ALBERT

Description: Background: The Hyper-CVAD regimen is safe and effective in the frontline treatment of B-ALL. The addition of rituximab to the Hyper-CVAD regimen (HCVAD-R) improved the 3-year overall survival (OS) to 60% in pts with B-ALL. Ofatumumab is an anti-CD20 monoclonal antibody that binds to the small extracellular loop of the CD20 molecule and has greater in vitro potency and increased complement-mediated cell lysis compared to rituximab. We hypothesized that ofatumumab plus Hyper-CVAD may increase the rates of complete remission (CR) and measurable residual disease negativity (MRD-) and improve survival by decreasing relapse rates. Methods: Pts were eligible if they had newly diagnosed untreated or minimally treated (≤ 1 cycle) Philadelphia chromosome (Ph)-negative CD20+ B-ALL. CD20 positivity was defined as ≥ 1% positive B-ALL cells. Pts received 8 alternating cycles of Hyper-CVAD and high-dose methotrexate/cytarabine (MTX/AraC). Ofatumumab was administered on days 1 and 11 of cycles 1 and 3; and days 1 and 8 of cycles 2 and 4. Pts then received POMP maintenance on cycles 1-5, 8-17 and 20-30 and late intensifications on cycles 6-7 and 18-19 (Hyper-CVAD + ofatumumab followed by MTX + peg-asparaginase). Pts received a total of 8 intrathecal injections of MTX and AraC for CNS prophylaxis. The primary endpoint was relapse-free survival (RFS) and secondary endpoints include CR rates, MRD negativity rates and OS. On a subset of 27 patient samples, transcriptome sequencing (RNA-seq) was performed to identify translocations and RNA expression signature for Ph-like ALL. We also performed a comprehensive detection of fusions and mutations reported in Ph-like ALL on RNA from these 27 samples using a multiplex fusion and mutation detection assay (Archer® FusionPlex® ALL). Results: Between August 2011 and May 2017, 69 pts were enrolled, including 4 already in CR at baseline after receiving 1 cycle of chemotherapy. Pts characteristics are summarized in Table 1. The median age was 41 years (18-71) and 48% pts were in the adolescent and young adult (AYA) age category (18-39 year-old). 7 of the 27 pts (26%) who had RNA-seq had Ph-like ALL gene expression signature. Among the 7 pts; 5 had Ph-like ALL fusions identified by Archer and/or RNA-seq-based fusion detection, including 2 P2RY8-CRLF2, 1 IGH-CRLF2, 1 BCR-FGFR1, and 1 ATF71P-PDGFRB. One patient had high CRLF2 expression with an unknown fusion partner. The remaining case lacked a fusion by either platform. Pts with Ph-like ALL had a higher median WBC of 41 x 109/L (range, 2 - 184). 43 pts (62%) had CD20 expression on ≥20% of the leukemic cells. 10/44 tested pts (23%) had TP53 mutation and 10/37 (27%) had CRLF2 overexpression by flow cytometry (4/5 CRLF2 rearrangement confirmed by Archer). 4 pts (6%) had low-hypodiploidy / near triploidy (Ho-Tr) and 2 (3%) pts had complex karyotype (CK). All but 1 pt (98%) achieved CR (2 after 2 cycles); only 1 pt (2%) died during induction. The MRD- rate was 65% after cycle 1 and 93% overall. These rates were 14% and 71%, respectively for pts with Ph-like ALL. The median time to MRD- was 0.7 month (range, 0.4-8 months) overall and 3 months (range, 0.7-6.5 months) for pts with Ph-like ALL. A total of 13 pts (19%) underwent allogeneic stem cell transplantation for adverse-risk cytogenetics (CK or Ho-Tr), Ph-like ALL (n=1/7), or persistent MRD+. The most common non-hematologic grade 3-4 toxicity was infection which occurred in 56% and 81% of pts, during induction and consolidation, respectively. With a median follow-up of 44 months, 46 pts (64%) are alive, including 37 pts (54%) in CR1. The median RFS and OS were 52 months (95% CI, 43 - NR) and not reached (95% CI, 65 - NR), respectively. The estimated 4-yr RFS and OS rates were 60% (95% CI, 49 - 73%) and 68% (95% CI, 58 - 81%), respectively (Figure 1A-1B). For AYA pts, the 4-yr OS rate was 74% (95% CI, 60 - 91%) (Figure 2A). The 4-yr OS rates were 54% (95%, 26 - 100%) for pts with Ph-like ALL compared to 74% (95% CI, 57 - 97%) for pts without Ph-like ALL (Figure 2B). There was no difference in OS according to the CD20 expression level (20% cut-off; p = 0.31). Using historical control pts, there was a trend towards improved OS with HCVAD-O versus HCVAD-R for pts with CD20 ≥ 20% (4-yr OS rate 63% vs 49%, p = 0.16) and HCVAD-O versus HCVAD alone for pts with CD20 1-19% (4-yr OS rate 73% vs 62%, p = 0.46). Conclusion: HCVAD-O is a safe and highly effective regimen in pts with CD20+ Ph-negative B-ALL. This regimen achieves excellent outcomes in the AYA population. Disclosures Kantarjian: BMS: Research Funding; AbbVie: Honoraria, Research Funding; Takeda: Honoraria; Daiichi-Sankyo: Research Funding; Amgen: Honoraria, Research Funding; Jazz Pharma: Research Funding; Immunogen: Research Funding; Cyclacel: Research Funding; Pfizer: Honoraria, Research Funding; Ariad: Research Funding; Astex: Research Funding; Novartis: Research Funding; Agios: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees. Konopleva:Agios: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Astra Zeneca: Research Funding; Ablynx: Research Funding; Calithera: Research Funding; Kisoji: Consultancy, Honoraria; Cellectis: Research Funding; Amgen: Consultancy, Honoraria; Ascentage: Research Funding; Genentech: Honoraria, Research Funding; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Eli Lilly: Research Funding; Forty-Seven: Consultancy, Honoraria. Ravandi:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cyclacel LTD: Research Funding; Menarini Ricerche: Research Funding; Xencor: Consultancy, Research Funding; Macrogenix: Consultancy, Research Funding; Selvita: Research Funding. Jain:AstraZeneca: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cellectis: Research Funding; Verastem: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Precision Biosciences: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics, an AbbVie company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Pharmaceuticals, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; ADC Therapeutics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Short:AstraZeneca: Consultancy; Amgen: Honoraria; Takeda Oncology: Consultancy, Research Funding. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Cortes:Daiichi Sankyo: Consultancy, Honoraria, Research Funding; Merus: Consultancy, Honoraria, Research Funding; Biopath Holdings: Consultancy, Honoraria; Immunogen: Consultancy, Honoraria, Research Funding; Forma Therapeutics: Consultancy, Honoraria, Research Funding; Sun Pharma: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Astellas Pharma: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; BiolineRx: Consultancy. Sasaki:Otsuka: Honoraria; Pfizer: Consultancy. Kadia:Celgene: Research Funding; Bioline RX: Research Funding; BMS: Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Research Funding. DiNardo:celgene: Consultancy, Honoraria; medimmune: Honoraria; abbvie: Consultancy, Honoraria; jazz: Honoraria; syros: Honoraria; agios: Consultancy, Honoraria; daiichi sankyo: Honoraria; notable labs: Membership on an entity's Board of Directors or advisory committees. Verstovsek:Astrazeneca: Research Funding; Ital Pharma: Research Funding; Protaganist Therapeutics: Research Funding; Constellation: Consultancy; Pragmatist: Consultancy; Incyte: Research Funding; Roche: Research Funding; NS Pharma: Research Funding; Celgene: Consultancy, Research Funding; Gilead: Research Funding; Promedior: Research Funding; CTI BioPharma Corp: Research Funding; Genetech: Research Funding; Blueprint Medicines Corp: Research Funding; Novartis: Consultancy, Research Funding; Sierra Oncology: Research Funding; Pharma Essentia: Research Funding. Mullighan:Loxo Oncology: Research Funding; AbbVie: Research Funding; Pfizer: Honoraria, Other: speaker, sponsored travel, Research Funding; Illumina: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: sponsored travel; Amgen: Honoraria, Other: speaker, sponsored travel. O'Brien:AbbVie: Consultancy, Honoraria; Acerta: Research Funding; Alexion: Consultancy; Amgen: Consultancy; Astellas: Consultancy; Aptose Biosciences, Inc: Consultancy; Celgene: Consultancy; Kite: Research Funding; GlaxoSmithKline: Consultancy; Eisai: Consultancy; Gilead: Consultancy, Research Funding; Janssen: Consultancy, Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding; Regeneron: Research Funding; Vaniam Group LLC: Consultancy; Verastem: Consultancy; Pfizer: Consultancy, Honoraria, Research Funding. Jabbour:Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Cyclacel LTD: Research Funding. OffLabel Disclosure: Ofatumumab is not approved by the FDA for treatment of B-cell acute lymphoblastic leukemia.

Description: Background: We have previously shown that CMR predicts better outcomes in Ph+ ALL. The lack of achievement of CMR and particularly major molecular response (MMR) at 3 months may confer poor outcomes. We sought to investigate the outcomes of pts who did not achieve CMR at 3 months as best response in terms of progression free survival (PFS) and overall survival (OS), and the role of allogeneic stem cell transplant (ASCT) in this population. Methods: We reviewed 204 pts with newly diagnosed Ph+ ALL treated at our institution between January 2001 and June 2019 with the combination of Hyper-CVAD plus tyrosine kinase inhibitors (TKI); dasatinib (n=88, 43%), ponatinib (n=72, 35%) and imatinib (n= 44, 22%). PFS was defined from the start of therapy to relapse or death. OS was defined from diagnosis to death or last follow-up. Backward multivariate Cox regression was used to identify prognostic factors for PFS and OS after variable selection at a p-value cutoff of 0.200. Time to ASCT was handled as a time-dependent variable. Survival curves were estimated by Kaplan-Meier method. Landmark analysis at the median time to ASCT was analyzed to evaluate the impact of ASCT. Results: We identified 94 pts (46%) who did not achieve 3-month CMR. Of pts treated with imatinib, 29 (66%) did not achieve 3-month CMR and 16 pts (36%) achieved 3-month MMR. Of pts treated with dasatinib, 42 (48%) did not achieve 3-month CMR and 29 pts (33%) achieved 3-month MMR. Of pts treated with ponatinib, 23 (32%) did not achieve 3-month CMR and 17 pts (24%) achieved 3-month MMR. Patient characteristics are summarized in table 1. Median age was 54 years (range: 21-80). The TKI administered was dasatinib, imatinib and ponatinib in 42 (45%), 29 (31%) and 23 (24%) pts, respectively. Overall, ASCT was performed in 28 pts (30%); 21 out of 62 pts (34%) with 3-month MMR, and 7 out of 32 pts (22%) who did not achieve MMR, within a median time of 5 months (range, 2.3-12.3). After a median follow-up of 97 months, median PFS was 21 months and median OS was 46 months. There was no difference in survival by TKI choice. The 5-year PFS and OS rates were 52% and 23% (p=0.001) (Figure 1A), and 58% and 26% (p=0.001) (Figure 1B) for pts with and without 3-month MMR, respectively. In multivariate analysis (table 2), 3-month MMR predicted longer PFS (p

Description: INTRODUCTION: Most clinical trials exclude patients with poor performance, organ dysfunction, and presence of other active malignancies or comorbidities. Although some of these criteria are based on clinical reasoning, patients with such clinical features have dismal expected outcomes and limited therapeutic options and could therefore have a more favorable risk/benefit ratio if treated with a low intensity investigational intervention. The current study was designed to test whether it is feasible to treat patients not eligible for conventional studies in a clinical trial. METHODS: We conducted an initial Bayesian designed single-arm study and a subsequent randomized study for patients with AML or higher-risk MDS (intermediate-2 or high risk by IPSS) with either ECOG performance status (PS) ≥3, creatinine or bilirubin ≥2mg/dL, presence of other malignancy or other comorbidities. Primary endpoint was survival at day 60. The study included stopping rules for survival, response and toxicity. All patients received azacitidine 75mg/m2 sc daily for 5 days. Patients in the single-arm study and in the combination arm of the randomized study also received vorinostat 200mg tid for 5 days. Cycles could be repeated every 3-8 weeks. Responses were evaluated following the revised 2006 IWG criteria for patients with MDS and the IWG 2003 recommendations for patients with AML. Comorbidities were evaluated using the Adult Comorbidity Evaluation-27 (ACE-27) index. Adverse events (AEs) were assessed and graded according to the CTCAE v4 criteria. Overall survival (OS) was censored at the time of transplant. Event-free survival (EFS) was defined as the time interval between treatment start and date of resistance, progression or death. RESULTS: A total of 30 patients (16 with MDS, 14 with AML) were enrolled in the initial single-arm study. Patient characteristics and inclusion criteria are detailed in Table 1. Median age was 73 years (44-83). Median follow-up was 7.4 months (0.3-29). Sixty-day survival was 83%. Median number of cycles administered was 3.5 (1-12). The overall response rate (ORR) was 40% with 8 (27%) patients achieving CR, 4 with AML and 4 with MDS. Median OS was 7.8 months (0.3-29, CI 7.54-8.03) (Figure 1A) and median EFS was 5.1 months (0.3-15.9, CI 4.87-5.37) (Figure 1B). Stopping rules for survival and response were not met. Main adverse events (AEs) where grade 1-2 gastrointestinal toxicities. Mortality at 4 and 8 weeks was 10 and 20% respectively. A total of 79 patients were enrolled in the subsequent randomized study: 27 to azacitidine (A) and 52 to azacitidine and vorinostat (A+V). Patient characteristics and inclusion criteria are also shown in Table 1. Median age was 70 years (30-90). Forty-seven (59%) patients had MDS and 32 (41%) had AML. Median follow-up was 22.7 months (12.6-47.5). Sixty-day survival rates were 67% (A) and 85% (A+V), respectively (p=0.07). No differences in ORR (48% vs 46%, p=0.87), OS (6.1 vs 7.6 months, p=0.49) (Figure 1C) or EFS (3 vs 5.5 months, p=0.05) (Figure 1D) were observed between groups. Main AEs included grade 1-2 gastrointestinal toxicities with a higher proportion of AEs with A+V (81 vs 56%). Mortality at 4 and 8 weeks was 10% (A: 4, A+V: 4) and 19% (A: 9, A+V: 6) respectively. By univariate analysis neither PS ≥3, creatinine or bilirubin ≥2mg/dL nor presence of other malignancy were predictive for 60-day survival, OS or EFS. There were no significant differences in survival between patients with ACE-27 scores of 0-1 compared to 2-3 both in the single-arm (6.3 vs 7 months, HR=0.88, 95% CI 0.41-1.91, p=0.75) and the randomized phase of the study (A: 13.5m vs 6.1m, HR 0.93, 95% CI 0.27-3.17, p=0.9 and A+V: 12.1m vs 7.4m, HR 1.38, 95% CI 0.61-3.14, p=0.4). CONCLUSION: Most enrolled patients met the study's primary endpoint of survival at 60 days without major toxicity. Patients obtained clinical benefit with acceptable responses and survival despite their high comorbidity burden. Our results support the feasibility of treating patients with MDS or AML not eligible to other clinical trials due to poor performance status, comorbidities or organ dysfunction, with low intensity therapies within a clinical trial. These findings suggest relaxation of such criteria may likely increase the pool of clinical trial patient candidates and allow access to potential beneficial therapies for patients with otherwise dismal prognosis. Table 1 Table 1. Figure 1 Figure 1. Disclosures Jabbour: ARIAD: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy. DiNardo:Abbvie: Research Funding; Novartis: Research Funding; Agios: Research Funding; Daiichi Sankyo: Research Funding; Celgene: Research Funding. Cortes:ARIAD: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Research Funding. Wierda:Genentech: Research Funding; Gilead: Research Funding; Novartis: Research Funding; Acerta: Research Funding; Abbvie: Research Funding. Konopleva:Reata Pharmaceuticals: Equity Ownership; Abbvie: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Stemline: Consultancy, Research Funding; Eli Lilly: Research Funding; Cellectis: Research Funding; Calithera: Research Funding. Jain:Novimmune: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Celgene: Research Funding; ADC Therapeutics: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Abbvie: Research Funding; Infinity: Research Funding; Incyte: Research Funding; Seattle Genetics: Research Funding; BMS: Research Funding; Novartis: Consultancy, Honoraria; Servier: Consultancy, Honoraria.

Description: Background: Myelodysplastic syndrome (MDS) is a heterogeneous malignant myeloid neoplasm of hematopoietic stem cells due to cytogenetic alterations and somatic mutations in genes (DNA methylation, DNA repair, chromatin regulation, RNA splicing, transcription regulation, and signal transduction). Hypomethylating agents (HMA) are the standard of care for MDS, and 40-60% of patients achieved response to HMA. However, the prediction for response is difficult due to the nature of heterogeneity and the context of clinical conditions such as the degree of cytopenias and the dependency on transfusion. Machine learning outperforms conventional statistical models for prediction in statistical competitions. Prediction with machine learning models may predict response in patients with MDS. The aim of this study is to develop a machine learning model for the prediction of complete response (CR) to HMA with or without additional therapeutic agents in patients with newly diagnosed MDS. Methods: From November 2012 to August 2017, we analyzed 435 patients with newly diagnosed MDS who received frontline therapy as follows; azacitidine (AZA) (3-day, 5-day, or 7-day) ± vorinostat ± ipilimumab ± nivolumab; decitabine (DAC) (3-day or 5-day) ± vorinostat; 5-day guadecitabine. Clinical variables, cytogenetic abnormalities, and the presence of genetic mutations by next generation sequencing (NGS) were included for variable selection. The whole cohort was randomly divided into training/validation and test cohorts at an 8:2 ratio. The training/validation cohort was used for 4-fold cross validation. Hyperparameter optimization was performed with Stampede2, which was ranked as the 15th fastest supercomputer at Texas Advanced Computing Center in June 2018. A gradient boosting decision tree-based framework with the LightGBM Python module was used after hyperparameter tuning for the development of the machine learning model with training/validation cohorts. The performance of prediction was assessed with an independent test dataset with the area under the curve. Results: We identified 435 patients with newly diagnosed MDS who enrolled on clinical trials as follows: 33 patients, 5-day AZA; 23, 5-day AZA + vorinostat; 43, 3-day AZA; 20, 5-day AZA + ipilimumab; 19 patients, AZA + nivolumab; 7, AZA + ipilumumab + nivolumab; 114, 5-day DAC; 74, 3-day DAC; 4, DAC + vorinostat; 97, 5-day guadecitabine. In the whole cohort, the median age at diagnosis was 68 years (range, 13.0-90.3); 117 (27%) patients had a history of prior radiation or cytotoxic chemotherapy; the median white blood cell count was 2.9 (×109/L) (range, 0.5-102); median absolute neutrophil count, 1.1 (×109/L) (range, 0.0-55.1); median hemoglobin count, 9.5 (g/dL) (range, 4.7-15.4); median platelet count, 63 (×109/L) (range, 2-881); and median blasts in bone marrow, 8% (range, 0-20). Among 411 evaluable patients for the revised international prognostic scoring system, 15 (4%) had very low risk disease; 42 (10%), low risk; 68 (17%), intermediate risk; 124 (30%), high risk; and 162 (39%), very high risk. Overall, 153 patients (53%) achieved CR. Hyperparameter tuning identified the optimal hyperparameters with colsample by tree of 0.175, learning rate of 0.262, the maximal depth of 2, minimal data in leaf of 29, number of leaves of 11, alpha regularization of 0.010, lambda regularization of 2.085, and subsample of 0.639. On the test cohort with 87 patients, the machine learning model accurately predicted response in 65 patients (75%); 53 non-CR among 56 non-CR (95% accuracy); and 12 CR among 31 CR (39% accuracy). The trend of accuracy improvement by iteration (i.e., the number of decision trees) is shown in Figure 1. The area under the curve was 0.761521 in the test cohort. Conclusion: Our machine learning model with clinical, cytogenetic, and NGS data can predict CR to HMA in patients with newly diagnosed MDS. This approach can identify patients who may benefit from HMA therapy with and without additional agents for response, and can optimize the timing of allogeneic stem cell transplant. Disclosures Sasaki: Otsuka: Honoraria; Pfizer: Consultancy. Jabbour:Takeda: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Cyclacel LTD: Research Funding. Ravandi:Cyclacel LTD: Research Funding; Selvita: Research Funding; Menarini Ricerche: Research Funding; Macrogenix: Consultancy, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Xencor: Consultancy, Research Funding. Kadia:Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Bioline RX: Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Research Funding; BMS: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Takahashi:Symbio Pharmaceuticals: Consultancy. DiNardo:syros: Honoraria; jazz: Honoraria; agios: Consultancy, Honoraria; celgene: Consultancy, Honoraria; notable labs: Membership on an entity's Board of Directors or advisory committees; medimmune: Honoraria; abbvie: Consultancy, Honoraria; daiichi sankyo: Honoraria. Cortes:Novartis: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Immunogen: Consultancy, Honoraria, Research Funding; Sun Pharma: Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Astellas Pharma: Consultancy, Honoraria, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Merus: Consultancy, Honoraria, Research Funding; Forma Therapeutics: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Consultancy, Honoraria, Research Funding; BiolineRx: Consultancy; Biopath Holdings: Consultancy, Honoraria; Takeda: Consultancy, Research Funding. Kantarjian:AbbVie: Honoraria, Research Funding; Cyclacel: Research Funding; Pfizer: Honoraria, Research Funding; Astex: Research Funding; Agios: Honoraria, Research Funding; Jazz Pharma: Research Funding; Daiichi-Sankyo: Research Funding; Novartis: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Immunogen: Research Funding; Takeda: Honoraria; BMS: Research Funding; Ariad: Research Funding; Amgen: Honoraria, Research Funding. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding.

Description: Background: Allogeneic stem cell transplant (ASCT) is a curative option for patients with higher risk myelodysplastic syndromes (MDS). Hypomethylating agents (HMA) have been shown to improve survival of patients with MDS and have an excellent toxicity profile. In eligible patients, HMA and ASCT are used as complementary strategies. The aim of this study is to compare outcome with HMA alone vs HMA+ASCT where ASCT is used as consolidation approach or as salvage therapy after HMA failure. Methods: We performed a retrospective analysis of 216 patients with high-risk MDS who received HMA treatment at our institution from between April 2004 and October 2012; after HMA therapy, 61 (28%) patients underwent ASCT: 25 (41%) of them received as a consolidation treatment and 36 (59%) as a salvage therapy. The remaining 155 patients continued on HMA therapy until relapse or progression and did not receive a further ASCT. We used SPSS v.20 for all statistical analysis. Categorical and continuous variables were compared by chi-square and Student’s t test, respectively, and survival analysis was conducted using Kaplan-Meier analysis with the log-rank test and Cox regression for multivariate models. We also implemented a landmark survival analysis that considered median time to transplant. Results: Median age was 65 (20-89), and patients were older in the group that did not receive ASCT (69 vs 58 years; p=0.000). WHO diagnoses were RA/RARS in 31 patients (15%), RCMD in 43 patients (19.9%), RAEB in 133 patients (62%), CMML in 23 patients (11%), and unclassifiable MDS in 18 patients (8.3%). IPSS risk was int-2 in 107 patients (50%) and high in 61 (28%), and the percentage of inttermediate-2/high-risk MDS was higher in the ASCT group (89% vs 73%; p=0.001). High-risk cytogenetics were found in 71% of patients (82% in ASCT vs 67% in HMA alone; p=0.02). Patients received a median of 6 (1-58) courses of HMA. Overall response rate (ORR) to HMA was 45% (n=97), with 38% (n=82) having complete response (CR), 2% (n=5) partial response, and 5% (n=10) hematologic improvement. There were no significant differences between response to HMA in the ASCT group when compared to the group that did not receive ASCT (ORR: 46% vs 43%, p=0.3; CR: 38% vs 37%, p= 0.5). When we further analyzed the 61 ASCT patients, 25 (41%) received it as a consolidation after achieving response and 36 (59%) as a salvage therapy after treatment failure. Response to ASCT was CR in 65% of patients, and 20% were not evaluable due to early mortality. Median overall survival (OS) for the whole series was 14 months (12-16), with 1- and 2-year OS rates of 57% and 24%, respectively. To adjust for early mortality after ASCT and to eliminate any bias, we performed a landmark analysis after a median time of 7 months after ASCT. Patients who received ASCT had better survival. This advantage was more evident among patients who received ASCT as salvage therapy, although there were no differences between both strategies, with respective median survivals of 14 months for consolidation ASCT and 23 months for salvage ASCT (p=0.29)Furthermore, no significant differences in survival were observed between patients who received HMA alone and those who received ASCT as a consolidation therapy (median survival of 14 and 16 months; p=0.498), although there was a tendency for a better OS after 2 years of follow up: the OS for HMA treatment and HMA+ASCT consolidation were 68% and 56% at 1 year, 25% and 31% at 2 years, and 10% and 31% at 3 years. The 1-year survival rates for patients who received HMA alone, HMA followed by ASCT as consolidation, and HMA followed by ASCT as salvage were 68%, 56%, and 78%, respectively, and the 2-year survival rates were 25%, 31%, and 42%, respectively. In a Cox regression model to analyze effects on OS, receiving an ASCT (median OS of 13 (7-19) vs 10 months (8-12); HR 0.62 [0.42 – 0.92], p=0.018) and hemoglobin levels at diagnosis (HR 0.829 [0.73 – 0.93], p=0.002) had a significant impact. Conclusions: ASCT is a feasible and curative strategy for patients with MDS, both as a consolidation or a salvage therapy, and thus it can be a good option after HMA failure. However, its benefits as a consolidation therapy after HMA treatment compared with continuation of HMA treatment are not clear owing to early mortality related to procedure, so ASCT should be carefully considered in patients responding to HMA. Disclosures Borthakur: Tetralogic Pharmaceuticals: Research Funding. Cortes:Ariad: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Teva: Consultancy, Research Funding. Ravandi:Incyte Corporation: Research Funding. Kadia:GSK: Research Funding; ARIAD: Honoraria. Champlin:Otsuka: Research Funding. Kantarjian:ARIAD: Research Funding; Pfizer: Research Funding; Amgen: Research Funding.

Description: Introduction: Venetoclax (VEN) is approved for the treatment of acute myeloid leukemia (AML) in combination with hypomethylating agents (HMAs) or low-dose cytarabine and commonly used for patients (pts) unfit for intensive chemotherapy. Prophylaxis with triazole antifungals (azoles) during induction treatment in pts with AML has decreased mortality and is the standard of care for pts receiving treatment regimens associated with prolonged myelosuppression (Cornely et al, 2007). Azoles inhibit CYP3A4 (CYP3A4i), the enzyme responsible for the metabolism of VEN, and p-glycoprotein to varying degrees, which VEN is a substrate. Based on this interaction and the results of a small pharmacokinetic study, significant VEN dosage reductions are recommended (Agarwal et al, 2017). Little real-world data exists to demonstrate the tolerability of VEN in combination with azoles during induction treatment with VEN and HMAs. Methods: All pts with newly diagnosed AML treated at our institution with VEN and HMAs from 11/2014-1/2019 were retrospectively reviewed. Pts were treated as standard of care or as part of clinical trial in combination with azacitidine (NCT02203773) or decitabine (NCT03404193; NCT02203773). Pts who received concomitant antifungal for 〉5 days while also receiving VEN for 〉7 days were included. VEN 100mg daily with posaconazole or voriconazole (strong CYP3A4i) and VEN 200mg daily with isavuconazole or fluconazole (moderate CYP3A4i) were considered 400mg equivalent dosages. Higher doses of VEN in these combinations were considered 〉VEN 400mg equivalent. To determine the clinical impact of concomitant azoles, time to absolute neutrophil count (ANC) and platelet (PLT) recovery after induction was analyzed, in addition to response rates, episodes of febrile neutropenia (FN) and documented infections. Results:One-hundred twenty-one pts treated with HMA and VEN were identified (Table 1). The median age was 72 years (48-86) and 35% were 〉 75 years. Forty pts (33%) had secondary AML, and 10% had therapy-related AML. Most were treated with decitabine 20mg/m2 administered for 10 days (67%) or 5 (22%). VEN was administered for a median of 23 days (7-30) at a 400mg daily dose equivalent in 74 pts (62%) and 〉400mg dose equivalent in 40 pts (33%). Eighty-nine (74%) received a concomitant azole with VEN including posaconazole (38%), isavuconazole (21%), voriconazole (13%), or fluconazole (2%). Following induction therapy with VEN and HMA, 37% achieved a complete response (CR) and 22% achieved a CR with incomplete blood count recovery (CRi). An additional 10% achieved a morphologic leukemia free state (MLFS) (Table 2). Prior to cycle 2, 55% of pts achieved ANC〉500 cells/mm3 and 64% achieved PLT〉50,000 cells/mm3 after a median of 34 days and 24 days, respectively. No difference in response was observed based on VEN dosage or duration (Table 3). Pts achieving CR/CRi received VEN for a median of 22 days (7-29), and 38% at the 400mg equivalent VEN dosage with an azole. When analyzing VEN dosage by the use of an azole, duration of neutropenia (ANC0.05) (Table 4). Number of pts achieving PLT〉50,000 cells/mm3 was not affected by concomitant antifungal or VEN dosage, but duration of thrombocytopenia was. Time to PLT〉50,000 cells/mm3 was significantly longer for pts receiving VEN 400mg equivalent with an azole (25 vs 20 days, p=0.01) as well as time to PLT〉100,000 cells/mm3 (27 vs 22 days, p=0.03). Despite prolonged cytopenias, all pts receiving the VEN 400mg equivalent dosage had similar rates of FN, documented infections, and hospital duration regardless of the use of an azole (Table 4). Those receiving 〉400mg VEN equivalent had numerically higher rates of FN, infections, and duration of hospitalization. Conclusion: The combination of VEN with HMA is an effective treatment option in pts with newly diagnosed AML. VEN is associated with significant myelosuppression which can be enhanced by concomitant CYP3A4i, such as the azoles. The combination of VEN and azoles resulted in prolonged cytopenias, namely thrombocytopenia, compared to the use of VEN without an azole. This did not result in higher rates of FN, infections, or duration of hospitalization, therefore the concomitant use of VEN and azole appear to provide a clinically safe and effective therapeutic regimen. Higher doses of VEN do not appear to be advantageous in this setting. Disclosures DiNardo: daiichi sankyo: Honoraria; jazz: Honoraria; syros: Honoraria; medimmune: Honoraria; notable labs: Membership on an entity's Board of Directors or advisory committees; abbvie: Consultancy, Honoraria; agios: Consultancy, Honoraria; celgene: Consultancy, Honoraria. Maiti:Celgene: Other: research funding. Kadia:Celgene: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bioline RX: Research Funding; BMS: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Research Funding. Borthakur:Polaris: Research Funding; Strategia Therapeutics: Research Funding; Tetralogic Pharmaceuticals: Research Funding; FTC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Xbiotech USA: Research Funding; Bayer Healthcare AG: Research Funding; AstraZeneca: Research Funding; BMS: Research Funding; Eli Lilly and Co.: Research Funding; Oncoceutics, Inc.: Research Funding; PTC Therapeutics: Consultancy; NKarta: Consultancy; BioLine Rx: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cyclacel: Research Funding; GSK: Research Funding; Janssen: Research Funding; Incyte: Research Funding; AbbVie: Research Funding; Argenx: Membership on an entity's Board of Directors or advisory committees; Eisai: Research Funding; Novartis: Research Funding; Cantargia AB: Research Funding; Arvinas: Research Funding; Oncoceutics: Research Funding; BioTheryX: Membership on an entity's Board of Directors or advisory committees; Merck: Research Funding; Agensys: Research Funding. Pemmaraju:affymetrix: Research Funding; sagerstrong: Research Funding; Daiichi-Sankyo: Research Funding; plexxikon: Research Funding; novartis: Consultancy, Research Funding; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; cellectis: Research Funding; celgene: Consultancy, Honoraria; samus: Research Funding; abbvie: Consultancy, Honoraria, Research Funding; mustangbio: Consultancy, Research Funding; incyte: Consultancy, Research Funding. Sasaki:Pfizer: Consultancy; Otsuka: Honoraria. Ravandi:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Menarini Ricerche: Research Funding; Cyclacel LTD: Research Funding; Selvita: Research Funding; Xencor: Consultancy, Research Funding; Macrogenix: Consultancy, Research Funding. Kantarjian:Astex: Research Funding; AbbVie: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Immunogen: Research Funding; Takeda: Honoraria; Agios: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; BMS: Research Funding; Cyclacel: Research Funding; Daiichi-Sankyo: Research Funding; Novartis: Research Funding; Jazz Pharma: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Ariad: Research Funding. Konopleva:Astra Zeneca: Research Funding; Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Ablynx: Research Funding; Agios: Research Funding; Kisoji: Consultancy, Honoraria; Ascentage: Research Funding; Calithera: Research Funding; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Forty-Seven: Consultancy, Honoraria; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Cellectis: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Eli Lilly: Research Funding.

Description: Background Internal tandem duplication (ITD) mutations inFLT3 (fms-like tyrosine kinase III) are detected in approximately 25% of patients (pts) with acute myeloid leukemia (AML) and are associated with an increased risk of relapse and adverse outcome. In the present study we evaluate the potential predictors of induction failure and CR1 duration in pts with FLT3-ITD mutated AML. Methods We retrospectively evaluated adult pts with FLT3-ITDmutated AML treated at our institution from July 2012 to January 2018. Pts with acute promyelocytic leukemia or core-binding factor AML were excluded. Demographic, clinical, laboratory and pathologic data were obtained from clinical records. FLT3-ITD mutational analysis was performed using PCR-based DNA sequencing. FLT3-ITD was quantified by the quantity of mutant allele burden as a percentage of total allele burden, high level was defined as ≥50%. Response to treatment was evaluated according to the 2003 revised International Working Group AML criteria. Patients with available cytogenetic data were classified according to the European Leukemia Net (ELN) guidelines. Statistical analysis included Mann Whitney test for continuous, Fisher's exact test for categorical variables and Kaplan-Meier survival curves for overall survival (OS) and relapse free survival (RFS). Results We identified 235 pts.The median age was 64 years (19-92) with 45% being male. Cytogenetic data at diagnosis was available in 166 pts and risk stratification by the ELN criteria included, 33 (20%) favorable, 117 (70%) intermediate and 16 (10%) adverse risk, respectively. Forty-two (18%) pts had a history of antecedent hematological disease (AHD) and 26 (11%) had therapy related AML (t-AML). Pts were treated with several different therapies as induction treatment for AML, including: high dose cytarabine based (HiDAC) in 84 (36%), conventional dose cytarabine based in 59 (26%), hypomethylating agents (HMA) in 70 (29%) and other in 22 (9%). Approximately half of pts (n=120, 51%) received a FLT3 inhibitor during induction. A total of 166 (71%) pts achieved a complete remission (CR)/CR with incomplete hematologic recovery (CRi) and 69 (29%) failed induction. Baseline characteristic of the pts are shown in Table 1. Compared with responders, pts with primary induction failure were more frequently treated with HMA based induction (p=0.001), were older (p=0.002), male (p=0.01), had an increased incidence of AHD (p=0.04), lower levels of FLT3-ITD allele ratio (p=0.04), and adverse cytogenetic risk (p=0.001). There was no significant difference in analyzed molecular mutations (Table 1). Among the 166 complete responders; 92 (61%) remain in CR1 over a median follow-up of 16 months (range, 2-69). Of the 74 (39%) pts that relapsed, 38 (23%) relapsed within 6 months of CR1, 27 (16%) between 6 to 12 months and 9 (5%) relapsed after 12 months of CR1. Median duration of CR1 was 8 months (range, 0.2-68). We classified pts into 2 categories based on their duration of CR1 including: CR1 duration 65 years (p=0.001), presence of EZH2(p〉0.001) or RUNX1(p=0.01) mutations at baseline were associated with early relapse; achievement of a MRDneg by flow cytometry (p=0.0015), CR vs CRi (p

Description: Background: Fludarabine, cytarabine and G-CSF (FLAG) based regimens have resulted in marked improvement in newly diagnosed core binding factor (CBF) acute myelogenous leukemia (AML)(1-3). Addition of gemtuzumab ozogamicin (GO) to chemotherapy has also improved survival outcomes in CBF-AML(4). In 2007 we initiated a frontline study of FLAG-GO in newly diagnosed CBF-AML but after withdrawal of GO from US market, GO was replaced with idarubicin (FLAG-Ida). We report on mature data including early molecular response in patients treated in these sequential protocols. Methods: One hundred and forty five patients [Median age, 48 years (range, 19-78 years) were treated in these sequential protocols (FLAG=GO=50, FLAG-Ida= 95 patients). The treatment groups were comparable for age and distribution of cytogenetic (T8;21 or Inv16) subgroups (p≥0.5). FLAG regimen has been published before(2), GO was administered at 3 mg/m2 on day 1 in induction and in 2 consolidations out of planned 6 and idarubicin was administered at 6 mg/m2 on days 3 and 4 in induction and on day 2 in one of the consolidation cycles out of planned 6. Serial assessment of fusion transcript product relevant to the cytogenetic abnormality was performed in bone marrow samples at baseline, end of induction and every 2-3 cycles thereafter. Results: All except 3 patients (2 induction deaths) achieved remission (98%). After median follow up of 5 years, 5 year overall survival (OS) and relapse free survival (RFS) for the entire cohort is 77% and 72% respectively. There were no differences in OS among FLAG-GO vs FLAG-Ida (p=0.3) and Inv16 vs T(8;21) (p=0.6). While RFS was similar among Inv 16 and T(8;21) subgroups, it was significantly better among the cohort treated with FLAG-GO compared to FLAG-Ida (p=0.04)(Fig 1). We confirmed our earlier report of higher than 3 log reduction of fusion transcript ratio at end of induction(5) being most indicative of sustained RFS (p=0.006) (Fig 2) and this end point was more frequently achieved in the FLAG-GO cohort (57%) compared to FLAG-Ida cohort (29%) (p=0.002). On the other hand, within each regimen there was no difference in RFS between Inv 16 andf T(8;21) subgroups (p=0.3) (Fig. 3). SAEs were mostly related to cytopenias and associated infectious complications for both regimens and no hepatic veno-occlusive disease (VOD) was encountered. Presence of KIT, RAS, FLT3 mutations individually or in combination did not have any impact on outcomes. Conclusion: Compared to idarubicin, GO when added to FLAG based frontline induction/consolidation regimen results in better early molecular responses and improved relapse free survival in CBF AML. Our current frontline protocol is exploring safety and efficacy of addition of both GO and Ida to FLAG based regimen. ReferencesBorthakur G, Cortes JE, Estey EE, Jabbour E, Faderl S, O'Brien S, et al. Gemtuzumab ozogamicin with fludarabine, cytarabine, and granulocyte colony stimulating factor (FLAG-GO) as front-line regimen in patients with core binding factor acute myelogenous leukemia. Am J Hematol. 2014;89(10):964-8.Borthakur G, Kantarjian H, Wang X, Plunkett WK, Jr., Gandhi VV, Faderl S, et al. Treatment of core-binding-factor in acute myelogenous leukemia with fludarabine, cytarabine, and granulocyte colony-stimulating factor results in improved event-free survival. Cancer. 2008;113(11):3181-5.Burnett AK, Russell NH, Hills RK, Hunter AE, Kjeldsen L, Yin J, et al. Optimization of Chemotherapy for Younger Patients With Acute Myeloid Leukemia: Results of the Medical Research Council AML15 Trial. Journal of Clinical Oncology. 2013;31(27):3360-8.Hills RK, Castaigne S, Appelbaum FR, Delaunay J, Petersdorf S, Othus M, et al. Addition of gemtuzumab ozogamicin to induction chemotherapy in adult patients with acute myeloid leukaemia: a meta-analysis of individual patient data from randomised controlled trials. The Lancet Oncology. 2014;15(9):986-96.Boddu P, Gurguis C, Sanford D, Cortes J, Akosile M, Ravandi F, et al. Response kinetics and factors predicting survival in core-binding factor leukemia. 2018. Disclosures Cortes: novartis: Research Funding. Ravandi:Jazz: Honoraria; Sunesis: Honoraria; Jazz: Honoraria; Astellas Pharmaceuticals: Consultancy, Honoraria; Abbvie: Research Funding; Bristol-Myers Squibb: Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Macrogenix: Honoraria, Research Funding; Seattle Genetics: Research Funding; Xencor: Research Funding; Orsenix: Honoraria; Xencor: Research Funding; Macrogenix: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Seattle Genetics: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Sunesis: Honoraria; Orsenix: Honoraria. Kadia:Novartis: Consultancy; Celgene: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Research Funding; Pfizer: Consultancy, Research Funding; BMS: Research Funding; Jazz: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; BMS: Research Funding; Pfizer: Consultancy, Research Funding; Abbvie: Consultancy; Novartis: Consultancy; Jazz: Consultancy, Research Funding; Abbvie: Consultancy; Takeda: Consultancy. Pemmaraju:SagerStrong Foundation: Research Funding; Affymetrix: Research Funding; plexxikon: Research Funding; daiichi sankyo: Research Funding; samus: Research Funding; celgene: Consultancy, Honoraria; abbvie: Research Funding; cellectis: Research Funding; stemline: Consultancy, Honoraria, Research Funding; novartis: Research Funding. Daver:ARIAD: Research Funding; Daiichi-Sankyo: Research Funding; Kiromic: Research Funding; Alexion: Consultancy; Otsuka: Consultancy; Sunesis: Consultancy; Karyopharm: Consultancy; BMS: Research Funding; Karyopharm: Research Funding; Pfizer: Research Funding; Pfizer: Consultancy; Incyte: Consultancy; Sunesis: Research Funding; Novartis: Consultancy; Novartis: Research Funding; Incyte: Research Funding; ImmunoGen: Consultancy.

Description: Background: The addition of midostaurin to induction therapy has become a standard approach in newly diagnosed FLT3-mu AML. Second gen FLT3i's quizartinib and gilteritinib demonstrated single-agent CR/CRi rates of 45-55% in pts with R/R FLT3-mu AML in phase II/III trials. The majority of pts in these trials were prior FLT3 inhibitor naïve, a population likely to become obsolete soon. The response rates to second and third FLT3i exposure remain poorly defined. This will be an important clinical question as multiple FLT3i are approved. Methods: Adult pts with FLT3-ITD mu AML who received at least one FLT3i based therapy at MDACC from 2007 to 2018 were included. Single agent FLT3i and FLT3i combinations with cytotoxic chemotherapy (CCT) and low intensity therapy (LIT) (hypomethylating agents and low-dose cytarabine) were included. FLT3 testing was performed as previously reported (Luthra R et al., Haematologica 2014). All FLT3-ITD positive pts were included irrespective of the allelic frequency. Results: 217 pts with FLT3-ITD mu AML received one FLT3i therapy, 109 pts received a second FLT3i, 29 received a third FLT3i, and 4 received a fourth FLT3i (Table.1). Overall response rates (ORRs) (ORR = CR+CRp+CRi+PR) were 49%, 27%, 17% and 25% with the first, second, third, and fourth FLT3i (composite CR (CRc) rates of 49%, 27%, 13% and 25%), respectively (Table.1A). The median OS was 8.7, 4.2, 3.5 and 3.9 months with the first, second, third, and fourth FLT3i, respectively. In the first FLT3i exposure, the ORRs with CCT, LIT, and single-agent FLT3i were 57%, 62%, and 32%. The median (med) prior AML treatment in this group was 1 (range, 0 - 7), however none had received a prior FLT3i. In the second FLT3i exposure, the ORRs with CCT, LIT, and single-agent FLT3i were 27%, 46%, and 15%, respectively. The med prior AML treatments in this group were 3 (range, 1 - 8), including one prior FLT3i. In the third FLT3i exposure, the ORRs with CCT, LIT, and single-agent FLT3i were 0%, 29%, and 18%. The med prior AML treatments in this group were 4 (range, 2 - 10), including two prior FLT3i's. Only 4 pts received a fourth FLT3i and 1 had a CRi. Analyzing by individual FLT3i, 359 FLT3i's were used at different time points, excluding duplication of FLT3i's in any pt. The most frequently used was quizartinib (131 pts, 37% of all pts). Quizartinib was used in combination with LIT (63 pts) or as a single-agent (68 pts) only, with ORRs in all FLT3i exposure groups of 73% and 38% (CRc 70% and 38%), respectively. In the first (n=102), second (n=23), and third (n=6) FLT3i exposures, ORRs with quizartinib-based therapies were 59%, 39%, and 50% (CRc 59%, 35%, and 33%), respectively (Fig.1B). Quizarinib is a potent FLT3i. Switching to another FLT3i after failing first line quizartinib (n=33) still produced ORRs of 24% (CRc 21%). The second commonest used FLT3i was sorafenib (108 patients, 30% of all pts). Sorafenib was used in combination with CCT (n=38), LIT (n=57), and as single-agent (n=13) with ORRs in all FLT3i exposure groups of 54%, 42%, and 7% (CRc 54%, 39%, and 7%). Single agent sorafenib was not as effective. In the first (n=69), second (n=33), and third (n=6) FLT3i exposures, ORRs with sorafenib-based therapies were 49%, 30%, and 17% (CRc 46%, 30%, and 17%), respectively. Quizartinib-based therapies had an ORR of 37% (32% CR/CRi) as second line post-sorafenib (Fig.1C). Gilteritinib was used in 12 pts as a single-agent. 3, 8 and 1 pts received gilteritinib in first, second and third FLT3i exposures with ORRs of 67%, 38% and 100% (all CRc responses), respectively. Midostaurin was always used in combination, with CCT (n=2) or LIT (n=10) with ORRs of 50% and 40% (all CRc responses) in all FLT3i groups, respectively. In this small set, post-midostaurin ORRs to second FLT3i's were 57% (all CRc). Conclusions: ORRs dropped from 49% to 27% to 17% with first, second, and third FLT3i-based therapies. Combining FLT3is with low or high intensity chemotherapy appeared superior to single agent in all exposure groups. LIT (HMA and LDAC)-based combinations had encouraging ORRs of 46% and 29% in the second and third FLT3i exposure, likely because many pts received CCT-based combinations as initial therapy. Quizartinib and gilteritinib were effective with ORR of 35-40% even when used as a second FLT3i. This is a first attempt at identifying benchmark response rates for second and third FLT3i exposures, for developing novel FLT3i combinations and expectations with sequential FLT3i usage. Disclosures Ravandi: Xencor: Research Funding; Sunesis: Honoraria; Macrogenix: Honoraria, Research Funding; Seattle Genetics: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Jazz: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Astellas Pharmaceuticals: Consultancy, Honoraria; Jazz: Honoraria; Orsenix: Honoraria; Astellas Pharmaceuticals: Consultancy, Honoraria; Xencor: Research Funding; Macrogenix: Honoraria, Research Funding; Abbvie: Research Funding; Bristol-Myers Squibb: Research Funding; Orsenix: Honoraria; Abbvie: Research Funding; Sunesis: Honoraria. Konopleva:Stemline Therapeutics: Research Funding. Kadia:Novartis: Consultancy; Takeda: Consultancy; BMS: Research Funding; Jazz: Consultancy, Research Funding; Novartis: Consultancy; Celgene: Research Funding; Amgen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy; Jazz: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Abbvie: Consultancy; Takeda: Consultancy; Celgene: Research Funding; Pfizer: Consultancy, Research Funding; BMS: Research Funding. Jabbour:Pfizer: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Abbvie: Research Funding. DiNardo:Karyopharm: Honoraria; Bayer: Honoraria; Agios: Consultancy; Medimmune: Honoraria; Celgene: Honoraria; Abbvie: Honoraria. Pemmaraju:SagerStrong Foundation: Research Funding; Affymetrix: Research Funding; plexxikon: Research Funding; daiichi sankyo: Research Funding; samus: Research Funding; celgene: Consultancy, Honoraria; abbvie: Research Funding; cellectis: Research Funding; stemline: Consultancy, Honoraria, Research Funding; novartis: Research Funding. Short:Takeda Oncology: Consultancy. Andreeff:United Therapeutics: Patents & Royalties: GD2 inhibition in breast cancer ; Daiichi-Sankyo: Consultancy, Patents & Royalties: MDM2 inhibitor activity patent, Research Funding; Oncolyze: Equity Ownership; Celgene: Consultancy; Oncoceutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; SentiBio: Equity Ownership; Jazz Pharma: Consultancy; Eutropics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding; Amgen: Consultancy, Research Funding; Reata: Equity Ownership; Aptose: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Cortes:Pfizer: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Arog: Research Funding; Novartis: Consultancy, Research Funding. Daver:Alexion: Consultancy; ImmunoGen: Consultancy; Novartis: Research Funding; ARIAD: Research Funding; BMS: Research Funding; Kiromic: Research Funding; Incyte: Research Funding; Incyte: Consultancy; Karyopharm: Research Funding; Novartis: Consultancy; Sunesis: Consultancy; Daiichi-Sankyo: Research Funding; Pfizer: Consultancy; Karyopharm: Consultancy; Otsuka: Consultancy; Pfizer: Research Funding; Sunesis: Research Funding.

Description: Background: Outcomes of patients (pts) with Richter transformation (RT) remain dismal with a median survival of less than 1 year with chemoimmunotherapy (CIT). Dysfunction of T cells, NK cells and other immune subsets is common in pts with CLL. Checkpoint blockade is an emerging treatment approach for pts with RT (Ding et al. Blood 2017; Younes et al. ASH 2017). Methods: We designed an investigator-initiated phase II clinical trial combining nivolumab (anti-PD1 monoclonal antibody) with ibrutinib in pts with R/R CLL or RT (NCT02420912). We report data on the RT cohort. Nivolumab was given 3 mg/kg IV every 2 weeks, starting cycle 1 day 1 for a total of 24 cycles. Ibrutinib was given 420 mg once daily starting cycle 2 day 1 (Ibrutinib could be added during cycle 1, in case of worsening disease) and continued until disease progression or unacceptable toxicities. Each cycle was 4 weeks. Eligibility criteria included age ≥18 years, adequate organ function (total bilirubin ≤1.5 x ULN, ALT and AST ≤3 x ULN, creatinine ≤1.5 x ULN). Pts were included if they had received at least one therapy for CLL or RT (pts with del(17p) could be treatment-naïve). Response assessments were done by PET scan and bone marrow after cycle 1, cycle 3, cycle 6, cycle 9, and cycle 12, cycle 18, and cycle 24. Results: A total of 23 pts with RT have been enrolled. The median age was 65 years (range, 49-88); 10 women, 13 men. The median number of prior therapies for CLL/RT was 3 (range, 0-10); one pt with previously untreated CLL who developed RT with del(17p) was enrolled. Prior therapies included CIT (n=18), ibrutinib (n=11), acalabrutinib (n=1), P13K inhibitor (n=4), venetoclax (n=3), allo-SCT (n=2). A total of 10 pts (43%) responded (complete metabolic response, n=8; partial metabolic response, n=2). The median duration of response (censored for allo-SCT) for the responding pts (n=10) is 9.3 months (Figure 1). Two pts previously treated with ibrutinib responded. A total of 4 pts underwent a subsequent allo-SCT after achieving a response to therapy. Four additional pts underwent allo-SCT after receiving a subsequent salvage therapy. The median overall survival for the entire group (n=23) is 13.8 months (Figure 1). One pt had G3 transaminitis and one pt had grade 4 lipase/amylase elevation. One pt developed grade 2 pneumonitis, and one pt had grade 2 uveitis. Correlative studies, including flow-cytometry and immunohistochemistry for PD1 and PDL1 are ongoing. Conclusions: The combination of nivolumab and ibrutinib has clinical activity in pts with RT with a 43% response rate. Disclosures Jain: Pfizer: Research Funding; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; BMS: Research Funding; Astra Zeneca: Research Funding; Astra Zeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; ADC Therapeutics: Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding; Verastem: Research Funding; Servier: Research Funding; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Servier: Research Funding; Novimmune: Honoraria, Membership on an entity's Board of Directors or advisory committees; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees; Infinity: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Cellectis: Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Verastem: Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Infinity: Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Research Funding; Abbvie: Research Funding; Adaptive Biotechnologioes: Research Funding; Genentech: Research Funding; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; Adaptive Biotechnologioes: Research Funding; Cellectis: Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Celgene: Research Funding; Astra Zeneca: Research Funding; Pharmacyclics: Research Funding; Abbvie: Research Funding; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Servier: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novimmune: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees. Thompson:AbbVie: Honoraria, Research Funding; Pharmacyclics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnologies: Research Funding; Genentech: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Honoraria, Membership on an entity's Board of Directors or advisory committees. Kadia:Pfizer: Consultancy, Research Funding; Jazz: Consultancy, Research Funding; BMS: Research Funding; Novartis: Consultancy; BMS: Research Funding; Celgene: Research Funding; Amgen: Consultancy, Research Funding; Celgene: Research Funding; Abbvie: Consultancy; Takeda: Consultancy; Jazz: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Abbvie: Consultancy; Novartis: Consultancy. Pemmaraju:novartis: Research Funding; samus: Research Funding; stemline: Consultancy, Honoraria, Research Funding; daiichi sankyo: Research Funding; abbvie: Research Funding; celgene: Consultancy, Honoraria; cellectis: Research Funding; plexxikon: Research Funding; Affymetrix: Research Funding; SagerStrong Foundation: Research Funding. Khoury:Stemline Therapeutics: Research Funding. O'Brien:Aptose Biosciences Inc.: Consultancy; Vaniam Group LLC: Consultancy; Pfizer: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Regeneron: Research Funding; Alexion: Consultancy; Gilead: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Kite Pharma: Research Funding; Abbvie: Consultancy; Celgene: Consultancy; Astellas: Consultancy; Pharmacyclics: Consultancy, Research Funding; Acerta: Research Funding; Amgen: Consultancy; Janssen: Consultancy; Sunesis: Consultancy, Research Funding. Wierda:Genentech: Research Funding; AbbVie, Inc: Research Funding.