Chanan‐Khan, Asher

Abstract Background: Multiple myeloma (MM) is characterized by the invasion of malignant plasma cells into the bone marrow. While first line treatment options result in significant clinical benefit to patients, spatiotemporal clonal evolution results in disease relapse and mortality. Advances in genomics have armed clinicians with unprecedented insight into the molecular architecture of MM cells, however, the clinical benefit derived by genomics-guided intervention has been limited. We present a novel computational biology modelling (CBM) tool, which takes into account the combined effect of individual mutations, gene copy number abnormalities and large scale chromosomal changes in order to predict the salient molecular pathways utilized by the MM cell for survival. By reverse-engineering MM cell architecture in silico, the CBM tool is able to predict drug response and resistance mechanisms. Thus, our aim was to determine the accuracy of the CBM tool in predicting treatment response of relapsed/refractory MM patients for future management of their disease, in a more individualized manner. Methods: Cytogenetics and somatic mutations (by targeted NGS) for 15 MM patients were input into the CBM model to predict responses to different therapeutic combinations. All patients were relapsed to prior treatment. CBM uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated disease pathways. We simulated the specific combinations of the drugs per patient and measured the quantitative drug effect on a composite MM disease inhibition score (i.e., cell proliferation, viability, apoptosis and paraproteins). The actual clinical outcome of the treatments was compared with predicted outcomes. Results: Fifteen patients were analysed using CBM for prediction of treatment response after NGS was performed. 13/15 were clinically evaluable, of which 1 was a responder and 12 were non-responder. 6/13 patients were treated on clinical trial and 7/13 were on drug combinations per physician decision. CBM correctly predicted 1 responder and 11 non-responder with a PPV of 50%, NPV 100%, specificity 91.67%, sensitivity 100%. The accuracy of CBM prediction was 92.30%. CBM also predicted the response of prior drug therapies for its non-response at relapse. For prior drug treatment options, 14 patients were evaluable. All the 14 patients were clinically non-responders and CBM correctly predicted for 13 patients with NPV 100%, Specificity 92.85% and overall accuracy of 92.85%. The majority of patients did not respond to therapies recommended at relapse. As an example, the operative molecular pathways from 2 patients who did not respond to combination treatment, either pre-NGS or post-NGS profiling, are shown in Fig. 1 and Table 1. CBM identified amplification (AMP) of chromosome (chr) 1 (WNT3A, IL6R, CKS1B, MCL1, PIK3C2B, USF1), chr 3 (HES1, PIK3CA, CTNNB1, WNT7A, FANCD2), chr 5 (IL6ST, IRF1, GLRX, SKP2), chr 7 (CDK5, EZH2, IL6, CAV1, ABCB1), chr 9 (NOTCH1, HSPA5, FANCC, FANCG), chr 15 (DLL4, FANCI, ALDH1A2), chr 19 (ERCC1, ERCC2, USF2); deletion(DEL) of chr 13 (CUL4A) , chr 16 (AXIN1, CDH1) and TP53 mutation in different combinations, which confer resistance to therapies at relapse. Conclusions: The CBM technology represents a potential means to identify therapeutic options for MM patients based on the patients individual tumor-genome profile and which can also be deployed for uncovering drug resistance mechanisms. This tool may aid clinicians in decision making for recommending the most appropriate therapy based on standard of care agents or clinical trials; thus improving patient outcomes and reducing unnecessary costs or drug-related toxicities. Disclosures Singh: Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Kumar:Cellworks Research India Private Limited: Employment. Kumari:Cellworks Research India Private Limited: Employment. Tyagi:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment. Ailawadhi:Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

Abstract Background: Therapeutic advancements have led to significant improvement in outcomes for MM patients. Revised diagnostic criteria from International Myeloma Working Group focus on initiating treatment before the onset of end-organ damage. Thus, timeliness of initial therapy can significantly improve patient morbidity and outcomes. Such an analysis has not been reported for MM. Methods: We analyzed patients diagnosed with MM between 2004-2015 from the National Cancer Database (NCDB). Patients who received systemic treatment any time within the first year of diagnosis were included; those treated later than one year were considered possibly initially diagnosed with smoldering myeloma and hence, excluded. Time to initial treatment was divided into centiles with the 4 centiles analyzed being 0-7 days, 8-18 days, 19-37 days and >37 days. We performed univariate and multivariate analyses to compare sociodemographic and clinical factors influencing patient distribution across these timeliness categories and trends over time. Results: A total of 53,665 patients were included with 15,282 in 0-7 days, 12,462 in 8-18 days, 12,723 in 19-37 days and 13,198 in the >37 days treatment categories. Distribution across these centiles over time is shown in Figure. Univariate analyses showed a significant difference in distribution across the timeliness categories by year of diagnosis, patient age, gender, race/ethnicity, education level, insurance type, comorbidity score, treatment facility type, geographical location and distance to treating facility (all p<0.001) but no effect of income level. Multivariate analysis showed that there was a significantly higher likelihood of being in 4th centile (>37 days to treatment) for women (p<0.001), African Americans (p<0.001) or Hispanics (p=0.03; reference: Whites) or diagnosed in more recent years (p<0.001). Patients were less likely to be in the 4th centile if they were ≥80 years (HR 0.89, 95% CI 0.81-0.98, p=0.02), had >0 Charlson comorbidity score (p<0.001), were uninsured (p=0.02) or had Medicaid (p=0.03) as compared to having private insurance, were in non-community treatment facilities or geographical location other than Northeast (p<0.001). Patient education, income level or distance from treating facility was no longer significant. Conclusions: Several factors were found to affect timeliness of treatment in MM. We noted relatively faster time to initial treatment in elderly, uninsured or those who were treated in academic/comprehensive cancer programs but a delay in treatment for women and racial/ethnic minorities among other factors. These factors need to be addressed for equitable access and treatment practices and to realize improved outcomes for all. Figure. Figure. Disclosures Ailawadhi: Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Pharmacyclics: Research Funding.

Abstract Introduction: The CD19 antigen is an attractive therapeutic target as it is highly expressed in chronic lymphocytic leukemia (CLL). CD19 is not down-regulated in patients (pts) pretreated with CD20-targeting agents and has a signaling function that promotes the malignant phenotype. In preclinical studies, the Fc-enhanced, humanized, CD19 antibody MOR208 showed synergistic potential in combination with venetoclax (VEN, a small molecule selective inhibitor of the apoptosis regulator BCL-2). Pts with relapsed or refractory (R/R) CLL who failed treatment with the Bruton's tyrosine kinase inhibitor (BTKi) ibrutinib have poor prognosis. A previous phase I study showed that MOR208 was well tolerated, with encouraging single-agent activity in pts with R/R CLL. This ongoing phase II study was designed to assess the safety and preliminary efficacy of MOR208 in combination with idelalisib (Cohort A) or VEN (Cohort B) in pts with R/R CLL previously treated with a BTKi. Results of Cohort A were previously published at EHA 2018 (Poster PF350). Here we report the initial safety and efficacy results for Cohort B. Methods: Adult pts with R/R CLL without transformation or Richter's syndrome, who progressed on BTKi therapy or were intolerant to a BTKi during their last prior therapy, were eligible if they had ECOG performance status 0-2 and adequate organ function. In Cohort B, pts were treated until progression or for up to 24 cycles (C; 28 days (D)/C). MOR208 was administered intravenously at 12 mg/kg body weight, starting from C1D1, weekly during C1-3 (with an equivalent loading dose on D4 of C1), every other week in C4-6, and monthly in C7-24. Oral VEN was administered daily starting from C1D8 on a weekly ramp up dosing schedule, starting at 20 mg on C1D8, increasing to 50 mg on C1D15, 100 mg C1D22, 200 mg C2D1 and reaching the full daily dose of 400 mg from C2D8 onwards. Primary endpoint is the incidence and severity of adverse events (AEs); secondary endpoints include overall response rate (ORR) as per investigator assessment according to IWCLL 2008 guidelines. Results: We report preliminary results of Cohort B with a data cutoff date of June 18, 2018 and a median observation time of 4.6 months. Recruitment in Cohort B was completed with 13 pts who received at least one dose of MOR208. Eleven pts started combination treatment with VEN; 10 pts completed at least 5 weeks of combination treatment, reaching the full daily dose of VEN. Baseline characteristics are shown in Table 1. All pts had received ibrutinib therapy and 1 pt had subsequent acalabrutinib treatment. The median number of prior treatment lines, including BTKi therapy in all 13 pts, was 3 (range 1-4). Table 2 summarizes treatment-emergent (TE)AEs. The most common hematological TEAE was neutropenia (38%). Eleven TE serious (S)AEs were reported in 9 pts (69%); all resolved. One grade 3 SAE, tumor lysis syndrome, occurred at ramp up to 50 mg VEN. The pt recovered after treatment and continued VEN 50 mg the day after event onset. Three serious adverse reactions (2 pts with infusion-related reactions, 1 pt with bone pain with pyrexia) were reported in total. Two pts (15%) permanently discontinued study treatment due to an infusion-related reaction arising during MOR208 monotherapy (i.e. before C1D8). One pt (8%) discontinued study participation due to withdrawal of informed consent, when on a dose of 50 mg VEN. The 3 discontinued pts did not undergo a response assessment. Treatment of 10 pts is ongoing and seven pts had at least 1 post-baseline assessment of tumor response on C4D1; all (7/7) had a partial response (PR) based on local investigator assessment. Conclusions: The novel combination treatment of MOR208 with VEN showed generally acceptable safety and tolerability as well as encouraging antitumor activity in pts with R/R CLL who discontinued prior treatment with a BTK inhibitor. Disclosures Staber: Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: 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; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda-Millenium: Honoraria, Membership on an entity's Board of Directors or advisory committees; CTI: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees. Munir:Alexion: Honoraria; Novartis: Honoraria; Gilead: Honoraria; Janssen: Honoraria; Abbvie: Honoraria; MorphoSys: Membership on an entity's Board of Directors or advisory committees. Schetelig:Roche: Honoraria; Sanofi: Consultancy, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Abbvie: Honoraria; Janssen: Consultancy, Honoraria. Middeke:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees. Dirnberger-Hertweck:MorphoSys: Employment. Kelemen:MorphoSys: Employment. Weirather:MorphoSys: Employment. Parikh:MorphoSys: Research Funding; Gilead: Honoraria; Janssen: Research Funding; Pharmacyclics: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding. Stilgenbauer:Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: travel support, Research Funding; Janssen: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; Genetech: Consultancy, Honoraria, Other: travel support, Research Funding; Novartis: Consultancy, Honoraria, Other: travel support, Research Funding; Mundipharma: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Roche: Consultancy, Honoraria, Other: travel support, Research Funding. Wendtner:Abbvie: Consultancy, Honoraria, Other: travel support, Research Funding; Genetech: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: travel support, Research Funding; Janssen: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Other: travel support, Research Funding; Mundipharma: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding.

Abstract Introduction: Several prognostic models for overall survival (OS) in chronic lymphocytic leukemia (CLL) have been developed, but none were derived for patients (pts) with relapsed or refractory (R/R) CLL treated in the era of novel agents. We used a comprehensive approach to derive and validate a novel risk model for OS in 2,475 pts with R/R CLL who received therapy in randomized phase 3 trials evaluating ibrutinib (IBR), idelalisib (IDELA), and venetoclax (VEN) vs control arms, or the Mayo Clinic CLL Database (MCCD). Methods: In collaboration with Janssen, Gilead, Pharmacyclics, and Genentech/Roche, the analysis included 2,475 pts from 6 multicenter randomized phase 3 trials or the MCCD. Trials included were: IBR plus bendamustine-rituximab (BR) vs placebo plus BR (HELIOS: NCT01611090), IBR vs ofatumumab (RESONATE: NCT01578707), IDELA plus BR vs placebo plus BR (Study 115: NCT01569295); IDELA plus rituximab vs placebo plus rituximab (Study 116: NCT01539512); IDELA plus ofatumumab vs ofatumumab (Study 119: NCT01659021); VEN plus rituximab vs BR (MURANO: NCT02005471). All pts had R/R CLL and required treatment by iwCLL criteria. The model-building dataset (n=969) included pts from HELIOS and RESONATE, and was randomly assigned to the IBR/chemoimmunotherapy (CIT) training dataset (n=727) and IBR/CIT internal-validation dataset(n=242). Three independent external validation datasets included IDELA/CIT (n=897), VEN/CIT (n=389), and MCCD (n=220). We applied univariate and multivariate analyses (MVA) to 28 candidate clinical/laboratory and genetic prognostic factors to derive the risk model in the training dataset. The primary endpoint was OS. We assessed the need for separate models for targeted agents by interactions with treatment in univariate analyses. We proceeded to develop a single model for all pts with R/R CLL, as only one candidate factor (del(13q), interaction p value <0.1) demonstrated a marginal differential effect. We evaluated cutoffs for dichotomized covariates and for definition of risk groups after the final factors were selected. We fit a Cox regression on the training and internal/external validation datasets using the risk categories as the covariate to test the difference among the groups, and calculated the C-statistic as a measure of discrimination. Results: Of 11 selected factors with a significant univariate effect on OS (p<0.1), 6 were independently prognostic in the MVA of OS (p<0.05): Baseline β2-microglobubulin (B2M), lactate dehydrogenase (LDH), hemoglobin (HGB), IGHV mutational status, number of prior therapies, and time from initiation of last therapy. We excluded number of prior therapies from the model, reasoning that its optimal cutoff might change with advances in CLL therapies. IGHV did not remain significant (p=0.0592) in MVA of 5 remaining prognostic factors. Notably, del(17p) was not independently prognostic for OS. The final risk model consisted of 4 prognostic factors: B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months. Because hazard ratios for each factor were similar (range, 0.55-0.68) with overlapping confidence intervals, 1 point was assigned to each factor. The resulting score separated pts into low (score 0-1), intermediate (score 2-3), and high risk (score 4) groups. Our risk model was prognostic for OS in the IBR/CIT training dataset (C-statistic 0.74 [95% CI 0.60-0.85]; log-rank p<0.0001) and was validated in the IBR/CIT internal validation (C-statistic 0.79 [95% CI 0.56-0.97]; log-rank p<0.0001), as well as in all 3 external validations: IDELA/CIT dataset (CS=0.71, 95% CI 0.59-0.81; log-rank p<0.001); VEN/CIT dataset (CS=0.76, 95% CI 0.66-0.85; log-rank p=0.01); MCCD (CS=0.61, 95% CI 0.56-0.66; log-rank p<0.001). Conclusions: We present the first validated risk model for OS in R/R CLL in the era of targeted therapies. Our model consists of 4 readily available factors (B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months), identifies 3 prognostic groups with significantly different OS, and has been validated for pts treated with all FDA approved targeted therapies: IBR, IDELA, and VEN. This identifies a well-defined cohort of pts with R/R disease with an unmet clinical need who are suitable for prospective trials targeting these pts. An exploratory analysis regarding prediction of MRD is ongoing. Figure. Figure. Disclosures Darif: Jannsen: Employment. Londhe:Jannsen: Employment. Xing:Gilead Sciences, Inc.: Employment. Mun:Genentech: Employment, Equity Ownership. Kay:Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Shanafelt:Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Abbvie: Research Funding; Celgene: Research Funding. Furman:Loxo Oncology: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy; Verastem: Consultancy; Gilead: Consultancy; Incyte: Consultancy, Other: DSMB; Acerta: Consultancy, Research Funding; Genentech: Consultancy; Janssen: Consultancy; AbbVie: Consultancy. Hillmen:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Alexion Pharmaceuticals, Inc: Consultancy, Honoraria; Novartis: Research Funding; Gilead Sciences, Inc.: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees. Sharman:Acerta: Consultancy, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Research Funding. Seymour:AbbVie: Consultancy, Honoraria, Research Funding; Celgene: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding. Jones:Celgene: Employment, Equity Ownership. Ferrante:Jannsen: Employment. Dreiling:Gilead: Employment. Mobasher:F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC; Genentech Inc: Employment. Stark:Genentech: Employment. Reddy:Actinium Pharmaceuticals: Employment, Equity Ownership; Pharmacyclics: Employment. Howes:Janssen: Employment. James:Pharmacyclics: Employment. Bhargava:Gilead: Employment. Zelenetz:Novartis/Sandoz: Consultancy; Abbvie: Research Funding; Celgene: Consultancy; Amgen: Consultancy; Gilead: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech/Roche: Consultancy, Research Funding.

Abstract INTRODUCTION: Significant burden of pain syndromes are reported in patients with hematological malignancies undergoing HSCT mostly due to underlying disease and associated treatments. Opioid analgesics and benzodiazepines are routinely used for symptomatic management in this patient population. The use of narcotic analgesics and benzodiazepines in non-transplant hospitalized patients has been shown to adversely affect health related outcomes such as length-of-stay (LOS), falls and other complications. However, there is a significant knowledge gap regarding the patterns of opioid and benzodiazepine use and their impact on health outcomes in HSCT patients. METHODS: We identified 275 patients from the year 2015-2018 who underwent HSCT (allogeneic and autologous transplants) at our center for a variety of hematological malignancies. Opioid exposure was defined in three groups of patients 1) Opioid naïve: those did not report prior use of opioid at admission and who were not prescribed opioid during hospitalization, 2) Previous Opioid users: those who reported active use of opioid at admission and continued during hospitalization 3) New Opioid users: Patients who did not report opioid use at admission but were prescribed opioid during hospitalization. Multivariable analysis was performed to identify differences in opioid status, opioid use, benzodiazepine use, disease diagnosis, Karnofsky score, gender, age, race, and marital status with associated complications (Poisson regression), emergency department visits (Logistic Regression) and length of stay (Ordinal Logistic Regression) Figure 1 and Figure 2. RESULTS: The median age of patients was 59 (range: 25-74 ) years with slight male predominance (57%). Patients undergoing autologous transplants for multiple myeloma (MM) comprised 48% of the population. The majority (72 %) were exposed to opioid during hospitalization. Ninety two percent of the opioid naïve population (28% of the total population) underwent autologous transplant. Conversely, 36% of patients undergoing autologous transplants never received opiates during hospitalization as compared to 7% of those who received an allogeneic transplant. Median morphine milligram equivalent daily dose was 3.1 mg. Median diazepam equivalent daily dosage in patients that were opiate exposed was 2.07 milligram. Of the total transplant population, 55% received benzodiazepine concurrently with opiates during hospitalization. 76 % of the population was exposed to both opioid and benzodiazepine. Twenty five percent of those who were exposed to opioid did not receive benzodiazepines. Sixty four percent of the MM patients were exposed to opioid of which majority (59%) were previous opioid users. Of the non-MM patients undergoing HSCT, 80% were exposed to opioid of which 36% were previous opioid users and 64% were new users. A wide range of complications from neutropenic fever to death, were seen in 89% of all patients (opioid users and non-users) but all the falls occurred in patients who were on opioid medications. Autologous transplant recipients had higher odds of having a greater number of complications compared to Allogeneic transplant patients (OR 1.25, 95% CI: 1.01 - 1.55, p=0.04), as well as a reduced odds of having a medium or high length of stay (OR 0.03, 95% CI: 0.02 - 0.07). Of the opioid naïve patients, 6% presented to the ED within 30 days of discharge versus 15% of those that were exposed to opiates during hospitalization. Benzodiazepine use at admission for HSCT was associated with greater odd of presenting to ED within 30 days of discharge (OR 3.94, 95% CI: 1.55-10.04) and this was more significant in patients with MM (OR 4.08, 95% CI: 1.01-16.44). Finally, we also saw a trend towards longer stay in patients who were exposed to opioids as compared to opioid naïve (40% vs. 17%). CONCLUSION: Our study, albeit limited due to its retrospective design, is among the first to report the patterns of use and the impact of opioids and benzodiazepines in patients undergoing HSCT. Our results indicate that the use of these medications is frequent in this population and as in the non-transplant hospitalized patients and is associated with more emergency room visits post discharge, along with other potentially adverse outcomes. Disclosures Kharfan-Dabaja: Incyte Corp: Speakers Bureau; Seattle Genetics: Speakers Bureau; Alexion Pharmaceuticals: Speakers Bureau. Ailawadhi:Amgen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy; Janssen: Consultancy.

Abstract INTRODUCTION: Treatment of chronic lymphocytic leukemia (CLL) has expanded significantly with the approval of multiple small molecule inhibitors. This is of great significance for patients with adverse cytogenetic features who tend to respond poorly to standard chemo-immunotherapy (CIT). While single agent ibrutinib and venetoclax (V) have shown high rates of overall response, complete remission and minimal residual disease (MRD) eradication rates remain low. This argues for further testing and development of various combination strategies. The MURANO trial compared venetoclax and rituximab (VR) versus bendamustine and rituximab (BR) in patients with relapsed/refractory CLL reporting clear superiority of VR over BR. MRD rates in the bone marrow were reported to be 27.3% for VR versus 1.5% for BR. Given much higher rates of MRD eradication with combination of small molecule inhibitors and monoclonal antibodies (mAb) compared to standard CIT, we performed a comparative investigation into the direct and immune-mediated cytolytic effects of VR versus V + Obinutuzumab (O, type II anti-CD20 mAb) in primary CLL cells and B-lymphoid cell lines. METHODS: CD19+ B-cells were isolated from PBMCs of CLL patients (N=3). For all experiments using primary CLL cells, concentration of VR and VO was 3nM (V) and 10ug /ml (R, O), respectively. For cell lines, VR and VO was used at 5uM (V) and 10ug /ml (R, O), respectively. Apoptosis was determined by annexin-V/PI staining followed by flow cytometry. Antibody-dependent cell-mediated cytotoxicity (ADCC) induced by VR and VO was assessed in Calcein AM labeled CLL cells or cell lines co-cultured with healthy donor PBMCs (E:T ratio, 40:1); complement-dependent cytotoxicity (CDC) was measured using 10% serum from a healthy human donor. RESULTS: We assessed the ability of V+/-O or V+/-R to induce apoptotic cell death in the CD20+ BCWM.1 cell line (Waldenström's macroglobulinemia [WM] phenotype) and the MEC-1 cell line (B-PLL phenotype); with CD20- RPCI-WM1 (WM cells, negative control). Notably, Bcl-2 protein is expressed in all the aforementioned cell lines. We observed that single agent V, O and R induced ~30%, 61% and 13.64% annexin V/PI positivity in BCWM.1 cells, respectively. However, a significant degree of cell death was noted in VO-treated cells (~74%) compared to VR-treated cells (~40%) (p<0.01). Next, we examined for apoptosis in MEC1 cells and noted a similar trend; where the VO combination induced markedly more cell death (~71%) than VR (~57%). Contrastingly, in RPCI-WM1 cells neither single agent O or R could elicit >12% annexin V/PI positivity and where the addition of V increased apoptosis by only 3 - 4%. We also examined the apoptotic potential of VO or VR in tumor cells from low, intermediate and high-risk CLL patients. In low and intermediate-risk CLL cells from low and intermediate-risk patients, V alone induced ~30% cell death, which increased significantly with the addition of O (VO) to between 48 - 52%. Contrastingly, the combination of VR did not induce more than 29 - 32% apoptosis. In CLL cells from high-risk patient, we noted that exposure to single agent V induced ~ 28% cell death and in VO-treated cells, this number increased to 47%. We also examined for ADCC and CDC in the same cell lines and primary CLL cells. Despite considerable variability, single agent O and VO treatment of tumor cells resulted in greater ADCC than VR treatment. By contrast, in single agent R or VR-treated cells, more CDC was observed. CONCLUSION: Our preliminary investigation in VR- and VO-treated cell lines and primary CLL cells suggests the VO combination may be superior to VR in induction of direct tumor cell death. Mechanistic experiments underway will provide further insight and can aid in design of future VO-based clinical studies in CLL. Disclosures Ailawadhi: Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Amgen: Consultancy.

Abstract Background: DLBCL is the most common adult NHL and despite significant advancements, outcomes in ethnic minorities remain suboptimal. Factors responsible for these disparities in ethnic minorities, especially variability in clinical and pathological features with evaluation of patient-level data have not been studied. Methods: A multi-institutional database of DLBCL patients seen at Mayo Clinic in Florida, University of Miami and University of Southern California between 1996-2016 was developed. Patient demographics, clinical disease characteristics and details of DLBCL immunophenotype [CD10, MUM1, BCL6 (Han's classification), Ki 67, MYC, BCL2) were reviewed. Comparisons between Hispanic and Non-Hispanic patients were made by Chi-square, Fischer's exact and Signed rank tests, where applicable. Patients with missing data on a certain feature were not included in the statistical analysis of that specific characteristic. Results: A total of 966 DLBCL patients with 69 Hispanics and 752 non-Hispanics were identified. These included 52% males (N=36) and 48% females (N=33) in Hispanics versus 58% males (N=436) and 42% females (N=316) in Non-Hispanics (p=0.35). Median age at diagnosis was significantly lower at 61 years (range 27-89) in Hispanics versus 66 in non-Hispanics (p=0.014). Extranodal disease was seen significantly more commonly in Hispanics (74%) than in non-Hispanics (60%) (p=0.037). There was no significant difference in disease stage at presentation between the two cohorts (p=0.189) although the proportion of patients with stage III and IV disease was higher among Hispanics (80.4%) as compared to non-Hispanics (68.5%). Similarly there was no significant difference in presence of primary CNS DLBCL at diagnosis between the two groups (p=0.74). GCB phenotype per the Hans' classification was seen in 59% (N=29) in both, Hispanics and Non-Hispanics (N=241) (p=0.99). Similarly, the median ki67 index of 80% was seen in both cohorts (p=0.48). MYC was positive in 59% in Hispanics versus only 37.5% in non-Hispanics (p=0.024). BCL2 expression by itself and also combined BCL2 and MYC double expression were not significantly different between the two groups (p=0.58 and p=0.11, respectively). Median overall survival (OS) was 22.5 months in Hispanics compared 54.9 months in Non-Hispanics (p<0.0001) (Figure 1). Conclusion: Survival outcome disparities in racial and ethnic minorities have been previously reported from population-based analyses. Lack of patient-level clinical data makes these analyses hypothesis generating, but not conclusive. We confirmed some prior findings including younger age at diagnosis for Hispanics with DLBCL. We also reported greater incidence of extranodal as well as stage III or IV disease at the time of presentation among Hispanics which may contribute to poor outcomes in this population. From DLBCL pathology standpoint, we found increased expression of MYC among Hispanics but no other significant immunohistochemical differences including double expression or non-GCB phenotype. The inferior OS despite uniform treatment practices at large Cancer Centers suggest multifactorial influences on patient outcomes which may at least in part include some of the differences we report here. Disclosures Ailawadhi: Pharmacyclics: Research Funding; Janssen: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy.

Abstract Background Outcomes for patients with chronic myeloid leukemia (CML) have improved in recent years. Nonetheless, survival disparities persist between various patient subgroups. There have been limited reports of ethnic variations in CML outcomes, with limited data on ethnic minorities (Hispanics and Asians), who are the fastest growing ethnic subgroups in the Unites States. We undertook a large Surveillance Epidemiology and End Results (SEER) based analysis to describe outcome disparities in different subgroups of CML patients, with a specific focus on various ethnicities. Methods SEER 17 Registry data (1973-2010) was utilized. Adult (>18 years) patients with confirmed diagnosis of CML were eligible. To avoid bias of under representation by ethnic minorities, analysis was restricted to patients with a diagnosis date of 1992 or later (SEER expansion). Cases that received a diagnosis at death certificate/autopsy, no follow-up records, or lacking age at diagnosis, sex, or race/ethnicity documentation were excluded. Cox proportional hazards models, adjusted for confounding variables, were used to evaluate association between patient characteristics and overall survival (OS). All statistical tests were two-sided with a significance level of 0.05, utilizing the SAS software (v9.2). Results The final analysis included 10,356 CML patients (5,943 males; 57.4%, 4,413 females; 42.6%). Age group cohorts included: 18-44 years (2,592; 25%), 45-54 years (1,706; 16.5%), 55-64 years (1,817; 17.6%), 65-74 years (1,876; 18.1%), and ≥75 years (2,365; 22.8%). Patients were stratified by race/ethnicity: White (7,292; 70.4%), African-American (AA) (1,143; 11%), Hispanic (1,163; 11.2%), Asian (697; 6.7%), and Native American (61; 0.6%). For survival analysis, Native Americans were excluded due to their small numbers. Patients were also stratified based on year of diagnosis (1992-1999, 2000-2004 and 2005-2010) to study the impact of evolving therapeutics on CML outcomes. Median age at diagnosis was significantly different among ethnicities (p<0.001) with Hispanics the youngest (47 years) and Whites the oldest (63 years) (Figure 1). There were more Hispanic and AA CML patients reported in recent years in the database than those in 1992-1999 or 2000-2004 (p<0.001). Survival analysis revealed that for all patients, females had a significantly better median OS than males (7.8 years vs. 6.4 years; p<0.001). Among the different age cohorts, median OS got progressively worse with increasing age at diagnosis (p<0.001), with a median OS of 15+ years in 18-44 year cohort vs. 2.3 years in patients ≥75 years. Patients diagnosed more recently had a better median OS (1992-1999: 4.5 years vs. 2000-2004: 7.7 years vs. 2005-2010: 9.8 years; p<0.001). AA had the worst median OS among all ethnicities, which was significantly worse than Whites (reference) (5.8 years vs. 7.4 years; p<0.001). Asians had a median OS of 6.4 years and Hispanics 6 years. In a multivariate model using race, age at diagnosis, year of diagnosis, sex and marital status, a significant interaction was noted between year of diagnosis and race, with all racial subgroups showing improvement in 5-year survival in more recent time periods (p=0.001) (Figure 2). A significant interaction was also noted between year of diagnosis and age, with a progressive improvement in 5-year survival noted across all age groups in more recent years (p<0.001) (Figure 3). Conclusions We present a population-based study of outcomes in CML with the largest representation of ethnic minorities reported so far. We noted a higher number of AA and Hispanic patients reported to the SEER database in recent years. Hispanic patients had a significantly younger age at diagnosis, which could mean longer treatment duration over the lifetime of a patient. AA patients had the worst median OS among all ethnicities, although all ethnicities and age groups were noted to have progressive improvement in outcomes in more recent years of diagnosis. The incremental benefit in outcomes was seen most for Asians and least for Whites. These results will help in better understanding of ethnic influences on disease biology and clinical behavior as well as optimal triaging of healthcare resources. Disclosures: Off Label Use: The abstract shows scientific information on SAR245409 which is an investigational product developed by Sanofi. This investigational product is not approved by any health authority for any indication.

Abstract Background: Racial disparities in outcomes of cancer patients have been reported. Access to comprehensive cancer centers is associated with improved overall survival (OS) but racial/ethnic minorities may have a disparate access to such care. While the impact of treatment facility volume on outcomes has been evaluated, outcomes of centers with minority-predominant patient population have not been studied. We compared demographic profiles, facility level data and OS of patients treated at minority-predominant facilities to facilities that treated predominantly non-Hispanic Whites (NHW) with non-DLBCL. Methods: The National Cancer Database (NCDB) was used to identify all non-DLBCL patients diagnosed between 2004 and 2015. "Minority-treating facilities" were defined as facilities in the top decile by proportion for initial treatment of non-Hispanic African-Americans (NHAA), Hispanics and other races. We performed univariate and multivariate analyses to compare sociodemographic and clinical factors influencing outcomes between minority treating and non-minority treating facilities. A subgroup analysis stratified by race/ethnicity was also conducted to study the effect of treating facilities on the outcome of NHWs and minorities separately. Results: Of 1339 total facilities, 123 (9.1%) qualified as minority treating. Of 207,239 eligible patients in NCDB, 18,719 (9.03%) received treatment at the minority-treating facilities and of these, 11,190 (~60%) belonged to the minority races. Overall, 4.5% (6,988/156,664) NHWs and 30% (11,190/37,639) minorities received treatment at the minority-treating facilities. Several demographic and facility level characteristics were significantly different among the patients treated at minority-treating facilities as compared to non-minority treating facilities. Overall, significantly higher number of patients in minority-treating hospitals had lower income and education, had Medicaid coverage or lack of insurance. The OS of patients in minority treating facilities was significantly worse as compared to non-minority facilities (Figures). On multivariate analysis, patients who received treatment at minority-treating facilities were at 10% (HR=1.10, 95% CI: 1.06-1.14 p<0.001) higher risk of mortality as compared to those treated at the non-minority treating facilities. On multivariate analysis, NHAA (30% increased risk) and 'other races' (9% increased risk) were at significantly higher risk of mortality as compared to the NHW (Table 2). To study the effect of treatment at minority-treating facilities on OS among the patients of same race/ethnicity group, a multivariate analysis was also run separately for NHW and racial minorities. The NHWs who received treatment at minority-treating facilities were at 13% higher risk of death (HR=1.13, 95% CI: 1.08-1.19 p<0.001) as compared to NHWs who were treated at non-minority treating facilities. Similarly, the racial minorities who received treatment at minority treating facilities were at 8% higher risk of death (HR=1.08, 95% CI: 1.03-1.19 p=0.003) as compared to those who received treatment at the nonminority treating facilities. Conclusions:Outcomes of patients who received treatment at minority treating facilities was significantly worse than those at non-minority treating facilities. This was true for NHWs and racial minorities separately as well. Several demographic and facility level characteristics were significantly different in the two groups however OS remained worse after adjusting for them. Causes of poor outcomes at minority-treating facilities must be analyzed to mitigate them and improve outcomes for all. Figure. Figure. Disclosures Ailawadhi: Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding.

Abstract Background: The treatment of NHL has witnessed a paradigm shift over time, with targeted immunotherapy, stem cell transplant (SCT) among others. Historically, XRT was used quite frequently for the management of NHL but with advent of better systemic therapy, its utilization has changed. Trends and patterns of care for XRT use have never been formally reported. Methods: We identified patients with NHL diagnosis in the National Cancer Database (NCDB) between years 2004 and 2015. Demographic, clinical, facility level, initial treatment and outcome data were collected. The utilization of XRT in diffuse large B-cell (DLBCL) and non-DLBCL NHL were analyzed separately by univariate and multivariate analyses. To analyze the trends in the rates of XRT, we applied segmented linear regression to calculate the average annual percent change (AAPC) and 95% confidence Interval (CI) with a 'p' value. AAPC and CIs were calculated using the segmented package in R studio v1.1.49. Rest of the analyses was conducted using StataCorp version 15.1. Results: A total of 133,182 DLBCL and 204,933 non-DLBCL patients were identified. Among patients with DLBCL, 27,895 (20.9%) patients received RT. The rate of XRT declined from 25% in 2004 to 18.4% in 2015 with estimated AAPC of -0.59% (95%CI: -0.70- -0.49), p= 0.03 (Figure 1). In a subgroup analysis, a similar decline in the rate of XRT was evident across all the age groups, combined stages I and II vs stages III and IV and nodal vs extra nodal DLBCL (Table 1). Among non DLBCL, 33,369 (16.3%) patients received XRT. There was a statistically significant decline in the rate of XRT from 18.03% in 2004 to 16.3% in 2014 with an AAPC of -0.26 (95%CI: -0.38- -0.14) p <0.001 (Figure 1). On the subgroup analysis, the utilization of XRT declined across all the studied subgroups except among patients aged 80 years and above (Table 1). On multivariate analysis, several demographic, clinical and facility level factors were found to be significantly associated with XRT utilization in NHL (Table 2). In particular, older age groups, racial/ethnic minorities, advanced stages, higher Charlson comorbidity scores and diagnosis in the more recent calendar years were associated with lesser chances of receiving RT. Extranodal DLBCL had lower utilization while extranodal non-DLBCL had increased XRT utilization. Conclusion: There has been a significant decline in the utilization of XRT among patients with NHL (DLBCL and non-DLBCL) in the US since 2004, likely due to introduction of practice changing systemic therapeutics. There is still significant heterogeneity noted in practice patterns regarding utilization of XRT across the US. Having more standardized guidelines will help streamline delivery of evidence-based patient care. Disclosures Ailawadhi: Celgene: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Pharmacyclics: Research Funding.