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Neoadjuvant chemotherapy (NAC) is increasingly used for operable breast cancer (BC). Appropriate radiation therapy (RT) fields (ie, whole breast [WB] ± regional nodal irradiation [RNI]) in patients who were clinically node positive (cN1) but convert to pathologically node negative (ypN0) after NAC are unknown and the subject of the accruing NSABP B-51 trial. We sought to compare outcomes between WB RT with or without RNI following breast conservation and sentinel lymph node biopsy (SLNB) alone in cN1, ypN0 women following NAC.We identified all BC patients with cN1, ypN0 who underwent NAC followed by lumpectomy and SLNB between 2006 and 2015 in the National Cancer Database. RNI utilization was evaluated using Cochran-Armitage test. Overall survival between WB RT alone versus WB + RNI was compared using Kaplan-Meier with and without propensity score-based weighted adjustment and multivariable (MVA) Cox proportional hazards.From 2006 to 2015, RNI use increased from 48.13% to 62.13% (Pfor trend.001). The 10-year survival for WB alone versus WB + RNI was 83.6% and 79.5%, respectively (P= .14). On MVA analysis, the addition of RNI compared to WB alone was not associated with a survival benefit (WB vs. WB + RNI: hazard ratio 0.80, 95% confidence interval, 0.58-1.11, P= .19). Results were unchanged after propensity score-based adjustment.For women with cN1 BC who convert to ypN0 following NAC and breast conserving surgery with SLNB alone, more extensive RNI may not provide a long-term survival benefit. Prospective validation via the NSABP B-51 trial will be essential.

Background Several immune checkpoint inhibitors (ICIs) are approved for the treatment of advanced urothelial carcinoma (UC). There are limited biomarkers for ICI-treated patients with UC. We investigated the association between body composition and clinical outcomes in ICI-treated UC patients. Materials and Methods We conducted a retrospective analysis of 70 ICI-treated patients with advanced UC at Winship Cancer Institute from 2015 to 2020. Baseline computed tomography images within 2 months of ICI initiation were collected at mid-L3 and muscle and fat compartments (subcutaneous, intermuscular, and visceral) were segmented using SliceOMatic v5.0 (TomoVision, Magog, Canada). A prognostic body composition risk score (high: 0–1, intermediate: 2–3, or low-risk: 4) was created based on the β coefficient from the multivariate Cox model (MVA) following best-subset variable selection. Our body composition risk score was skeletal muscle index (SMI) + 2 × attenuated skeletal muscle (SM) mean + visceral fat index (VFI). Concordance statistics (C-statistics) were used to quantify the discriminatory magnitude of the predictive model. Results Most patients (70%) were men and the majority received ICIs in the second- (46%) or third-line (21%) setting. High-risk patients had significantly shorter overall survival (OS; hazard ratio [HR], 6.72; p Conclusion Body composition variables such as SMI, SM mean, and VFI may be prognostic and predictive of clinical outcomes in ICI-treated patients with UC. Larger, prospective studies are warranted to validate this hypothesis-generating data. Implications for Practice This study developed a prognostic body composition risk scoring system using radiographic biomarkers for patients with bladder cancer treated with immunotherapy. The study found that the high-risk patients had significantly worse clinical outcomes. Notably, the study's model was better at predicting outcomes than body mass index. Importantly, these results suggest that radiographic measures of body composition should be considered for inclusion in updated prognostic models for patients with urothelial carcinoma treated with immunotherapy. These findings are useful for practicing oncologists in the academic or community setting, particularly given that baseline imaging is routine for patients starting on treatment with immunotherapy.

INTRODUCTION: While most patients with mantle cell lymphoma (MCL) receive therapy shortly after diagnosis, a subset of patients with indolent-behaving disease can safely defer treatment. In this subgroup, we evaluated the importance of treatment intensity in patients with MCL who defer initial therapy. METHODS: Out of 1134 patients with MCL from 12 academic centers, we analyzed 219 patients who initiated therapy at least 90 days after diagnosis. Patients who received induction with high-dose cytarabine and/or autologous stem cell transplantation (ASCT) in first remission were considered to have received intensive therapy (n = 88) while all other approaches were non-intensive (n = 131). RESULTS: There was no difference in progression-free (PFS; P = .224) or overall survival (OS; P = .167) in deferred patients who received non-intensive vs. intensive therapy. Additionally, univariate and multivariate Cox proportional hazards models were performed for PFS and OS. Treatment at an academic center (HR 0.43, P = .015) was associated with improved OS in both univariate and multivariate models, while intensity of treatment was not associated with improved OS in either model. CONCLUSIONS: These results indicate that intensified initial treatment is not associated with improved survival after deferring initial therapy, although prospective studies are needed to determine which of these patients with MCL may benefit from intensive therapy.

Background Immune checkpoint inhibitor (ICI) therapy is highly effective in metastatic mismatch repair-deficient (MMR-D) colorectal cancer (CRC). In this study, we evaluated molecular and clinical predictors of ICI response in MMR-D CRC. Materials and Methods Patient databases at four cancer institutions were queried. The Fisher exact test was performed to test the association of clinical and molecular markers. The Kaplan-Meier method was used to estimate progression-free survival (PFS) and compared by the log-rank test. Twelve- and 24-month PFS rates were compared by the Z test. Results A total of 60 patients with CRC with MMR-D/microsatellite instability-high who previously received ICIs were identified. Patients with liver metastasis had a lower overall response rate as compared with other sites of metastasis (36.4% vs. 68.7%; p = .081). Patients with MLH1/PMS2 loss had worse 1-year and 2-year PFS rates compared with patients with MSH2/MSH6 loss (84.2% vs. 57.8% and 78.2% vs. 54.2%, respectively; p < .001). There were improved 1-year and 2-year PFS rates in patients with wild-type BRAF when compared with patients with BRAF V600E mutation (73.3% vs. 40%, and 73.3% vs. 26.7%; respectively; p < .001). Patients aged >65 had significantly worse PFS rates as compared with patients aged ≤65 (p < .001). Conclusion BRAF V600E mutation, MLH1 and/or PMS2 loss, as well as age >65 years and liver metastasis, may be predictive of duration of ICI response in patients with MMR-D CRC. Larger cohorts are needed to confirm our findings. Implications for Practice The results of this study reveal clinically important biomarkers that potentially predict immune checkpoint inhibitor response in patients with mismatch repair-deficient colorectal cancer.

Background To the authors' knowledge, race-based differences in efficacy for the treatment of patients with advanced non-small cell lung cancer (NSCLC) have not been studied to date due to the underrepresentation of patients of minority backgrounds in pivotal trials. In the current study, the authors examined real-world differences in outcome in a diverse patient population. Methods The authors retrospectively analyzed the clinical outcomes of patients with advanced NSCLC who were treated with single-agent immune checkpoint blockade (ICB) between 2013 and July 2018 at Winship Cancer Institute of Emory University in Atlanta, Georgia. Primary efficacy comparison between Black patients and White patients was performed using bivariate and multivariate analyses for overall survival (OS) and progression-free survival (PFS). Results Data from 257 patients were analyzed. The median age of the patients was 69 years; 50.6% of the patients were female, 63.4% were White, 29.5% were Black, and 7.1% of the patients were of "other" race. ICB was the first-line treatment in 51 patients (19.9%), the second-line treatment in 161 patients (62.6%), and the third-line treatment in 33 patients (12.9%). The most commonly used agents were nivolumab (49.0%), pembrolizumab (25.2%), and atezolizumab (21.3%). No differences with regard to OS (P = .839) and PFS (P = .235) were noted between Black and White patients. The sample overall response rate was 20.6% (15.2% in Black patients and 23.1% in White patients). No differences with regard to OS (P = .081) and PFS (P = .176) were observed between female and male patients. The rate of immune-related adverse events was found to be similar in Black and White patients (20.0% vs 29.9%; P = .148). On multivariate analysis, race was not found to be significantly associated with OS or PFS. Conclusions Real-world analysis of the authors' institutional experience demonstrated similar efficacy and tolerability of ICB in Black versus White patients with advanced NSCLC. Larger multi-institutional studies including other US minority populations would make the findings of the current study more generalizable.

Although an expanding array of effective treatments has resulted in recent improvement in survival of patients with mantle cell lymphoma (MCL), outcomes remain heterogeneous, and identification of prognostic factors remains a priority. We assessed the prognostic impact of time to progression of disease (POD) after first-line therapy among 455 patients with relapsed MCL. Patients were categorized by duration of first remission as PRF/POD6, defined as progressive disease during induction or POD within 6 months of diagnosis (n = 65; 14%); POD6-24, defined as POD between 6 and 24 months after diagnosis (n = 153; 34%); and POD>24, defined as POD >24 months after diagnosis (n = 237; 53%). The median overall survival from POD (OS2) was 1.3 years (95% confidence interval [CI], 0.9-2.4) for patients with PRF/POD6, 3 years (95% CI, 2-6.8) for those with POD6-24, and 8 years (95% CI, 6.2-NR) for those with POD>24. Median OS2 was inferior in patients with early POD (defined as PRF/POD6 or POD6-24) after both intensive and less intensive frontline treatment. The prognostic performance of time until POD was replicated in an independent cohort of 245 patients with relapsed MCL, with median OS2 of 0.3 years (95% CI, 0.1-0.5) for PRF/POD6, 0.8 years (95% CI, 0.6-0.9) for POD6-24, and 2.4 years (95% CI 2.1-2.7) for POD>24. Early POD is associated with inferior OS2 in patients with relapsed MCL, identifying a high-risk population for future prospective studies.

Background Limited data are available on the clinical activity of venetoclax (ven) in mantle cell lymphoma (MCL). In 2 small retrospective studies of patients (pts) with MCL previously treated with BTK inhibitors (BTKi), ven resulted in overall response rates (ORRs) of 50-53% and median overall survival (OS) of 9-14 months (Eyre et al, Haematologica 2019; Zhao et al, Am J Hematol 2020). We sought to report the clinical activity of ven and identify factors associated with outcomes in a larger cohort of pts. Methods We included pts with relapsed MCL from 12 US medical centers treated with ven alone or in combination with an antiCD20 monoclonal antibody (mAb) or a BTKi. Response was determined by the local investigator. We defined OS as time from start of ven to death. Pts not experiencing an event were censored at their last known follow up. OS was determined using the Kaplan-Meier method, and univariable (UVA) and multivariable (MVA) models were developed to identify predictors of response and OS. Results Eighty-one pts were included. Pt characteristics (Table) at diagnosis (dx) were: median age 64 years (yrs) (range 38-87), male 79%, stage III/IV 95%, Ki67 >30% in 61% (available n=62), blastoid/pleomorphic histology 29% (available n=75) and ≥3 cytogenetic abnormalities 34% (available n=62). BCL2 expression was present in 93% (available n=40). Frontline treatment (tx) included intensive chemotherapy [defined as including high-dose cytarabine and/or autologous transplant (ASCT) in first remission] in 52% with ASCT in first remission in 32%. Median number of therapies prior to ven was 3 (range 1-8) including antiCD20 mAb 99%, alkylator 93%, BTKi 91%, anthracycline 58%, cytarabine 56%, and lenalidomide 37%. 55% were refractory (defined as stable (SD) or progressive disease (PD)) to last tx prior to ven. ORR to BTKi prior to ven (n=70) was 66% (complete response (CR) 20%) with median duration of tx of 6.4 months (range 0.5-69). BTKi was stopped due to PD 82% and toxicity 18%. Median time from dx to start of ven was 3.9 yrs (range 0.2-17.8). Ven was given as monotherapy in 62% (n=50) and in combination with BTKi 20% (n=16), antiCD20 mAb 14% (n=11), or other 5% (n=4). Ten pts treated with ven in combination with BTKi received prior tx with BTKi with ORR to BTKi of 40% (all PR). Ven highest dose received was 20-100 mg in 12% (n=9), 200 mg 11% (n=8), 400 mg 61% (n=46), and 800 mg 17% (n=13). Median duration of tx with ven was 2.8 months (range 0.1-30). The best response to ven was CR 18%, partial response (PR) 24%, SD 11%, and PD 47% with ORR of 42%; 19 pts (23%) did not have available data for response. ORR was not significantly different with ven monotherapy 36% (13/36) vs ven + antiCD20 mAb 56% (5/9) vs ven + BTKi 43% (6/14) (p=.559), or with ven monotherapy 36% vs combination therapy 50% (13/26) (p=.274). Ven was stopped due to PD 69%, toxicity 9%, allogeneic transplant 3% or other reasons 19%. Laboratory tumor lysis syndrome (TLS) occurred in 10 pts (12%) including 3 (3.7%) with clinical TLS. 38 pts received post-ven tx with median time from stopping ven to next tx of 0.24 months (range 0-2.2); for the 33 pts with available data, the best response to post-ven tx was CR 24%, PR 27%, SD 9% and PD 39% with ORR of 51%. For the 75 pts with available data, median OS was 12.5 months (95% CI 6-17) with 3-year OS of 13.1% (95% CI 1.4-38.0%) (Figure A). Median OS was numerically longer with ven combination (28.7 months, 95% CI 4-not reached) vs monotherapy (8.6 months, 95% CI 4.7-14.4), p=.0825 (Figure B). Median OS did not significantly differ based on response (CR/PR vs SD/PD) to prior tx with BTKi (14.4 vs 9.5 months, p=.53, Figure C) or last tx prior to ven (16.7 vs 12.4 months, p=.14, Figure D). In MVA for response, achieving CR/PR with BTKi prior to ven (vs SD/PD) was associated with response to ven (odds ratio 3.48, 95% CI 1.01-12.05, p=.049). In MVA for OS, ven combination vs monotherapy (HR 0.13, 95% CI 0.03-0.53; p=.006), longer time from dx to start of ven (>4 vs ≤4 yrs) (HR 0.08, 95% CI 0.02-0.36; p=.001), and higher dose of ven (≥400 mg vs 6 vs ≤6 months) (HR 3.47, 95% CI 1.10-10.99; p=.038) was associated with inferior OS. Conclusions In these high-risk and heavily pretreated pts with MCL, ven resulted in low response rate and poor OS. Ven may have a better role in MCL in earlier lines of therapy and when combined with other agents such as BTKi and/or antiCD20 mAbs. Disclosures Kamdar: Roche: Research Funding. Greenwell:Lymphoma Research Foundation: Research Funding; Acrotech Biopharma LLC, Kyowa Kirin: Consultancy. 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. Portell:Acerta/AstraZeneca: Research Funding; Kite: Consultancy, Research Funding; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; AbbVie: Research Funding; TG Therapeutics: Research Funding; Infinity: Research Funding; Roche/Genentech: Consultancy, Research Funding; Xencor: Research Funding. Goldsmith:Wugen Inc.: Consultancy. Grover:Genentech: Research Funding; Tessa: Consultancy. Riedell:Morphosys: Research Funding; Celgene/Bristol-Myers Squibb Company: Honoraria, Research Funding; Verastem Oncology: Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Kite Pharmaceuticals/Gilead: Honoraria, Research Funding; Bayer: Honoraria; Karyopharm Therapeutics: Honoraria. Karmali:BeiGene: Speakers Bureau; AstraZeneca: Speakers Bureau; Karyopharm: Honoraria; Takeda: Research Funding; Gilead/Kite: Honoraria, Other, Research Funding, Speakers Bureau; BMS/Celgene/Juno: Honoraria, Other, Research Funding, Speakers Bureau. Kumar:AbbVie: Research Funding; Kite Pharmaceuticals: Honoraria, Other: Honoraria for Advisory Board; Astra Zeneca: Honoraria, Other: Honoraria for Advisory Board; Celgene: Honoraria, Other: Honoraria for Advisory Board; Seattle Genetics: Research Funding; Pharmacyclics: Research Funding; Celgene: Research Funding; Adaptive Biotechnologies,: Research Funding. Hill:Abbvie: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding. Kahl:AstraZeneca Pharmaceuticals LP: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Consultancy; AbbVie: Consultancy; Genentech: Consultancy; Pharmacyclics LLC: Consultancy; Roche Laboratories Inc: Consultancy; BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cohen:Genentech, BMS, Novartis, LAM, BioInvent, LRF, ASH, Astra Zeneca, Seattle Genetics: Research Funding; Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo: Consultancy. OffLabel Disclosure: Venetoclax is not licensed for use in mantle cell lymphoma

Gain of chromosome 1q (+1q) is commonly identified in multiple myeloma and has been associated with inferior outcomes. However, the prognostic implication of +1q has not been evaluated in the setting of standard triplet regimens. We retrospectively analyzed 201 consecutive patients with newly diagnosed myeloma who received induction with lenalidomide, bortezomib, and dexamethasone (RVD) and were tested for +1q at diagnosis by fluorescent in-situ hybridization. Patients with +1q (n = 94), compared to those without +1q (n = 107), had shorter median progression-free survival (PFS) (41.9 months vs 65.1 months, p = 0.002, HR = 1.90) and overall survival (median not reached (NR) for either arm, p = 0.003, HR 2.69). In subgroup analyses, patients with co-occurring +1q and t(4;14), t(14;16) or del(17p) or with 4 or more copies of 1q had significantly worse PFS (25.1 months and 34.6 months, p p = 0.0063, respectively), whereas patients with three copies and no other high-risk cytogenetic abnormalities had no significant difference in PFS. These data suggest that when treated with RVD induction, patients with +1q should be considered at very high risk for early progression in multiple myeloma when ≥4 copies are detected or in the context of other high-risk cytogenetic abnormalities.

Clinical outcomes and predictors of survival in patients with newly diagnosed mantle cell lymphoma (MCL) treated in the rituximab era (2000-2015) at 12 US academic centers were assessed to identify determinants of survival across age groups. Objectives were to characterize and compare practice patterns, outcomes and prognostic factors for survival in younger patients (age < 65) and older patients (age ≥ 65 years). Among 1162 patients included, 697 were younger and 465 were older. In younger patients, 2-year progression free survival (PFS) and overall survival (OS) rates were 79% and 92% respectively; blastoid histology, ECOG ≥ 2, and lack of maintenance rituximab (MR) remained statistically relevant to poor OS on univariate analysis (UVA) and multivariate analysis (MVA). In older patients, 2-year PFS and OS rates were 67% and 86% respectively; lack of maintenance rituximab remained significantly associated with inferior PFS and OS on UVA and MVA (p < 0.001). Two-year PFS rates were 79%, and 67% and 2-year OS rates were 92% and 86% for ages < 65 and ≥ 65 respectively (p < 0.001). First-line high-dose cytarabine exposure and/or MR lessened the negative impact of age on survival. Taken collectively, survival outcomes for older patients remain inferior to those of younger patients in the rituximab era. However, maintenance rituximab and potentially high-dose cytarabine-based induction can mitigate the negative impact of age on survival.

BackgroundImmune checkpoint inhibitors (ICI) have revolutionized the treatment of metastatic renal cell carcinoma (mRCC). Biomarkers for mRCC patients treated with ICI are limited, and body composition is underutilized in mRCC. We investigated the association between body composition and clinical outcomes in ICI-treated mRCC patients.MethodsWe performed a retrospective analysis of 79 ICI-treated mRCC patients at Winship Cancer Institute from 2015-2020. Baseline CT images were collected at mid-L3 and segmented using SliceOMatic v5.0 (TomoVision). Density of skeletal muscle (SM), subcutaneous fat, inter-muscular fat, and visceral fat were measured and converted to indices by dividing by height(m)2 (SMI, SFI, IFI, and VFI, respectively). Total fat index (TFI) was defined as the sum of SFI, IFI, and VFI. Patients were characterized as high versus low for each variable at gender-specific optimal cuts using overall survival (OS) as the primary outcome. A prognostic risk score was created based on the beta coefficient from the multivariable Cox model after best subset variable selection. Body composition risk score was calculated as IFI + 2*SM mean + SFI and patients were classified as poor (0-1), intermediate (2), or favorable risk (3-4). Kaplan-Meier method and Log-rank test were used to estimate OS and PFS and compare the risk groups. Concordance statistics (C-statistics) were used to measure the discriminatory magnitude of the model.ResultsMost patients were male (73%) and most received ICI as first (35%) or second-line (51%) therapy. The body composition poor-risk patients had significantly shorter OS (HR: 6.37, pConclusionsRisk stratification using the body composition variables IFI, SM mean, SFI, and TFI may be prognostic and predictive of clinical outcomes in mRCC patients treated with ICI. Larger, prospective studies are warranted to validate this hypothesis-generating data.

BackgroundImmune-checkpoint-inhibitors (ICIs) have become the cornerstone of metastatic renal-cell-carcinoma (mRCC) therapy. However, data are limited regarding clinical outcomes by race. In this study, we compared the real-world outcomes between African American (AA) and Caucasian mRCC patients treated with ICIs.MethodsWe performed a retrospective study of 198 patients with mRCC who received ICI at the Emory Winship Cancer Institute from 2015-2020. Clinical outcomes were measured by overall survival (OS), progression-free survival (PFS), and overall response rate (ORR) defined as a complete or partial response maintained for at least 6 months per response evaluation criteria in solid tumors version 1.1. Univariate and multivariable analyses were carried out for OS and PFS by Cox proportional-hazard model and ORR by logistical-regression model. Descriptive statistics compared rates of immune-related adverse events (irAEs) and non-clear-cell-RCC (nccRCC) histology were assessed using Chi-square test.ResultsOur cohort was comprised of 38 AA and 160 Caucasian patients. Most were diagnosed with clear-cell-RCC (ccRCC) (78%) and more than half received (57%) PD-1/PD-L1 monotherapy. Most patients were intermediate or poor-risk groups (83%). Comparing to Caucasians, our AA cohort contained more females and nccRCC cases. Kaplan-Meier method showed AAs had no statistically different median OS (17 vs 25 months, p=0.368) and PFS (3.1 vs 4.4 months, p=0.068) relative to Caucasian patients. On multivariable analysis, AA patients had significantly shorter PFS (HR=1.52, 95% CI: 1.01-2.3, p=0.045), similar ORR (OR=1.04, 95% CI: 0.42-2.57, p=0.936) and comparable OS (HR=1.09, 95% CI: 0.61-1.95, p=0.778) relative to Caucasians.ConclusionsOur real-world analysis of ICI-treated mRCC patients showed that AAs experienced shorter PFS but similar OS relative to Caucasians. This similarity in survival outcomes is reassuring for the use of ICI amongst real-world patient populations, however, the difference in treatment response is poorly represented in early outcomes data from clinical trials. Thus, the literature requires larger prospective studies to validate these findings.

Background Immune checkpoint inhibitors (ICIs) are an important treatment for metastatic renal cell carcinoma (mRCC). These agents may cause immune-related adverse events (irAEs), and the relationship between irAEs and outcomes is poorly understood. We investigated the association between irAEs and clinical outcomes in patients with mRCC treated with ICIs. Methods We performed a retrospective study of 200 patients with mRCC treated with ICIs at Winship Cancer Institute from 2015 to 2020. Data on irAEs were collected from clinic notes and laboratory values and grades were determined using Common Terminology Criteria in Adverse Events version 5.0. The association with overall survival (OS) and progression-free survival (PFS) was modeled by Cox proportional hazards model. Logistic regression models were used to define odds ratios (ORs) for clinical benefit (CB). Landmark analysis and extended Cox models were used to mitigate lead-time bias by treating irAEs as a time-varying covariate. Results Most patients (71.0%) were male, and one-third of patients (33.0%) experienced at least one irAE, most commonly involving the endocrine glands (13.0%), gastrointestinal tract (10.5%), or skin (10.0%). Patients who experienced irAEs had significantly longer OS (hazard ratio [HR], 0.52; p = .013), higher chance of CB (OR, 2.10; p = .023) and showed a trend toward longer PFS (HR, 0.71; p = .065) in multivariate analysis. Patients who had endocrine irAEs, particularly thyroid irAEs, had significantly longer OS and PFS and higher chance of CB. In a 14-week landmark analysis, irAEs were significantly associated with prolonged OS (p = .045). Patients who experienced irAEs had significantly longer median OS (44.5 vs. 18.2 months, p = .005) and PFS (7.5 vs. 3.6 months, p = .003) without landmark compared with patients who did not. Conclusion We found that patients with mRCC treated with ICIs who experienced irAEs, particularly thyroid irAEs, had significantly improved clinical outcomes compared with patients who did not have irAEs. This suggests that irAEs may be effective clinical biomarkers in patients with mRCC treated with ICIs. Future prospective studies are warranted to validate these findings. Implications for Practice This study found that early onset immune-related adverse events (irAEs) are associated with significantly improved clinical outcomes in patients with metastatic renal cell carcinoma (mRCC) treated with immune checkpoint inhibitors (ICIs). In this site-specific irAE analysis, endocrine irAEs, particularly thyroid irAEs, were significantly associated with improved clinical outcomes. These results have implications for practicing medical oncologists given the increasing use of ICIs for the treatment of mRCC. Importantly, these results suggest that early irAEs and thyroid irAEs at any time on treatment with ICIs may be clinical biomarkers of clinical outcomes in patients with mRCC treated with ICIs.

Background Patients with cancer are at higher risk for venous thromboembolism (VTE) and bleeding, in turn complicating anticoagulant therapy. An added complexity is the toxicity profile of agents used to treat certain cancers, namely the vascular endothelial growth factor receptor tyrosine kinase inhibitors (TKIs), which are associated with both thromboembolism and hemorrhages. The purpose of this study was to evaluate whether patients taking concurrent VEGF TKI and therapeutic anticoagulant were at higher risk for bleeding compared with patients taking VEGF TKI alone. Materials and Methods This was a single-center, retrospective chart review of patients who underwent treatment with a VEGF TKI with or without anticoagulant. The primary outcome included comparison of major bleeding rates between groups. Secondary outcomes included comparison of composite major and minor bleed rates and assessment of VTE incidence and recurrence among patients treated with a VEGF TKI and VEGF TKI plus anticoagulant, respectively. Results A total of 184 and 74 patients were included in the VEGF TKI alone and VEGF TKI + anticoagulant groups, respectively. Major bleeding events occurred in 6 of 184 patients (3.3%) and 6 of 74 patients (8.1%), respectively (p = .095). Composite major and minor bleeding events occurred in 22 of 184 (13.6%) and 17 of 74 (23%), respectively (p = .026). A total of 26 of 258 patients (10.1%) experienced a VTE event while taking a VEGF TKI, and 1 of 26 (3.8%) experienced a recurrent VTE event while taking a VEGF TKI plus anticoagulant. Conclusion Patients who received concomitant VEGF TKI plus anticoagulant had increased incidence of bleeding, although prospective studies are needed to further explore this association. Implications for Practice The current study showed that use of concomitant vascular endothelial growth factor receptor tyrosine kinase inhibitor (VEGF TKI) and therapeutic anticoagulation was associated with an increased risk of composite bleeding events, although at comparable rates between patients treated with VEGF TKI plus direct oral anticoagulant (DOAC) versus VEGF TKI plus non-DOAC anticoagulant. This suggests that when anticoagulation is indicated in a patient receiving a VEGF TKI, the novel DOACs may be a safe alternative to historical anticoagulants (warfarin and enoxaparin). These results fill a gap in the literature and will help guide treatment decisions for patients requiring concurrent VEGF TKI and anticoagulation.

Background Immune checkpoint inhibitors (ICI) have revolutionized the treatment of metastatic renal cell carcinoma (mRCC). Biomarkers for mRCC patients treated with ICI are limited, and body composition is underutilized in mRCC. We investigated the association between body composition and clinical outcomes in ICI-treated mRCC patients. Methods We performed a retrospective analysis of 79 ICI-treated mRCC patients at Winship Cancer Institute from 2015–2020. Patients with CT scans within 2 months of ICI-initiation were included. Baseline CT images were collected at mid-L3 and segmented using SliceOMatic v5.0 (TomoVision). Density of skeletal muscle (SM), subcutaneous fat, inter-muscular fat, and visceral fat were measured and converted to indices by dividing by height(m)2 (SMI, SFI, IFI, and VFI, respectively). Total fat index (TFI) was defined as the sum of SFI, IFI, and VFI. Patients were characterized as high versus low for each variable at gender-specific optimal cuts using overall survival (OS) as the primary outcome. A prognostic risk score was created based on the beta coefficient from the multivariable Cox model (MVA) after best subset variable selection. Body composition risk score was calculated as IFI + 2*SM mean + SFI, and patients were classified as high (0–1), intermediate (2), or low-risk (3–4). Kaplan-Meier method and Log-rank test were used to estimate OS and PFS and compare the risk groups. Concordance statistics (C-statistics) were used to measure the discriminatory magnitude of the model. Results Most were male (73%), and median age was 61 years. Patients were primarily intermediate (54%) or poor-risk (30%) per IMDC criteria and most received ICI as first (35%) or second-line (51%) therapy. The body composition high-risk patients had significantly shorter OS (HR: 6.37, p Conclusions Risk stratification using the body composition variables IFI, SM mean, SFI, and TFI may be prognostic and predictive of clinical outcomes in mRCC patients treated with ICI. Larger, prospective studies are warranted to validate this hypothesis-generating data. Acknowledgements Research reported in this publication was supported in part by the Breen Foundation and the Biostatistics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Trial Registration Not applicable Ethics Approval This retrospective study was approved by the Emory University Institutional Review Board. Consent Not applicable References Not applicable

Background Immune checkpoint inhibitors (ICI) have become an increasingly utilized treatment in metastatic renal cell carcinoma (mRCC). Although they have a favorable toxicity profile, immune-related adverse events (irAEs) can have a significant impact on patients‘ quality of life. It is not well understood whether irAEs are associated with improved clinical outcomes. We investigated the relationship between irAEs and clinical outcomes in mRCC patients treated with ICI. Methods We performed a retrospective study of 200 patients with mRCC who received ICI at Winship Cancer Institute of Emory University from 2015–2020. Clinical outcomes were measured by overall survival (OS), progression-free survival (PFS), and clinical benefit (CB). OS and PFS were calculated from ICI-initiation to date of death and radiographic or clinical progression, respectively. CB was defined as a best radiographic response of complete response (CR), partial response (PR), or stable disease (SD) for >6 months per response evaluation criteria in solid tumors (RECIST) version 1.1. Toxicity data was collected from clinic notes and laboratory values. The association with OS and PFS was modeled by Cox proportional hazards model. Kaplan-Meier curves were created for survival estimates. Results Most patients were males (71%), and 78% had clear-cell RCC (ccRCC). Most patients (58%) received anti-PD-1 monotherapy. The majority were international mRCC database consortium (IMDC) intermediate (57%) or poor-risk (26%). Anti-PD-1 monotherapy was the most common (58%) treatment regimen and most patients received ICI as first (38%) or second-line (42%) treatment. One-third of patients (33%) experienced an irAE, with the most common being endocrine (13%), gastrointestinal (11%), and dermatologic (10%). Patients who experienced irAEs had significantly longer OS (HR: 0.52, 95% CI: 0.32–0.87, p=0.013), higher chance of CB (OR: 2.10, 95% CI: 1.11–4.00, p=0.023) and showed a trend towards longer PFS (HR: 0.71, 95% CI: 0.49–1.02, p=0.065) in MVA (table 1). Patients who had thyroid irAEs had significantly longer OS, PFS, and higher chance of CB in MVA (table 1). The objective response rate was higher for patients who experienced irAEs (34% vs. 18%). Patients who experienced irAEs had significantly longer median OS (44.5 vs. 18.2 months, p=0.005) and PFS (7.5 vs 3.6 months, p=0.0028) compared to patients who did not (figure 1). Conclusions We showed that mRCC patients who experienced irAEs, particularly thyroid irAEs, had improved clinical outcomes. This suggests that irAEs may be prognostic of favorable outcomes in mRCC patients treated with ICI. Larger, prospective studies are needed to validate these findings. Acknowledgements Research reported in this publication was supported in part by the Breen Foundation and the Biostatistics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Trial Registration Not applicable Ethics Approval This retrospective study was approved by the Emory University Institutional Review Board. Consent Not applicable References Not applicable

Background Immune checkpoint inhibitors (ICIs) have increased in prevalence for the treatment of metastatic clear-cell renal cell carcinoma (mccRCC) in recent years given their efficacy and favorable toxicity profile. However, there has been insufficient investigation in the literature of how clinical outcomes differ on the basis of race. In this paper, we investigated differences in clinical outcomes between African American (AA) and Caucasian mRCC patients treated with ICI therapy. Methods We performed a retrospective study of 198 patients with mRCC who received ICI at the Emory Winship Cancer Institute from 2015–2020. Clinical outcomes were measured by overall survival (OS), progression-free survival (PFS), and clinical benefit (CB). OS and PFS were calculated from ICI-initiation to date of death and radiographic or clinical progression, respectively. CB was defined as a best radiographic response of complete response, partial response, or stable disease maintained for at least 6 months per response evaluation criteria in solid tumors version 1.1. The association of self-identified race with OS and PFS was generally modeled by Cox proportional hazards model. Univariable and multivariable logistic regression models were used for binary outcomes of CB. The univariate association of immune-related adverse events (irAEs) and non-clear-cell RCC (nccRCC) with race was assessed using Chi-square test. Results Our cohort was made up of 38 AA (19%) and 160 Caucasian (81%) patients. Most of the patients were diagnosed with ccRCC (78%) and more than half received PD-1 monotherapy (57%). Most patients were international mRCC database consortium (IMDC) intermediate (57%) or poor-risk (25%) groups. AA patients displayed significantly shorter PFS (HR=1.52, 95% CI: 1.01–2.3, p=0.045) and trended towards decreased CB (OR=0.51, 95% CI: 0.22–1.17, p=0.111) in MVA (table 1). There was no difference in OS (HR=1.09, 95% CI: 0.61–1.95, p=0.778) between the two racial groups in MVA (table 1). On Kaplan-Meier method, AA patients had shorter median OS (17 vs 25 months, p=0.3676) and median PFS (3.1 vs 4.4 months, p=0.0676) relative to Caucasian patients (figure 1). Additionally, AA patients more commonly had nccRCC compared to Caucasian patients (41.7% vs 17.5% nccRCC, p-0.002). AA patients also trended towards a lower incidence of irAEs compared to Caucasian patients in UVA (23.7% vs 35.8%, p=0.153). Conclusions In this group of mRCC patients treated with ICI, African American patients had significantly shorter PFS compared to Caucasian patients. These findings suggest race could play a role in the management of late-stage mRCC. Larger, prospective studies are needed to validate these findings. Acknowledgements Research reported in this publication was supported in part by the Breen Foundation and the Biostatistics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Trial Registration Not applicable. Ethics Approval This retrospective study was approved by the Emory University Institutional Review Board. Consent Not applicable. References Not applicable

Background Several immune checkpoint inhibitors (ICI) have been approved for the treatment of advanced urothelial carcinoma (UC). There are limited predictive biomarkers for UC patients treated with ICI. In this study, we investigated the association between body composition and clinical outcomes in ICI-treated advanced UC patients. Methods We conducted a retrospective analysis of 70 ICI-treated advanced UC patients at Winship Cancer Institute from 2015–2020. Inclusion criteria was available computed tomography (CT) scans within 2 months of ICI-initiation. Baseline CT images were collected at mid-L3 and muscle and fat compartments were segmented using SliceOMatic v5.0 (TomoVision). The density of subcutaneous fat, inter-muscular fat, visceral fat, and skeletal muscle (SM) were measured and converted to indices by dividing by height(m)2 (SFI, IFI, VFI and SMI, respectively). Attenuated SM mean (Hounsfield Units) was also collected. Myosteatosis was calculated by IFI/SMI*100%. Gender-specific optimal cuts were used to dichotomize patients as high or low for each variable using OS as the primary outcome. A prognostic body composition risk score was created based on the beta coefficient from the multivariable Cox model (MVA) following best-subset variable selection. Our body composite risk score was SMI + 2*SM mean + VFI and patients were categorized as high (0–1), intermediate (2–3), or low-risk (4). Comparison of OS and PFS between the risk groups was performed via Kaplan-Meier method and Log-rank test. Concordance statistics (C-statistics) were used to quantify the discriminatory magnitude of the predictive model. Results Most patients (70%) were male and more than one-quarter (26%) had an ECOG PS ≥ 2. The majority received ICI in the second (46%) or third-line (21%) setting. Body composite poor-risk patients had significantly shorter OS (HR: 6.18, p Conclusions Body composition variables such as SMI, SM mean, VFI and myosteatosis may be predictive of clinical outcomes in ICI-treated advanced UC patients. Larger, prospective studies are warranted to validate this hypothesis-generating data. Acknowledgements Research reported in this publication was supported in part by the Biostatistics and Bioinformatics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Trial Registration Not applicable Ethics Approval This retrospective study was approved by the Emory University Institutional Review Board. Consent Not applicable References Not applicable

The administration schedule of capecitabine for the treatment of metastatic colorectal cancer (mCRC) in clinical trials has been 14 days of drug with 7 days off in a 21 day cycle (14/7). In an effort to improve tolerability, an alternative every other week treatment (7/7) is often administered. The purpose of this study was to determine the safety and efficacy of administering 7/7 compared with 14/7 capecitabine dosing.In this retrospective study, mCRC patients received capecitabine on a 7/7 or 14/7 schedule. The primary objective was to determine the tolerability of the respective dosing schedules, defined according to frequency of dose reductions and treatment delays. Secondary objectives included comparisons of objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and safety of dosing strategies.Of 175 included patients, 73 (41.7%) received the capecitabine 7/7 schedule and 102 (58.3%) received the 14/7 schedule. There was a statistically significant difference between the 7/7 and 14/7 groups with regard to dose reductions (4% vs. 29%; P .001) and treatment delays (22% vs. 43%; P = .004). The incidence of any adverse effects (45% vs. 72%; P .001) and specifically, palmar-plantar erythrodysesthesia (18% vs. 45%; P .001), were significantly higher in the 14/7 group. No significant difference was seen with regard to ORR, PFS, or OS.Patients with mCRC who received the 7/7 schedule had significantly fewer dose reductions and treatment delays compared with patients who received the 14/7 schedule. Although no difference in efficacy outcomes were observed, prospective studies are needed to confirm these findings.

Background: Brexucabtagene autoleucel (brexu-cel) is the first CD19 chimeric antigen receptor T-cell (CAR T) therapy approved for use in patients (pts) with relapsed mantle cell lymphoma (MCL). The ZUMA-2 trial demonstrated that brexu-cel induces durable remissions in these pts with an ORR of 85% (59% CR), estimated 12-month PFS rate of 61%, and similar toxicity profile to other CAR T therapies (Wang et al, NEJM 2020). We conducted a multicenter, retrospective study of pts treated with commercial brexu-cel to evaluate its safety and efficacy in the non-trial setting. Methods: We reviewed records of pts with relapsed MCL across 12 US academic medical centers. Pts who underwent leukapheresis between July 2020 and June 2021 with the intent to proceed to commercial brexu-cel were included. Baseline demographic and clinical characteristics were summarized using descriptive statistics. Survival curves were generated using the Kaplan-Meier method, and univariate models were fit to identify predictors of post-CAR T outcomes. Results: Fifty-five pts underwent leukapheresis. There were 3 manufacturing failures. Baseline characteristics of the 52 pts who received brexu-cel are summarized in Table 1. Median age was 66 yrs (range: 47-79 yrs) and 82% were male. Twenty of 29 (69%) pts with known baseline MIPI were intermediate or high risk. Seven pts had a history of CNS involvement. The median number of prior therapies was 3 (range: 2-8), including prior autologous stem cell transplant (ASCT) in 21 (40%) and prior allogeneic transplant in 2 pts (1 with prior ASCT and 1 without). Fifty percent had relapsed within 24 months of their initial therapy. All pts had previously received a Bruton's tyrosine kinase inhibitor (BTKi), including 29 (56%) with disease progression on a BTKi. Forty (77%) pts received bridging therapy (17 BTKi, 10 BTKi + venetoclax, 6 chemo, 3 venetoclax, 2 XRT only, 1 steroids only, 1 lenalidomide + rituximab). The ORR was 88% (CR 69%) among patients who received brexu-cel. Two pts had PD on initial restaging and 3 died prior to first response assessment (without evidence of relapse). Seven pts have not completed restaging due to limited follow-up (< 3 months) and were not included in the response assessment. Five pts have progressed, including 2 with CR and 1 with PR on initial restaging. With a median follow-up of 4.2 months, the estimated 6-month PFS and OS rates were 82.7% and 89.0%, respectively. All 7 pts with prior CNS involvement were alive without relapse at last follow-up. The incidence of cytokine release syndrome (CRS) was 84% (10% grade ≥ 3) with a median time to max grade of 5 days (range: 0-10 days). There were no cases of grade 5 CRS. The incidence of neurotoxicity (NT) was 57% (31% grade ≥ 3) with a median time to onset of 7 days (range: 4-15 days). NT occurred in 4/7 pts with prior CNS involvement (3 grade 3, 1 grade 4). Grade 5 NT occurred in 1 pt who developed cerebral edema and died 8 days after infusion. Thirty-five pts received tocilizumab, 33 received steroids, 7 received anakinra, and 1 received siltuximab for management of CRS and/or NT. Post-CAR T infections occurred in 8 pts, including two grade 5 infectious AEs (covid19 on day +80 and septic shock on day +40 after infusion). Rates of grade ≥ 3 neutropenia and thrombocytopenia were 38% and 37%, respectively. Among pts with at least 100 days of follow-up and lab data available, 5/34 (15%) had persistent grade ≥ 3 neutropenia and 4/34 (12%) had persistent grade ≥ 3 thrombocytopenia at day +100. Five pts have died, with causes of death being disease progression (2), septic shock (1), NT (1), and covid19 (1). Univariate analysis did not reveal any significant associations between survival and baseline/pre-CAR T MIPI, tumor pathologic or cytogenetic features, prior therapies, receipt of steroids/tocilizumab, or pre-CAR T tumor bulk. Conclusions: This analysis of relapsed MCL pts treated with commercial brexu-cel reveals nearly identical response and toxicity rates compared to those reported on ZUMA-2. Longer follow-up is required to confirm durability of response, but these results corroborate the efficacy of brexu-cel in a population of older adults with high-risk disease features. While all 7 pts with prior CNS involvement are alive and in remission, strategies to mitigate the risk of NT in this setting need to be evaluated. Further studies to define the optimal timing of CAR T, bridging strategies, and salvage therapies for post-CAR T relapse in MCL are warranted. Figure 1 Figure 1. Disclosures Gerson: TG Therapeutics: Consultancy; Kite: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy. Sawalha: TG Therapeutics: Consultancy, Research Funding; Celgene/BMS: Research Funding; BeiGene: Research Funding; Epizyme: Consultancy. Bond: Kite/Gilead: Honoraria. Karmali: Janssen/Pharmacyclics: Consultancy; BeiGene: Consultancy, Speakers Bureau; Morphosys: Consultancy, Speakers Bureau; Takeda: Research Funding; Genentech: Consultancy; AstraZeneca: Speakers Bureau; Roche: Consultancy; Karyopharm: Consultancy; Epizyme: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau; BMS/Celgene/Juno: Consultancy, Research Funding; EUSA: Consultancy. Torka: TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Chow: ADC Therapeutics: Current holder of individual stocks in a privately-held company, Research Funding; AstraZeneca: Research Funding. Shadman: Abbvie, Genentech, AstraZeneca, Sound Biologics, Pharmacyclics, Beigene, Bristol Myers Squibb, Morphosys, TG Therapeutics, Innate Pharma, Kite Pharma, Adaptive Biotechnologies, Epizyme, Eli Lilly, Adaptimmune , Mustang Bio and Atara Biotherapeutics: Consultancy; Mustang Bio, Celgene, Bristol Myers Squibb, Pharmacyclics, Gilead, Genentech, Abbvie, TG Therapeutics, Beigene, AstraZeneca, Sunesis, Atara Biotherapeutics, GenMab: Research Funding. Ghosh: Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding, Speakers Bureau; Karyopharma: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; TG Therapeutics: Consultancy, Honoraria, Research Funding; Incyte: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Genmab: Consultancy, Honoraria; Epizyme: Honoraria, Speakers Bureau; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Speakers Bureau; ADC Therapeutics: Consultancy, Honoraria; Adaptive Biotech: Consultancy, Honoraria; AbbVie: Honoraria, Speakers Bureau. Moyo: Seattle Genetics: Consultancy. Fenske: TG Therapeutics: Consultancy, Speakers Bureau; Servier Pharmaceuticals: Consultancy; Seattle Genetics: Speakers Bureau; Sanofi: Speakers Bureau; Pharmacyclics: Consultancy; MorphoSys: Consultancy; Kite (Gilead): Speakers Bureau; KaryoPharm: Consultancy; CSL Therapeutics: Consultancy; Bristol-Myers Squibb: Speakers Bureau; Biogen: Consultancy; Beigene: Consultancy; AstraZeneca: Speakers Bureau; ADC Therapeutics: Consultancy; Adaptive Biotechnologies: Consultancy; AbbVie: Consultancy. Grover: Genentech: Research Funding; Novartis: Consultancy; ADC: Other: Advisory Board; Kite: Other: Advisory Board; Tessa: Consultancy. Maddocks: Seattle Genetics: Divested equity in a private or publicly-traded company in the past 24 months; BMS: Divested equity in a private or publicly-traded company in the past 24 months; Pharmacyclics: Divested equity in a private or publicly-traded company in the past 24 months; Novatis: Divested equity in a private or publicly-traded company in the past 24 months; Janssen: Divested equity in a private or publicly-traded company in the past 24 months; Morphosys: Divested equity in a private or publicly-traded company in the past 24 months; ADC Therapeutics: Divested equity in a private or publicly-traded company in the past 24 months; Karyopharm: Divested equity in a private or publicly-traded company in the past 24 months; Beigene: Divested equity in a private or publicly-traded company in the past 24 months; Merck: Divested equity in a private or publicly-traded company in the past 24 months; KITE: Divested equity in a private or publicly-traded company in the past 24 months; Celgene: Divested equity in a private or publicly-traded company in the past 24 months. Jacobson: Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel support; Humanigen: Consultancy, Honoraria, Other: Travel support; Celgene: Consultancy, Honoraria, Other: Travel support; Pfizer: Consultancy, Honoraria, Other: Travel support, Research Funding; Lonza: Consultancy, Honoraria, Other: Travel support; AbbVie: Consultancy, Honoraria; Precision Biosciences: Consultancy, Honoraria, Other: Travel support; Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Other: Travel support; Nkarta: Consultancy, Honoraria; Axis: Speakers Bureau; Clinical Care Options: Speakers Bureau. Cohen: Janssen, Adaptive, Aptitude Health, BeiGene, Cellectar, Adicet, Loxo/Lilly, AStra ZenecaKite/Gilead: Consultancy; Genentech, Takeda, BMS/Celgene, BioInvent, LAM, Astra Zeneca, Novartis, Loxo/Lilly: Research Funding.

Purpose/Objective(s) Treatments offering anatomic and functional preservation of the larynx are offered to most patients with laryngeal squamous cell carcinoma (L-SCC). However, upfront laryngectomy (Lgx) with pathology-guided adjuvant therapy is generally preferred for patients with T4 disease. Analyses of national care patterns and outcomes among T4 patients have raised concern that inappropriate use of larynx preservation (LP) is contributing to reduced survival as compared to Lgx-based approaches. Little consideration has been given to confounding by indication, wherein patients ineligible for standard of care treatment (e.g., Lgx) receive non-standard therapy (e.g., LP). We assessed this potential source of bias by examining the impact of operability status in patients with T4 L-SCC. Materials/Methods We queried the National Cancer Database for cases of T4 M0 L-SCC newly diagnosed from 2004-2015. Patients were categorized according to treatment approach and operability: 1) Lgx patients, 2) LP patients undergoing concurrent chemoradiotherapy (CRT) who were coded as being offered surgery but declining it (LP-op), and 3) LP patients undergoing CRT and lacking these codes (LP-other). Chi-square tests were used to compare baseline characteristics between treatment groups. Overall survival (OS) in months (m) was estimated by Kaplan-Meier. Cox multivariate analysis (MVA) was used to identify variables associated with OS, expressed as hazard ratios (HR) and 95% confidence intervals (95% CI) with HR > 1 indicating worse OS. Analysis was repeated in a weighted sample created using inverse probability of treatment weights (IPTW) derived from propensity scores. Results We identified 1,405 Lgx patients, 164 LP-op patients, and 1,969 LP-other patients. LP-op patients were more likely to have glottic primary site, N0 status, and diagnosis before 2008. Median OS was 43.7 m for Lgx, 40.3 m for LP-op, and 31.4 m for LP-other (P Conclusion Patients with T4 L-SCC who are deemed operable but undergo LP do not appear to have worse OS compared to those undergoing Lgx. Our findings suggest that confounding by indication may have influenced earlier analyses that demonstrated inferior outcomes among LP patients. Additional research is needed to define which T4 patients may be eligible for LP.

BackgroundBiliary tract cancers (BTCs) are aggressive malignancies often refractory to chemotherapy and immunotherapy. There is urgent need to identify novel, data-driven therapeutic targets to change the course of disease. It is also challenging to procure substantial quantities of tissue for research from patients with advanced or metastatic disease. Thus, we posit that peripheral blood holds particular value for exploring immune landscapes in patients with advanced BTC. We hypothesized actionable immunotherapy targets can be identified from blood that are suited to improve outcomes for BTC patients.MethodsWe examined a comprehensive panel of immune biomarkers in pre-treatment blood from 79 patients with advanced BTC on a national, randomized Phase II clinical trial of atezolizumab ± cobimetinib in advanced metastatic BTC (NCI10139). A cohort of 12 healthy donors was obtained as a comparator. Blood was processed via ficoll and density gradient centrifugation. PBMCs and plasma were cryopreserved prior to analysis by bioplex assay and multiparameter flow cytometry (n=23 colors). Analysis of 45 peripheral soluble factors was performed on a Luminex 100. Flow cytometric analysis was conducted on a Cytek Aurora and analyzed using FlowJo software. Comparisons of normal versus BTC patient samples were conducted via unpaired two-tailed t tests.ResultsBioplex analysis of 45 peripheral soluble factors revealed significant elevations in BTC plasma compared to normal donors for several factors including IL-6, IL-18, eotaxin/CCL11, IP-10/CXCL10, MIP-1ß/CCL9, IFN-?, PDGF-BB, PIGF-1, and SCF (p’sAbstract 18 Figure 1Several immune biomarkers are elevated in the peripheral blood of biliary tract cancer patients compared to normal donors, including (a) percent of CD45% cells that are phenotypically defined as M2 macrophages (CD11b+CD11c+CD16+CD33+CD14+), (b) percent of CD45% cells that are BTLA+CD8+ T cells, (c) soluble MIP-1β/CCL9, and (d) soluble IL-6.ConclusionsTo our knowledge, this work represents the most comprehensive analysis of peripheral immune biomarkers in BTC patients to date. These data suggest that cytokine mediators and/or distinct immune checkpoints deserve further investigation as actionable targets in patients with BTC.Ethics ApprovalPatient samples were collected as part of a study approved by the National Cancer Institute’s (NCI) Cancer Therapy Evaluation Program (CTEP), as well as central and local institutional review boards (IRBs). All patients and healthy donors gave informed consent before participation in these studies.

Introduction Sézary syndrome (SS) is an aggressive, leukemic subtype of cutaneous T-cell lymphoma (CTCL) with a median survival of 3-5 years. Approved therapies include skin-directed therapy, radiation, and systemic therapies such as chemotherapy, histone deacetylase (HDAC) inhibitors, interferon, extracorporeal photopheresis (ECP), and oral retinoids. There is no consensus first-line therapy for SS and there is limited data regarding prognostic biomarkers. We assessed treatment patterns, outcomes, and racial differences at our institution. Methods We performed a retrospective review of 62 patients at Winship Cancer Institute of Emory University from 1990-2020 with a confirmed diagnosis of SS. Clinical data collected from the electronic medical record included demographics, baseline laboratory values, disease characteristics, and therapy. Clinical outcomes were measured by overall survival (OS) and time to next treatment (TTNT). OS was measured from time of diagnosis to date of death or last follow-up. TTNT was defined as the number of months from the start of the first line of therapy until the initiation of the subsequent therapeutic regimen. Descriptive analysis was performed for each variable and a comparison between African American (AA) and white patients was performed using ANOVA for numerical covariates and chi-square test or Fisher's exact test for categorical covariates. Kaplan-Meier curves for OS and TTNT were generated for the whole cohort. A Kaplan-Meier curve was also generated to compare time from diagnosis to initiation of first systemic therapy stratified by race along with the log-rank p-value. The univariate association of baseline variables with OS and TTNT was assessed by Cox proportional hazards models and the multivariable analyses (MVA) were performed on variables that had p-value less than 0.05 on univariate analyses. Results Males made up (58.1%) of our patients and the median age at diagnosis was 65.9 years. Nearly one-half (45.2%) of patients were AA. The median Sézary count at diagnosis was 1320 cells/uL. The median time from diagnosis to first systemic therapy was 2.4 months and the median number of systemic therapies was 3.0. Information regarding systemic treatments received after diagnosis is presented inTable 1. The most common first-line systemic therapies were oral retinoids (43.5%), ECP (32.3%), and interferon (30.6%). HDAC inhibitors and total skin electron beam (TSEB) radiation were common treatments beyond first line (46.8% received HDAC inhibitors, 38.7% received TSEB), but were rarely used in the first-line setting. The median OS and TTNT were 3.1 years and 6.3 months, respectively(Figure 1). In MVA, elevated WBC and LDH were significantly associated with shorter OS (WBC HR: 1.05, 95% CI: 1.01-1.08, p=0.01; LDH HR: 1.003, 95% CI: 1.001-1.005, p=0.011) and shorter TTNT (WBC HR: 1.04, 95% CI: 1.002-1.08, p=0.041; LDH HR: 1.002, 95% CI: 1.001-1.004, p=0.048). In analysis by race, AA patients had a higher proportion of females compared to non-hispanic white patients (53.6% vs 28.1%, p=0.045). AA patients also had lower median hemoglobin at diagnosis (12.6 vs 14.3, p=0.036), higher median LDH at diagnosis (360 vs 232, p=0.002), and longer median time from diagnosis to first systemic therapy compared to non-hispanic white patients (3.17 months vs 2.14 months, p=0.039,Figure 2). Conclusions SS is an aggressive subtype of CTCL with no consensus first-line therapy and limited data on prognostic biomarkers. In our cohort, oral retinoids, ECP, and interferon were the most commonly utilized treatments in the first-line setting. Elevated WBC and LDH were significantly associated with both OS and TTNT which suggests that these may have value as prognostic biomarkers in SS. AA patients may have delayed time from diagnosis to starting systemic therapy and higher LDH at diagnosis. This data is hypothesis-generating and should be validated in larger, prospective studies. Disclosures Allen: Bayer:Consultancy, Other;Imbrium:Consultancy, Other;Research to Practice:Speakers Bureau;Clinical Care Options:Speakers Bureau;Curio Sciences:Honoraria.

3601 Background: A minimum of 12 lymph nodes are required during colectomy to accurately stage colon cancer. Prior studies in stage II colon cancer patients demonstrate association of inadequate lymph node examination (LNE) with worse overall survival (OS). No large-scale analogous studies related to LNE have been completed in stage I colon cancer patients. We evaluated patients with stage I colon cancer to determine the association between lymph node yield and OS. Methods: We reviewed the National Cancer Database between 2004-2015 to identify patients with pathologic stage I colon cancer (pT1N0 or pT2N0) who underwent definitive surgical resection. Patients who received radiation therapy or had missing values were excluded. Clinical and demographic characteristics were analyzed. Based on LNE, patients were stratified into 4 cohorts (LNE, 0-5, 6-11, 12-19, 20+) and 2 cohorts (0-11, 12+). Univariable and multivariable analyses were performed to identify variables associated with OS. Kaplan-Meier survival curves were computed to compare the cohorts. Results: We included 81,909 patients for analyses. Median age at diagnosis was 69. A majority were female (51.1%), white (83.8%), received care in a community cancer program (59.5%), and had a Charlson-Deyo score of 0 (66.6%). Only 0.7% of patients had a margin positive resection with a 2.5cm median tumor size. Patients were similarly split between pT1 and pT2. Suboptimal LNE was noted in 27.8% of patients. Patients with LNE were distributed - 10.7% (0-5), 17.1% (6-11), 43.4% (12-19) and 28.9% (20+). Postoperative 30-day mortality was 1.9%. 521 (0.7%) received systemic therapy. Ten-year survival in patients with 0-5 LNE was 52.8% compared to 60.1% with 20+ LNE. On multivariable analyses, patients aged ≥ 69, male sex, increasing tumor size (quartile), pT2 staging and a higher Charlson-Deyo score independently predicted worse OS (p < 0.001). LNE categories were significantly associated with OS (p < 0.001) (Table). On regrouping into 0-11 and 12+ LNE groups, 0-11 LNE group predicted worse OS (HR 1.22, p < 0.001). On multivariable analysis, the above variables continued to show similar association with OS (p < 0.001). Conclusions: Our study demonstrates that lymph node yield is associated with overall survival in patients with stage 1 colon cancer undergoing surgical resection. Furthermore, patients with suboptimal lymph node yield are associated with an inferior overall survival compared to those with optimal lymph node yield. Moreover, this study finds that a large number of patients ( > 25%) continue to have suboptimal lymph node yields. Future efforts should focus on improving the lymph node yield with optimal efforts by the surgeon and pathologist. Future studies should examine the role of systemic therapy in patients with inadequate lymph node yield.[Table: see text]

e16085 Background: Treatment of localized esophageal, gastroesophageal junction (GEJ), and stomach cancer is neoadjuvant therapy with either chemoradiation or chemotherapy followed by surgery. Treatment for T1b-2 stage disease is not well evaluated and this stage is underrepresented in prospective studies. The aim of this study is to evaluate survival outcomes among the three treatment modalities (neoadjuvant chemotherapy (NACT), neoadjuvant chemoradiation (NACRT), and upfront surgery (US)) in this population using the National Cancer Database (NCDB). Methods: Patients (pts) with clinical stage T1b-2N0 and any pathological stage (excluding metastatic) adenocarcinoma of the esophagus, GEJ, and stomach treated with neoadjuvant therapy or upfront surgery, with or without adjuvant chemotherapy (AC), were identified between 2004 and 2015 in the NCDB. Univariate and multivariable analyses were conducted, and Kaplan-Meier analysis and Cox proportional hazard models were used to identify the association between the three treatment modalities and overall survival (OS). Results: A total of 2260 pts were analyzed. The median follow-up was 66.6 months. The median age was 67 years. Most pts were White (86%) and male (77%). 1018 (45%) had moderately-differentiated grade, while 946 (42%) had poorly-differentiated/undifferentiated grade. The most common site of disease was the lower third of esophagus (34.1%). 161 pts (7%) received NACT, of whom 45 pts received AC; 537 pts (24%) received NACRT, of whom 40 pts received AC. 1562 pts (69%) underwent US, of whom 146 pts received AC. US with AC was associated with the best survival, followed by NACT with AC; median OS was 90.1 and 86.8 months for surgery with AC and NACT with AC, respectively. NACRT was associated with the worst survival (39.5 and 40.2 months with and without AC, respectively). The 5-year OS rates were 59.8%, 58.5%, 52.1%, 44.9%, 37.3%, and 37.8%, for US, NACT, and NACRT, with and without AC, respectively. The rate of tumor upstaging was highest in the NACT group, followed by the NACRT group, and lowest in the US group. Postsurgically, 62 (39%) and 48 (30%) pts in the NACT group and 198 (37%) and 161 (30%) pts in the NACRT group had upstaging in their T and N stages, respectively, compared to 214 (13%) and 326 (21%) pts in the US group. For the 1107 pts who also had pathological T1b-2N0 stage disease following US, no difference in survival was observed with or without AC. Conclusions: Upfront surgery with adjuvant chemotherapy and perioperative chemotherapy are associated with the best survival compared to preoperative radiotherapy. This is the largest study to address the best approach for the treatment of T1b-2 stage disease.

Key Points Question Is a cancer facility’s radiation case volume associated with long-term outcomes in men with advanced prostate cancer who were treated with primary radiation therapy? Findings In this cohort study of 1899 men from a large US cancer database, men with node-positive prostate cancer undergoing curative-intent radiation therapy with concurrent androgen deprivation therapy had significantly improved median survival rates if they were treated at facilities with a high volume of such patients, independent of academic affiliation. Meaning Node-positive prostate cancer is a complex disease entity with the potential for long-term disease control with aggressive management, and these findings suggest that treatment at a high-volume radiation center is associated with improved long-term oncologic outcomes., This cohort study evaluates the association between radiation facility case volume and overall survival among men with node-positive prostate cancer., Importance Long-term control of node-positive (N1) prostate cancer, the incidence of which is increasing, is obtainable with aggressive treatment, and definitive external beam radiation therapy (EBRT) with long-term androgen deprivation therapy (ADT) is an increasingly preferred option. Caring for these patients is complex and may require resources more readily available at high-volume centers. Objective To evaluate the association between radiation facility case volume and overall survival (OS) in men with N1 prostate cancer. Design, Setting, and Participants This cohort study included 1899 men diagnosed with T1N1M0 to T4N1M0 prostate cancer treated with curative-intent EBRT and ADT between January 2004 and December 2016 at US facilities reporting to the National Cancer Database. Data analysis was performed from March to June 2020. Exposures Treatment at a center with high vs low average cumulative facility volume (ACFV), defined as the total number of prostate radiation cases at an individual patient’s treatment facility from 2004 until the year of that patient’s diagnosis. Main Outcomes and Measures OS was assessed between high- vs low-ACFV centers using the Kaplan-Meier method with and without propensity score–based weighted adjustment and multivariable Cox proportional hazards. The nonlinear association between continuous ACFV and OS was examined through a Martingale residual plot, and the optimal ACFV cutoff point that maximized the separation between high vs low ACFV was identified via a bias adjusted log rank test. Results A total of 1899 men met inclusion criteria. The median (interquartile range) age was 66 (60-72) years, 1491 (78.5%) were White individuals, and 1145 (60.3%) were treated at nonacademic centers. The optimal ACFV cutoff point was 66.4 patients treated per year. The median OS for patients treated at high-ACFV vs low-ACFV centers was 111.1 (95% CI, 101.5-127.9) months and 92.3 (95% CI, 87.7-103.9) months, respectively (P = .01). On multivariable analysis, treatment at a low-ACFV center was associated with increased risk of death (HR, 1.22; 95% CI, 1.02-1.46, P = .03) compared with treatment at a high-ACFV center. These results persisted after propensity score–based adjustment. Conclusions and Relevance This cohort study found a significant association of facility case volume with long-term outcomes in men with N1 prostate cancer undergoing EBRT with ADT. Specifically, treatment at a facility with high radiation case volume was independently associated with longer OS. Further studies should focus on identifying which factors unique to high-volume centers may be responsible for this benefit.

e13085 Background: The specifics of the salvage regimen gemcitabine/carboplatin (G/C) in metastatic breast cancer (MBC) are not well-characterized and are limited to the clinical trial setting, which often excludes heavily pretreated patients with high disease burden and velocity. The primary objective of this study is to assess real-world outcomes in patients with MBC treated with G/C. Methods: A retrospective chart review was conducted on adults with MBC who received >1 dose of G/C at Emory Healthcare / Winship Cancer Institute from December 1, 2005 to April 30, 2019 (n = 109). Patients were stratified by receptor status (hormone receptor (HR), triple-negative (TN), and human epidermal growth factor receptor-2 (HER2)). Results: Patients were heavily pretreated (median 2 lines, range 0-11) and had extensive metastatic disease (median 3 sites, range 1-6). The median starting doses were carboplatin AUC 2 (range: 1.5-5) and gemcitabine 1000 mg/m2 (range 400-1100). The median cycle length was 21 days (range 14-28). The median progression-free survival (mPFS) was 3.7 months and median overall survival (mOS) was 7.7 months. OS at 24 months was 23.1%. Previous immunotherapy, radiation for palliation, or historical receipt of neoadjuvant/adjuvant cytotoxic therapy was significantly associated with improved survival outcomes, while possessing lung, liver, or bone metastases was significantly associated with worse survival outcomes. The presence of brain metastases did not correlate with outcomes. Side effect/intolerance led to dosing and scheduling adjustments in 38.5% and 49.5% of patients, respectively, and resulted in treatment discontinuation in 21% of patients. Hospitalization occurred in 51.4% of patients on treatment. Conclusions: G/C is a safe and effective regimen in real-world MBC patients regardless of receptor subtype. Even low doses of G/C may provide some CNS penetration and control. Improved survival outcomes associated with previous immunotherapy and radiation for palliation may be due to disease control or carry over effect and warrant further study. [Table: see text]

144 Background: A number of studies have demonstrated that overweight and early obese states are associated with improved survival in renal and melanoma cancer patients. The purpose of this study was to investigate the impact of BMI on outcomes of GI cancers treated with SMIs. Methods: A retrospective chart review was conducted to compare outcomes between patients with BMIs ≥ 25 and < 25 who received treatment at Winship between 1/2010-8/2019. The primary objective was to determine the PFS, OS, and ADR rates of patients with BMI ≥ 25 treated with SMIs compared to patients with BMIs < 25. PFS and OS rates were estimated with the Kaplan-Meier method and compared between the groups using the log-rank test. The incidence of adverse events was estimated as frequency and percentage and logistic regression was used to estimate the impact of BMI on adverse effects. Results: 269 patients were included in analysis for PFS, 61 for OS and 281 for ADR rate analysis. Diagnoses included HCC (n = 123, 44%) and CRC (n = 158, 56%). There was no significant difference seen in PFS and OS between the BMI < 25 and BMI ≥ 25 groups (HR 1.17 (0.87-1.56), p = 0.291, HR 1.10 (0.66-1.84), p = 0.713, respectively). A significant difference was demonstrated in the rates of adverse reactions between the two groups (OR 0.31 (0.19-0.52), p [Table: see text]

Background Autologous stem cell transplant (ASCT) is frequently used as a consolidative therapy option after induction treatment in fit patients with mantle cell lymphoma (MCL) with the goal of prolonging the initial response duration. Despite recent advances there remains a subset of patients who experience early disease relapse after ASCT. We examined predictors of shortened progression-free survival (PFS) and post-relapse overall survival (OS) in a cohort of patients completing ASCT in first remission. Methods We evaluated MCL patients treated at 10 US academic medical centers. Eligible patients were treated from 2000 through 2017, and we collected information on demographic, clinical, and treatment-related variables of interest. Patients were then categorized into three post-ASCT PFS groups: 0-2 years, 2-5 years, and > 5 years, with PFS determined from the date of ASCT until progression or death from any cause. Patients followed for at least 5 years post-ASCT who were relapse free were included in the > 5 sub group. Associations were examined between groups and collected characteristics using chi-squared tests for categorical patient characteristics and ANOVA for numeric patient characteristics. The Kaplan-Meier method was used to estimate overall survival (OS) for each group, using time of relapse after ASCT as the starting point. Results Of 968 total MCL patients, 242 patients completed ASCT in first remission and either had a PFS event or were relapse-free for at least 5 years post-ASCT. Patients were 80% male, and the median age was 59 (Range: 29-83). The patients were divided into groups of post-ASCT PFS 0-2 years (n=74), 2-5 years (n=75), and more than 5 years (n=93). Post-ASCT PFS was shorter in patients with stage 4 disease (p=0.022), splenomegaly at baseline (p=0.005), and a lymph node size > 5 centimeters at baseline (p=0.043). Other variables were not significantly associated with PFS, including time to transplant and use of intensive therapy. Patients with 0-2 year PFS had a shorter median OS (22.1 months, 95% CI: 13.1- 38.1 months) in comparison to 2-5 year PFS (132 months, 95% CI: 36-132 months) and 5+ year PFS not reached (95% CI: 41.2 – N.A; Figure). Conclusion Patients with higher tumor burden at baseline have a shorter post-ASCT PFS and are more likely to relapse within 2 years. As has been seen in other lymphoma subtypes, early relapse is associated with shorter OS. This represents a patient group requiring improved therapies and perhaps are the best candidates for post-ASCT maintenance or consolidation approaches. Further studies integrating minimal residual disease and molecular risk-stratification may better identify patients at high risk for early progression.

INTRODUCTION The optimal frontline treatment for mantle cell lymphoma (MCL) is not clearly defined. Bendamustine + rituximab (BR) is commonly used as initial therapy. The role of maintenance rituximab (MR) after BR is not agreed upon due to limited data supporting this practice, whereas MR improves overall survival (OS) after autologous stem cell transplant (ASCT) and after R-CHOP for elderly patients who do not receive ASCT. Preliminary results from a subgroup analysis of the randomized phase 3 MAINTAIN study revealed neither a progression-free survival (PFS) nor OS benefit for MR as compared to observation for MCL pts (Rummel, ASCO 2016). In follicular lymphoma patients, however, there does appear to be a PFS benefit to rituximab maintenance following BR. Given these disparate results, we sought additional data to evaluate the role of rituximab maintenance following BR in MCL METHODS MCL pts treated at 12 U.S. medical centers with frontline BR who achieved a complete response (CR) or partial response (PR) and who did not receive consolidative ASCT from 2011 - 2017 were included. Use of MR was based on individual physician/patient preferences. Baseline pt characteristics were compared using chi-squared test, Fisher's exact tests, or ANOVA. Descriptive statistics, comparisons, and OS using the Kaplan-Meier method were stratified by response status as determined by the treating site (complete response (CR) only, partial response (PR) only, and CR/PR). RESULTS Among 135 pts responding to frontline BR who did not complete subsequent ASCT, 80% achieved complete remission (CR) and 20% had a partial remission (PR). Median age was 70 (range 45 - 93) years and 66% were male. Baseline MIPI score was low (13%), intermediate (38%), or high (49%) among patients with available data (n = 92) and did not differ between treatment cohorts. Among responding patients, 78 (58%) received MR and 57 (40%) were observed. With a median follow up of 3.1 years, median OS was not reached for pts responding to BR (with CR or PR) who received MR vs. 6 years for those who received no maintenance (Figure Panel A, P = 0.0013). Use of MR vs. observation was associated with a significant improvement in OS for pts in PR at the end of induction therapy (Figure Panel B, median not reached vs. 1.7 years, P = 0.006), but there was no statistically significant OS difference for pts in CR (Figure Panel C, median not reached vs. 9.6 years, P = 0.2575). In multivariable analysis, MIPI score CONCLUSIONS Whereas the MAINTAIN trial showed no PFS advantage to MR after BR for MCL pts, in this multi-center outcomes analysis across multiple US centers, the use of MR was associated with an improvement in OS in pts receiving frontline BR without consolidative ASCT. The survival benefit was only observed for pts in PR after induction therapy. Because of the potential for selection bias in the application of MR, further validation cohorts and prospective study are needed to clarify if there is benefit to maintenance therapy after BR-treated patients not undergoing ASCT as well as the potential for differential benefit of maintenance based on remission status Disclosures Hill: Takeda: Research Funding; Amgen: Research Funding; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding. Martin:Janssen: Consultancy; I-MAB: Consultancy; Celgene: Consultancy; Sandoz: Consultancy; Karyopharm: Consultancy; Teneobio: Consultancy. Calzada:Seattle Genetics: Research Funding. Kolla:Amgen: Equity Ownership. Bachanova:Gamida Cell: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; GT Biopharma: Research Funding; Novartis: Research Funding. Gerson:Abbvie: Consultancy; Seattle Genetics: Consultancy; Pharmacyclics: Consultancy. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Celgene: Research Funding; Merck: Research Funding; Mundipharma: Honoraria; Seattle Genetics: Honoraria, Research Funding; Celgene: Research Funding; Mundipharma: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Bayer: Consultancy, Research Funding. Danilov:Curis: Consultancy; Bristol-Meyers Squibb: Research Funding; TG Therapeutics: Consultancy; Abbvie: Consultancy; Genentech: Consultancy, Research Funding; Bayer Oncology: Consultancy, Research Funding; Takeda Oncology: Research Funding; MEI: Research Funding; Pharmacyclics: Consultancy; Aptose Biosciences: Research Funding; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Seattle Genetics: Consultancy; AstraZeneca: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Celgene: Consultancy; Janssen: Consultancy. Grover:Seattle Genetics: Consultancy. Karmali:Takeda, BMS: Other: Research Funding to Institution; Astrazeneca: Speakers Bureau; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Ghosh:Celgene: Consultancy, Research Funding, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy, Speakers Bureau; Spectrum: Consultancy, Speakers Bureau; Astra Zeneca: Speakers Bureau; Forty Seven Inc: Research Funding; Genentech: Research Funding; Gilead/Kite: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau. Park:G1 Therapeutics: Consultancy; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; Teva: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Epperla:Pharmacyclics: Honoraria; Verastem Oncology: Speakers Bureau. Hamadani:Otsuka: Research Funding; Merck: Research Funding; Celgene: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Janssen: Consultancy; Sanofi Genzyme: Research Funding, Speakers Bureau; Pharmacyclics: Consultancy; Medimmune: Consultancy, Research Funding; Takeda: Research Funding. Kahl:Seattle Genetics: Consultancy; BeiGene: Consultancy; TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy, Research Funding. Flowers:Optimum Rx: Consultancy; Acerta: Research Funding; Gilead: Consultancy, Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; AbbVie: Consultancy, Research Funding; Bayer: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Millenium/Takeda: Research Funding; V Foundation: Research Funding; Karyopharm: Consultancy; BeiGene: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Burroughs Wellcome Fund: Research Funding; AstraZeneca: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy; Denovo Biopharma: Consultancy. Cohen:Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; LAM Therapeutics: Research Funding; UNUM: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; Genentech, Inc.: Consultancy, Research Funding.

Introduction: Smoking is a potential risk factor for the development of non-Hodgkin lymphoma (NHL), and prior studies have reported inferior survival in tobacco users with certain subtypes of the disease (Taborelli et al, BMC Cancer, 2017; Ollberding et al, Br J Haematol, 2013). For instance, tobacco smokers with NHL had an inferior overall survival (OS) compared to non-smokers in a series of 471 patients who were managed up front with either chemotherapy (68%), radiation (27%), or observation, and this appeared to be most pronounced in patients with follicular lymphoma and in those with a 20+ pack year smoking history (Geyer et al, Cancer, 2010). The impact of tobacco use on survival specifically in patients with mantle cell lymphoma (MCL) has not been well studied. We conducted a multicenter study in MCL and evaluated the prognostic impact of tobacco use. Methods: We included patients with MCL from 12 sites who were ≥18 years old and for whom smoking status was known at the time of diagnosis. Cases were evaluated for reported smoking status at the time of diagnosis (active smoker, prior smoker, or never smoker) and standard baseline clinical prognostic data were obtained for each patient. Descriptive statistics were generated for these characteristics and were then compared across smoking status using chi-squared tests, Fisher's exact tests, or ANOVA, where appropriate. Overall survival (OS) and progression free survival (PFS) were estimated using the Kaplan-Meier method, and were compared using log-rank tests. Results: Of 946 included patients, 456 (48.2%) reported never using tobacco, 360 (38.7%) reported prior tobacco use, and 130 (13.7%) reported active tobacco use at the time of diagnosis. Median age was 59 in the active smoker group, 65 in prior smokers, and 61 in never smokers (p < 0.001). Any major medical comorbidity (defined as the presence of CAD, CHF, diabetes, CKD, ESRD, COPD, DVT, prior malignancy, or cirrhosis) was present in 59 (45.4%) of the active smokers, 143 (39.7%) of the prior smokers, and 140 (30.7%) of the never smokers (p = 0.002). Intensive induction regimens were used in 58.2% of active smokers, 47.2% of prior smokers, and 58.4% of never smokers (p=0.007). There were no significant differences between groups in regards to sex, race, ECOG performance status, Ann Arbor stage, time to first treatment, and use of auto transplant in first remission. Patients with no prior history of tobacco use were less likely to have a high risk MIPI score at diagnosis (26% high risk) compared to prior smokers (39.5%) and active smokers (32.5%, p=0.019). With a median follow up of 3.5 years after diagnosis, there was no significant difference between the 3 groups with regards to PFS or OS (Figure 1). Five-year OS in the never smoker group was 79.8% (95% CI: 74.8%, 83.9%) vs 75.1% (64.5%, 82.9%) in the active smoker group, and 80.6% (74.6%, 85.3%) in the prior smoker group (log rank p = 0.4079). Five- year progression free survival was 50.4% (44.6%, 56.0%) in the never smoker group, 42.5% (32.2%, 52.5%) in the active smoker group, and 50.2% (43.5%, 56.6%) in the prior smoker group (log rank p= 0.3595). Conclusions: Our data suggest that active or prior smoking does not significantly impact OS or PFS in patients with MCL. This study is limited by the fact that amount of current or former tobacco use was not available and it is not known how many current tobacco users ultimately stopped smoking during the course of their treatment. Future studies should incorporate more specific information regarding smoking history including pack-years and time between discontinuation of tobacco use and date of diagnosis. While tobacco use and other modifiable cardiovascular risk factors should be addressed as appropriate for all patients with MCL, current and former tobacco users can still achieve prolonged PFS and OS and may be candidates for intensive treatments after consideration of their other comorbidities and disease-specific risk factors. Disclosures Calzada: Seattle Genetics: Research Funding. Kolla:Amgen: Equity Ownership. Bachanova:Gamida Cell: Research Funding; GT Biopharma: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Celgene: Research Funding; Novartis: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees. Gerson:Seattle Genetics: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Mundipharma: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Takeda: Research Funding; Merck: Research Funding; Mundipharma: Honoraria; Bayer: Consultancy, Research Funding; Seattle Genetics: Honoraria, Research Funding. Danilov:Celgene: Consultancy; Abbvie: Consultancy; TG Therapeutics: Consultancy; Bayer Oncology: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Janssen: Consultancy; AstraZeneca: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Aptose Biosciences: Research Funding; Bristol-Meyers Squibb: Research Funding; MEI: Research Funding; Pharmacyclics: Consultancy; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Curis: Consultancy; Takeda Oncology: Research Funding; Seattle Genetics: Consultancy. Grover:Seattle Genetics: Consultancy. Karmali:Astrazeneca: Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Hill:Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; AstraZeneca: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celegene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ghosh:Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Speakers Bureau; Genentech: Research Funding; Celgene: Consultancy, Research Funding, Speakers Bureau; Forty Seven Inc: Research Funding; Gilead/Kite: Consultancy, Speakers Bureau; Spectrum: Consultancy, Speakers Bureau; AbbVie: Consultancy, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; Astra Zeneca: Speakers Bureau. Park:BMS: Consultancy, Research Funding; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; G1 Therapeutics: Consultancy; Teva: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Epperla:Pharmacyclics: Honoraria; Verastem Oncology: Speakers Bureau. Hamadani:Pharmacyclics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Merck: Research Funding; Celgene: Consultancy; Janssen: Consultancy; Medimmune: Consultancy, Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Otsuka: Research Funding; Takeda: Research Funding. Kahl:TG Therapeutics: Consultancy; BeiGene: Consultancy; Seattle Genetics: Consultancy; ADC Therapeutics: Consultancy, Research Funding. Martin:Janssen: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Teneobio: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy. Flowers:Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Burroughs Wellcome Fund: Research Funding; AbbVie: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; Spectrum: Consultancy; AstraZeneca: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; Bayer: Consultancy; Acerta: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Optimum Rx: Consultancy; Millenium/Takeda: Research Funding; Eastern Cooperative Oncology Group: Research Funding; National Cancer Institute: Research Funding; V Foundation: Research Funding; BeiGene: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; TG Therapeutics: Research Funding. Cohen:Genentech, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; LAM Therapeutics: Research Funding; UNUM: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding.

Background: Early progression of disease (POD) in patients (pts) with mantle cell lymphoma (MCL) following intensive frontline treatment has been associated with inferior survival (Dietrich et al Ann Oncol 2014 and Visco et al Br J Haematol 2019), but the optimal time point to define early POD and the predictive significance of early POD following less intensive frontline treatment is not well established. We compare outcomes after all frontline treatments in a large MCL cohort categorized by time to progression and describe outcomes by class of second line treatment for pts with primary refractory disease. Methods: Clinical and outcome data for MCL pts treated between 2000 and 2017 were collected from 12 US centers. Overall survival (OS), defined from time of 1st progression, and secondary progression free survival (PFS2), defined from 1st progression to 2nd progression or death, were estimated by Kaplan-Meier and compared by log-rank test. Univariable and multivariable analyses were performed using Cox proportional hazards models for OS. 95% confidence intervals were calculated for all estimates and displayed in square brackets. We defined intensive treatment as high dose cytarabine in frontline therapy and/or autologous stem cell transplant in 1st remission. Pts were categorized into three groups: (a) refractory disease to frontline therapy or POD within 6 months of frontline therapy was termed primary refractory (PRF); (b) POD between 6 to 24 months of therapy was termed POD24 and (c) POD beyond 24 months was termed POD>24. Salvage therapy was categorized as chemoimmunotherapy (CIT) for pts treated with CIT alone, BTK inhibitor (BTKi) for pts treated with BTKi single agent or in combination, and lenalidomide / bortezomib for pts treated with one or both agent +/- anti-CD20 therapy. Results: Of 1,168 pts with MCL, 457 pts had relapsed and were included in this analysis. The median age was 62, 77% were male, and ECOG PS was 0/1 in 94%. Median follow-up was 2.6 years (yr) after first progression. The most common induction regimens were R-HyperCVAD (26%), R-CHOP (24%), bendamustine and rituximab (19%), and R-M-CHOP (10%). Frontline treatment was intensive in 54%. Sixty five pts (14%) were PRF, 153 (34%) had POD24, and 239 (53%) had POD>24. Additional baseline characteristics and comparison between groups are summarized in Table 1. The median OS was 1.3 yr [0.9-2.4] for PRF pts, 3 yrs [2-6.8] for POD 24, and 8 yrs [6.2-not reached (NR)] for POD>24 (p24 pts (p Among pts with PRF MCL, median PFS2 and OS were 1.2 [0.5-2.3] and 2.4 [0.7-4.5] yrs for BTKi (n=21), 0.5 [0.2-2.3] and 1.1 [0.5-NR] yrs for CIT (n=22), and 0.3 [0.1-0.6] and 1.9 [0.1-2] yrs for lenalidomide / bortezomib (n=8) as 2nd line therapy. Two pts with PRF MCL received no further therapy and both died within one month of POD. Conclusions: Time to relapse is predictive of outcome in pts with MCL and outcomes with current salvage therapies are poor for pts with relapse within 6 months of frontline therapy. Of currently available second line therapies, BTKi were associated with improved PFS2 in refractory pts. Outcomes are particularly poor for pts who receive intensive induction therapies yet still relapse early, representing a population at high risk for early mortality related to MCL. Novel treatment approaches should be evaluated in this population, including CAR-T cell therapy, and attempts to improve risk stratification at diagnosis and develop improved therapies for high-risk pts should continue. Disclosures Maddocks: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Research Funding; Merck: Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Teva: Membership on an entity's Board of Directors or advisory committees. Kolla:Amgen: Equity Ownership. Bachanova:Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Research Funding; Novartis: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees; Incyte: Research Funding; Celgene: Research Funding; GT Biopharma: Research Funding. Gerson:Abbvie: Consultancy; Seattle Genetics: Consultancy; Pharmacyclics: Consultancy. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Merck: Research Funding; Mundipharma: Honoraria; Bayer: Consultancy, Research Funding; Seattle Genetics: Honoraria, Research Funding; Takeda: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Mundipharma: Honoraria. Hill:Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding. Martin:Karyopharm: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Teneobio: Consultancy. Danilov:Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Bristol-Meyers Squibb: Research Funding; Aptose Biosciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; TG Therapeutics: Consultancy; Curis: Consultancy; Seattle Genetics: Consultancy; Celgene: Consultancy; MEI: Research Funding; Janssen: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy; Takeda Oncology: Research Funding; AstraZeneca: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Genentech: Consultancy, Research Funding. Grover:Seattle Genetics: Consultancy. Karmali:Takeda, BMS: Other: Research Funding to Institution; Astrazeneca: Speakers Bureau; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau. Ghosh:AstraZeneca: Honoraria, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Speakers Bureau; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding, Speakers Bureau; SGN: Consultancy, Honoraria, Research Funding, Speakers Bureau; TG Therapeutics: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Research Funding; Genentech: Research Funding; Forty Seven Inc: Research Funding. Park:BMS: Consultancy, Research Funding; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; G1 Therapeutics: Consultancy; Teva: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Epperla:Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Hamadani:Pharmacyclics: Consultancy; Merck: Research Funding; Celgene: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Janssen: Consultancy; Otsuka: Research Funding; Medimmune: Consultancy, Research Funding; Takeda: Research Funding. Kahl:BeiGene: Consultancy; TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy. Flowers:Gilead: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; AstraZeneca: Consultancy; Denovo Biopharma: Consultancy; National Cancer Institute: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Bayer: Consultancy; AbbVie: Consultancy, Research Funding; V Foundation: Research Funding; Optimum Rx: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Karyopharm: Consultancy; Burroughs Wellcome Fund: Research Funding; TG Therapeutics: Research Funding; Acerta: Research Funding; Pharmacyclics/Janssen: Consultancy, Research Funding; Spectrum: Consultancy. Cohen:LAM Therapeutics: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; Astra Zeneca: Research Funding; Genentech, Inc.: Consultancy, Research Funding; Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; ASH: Research Funding; Lymphoma Research Foundation: Research Funding; Hutchison: Research Funding; UNUM: Research Funding.

Introduction: Mantle cell lymphoma (MCL) is a rare form of lymphoma with no current standard of care. As a result, clinical trials are critical to improving our understanding of the disease and its management. However, clinical trial participation is often limited due to lack of access to studies, restrictive eligibility criteria, and decisions by treating physicians or patients not to participate. We evaluated the rate of enrollment and outcomes associated with clinical trial participation of patients with MCL at 12 US Medical Centers. Methods: We included patients from 12 medical centers in the United States with MCL diagnosed between January 1, 2000, and January 1, 2018, who were ≥ 18 years old, received any induction therapy, and for whom it was known whether initial treatment was on a clinical trial (CT) or not. We compared differences between the two groups (CT vs not) using Fisher's Exact and Chi-square tests as appropriate. We defined overall survival (OS) as time from diagnosis to death. Patients not experiencing an event were censored at their last known follow-up. OS was determined using the Kaplan-Meier method, and univariate and multivariable models were developed to identify predictors of OS. Results: Eight hundred twelve patients were included in this analysis, including 164 (20%) patients who participated in a clinical trial during initial therapy. Rate of participation ranged from 4% to 36% across contributing sites. Median age for the entire cohort was 62 years, 572 (74%) of patients were male, and 95% of patients had ECOG 0-1. MCL International Prognostic Index (MIPI) risk score was high in 163 patients (31%), and 84% of patients had stage IV disease. Ki67 was >30% in 169/225 (43%) patients with available data, and 19% of patients (65/271) had a complex karyotype with > 3 chromosomal abnormalities. Four hundred sixteen (53%) of patients received an intensive induction regimen (defined as initial treatment with a high-dose cytarabine-containing regimen and/or receipt of autologous hematopoietic cell transplantation as consolidation), including 333 patients (43%) who underwent transplant consolidation. Patients with an increased lactate dehydrogenase (LDH) level (p 3 cytogenetic abnormalities (p=0.015) were less likely to participate in clinical trials, but there was no significant difference in rates of participation based on MIPI (p=0.49) or ECOG performance status (p=0.22; Table). Patients treated on study were less likely to receive an intensive regimen compared to those treated off study (p=0.002). Median time to treatment from diagnosis was 35 days for patients enrolled on trial and 31 days for patients not enrolled on trial (p=0.83). With a median follow-up of 3.8 years, the median OS was 13.6 years (95% CI: 11.5-21.1) for patients not treated on a trial and not reached (95% CI: 9.9 - Not Reached) for patients treated on trial (Figure; p=0.036). In a multivariable model including clinical trial participation, MIPI, time to initial treatment, and receipt of an intensive induction regimen, only clinical trial participation (HR 0.54, 95%CI: 0.31-0.93; p=0.028) and high risk MIPI score (HR 4.24, 95% CI: 2.37-7.56; p Conclusions: Participation in a clinical trial is associated with improved OS among patients with untreated MCL, even when accounting for time to initial treatment and MIPI score. This study is unable to account for other factors that may predict trial participation including baseline comorbidities, socioeconomic status, social support, and distance to the treating center that are frequently factors that limit trial participation. However, these findings do suggest that enrollment on a clinical trial frequently leads to a successful outcome for patients in addition to providing answers to key clinical questions and should be considered for all eligible patients. Disclosures Cohen: Janssen Pharmaceuticals: Consultancy; Seattle Genetics, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; UNUM: Research Funding; LAM Therapeutics: Research Funding; Hutchison: Research Funding; Genentech, Inc.: Consultancy, Research Funding; ASH: Research Funding; Lymphoma Research Foundation: Research Funding; Astra Zeneca: Research Funding. Calzada:Seattle Genetics: Research Funding. Kolla:Amgen: Equity Ownership. Bachanova:Incyte: Research Funding; Novartis: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Research Funding; GT Biopharma: Research Funding; Celgene: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees. Gerson:Abbvie: Consultancy; Seattle Genetics: Consultancy; Pharmacyclics: Consultancy. Barta:Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Mundipharma: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Seattle Genetics: Honoraria, Research Funding; Bayer: Consultancy, Research Funding; Mundipharma: Honoraria; Merck: Research Funding; Celgene: Research Funding. Danilov:MEI: Research Funding; Seattle Genetics: Consultancy; Janssen: Consultancy; AstraZeneca: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; TG Therapeutics: Consultancy; Curis: Consultancy; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Celgene: Consultancy; Aptose Biosciences: Research Funding; Takeda Oncology: Research Funding; Bayer Oncology: Consultancy, Research Funding; Bristol-Meyers Squibb: Research Funding; Abbvie: Consultancy; Pharmacyclics: Consultancy. Grover:Seattle Genetics: Consultancy. Karmali:Astrazeneca: Speakers Bureau; Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution. Hill:TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding. Ghosh:Spectrum: Consultancy, Speakers Bureau; Gilead/Kite: Consultancy, Speakers Bureau; Astra Zeneca: Speakers Bureau; Seattle Genetics: Consultancy, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; Forty Seven Inc: Research Funding; Genentech: Research Funding; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; AbbVie: Consultancy, Speakers Bureau. Park:BMS: Consultancy, Research Funding; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; G1 Therapeutics: Consultancy; Teva: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Epperla:Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Hamadani:Otsuka: Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Janssen: Consultancy; Merck: Research Funding; ADC Therapeutics: Consultancy, Research Funding; Takeda: Research Funding; Celgene: Consultancy; Medimmune: Consultancy, Research Funding; Pharmacyclics: Consultancy. Martin:Karyopharm: Consultancy; I-MAB: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Sandoz: Consultancy; Teneobio: Consultancy. Flowers:Pharmacyclics/Janssen: Consultancy, Research Funding; Denovo Biopharma: Consultancy; Millenium/Takeda: Research Funding; Karyopharm: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Bayer: Consultancy; Acerta: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; V Foundation: Research Funding; Optimum Rx: Consultancy; BeiGene: Consultancy, Research Funding; TG Therapeutics: Research Funding; Burroughs Wellcome Fund: Research Funding; Eastern Cooperative Oncology Group: Research Funding; National Cancer Institute: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding. Kahl:BeiGene: Consultancy; TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy, Research Funding; Seattle Genetics: Consultancy.

Introduction: Time to treatment (TTT) is an important prognostic factor in patients with newly diagnosed diffuse large B-cell lymphoma (Maurer et al JCO 2018) where patients who initiate therapy quickly after diagnosis have an inferior event free survival compared to those who do not require such immediate treatment initiation. More recently, TTT has shown to be associated with adverse clinical factors and inferior outcomes in mantle cell lymphoma (MCL; Maurer, et al ASH, 2018). However, there is a paucity of data on the impact of TTT on overall survival (OS). We sought to validate these findings and to evaluate the impact of TTT on survival outcomes in newly diagnosed patients with MCL. Methods: We included patients from 12 medical centers in the United States with MCL diagnosed between January 1, 2000, and January 1, 2018, who had information on the TTT and initiated treatment within 60 days of diagnosis (to exclude patients whose treatment was purposefully deferred). TTT was defined as the time in days from first lymphoma diagnosis to initiation of therapy. Patients who received treatment within 14 days were categorized into short TTT group. We compared differences between the two groups (TTT 14 days and ≤ 60 days, longer TTT group) using chi-squared test, Fisher's exact tests, or ANOVA tests as appropriate. OS was defined as the time from diagnosis to death or last follow-up. Patients not experiencing an event were censored at their last known follow-up. OS was determined using the Kaplan-Meier method, and univariable and multivariable models were developed to identify predictors of OS. Results: Of 1,168 patients with newly diagnosed MCL, seven hundred fifty-five patients met the inclusion criteria and were included in this analysis, including 205 (27%) with short TTT and 550 (73%) with longer TTT. Median time to treatment was 7 days (range, 0-14) for the short TTT group vs 31 days for the longer TTT group (range, 15-60 days). The median age for the entire cohort was 63 years, 75% of patients were male, and 93% of patients had ECOG 0-1. The proportion of patients with stage 4 disease (93 vs 86%, p=0.015), elevated LDH (58 vs 39%, p3 cytogenetic abnormalities (29 vs 14%, p=0.005), B symptoms (47 vs 29%, p On univariable analysis, factors associated with inferior OS included, TTT=2 (p10k (p=0.002), BM involvement (p=2 (HR=2.25, 95%CI=1.22-4.14; p=0.009), elevated LDH (HR=1.81, 95%CI=1.16-2.85; p=0.01), and receipt of non-intensive regimen (HR=1.61, 95%CI=1.04-2.50; p=0.03) were significant predictors of OS while B symptoms was not. Conclusions: Short TTT for patients with newly diagnosed MCL is associated with aggressive disease features and inferior OS despite an increased likelihood of receiving intensive induction regimens. Further studies are needed to identify molecular determinants of such aggressive disease behavior that can be assessed quickly and utilized to initiate appropriate therapy in a timely manner. Ongoing front-line clinical trials in MCL should be developed in a way to facilitate enrollment of patients requiring urgent therapy, including potentially permitting a cycle of off-study treatment to manage symptoms while a patient is screened and enrolled. Disclosures Epperla: Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Kolla:Amgen: Equity Ownership. Bachanova:GT Biopharma: Research Funding; Incyte: Research Funding; Novartis: Research Funding; Gamida Cell: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Gerson:Seattle Genetics: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy. Barta:Mundipharma: Honoraria; Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Seattle Genetics: Honoraria, Research Funding; Bayer: Consultancy, Research Funding; Mundipharma: Honoraria; Merck: Research Funding; Celgene: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Danilov:Bristol-Meyers Squibb: Research Funding; Aptose Biosciences: Research Funding; Takeda Oncology: Research Funding; AstraZeneca: Consultancy, Research Funding; TG Therapeutics: Consultancy; Bayer Oncology: Consultancy, Research Funding; Celgene: Consultancy; Curis: Consultancy; Seattle Genetics: Consultancy; Verastem Oncology: Consultancy, Other: Travel Reimbursement , Research Funding; Genentech: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; MEI: Research Funding; Janssen: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy. Grover:Seattle Genetics: Consultancy. Karmali:Gilead/Kite; Juno/Celgene: Consultancy, Speakers Bureau; Takeda, BMS: Other: Research Funding to Institution; Astrazeneca: Speakers Bureau. Hill:Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Celegene: Consultancy, Honoraria, Research Funding; Kite: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Research Funding. Ghosh:Forty Seven Inc: Research Funding; AbbVie: Consultancy, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; Seattle Genetics: Consultancy, Speakers Bureau; Gilead/Kite: Consultancy, Speakers Bureau; T G Therapeutics: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding, Speakers Bureau; Astra Zeneca: Speakers Bureau; Genentech: Research Funding; Spectrum: Consultancy, Speakers Bureau. Park:Teva: Consultancy, Research Funding; Gilead: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau; Rafael Pharma: Membership on an entity's Board of Directors or advisory committees; G1 Therapeutics: Consultancy; BMS: Consultancy, Research Funding. Hamadani:Pharmacyclics: Consultancy; Medimmune: Consultancy, Research Funding; Janssen: Consultancy; Sanofi Genzyme: Research Funding, Speakers Bureau; Celgene: Consultancy; Otsuka: Research Funding; Merck: Research Funding; ADC Therapeutics: Consultancy, Research Funding; Takeda: Research Funding. Martin:I-MAB: Consultancy; Sandoz: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy; Teneobio: Consultancy. Kahl:AbbVie Inc, Acerta Pharma - A member of the AstraZeneca Group, AstraZeneca Pharmaceuticals LP, BeiGene, Celgene Corporation, Genentech, Pharmacyclics LLC, an AbbVie Company, Roche Laboratories Inc.: Consultancy. Flowers:V Foundation: Research Funding; National Cancer Institute: Research Funding; Millenium/Takeda: Research Funding; Gilead: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Burroughs Wellcome Fund: Research Funding; Karyopharm: Consultancy; Spectrum: Consultancy; AstraZeneca: Consultancy; AbbVie: Consultancy, Research Funding; Denovo Biopharma: Consultancy; Optimum Rx: Consultancy; Pharmacyclics/Janssen: Consultancy, Research Funding; TG Therapeutics: Research Funding; Acerta: Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Eastern Cooperative Oncology Group: Research Funding; Bayer: Consultancy. Cohen:Seattle Genetics, Inc.: Consultancy, Research Funding; Genentech, Inc.: Consultancy, Research Funding; Bristol-Meyers Squibb Company: Research Funding; Takeda Pharmaceuticals North America, Inc.: Research Funding; Gilead/Kite: Consultancy; LAM Therapeutics: Research Funding; UNUM: Research Funding; Hutchison: Research Funding; Astra Zeneca: Research Funding; Lymphoma Research Foundation: Research Funding; ASH: Research Funding; Janssen Pharmaceuticals: Consultancy.

9042 Background: Race-based differences in ICI efficacy for advanced NSCLC have not been studied due to under-representation of patients of minority background in pivotal trials. We systematically explored real-world differences in outcome in our diverse patient population. Methods: This is a retrospective review of clinical outcome of patients with advanced NSCLC treated with single-agent ICI between 2013 and July 2018 at the Winship Cancer Institute of Emory University. We performed univariate and multivariate analyses for overall survival (OS) and progression free survival (PFS) patients according to self-reported race and of OS according to gender and PD-L1 expression levels. Results: We analyzed clinical data from 90 eligible patients: Median age of 68.5 yrs, 51% male, White (W)/Black(B)/Asians(A) made up 62.3%/30.7%/5%; 36.5% had brain metastasis at the time of ICI initiation. The majority (85.9%) had ECOG PS ≤2; ICI was 1st line in 15 (16.9%), 2nd line in 59 (66.3%), 3rd line in 12 (13.5%) and nivolumab was the most commonly used agent (41.1%) followed by atezolizumab (32.2%) and pembrolizumab (26.7%). The median OS for the entire population was not reached (NR) (95%CI: 15.6, NR) while 12-month and 24-month OS rates were 63.8% (52.8%, 72.8%) and 53.1% (40.2%, 64.4%). The median OS, 12-month and 24-month OS rates for W and B respectively, were 23.6 months vs. NR; HR: 1.02 (95%CI: 0.51-2.04), p = 0.9571; 61.8% (47.7%, 73.2%) vs. 59.3% (38.6%, 75.0%) and 46.0% (27.9%, 62.4%) vs. 53.9% (32.8%, 70.9%). The overall response rate was 16.7%; 23.8% vs. 11% for B and W respectively. The median duration of response was comparable at 3.36 months vs. 2.94 months for W and B. The median PFS and 12-month PFS rate for W and B respectively were 5.5 (3.2, 14.8) vs. 3.0 (1.4, 10.7) months, p = 0.1350 and 40.0% (27.1%, 52.5%) vs. 29.6% (14.1%, 47.0%). Conclusions: Real-world analysis of our institutional experience showed no significant racial disparity in advanced NSCLC patients treated with ICI. Larger multi-institutional studies to include other US minority population would make our findings generalizable.

Background High dose chemotherapy and autologous stem cell transplant (ASCT) results in cure for up to 50% of patients with Hodgkin (HL) and aggressive non-Hodgkin lymphoma (NHL) that relapse after initial treatment with chemo-immunotherapy. Despite improvements in supportive care and patient selection, death after ASCT remains a concern due to progressive disease, infection, and other treatment- and non-treatment-related causes. We evaluated causes and predictors of death in patients undergoing ASCT for HL and NHL. Methods We conducted a single-institution, retrospective study of all patients with HL and NHL including diffuse large B-cell lymphoma, high grade B-cell lymphoma NOS, follicular lymphoma, Burkitt lymphoma, marginal zone lymphoma, and T-Cell lymphoma who underwent ASCT at Emory University between January 1, 2006 and June 1, 2017. We evaluated each patient with regards to pre-transplant disease and other baseline characteristics, treatment response after ASCT, occurrence of relapse post-ASCT, post-ASCT death and cause of death. Among patients who died, we compared baseline characteristics of interest between groups based on the documented cause of death using Fisher's Exact tests and t-tests. The association between cause of death and time to death from ASCT was evaluated by the Kruskal-Wallis test. Box plots were used to describe time to death post-transplant. Results Of 642 patients completing ASCT, 192 died during the period of observation after a median follow-up of 24 months. Among patients who died, the leading causes of death were relapsed disease (n=136, 71%), infection (n=18, 9%), organ dysfunction (n=16, 8%), secondary malignancy (n=8, 4%), and other/unspecified (n-14, 7%). When the group was divided into disease-related (n=136) vs non-disease-related death (n=56), none of the pre-specified variables of interest including age, gender, disease status at transplant, stage, induction or salvage therapy, conditioning regimen, or KPS were significantly associated with disease- vs non-disease-related death. Of the 18 deaths due to infection 7 were due to bacterial sepsis (including 5 prior to day +30 post ASCT), 3 were due to fungal infections, 3 were due to pneumonia, 1 death each was due to hepatitis C, nocardia, pneumocystis jirovecii, cytomegalovirus, and C. Difficile. The median time to death for patients experiencing infection or organ dysfunction was 0.5 years each compared to 1 year for patients dying of disease relapse and 4 years for patients experiencing a secondary malignancy (p Conclusions Among patients completing ASCT for HL or NHL, most deaths occurred due to relapse of the primary disease. There were no significant associations with baseline or treatment-related variables with the cause of death. The median time to death for patients with infection or organ dysfunction was 0.5 years, suggesting that continued monitoring and supportive care of patients completing ASCT is required beyond the initial engraftment period. Our findings support the role of intensive follow-up during the first year post- ASCT and continued monitoring for long-term toxicities for subsequent years of follow-up. Figure Figure. Disclosures Roberts: AstraZeneca: Consultancy. Flowers:Eastern Cooperative Oncology Group: Research Funding; National Cancer Institute: Research Funding; Gilead: Research Funding; Burroughs Wellcome Fund: Research Funding; V Foundation: Research Funding; OptumRx: Consultancy; Genentech/Roche: Research Funding; Janssen Pharmaceutical: Research Funding; Celgene: Research Funding; Millennium/Takeda: Research Funding; Pharmacyclics: Research Funding; Abbvie: Consultancy, Research Funding; Gilead: Consultancy; Karyopharm: Consultancy; Pharmacyclics/ Janssen: Consultancy; TG Therapeutics: Research Funding; BeiGene: Research Funding; Acerta: Research Funding; Abbvie: Research Funding; Spectrum: Consultancy; Genentech/Roche: Consultancy; Denovo Biopharma: Consultancy; Bayer: Consultancy. Waller:Novartis Pharmaceuticals Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celldex: Research Funding; Kalytera: Consultancy; Pharmacyclics: Other: Travel Expenses, EHA, Research Funding; Cambium Medical Technologies: Consultancy, Equity Ownership. Lonial:Amgen: Research Funding. Allen:Merck: Research Funding; Bayer: Consultancy. Blum:Morphosys: Research Funding; Novartis: Research Funding; Seattle Genetics: Research Funding; Celgene: Research Funding. Kaufman:Roche: Consultancy; Karyopharm: Other: data monitoring committee; Abbvie: Consultancy; Janssen: Consultancy; BMS: Consultancy. Nooka:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Spectrum Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Adaptive technologies: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees. Cohen:Bristol-Myers Squibb: Research Funding; Janssen: Research Funding; Bristol-Myers Squibb: Research Funding; Infinity Pharmaceuticals: 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; Celgene: 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; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; AbbVie: 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; Millennium: 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; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: 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; Takeda: Research Funding; BioInvent: Consultancy; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Introduction Mantle cell lymphoma (MCL) frequently impacts elderly patients (median age of diagnosis is 68), and management of these patients can be difficult due to the presence of comorbidities in this group. Presence of comorbidities is associated with inferior outcomes in many hematologic malignancies but there has not been a systematic assessment of comorbidities in MCL. We utilized the Charlson Comorbidity Index (CCI) to describe the presence of comorbidities in MCL patients and to explore their impact on patient outcomes. Methods We included patients with MCL evaluated at Emory between January 1, 2000 and December 31, 2016. Patients with limited or inadequate follow-up or for whom data to determine the CCI were inadequate were excluded. We determined the CCI at the time of initiation of treatment for all patients with MCL and excluded "lymphoma" from this calculation. Patients were categorized into severity classes based on their summed scores. The median score of 1 was used to delineate the "low" and "high" CCI groups. For each group (low and high CCI), we evaluated baseline demographic, clinical and treatment characteristics and identified specific toxicity-related outcomes including: failure to complete induction chemotherapy, unplanned hospitalizations, or treatment related toxicities. Progression-free (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method, and we assessed for the impact of CCI score on PFS and OS using Cox proportional hazards models. Results Of 178 patients with MCL, 129 were male (73.3%) and median age was 61 (32-86). One hundred forty patients (86.4%) had stage IV disease. Among the 99 reported values, 31 patients (31.3%) had an elevated LDH, and ECOG PS was 0 in 47 patients, 1 in 66 patients, and 2-4 in 8 patients. Induction therapy was R-HyperCVAD (n=79; 45.4%), R-CHOP (n=49; 28.2%), BR (n=13; 7.5%) RCHOP/RDHAP (n=3; 1.7%) and Other (N=29; 16.7%). The CCI scores for the whole cohort were 0 in 78 pts (43.8%), 1 in 57 pts (32%), 2 in 24 pts (13.5%) and 3+ in 19 pts (10.7%; See Figure 1). One hundred thirty-five patients (75.8%) patients had a low CCI score (0-1) and 43 patients (24.2%) had a high CCI score (>1). Compared to patients with a low CCI, those with high CCI were older (median 67 years vs 59 years, p Twenty-eight patients experienced an unplanned hospitalization during induction, including 23 in the low CCI group (22%) and 5 in the high CCI group (16%; p=0.49). Seventeen patients de-escalated or discontinued induction therapy prematurely including 13 (12.4%) in the low CCI group and 4 (13.3%) in the high CCI group (p=1.00). There was no significant difference in OS between the low- and high-CCI groups (5-year OS 70.3% vs 68.7%, p=0.9; See Figure 2). Within the cohort of patients treated with intensive induction therapy, there was no significant impact of CCI on incidence of unplanned hospitalizations, de-escalation or discontinuation of therapy, or OS (p> 0.3). Conclusion CCI score was not shown to be a reliable predictor of unplanned hospitalizations, premature cessation of chemotherapy, or OS in our cohort, although many of our patients had very limited comorbidities. These results suggest that patients with limited comorbid conditions can likely be successfully managed with appropriate supportive care and should be considered for the most effective regimens. Future studies with a larger patient population with increased number of comorbidities may improve our ability to detect the impact of CCI on these outcomes and explore the relative contribution of specific comorbidities in MCL. Disclosures Calzada: Seattle Genetics: Research Funding. Flowers:BeiGene: Research Funding; Burroughs Wellcome Fund: Research Funding; Abbvie: Consultancy, Research Funding; Abbvie: Research Funding; Pharmacyclics/ Janssen: Consultancy; Millennium/Takeda: Research Funding; Gilead: Consultancy; Genentech/Roche: Consultancy; Janssen Pharmaceutical: Research Funding; Genentech/Roche: Research Funding; OptumRx: Consultancy; Acerta: Research Funding; Gilead: Research Funding; Denovo Biopharma: Consultancy; Celgene: Research Funding; Bayer: Consultancy; Spectrum: Consultancy; Karyopharm: Consultancy; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Pharmacyclics: Research Funding; V Foundation: Research Funding. Cohen:AbbVie: 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; Infinity Pharmaceuticals: 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; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Millennium: 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; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: 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; Takeda: Research Funding; BioInvent: Consultancy; BioInvent: Consultancy; Seattle Genetics: 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.

Background: Autoimmune (AI) disorders, in particular Sjögren's syndrome (SS), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE), have been increasingly recognized as risk factors for diffuse large B cell lymphoma (DLBCL). It remains controversial whether increased lymphoma risk arises from the diseases themselves or the immunosuppressive agents used to treat them. It is possible that AI-associated lymphomas comprise a distinct lymphoma subset, exhibiting their own characteristic clinical and biologic behavior. In a recent analysis of >5,000 DLBCL patients in a large national database, our group described decreased lymphoma-related survival in patients with concomitant RA and a trend towards decreased survival in patients with SLE (Koff JL, Clin Lymphoma Myeloma Leuk 2018). Unfortunately, this database did not contain data about cell-of-origin subtype, which is highly associated with survival in DLBCL, or immunosuppressive regimen used to treat AI disease. To determine the prevalence of AI-associated disease among DLBCL patients and better characterize this unique population in terms of demographics, clinical features, and survival outcomes, we examined a large institutional database that included more granular information regarding tumor immunohistochemical (IHC) markers and AI disease treatment. Methods: We used an existing clinic-based registry of DLBCLs to identify patients diagnosed with DLBCL between 1989 and 2018 with concomitant AI disease as defined by the American College of Rheumatology. To be included, AI disease diagnosis was required to precede diagnosis of DLBCL by a minimum of six months. Patient age, sex, race, dates of DLBCL and AI diagnoses, stage, International Prognostic Index (IPI) score, poor performance status (ECOG score ≥2), B symptoms, lymphoma treatment strategies, date of progression/relapse, and date of death were identified via chart review. We also examined history of immunosuppressive therapies for AI disorders, AI serum markers such as ANA and rheumatoid factor, DLBCL cell-of-origin subtype by IHC Hans algorithm, and "double-hit" status by fluorescent in situ hybridization testing for translocations of MYC, BCL2, and BCL6. First-line treatments were categorized as: cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP), rituximab-CHOP (R-CHOP), and "other." We analyzed demographics and baseline clinical characteristics for patients with DLBCL and concurrent SS, RA, SLE, or any other AI disease, plotted overall survival (OS) and progression-free survival (PFS) for these groups, and compared median survival times. Results: Upon initial chart review of 1,045 total patients with DLBCL, 60 patients had a preceding diagnosis of AI disease; of these, 35 carried a diagnosis of either SS, RA, or SLE. Patient characteristics are summarized in the Table. Compared to DLBCL patients with other AI diseases, patients with SS, RA, or SLE were more commonly female (73.3% vs 44.4%, p=0.026), more likely to experience B symptoms (46.7% vs 18.5%, p=0.033) and more likely to have a history of methotrexate treatment (36.7% vs 11.1%, p=0.037). All patients received similar first-line DLBCL treatments regardless of AI disease type. Data on IHC results and FISH status was inconsistently documented prior to 2010. AI factors of interest, including serum markers and immunosuppressive therapies, were also not reliably recorded for any era. Compared to patients with SS and RA, there was a trend towards lower OS in patients with SLE and other AI diseases, although this difference was not statistically significant (Figure). PFS was not significantly different between any groups (range, 41.9%-55.0%). Conclusions: In this retrospective study of over 1,000 patients with DLBCL, concomitant AI disease was uncommon. A more complete evaluation of factors impacting survival in AI-associated DLBCL was limited by small sample size and incomplete documentation of key lymphoma and AI disease features in this dataset. The possibility of lower OS for patients with SLE and other AI diseases should be explored in future prospective studies, which may also better capture molecular features of both DLBCL and AI disease. Disclosures Flowers: Pharmacyclics/ Janssen: Consultancy; Gilead: Consultancy; Gilead: Research Funding; Abbvie: Research Funding; Burroughs Wellcome Fund: Research Funding; Janssen Pharmaceutical: Research Funding; Genentech/Roche: Research Funding; Spectrum: Consultancy; V Foundation: Research Funding; Pharmacyclics: Research Funding; TG Therapeutics: Research Funding; OptumRx: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Karyopharm: Consultancy; Genentech/Roche: Consultancy; National Cancer Institute: Research Funding; Denovo Biopharma: Consultancy; Millennium/Takeda: Research Funding; Bayer: Consultancy; Abbvie: Consultancy, Research Funding; Celgene: Research Funding; BeiGene: Research Funding; Acerta: Research Funding.

e20064 Background: Therapeutic intensity poses a challenge for older or medically unfit pts with untreated MCL. We assessed clinical outcomes and predictors of survival in older MCL pts treated in the rituximab era. Methods: We included pts ≥ 65 yrs of age with newly diagnosed MCL treated between 2000 and 2015. The primary objective was to characterize practice patterns and survival outcomes in older pts and secondarily to assess predictive factors of survival. Results: Data were collected from 12 centers for 1168 pts. For 465 pts ≥ 65 yrs of age (median 70; range 65-100), variable denominators indicate missing data: 305 of 444 pts (69%) were male; 23 (8%), 110 (39%) and 148 (53%) of 281 pts had low, intermediate and high-risk MIPI respectively. Median time from diagnosis to first treatment was 31 days (range 0-2611 days). In 407 older pts with initial treatment data, 148 (36%) received BR, 65 (16%) a cytarabine containing regimen, 9 (2%) lenalidomide, and 92 (23%) other treatments that excluded BTK inhibitors (BTKi). 68 of 365 pts (19%) were enrolled on clinical trial for initial therapy, 88 of 369 pts (24%) received autologous transplant (AHCT) in first remission, and 155 of 351 pts (44%) received maintenance rituximab (MR). Median f/u was 2.7 yrs. 41 of 465 pts (9%) had primary refractory disease (POD6); 107 (23%) progressed within 24 months (POD24). Treatment data were available for 157 relapsing pts: 58 (37%) were treated with BTKi/BTKi combinations. PFS and OS rates were compared across young and older age cohorts: 2 yr PFS rates were 79%, 69%, and 66% and 2 yr OS rates were 92%, 87%, and 84% for age < 65, age 65-69, and age ≥ 70 respectively (p < 0.001). In the older cohort: on UVA, ECOG ≥2, BM involvement, blastoid histology, > 3 cytogenetic abnormalities and lack of MR were associated with inferior PFS and OS (p = 0.012 – < 0.001). POD6 and POD24 were associated with decreased OS (p < 0.001). AHCT in first remission did not impact PFS or OS. After MVA, MR remained significantly associated with improved PFS and OS (p < 0.001). 2 yr PFS rates were 81% and 58% and 2 yr OS rates were 96% and 80% with and without MR respectively (p < 0.001). Conclusions: In this large cohort of older pts in the rituximab era, survival outcomes remain inferior to younger pts. MR is associated with improved PFS and OS but AHCT does not yield better survival. A small number of pts received BTKi salvage therapy. As such, our data does not reliably reflect the potential advancements in survival achieved with the introduction of BTKis. Focused clinical trials are necessary to identify effective therapeutics in this population.