Lossos, Izidore S.

Abstract Introduction Although chemo-free regimens are increasingly used in elderly patients with large B-cell lymphoma (LBCL), most still receive conventional chemoimmunotherapy. Patients up to 75–80 years old are usually treated with full-dose R-CHOP, while 80+ patients receive the attenuated R-miniCHOP regimen as standard of care. Prior studies have shown that in patients aged 65+ years, R-CHOP was associated with improved survival based on propensity score matching (PSM) analysis (Al-Sarayfi, Am J Hematol, 2023), though this did not include comorbidity data. Furthermore, no formal studies have focused specifically on 80+ patients. We aimed to perform a PSM comparison of R-CHOP versus R-miniCHOP to better inform treatment decisions in this population. Methods We harmonized and pooled data from 237 LBCL patients receiving chemotherapy with rituximab (out of all 263 80+ patients) from the prospective LEO cohort (USA, n=147; 2015–2020) and NiHiL registry (Czech Republic, single center, n=116; 2010–2023). Of them, 205 (86%) receiving anthracycline(A)-based regimens were included. Baseline characteristics, comorbidities, treatments, and outcomes were collected. PSM (1:1, caliper 0.2) was performed to compare R-CHOP and R-miniCHOP using age, ECOG performance status (PS), clinical stage, lactate dehydrogenase (LDH), and major comorbidities (heart disease, history of stroke, and other recent cancer) as matching variables. The endpoints were overall survival (OS), event-free survival (EFS), and lymphoma-specific survival (LSS, defined as death attributed to lymphoma progression). Results Among 205 A-treated patients, median age was 83 years (range 80–99); 30% had ECOG PS 2–4, 67% clinical stage III–IV, 34% ≥2 involved extranodal sites, 59% elevated LDH, and 58% had International Prognostic Index (IPI) scores 3–5. Median follow-up was 5.5 years; median OS and EFS were 4.1 and 3.4 years, resp. A-based regimens comprised full-dose R-CHOP-like (n=79; 39%; R-CHOP n=74, DA-EPOCH-R n=5) and R-miniCHOP (n=126; 61%). Patients receiving R-CHOP-like regimens had more favorable baseline characteristics (median age 82 vs 83 years, P=0.04; ECOG PS 2–4: 16% vs 39%, P<0.01; IPI 3–5: 46% vs 66%, P=0.03) and a lower, though not statistically significant, comorbidity burden (mean 1.14 vs 1.39; heart disease 35% vs 45%, P=0.22; history of stroke 4% vs 6%, P=0.64; other cancer 6% vs 5%, P=0.87). R-CHOP-like regimens vs R-miniCHOP had superior OS (median 6.3 vs 3.4 years; HR=0.61, 95% CI 0.42–0.90; P=0.01) and EFS (median 5.3 vs 2.1 years; HR=0.58, 95% CI 0.40–0.83; P<0.01), with no significant difference in LSS (2-year 89% vs 82%, HR=0.77, 95% CI 0.39–1.54, P=0.46). To mitigate selection bias, we performed PSM on patients with available baseline characteristics treated with R-CHOP (n=69) and R-miniCHOP (n=121), resulting in 63 matched pairs. Matched cohorts were well-balanced on age (median 82 years in both cohorts; P=0.68), ECOG PS 2–4 (17% vs 19%; P=0.82), IPI 3–5 (52% vs. 59%; P=0.41), and comorbidity burden (mean 1.10 vs. 1.29; P=0.30). The presence of heart disease (40% in both cohorts), history of stroke (5% vs 6%), and cancer (5% vs 6%) were similar. Survival modestly favored R-CHOP, but differences were not significant: median OS 5.3 vs 3.5 years (HR=0.73; 95% CI 0.46–1.15; P=0.17), median EFS 3.8 vs 2.8 years (HR=0.76; 95% CI 0.49–1.18; P=0.23), and 2-year LSS 88% vs 84% (HR=1.09; 95% CI 0.45–2.63; P=0.85). Treatment-related mortality was similar in both cohorts (16%). Among R-miniCHOP patients, survival outcomes did not differ between matched (n=63) and unmatched (n=63) groups (OS P=0.72; EFS P=0.23; LSS P=0.27). Unmatched (n=16) R-CHOP patients had a trend toward improved survival compared to matched (n=63) individuals (OS P=0.10; EFS P=0.049; LSS P=0.24). Conclusion This is the first PSM-based analysis comparing R-CHOP and R-miniCHOP in LBCL patients 80+ years old. Despite inherent limitations of a non-randomized design and limited number of matched patients, our findings – derived from two prospective cohorts – suggest that R-miniCHOP may offer outcomes comparable to R-CHOP, particularly with respect to LSS. While these results support R-miniCHOP as an appropriate frontline option, treatment decisions remain highly individualized. These data may help inform clinical decision-making and provide a basis for designing future trials targeting this population, where R-miniCHOP could serve as a comparator arm. Funding: NU21-03-00411, U01 CA195568.

Abstract Introduction: cBTKi have made a substantial impact in pts w/ MCL, but pts who develop PD while on treatment w/ cBTKi have historically had poor responses to subsequent lines of therapy (LOT). Brexucel, lisocel, and the non-covalent BTKi pirto have been approved in this population. While two RW studies have substantiated the benefit of brexucel, similar data for pirto are lacking. Accordingly, we aimed to evaluate the outcomes of pts treated w/ pirto in the RW setting. Methods: We performed a multi-center retrospective cohort study of adult pts w/ a diagnosis of MCL who experienced PD after any approved cBTKi and subsequently received pirto. Pts who received pirto w/ bridging intent and those who switched to pirto due to intolerance of cBTKi were excluded. The 95% exact binomial confidence intervals (CI) were calculated for overall response rate (ORR) and complete response rate (CRR). Progression-free survival (PFS) and overall survival (OS) were defined as the time from pirto start to PD or death, whichever occurred first, and the time from pirto start to death, respectively, and calculated w/ the Kaplan-Meier method. The log-rank test was used to compare survival curves. A multivariate (MV) Cox proportional hazard model was built to calculate adjusted hazard ratio (aHR). Analyses were performed w/ SAS, version 9.4. Results: Data on 111 pts w/ MCL treated across 21 institutions were collected. Median (mdn) age was 72 (range 33 – 93) years. Twenty-seven pts (24%) were female, 3 (3%) were Asian, 5 (5%) Black, 9 (8%) Hispanic, 86 (77%) White. Among the 53 (48%) pts w/ available MIPI-c at diagnosis, 28 (53%) pts were high-risk. Ki67 at diagnosis was available in 84 (76%) pts: of those, 58 (69%) had a Ki67 ≥30%, and 41 (49%) ≥50%. TP53 mutational status was available in 70 (63%) pts: 33 (47%) had documented TP53 mutation and 10/52 (19%) pts had a disease w/ complex karyotype. Pts had a mdn of 3 (range 1 – 9) prior LOT (n=106). Ninety-one pts (86%) received chemo-immunotherapy (CIT), 16 (15%) autologous stem cell transplant, 19 (18%) venetoclax (ven), 29 (27%) chimeric antigen receptor T-cell, 4 (4%) allogeneic stem cell transplant. For cBTKi, 39 (35%) pts received ibrutinib, 56 (50%) pts acalabrutinib, 33 (30%) pts zanubrutinib, and 17 (15%) pts received more than one cBTKi. The mdn time from the last dose of cBTKi to pirto start was 55 (range 0 – 2587) days, w/ 51 (46%) pts who switched from a cBTKi directly to pirto. Thirty (27%) pts had no response (stable disease or PD as best response) to cBTKi, and 40 (36%) pts had no response to the last LOT. Two (2%) pts received pirto in combination w/ CIT, 8 (7%) w/ an anti-CD20 monoclonal antibody (mAb), 11 (10%) w/ ven ± a mAb, while 86 (77%) pts as single agent. In 104 (94%) pts, pirto was given at full dose, 10 (9%) pts had a subsequent dose reduction. A total of 35 serious (grade ≥3) adverse events (AE) were documented in 27 (24%) pts: 4 (4%) pts had a serious bleeding AE, 5 (5%) pts a serious cardiac AE, 10 (9%) a serious GI AE, and 16 (14%) a serious infectious AE. Ninety-eight (88%) pts were evaluable for response. The ORR was 40% (95% CI 30% – 50%) w/ a CRR of 29% (95% CI 20%– 39%). At the last follow-up, 29 (26%) pts remained on pirto w/ a mdn treatment duration of 15.1 months (range 0.4 – 26). Fifty-eight (52%) pts died, 35 (78%) because of PD. At a mdn follow-up of 15.8 (range 0.4 – 26) months among survivors, the mdn PFS was 4.7 months (95% CI 3.3 – 8.2) and the mdn OS was 13 months (95% CI 9.2 – not available). Using the log-rank test, age (quartile groups), number of LOT (1-2 vs. 3-4 vs. 5+), time from cBTKi to pirto (quartile groups), Ki67≥30%, and high MIPI-C did not result in a statistically significant difference in PFS (p>0.05). Presence of TP53 mutation was associated w/ a non-statistically significant adverse trend in PFS (p=0.0585). No response to cBTKi and Ki67≥50% were associated w/ a statistically significant inferior PFS in log-rank test (p=<0.05), which persisted in a MV Cox regression model (aHR 2.4, 95% CI 1.4-4.2, and aHR 2.6, 95% CI 1.6-4.4, respectively). Conclusions: This is the first RW report on pirto in MCL pts. In this high-risk population, ORR to pirto was comparable to the BRUIN trial, while PFS was significantly worse, especially in pts w/ no response to cBTKi and w/ a high Ki67. However, prolonged remissions were seen in a subset of pts, suggesting that a better characterization of this population w/ durable benefit from pirto is needed.

Introduction: Patients with non-Hodgkin Lymphoma (NHL), especially adolescents and young adults, can face late effects from treatment, including decreased fertility. Due to time constraints prior to treatment initiation and sometimes financial limitations, implementing fertility counseling and referral-based guideline care remains challenging. We aim to understand the occurrence and predictors of fertility counseling and preservation in patients with NHL in the Lymphoma Epidemiology of Outcomes (LEO) cohort study. Methods: The LEO cohort prospectively enrolled newly diagnosed patients with NHL from 2015-2020 at 8 academic medical centers in the US. Clinical. Treatment data were abstracted from medical records, pathology was reviewed and classified by a LEO pathologist, and participants completed a self-administered questionnaire. Participants were then prospectively followed to identify outcomes and collect additional patient reported data, including a survivorship questionnaire at follow-up 3 years (FU3) after diagnosis that included items on fertility counseling and preservation. The questionnaire contained two fertility questions analyzed: whether healthcare providers discussed the impact of lymphoma treatment on fertility, and whether providers discussed the process of fertility preservation. This analysis was based on participants aged 18-50 years at enrollment and who completed the fertility questions at FU3. Women who had undergone natural or procedural menopause and men who had undergone vasectomy pre-treatment were excluded. We estimated the association of demographic and clinical factors with fertility preservation using odds ratios (ORs) and 95% confidence intervals (CI) from univariate and multivariable logistic regression models. Results: Seventy-seven patients were included in the analysis: 36 females (46%) and 41 males (53%). The median age of diagnosis was 40 years (IQR 30-45), and 36 (47%) participants were in the age 18-39-year category. Participant self-identified race/ethnicity was 69% non-Hispanic White, 22% Hispanic, 4% Black and 3% Asian. Sixty (78%) patients were treated with alkylators, 12 (15.6%) with non-alkylators, and 5 (6.5%) with radiation. Fifty-five (71%) of the patients were classified as having aggressive lymphoma, with follicular, extranodal marginal zone, primary cutaneous follicle center, and nodal marginal zone B-cell lymphoma defined as indolent and remaining subtypes aggressive. Around 6% of female patients underwent fertility preservation after lymphoma diagnosis, compared to 12.2% of male patients. All the patients who had undergone fertility preservation after lymphoma diagnosis were in the 18-39-year age group. On univariate analysis, females were more likely to have undergone fertility toxicity and preservation discussions compared to males, with 72% of females and 59% of males recalling a discussion regarding fertility (OR 1.8, 95% CI 0.7-4.9, p=0.21). Those age 18-39 were significantly more likely to have undergone fertility discussion compared to those aged 40-50 (OR 10.2, 95% CI 3.3-39.2, p<0.001). Patients treated with alkylating therapy were significantly more likely to undergo fertility discussion when compared to those on non-alkylating therapy (OR 9.0, 95% CI 2.3-45.5, p<0.01). In addition, 75% of those with aggressive lymphoma compared to 41% of patients with indolent lymphoma had fertility discussion (OR 4.2, 95% CI 1.5-12.4, p=0.01). White patients were significantly less likely than Hispanic, Black and Asian patients to have fertility discussion (OR 0.2, 95% CI 0.04-0.6, p<0.01). In the multivariable analysis, alkylating therapy (OR 8.9, 95% CI 1.6-66.7) and age 18-39 years (OR 10.9, 95% CI 2.9-55.3) remained significant predictors of fertility discussion; White race was also trending towards significance (OR 0.2, 95% CI 0.04-1.0, p=0.08). Aggressive lymphoma subtype was not a significant predictor of fertility discussion. Conclusions: In this cohort of lymphoma survivors 3 years post-diagnosis, we found that Hispanic patients, those diagnosed at a younger age and exposed to alkylating chemotherapy agents were significantly more likely to undergo discussions regarding the effects of lymphoma treatment on fertility. Our study highlights the importance of all cancer patients of childbearing age having the opportunity to address fertility concerns during clinic visits.

Background: Due to recent advances, patients with follicular lymphoma (FL) have multiple treatment options with high response rates and durability. However, there is a gap in understanding how patient preferences influence treatment selection. To close this gap, we conducted a qualitative study using focus groups of adults with FL to understand their knowledge of treatment options, priorities, and decision-making process. We designed this study to inform the content of a planned discrete choice experiment in a larger population of patients with FL to better understand patient preferences and trade-offs around treatment delivery, side effects, outcomes, and quality of life. Methods: We conducted focus groups lasting 60-90 minutes, each with 3-5 participants recruited from the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study. The LEO Cohort Study is a multi-institutional prospective cohort study of newly diagnosed adults with non-Hodgkin lymphoma from July 2015 to present. Each focus group was co-led by two investigators (U.D. and M.T.) and conducted using Zoom video technology. Participants were asked to comment on their understanding about FL and available treatments, their ideal treatment, their decision-making process about prior therapies, and quality of life and side effects associated with treatment. We performed exploratory content analysis of participant understanding of FL and their treatment preferences. We will continue to conduct focus groups until we reach thematic saturation, which we anticipate will occur with one additional focus group. Themes from all focus groups were identified and agreed upon by both investigators (U.D. and M.T.) and were verified by additional investigators (J.D., M.L, M.H., B.K.L, C.C., M.M.). Results: To date, we conducted five focus groups with a total of N=21 participants (median age 60 [range 41-88], 66.7% female, 71.4% non-Hispanic White, 14.3% Hispanic, 9.5% Asian, 4.8% Black/Hispanic). We identified the following themes and representative quotes: 1) Holistic approach:Participants wanted their oncologists to view their care from a holistic perspective, discussing their individual priorities and options that would accommodate their fitness routine and ability to work. “[I wish] if doctors can consider not just the physical choices, but also the mental and emotional choices as well, the holistic person.” - Participant 13 “There's zero chance I can go back to working in the type of career where other people rely on me for things. I can't keep things straight.” - Participant 16 2) Ideal treatment:An ideal treatment would limit impact on fatigue, cognitive function, and have minimal toxicity to preserve quality of life and an active lifestyle. “I would say something that has minimal impact on daily life would be ideal and something that would make you feel better.” - Participant 6 3) Shared decision-making: Participants wanted to be better informed about available treatment options and often utilized second opinions to inform their decisions. “It helped to get the second opinion versus not. It would've been a completely different set of events.” - Participant 17 4) Treatment burden:Financial impact and effort required by patients to receive care (e.g., travel, number of office visits, and duration of therapy) were key factors in patient decision-making. “Part of my quality of life went down because I had to fight with my insurance company consistently, and we pay a lot of money.” - Participant 11 “Really explain the time options and calendarize the treatment and be more specific about the amount of time that you're going to spend at the hospital and the process.” - Participant 20 5) Representation: Minority participants raised concerns about not knowing if the available treatment data pertained to them. “[My end-goal would be] having an understanding of how the treatment is going to be for minority people. Many times the treatments are tested, they are not tested for minorities.” - Participant 21 Conclusions: The patient perspective is critical for treatment decision-making and education. People living with FL expressed a desire for a holistic and individualized approach to treatment decision-making that incorporated their lifestyle, minimized side effects, and limited overall treatment burden. These focus groups identified emerging themes that warrant further investigation for survivors with FL.

Introduction: The use of standardized, evidence-based classification systems is crucial for the accurate diagnosis and treatment of diseases. Moreover, standardized classification facilitates research and epidemiologic studies and promotes consistency in communication among healthcare professionals. Since 2016, the revised 4 th edition of the World Health Organization classification (WHO-HAEM4R) has been the global standard for diagnosis of lymphoid malignancies. With the emergence of new data, 2 new classification systems were developed and published in 2022: the 5 th edition of the WHO Classification (WHO-HAEM5) and the International Consensus Classification (ICC). Both WHO-HAEM5 and ICC maintain a shared fundamental concept of disease classification that integrates clinical, pathologic, and molecular data. However, they differ on nomenclature, establishment of new entities, and/or diagnostic criteria for some disease categories. To evaluate the impact of these differences on real-world diagnosis of non-Hodgkin lymphoma (NHL), we examined the diagnostic classification of NHL in the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study (NCT02736357). Methods: Initiated in 2015, LEO is an ongoing prospective observational study of patients aged ≥18 years with newly diagnosed NHL. Patients are enrolled at 8 major U.S. medical centers. Clinical, epidemiologic, pathologic, and treatment data are abstracted at baseline and active follow-up is conducted for all patients. Lymphoma subtype is coded for each case based on expert hematopathology re-review of the diagnostic pathology slides, the pathology report, biomarker data, and clinical data. Of note, NHL subtype distribution is similar to SEER data. We studied all patients enrolled in LEO between 7/1/2016 (the date LEO pathology review started using WHO-HAEM4R diagnostic codes) and 5/31/2020. WHO-HAEM4R diagnoses and additional clinicopathologic data, when relevant, were used to map cases into the corresponding WHO-HAEM5 and ICC diagnoses. Differences between WHO-HAEM5 and ICC were annotated for each case as: None - same disease entity; Minor - difference in nomenclature with similar diagnostic criteria; Major - difference in disease category and/or diagnostic criteria; or Unevaluable - insufficient data to assign WHO-HAEM5 and/or ICC diagnosis. Results: LEO enrolled 6143 patients during the study period. Of these, comparison between WHO-HAEM5 and ICC was evaluable in 5730 (93.3%). Unevaluable cases included those without a specific WHO-HAEM4R diagnosis at enrollment (N=384; e.g., patients with a low-grade B-cell lymphoma that could not be definitively sub-classified) and those with a specific WHO-HAEM4R diagnosis, but with insufficient clinicopathologic data to assign a specific WHO-HAEM5 and/or ICC diagnosis (N=29). Of the 5730 evaluable cases, 5376 (93.8%) showed no difference between WHO-HAEM5 and/or ICC diagnosis, 311 (5.4%) showed minor differences (nomenclature only), and 43 (0.8%) showed major differences (Table 1). The 43 major differences all involved B-cell NHLs; 20 (46.5%) were attributable to different approaches to classifying double-hit lymphomas, 21 (48.9%) to classification of splenic/leukemic B-cell lymphomas, and 2 (4.6%) to classification of B-cell lymphomas occurring at specific anatomic sites (Table 2). Conclusion: In a large, prospective lymphoma cohort reflecting real-world clinical practice at 8 major U.S. medical centers, major diagnostic differences in the classification of NHL using WHO-HAEM5 or ICC classification criteria were seen in 0.8%, whereas the remaining 99.2% of diagnoses were either the same or showed differences in nomenclature only. The existence of 2 concurrent classification systems presents potential for discrepancies in pathologic diagnosis, clinical practice, clinical trials, and other lymphoma research. Furthermore, some of the differences between WHO-HAEM5 and ICC are clinically and potentially therapeutically significant, and their resolution requires further study. Nevertheless, our findings argue that the proportion of patients affected would be small in real-world practice settings. This appears largely related to incidence rates of specific lymphoma subtypes, with major differences between the 2 classifications predominantly affecting rare entities, while there is general concordance on the most common forms of NHL.

AbstractPlasmablastic lymphoma (PBL) is a rare entity, commonly associated with immunosuppressed states such as human immunodeficiency virus (HIV) infection or solid organ transplant. The clinical course is characterized by high relapse rates and a poor prognosis, leading some clinicians to recommend aggressive frontline therapy. However, a specific review of limited stage (LS) PBL patients is not available to evaluate outcomes and justify treatment recommendations. We performed a retrospective review of LS PBL cases to provide insight into this rare disease. Our cohort consisted of 80 stage I or II PBL patients from 13 US academic centers. With a median follow up of 34 months (1–196), the 3‐year progression‐free survival (PFS) and overall survival (OS) of the entire cohort were 72% (95% CI 62, 83) and 79% (95% CI 70, 89), respectively. The 3‐year PFS and OS of patients treated with frontline chemotherapy alone was 65% (95% CI 50, 84) and 71% (95% CI 56, 89), respectively, compared to 85% (95% CI 72, 100) and 96% (95% CI 89, 100), respectively, in patients treated with combined frontline chemotherapy with radiation consolidation. Our data demonstrate favorable outcomes in LS PBL with no improvements in outcome from aggressive frontline treatment including Hyper‐CVAD or auto‐SCT consolidation. Multivariate regression analysis (MRA) demonstrated improved PFS for patients receiving EPOCH based frontline therapy versus CHOP (HR: 0.23; p = 0.029). Frontline chemotherapy followed by radiation consolidation versus chemotherapy alone appeared to be associated with improved relapse and survival outcomes but did not show statistical significance in MRA.

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