Nowakowski, Grzegorz S.

7556 Background: The frontline treatment for advanced follicular lymphoma has evolved with the introduction of maintenance therapy, bendamustine (Benda), obinutuzumab (G), and lenalidomide (Len). We conducted a network meta-analysis of phase 3 randomized controlled trials (RCTs) to identify the regimens with superior efficacy. Methods: Data were extracted from 7 RCTs (FOLL05, StiL NHL1, BRIGHT, PRIMA, GALLIUM, StiL NHL7, and RELEVANCE). Progression-free survival (PFS) was compared between 11 regimens with different immunochemotherapy and maintenance strategies. To incorporate direct and indirect comparisons, random-effects Bayesian network meta-analyses were conducted after adjusting for study-wise variation. The posterior inference was derived based on Markov chain Monte Carlo methods and implemented using JAGS v4.3.0. Pairwise comparison of hazard ratios (HRs) and 95% credible intervals (CIs) were calculated. Results: PFS HRs of other regimens compared to the reference regimen are summarized in the Table. Compared to Rituximab(R)-Benda, R-CHOP had inferior PFS, R-CHOP-R, G-CHOP-G, and R-Len-R had similar PFS, while R-Benda-R, R-Benda-R4 and G-Benda-G had better PFS. Compared to R-CHOP-R, G-CHOP-G and R-Len-R had similar PFS, while R-Benda-R, R-Benda-R4 and G-Benda-G had better PFS. In addition, the PFS for G-Benda-G was similar to R-Benda-R4 (HR 0.94, 95% CI 0.78-1.09) but better than R-Benda-R (HR 0.82, 95% CI 0.75-0.97). Conclusions: Compared with the commonly used R-Benda and R-CHOP-R regimens, G-CHOP-G, R-Benda-R and R-Benda-R4 had better PFS, while the chemotherapy-free regimen R-Len-R had similar PFS. [Table: see text]

7554 Background: Predicting early clinical failure in patients with untreated FL is important but difficult. Lymphoma involvement of EN sites is better detected by FDG-PET/CT than CT alone, but PET parameters are not part of the usual predictive indices. We aimed to determine the incidence and patterns of spleen and EN disease using PET/CT, and learn if they are useful in predicting early clinical failure. Methods: PET/CT images from 613 cases of newly diagnosed FL between 2003 – 2016 were retrospectively reviewed. The location, pattern, and number of EN sites, as well as splenic involvement, were recorded. Associations with outcomes were assessed using event-free survival (EFS) and overall survival (OS). Results: 49% (301/613) of patients had PET/CT-detected EN involvement, and 28% (171/613) had spleen involvement. Presence of ≥2 EN sites, spleen, bone, or soft tissue involvement, as well as a multifocal on diffuse pattern of bone involvement by imaging, were univariate predictors of EFS; presence of ≥2 EN sites and bone involvement pattern were also predictive of OS. In a multivariate analysis with FLIPI-2 factors, spleen involvement, pattern of bone involvement, and soft tissue involvement independently predicted a lower EFS (Table). When the multivariate analysis was performed using PRIMA-PI factors, the presence of ≥2 EN sites was an adverse independent prognostic factor for OS (HR 2.28; 95% CI 1.01-5.18; p=0.05). Conclusions: Baseline PET/CT identifies EN and spleen sites of disease that can predict early clinical failure of FL. These results may be useful to better identify high-risk patients and guide appropriate therapy. [Table: see text]

7520 Background: We report results of a phase 2, open-label study of durvalumab (durva) in combination with R-CHOP or R2-CHOP (R-CHOP + lenalidomide) in previously untreated, high-risk diffuse large B-cell lymphoma (DLBCL). Methods: Subjects (≥18 y; ECOG 0–2) with previously untreated, high/high-intermediate risk DLBCL (IPI ≥3/NCCN-IPI ≥4) were stratified to durva + R-CHOP (Arm A, GCB DLBCL) or R2-CHOP for 6–8 cycles (Arm B, ABC DLBCL) based on cell of origin identified by gene expression followed by durva consolidation up to month 12 from start of induction. After FDA placed clinical holds on trials including combination therapy with checkpoint inhibitors and immunomodulatory agents, the study was revised to include both ABC and GCB in Arm A (durva + R-CHOP). The primary endpoint was complete response rate (CRR) at end of induction; secondary endpoints were rate of subjects continuing to consolidation, safety, and response in biological. Results: A total of 46 subjects were treated (safety; A/B, n=43/3); median age, 62/66 y; male, 61%/67%; ECOG 2, 19%/33%; Ann Arbor stage IV, 79%/33%; bulky disease: 49%/67%; double/triple-hit lymphoma, 30%/33%. As of Aug 2, 2018, 30/3 (A/B) had completed induction therapy, and 19 subjects (A) were ongoing. CRR (95% confidence interval) at end of induction was (A) 54% (37%-71%) and (B) 67% (9%-99%); 68%/67% (A/B) continued to consolidation therapy and were progression free at month 12. Safety profile was as expected for the components of the combination regimen with no new safety signal identified. Frequent treatment-emergent adverse events (TEAEs; ≥25%; A+B) included fatigue (61%), neutropenia (52%), peripheral sensory neuropathy (50%), nausea (46%), diarrhea (28%); constipation, decreased appetite, insomnia, pyrexia (24% each); and alopecia, dizziness, dyspnea, headache, stomatitis (22% each). Grade 3/4 TEAEs occurred in 84%/100% of subjects (A/B), and 3 subjects (2/1) died with no death related to study treatment. Follow-up for efficacy and safety is ongoing. Conclusions: Durva + R-CHOP combination therapy is safe and demonstrates encouraging response rates in subjects with high-risk DLBCL including double-hit lymphoma. Clinical trial information: NCT03003520.

7514 Background: Relapse is expected in treated indolent lymphoma patients, and an unmet need exists to prolong remission with effective therapies. Lenalidomide + rituximab (R2) may improve the efficacy of next treatment by their unique mechanisms. Methods: The AUGMENT phase III study evaluated patients with R/R FL gr 1-3a (82%) and MZL (18%) after ≥ 1 prior systemic therapy (not rituximab refractory). Randomization was 1:1 to R2 (lenalidomide PO 20 mg/d, d1-21/28 X12 cycles [c] + rituximab [R] IV 375 mg/m2/wk, c1, d1, 8, 15, 22 and c2-5, d1) and R/placebo (same dosing schedule). The primary endpoint was PFS by 2007 IWG; secondary/exploratory analyses were time to next antilymphoma/chemotherapy treatment (TTNLT/TTNCT) and response to next treatment. Per regulatory guidance, PFS2 was defined as time from randomization to first PD or death from any cause after next antilymphoma treatment, or initiation of a third antilymphoma treatment. Results: Median PFS was superior for R2 over R/placebo (39.4 vs 14.1 mo; HR = 0.46; P < 0.0001). As of 22June2018, median TTNLT, TTNCT, and PFS2 were not reached for R2, and were significantly longer than R/placebo (HR = 0.54, 0.50, and 0.52, respectively). For 49/178 (28%) R2 and 80/180 (44%) R/placebo patients receiving next antilymphoma therapy, response was generally higher with R2 (57% ORR; 31% CR) than R/placebo (36% ORR; 16% CR; Table). Conclusions: These analyses suggest that R2 (vs R/placebo) prolonged time to subsequent treatment and is associated with longer PFS2, enabling greater response to next therapy. Although patient numbers were modest, it is hypothesized that patients who received R2 were generally more sensitive to subsequent therapy than those treated with R/placebo. Clinical trial information: NCT01938001. [Table: see text]

9057 Background: The incidence of CAM use among patients with cancer is higher when compared to the general population. However, there are few studies examining CAM use in NHL survivors, and limited data are available regarding beliefs in CAM. This study was conducted to examine the prevalence of CAM use in NHL, define CAM beliefs among NHL survivors, and explore differences between patients with indolent and aggressive lymphoma. Methods: Newly diagnosed lymphoma patients were prospectively enrolled within 9 months of diagnosis in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource from 2002-2008. NHL patients who completed the 3-year post diagnosis questionnaire, which includes questions regarding CAM use and beliefs, were included in this study. Chi-squared tests and Wilcoxon rank-sum tests were used to assess the association of CAM use with prognostic and demographic factors. Results: 719 patients were included with a median age of 63 years (range 22-92). 53% were male. Overall, 636 (89%) reported ever using CAM. 78% of patients used vitamins and 54% alternative therapies (chiropractic (36%) and massage therapy (24%)). Among CAM users, 141 (22%) believe CAM can assist the body to heal, 123 (19%) believe CAM can relieve cancer symptoms, 115 (18%) believe CAM use gives a feeling of control, 106 (17%) believe CAM can boost immunity, 24 (4%) believe CAM can cure cancer, and 35 (6%) believe CAM can prevent the spread of cancer. Female gender was associated with increased overall CAM use (p<0.0001) as well as use of vitamins (p<0.0001), herbal supplements (p=0.006) and alternative therapy (p=0.0002) specifically for cancer. Older age was also associated with increased vitamin use (p=0.005) and decreased herbal supplements use (p=0.008). There was no significant difference in overall CAM use between those with follicular lymphoma grades I-II (n=195, 91%) and non-relapsed diffuse large B-cell lymphoma (n=151, 87%), although massage therapy was utilized more often by FL survivors (29% versus 18%, p=0.005). Conclusions: CAM modalities are used by the majority of NHL survivors (89%). The assessment of CAM use and education regarding potential harms is imperative for the NHL survivor.

8053 Background: Lenalidomide (LEN) is an immunomodulatory agent that has shown significant single-agent anti-lymphoma activity in patients with relapsed disease and in combination may enhance the efficacy of rituximab by various mechanisms. There is limited data on the role of LEN in combination regimens for treatment-naïve patients. This phase II single arm trial was designed to evaluate tumor response, toxicity (AE) and survival with a combination of LEN, rituximab, cyclophosphamide (CTX) and dexamethasone (DEX) (LR-CD) in symptomatic untreated patients with low grade B-cell non-Hodgkin lymphoma. Methods: Eligibility required age ≥18, ECOG PS ≤2, confirmed diagnosis of low-grade B-cell lymphoma (FL1-2, SLL, MZL or LPL/WM), measurable nodes ≥2cm or IgM ≥400mg/dL(LPL/WM), ANC ≥1400/mm3, platelets ≥100,000/mm3, creatinine ≤2mg/dL, signed informed consent and in need of therapy. Treatment consisted of IV rituximab 375mg/m2 D1, oral LEN 20mg D1-21, CTX 250mg/m2 D1, 8, 15, DEX 40mg D1, 8, 15, 22 and ASA 325 mg daily in a 28 day cycle. Treatment continued 2 cycles beyond best response (max 12). Toxicity was assessed by NCI CTCAE v3.0. Results: 28 patients have enrolled at Mayo Clinic with 25 evaluable for toxicity and 21 for response: Median age 65(43-83), 72% male, FL 24%, MZL 28%, LPL/WM 38%, and SLL 4%. Median number of cycles given was 5. Overall response in 21 patients with response data is 95% (95% CI 76-100%) with 19% CR (95% CI 5-42%), and 76% PR (confirmed and unconfirmed, 95% CI 53-92%). The ORR in 8 patients with LPL/WM with response data was 88%, all PR (95% CI 47-100%). At a median f/u of 14.7 months 96% are alive without progression. 1 death (unrelated) occurred 7.7 months after completing 12 cycles of treatment. The most common grade ≥3 AEs were neutropenia (37.5%), leukopenia (16.7%), anemia (12.5%) and fatigue (12.5%). Conclusions: The combination LR-CD with the novel agent LEN is feasible, well tolerated and produces high response rates in symptomatic patients with low grade B-cell NHL. Toxicities are manageable and similar to reported data of single agent LEN.

e19055 Background: IRAK4 is a signaling modulator of Toll-like receptors (TLRs) and members of the IL-1R family. TLR/IL-1R activity is frequently dysregulated in NHL, including DLBCL and Waldenström macroglobulinemia (WM). CA-4948, an oral inhibitor of IRAK4, has demonstrated anti-tumor activity in preclinical models. Methods: Dose finding cohorts (3+3 design) will test QD or BID dosing schedule in pts with R/R NHL. Dose expansion will occur in 2 cohorts of R/R NHL with or without MYD88 mutation at the RP2D or MTD. Key eligibility criteria: age ≥ 18 years, ECOG ≤1, and adequate organ function. Objectives: safety, MTD and RP2D (primary); PK and anti-tumor activity (secondary); exploratory biomarkers and PD effects. Plasma cytokine levels are being evaluated post ex-vivo TLR stimulation in whole blood. Results: 13 pts have been treated (6 at 50 mg QD; 3 at 100 mg QD; 4 at 50 mg BID). Tumor types included DLBCL (7), FL (5), WM (1). The most frequent treatment-emergent AEs (≥10% of pts) were fatigue (23%), conjunctivitis, constipation, neutrophil count decrease, white blood cell count decrease (each 15%). One pt treated at 100 mg QD experienced Gr 3 rash which resolved following oral steroid treatment; dose reduction to 50 mg QD was tolerated without flare up. One SAE of disease progression occurred. 9 pts completed the DLT evaluation period thru Cycle 2 including 2 ongoing in Cycle 4 and 6. Preliminary PK showed that CA-4948 is rapidly absorbed with maximum plasma concentration observed 1.0 to 4.0 hrs post administration. T1/2 in plasma was about 6 hrs. Minimal to no accumulation was observed following multiple doses. Plasma exposures were dose proportional. Preliminary PD data showed, similar to murine studies, on target reduction of NF-kB-associated factors such as IL-6 post-treatment from pts with complete sample sets (N = 8). Conclusions: Current dose/schedule is well tolerated with preliminary PK and PD effects at the initial dose level. MTD has not been reached. Clinical trial information: NCT03328078.

Background: DLBCL has traditionally been classified by cell of origin (COO) subcategories based on tumor gene expression profiles which include Activated B-Cell (ABC) and Germinal Center B-Cell (GCB). Recently, using tumor samples from patients treated with RCHOP, new classification models have focused on DNA alterations. However, a comprehensive integrative approach using a large transcriptomic data set across both newly diagnosed (nd) and relapsed/refractory (r/r) DLBCL is yet to be accomplished. A robust clustering of this type will allow for identification of biologically driven DLBCL patient subgroups and may predict patient outcome and inform treatment approaches. Methods: RNAseq was performed on a total of 882 DLBCL tumor FFPE biopsies from 2 ndDLBCL cohorts (cohort 1 and 2) and 2 r/r DLBCL cohorts (cohorts 3 and 4). Cohort 1 (N=267) was commercially sourced and served as the discovery cohort. Cohort 2 (N=340) was from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER) and served as the replication cohort. Cohort 3 (N=189) was from the CC-122-ST-001 and CC-122-DLBCL-001 clinical trials (NCT01421524 and NCT02031419), and cohort 4 (N=86) was from r/r patients from the MER. Clustering input consisted of gene expression data, gene set variation analysis (GSVA) scores computed from the hallmark gene sets of MSigDB gene sets, as well as immune cell abundance estimates from a DLBCL-specific deconvolution method. An integrative clustering method iClusterPlus was applied to the input data to identify patient subgroups. A multinomial generalized linear model classifier was trained on the discovery dataset and applied to cohorts 2, 3, and 4 to assess patterns of gene expression and clinical features among the subgroups. Results: Integrative clustering identified 8 subgroups of ndDLBCL patients (DLBCL1-8; D1-D8) in cohort 1. Classifiers trained on cohort 1 were applied to cohort 2 and the same 8 clusters were identified. Among RCHOP treated patients in cohort 2, subgroups D4 (p&lt;0.01) and D8 (p&lt;0.0001) had significantly worse survival outcomes than the rest of the population. D4 comprised 21% of the MER ndDLBCL replication cohort (cohort 2) with a median event-free survival (mEFS) of 38.2 months and a median overall survival (mOS) of 80.3 months. D8 comprised 5% of the cohort with a mEFS of 7.5 months and a mOS of 12.1 months. The remaining 6 subgroups were standard risk, with mEFS ranging from 82.1 months to not reached, and none reaching mOS. The subgroups were not uniquely defined by previously known molecular classification methods such as COO or double hit signature (DHITsig), nor by clinical risk factors such as age or international prognostic index (IPI). Within D4, 92% of patients were ABC, representing a high risk subset of ABC patients. The mEFS in D4 ABCs was 38.2 months, while mEFS of non-D4 ABCs was not reached (p&lt;0.005). Transcriptomic analysis revealed a lower abundance of immune infiltration. D4 was associated with high IPI, with 49% of D4 having IPI&gt;2, compared to 33% of non-D4 with IPI&gt;2 (p&lt;0.05). D8 represented a high-risk subset which was 73% GCB. The mEFS of D8 GCBs was 5.4 months, while mEFS of non-D8 GCBs was not reached (p&lt;0.0001). Transcriptomic analysis revealed low expression of immune response and cytokine signaling pathways, consistent with the low abundance of immune cells in D8. This subgroup consisted of 63% DHITsig positive patients. Although only 20% of all DHITsig positive patients were in D8, these D8 DHITsig patients showed significantly worse survival than non-D8 DHITsig patients (mEFS 11.3 months vs. not reached, p&lt;0.0001). In the r/r DLBCL setting, D1-D8 were all present, with an increased prevalence of D4 and D8 in Cohort 3 (30% and 17%, respectively) and Cohort 4 (30% and 14%) compared to the newly diagnosed setting. Mutational data for these cohorts has been collected and is being interpreted in the context of the discovered subgroups. Conclusion: A novel integrative clustering of transformed gene expression data revealed 8 biologically homogeneous groups, two of which had inferior outcomes when treated with RCHOP therapy. Furthermore, these two subgroups were more prevalent in r/r DLBCL. This classification allows for the transcriptomic identification of high-risk patients underserved by RCHOP therapy. *Ortiz, Wenzl and Stokes contributed equally **Gandhi and Novak contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ratushny:Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Nowakowski:Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Novak:Celgene Coorperation: Research Funding.

Background With lymphoma survival rates increasing and a growing population of long-term survivors, the development of cardiovascular disease (CVD) in this patient population is of increasing importance. Anthracyclines are critical in the management of many lymphoma subtypes. However, there is a risk of developing anthracycline-induced CVD. Here, we estimate the cumulative incidence of CVD in adult lymphoma survivors and investigate risk factors associated with post diagnosis CVD. Methods Participants were from the Mayo component of the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). From 2002-2015, the MER offered enrollment to all patients with newly diagnosed lymphoma who are US residents and age &gt;18 years. Participants completed a risk factor questionnaire, and clinical and treatment data were abstracted from medical records. Patients were contacted every 6 months for the first 3 years after diagnosis and annually thereafter to assess disease status, re-treatment and new onset morbidity including CVD. CVD events, including congestive heart failure (CHF), coronary artery disease (CAD), valvular heart disease (VHD), and arrhythmia were identified and validated against medical records. CHF was validated with the Cardiovascular Health Study Criteria and/or the Framingham Criteria. CAD, arrhythmia, and VHD were validated using clinical definitions. We calculated the cumulative incidence of CVD, with death modeled as a competing risk. The association of risk factors and treatments with risk of CVD was estimated using hazard ratios (HR) and 95% confidence intervals (CI) from Cox regression with a competing risk of death. Risk factors included age, sex, diabetes, smoking, body mass index (BMI), and treatment with anthracyclines or radiation therapy. Results The study consisted of 3,063 lymphoma patients after excluding those with chronic lymphocytic leukemia and CVD prior to lymphoma diagnosis. The median age at diagnosis was 59 years (range 18-95), and 56% were males. At a median follow-up was 6.9 years (range 0.8-17.1), 640 patients (21%) had died without CVD and 485 patients self-reported CVD post lymphoma diagnosis, of which 280 (57.7%) were validated. Cardiovascular events included 86 CHF, 78 CAD, 40 VHD, and 164 arrhythmias. The cumulative incidence of CVD (Figure 1) at 5 and 10 years was 6.0% (95% 5.2%-7.0%) and 10.7% (95% CI 9.5%-12.1%), respectively. In multivariable analysis, increasing age (HR=3.93 per 5 years, p&lt;0.001), male sex (HR=1.33, p=0.03), former smoker (HR=1.04, p=0.77), current smoker (HR=1.96, p&lt;0.001), BMI&gt;30 kg/m2 (HR=1.50, p=0.01), and anthracycline treatment (HR=1.49. p&lt;0.001) were all significantly associated with risk of overall CVD, while there was no association with diabetes (HR=0.92, p=0.70) or radiation therapy (HR=1.05, p=0.78) in the multivariable model. Anthracycline use was significantly associated with increased risk of CHF (HR=2.64, p&lt;0.001) and arrhythmia (HR=1.51, p&lt;0.01), but not VHD (HR=0.83, p=0.56) or CAD (HR=1.23, p=0.31) after adjustment for the cardiac risk factors. The number of anthracycline cycles ranged from 0 to 12. 63.2% of individuals that received anthracyclines received 6 cycles. The 5-year cumulative incidence of CVD for 0, 1-5, 6, and &gt;6 anthracycline cycles was 5%, 6.9%, 7.4%, and 7.7%, respectively. Adjusting for cardiac risk factors, the number of anthracycline cycles was significantly associated with increased risk of CVD (1-5 cycles HR=1.34, p=0.11; 6 cycles HR=1.51, p&lt;0.01; &gt;6 cycles HR=2.04, p=0.03). Furthermore, the number of anthracycline cycles was associated with CHF (1-5 cycles HR=2.82, p&lt;0.001; 6 cycles HR=2.46, p&lt;0.001; &gt;6 cycles HR=5.33, p&lt;0.001) and arrhythmia (1-5 cycles HR=1.31, p=0.27; 6 cycles HR=1.60, p&lt;0.01; &gt;6 cycles HR=1.65, p=0.27). Conclusions In the modern treatment era, the risk of new onset CVD in patients with lymphoma without a history of CVD is approximately 1% per year after diagnosis. Arrhythmia and CHF were the most commonly occurring CVD events in this cohort. Both traditional CVD risk factors and treatment with anthracyclines was associated with an increased risk of developing CVD, and anthracyclines were a risk factor for arrhythmia and CHF in particular. Prevention of CVD in lymphoma patients will need to address both treatment and traditional lifestyle factors. Figure 1 Disclosures Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding; Celgene: Research Funding. Nowakowski:Selvita: Membership on an entity's Board of Directors or advisory committees; Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:NanoString: Research Funding; Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees.

Background: Disease progression (PD) after frontline IC therapy for DLBCL is a clinically significant event and only 20-40% of patients achieve durable remissions with salvage chemotherapy. Patients who experience early PD or have disease refractory to IC have especially poor outcomes. Chimeric antigen receptor T-cell therapy has emerged as a novel effective therapy for selected cases of relapsed or refractory (r/r) DLBCL, although its availability is limited by cost and logistic challenges. Simple, clinically applicable prognostic tools would be useful for selecting patients for consideration for novel therapies vs those who are more likely to be successfully managed by conventional therapies, but few have been developed for r/r DLBCL. Methods: Model building was performed in patients with PD after IC from 13 frontline, multicenter, randomized DLBCL clinical trials from the SEAL Consortium. All patients received rituximab and an anthracycline-based combination IC and were followed systematically; however therapy received, clinical, and laboratory data at progression were not available. OS was defined as time from first progression until death from any cause. Associations between variables and OS were evaluated using Cox models; splines were used to model functional forms. Validation was performed in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and Danish LYFO cohorts. Model performance was assessed using time-dependent concordance indices (c-stat), Brier scores, and calibration with metrics evaluated at two years from progression. Results: Model Development (SEAL): 1125 of 5112 patients had PD after IC. Median time to PD (TTP) was 11.8 months (IQR 6.6-23.5); median age at PD was 68 years (IQR 60-73). At a median follow-up of 21 months from PD (IQR 7-43), 732 patients (65%) had died and 24 month overall survival after PD (OS24) was 35% (95% CI: 32-38). TTP was strongly associated with post PD OS (spline p-value&lt;0.0001) with OS24 ranging from 18% in patients with TTP &lt;6 months compared to 69% in patients with TTP &gt; 36 months (Figure A). Additionally, age at PD (spline p-value&lt;0.0001) was associated with post PD OS. A model consisting of age at PD including patients 40-80 years and TTP ranging 0-60 months was created (n=1011, Figure B) due to sparse data outside these intervals. C-stat was 0.67, and the model was well calibrated (predicted OS24 = 34% vs. actual OS24 = 34%). External Validation (MER): The model was validated in 290 patients with DLBCL who initiated 2nd line therapy after PD to IC. Median age at PD was younger than the SEAL cohort at 62 years (IQR 57-70). Patients with biopsy proven indolent histology at relapse were excluded. Median TTP was 8.2 months (IQR 5.1-17.0). At a median follow-up of 87 months from PD, 201 patients (69%) had died. OS24 was 47% (95% CI: 41-53). The model showed similar concordance (c-stat=0.65), but underestimated OS24 (predicted =33% vs. 47% actual, Figure C). External Validation (LYFO): The model was validated in 599 patients with DLBCL and PD after frontline IC. Median age at PD was 67 years (IQR 60-73). Median TTP was 10.1 months (IQR 6.0-19.4). At a median follow-up of 82 months from PD, 435 patients (73%) had died. OS24 was 38% (95% CI: 34-42). The model showed similar concordance (c-stat=0.67) when applied to the LYFO cohort, but again underestimated OS24 (predicted =32% vs. 38% actual, Figure D). Case vignettes: A 74 year old patient who progressed 9 months after diagnosis would have a predicted OS24 of 20%. A 58 year old patient who progressed 32 months after diagnosis would have a predicted OS24 of 65% Conclusions: TTP to following IC is strongly associated with post-progression survival in DLBCL. We developed a model from the largest frontline clinical trial dataset in DLBCL and validated a simple to apply clinical prognostic tool in the r/r setting. The model allows better understanding of expected outcomes in r/r DLBCL and can aid design and interpretation of trial results in this setting. The model underestimated the actual survival probability when applied to non-trial validation cohorts. Recalibration of the model for transplant eligible patients and development of smartphone based point-of-care application of the model is ongoing. Figure Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees. Schmitz:Riemser: Consultancy, Honoraria; Celgene: Equity Ownership; Gilead: Honoraria; Novartis: Honoraria. Farooq:Kite Pharma: Research Funding; Celgene: Honoraria. Flowers:Optimum Rx: Consultancy; Burroughs Wellcome Fund: Research Funding; BeiGene: Consultancy, Research Funding; Karyopharm: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Bayer: Consultancy; TG Therapeutics: Research Funding; Acerta: Research Funding; Celgene: Consultancy, Research Funding; National Cancer Institute: Research Funding; Denovo Biopharma: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy; Millenium/Takeda: Research Funding; AbbVie: Consultancy, Research Funding; V Foundation: Research Funding. Frederiksen:Alexion: Research Funding; Gilead: Research Funding; Abbvie: Research Funding; Janssen Pharmaceuticals: Research Funding; Novartis: Research Funding. Cunningham:Eli Lilly: Research Funding; 4SC: Research Funding; Bayer: Research Funding; MedImmune: Research Funding; Celgene: Research Funding; AstraZeneca: Research Funding; Merrimack: Research Funding; Sanofi: Research Funding; Amgen: Research Funding; Janssen: Research Funding; Merck: Research Funding; Clovis: Research Funding. Jørgensen:Gilead: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Poeschel:Amgen: Other: Travel, accommodations, expenses; Abbvie: Other: Travel, accomodations, expenses; Hexal: Speakers Bureau; Roche: Other: Travel, accomodations, expenses. Nowakowski:F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding; Genentech, Inc.: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Seymour:Takeda: Consultancy; Celgene: Consultancy, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Research Funding, Speakers Bureau; Acerta: Consultancy; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding, Speakers Bureau. Merli:Takeda: Honoraria, Other: Travel Expenses; Gilead: Honoraria; Mundipharma: Honoraria; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel expenses, Research Funding; Sandoz: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; Janssen: Honoraria. Haioun:novartis: Honoraria; celgene: Honoraria; roche: Consultancy; celgene: Consultancy; gilead: Consultancy; takeda: Consultancy; janssen cilag: Consultancy; amgen: Honoraria; servier: Honoraria. Tilly:roche: Membership on an entity's Board of Directors or advisory committees; servier: Honoraria; merck: Honoraria; Gilead: Honoraria; Janssen: Honoraria; BMS: Honoraria; Karyopharm: Consultancy; Astra-Zeneca: Consultancy; Celgene: Consultancy, Research Funding; Roche: Consultancy. Salles:Amgen: Honoraria, Other: Educational events; BMS: Honoraria; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis, Servier, AbbVie, Karyopharm, Kite, MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Autolus: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events; Epizyme: Consultancy, Honoraria; Roche, Janssen, Gilead, Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Educational events. El-Galaly:Roche: Employment, Other: Travel support; Takeda: Other: Travel support.