8/29 AML MD (p〉0.05). 19/30 AUL patients received induction chemotherapy (AML-type regimen in 18 cases and an ALL-type regimen in 1 case) and 15/30 achieved complete remission. In 10 AUL patients who relapsed, 9 showed identical immunophenotype and one case showed expression of CD13 and CD33. Outcome data in the subset of patients who received induction showed no difference in OS, RFS, or rates of complete remission between AUL and AML MD groups (p〉0.05). The 28 AML MRC cases that were originally classified as AUL or AML MD presented with lower WBC (p=0.026), more frequent abnormal karyotype (27/28) specifically complex karyotype (20/28 p=0.002), frequent TP53 mutations (p=0.0002) when compared to the AUL group. AML MRC patients showed worse overall OS (p=0.029) as compared with AUL patients and a trend toward worse outcome as compared with AML MD (p=0.068). Conclusions: In this largest series to date, AUL group shows distinct characteristics from AML MD, including more frequent PHF6 and SRSF2 mutations and expression of TdT. However, clinical outcome is similar between the two groups in patients treated with induction chemotherapy. Cases reclassified as AML-MRC had shorter survival compared to de novo AUL and trend towards worse outcome when compared to AML MD patients. These results suggest a genetic rationale for the separation of AUL as a distinct entity from AML MD and also support the WHO classification of cases with history of prior MDS and/or MDS-type karyotype findings as AML-MRC. Disclosures Garcia: Celgene: Consultancy.

Description: Introduction: Myeloproliferative Neoplasm (MPN) patients encounter debilitating pain syndromes as a result of their disorder. Opioids are frequently employed in cancer-related pain but have been increasingly recognized for their risk profiles including accidental overdose, addiction and death. With many MPN patients facing near-normal life expectancies, chronicity of opioid use may increase the risk of adverse events. In this survey, we evaluated the prevalence of MPN opioid use, risk factors for negative outcomes and compared the features of this population to MPN patients not receiving opioid therapy. Methods: This study was performed by the MPN Quality of Life Study Group. A survey was designed by a team of MPN investigators experienced with MPN symptomatology. Patients completed the MPN-10, a 10 item survey of MPN symptoms completed on a 0 (absent) to 10 (worst imaginable) scale (Blood. 2011 Jul 14;118(2):401-8). Other surveyed tools included the Opioid Risk Tool (ORT) as well as DSMV criteria for Opioid Use Disorder (OUD). The survey was posted on high-traffic MPN-related webpages focused on patient education and advocacy (MPN Forum, MPN Net, MPN Research Foundation, MPN Voice)for a total of 28 days. Patients currently receiving opioids were compared to patients not receiving opioids and statistical significance was defined as p10 years ago (30.4%). Patients were furthermore of expected mean age (60.7), primarily female (75.0%) and from the United States (66.6%). Few patients had a history of transformation to acute leukemia (0.5%), severe bleeding (12.3%) or blood clot (26.5%). Mean individual symptom scores and prevalences were 3.0 and 65.6% for abdominal discomfort and 3.3 and 59.4% for bone pain, respectively, indicating a low to moderate symptom burden. Patients Receiving Opioid Therapy Patients on opioid therapy (n=69) displayed a number of high risk features for adverse outcomes including a personal history of substance abuse (20.2%), respiratory disease (33%) and mental health disorders (60.1%). By DSMV criteria, 5.9% of opioid patients scored 'mild' and 2.9% scored 'moderate' for OUD (total 8.8%), consistent with prevalence in the general population. Approximately 24.6% of opioid-using patients scored moderate to high risk on the ORT but despite this, did not appear more likely to meet criteria for OUD (p=0.81). Palliative care and pain management were involved in only 34.3% of patients and side effects of opioids were discussed in only 70.1% of all cases. Opioid vs. Non-Opioid Patients Compared to patients not receiving opioid therapy, patients currently on opioid treatment were more likely to describe more frequent and/or more severe abdominal discomfort (88.4% vs. 61.0%, p

Description: Introduction: Induction therapy consisting of dasatinib (DAS) and corticosteroids (CS) yields high rates of morphologic complete response (CR) in adults w/ newly diagnosed Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL). However, only ~20% of patients (pts) achieve BCR-ABL1 response depth of

Description: Background: Chimeric antigen receptor-modified (CAR) T cells have the potential to provide durable clinical benefit in patients with several relapsed or refractory hematologic malignancies. We aimed to characterize institutional resources utilized (other than T cell collection and CAR T cell manufacturing and infusion) around the time of CAR T cell administration. Methods: Adult patients treated on selected investigator-initiated clinical trials of CAR T cell therapy at Memorial Sloan Kettering Cancer Center were identified from the institutional database. Utilization data was collected from the start of admission for CAR T cell infusion through the end of the initial admission for infusion or through 30 days following initial CAR T cell infusion, whichever was longer. The data were sorted by disease type and into the categories of encounters, lab work, radiology, medications, and other diagnostic testing. Descriptive statistics were used to analyze the data. Results: We identified 106 patients on 4 clinical trials receiving inpatient CAR T cell infusions between 6/2007 to 4/2018, with 56 patients (53%) having B-cell acute lymphoblastic leukemia (ALL), 37 (35%) chronic lymphocytic leukemia (CLL) or B-cell non-Hodgkin lymphoma (NHL), and 13 (12%) multiple myeloma (MM). The median age was 53 years (range 22-77), 45 years (range 22-74), 64 years (range 35-77), and 58 years (range 43-68) for the total population, and the ALL, CLL/NHL, and MM groups, respectively, and 65%, 75%, 41%, and 31% were male, respectively. The median length of stay for the admission during which CAR T cells was given was 23 days (range 4 -133), with ALL patients admitted longer (Figure 1). Intensive care unit (ICU) days were limited with a range of 0-43 days, though 43 (41%) spent at least one day in the ICU. Of note, some protocols required infusion of the CAR T cells to be in the ICU. ICU admissions for ALL patients were than for other histologies longer (median 9 days vs 4 days). Outpatient clinic visits through day 30 post CAR T cell infusion occurred in 57 (53%) patients, with more of these in the CLL/NHL patients (median of 2 visits, range 1-4). As expected, laboratory and radiology studies accounted for a large portion of resource utilization with a total of 62,953 laboratory panels and 1,190 radiology studies done during the study time frame. Fourteen percent of the labs were complete blood counts, basic or comprehensive metabolic panels, or liver function tests. For the total population, ALL, CLL/NHL, MM, there were a median of 63.5 (range 13-368), 91.5 (21-368), 47 (13-167), and 51 (range 38-113) of these panels done per patient during the time frame, respectively. Blood cultures accounted for 1.3% of the total laboratory tests. Among the radiology studies, 25% were CT scans, 10% MRIs, 7% PET scans, 5% ultrasounds, and 53% x-rays, with differences in patterns of use by disease type (Figure 2). Cardiac testing (echocardiographs & electrocardiograms) was done in 104 (98%, total 634 tests). Electroencephalogram was performed in 18 patients (17%, total 18 tests). There were 173 bone marrow aspirations/biopsies in 88 patients (83%) and 71 lumbar punctures in 38 patients (36%), many of which were potentially done for disease assessment rather than toxicity management. Finally, 41,331 units of medications were given in this time frame, of which chemotherapy was 328 units (0.8%). The median medication units per patient was 255 (range 35-2091), 423 (range 35-2091), 200 (range 41-1190), and 207 (range 90-666) for the total population, and the ALL, CLL/NHL, and MM patients groups, respectively. Thirty-two doses of tocilizumab were given to 25 patients (24%), with ALL patients receiving 23 of those doses (72%). Conclusion: While providing potential clinical benefit, CAR T cell therapy utilizes resources across the therapeutic spectrum, and increasing use of this therapeutic modality can create challenges in institutional resource capacity. Identifying these resources will allow for better care delivery and allocation of funds. Further refinement of CAR T cell products and improvements in CAR T cell-related toxicity management may permit safer delivery of this therapy and reduce costs per patient. Additional analysis of resource utilization among patients treated with commercial CAR T cell products, as well as comparison with alternative therapies and cost-effectiveness analysis, is warranted. Disclosures Shah: Amgen: Research Funding; Janssen: Research Funding. Park:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Consultancy; Shire: Consultancy; AstraZeneca: Consultancy; Pfizer: Consultancy; Novartis: Consultancy; Kite Pharma: Consultancy; Juno Therapeutics: Consultancy, Research Funding. Sauter:Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding; Spectrum Pharmaceuticals: Consultancy; Novartis: Consultancy; Precision Biosciences: Consultancy; Kite: Consultancy. Palomba:Pharmacyclics: Consultancy; Celgene: Consultancy. Younes:Genentech: Research Funding; BMS: Honoraria, Research Funding; Pharmacyclics: Research Funding; Abbvie: Honoraria; Merck: Honoraria; Takeda: Honoraria; J&J: Research Funding; Incyte: Honoraria; Janssen: Honoraria, Research Funding; Celgene: Honoraria; Roche: Honoraria, Research Funding; Curis: Research Funding; Astra Zeneca: Research Funding; Novartis: Research Funding; Bayer: Honoraria; Seattle Genetics: Honoraria; Sanofi: Honoraria. Geyer:Dava Oncology: Honoraria. Smith:Celgene: Consultancy, Patents & Royalties: CAR T cell therapies for MM, Research Funding. Mailankody:Physician Education Resource: Honoraria; Janssen: Research Funding; Juno: Research Funding; Takeda: Research Funding. Perales:Incyte: Membership on an entity's Board of Directors or advisory committees, Other: Personal fees and Clinical trial support; Merck: Other: Personal fees; Takeda: Other: Personal fees; Abbvie: Other: Personal fees; Novartis: Other: Personal fees. Brentjens:Juno Therapeutics, a Celgene Company: Consultancy, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding. Bach:Vizient: Other: Personal Fees; Hematology Oncology Pharmacy Assoc: Other: Personal Fees; Excellus Health Plan: Other: Personal Fees; Gilead: Other: Personal Fees; Foundation Medicine: Other: Personal Fees; JMP Securities: Other: Personal Fees; Janssen: Other: Personal Fees; Grail: Other: Personal Fees; American Society for Hospital Pharmacy: Other: Personal Fees; Kaiser Permanente: Research Funding; Third Rock Ventures: Other: Personal Fees; WebMD: Other: Personal Fees; Anthem: Other: Personal Fees; Goldman Sachs: Other: Personal Fees; Novartis: Other: Personal Fees; Defined Health: Other: Personal Fees.