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Background: IVO (Agios Pharmaceuticals, Inc.) and ENA (Celgene) are small molecules approved by the FDA for treatment of adults with R/R AML with an IDH1 or IDH2 mutation, respectively. Gain-of-function mutations in IDH1 and IDH2 alter normal DNA methylation and impair differentiation (Im et al, Leukemia 2014). IVO and ENA inhibit IDH1 and IDH2 gain-of-function mutant enzymes, respectively, with the intent of restoring differentiation. IVO and ENA carry boxed warnings for differentiation syndrome (DS), a clinical syndrome that can be fatal if not treated. Montesinos et al (Blood 2009) proposed diagnostic criteria for DS based on at least 2 of the following signs and symptoms: 1) dyspnea, 2) unexplained fever, 3) weight gain, 4) unexplained hypotension, 5) acute kidney injury, and 6) pulmonary infiltrates or pleuropericardial effusion. Patients with 2 or 3 criteria were classified as having moderate and patients with at least 4 criteria were classified as having severe DS. DS was excluded in cases with an alternative explanation (e.g. septic shock). The incidence of DS in patients treated with IVO (DiNardo et al. NEJM 2018) and ENA (Fathi et al. JAMA Oncol 2018) has been reported based on investigator and review committee determination. FDA sought to perform a systematic analysis of DS cases in patients treated with IVO or ENA based on adverse event (AE) preferred terms (PTs) and laboratory test results grouped per the Montesinos criteria. We hypothesized that using an algorithmic approach would uncover a higher incidence of DS than reported initially. Methods: We searched for cases of DS in Study AG120-C-001 for IVO and Study AG221-C-001 for ENA using PTs and laboratory data within the first 90 days of treatment, grouped per the Montesinos criteria. Patients were included in the analysis if they had been treated for R/R AML using the approved dose of IVO (n=179) or ENA (n=214). We reviewed case narratives and laboratory data for algorithmically-identified cases of DS to adjudicate whether cases were DS or unlikely DS, due to an alternative explanation (e.g., infection, disease progression). An additional query for the DS cases was performed for concomitant leukocytosis, defined using PTs Leukocytosis, Hyperleukocytosis, or White blood cell count increased, or laboratory results showing leukocyte count > 10Gi/L within 7 days of clinical signs/symptoms. Results: The algorithm identified 72/179 (40%) cases of potential DS for IVO and 86/214 (40%) for ENA. FDA reviewer adjudication revealed that roughly half of the cases identified by the algorithm were DS for IVO (34/179, 19%) and ENA (41/214, 19%). This contrasts with the DS incidence of 11% (19/179) for IVO (DiNardo et al. NEJM 2018) and 12% (26/214) for ENA (Fathi et al. JAMA Oncol 2018) reported by investigators and review committee determination, respectively. Characteristics of FDA-identified DS cases in patients treated with IVO and ENA and FDA-adjudicated complete remission (CR) + CR with partial hematologic recovery (CRh) responses to the respective drugs in patients with DS are presented in the Table. For both IVO and ENA, CR+CRh rate in patients with DS was numerically lower than that for patients without DS (IVO: 18% [95% CI 7-35%] vs. 36% [95% CI 28-45%]; ENA: 18% [95% CI 7-33%] vs. 25% [95% CI 18-32%]). Age, demographics, and cytogenetic risk of patients with FDA-identified DS were similar to those of patients without DS. Conclusions: An algorithmic analysis of AEs and laboratory tests using the Montesinos criteria led to recognition of additional cases of DS not identified by investigators for patients treated with IDH inhibitors IVO and ENA. DS occurred in roughly one in five patients treated with both drugs and grade 3 or higher adverse reactions were present in over half of cases. Leukocytosis was not always present. Patients with DS had numerically lower response rates, but firm conclusions regarding the impact on response cannot be inferred based on this post-hoc subgroup analysis. Increased recognition of signs and symptoms of DS through the framework of the Montesinos criteria may lead to earlier diagnosis and treatment, which may decrease severe complications and mortality. Furthermore, integration of the algorithmic approach into clinical trials of differentiating therapies may help to prospectively monitor the incidence and severity of DS. Disclosures No relevant conflicts of interest to declare.

BACKGROUND: Pomalidomide-dexamethasone (Pom-Dex) represents an important therapeutic advance for the treatment of patients with relapsed/refractory multiple myeloma (MM). Nonetheless, patients with lenalidomide (Len) and bortezomib (double) refractory disease have a median progression-free survival of only 3.7 months with the combination, thus highlighting the need for further progress. Ixazomib, a novel, oral proteasome inhibitor, has pharmacodynamic properties that may allow for improved proteasome inhibition at the tumoral level and has synergistic activity in combination with IMiDs in preclinical MM models. Clinical studies have demonstrated activity as a single agent in relapsed/refractory MM and in combination with Len-Dex in newly diagnosed patients. We therefore evaluated the safety and preliminary efficacy of the combination of Pom, ixazomib and Dex in patients with Len and proteasome inhibitor (PI) refractory MM in the phase I portion of Alliance study A061202. METHODS: Key eligibility criteria included: relapsed or relapsed/refractory disease; ≥2 prior lines of therapy; double refractory disease (progression on or ≤60 days from the last dose of a Len- and PI-based therapy); ECOG performance status (PS) ≤2; absolute neutrophil count ≥1.0 x 109/L, platelets ≥50 x 109/L, creatinine clearance ≥50 mL/min; and ≤grade 2 peripheral neuropathy. Patients were treated with escalating doses of Pom and ixazomib utilizing a standard 3 + 3 dose escalation design in combination with standard dose Dex (Table 1). Patients received 2 - 4 mg of Pom on days 1 - 21; ixazomib 3 - 4 mg on days 1, 8 and 15; and Dex 40 mg (20 mg for those >75 years of age) on days 1, 8, 15 and 22 of a 28-day cycle. Patients were treated until disease progression or the development of unacceptable toxicity. RESULTS: Out of 17 evaluable patients, the median age was 64 (range 47 - 77) and the median time from diagnosis 5.5 years (range 3.3 - 8.3). Sixty-five percent, 24% and 12% had ISS stage 1, 2 and 3 disease at the start of treatment, respectively, and 65% had high-risk cytogenetics (gain of 1q, del[17p] and/or high-risk IgH translocation). All patients had an ECOG PS of 0 or 1 (59% and 41%, respectively). Of 14 patients with complete prior treatment data available, 100% had received prior Len, bortezomib and Dex, 71% alkylating agents (cyclophosphamide or low dose melphalan), 71% autologous stem cell transplant and 29% carfilzomib. Eighty-two percent were refractory to sequential Len- and bortezomib regimens, whereas 6% were refractory to a prior Len/proteasome inhibitor combination (12% not reported). Two dose limiting toxicities have occurred to date, 1 each at dose levels 3 and 4 (Table 1). Grade 3 and 4 neutropenia, thrombocytopenia and lymphopenia attributable to protocol therapy have been seen in 29%/6%, 12%/6% and 29%/0% of patients, respectively. Twelve percent of patients have experienced grade 3 infection, regardless of attribution, but none have experienced ≥grade 4 infection. The incidence of therapy-related peripheral neuropathy was 24%, none of which was ≥grade 3 in severity. Other common, therapy-related adverse events have included fatigue (53%), nausea (24%), constipation (18%), diarrhea (29%), rash (18%), tremor (24%), anxiety (18%), insomnia (29%) and edema (24%), all of which were ≤grade 2 in severity. Fifty-three percent of patients had at least 1 of the 3 medications dose reduced, and 35% experienced dose delays. To date, 1 patient has discontinued therapy due to adverse events and 1 due to refusal of further therapy. Of 13 patients receiving >1 cycle of therapy, the best overall response rate was 62% (7 partial responses, 1 very good partial response). CONCLUSIONS: The Pom, ixazomib and Dex combination has demonstrated an acceptable toxicity profile thus far with encouraging preliminary efficacy. Updated results of the phase I portion of the study will be presented at the meeting, including the maximum tolerated dose that will be used in the randomized, phase II portion of the study, in which the 3-drug combination will be compared with Pom-Dex in double refractory MM patients. ClinicalTrials.gov Identifier: NCT02004275. Supported by U10CA180821, U10CA180882. Table 1. Dose Level Pomalidomide Dose (mg) Ixazomib Dose (mg) DLT Evaluable DLTs 1 2 3 3 None 2 3 3 3 None 3 4 3 6 1 febrile neutropenia 4‡ 4 4 4 1 grade 4 thrombocytopenia lasting 8 days ‡enrollment into dose level 4 is complete. Disclosures Voorhees: Janssen, Celgene, GlaxoSmithKline, Onyx Pharmaceuticals and Oncopeptides: Consultancy, Research Funding; Array BioPharma, Celgene, GlaxoSmithKline, and Oncopeptides: Consultancy; Millennium/Takeda and Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Off Label Use: We will discuss the use of Ixazomib, an agent that is not FDA approved, in combination with pomalidomide and dexamethasone for the treatment of multiple myeloma.. Richardson:Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gentium S.p.A.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium Takeda: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees.

Introduction There are mounting data associating obesity with an increased risk of developing acute myeloid leukemia (AML) and acute promyelocytic leukemia (APML). However, the role of obesity in the outcome of patients with AML and APML has not been extensively evaluated. In this study, we assess the effect of obesity in relapse and survival rates of clinical trial patients with AML and APML. Methods Data on patients ≥18 years from 4 prospective clinical trials from the Cancer and Leukemia Group B (Alliance) were pooled for this analysis (n=2,093). This reflects exclusion of 72 patients deemed ineligible or non-evaluable, and 8 patients without height or weight data. Three studies were in de novo AML: 9621 (n=393), 10503 (n=541) and 19808 (n=714), and one study was in de novo APML: 9710 (n=445). BMI was calculated following the formula (BMI=weight/height2) and categorized according to WHO criteria as underweight/normal (BMI Results In the AML cohort (n=1,648), median age was 46 years (range: 18-66 years), 53% were men, 87% had PS 0-1, 17% were non-white and 7% Hispanic. For the APML cohort (n=445), median age was 43 years (range: 18-80 years), 52% were male, 82% had PS 0-1, 18% were non-white and 11% Hispanic. The proportion of obesity at study entry for AML and APML was 38% and 50%, respectively. APML patients experienced a superior OS than AML patients (5-year OS: 81% vs. 37%). In AML, age, gender and race were all significantly related to whether or not patients were obese in univariate and multivariate settings. In APML, only age and race were significantly associated with obesity. Median follow-up time was 6.8 years for AML and 8.5 years for APML patients. In the AML cohort, 1058 of 1648 patients have died, and 813 of 1246 patients evaluable for DFS had an event. For APML, 102 of 445 patients died and 106 of 401 patients evaluable for DFS had an event. DFS and OS distributions were not significantly different in obese vs. non-obese AML patients (p=0.8 and p=0.6, respectively). However, obese APML patients had a significantly shorter OS than non-obese patients (HR=1.61, p=0.02; 5-year OS rates: 76% vs. 85%, respectively). Similarly, obese APML patients tended to have shorter DFS than non-obese patients (HR=1.49, p=0.05; 5-year DFS rates: 74% vs. 82%, respectively). Only focusing on those APML patients between 18-60 years of age, differential OS and DFS in obese patients was more pronounced with corresponding worse survival (OS: HR=2.13, p=0.003; DFS: HR=1.75, p=0.015). Conclusion Obesity did not influence OS and DFS in AML. However, in a multivariate analysis, obese APML patients had significantly inferior OS and DFS than non-obese patients. Multivariate analysis suggests that the adverse impact of obesity in APML is independent of age, sex, performance and race/ethnicity. Previous studies have suggested that obesity is a risk factor for developing APML; we now show that obesity at diagnosis also confers a worse prognosis. Reasons for our findings could include potential pharmacological issues, such as relative dose intensity, which needs further research. Moreover, it will be necessary to determine if our findings will be replicated in patients with APML treated without chemotherapy as is now becoming the standard of care for those who present with white blood cell counts Disclosures: No relevant conflicts of interest to declare.

Abstract 3535 Background: AYAs with ALL are increasingly recognized as a distinct population with unique biomedical and psychosocial characteristics. However, little is known about factors that may influence participation in, and compliance with, the challenging treatment regimens that are currently being tested in this patient population. U.S. Intergroup trial C10403 was designed to prospectively evaluate a successful pediatric treatment approach in AYAs with ALL, with an additional aim to assess demographics, social support, and potential barriers to care that may impact outcomes. We describe here for the first time the baseline characteristics of patients enrolled on C10403 in order to begin to understand the personal challenges they face during treatment. Methods: Self-administered surveys were conducted at specified time points over the course of treatment. Survey 1, which explored demographics, decision making, and social support, was administered to patients following completion of induction chemotherapy. Survey 2, which evaluated treatment delays and barriers to care, was administered after remission consolidation at about 6 months. Descriptive statistics were used to summarize patient demographics and responses to survey questions. Results: Between November, 2007 and July, 2012, 296 patients across the United States aged16–39 were enrolled on C10403; 269 signed consent to participate in the survey study. 183 (68%), 129 (48%), and 193 (72%) completed survey 1, survey 2, or either survey. Of the survey respondents, 61% were male, 73% white, 11% African American, and 11% Hispanic. Median age was 24 years (yrs) (range 17–39); 17%, 62%, and 22% were Regarding social support, 51% of AYAs still live with parents while 36% live with their own families, and 6% live alone. 97% of those AYAs report that referral to specific treatment centers was primarily initiated by a physician (78%) rather than self or family. After protocol initiation, 35% recall that some chemotherapy was missed or delayed; 43% report ≥2 treatment delays. Delays were primarily due to low blood counts (52%) or toxicity (27%); only 7% were due to modifiable patient circumstances. Most patients did not report barriers to receiving care; however 9% had childcare difficulties, 14% had conflicting commitments, 15% had trouble keeping track of appointments, 18% had difficulty with co-pays, 19% had transportation issues, and 59% report long clinic wait times. Conclusions: AYAs enrolled on C10403 tend to be white, of middle/low income, and to have been previously healthy. Contrary to what has been hypothesized about AYAs, in general, they self-report a strong social support structure, and do not perceive substantial barriers to receiving treatment. Older AYAs are more independent and report that they, rather than others, are most responsible for their own leukemia care. Additional surveys are being distributed at treatment completion that explore whether these findings persist throughout the 2–3 year period of ALL therapy and the post-treatment follow up period. Disclosures: No relevant conflicts of interest to declare.