Abstract: Introduction-Chronic graft-versus-host disease (cGVHD) poses as a major late complication of hematopoietic stem cell transplantation. The role of cGVHD as a determinant in transplant-related morbidity and mortality, infectious complications, prolonged immune suppression, and impaired patient-reported quality of life has been extensively studied. Nonetheless, numerous advances in allogeneic hematopoietic stem cell transplant (allo-SCT) in recent years have expanded the indications for allo-SCT to a broader range of patients, including previously excluded older patients. However, long-term health status of older transplant recipients is poorly studied. Notably, the incidence of cGVHD may increase with age. Therefore, the development of cGVHD and the use of immunosuppressive therapy may lead to a higher degree of non-relapse mortality (NRM) in older patients. The objective of this study was to compare the NRM in both younger and older transplant recipients with and without cGVHD. Methods-We performed a retrospective cohort study of patients that underwent allo-SCT at the Ohio State University from 1999 to 2018. Data was analyzed from 1194 patients who survived or have been followed up with by at least day (d) 180 post-transplantation, among which 373 patients had developed cGVHD. Patients were grouped based on their age into a younger and older population. The older population was defined as ≥60 (N=373, 31%) with the younger population defined as & lt;60 (N=821, 69%) years (yr) of age. NRM was defined as death unrelated to relapse, with relapsed mortality as a competing risk. A landmark analysis approach was used to study the association between the age groups to NRM, stratified by whether or not patients had developed cGVHD by d180. Fine and Gray competing risk model was used to build the multivariable regression model controlling for confounding variables, such as gender, donor type, donor source, conditioning regimen, and diagnosis. Results-The median age at allo-SCT was 53.0 yr (range: 18-76) and 61.1% were male. Acute myeloid leukemia accounted for 36.7% of transplants, followed by non-Hodgkin's lymphoma (14.8%), acute lymphoid leukemia (12.7%), and myelodysplastic syndrome (11.0%). Additionally, 58.0% received reduced-intensity conditioning regimen. The majority of stem cell donor types were match unrelated (45.3%) and match related (39.8%). Patients who had developed cGVHD by d180, regardless of age, were at higher risk of NRM compared to patients with no cGVHD (hazard ratio [HR]: 1.52, 95% confidence interval [CI] : 1.16-1.99; p=0.002). To examine the influence of age with NRM, we stratified the analysis by cGVHD status by d180. Among patients developed cGVHD by d180, in both univariable (HR 1.22, 95% CI 0.79-1.9, p=0.373) and multivariable analysis (HR: 1.17, 95% CI: 0.74-1.87; p=0.501), there was no statistically significant difference in NRM between patients ≥60 and & lt;60 yr of age. Among patients without cGVHD by day 180, age ≥60 yr was a significant factor for increased NRM in both univariable (HR: 1.52, 95% CI 1.08-2.15; p=0.017) and multivariable (HR: 1.55, 95% CI: 1.04-2.30; p=0.031) analysis. Conclusion-This study showed that patients with cGVHD by day 180 were at higher risk for higher NRM compared to patients without cGVHD. Among cGVHD patients, there was no difference on the outcome of older patients (≥60 years old) compared to younger ones ( & lt;60 years old). This suggests that cGVHD therapy is equally tolerable among different age groups. Disclosures Chaudhry: Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bumma:Sanofi: Speakers Bureau; Amgen: Speakers Bureau. Khan:Amgen: Consultancy; Janssen: Consultancy. Devarakonda:Janssen: Consultancy. Vasu:Kiadis Inc: Other: Kiadis has obtained exclusive licensing requirements from The OHio State University; Janssen: Membership on an entity's Board of Directors or advisory committees; Omeros: Membership on an entity's Board of Directors or advisory committees. Jaglowski:Novartis: Consultancy, Research Funding; Juno: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; CRISPR: Consultancy. William:Celgene: Consultancy, Honoraria; Dova: Research Funding; Guidepoint Global: Consultancy; Merck: Research Funding; Kyowa Kirin: Consultancy, Honoraria; Seattle Genetics: Research Funding; Incyte: Research Funding. Mims:Syndax Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Other: Data Safety Monitoring Board; Abbvie: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Leukemia and Lymphoma Society: Other: Senior Medical Director for Beat AML Study; Novartis: Speakers Bureau; Agios: Consultancy. Brammer:Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Seattle Genetics: Honoraria, Speakers Bureau; Kymera: Honoraria; Verastem Oncology: Other: Travel. Saad:Magenta Therapeutics: Other: Personal Fees; Incyte Pharmaceuticals: Other: Personal Fees; Amgen: Other: research support; Kadmon: Other: research support; Orcabio: Other: research support. Efebera:Takeda: Honoraria, Speakers Bureau; Pharmacyclics: Research Funding; Celgene: Research Funding; Ohio State University: Current Employment.

Abstract: Background: Allogeneic transplantation (allo-HCT) is a potentially curative treatment for a variety of hematologic malignancies and nonmalignant hematologic disorders. Allo-HCT from a haploidentical (Haplo) related donor has emerged as a suitable alternative in the absence of matched related donor (MRD) and matched unrelated donor (MUD). Haplo HCT patients however have higher risk of graft rejection and graft versus-host disease (GVHD). Thus, patients often receive post-transplant cyclophosphamide (PTCy), which has proven to be highly effective in reducing GVHD. While the use of peripheral blood is an attractive option due to the ease of collection and rapid peripheral blood count recovery, not much information is available on the impact of graft sources using PTCy in Haplo-HCT. This study compares outcomes of bone marrow (BM) versus peripheral blood (PB) stem cell graft for Haplo-HCT in adult patients. Methods: We performed a retrospective study of 81 adult patients who underwent Haplo-HCT at The Ohio State University from 2009 to 2018. The study endpoints were overall survival (OS), progression free survival (PFS), non-relapse mortality (NRM), relapse, engraftment, acute GVHD (grade II-IV), and chronic GVHD. All endpoints were measured from the time of transplantation. Patient, disease, and transplant-related characteristics were compared between the two groups (BM versus PB) using the Mann-Whitney U test for continuous variables, and chi-squared or Fisher's exact test for categorical variables. The probabilities of OS and PFS were calculated using the Kaplan-Meier (KM) method and compared using log-rank test. Cumulative incidence rates were estimated and compared using Gray's test accounting for competing risks. Results: We compared the outcomes of patients who received a BM graft (N=43) with those receiving a PB graft (N=38). The median age at transplant was 57 years (20-74). All patients received PTCy in addition to tacrolimus and mycophenolate in 91% of patients. Reduced intensity conditioning (RIC) was used in majority of patients (N=63, 78%). The two groups were comparable including age (median, 60 years for BM and 56 years for PB, p=0.60) and the type of conditioning regimen (79% RIC for BM, 76% RIC for PB, p=0.77). The number of CD34+ and CD3+ infused cells was higher in PB grafts (median, 8.6x106 CD34+ cells/Kg, 2.0 x108 CD3+ cells/Kg, respectively) than for BM (median, 3.7x106 CD34+cells/Kg, 0.4x108 CD3+cells/Kg, respectively). Time to neutrophil and platelet engraftment were significantly shorter in patients receiving PB versus those getting BM grafts: median 15 vs. 17.5 days, (p=0.02) and median 20 vs. 29 days (p & lt;0.01) respectively. In univariable analysis there was no difference in OS (p=0.30), PFS (p=0.29) or NRM (p=0.33) between the groups. The BM cohort showed a 3-year OS rate of 62% (95% confidence interval [CI]: 45-75), and 3-year PFS of 48% (95% CI: 32-62). For PB group, 3-year OS and PFS were 68% (95% CI: 50-80) and 60% (95% CI: 43-74), respectively. There were no differences in the incidence of acute GVHD (p=0.80) and chronic GVHD (p=0.53). For BM vs. PB, cumulative incidences of grade II-IV acute GVHD at day +180 were 57% (95% CI: 41-70) vs. 55% (95% CI: 69-38) and for chronic GVHD at day 365, they were 40% (95% CI 26-55) vs. 47% (95% CI: 31-62), respectively. There was a significant difference in the incidence of relapse (p=0.04, Figure 1) with 2-year relapse rate of 36% (95% CI: 22-50) for BM vs. 19% (95% CI: 8-32) for PB. After controlling for conditioning regimen, PB graft had a reduced risk of relapse compared to BM graft, HR=0.35 (95% CI: 0.13-0.93, p=0.03). Conclusion: Our study suggests peripheral blood for haploidentical transplant to be a good alternative to bone marrow. Similar PFS, OS and NRM were seen between the two graft sources. As expected, faster neutrophil and platelets engraftment were seen with PB due to more CD3+ and CD34+ infused, but without an increase in acute or chronic GVHD. A reduced relapse risk was observed with PB graft. Our study is small and is retrospective, but provide encouraging results. A prospective randomized controlled trial is required to confirm these results. Disclosures Chaudhry: Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bumma:Sanofi: Speakers Bureau; Amgen: Speakers Bureau. Khan:Amgen: Consultancy; Janssen: Consultancy. Devarakonda:Janssen: Consultancy. Vasu:Kiadis Inc: Other: Kiadis has obtained exclusive licensing requirements from The OHio State University; Janssen: Membership on an entity's Board of Directors or advisory committees; Omeros: Membership on an entity's Board of Directors or advisory committees. Jaglowski:Novartis: Consultancy, Research Funding; Juno: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; CRISPR: Consultancy. William:Seattle Genetics: Research Funding; Merck: Research Funding; Dova: Research Funding; Kyowa Kirin: Consultancy, Honoraria; Guidepoint Global: Consultancy; Incyte: Research Funding; Celgene: Consultancy, Honoraria. Mims:Jazz Pharmaceuticals: Other: Data Safety Monitoring Board; Abbvie: Membership on an entity's Board of Directors or advisory committees; Syndax Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Leukemia and Lymphoma Society: Other: Senior Medical Director for Beat AML Study; Agios: Consultancy; Novartis: Speakers Bureau. Brammer:Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Seattle Genetics: Honoraria, Speakers Bureau; Kymera: Honoraria; Verastem Oncology: Other: Travel. Saad:Amgen: Other: research support; Magenta Therapeutics: Other: Personal Fees; Incyte Pharmaceuticals: Other: Personal Fees; Orcabio: Other: research support; Kadmon: Other: research support. Efebera:Celgene: Research Funding; Ohio State University: Current Employment; Takeda: Honoraria, Speakers Bureau; Pharmacyclics: Research Funding.

Abstract: Introduction: Allogeneic hematopoietic stem cell transplant (allo-HCT) is a potential curative therapy for a variety of both malignant and nonmalignant hematologic disorders. However, allo-HCT is costly and requires highly specialized, technologically advanced care that is only available in select healthcare centers across the country. Due to its cost and limited availability, minority populations are at risk for healthcare disparities in access to and outcomes of allo-HCT. Prior studies have focused on the impact of health disparities, including race, and geographic residence at time of transplant, on allo-HCT outcomes with variable results. The aim of this study was to evaluate the impact of race and location of residence on outcomes of allo-HCT at one major referral institution. Methods: We performed a retrospective cohort study of patients that underwent allo-HCT at the Ohio State University from 1984 to 2018. The impact of demographic factors including race and place of primary residence were assessed. Patients were divided into race defined as Caucasian, African American (AA), and other. They were also grouped by zip code into rural, suburban, and urban groups. Rural was defined as less than 1000 people per square mile, suburban between 1000-3000 people per square mile, and urban greater than 3000 people per square mile. 2018 population estimates were used. Patients were then stratified into 7 groups based on year (yr) of transplant for analysis. Group (gp) 1 included 1984-1988, gp 2 1989-1993, gp 3 1994-1998, gp 4 1999-2003, gp 5 2004-2008, gp 6 2009-2013, and gp 7 2014-2018. Primary endpoints were progression free survival (PFS) and overall survival (OS). PFS and OS were calculated using Kaplan Meier Curves and compared using log-rank test between race and residence groups. Results: A total of 1,943 patients were included in the study. Of these patients, median age at time of transplant was 50 years old (range 18-76), and 59.6% were male. AML/MDS patients made up the majority of the cohort at 46.3%, with the other most common diagnoses being non-Hodgkin's lymphoma (14.2%), acute lymphocytic leukemia (11.8%), and chronic myeloid leukemia (10.1%). Most patients (94.3%) identified as Caucasian, while 4.6% identified as AA, and 1.1% other. The majority of patients lived in a rural area at the time of transplant with 63.4% rural, 22.9% suburban, and 13.8% urban. There was no significant difference in OS or PFS between Caucasian and AA patients (Figure 1A and B; p=0.15, 0.21). Median OS for AA was 1.9 yrs [95% confidence interval (CI): 0.8-3.6] as compared to 2.3 yrs (95% CI: 1.9-2.9) for Caucasians, with 5 -yr OS of 33 vs. 42% and 10-yr OS of 21 vs. 36% for AA and Caucasian, respectively. Median PFS was 0.9 (95% CI: 0.5-2.7) and 1.3 yrs (95% CI 1.1-1.6), with 5 -yr PFS of 30 vs. 37% and 10-yr PFS of 21 vs. 32% for AA and Caucasian, respectively. There also was no significant difference in OS or PFS between rural, urban, and suburban patients (Figure 2A and 2B; p=0.39, 0.17), with median OS in the three groups 2.2 (95%CI: 1.7-2.9), 2.9 (95%CI: 1.6-4.5), and 2.2 (95% CI: 1.6-3.6) yrs, and 5-yr OS of 40 vs. 43 vs. 43% and 10-yr OS of 33 vs. 39 vs. 39%, respectively. Median PFS were 2.2 (95%CI: 1.7-2.9), 2.9 (95%CI: 1.6-4.5), and 2.2 yrs [95% CI: 1.6-3.6] , with 5-yr PFS of 36 vs. 40 vs. 38% and 10-yr PFS of 30 vs. 37 vs. 35%, respectively. Conclusion: Our study suggests that once patients undergo allo-HCT, there is no significant difference in outcomes between patients based on race or residence. This finding suggests that while these underserved populations may initially have less access to specialized care for HCT, if they ultimately undergo allo-HCT, outcomes are similar to their counterparts. Our study did show a significantly lower rates of allo-HCT performed in non-Caucasian races (94% Caucasians vs 4.6% AA and 1% other), which may reflect disparities in access to care in these groups as well as a lack of donors. Further research is needed to assess the barriers for these underserved patients to undergo transplant and to help ameliorate these barriers. Disclosures Chaudhry: Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bumma:Amgen: Speakers Bureau; Sanofi: Speakers Bureau. Khan:Amgen: Consultancy; Janssen: Consultancy. Devarakonda:Janssen: Consultancy. Vasu:Janssen: Membership on an entity's Board of Directors or advisory committees; Omeros: Membership on an entity's Board of Directors or advisory committees; Kiadis Inc: Other: Kiadis has obtained exclusive licensing requirements from The OHio State University. Jaglowski:Kite, a Gilead Company: Consultancy, Research Funding; Juno: Consultancy; Novartis: Consultancy, Research Funding; CRISPR: Consultancy. William:Merck: Research Funding; Celgene: Consultancy, Honoraria; Dova: Research Funding; Seattle Genetics: Research Funding; Incyte: Research Funding; Guidepoint Global: Consultancy; Kyowa Kirin: Consultancy, Honoraria. Mims:Syndax Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Leukemia and Lymphoma Society: Other: Senior Medical Director for Beat AML Study; Agios: Consultancy; Novartis: Speakers Bureau; Jazz Pharmaceuticals: Other: Data Safety Monitoring Board. Brammer:Seattle Genetics, Inc.: Speakers Bureau; Celgene Corporation: Research Funding. Efebera:Celgene: Research Funding; Pharmacyclics: Research Funding; Takeda: Honoraria, Speakers Bureau; Ohio State University: Current Employment.

Abstract: Introduction: CAR T-cell therapy has dramatically improved outcomes for patients (pts) with relapsed/refractory (r/r) DLBCL, with some achieving durable response. Still, the majority of pts have poor outcomes with CAR-T due to progressive disease, while inherent characteristics may predispose pts to CAR-T toxicities. Tools quantifying frailty and comorbidities have not been verified in large patient cohorts. The Cumulative Illness Rating Scale (CIRS) is a comprehensive tool that has been found to predict outcomes in various B cell malignancies. Here we use a machine learning algorithm to rank the prognostic impact of specific comorbidities, as measured by CIRS, and then assess survival and toxicities in pts treated with commercially available CAR T-cell products for DLBCL. Methods: We conducted a retrospective RWE analysis of pts with r/r DLBCL who underwent leukapheresis for CART at 9 academic centers. CIRS was assessed at the time of T-cell collection and calculated as in Salvi et al, 2008. High comorbidity burden was defined using a published cutoff of CIRS score ≥7. Progression-free survival (PFS) and overall survival (OS) were measured from T-cell collection. Repeated subsampling and random survival forest (RSF) modeling of PFS were used to determine the most prognostic CIRS categories in the presence of covariates. Cox proportional hazards models were fit to quantify the association between survival and the following patient features: IPI at diagnosis, concurrent indolent lymphoma, age, ECOG performance status, number of prior therapies, prior transplant, number of medications, cell of origin subtype, complex karyotype, MYC rearrangement by FISH, and MYC+BCL2/BCL6 rearrangement (double-hit). Associations between comorbidities and CAR-T adverse events were evaluated with Fisher's exact test. Results: We analyzed data from 577 pts, with a median age of 63 (range, 19-90); 90% had ECOG 0-1. Median number of prior therapies was 3 (range, 1-11) and 25% of pts (n=143) had prior autologous stem cell transplant. GCB subtype was found in 54% of pts (n=312), with 38% (n=218) non-GCB and 8% (n=47) unknown (Hahn's algorithm). MYC gene rearrangement was present in 21% and double-hit in 16% with 9% lacking FISH. Twenty-seven pts (4.7%) died before CAR-T infusion (progressive disease in 24 and infection in 3). Of the 550 pts who received CAR-T, 71% (n=393) got axicabtagene ciloleucel, 22% (n=120) tisagenlecleucel, and 7% (n=37) lisocabtagene maraleucel. The median CIRS score was 7 (range, 0-25) with 54% (n=309) having CIRS ≥7. The most frequent comorbidities were seen in the vascular (51%), endocrine (45%), and hypertension (43%) organ system categories. PFS event was observed in 56% of pts and 41% died, while survivors had a median follow-up time of 20 months. Median survival estimates were 11 months (95% CI: 8 - 15) for PFS and 30 months (95% CI: 23 - NA) for OS. CIRS ≥7 was significantly associated with PFS (HR=1.26, Fig 1A) and OS (HR=1.35, Fig 1B) in univariable analysis. According to RSF variable importance and node splits, key CIRS categories were respiratory, upper GI, renal, and hepatic (Fig 1C). Multivariable analysis showed higher ECOG (2/3 vs 1 vs 0) and 3 or more prior lines of treatment predicted shorter PFS and OS. Non-GCB subtype was related to reduced PFS but not OS, while double-hit status did not correlate with either outcome. Interestingly, CIRS ≥7 was not a significant predictor of outcomes in multivariable models. However, a severe comorbidity in any of the above four systems (denoted "Severe4", 9% of pts) was independently associated with inferior PFS (HR=2.45, Fig 1D) and OS (HR=2.30, Fig 1E). Although CIRS ≥7 was not associated with the development of CRS, pts with "Severe4" had a higher rate of grade ≥3 CRS (16% vs 6%; p=0.013). In addition, development of grade ≥3 ICANS was associated with CIRS ≥7 (26% vs 12%; p & lt;0.001). Conclusions: In this large RWE study, we demonstrate that CIRS is predictive of outcomes and identify a composite index comprising four CIRS organ systems (respiratory, upper GI, renal and hepatic; "Severe4") that had prognostic significance in CAR-T recipients for r/r DLBCL. "Severe4" is predictive of severe CRS and CIRS ≥7 is predictive of severe ICANS. The underlying mechanism leading to this observation is an area of active ongoing investigation. Given these results, CIRS evaluation and "Severe4" should be considered prior to CAR-T in DLBCL. GS & AK contributed equally Figure 1 Figure 1. Disclosures Shouse: Beigene Pharmaceuticals: Honoraria; Kite Pharmaceuticals: Speakers Bureau. Jaglowski: Novartis: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Juno: Consultancy; Takeda: Consultancy; CRISPR Therapeutics: Consultancy. 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. Patel: Kite Pharma: Consultancy, Speakers Bureau; Morphosys: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Bristol Myers Squibb: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy; Abbvie: Consultancy; TG Therapeutics: Consultancy, Speakers Bureau; MEI Pharma: Consultancy; BeiGene: Consultancy; AstraZeneca: Consultancy, Research Funding, Speakers Bureau; ADC Therapeutics: Consultancy; Lilly: Consultancy. Stephens: CSL Behring: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy; Novartis: Research Funding; JUNO: Research Funding; Mingsight: Research Funding; Arqule: Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kamdar: TG Therapeutics: Research Funding; Adaptive Biotechnologies: Consultancy; ADC Therapeutics: Consultancy; AstraZeneca: Consultancy; Genentech: Research Funding; Genetech: Other; Celgene: Other; SeaGen: Speakers Bureau; Celgene (BMS): Consultancy; Kite: Consultancy; KaryoPharm: Consultancy; AbbVie: Consultancy. Hill: Novartis: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel Support, Research Funding; Pfizer: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria, Research Funding; Celgene (BMS): Consultancy, Honoraria, Research Funding; Gentenech: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria; Incyte/Morphysis: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding. Karmali: Genentech: Consultancy; BeiGene: Consultancy, Speakers Bureau; Kite, a Gilead Company: Consultancy, Research Funding, Speakers Bureau; Karyopharm: Consultancy; Takeda: Research Funding; EUSA: Consultancy; Epizyme: Consultancy; Roche: Consultancy; Morphosys: Consultancy, Speakers Bureau; AstraZeneca: Speakers Bureau; BMS/Celgene/Juno: Consultancy, Research Funding; Janssen/Pharmacyclics: Consultancy. Kittai: Abbvie: Consultancy; Bristol-Meyers Squibb: Consultancy; Janssen: Consultancy. Danilov: Abbvie: Consultancy, Honoraria; TG Therapeutics: Consultancy, Research Funding; Takeda Oncology: Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria; Beigene: Consultancy, Honoraria; Bayer Oncology: Consultancy, Honoraria, Research Funding; Gilead Sciences: Research Funding; Bristol-Meyers-Squibb: Honoraria, Research Funding; Rigel Pharm: Honoraria; Astra Zeneca: Consultancy, Honoraria, Research Funding; SecuraBio: Research Funding.

Abstract: Introduction: CAR T-cell therapy (CART) has dramatically improved outcomes for patients (pts) with relapsed/refractory (r/r) DLBCL, but the majority of pts still have poor outcomes due to progressive disease and toxicities. Here we used a machine learning algorithm to rank the prognostic impact of specific comorbidities measured by the Cumulative Illness Rating Scale (CIRS) in DLBCL pts indicated for CART in a multicenter learning cohort (LC) and a separate validation cohort (VC). Methods: pts with r/r DLBCL included in RWE analysis underwent leukapheresis for CART at 10 academic centers. CIRS was assessed at the time of T-cell collection (Salvi et al, 2008). Progression-free survival (PFS) and overall survival (OS) were measured from T-cell collection. Random survival forest (RSF) modeling of PFS and OS was repeatedly applied to random subsets of the LC to determine the most important CIRS categories and comorbidity levels in the presence of known prognostic factors. Cox proportional hazards models of PFS and OS were fit to both cohorts. Associations between comorbidities and CART adverse events were evaluated with Fisher’s exact test. Results: The LC comprised 577 pts, median age of 63 (range, 19-90); 90% had ECOG 0-1. Median number of prior therapies was 3 (range, 1-11). GCB subtype was found in 54% of pts, with 38% non-GCB and 8% unknown. Twenty-seven pts (4.7%) died before CART infusion. Of the 550 pts who received CART, 71% got axicabtagene ciloleucel, 22% tisagenlecleucel, and 7% lisocabtagene maraleucel. The median CIRS score was 7 (range, 0-25) with 54% having CIRS ≥7. The median PFS was 11 months (95% CI: 8 – 15) and OS 30 months (95% CI: 23 – NA), with a median follow-up time of 20 months. Although CIRS ≥7 was significantly associated with PFS (HR=1.26) and OS (HR=1.35) in univariable analysis, it did not remain significant in multivariable models. According to a RSF tree depth-weighted nodal split score, severe comorbidities in the following CIRS categories had the greatest impact on PFS: respiratory, upper GI, renal, and hepatic (denoted Severe4, 9% of pts). When accounting for other significant variables, Severe4 was independently associated with inferior PFS (HR=2.45, p & lt;0.001) and OS (HR=2.30, p & lt;0.001) in the LC. This finding was recapitulated in a single-center VC (n=218, median follow-up of 35 months, median age 61 years, median of 3 prior therapies, ECOG 0-1 in 74%, Severe4 in 16% of pts, 98% receiving axicabtagene ciloleucel) as Severe4 remained independently associated with inferior PFS (HR=1.84, p=0.003) and OS (HR=1.82, p=0.007). Pts with Severe4 also had a higher rate of grade ≥3 CRS (16% vs 6%; p=0.013), while development of grade ≥3 ICANS was associated with CIRS ≥7 (26% vs 12%; p & lt;0.001).Conclusions: In this large RWE study, we identify and validate a composite index comprising four organ systems (respiratory, upper GI, renal and hepatic; Severe4) that correlates with survival outcomes in CART recipients for r/r DLBCL. GS & AK contributed equally Citation Format: Geoffrey Shouse, Andy Kaempf, Max Gordon, David Yashar, Audrey M Sigmund, Gordon Smilnak, Steven M Bair, Agrima Mian, Lindsey Fitzgerald, Amneet Bajwa, Samantha Jaglowski, Neil Bailey, Mayzar Shadman, Krish Patel, Deborah M Stephens, Manali Kamdar, Brian T Hill, Jordon Gauthier, Reem Karmali, Loretta Nastoupil, Adam S Kittai, Alexey V Danilov. Impact of a validated composite comorbidity score on outcomes in patients treated with CAR T-cell therapy for diffuse large B cell lymphoma (DLBCL): A multicenter real-world evidence (RWE) study [abstract]. In: Proceedings of the Third AACR International Meeting: Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2022 Jun 23-26; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2022;3(5_Suppl):Abstract nr A27.