Citations

Background: Plasmablastic lymphoma (PBL) is a rare subtype of Non-Hodgkin Lymphoma with a well-known association with HIV infection. The outcomes of PBL patients are typically described with high relapse rates and poor prognosis. (Loghavi S, J Hematol Oncol. 2015; Morscio J, Am J of Pathol. 2014; Castillo JJ, Clin Lymphoma Myeloma Leuk. 2011; Castillo JJ, Am J Hematol. 2008) There has been a paucity of data suggesting that limited stage disease (Ann Arbor stage I-II) may have a more favorable prognosis. However, due to the rarity of this disease there have been no large-scale reviews to confirm this. Thus, many patients with limited stage disease are subject to the aggressive therapy recommendations based on the poor outcomes of PBL patients as a whole. (Loghavi S, J Hematol Oncol. 2015; NCCN Guidelines, version 2.2020; Al-Malki MM, BBMT. 2014) We attempted to determine the treatment patterns and outcomes of patients with limited stage PBL. Methods: We conducted a multi-center (13 US academic centers) retrospective study of patients with limited stage (Ann Arbor stage I-II) Plasmablastic lymphoma. Determination of limited stage and diagnosis of PBL was determined by the investigators at each individual center. Patients diagnosed between 1/1/1990 and 6/1/2018 were included. Baseline demographic, clinical, laboratory, pathology, and outcomes data were extracted by retrospective chart review. Kaplan Meier was utilized for time to event analysis. Results: Baseline characteristics are included in table 1. A total of 80 patients were identified with limited stage disease. With a median follow up of 34 months the 3-yr Progression free survival (PFS) and overall survival (OS) was 71.9% and 78.7% respectively (Figure 1A and 1B). Patients that received frontline chemotherapy with (n=29) and without RT (n=36) had a 3-yr PFS and OS of 84.6% and 96.2% as compared to 64.5% and 70.8%, respectively (Figure 2A and 2B; Figure 3A and 3B). The Hazard ratio (HR) for PFS and OS for chemo (reference) vs chemo-RT was 0.47 (95% CI 0.18-1.3; P=0.131) and 0.18 (95% CI 0.04-0.84; p=0.029) respectively. The HR for PFS and OS for CHOP (n=14, reference) vs EPOCH (n=33) based regimens was 0.37 (95% CI 0.11-1.2; p=0.106) and 0.36 (95% CI 0.079-1.6; p=0.182) respectively. Patients with stage I/IE disease (n=56) had a 3-yr PFS and OS of 73.1% and 81.2% respectively. Patients with stage II/IIE disease (n=24) had a 3-yr PFS and OS of 69.3% and 73.4% respectively. Patients that received aggressive treatment (n=17) with Hyper-CVAD based regimens and/or Auto-SCT as consolidation had a 3-yr PFS and OS of 63.6% and 72.7% respectively. Patients with concomitant HIV (n=16) had a 3-yr PFS and OS of 80.8% and 77.4% respectively. Seven patients received RT alone and 6 patients had surgical resection alone as frontline therapy; 1 patient received no therapy; 1 patient received HAART therapy only and remains in CR without any other treatment for PBL 29 months after diagnosis. There were 8 deaths (10%) related to PBL, 3 deaths (4%) related to treatment of PBL (2 during frontline chemo and 1 upon relapse with salvage chemo), and 9 deaths (11%) related to other causes. The 3-yr lymphoma free survival (LFS) of the entire cohort, pts receiving chemo alone, and pts receiving chemo-RT (without including treatment related mortality (TRM) as an event) was 89.1%, 85.2%, and 100% respectively. The 3-yr LFS survival of the entire cohort, pts receiving chemo alone, and pts receiving chemo-RT (including TRM as an event) was 85.1%, 80.0%, and 96.2% respectively. Discussion: Here we report the largest review to our knowledge of limited stage PBL. Outcomes appear to be excellent with 3-yr PFS and OS of 71.9% and 78.7% respectively and a 3-yr LFS of 89.1% (85.1% when attributing TRM as an event). There was no obvious benefit to receiving aggressive therapy with H-CVAD based regimens and/or Auto-SCT. Although this is a small, uncontrolled sample size the HR for OS was improved in patients receiving frontline chemo-RT vs chemo alone 0.18 (95% CI 0.04-0.84; p=0.029). However, this did not take into account TRM with or progression while receiving frontline chemotherapy. Patients who were HIV+ had similar PFS and OS outcomes compared to the entire cohort. This retrospective study clearly demonstrates the favorable outcomes in this patient population, especially in those able to receive definitive therapy for their disease. Disclosures Hess: ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS, AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Patel:Takeda: Consultancy, Research Funding; Precision Biosciences: Research Funding; Nektar: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Poseida: Research Funding; Cellectis: Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Research Funding. Nowakowski:Nanostrings: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Kymera: Consultancy; Denovo: Consultancy; Kite: Consultancy; Celgene/BMS: Consultancy, Research Funding; Roche: Consultancy, Research Funding; MorphoSys: Consultancy, Research Funding. Chavez:Bayer: Consultancy; AbbVie: Consultancy; BeiGene: Speakers Bureau; Morphosys: Consultancy, Speakers Bureau; Merck: Research Funding; AstraZeneca: Speakers Bureau; Celgene: Consultancy; Genentech: Speakers Bureau; Epizyme: Speakers Bureau; Gilead: Consultancy; Novartis: Consultancy; Kite, a Gilead Company: Consultancy, Speakers Bureau; Karyopharm: Consultancy; Verastem: Consultancy; Pfizer: Consultancy. Hill:Beigene: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding. Maddocks:Pharmacyclics: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Karyopharm: Consultancy; ADC Therapeutics, AstraZeneca: Consultancy; BMS: Consultancy, Research Funding. Wagner-Johnston:ADC Therapeutics, Regeneron, CALIB-R, Verastem: Membership on an entity's Board of Directors or advisory committees. Kahl:AstraZeneca Pharmaceuticals LP: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Pharmacyclics LLC: Consultancy; Genentech: Consultancy; Acerta: Consultancy, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Consultancy; ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche Laboratories Inc: Consultancy. Alderuccio:ADC Therapeutics: Membership on an entity's Board of Directors or advisory committees; Forma Therapeutics: Other: Family member; Agios Pharmaceuticals: Other: Family member; Oncinfo: Honoraria; Inovio Pharmaceuticals: Other: Family member; Foundation Medicine: Other: Family member; Puma Biotechnology: Other: Family member; OncLive: Honoraria. Lossos:Janssen Biotech: Honoraria; Verastem: Consultancy, Honoraria; Janssen Scientific: Consultancy, Other; Seattle Genetics: Consultancy, Other; Stanford University: Patents & Royalties; NCI: Research Funding. Portell:Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; AbbVie: Research Funding; TG Therapeutics: Research Funding; Infinity: Research Funding; Roche/Genentech: Consultancy, Research Funding; Xencor: Research Funding. Landsburg:Celgene: Membership on an entity's Board of Directors or advisory committees; Triphase: Research Funding; Takeda: Research Funding; Curis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Speakers Bureau. Castillo:TG Therapeutics: Research Funding; Beigene: Consultancy, Research Funding; Kymera: Consultancy; Janssen: Consultancy, Research Funding; Abbvie: Research Funding; Pharmacyclics: Consultancy, Research Funding.

AbstractObjectiveTo examine the prevalence of hypogammaglobulinemia in chronic lymphocytic lymphoma (CLL) patients and to test the hypothesis that patients with hypogammaglobulinemia have a distinct clinical profile and outcome.MethodsImmunoglobulin levels (IgA, IgG, IgM, IgE) were measured in newly diagnosed, treatment naïve banked samples of 150 patients with CLL followed prospectively for outcomes. Cox regression models were used to assess the effects of clinical variables on overall survival (OS).ResultsThe median age of the selected CLL cohort was 64 years with a male predominance; 96.2% of the patients were white. Fifty‐nine deaths occurred during a median follow up of 6.8 years. Hypogammaglobulinemia in CLL was common in our cohort with 88 (58.7%, 95% CI: 50.4‐66.6%) patients having a measurable isotype deficiency. The most common Ig deficiency was IgM (44.0%). IgA deficiency or low IgE was associated with higher Rai stages as well as with higher white blood cell counts at presentation. Any immunoglobulin deficiency was not associated with overall survival.ConclusionA significant proportion of treatment‐naïve CLL patients had underlying Ig deficiencies – both in isolation and in isotype combinations. Although a deficiency of IgA or IgE was associated with more severe disease at presentation, the impact of this association was mild.

8052 Background: A significant proportion of patients with FL experience an early relapse and a subsequent poor outcome. While several prognostic indices have been developed, none were designed to predict early failure. Recently, we established that lack of intrafollicular CD4+ T-cell expression predicted risk of early failure, and integrating this microenvironment biomarker with the Follicular Lymphoma International Prognostic Index, termed BioFLIPI, further improved identification of FL patients at risk of early failure ( Blood 2019;134(suppl1):121). However, the microenvironment may be influenced by the genetic composition of tumor. We investigated whether the CD4 biomarker and BioFLIPI were impacted by genetic features of the tumor as assessed by a 23-gene expression prognostic score ( Lancet Oncol 2018;19:549-61). Methods: Of the 186 cases with FL grade 1-3A treated with immunochemotherapy (IC) in our prior study, 152 had digital expression quantification of 23 selected genes (23-GEP score), which used RNA from formalin-fixed, paraffin-embedded samples. Event-free survival (EFS) was defined as time from diagnosis to progression, relapse, retreatment, or death. Early failure was defined as failing to achieve EFS at 24 months. Risk of early failure was estimated using odds ratios (ORs) and 95% confidence intervals from logistic regression models. We also used Cox regression to assess associations with continuous EFS and overall survival (OS). Results: 28% of patients failed to achieve EFS24. Lack of CD4+ intrafollicular expression (38% of patients, OR = 2.33, p = 0.024) and high risk 23-GEP score (26% of patients, OR = 3.52, p = 0.001) each predicted early failure, and in a multivariable model that included FLIPI, both CD4+ (OR = 2.26, p = 0.046) and 23-GEP score (OR = 2.26, p = 0.0.057) remained predictors. Similarly, BioFLIPI modeled as a continuous score (1-4, OR per one point increase = 2.31, p < 0.001) predicted early failure, and the association remained (OR = 2.14, p < 0.001) when the high risk 23-GEP score (OR = 2.79, p = 0.013) was included in the model. When stratified on 23-GEP score, BioFLIPI was a stronger predictor of early failure in low risk (74%, OR = 2.51, p = 0.002) relative to high risk (26%, OR = 1.55, p = 0.27) patients. Similar patterns were observed for EFS and OS. Conclusions: CD4+ T-cell infiltrate and tumor gene expression appear to be independently predictive of early failure in newly diagnosed FL patients treated with IC. Future studies should integrate and validate these measures.

e14100 Background: Only 3-5% of adult cancer patients in the US enroll in clinical trials. Patients with organ dysfunction are often excluded from clinical trials, regardless of specific drug metabolism or relative function of the organ. The ASCO and the US FDA recommend modernizing criteria related to baseline organ function and comorbidities. In hematological malignancies, often the disease itself is the reason for organ function derangement. In order to better inform clinical trial eligibility and improve participation in the future, we evaluated the impact of baseline organ function on the potential eligibility for clinical trial enrollment for real world patients with newly diagnosed DLBCL. Methods: Consecutive, newly diagnosed lymphoma patients were offered enrollment from 2002-2015 into the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence. This analysis is based on 1270 DLBCL patients receiving immunochemotherapy. Baseline organ function parameters were identified from the exclusion criteria for hemoglobin, absolute neutrophil count (ANC), platelet count, creatinine, and bilirubin reported in recent frontline trials in DLBCL (Table). Abstracted clinical labs from the MER were used to determine the percent of patients that would be excluded based on the criteria. Results: We determined that 11-23% of MER DLBCL patients receiving standard of care frontline therapy would have been excluded in the various trials utilizing baseline organ function alone (Table). Hemoglobin and renal function had the greatest impact on exclusion. Conclusions: Current national and international (phase II and III) trials are excluding up to 23% of patients from clinical trial participation based on organ function alone in DLBCL. These data will be useful in future clinical trial development to meet ASCO recommendations to increase trial accrual, while balancing the drug toxicities and patient safety. An online tool was developed based on these results to aid future trial development. [Table: see text]

Abstract Antibody-dependent cellular cytotoxicity (ADCC) mediated by PBMC’s is believed to play an important role in the anti-tumor effects of rituximab in patients (pts) with NHL but little is known about the trafficking of PBMC’s into the involved nodes. The primary objective of this pilot study is to demonstrate the feasibility of imaging PBMC trafficking in pts with NHL prior to and following various forms of therapy, including rituximab. To date, autologous PBMC’s were harvested in 9 pts (7M, 2F, age 49–83 y) using 100 ml of peripheral blood and Ficoll-Paque density gradient for cell separation and then radiolabeled with 400–450 mCi of 111In-oxine. Total number of leukocytes in the final product ranged from 1.5–12x107 (mean=5.5x107) with %PBMC’s ranging from 40–98 (mean= 75). The radiolabeling efficiency ranged from 53 to 87% (mean = 71) Viability of PBMC’s by trypan blue exclusion was 99–100%. Eight patients were imaged at baseline and six of these also following 2 cycles of rituximab (n=5) or one cycle of R-CHOP (n=1). Imaging was performed at approximately 4, 24, and 48 h after injection of 165–300 mCi of 111In-PBMCs. No significant adverse events were observed. All 8 pts showed the expected biodistribution of PBMC’s in normal organs, such as lung (primarily at 4h) and liver and spleen (at all timepoints). There was no evidence of PBMC localization in normal lymph nodes prior to or posttherapy. In contrast, PBMC localization was seen prior to therapy in ≥ 1 known tumor lesion per pt in all 8 pts and in the 6 pts imaged posttherapy, similar or greater PBMC tumor accumulation was observed. In conclusion, our initial results demonstrate the feasibility of imaging PBMC trafficking in pts with NHL prior to and following therapy with promising initial imaging findings. Our studies could eventually help better understand the role that PBMC play in the anti-tumor effect of rituximab and prove useful in the development of combination treatments such as the use of moAbs and cytokines.

Abstract Background: FL comprises one quarter of lymphoma in the United States, presents in a heterogeneous fashion, and generates substantial debate regarding optimal management strategies. The recently published clinical prognostic index (FLIPI, BLOOD104:1258) facilitates outcome evaluation and may guide therapeutic strategy. The National LymphoCare Study (NLCS) is an ongoing disease-based longitudinal observational study designed to assess patterns of initial disease presentation including prognosis, long term treatment choices, and clinical outcomes in FL patients. Methods: Beginning March, 2004, pts were recruited from U.S. community practices and academic centers. Pts with FL diagnosed within 6 months with no prior lymphoma history are eligible for enrollment. Collected data includes histology, staging and prognostic evaluation, serial management strategies including drug choices but not doses, response to treatment, and events including relapses and death. There is no study-specific prescribed treatment regimen or intervention. The treating physician determines management for FL according to clinical judgment. Results: 992 pts were enrolled from 207 sites through April, 2005. 182 community sites enrolled 86% of subjects. Pt characteristics include median age 62y, 52.5% female, 90.6% Caucasian, 40% Gr1, 26% Gr2, 19% Gr3, 13% NOS, with highest determined Ann Arbor stage = 17% I, 15%II, 26% III, 33%IV, 8% Unk. The demographic characteristics are similar to pts in the national SEER registry (median age 64, 51% F, 91.3% Caucasian) but clinical characteristics are notable for a higher fraction of advanced stage disease. 686/992 (69%) patients had calculable FLIPI scores based on initial investigator workup. Of factors contributing to FLIPI scores, LDH was collected by investigators in 78% of pts. When correlated with age, geography, and academic/community sites, LDH collection rates differ with 90% in academic sites vs 76% in community sites (p = .0002). Distribution of FLIPI among 686 pts with complete scores are shown in Table1, and show remarkable consistency across grades. Summary: The NLCS is an ongoing study with a large and rapidly growing database combining clinical and treatment data and is the first database investigating initial workup, prognosis, and outcomes of pts in a predominantly community based U.S. population. FL pts enrolled in NLCS are similar to those in the SEER database, and should be widely generalizable to the US population. FLIPI continues to define three distinct groups in the NLCS and is independent of histologic grade. Current evaluation patterns result in 31% incomplete FLIPI scores, suggesting this useful prognostic index is underutilized. FLIPI distribution (%) Low 36 37 37 38 34 81 14 Intermed 37 31 32 28 37 14 40 High 27 32 31 34 29 5 46 Solal Celigny n=1795 NLCS n=686 NLCS Gr1 n=276 NLCS Gr2 n=188 NLCS Gr3 n=136 Stage I/II n=234 Stage III/IV n=452

Abstract Background: A significant percentage of DLBCL patients present with a composite histology, often seen as a node containing both follicular lymphoma and DLBCL or DLBCL in the node and discordant indolent lymphoma in the bone marrow. Literature from the pre-rituximab era suggests DLBCL patients with transformed lymphoma or composite histology have worse outcome than de novo DLBCL. Here we report on early events in a cohort of R-CHOP treated patients. Goal: To determine whether patients with composite lymphoma have an inferior event free survival (EFS) and overall survival (OS) compared to de novo diffuse large B-cell lymphoma when treated with R-CHOP. Methods: Newly diagnosed patients treated with an R-CHOP containing regimen were prospectively enrolled in our Lymphoma SPORE registry from 9/2002 through 6/2007. Pathology was centrally reviewed. All patients were followed for retreatment, disease progression, and death. Results: 401 DLBCL patients were enrolled; 14% (57/401) had a composite histology. 33 patients had DLBCL and another histology, predominantly follicular lymphoma (n=29), in the same node. 20 patients had a non-DLBCL histology in a distinct location from the DLBCL; this was primarily indolent lymphoma in the bone marrow (n=15). 4 patients had both. 19% (75/401) of patients died during follow-up and 30% (121/401) had an event (death due to any cause, progression, or retreatment). Median follow-up for living patients was 34 months (range, 5–73). Composite DLBCL patients had higher event-free (3 year EFS = 79%) and overall (3 year OS = 93%) survival then de novo DLBCL (3 year OS = 66%, 3 year EFS 79%), p=0.05 and p=0.005 respectively. These differences remained statistically significant after adjusting for the International Prognostic Index (IPI): EFS HR = 0.53, 95% CI: 0.29–0.97, p=0.02; OS HR=0.28, 95% CI: 0.10–0.76, p=0.002. OS and EFS for composite DLBCL more closely resembled R-CHOP treated grade III follicular lymphoma (A,B) from the same cohort (3 year EFS = 81%, 3 year OS = 93%). Improved outcome for composite DLBCL was consistent whether the additional histology was in the same node or distinct from the DLBCL. Conclusions: R-CHOP treated DLBCL patients with indolent discordant bone marrow involvement or other composite histology have improved early OS and EFS compared to de novo DLBCL. Further follow-up is needed to assess the long-term prognosis of composite DLBCL in the rituximab era. Histology N Age &gt; 60 Stage III/IV LDH &gt; ULN PS &gt; 1 &gt;2 EN Sites 3 YR EFS 3 YR OS * Denotes statistically significant difference at p=0.05 de novo DLBCL 344 58% 56% 56% 17% 22% 66% 78% Composite DLBCL 57 65% 77%* 34%* 18% 32% 79%* 93%* Figure Figure

7536 Background: While most patients (pts) with follicular lymphoma (FL) achieve an initial response to treatment, the majority relapse. Recently, Goldman et al. reported that surveillance imaging (SI) in FL is not associated with improved post-relapse outcomes and is frequently associated with false positive scans (ASH 2017). The goal of this study was to validate these findings. Methods: Pts were enrolled in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER), a prospective cohort of newly diagnosed lymphoma pts. All pts were followed for events including relapse, re-treatment, and death, with events verified by medical records. Pts eligible for this study had biopsy proven FL grade 1, 2, or 3a who had achieved a response after induction therapy and later relapsed. Initial and post-treatment management was per treating physician. Medical records were re-reviewed in pts with events for clinical details at relapse in relationship to planned follow-up visits and SI. Relapse detection was categorized either by clinical suspicion (CS) via history, exam, and/or labs; or by SI in an asymptomatic pt. Univariate survival analysis was conducted for each variable. The hazard ratio with 95% confidence interval based on Cox Proportional Hazard models was presented along with the log rank test p-value. Kaplan-Meier plots were produced to evaluate the difference in overall survival (OS) between groups. Results: 1121 FL pts were enrolled in MER from 2002-2015, of which 117 were eligible. Median age at diagnosis was 60 years (range 35-83), and 61% were men. Median time to relapse of the 117 pts was 26 months (range 9-125). At a median follow-up from relapse of 69 months (range 0.23-179), 26 pts died. Pts completed a median of 3 imaging studies (range 0-15) during post-induction surveillance. 63 relapses (56%) were detected based on CS; 50 (44%) were detected by SI; and 4 were unknown. There was no difference in OS from relapse for those with relapse detected via CS vs. SI (HR = 0.98 [0.45,2.12], p = 0.96). Conclusions: Routine SI does not appear to improve survival outcomes in FL after achieving first remission, and its common practice should be questioned. Further investigation of prognostic markers to identify high-risk FL pts who may benefit from SI is needed.

8563 Background: Optimal initial treatment of follicular lymphoma (FL) is unknown. Rituximab as monotherapy (R) or as a component of immunochemotherapy (R+Chemo) is established as effective and it is now reasonable to re-examine the role of chemotherapy dosing. We explored clinical features, systemic treatment and chemotherapy delivery with comparative effectiveness of delivered dose intensity (DDI) on outcomes. Methods: We reviewed the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource database along with medical records on newly diagnosed grade I-IIIa FL who received systemic therapy from 2002 to 2009. Presenting clinicopathologic factors, outcomes and systemic therapy details including doses of chemotherapy were collected. The event-free (EFS) and overall survival (OS) effects of systemic therapy and chemotherapy DDI were analyzed with multivariate Cox regression. Confounding effects of FLIPI, grade, stage, and age were considered in the analysis. Results: From 2002 to 2009, 631 newly diagnosed FL were enrolled. Median follow up duration was 52.7 months. We identified 322 grade I-IIIa FL treated with systemic therapy including 93 R and 229 R+Chemo. Age and stage were similarly distributed between the R and R+Chemo groups; however, patients in the R group had lower grade (p<0.01) and FLIPI (p=0.03). Multivariate analysis showed no significant differences in EFS (HR=1.24, p=0.28) or OS (HR=0.55, p=0.13) for R compared to R+Chemo. Among R-CVP or R-CHOP treated FL, DDI data were collected for 73 doxorubicin (dox) and 137 cyclophosphamide (cyc) patients. Eighty-five percent of patients received 90% or more pre-planned DDI. After controlling for confounding factors, higher cycDDI was associated with improved EFS (HR 0.55, P=0.04) and OS (HR 0.74, P=0.03). No significant OS or EFS effects of doxDDI were observed. Conclusions: Addition of chemotherapy to rituximab was not associated with a detectable difference in survival outcomes in grade I-IIIa FL at a median follow-up of 52.7 months. Among R+Chemo treated FL, chemotherapy was delivered completely in most patients and more completed delivery of cyclophosphamide was associated with improved EFS and OS.

8504 Background: Diffuse large B-cell lymphoma (DLBCL) is an aggressive lymphoma. The optimal follow-up strategy for patients (pts) in remission is not clear. The goal of this study is to determine the utility of surveillance scans in a large, prospective, multi-institutional cohort of DLBCL pts. Methods: Patients were enrolled in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER), a prospective cohort of newly diagnosed lymphoma pts. All pts were followed for events including relapse, re-treatment, and death with events verified by medical records. Patients eligible for this study had biopsy proven DLBCL and were treated with anthracycline based immunochemotherapy (IC). Initial and post-treatment management was per treating physician. Medical records were re-reviewed in pts with events for clinical details at relapse and relationship to planned follow-up visits and surveillance scans. Results: 644 pts with DLBCL treated with IC were enrolled in MER from 2002-2009. Median age was 63 years (range 18-92), 54% were men, and median f/u was 59 months (range 8-116). 537 pts entered post-treatment observation; 109 (20%) of the 537 pts relapsed and 41 died from other causes. 42% of relapses were in the first 12 months following diagnosis, 27% between 12-24 months, and 31% >24 months. In the 109 who relapsed, 62% of pts (62/100, 9 unknown) presented to their physician earlier than a planned follow-up visit due to symptoms. At the time of relapse, 68% were symptomatic, 42% of pts had abnormal physical exam, and 55% had elevated LDH; 87% of pts had ≥1 of these features. Of the 38 pts with relapse detected at a planned visit, 26 had clinical features of relapse and 12 pts had relapse detected solely by planned surveillance scan; 4 pts had relapse of low-grade or other subtype and 8 had DLBCL relapse (4 of whom had equivocal/positive PET at the end of IC). Thus, surveillance scanning detected DLBCL relapse prior to clinical manifestations in only 8/537 pts (1.5%) observed post DLBCL therapy. Conclusions: The vast majority of DLBCL relapses occur outside of planned follow-up visits and are accompanied by symptoms, physical exam, or laboratory abnormalities. Routine surveillance scans post-therapy add little to detection of DLBCL relapse.