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Abstract Background: Lenalidomide (Revlimid®) has been reported to show activity in non-Hodgkin’s Lymphoma (NHL). However, prognostic factors predicting an individual patient’s response were unavailable. Aim: To investigate prognostic factors for lenalidomide response in patients with relapsed/refractory aggressive NHL. Methods: Patients with relapsed/refractory aggressive NHL with measurable disease ≥2 cm after at least 1 prior treatment regimen were eligible. Patients received 25 mg lenalidomide orally once daily on Days 1-21 every 28 days and continued therapy for 52 weeks as tolerated or until disease progression. Response and progression were evaluated using the IWLRC methodology. Univariate analyses using Fisher’s exact test and multivariate analyses using logistic regression were conducted to investigate associations of prognostic variables with response. Results: Forty-nine patients received lenalidomide oral monotherapy. The median age was 65 (23-86) and 24 were female. Histology was diffuse large B-cell lymphoma (n=26), follicular center lymphoma grade 3 (n=5), mantle cell lymphoma (n=15) and transformed (n=3). Median time from diagnosis was 2.7 (0.4-32) years and median number of prior treatment regimens was 4 (1-8). Forty-five (92%) of the patients had received prior rituximab and 63% were rituximab-refractory. Seventeen patients (35%) exhibited an objective response (2 complete responses, 4 complete responses unconfirmed and 11 partial responses). Response to lenalidomide was the same for patients who were refractory to rituximab (30%) and those who were not (31%). Three of 4 patients who were rituximab naive responded. Multivariate analysis including IPI, ECOG PS, stage, LDH, # of extranodal sites, age, sex, # of prior regimens and time from diagnosis identified only time since last rituximab and tumor burden as correlated with response. Response to lenalidomide was associated with low tumor burden (52% for <50 cm2v 0% for ≥50 cm2, P=0.033, odds ratio=10.9) and longer time from rituximab to lenalidomide treatment (52% for ≥ 230 days v 6% for <230 days, P=0.031, odds ratio=6.6). Rituximab depletes normal host B-cells and the kinetics for their loss and recovery are consistent with the timing of lenalidomide activity following rituximab. This may be a basis for this effect. However other tumor/host biological factors may also play a role. Patients with favorable values for both prognostic factors (N=24) had a 67% response rate [RR] compared to a 4% RR for patients with unfavorable values (N=25; P< 0.001) and a progression free survival (ongoing) of 7.5 months v 1.9 months. Although absolute lymphocyte count was not selected as a prognostic indicator of response in the multivariate setting, a trend was evident in the univariate analysis (42% for > 0.6 × 109/L v 9% for ≤0.6 × 109/L, P=0.071). Conclusion: Tumor burden and host immune competence may determine the response of relapsed/refractory aggressive NHL to lenalidomide monotherapy.

17569 Background: Lenalidomide is an immunomodulatory drug of the IMiD class that has activity in multiple myeloma, myelodysplastic syndromes and chronic lymphocytic leukemia. We report preliminary results of two Phase II studies assessing the safety and efficacy of lenalidomide monotherapy in subjects with relapsed/refractory indolent or aggressive non-Hodgkin’s lymphoma (NHL). Methods: Subjects with indolent (study NHL-001) or aggressive (study NHL-002) relapsed/refractory NHL following ≥ 1 prior treatment regimen with measurable disease are eligible. Subjects receive 25 mg lenalidomide orally once daily on Days 1–21 every 28 days and continue therapy for 52 weeks as tolerated until disease progression. Response and progression are evaluated using cross sectional imaging by the NCI criteria. Results: 10 subjects (2 indolent (I), 8 aggressive (A)) of a planned 80 (40 in each study) have enrolled thus far. Median age is 66 (45–80) and 7 subjects are female. Indolent histology is follicular center lymphoma grade 1, 2 (n = 2) and aggressive histology diffuse large cell lymphoma (n = 7) and follicular center lymphoma grade 3 (n = 1). Median time from diagnosis to lenalidomide monotherapy is 2.9 years (1.1–10) and median number of prior treatment regimens per subject is 3 (1–6). Median duration of follow-up is 2 months. Of eight subjects (2 I, 6 A) evaluable for response at two months, three demonstrated a decrease in their tumor burden by 72% (I), 68% (A) and 52% (A), two subjects (2 A) exhibited stable disease and three subjects (1 I, 2 A) had disease progression. Six of the ten subjects (2 I, 4 A) demonstrated no Grade 3 or 4 adverse events. Grade 3 or 4 hematological adverse events (neutropenia, thrombocytopenia) occurred in four subjects including one febrile neutropenia and one of these four subjects also exhibited Grade 3 cellulitis. No tumor flare or tumor lysis has been observed to date. Conclusions: Preliminary data of lenalidomide monotherapy in relapsed and refractory NHL are encouraging. [Table: see text]

8052 Background: Lenalidomide (Revlimid), an immunomodulatory drug of the IMiDs class, is approved in the US for treatment of relapsed/refractory multiple myeloma and myelodysplastic syndromes associated with a deletion 5q[31] cytogenetic abnormality. Lenalidomide also has activity in chronic lymphocytic leukemia and cutaneous T-cell lymphoma. This study was designed to assess the safety and efficacy of lenalidomide in patients with relapsed/refractory aggressive non-Hodgkin's lymphoma (NHL). Methods: Patients with relapsed/refractory aggressive NHL with measurable disease after at least 1 prior treatment regimen were eligible. Patients received 25 mg lenalidomide orally once daily on Days 1–21 every 28 days and continued therapy for 52 weeks as tolerated or until disease progression. Response and progression were evaluated using the IWLRC methodology. Results: As of enrollment cut-off, 50 patients were enrolled and 49 received drug. Forty-one patients were evaluable for response. The median age was 65 (46–84) and 18 were female. Histology was diffuse large B-cell lymphoma [DLBCL] (n=21), follicular center lymphoma grade 3 [FL] (n=3), mantle cell lymphoma [MCL] (n=14) and transformed [TSF] (n=3). Median time from diagnosis to lenalidomide was 3.2 (0.4–32) years and median number of prior treatment regimens was 3 (1–7). Fourteen patients (34%) exhibited an objective response (5 complete responses unconfirmed (CRu) and 9 partial responses (PR)), 12 had stable disease (SD) for a tumor control rate (TCR) of 63% and 15 progressive disease (PD). Responses were seen in each of the aggressive histologic subtypes studied: DLBCL (5/21), MCL (6/14), FL (2/3), and TSF (1/3). Five of 11 patients (45%) with a prior stem cell transplant responded. Progression free survival although ongoing is currently > 239 (>191 - >373) days in patients experiencing CRu and > 160 (>54 - >251) days in patients with PR. Most common Grade 4 adverse events were neutropenia (8.2%) and thrombocytopenia (8.2%) while most common Grade 3 adverse events were neutropenia (22%), leukopenia (14%) and thrombocytopenia (12%). Conclusion: Lenalidomide oral monotherapy is active with manageable side effects in relapsed/refractory aggressive NHL. No significant financial relationships to disclose.

Introduction. The VES-13 is a simple, self-reported, function based tool originally developed to screen community-dwelling populations to identify persons age 65 years and older at risk of death and functional decline, including death in the next 12 months. The VES-13 items include patient's age, self-rated overall health status, functional limitations in physical activity, and functional disabilities in more complex activities of daily living. As part of the Lymphoma Epidemiology of Outcomes (LEO) cohort study, we collected self-reported VES-13 data at study enrollment on all participants regardless of age, and here we report on the prevalence of vulnerable status defined by the VES-13 and its association with 1-year mortality, overall, stratified at age 65 years, and in the subset of diffuse large B-cell lymphoma (DLBCL) treated with immunochemotherapy. Methods. From 7/2015 to 6/2017, 3253 participants with NHL were enrolled within 6 months of their diagnosis into the LEO cohort. 2004 were evaluable on VES-13, and 1183 (59%) completed it before the initiation of therapy. VES-13 scores range from a minimum of 0 (low risk for decline) to a maximum of 10 (greatest risk for decline), and a score ≥3 was classified as vulnerable. Clinical, pathology and treatment data were abstracted using a standard protocol, and participants were contacted every 6 months for the first three years and then annually thereafter to identify outcomes. Medical records were reviewed by LEO clinicians to classify cause of death according to a standard protocol. Therapy was determined by the treating physician, and this was independent of knowledge of the VES-13 score. The association of VES-13 with 1-year mortality from date of diagnosis was estimated using odds ratios (OR) and 95% confidence intervals (CI) from logistic regression models, which also provided model c-statistics. Results. The median age of the 2004 participants in this analysis was 62 years (range 18-94); 57% were male; 54% were ≥65 years; and 28% had a normal body mass index (BMI), 1% were underweight, 35% were overweight, and 36% were obese. Clinically, 59% of participants had an aggressive subtype, 65% were stage III-IV, 24% had B-symptoms, and 11% had a performance status (PS) of ≥2. Overall, 28% of participants were classified as vulnerable (95% CI 26%-30%), with a higher prevalence among those completing the survey after initiation of therapy (38%, 95% 34%-41%) versus before initiation of therapy (22%, 95% CI 20%-24%), and a higher prevalence for those ≥65 years (32%, 95% CI 29%-34%) versus <65 (25%, 95% CI 22%-28%). During the first year of follow-up, there were 147 deaths, with 61% due to lymphoma, 14% therapy-related, 12% due to another malignancy, 3% other causes, and 10% unknown. Significant univariate predictors of 1-year mortality included vulnerable status, older age, PS 2+, stage III-IV, aggressive subtype, lower quality of life score, lower BMI, and 1 or more comorbidities, and were included the backward stepwise modeling. Vulnerable status (OR=3.26, 95% CI 2.15-4.96) was retained in the final model that also included age, PS, stage, and NHL subtype (Table), with a model c-statistic of 0.81. As shown in the Table, these associations were similar whether VES-13 was assessed before (c-statistic 0.77) or after (c-statistic 0.81) initiation of therapy. After adjustment for age, PS, stage and NHL subtype, vulnerable status predicted 1-year mortality in participants ≥65 years (OR=1.96, 95% CI 1.15-3.36; model c-statistic 0.80) as well as <65 years (OR=6.38, 95% CI 3.07-13.3; model c-statistic 0.83). Finally, in the DLBCL patients treated with immunochemotherapy (N=521), vulnerable status (38% of patients) also predicted 1-year mortality (OR=2.11, 95% CI 1.05-4.26) after adjusting for age, PS and stage (model c-statistic 0.78). Conclusion. Based on a self-administered VES-13, 28% of newly diagnosed NHL patients in the LEO cohort were classified as vulnerable, including 25% of those <65 years, and vulnerable status was a strong predictor of 1-year-mortality, even in the subset of DLBCL patients treated with presumed curative intent. These results highlight the potential value of screening for vulnerable status overall and across a wider age spectrum in order to optimize patient management and reduce early mortality. Disclosures Martin: Karyopharm: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Teneobio: Consultancy. Casulo:Gilead: Honoraria, Other: Travel, accommodation, expenses; Celgene: Research Funding; Roche: Other: Travel, accommodation, expenses. Cohen:Takeda Pharmaceuticals North America, Inc.: Research Funding; Bristol-Meyers Squibb Company: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; LAM Therapeutics: Research Funding; UNUM: Research Funding; Gilead/Kite: Consultancy; Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Genentech, Inc.: Consultancy, Research Funding. Farooq:Kite Pharma: Research Funding; Celgene: Honoraria. Friedberg:Acerta: Other: Data & Safety Monitoring Committee; Bayer: Honoraria, Other: Data & Safety Monitoring Committee. Kahl:Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; BeiGene: Consultancy; TG Therapeutics: Consultancy. Lossos:Janssen Scientific: Membership on an entity's Board of Directors or advisory committees; NIH: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Maurer:Nanostring: Research Funding; Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees. Nastoupil:Spectrum: Honoraria; Genentech, Inc.: Honoraria, Research Funding; Gilead: Honoraria; Janssen: Honoraria, Research Funding; Novartis: Honoraria; TG Therapeutics: Honoraria, Research Funding; Bayer: Honoraria; Celgene: Honoraria, Research Funding. Rutherford:Heron: Consultancy, Honoraria; Janssen Scientific Affairs: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Juno Therapeutics Inc: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Verastem: Consultancy, Honoraria; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees. Flowers:National Cancer Institute: Research Funding; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Bayer: Consultancy; Spectrum: Consultancy; Karyopharm: Consultancy; Acerta: Research Funding; TG Therapeutics: Research Funding; Millenium/Takeda: Research Funding; AstraZeneca: Consultancy; Optimum Rx: Consultancy; V Foundation: Research Funding; Celgene: Consultancy, Research Funding; Burroughs Wellcome Fund: Research Funding; Denovo Biopharma: Consultancy; Gilead: Consultancy, Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding.

INTRODUCTION: EMZL is a heterogeneous disease with variable risk for relapse and progression. Based on age ≥70 years, stage III-IV and elevated LDH, Thieblemont et al (Blood. 2017) developed the MALT-IPI to identify high-risk patients. In this index, disease characteristics (stage and LDH) account for 66% while a disease nonspecific characteristic (age) for 33% of the index score. We reported (Am J Hematol. 2019) that EMZL with multiple mucosal sites (MMS) at diagnosis is characterized by shorter survival and increased incidence of higher grade transformation. To better recognize disease-attributable high-risk patients, we developed a new EMZL prognosis score chiefly based on patient's disease characteristics. METHODS: The revised (R)-MALT-IPI was developed using a retrospective data set of 405 EMZL patients treated at the University of Miami (UM) from 1995 to 2017. Cox proportional hazards regression analysis was conducted to evaluate the effect of the potential prognostic variables on progression-free survival (PFS) and overall survival (OS) and to develop the new index R-MALTI-IPI based on PFS. Model validation was performed in two independent cohorts of EMZL patients from the University of Iowa/Mayo Clinic Molecular Epidemiology Resource (MER) database (n=297) and the IELSG-19 study (n=400) used for the development of MALT-IPI. Performance of various prognostic indices was compared using AIC statistics, and concordance c-statistics by Harrell (CH) and by Gonen and Heller (CGH). RESULTS: Among the candidate variables tested in univariable analysis, the following were statistically significant predictors of shorter PFS: age >60, age ≥70, anemia (Hb<12g/dL), stage III-IV, ECOG PS ≥2, elevated serum LDH, number of extranodal sites >1, number of nodal sites >4, and presence of MMS at diagnosis, defined as EMZL with ≥2 different extranodal sites excluding spleen and bone marrow. A stepwise Cox regression analysis yielded a multivariable model with four independent predictors of shorter PFS: age >60 (HR=1.53, p=0.010), elevated LDH (HR=1.73, p=0.004), stage III-IV (HR=2.03, p=0.0003) and presence of MMS (HR=2.78, p<0.0001). Based on this, a new index R-MALT-IPI was developed with scores ranging from 0 to 5, calculated as a sum of 1 point for age >60, elevated LDH, stage III-IV, and 2 points for MMS. The R-MALT-IPI defined 4 risk groups: low-risk (score 0 (35%), reference group), low-medium risk (score 1 (39%), HR=1.91, p=0.005), medium-high risk (score 2 (13%), HR=3.77, p<0.0001), and high-risk (score 3+ (13%), HR=8.54, p<0.0001). When compared with MALT-IPI, R-MALT-IPI better stratifies and separates high risk patients (26%) into medium-high risk and high-risk patients with a median PFS of 5.8 years (2.9-9.1) and 1.8 years (1.3-2.6) respectively, compared to 2.6 years (1.8-4.7) in the high-risk MALT-IPI patients (16.8%). The R-MALT-IPI index also distinguished patients with different OS. For validation, we analyzed R-MALT-IPI index performance in independent Iowa/Mayo Clinic MER and IELSG-19 cohorts. Both R-MALT-IPI and MALT-IPI were useful in distinguishing PFS and OS in all the cohorts. In the UM training cohort, the concordance c-statistics' values for the two indices were similar: for PFS, CH=0.6893 and CGH=0.6611 for R-MALT-IPI, and CH=0.6551 and CGH=0.6367 for MALT-IPI; for OS, CH=0.7017 and CGH=0.6813 for R-MALT-IPI, and CH=0.7029 and CGH=0.67715 for MALT-IPI. In the validation cohorts, the concordance c-statistics' values for the two indices were also similar, but slightly lower than in the UM cohort for PFS. When comparing medium-high to high-risk R-MALT-IPI groups, there was a reduction of 4 years in median PFS in the UM cohort, and reduction in median EFS of 5.6 years in the MER cohort, an important difference between these risk groups identified by the R-MALT-IPI index. CONCLUSIONS: R-MALT-IPI is a new index for EMZL centered principally on disease characteristics. Overall, there is a similar prediction of PFS (EFS) by R-MALT-IPI and MALT-IPI indexes; however, R-MALT-IPI better recognizes a high-risk group accounting for 13% of EMZL patients with short median PFS and thus obviates the waiting period needed to recognize patients with shorter EFS24. Collaborative studies addressing best treatment approach for these high-risk EMZL patients are eagerly needed. Disclosures Alderuccio: Agios: Other: Immediate family member; Foundation Medicine: Other: Immediate family member; OncLive: Consultancy; Targeted Oncology: Honoraria; Puma Biotechnology: Other: Immediate family member; Inovio Pharmaceuticals: Other: Immediate family member. Thieblemont:Cellectis: Membership on an entity's Board of Directors or advisory committees; Kyte: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Roche: Honoraria, Research Funding; Gilead: Honoraria; Novartis: Honoraria. Cerhan:Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding. Zucca:Kite, A Gilead Company: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel Grant, Research Funding; AstraZenaca: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; Merck: Research Funding; Celltrion Helathcare: Membership on an entity's Board of Directors or advisory committees; Abbvie: Other: Travel Grant. Lossos:NIH: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Janssen Scientific: Membership on an entity's Board of Directors or advisory committees.

INTRODUCTION Complete staging via bone marrow assessment is standard of practice for most newly diagnosed non-Hodgkin lymphoma (NHL) patients, though the methods and patterns of bone marrow assessment vary in clinical practice. The 2014 Lugano Classification recommends that in diffuse large B cell lymphoma (DLBCL), positron emission tomography-computed tomography (PET/CT) alone can designated advanced-stage disease in many, but not all cases. For most other NHL subtypes, obtaining bone marrow biopsy (BMB) remains recommended. We aimed to assess clinical practice patterns of marrow assessment and the performance of PET/CT in the clinical setting. METHODS The Lymphoma Epidemiology of Outcomes (LEO) cohort is a prospective cohort from 8 academic medical centers. All patients were enrolled in the cohort within 6 months of diagnosis, and prospectively followed. Patients with lymphoma enrolled in the cohort between July 2015 and June 2017 were included for study. Baseline clinical characteristics at diagnosis, whether BMB and/or PET/CT were performed, and the result of these assessments were extracted from the database. Bone marrow involvement on PET/CT was abstracted via review of radiology reports. No central review of images was utilized. RESULTS In total, 3,251 patients were included, consisting of the following subtypes: DLBCL (n=1,098), follicular lymphoma (FL n=730), mantle cell lymphoma (MCL n=302), T-cell lymphoma (TCL n=278), marginal zone lymphoma (MZL n=269), other NHL (n=505) and composite lymphoma (n=69). Other clinical characteristics are shown in table 1. Staging BMB was obtained in 78% of patients, PET/CT was obtained in 56%, both BMB and PET/CT were obtained in 46% while neither were obtained in 9% (table 1). There were significant differences in lymphoma subtype between patients having any bone marrow assessment vs no bone marrow assessment (p<0.0001). MCL (96%) and DLBCL (94%) most frequently had any bone marrow assessment, while MZL was least frequently assessed (84%). Patients undergoing any bone marrow assessment had higher median lactate dehydrogenase (247 U/L vs 206 U/L, p=0.0002). Among the 8 enrolling medical centers, the frequency of bone marrow biopsy at diagnosis ranged from 53% to 86%, and the frequency of PET/CT at diagnosis ranged from 34% to 94% (p<0.0001, table 1). Among patients with DLBCL who had positive bone marrow by either PET/CT or BMB (N=107), 41% (44/107) were positive by BMB only, 19% (20/107) were positive by PET/CT only, and 40% (43/107) were positive by both. Figure 1 shows results of similar analyses for FL, MCL, MZL, and TCL. Using BMB as a gold standard for marrow involvement, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of PET/CT for marrow assessment in DLBCL is 49%, 90%, 68% and 91%, respectively. Data for other subtypes are shown in table 2. Patients undergoing both PET/CT and BMB had lower median LDH (231 U/L vs 254 U/L, p=0.0032) than those undergoing one or neither assessments. CONCLUSION Overall, 91% of all patients with newly diagnosed NHL had bone marrow assessments via either PET/CT, BMB or both. The significant variation in the frequency of BMB and PET/CT use among the 8 centers reflects a lack of clear consensus on staging practices regarding bone marrow assessment. The sensitivity of PET/CT for detection of marrow involvement was less than 50% across all subtypes. It is possible the sensitivity of PET/CT could be improved via a centralized review process of the images, as is performed in some clinical trials, however practical approaches for implementing such reviews in clinical practice have not been developed. Between 92-100% of all positive bone marrows were detected by BMB, except in cases with DLBCL in which 19% of positive bone marrows were missed by BMB but detected by PET/CT. Thus, in our analysis, BMB more reliably captured marrow involvement that PET/CT in all subtypes in which both assessments were performed. However, neither PET/CT nor BMB alone were able to identify all cases of bone marrow involvement and use of both modalities may be necessary in cases where marrow involvement would have clinically important implications. Disclosures Rutherford: Juno Therapeutics Inc: Consultancy, Honoraria; Janssen Scientific Affairs: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Verastem: Consultancy, Honoraria; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Heron: Consultancy, Honoraria. Kahl:ADC Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy; TG Therapeutics: Consultancy; BeiGene: Consultancy. Lossos:Janssen Scientific: Membership on an entity's Board of Directors or advisory committees; NIH: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Friedberg:Acerta: Other: Data & Safety Monitoring Committee; Bayer: Honoraria, Other: Data & Safety Monitoring Committee. Casulo:Celgene: Research Funding; Roche: Other: Travel, accommodation, expenses; Gilead: Honoraria, Other: Travel, accommodation, expenses. Cohen:Astra Zeneca: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Hutchison: Research Funding; Gilead/Kite: Consultancy; Bristol-Meyers Squibb Company: Research Funding; LAM Therapeutics: Research Funding; UNUM: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; Seattle Genetics, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Genentech, Inc.: Consultancy, Research Funding. Nastoupil:TG Therapeutics: Honoraria, Research Funding; Novartis: Honoraria; Spectrum: Honoraria; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Genentech, Inc.: Honoraria, Research Funding; Gilead: Honoraria; Bayer: Honoraria. Flowers:Denovo Biopharma: Consultancy; Spectrum: Consultancy; National Cancer Institute: Research Funding; Optimum Rx: Consultancy; Burroughs Wellcome Fund: Research Funding; Acerta: Research Funding; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; TG Therapeutics: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Karyopharm: Consultancy; AstraZeneca: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; V Foundation: Research Funding; Millenium/Takeda: Research Funding; Celgene: Consultancy, Research Funding. Cerhan:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; NanoString: Research Funding. Martin:Sandoz: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Teneobio: Consultancy; I-MAB: Consultancy; Janssen: Consultancy.

Abstract Background: Bendamustine and rituximab (BR) is a commonly chosen frontline treatment for grade 1-2 (G 1-2) follicular lymphoma (FL). This regimen resulted in significantly longer progression-free survival (PFS) and less toxicity compared to R-CHOP in the STiL trial [Rummel et al., 2013] and similar results were observed when comparing BR vs. R-CHOP/R-CVP in the confirmatory BRIGHT trial [Flinn et al., 2014, updated ASCO 2017]. Importantly, patients (pts) with grade 3A (G 3A) FL were excluded from these studies, yet the conclusions are often extrapolated to the treatment of G 3A pts. Notably, G 3A pts were included in the GALLIUM trial which used both bendamustine as well as CHOP backbones. Several retrospective studies of FL pts treated with frontline R-CHOP have demonstrated equivalent or improved overall survival (OS) for G 3A relative to G 1-2 FL (Koch et al., 2016, Mustafa et al., 2017, Yuan et al., 2017, Maeshima et al., 2013). Early disease progression after diagnosis and treatment with frontline R-CHOP has been identified as a strong predictor of poor OS in FL pts [Casulo et al. 2015], but has not been assessed in pts treated with frontline BR. We retrospectively evaluated outcomes of a large cohort of FL pts treated with frontline BR and stratified the results based on histologic grade and early vs. late progression. Methods: We reviewed medical records of adult (age >18) pts with FL treated with frontline BR at 18 US cancer centers. There was no central pathology review; each academic institution confirmed the diagnosis and grade of FL. Pts with unknown grade, grade 3B, or cutaneous FL were excluded. Baseline characteristics between grades were evaluated with the Chi-Square test for categorical variables and the Mann-Whitney U for continuous variables. Outcomes were calculated from time of initiation of BR. Patients were grouped according to whether or not they had progression of disease within 24 months of BR initiation (POD24). OS and PFS were estimated using the Kaplan-Meier method and compared using the log-rank test. Results: 687 pts were included (616 G 1-2, 71 G 3A). Median age at diagnosis was 60 years (range 21-94) with 53% men. The median time from diagnosis to treatment with BR was 1 month (range 0-139). The median duration of follow up for the entire cohort was 39 months. Characteristics including age, gender, ethnicity, ECOG, stage, LDH, and FLIPI are shown in the Table, and did not significantly differ between G 1-2 and G 3A pts. Rates of complete response (CR) and partial response (PR) to BR were similar between G 1-2 and G 3A (72%/22% vs. 66%/21%, respectively, p=0.114) but progressive disease (PD) was higher in G 3A pts (11.9%) relative to G 1-2 (4.8%, p=0.025). As shown in the Figure (A and B), 3-year PFS and OS was significantly longer for G 1-2 vs. G 3A pts (75% vs. 65%, log rank p= 0.035 and 90% vs. 86%, log rank p=0.007, respectively). Seventy-six (12.3%) of the 616 G 1-2 pts and 13 (18.3%) of the 71 G 3A pts experienced POD24 (p=0.19). For pts with both G 1-2 and G 3A FL, POD24 was associated with inferior OS (3-year OS 95% vs. 57% for G 1-2 pts, log rank p<0.0001 and 3-year OS 93% vs. 37% for G 3A pts, log rank p<0.0001) compared to patients without POD24. Conclusions: G 3A FL pts have an inferior OS and are significantly more likely to have PD to frontline BR compared to G 1-2, which differs from the published experience with R-CHOP. Similar to outcomes after frontline treatment with R-CHOP, POD24 after frontline BR for FL is associated with very poor OS. Future studies are needed to address optimal frontline management of pts with G3A as well as for pts with any grade FL with POD24 after frontline BR. Disclosures Nastoupil: Novartis: Honoraria; Genentech: Honoraria, Research Funding; Gilead: Honoraria; Celgene: Honoraria, Research Funding; TG Therappeutics: Research Funding; Karus: Research Funding; Merck: Honoraria, Research Funding; Spectrum: Honoraria; Janssen: Research Funding; Juno: Honoraria. Cerhan:Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding; Nanostring: Research Funding. Maurer:Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Smith:Genentech: Research Funding; Incyte Corporation: Research Funding; Portola Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Merck Sharp and Dohme Corp.: Consultancy, Research Funding; Acerta Pharma BV: Research Funding; Seattle Genetics: Research Funding. Lossos:Affimed: Research Funding. Portell:TG therapeutics: Research Funding; Amgen: Consultancy; Kite: Research Funding; AbbVie: Research Funding; BeiGene: Research Funding; Acerta: Research Funding; Genentech/Roche: Consultancy, Research Funding; Infinity: Research Funding. Calzada:Seattle Genetics: Research Funding. Cohen:Bristol-Myers Squibb: Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Research Funding; BioInvent: Consultancy. Ghosh:Spectrum: Consultancy; SGN: Consultancy, Research Funding, Speakers Bureau; Pharmacyclics, an Abbvie Company: Consultancy, Research Funding, Speakers Bureau; TG Therapeutics: Honoraria, Research Funding; Celgene: Consultancy; Juno: Consultancy, Research Funding; Abbvie: Consultancy, Speakers Bureau; Genentech: Research Funding; F. Hoffman-La Roche Ltd: Research Funding; PCYC: Consultancy, Research Funding, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Forty seven Inc: Research Funding. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Caimi:Kite Pharma: Other: Advisory Board Participation; Genentech: Other: Advisory Board PArticipation, Research Funding; Celgene: Speakers Bureau; Kite Pharma: Other: Advisory Board Participation. Danilov:Gilead Sciences: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; Astra Zeneca: Consultancy; Genentech: Consultancy, Research Funding; Takeda Oncology: Research Funding; TG Therapeutics: Consultancy; Verastem: Consultancy, Research Funding. Martin:AstraZeneca: Consultancy; Seattle Genetics: Consultancy; Janssen: Consultancy; Kite: Consultancy; Gilead: Consultancy; Bayer: Consultancy. Kamdar:Seattle Genetics: Speakers Bureau; Genentech: Consultancy. Kahl:AstraZeneca: Consultancy; Acerta: Consultancy; Juno: Consultancy; CTI: Consultancy; Celgene: Consultancy; Gilead: Consultancy; Seattle Genetics: Consultancy; Abbvie: Consultancy; Genentech: Consultancy; ADC Therapeutics: Consultancy. Hill:Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; 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; Pharmacyclics: 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; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Pfizer: 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: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Background: To address the current and long-term unmet health needs of the growing population of patients diagnosed with non-Hodgkin lymphoma (NHL) and NHL survivors, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/) with recruitment at eight centers (Cornell University, Emory University, Mayo Clinic, MD Anderson, University of Iowa, University of Miami, University of Rochester, and Washington University). Here we report on the first two years of enrollment. Methods: All patients ≥18 years with NHL (exclusive of chronic lymphocytic leukemia) newly diagnosed within 183 days of enrollment are eligible. LEO reviews all pathology diagnoses; annotates and harmonizes all cases with clinical, epidemiologic, pathology and treatment data; builds a NHL tumor bank that includes an H&E slide, a formalin-fixed, paraffin-embedded tissue sample and extracted tumor DNA and RNA; collects peripheral blood and banks DNA, serum, plasma and buffy coat in a central biorepository; and prospectively follows patients regularly to ascertain disease progression/relapse, retreatment, transformation, second cancers, survival, updated exposures, and patient-reported outcomes. We examined the demographics, clinical characteristics, and NHL subtypes for patients enrolled in the first two years (2015-2017) in LEO Cohort and compared these characteristics to population-based registry data from the United States Surveillance, Epidemiology, and End Results (SEER) Program for 2011-2015. We also examined baseline body mass index (BMI), comorbidities and quality of life (QOL) measured with the Functional Assessment of Cancer Therapy - General (FACT-G) scores (0-100 scale) overall and by NHL subtype that were collected in LEO but not available in SEER or any other large, prospective US NHL cohort. Results: From 2015-2017, LEO enrolled 3244 NHL patients across 47 states (Figure) with a median age at diagnosis of 62 years (range, 18-94 years) and 55.9% male. Based on self-identified race/ethnicity, 85% of the participants were White, 7.4% were Black/African American, 2.6% were Asian, and 3.5% other or more than one race; 9.9% were Hispanic (regardless of race). The most common subtypes were diffuse large B-cell (DLBCL, 33.9%), follicular (FL, 22.2%), mantle cell (MCL, 9.3%), marginal zone (MZL, 8.3%), T-cell (TCL, 10.9%), and all other NHL subtypes (other NHL, 15.3%). These distributions were all within 5% of SEER data, except that 6.8% of participant in LEO were in the age 80+ years group compared to 18.5% in SEER (Table). The overall prevalence of self-reported comorbidities at enrollment was 13.5% for heart disease (range, 12.1% for FL to 16.6% for MCL), 8.8% for diabetes (range, 7.1% for FL to 9.8% for DLBCL), 4.6% for osteoporosis (range, 3.0% for MCL to 6.3% for MZL), and 5.9% for autoimmune disease (range, 2.0% for MCL to 12.6% for MZL). The median BMI was 27.9 kg/m2 (range, 26.7 kg/m2 for TCL to 28.3 kg/m2 for MZL). A total of 2151 participants completed the FACT-G with a median score of 78.7 (range, 75.9 for TCL to 83.3 for MZL). Complete IPI data were available on 2296 participants: 40.4% IPI 0-1, 32.7% IPI 2, 18.3% IPI 3, 8.7% IPI 4-5. Overall, 73.7% of participants were initially treated with systemic therapy (range, 40.0% for MZL and 91.8% for DLBCL); 14.5% were initially managed with observation (range, 1.4% DLBCL and 31.8% for FL); and 2.0% were initially manage with radiotherapy (range, 0.2% for MCL and 3.8% for DLBCL). Outcomes are being prospectively collected. Conclusions: LEO is a large and diverse cohort of newly diagnosed NHL patients and the first two years of enrollment reflects the broader United States NHL population. Enrollment is ongoing. This unique resource will enable examination of the interactions among a broad array of clinical and molecular factors and their impact on multiple outcomes, to improve prognostication, identify new approaches to improve outcomes and survivorship, and facilitate clinical trials using this infrastructure. Disclosures Flowers: Acerta: Research Funding; Pharmacyclics/ Janssen: Consultancy; OptumRx: Consultancy; Janssen Pharmaceutical: Research Funding; V Foundation: Research Funding; Burroughs Wellcome Fund: Research Funding; Spectrum: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Abbvie: Consultancy, Research Funding; Bayer: Consultancy; Millennium/Takeda: Research Funding; Abbvie: Research Funding; Celgene: Research Funding; Gilead: Consultancy; BeiGene: Research Funding; Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Genentech/Roche: Consultancy; Gilead: Research Funding; Genentech/Roche: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Pharmacyclics: Research Funding. Nastoupil:TG Therappeutics: Research Funding; Merck: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Research Funding; Spectrum: Honoraria; Gilead: Honoraria; Genentech: Honoraria, Research Funding; Karus: Research Funding; Novartis: Honoraria; Juno: Honoraria. Kahl:Acerta: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Juno: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy. Casulo:Celgene: Research Funding; Gilead: Honoraria. Friedberg:Bayer: Honoraria. Lossos:Affimed: Research Funding. Martin:Seattle Genetics: Consultancy; Kite: Consultancy; Janssen: Consultancy; Gilead: Consultancy; Bayer: Consultancy; AstraZeneca: Consultancy. Leonard:Bayer: Consultancy; Celgene: Consultancy; Biotest: Consultancy; United Therapeutics: Consultancy; BMS: Consultancy; MEI Pharma: Consultancy; Juno: Consultancy; Sutro: Consultancy; Karyopharm: Consultancy; ADC Therapeutics: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Genentech/Roche: Consultancy; Novartis: Consultancy. Bernal-Mizrachi:Kodikaz Therapeutic Solutions: Consultancy, Equity Ownership; Takeda Pharmaceutical Company: Research Funding. Maurer:Morphosys: Research Funding; Nanostring: Research Funding; Celgene: Research Funding. Cerhan:Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.

Abstract Background AFM13 is a bispecific, tetravalent NK cell-engaging antibody construct binding to CD30 on CD30+ tumor cells and CD16A on NK cells. By engaging CD16A-positive NK cells, AFM13 leads to NK cell-mediated killing of CD30-positive lymphoma cells (Reusch et al., 2014) making it an attractive agent to target classical Hodgkin lymphoma (HL). Pembrolizumab is a PD-1 blocking antibody which has shown high single-agent response rates in patients (pts) with relapsed/refractory HL (RRHL; Armand et al., 2016, Chen et al., 2017). AFM13 has shown clinical activity in RRHL as a single agent in a preceding Phase 1 study (Rothe et al., 2015). Preclinical in vivo data of the combination of AFM13 with PD-1 blockade showed synergistic activity and the potential for induction of cross-talk between innate and adaptive immunity (Zhao et al., 2016). We hypothesize that the combination of the two agents could improve outcomes in pts with RRHL. Methods This Phase 1b study is evaluating the safety and tolerability of the combination of AFM13 with pembrolizumab (Keytruda) as salvage therapy after failure of standard therapies including brentuximab vedotin (BV) in HL (NCT02665650). Pts receive escalating doses of AFM13 in combination with pembrolizumab at a dose of 200 mg flat administered every 3 weeks following a classical 3+3 design, followed by enrollment into an extension cohort at the maximum tolerated dose (MTD)/maximum administered dose (MAD). Response assessment is performed every 12 weeks by PET/CT according to the Lugano Classification (Cheson et al., 2014). The main objectives of the study is to ascertain the MTD/MAD along with the preliminary efficacy of the combination. Results As of June 29, 2018, 30 pts have been enrolled into the study. The median age is 34 years (range, 18-73), with a median of 4 (range 3-7) prior lines of therapy. All pts had relapsed or refractory disease (43% relapsed, 57% refractory) and had failed standard treatments including BV and 43% of pts (13/30) had BV as their latest therapy. Thirty seven percent (11/30) had undergone prior autologous stem cell transplantation. All 30 pts have completed the 6-week dose-limiting toxicity (DLT) observation period. Twelve pts were enrolled into the dose escalation cohorts (Cohorts 1 (n=3), 2 (n=3), and 3 (n=6)) and 18 into the Extension Cohort, with a total of 24 patients treated at the MAD (dose level 3). One DLT was observed in Cohort 3 (missing ≥25% of AFM13 during the DLT period) and another observed in the Extension Cohort (G4 infusion-related reaction; IRR). The most common related adverse events (AEs) were IRRs (80%), rash (30%), pyrexia (23%), nausea (23%), diarrhea (20%), fatigue (17%), headache (17%), increased aspartate aminotransferase (13%), and increased alanine aminotransferase (10%). Treatment related G3/4 AEs included IRRs (13%), elevated AST (3%), gastritis (3%), hypotension (3%), nausea (3%), neutropenia (3%), and vomiting (3%). The majority of IRRs were manageable with standard of care measures and did not lead to treatment discontinuations. Included in the efficacy analysis were the best response from 29 evaluable pts who had at least one post-baseline disease assessment as of the data cutoff on June 29, 2018. The overall response rate (ORR) and complete response (CR) rate for evaluable pts treated at the dose and schedule chosen for expansion (n=23; Cohort 3 and Extension Cohort) were 87% and 35% by the investigator-confirmed assessment, respectively. Independent assessment resulted in an ORR of 87% and CR rate of 39% for these pts. Updated data for all 30 patients will be presented at the meeting. Conclusions The combination of AFM13 and pembrolizumab is a well-tolerated salvage therapy in pts with RRHL. IRRs were the most frequently observed adverse events; however, most of these events were of mild or moderate severity and manageable. Both the ORR and CR rate compare favorably to monotherapy pembrolizumab in a similar RRHL population (Chen et al., 2017). The combination of AFM13 and pembrolizumab could be a potential new therapeutic option for HL patients. Disclosures Bartlett: Immune Design: Research Funding; Affimed: Research Funding; Bristol-Meyers Squibb: Research Funding; Merck & Co: Research Funding; Pharmacyclics: Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Forty Seven: Research Funding; Novartis: Research Funding; Novartis: Research Funding; Millennium: Research Funding; ImaginAB: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astra Zeneca: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees. Chen:Affimed: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Genentech Inc.: Consultancy; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Merck & Co., Inc.: Consultancy, Research Funding, Speakers Bureau; Millennium Pharmaceuticals: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding. Domingo-Domenech:Affimed: Research Funding. Forero-Torres:Affimed: Research Funding. Garcia-Sanz:Affimed: Research Funding. Devata:Affimed: Research Funding. Rodriguez Izquierdo:Affimed: Research Funding. Lossos:Affimed: Research Funding. Reeder:Affimed: Research Funding. Sher:Affimed: Research Funding. Choe-Juliak:Affimed: Employment. Prier:Affimed: Research Funding. Schwarz:Affimed: Employment. Strassz:Affimed: Employment. Alland:Affimed: Employment. Ansell:Bristol-Myers Squibb: Research Funding; Celldex: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Pfizer: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Merck & Co: Research Funding; Affimed: Research Funding; Takeda: Research Funding.

Abstract Abstract 94 Background: Lymphoma diagnosed during pregnancy is a rare occurrence. Further, there is heterogeneity in clinical presentation and a range of lymphoma histologies resulting in a continued deficiency of lymphoma-specific data in the literature regarding prognosis, optimal therapy, maternal complications, and fetal outcome. Methods: A comprehensive retrospective analysis was completed for patients (pts) diagnosed (dx) with Hodgkin lymphoma (HL) or non-Hodgkin lymphoma (NHL) during pregnancy at 9 large U.S. academic centers over a 13-year period (1998–2011). The vast majority of cases were co-managed with high-risk maternal fetal medicine. Data on maternal disease characteristics, treatment details, obstetric complications, and fetal outcomes were analyzed. Results: 88 cases were identified with complete data available in 82. The median age of pts was 31 yrs (18–40). Lymphoma dx occurred at a median of 24 weeks (wks) gestation (5–40). 15% of pts were dx during the 1st trimester, 46% during the 2nd trimester, 35% during the 3rd trimester, while 4% (n=3) of pts had a pre-existing NHL dx (follicular lymphoma (FL)). 52% (n=43) of pts had NHL and 48% (n=39) HL. Of NHL cases, 83% (n=33) were B-cell and 17% (n=10) T-cell. B-cell histologies were DLBCL n=23 (including 2 primary CNS and 1 'double hit' NHL), FL n=5 (including 1 leukemic phase FL), Burkitt's lymphoma n=3, and mixed histology n=1; T-cell histologies were anaplastic large cell n=6, PTCL not otherwise specified n=2, and T-cell/NK NHL n=2. Pts with B-cell NHL and HL were dx at a median age of 29 yrs (range, 18–40), while T-cell NHL pts were dx at a median of 34 years (19–37). MRI without gadolinium was the most common imaging modality utilized for staging. 63% of NHL and 19% of HL pts had stage III/IV disease (25% of HL with stage IIB). Pregnancy was terminated in 6 pts (n=4 aggressive NHL and n=2 HD) to enable immediate chemotherapy (five in the 1st trimester [at 5, 8, 10, 10, and 12 wks] and 1 pt in the early 2nd trimester who required high-dose methotrexate). 48 pts (63%) initiated anti-lymphoma therapy at a median of 25 wks gestation (range, 13–37) with 79% of pts initiating therapy in the 2nd trimester (see Table 1). The median gestation at time of lymphoma dx for pts who received intra-partum treatment was 20 wks vs 34 wks for pts who had therapy deferred to post-delivery (p<0.0001). The overall response rate among pts who received therapy was 87% (74% complete remission). Notably, gestation went to full-term in 54% with delivery occurring at a median of 37 wks (31–40). Therapy was deferred until post-delivery in 28 pts (37%) and the majority of these pregnancies were also carried to term (median delivery at 38 wks). At a median follow-up of 41 months (6–157), the 3-year PFS and OS for all pts were 79% and 89% respectively. Histology-specific 3-year PFS and OS were: B-cell NHL: 73% and 82%, respectively; T-cell NHL: 50% and 90%, respectively; and HL: 90% and 95%, respectively (Figure 1). Detailed obstetrical information was available in 59 pts. There were minimal pre-term complications, the most common being induction of labor in 45%. Perinatal events included spontaneous rupture of membranes in 5% and pre-eclampsia in 8%. Further, there were no differences in these events detected among pts who received intra-partum treatment vs deferred therapy. No episodes of chorioamnionitis or endometritis were noted. There was 1 stillbirth that occurred at 19 wks gestation in a 34-year-old pt with double-hit NHL following 1 cycle of R-CHOP. The median birth weight of infants was 2427 grams (1005–5262) with no difference among pts who received intra-partum chemotherapy vs not (2637 grams vs 2212 grams, respectively; p=NS). Microcephaly was reported in 1 case following 4 intra-partum cycles of CHOP for DLBCL; there were otherwise no malformations detected. Conclusions: To our knowledge, this represents one of the largest experiences reported of lymphoma in pregnancy. Our data show that standard NHL and HL chemotherapeutic regimens (without anti-metabolites) administered during the 2nd and 3rd trimester, including as early as 13 wks gestation in select cases, is associated with minimal maternal complications or fetal detriment. In addition, pts with low risk clinical scenarios (e.g., indolent NHL and/or late gestational dx) had therapy safely deferred to post-partum. In our experience, this approach was associated with overall expected lymphoma-related survival. Disclosures: No relevant conflicts of interest to declare.