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Abstract Introduction: CAR-T therapy has transformed cancer therapy. with its first Food and Drug Administration (FDA) approved product in August 2017. Given the expanding indications and growing experience, particularly with management of immediate toxicities requiring specialized expertise such as Cytokine Release Syndrome (CRS) and Immune Effector Cell-Associated Neurotoxicity syndrome (ICANS), FDA recently removed the Risk Evaluation and Mitigation Strategies (REMS) for CD19 and BCMA targeting CAR-T on June 26th2025. In particular, given that CRS and ICANS typically occur in the first 2 weeks post CAR-T infusion, the minimum required stay near CAR-T treatment center is reduced from one month to 2 weeks. While this could reduce treatment burden for patients (pts) who need to travel away from home to receive CAR-T, there is a need to update the transition of care from CAR-T center to pts' local oncology practice. Pts carry in their rate of recovery and have varying supportive care needs in the second half of the month post CAR-T infusion. To assist with care transition and planning, we examine the use of AI multimodal large language model (LLM) to predict patients' supportive care needs 2 weeks after CAR-T infusion based on the clinical data at the time of CAR-T evaluation, prior to leukapheresis. This timepoint was selected to also maximize travel, lodging and caregiver planning for pts and family as well. Methodology: Pts who were treated with FDA-approved CAR-T at Mayo Clinic Rochester between December 2022 and June 2025 were examined. Based on experiences with referral practices in the Midwest region, we defined patients with high monitoring needs as those who between day 14-30 post CAR-T had either hospital admission due to recurrent CRS or ICANS or required transfusion of more than 1 blood product per week (red blood cell or platelets). Others were classified as low monitoring needs. Clinical notes, labs, vital signs and electrocardiogram at the time of CAR-T evaluation were abstracted and summarized by Gemini LLM for association with patients with high versus low monitoring needs post CAR-T. Model was developed and tested for predicted needs and concordance with actual outcome of these pts. Results: Among the 362 pts who received FDA approved CAR-T in the timeframe, 84 pts had high monitoring needs. An additional 84 pts with low monitoring needs were randomly selected from 278 pts. These were divided into a training cohort and test cohort of 84 pts each, with 42 pts with high and 42 pts with low monitoring needs. Demographics of the two cohorts displayed no statistical difference. LLM analysis of the clinical data at the time of CAR-T eval identified 5 categories associated with risk for high monitoring needs: 1) Disease status (clinical notes about bulky, progressive disease or CNS involvement); 2) inflammatory and tumor burden markers (CRP, LDH); 3) hematologic status (platelet, plt; neutrophil count ANC); 4) renal function; 5) performance status. Using common clinical lab parameter convention (platelets <100, ANC< 1, CrCl< 30ml/min), and prioritizing for not missing pts with high monitoring needs, LLM model was defined to predict patients for high monitoring needs if high risk feature was identified in category 1 or any category combinations; whereas patients with no high risk feature or only 1 category that is not disease status was predicted as low monitoring needs. In this model, the sensitivity was 85.7%, specificity 23.8%, F1 score 65.5%. Applying this model to test cohort 2, the sensitivity was 83.3%, specificity 28.6%, and F1 score 65.4%. Discussion: We demonstrate proof-of-concept that LLM can be used to analyze clinical data at the time of evaluation for CAR-T eligibility to predict for supportive care needs post treatment. Not surprisingly, features identified by LLM to be associated with high monitoring needs are those previously reported by us and others at the time of CAR-T evaluation and or pre-lymphodepletion to be associated with risk for cytopenia, infection, hospitalization and non-relapse mortality. Based on the summary output generated by LLM, additional opportunities for classification methods were identified to improve specificity and balanced accuracy of the LLM model. This is a promising tool for further development to assist clinicians and patients to plan their treatment journey.

Abstract Introduction The International Prognostic Index (IPI) is widely used to stratify risk in large B-cell lymphoma (LBCL) across all ages, with age-adjusted (aa)IPI applied to younger patients. While there have been efforts to develop prognostic indices (PIs) tailored to older patients, few are adopted in clinical practice due to their complexity and reliance on functional assessments, which are not routinely collected in real-world registry datasets. Recently proposed SENIOR-IPI (Dubois, ASH 2024) was developed for older patients with LBCL receiving anthracycline (A)-based therapy. We assessed the performance of standard and novel PIs in patients aged 80+ years and externally validated the SENIOR-IPI. Methods We harmonized and pooled data of patients aged 80+ years with newly diagnosed LBCL from a national registry and two prospective cohorts: NiHiL (Czech Republic, enrolled 2010–2023), LEO (USA; n=222, 2015–2020), and MER (USA; n=77, 2010–2015), forming a cohort of 819 individuals. We included 536 individuals with complete data on IPI components and albumin, including 485 treated with chemotherapy and 397 with A-based regimens (primary cohort). Following PIs were evaluated: IPI, NCCN-IPI, (aa)IPI, and SENIOR-IPI (age per year, aaIPI components, LDH >3x ULN as extra point, and albumin, all weighted six-fold; extranodal involvement excluded due to lack of prognostic significance). Multivariable hazard ratios (HR) were estimated using Cox proportional hazards models; discriminative ability was assessed using C-index and calibration plots. The primary endpoint was overall survival (OS); event-free survival results were consistent (230/357 events were deaths) and are not reported here. Results Among the 397 A-treated patients (median age 82 years, range 80–99), ECOG performance status (PS) 2–4 was observed in 35% of patients, clinical stage III–IV in 67%, elevated LDH in 65% (8% with >3x ULN), >1 extranodal (EN) site in 32%, and albumin levels < 3.5 g/dL in 27%. In multivariable modeling, only age per year (HR=1.07, P<0.01), and clinical stage (HR=1.36, P=0.048) were independent predictors of OS, whereas ECOG PS (HR=1.27, P=0.12), trichotomized LDH by ULN (HR=1.23, P=0.08) and albumin (HR=1.17, P=0.35) were not significant. SENIOR-IPI had the highest discrimination (C-index 0.631) in A-treated patients, outperforming IPI (0.617), NCCN-IPI (0.591), and aaIPI (0.620), with consistent results across cohorts: NiHiL (0.633), LEO (0.619), and MER (0.621). SENIOR-IPI stratified patients into low- (L-Risk, 0–9 points, 28%), low-intermediate (L-Int, 10–19 points, 42%), high-intermediate (H-Int, 20–29 points, 23%), and high-risk (H-Risk, 30–40 points, 7%) categories, with OS medians of 6.3, 3.8, 2.4, and 1.4 years, respectively (P<0.01), and significant separation between L-Int and H-Int (HR=1.47, P=0.02). By comparison, IPI categorized patients as L-Risk (12%), L-Int (24%), H-Int (27%), and H-Risk (37%), with median OS of 8.7, 4.6, 4.8, and 1.9 years, resp. (P<0.01). aaIPI yielded following distributions: 13%, 29%, 37%, and 21%; and median OS: 8.7, 5.3, 3.4, and 1.5 years; P<0.01. NCCN-IPI stratified patients into three groups: L-Int (13%), H-Int (49%), and H-Risk (39%), with respective OS medians of 8.7, 4.1, and 2.5 years (P<0.01). All PIs showed modest overestimation of mortality (calibration slopes: SENIOR-IPI 1.36; IPI 1.24; aaIPI 1.30; NCCN-IPI 1.26; intercept: -0.97, -0.87, -0.92, -0.87, resp.). In the entire cohort (n=536), SENIOR-IPI showed highest C-index (0.651 vs IPI 0.622, aaIPI 0.631, NCCN-IPI 0.606), and stratified patients into L-Risk (26%, 2-year OS: 6.4 years), L-Int (40%, 3.2 years), H-Int (24%, 1.5 years), and H-Risk (10%, 0.6 years). Calibration slope was 1.18 (intercept -0.33). Among patients not receiving chemotherapy, SENIOR-IPI also performed best (C-index 0.759 vs IPI 0.738, aaIPI 0.757, NCCN-IPI 0.728). Conclusion SENIOR-IPI enables effective risk stratification of patients aged 80+ years with LBCL into four prognostically distinct groups, outperforming traditional indices (IPI, NCCN-IPI, aaIPI) in patients receiving A-based therapy, as well as in the entire cohort and in patients not receiving chemotherapy. While its discrimination is superior, modest miscalibration suggests that future recalibration may improve precision. These findings support SENIOR-IPI as a clinically relevant prognostic tool for the elderly LBCL patient population. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

Abstract Over the past decade, classification systems using high-throughput genetic data have been developed to identify molecular subtypes of DLBCL. Although not a primary goal, these classifiers were also proposed as prognostic factors in their respective publications. To date, however, no study has directly compared these classifiers' ability to predict overall (OS) and event-free survival (EFS) in the same cohort. Herein, we sought to systematically compare predictive performance, benchmarked against the IPI, of several current established molecular classifiers and evaluate if any add significant independent prognostic information beyond the IPI. WES (including paired germline filter) and RNAseq data from newly diagnosed DLBCL patients (N=432; 2018 WHO criteria) in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource (MER) were available for analysis (WES n=112, RNAseq n=40, or both n=280). The number of cases able to be classified (including as unclassified) for each classifier was as follows: IPI (432, 100%), cell-of-origin (COO, by Hans algorithm; 346, 80.1%), refined COO (by gene expression with Dark Zone Signature; 320, 100%), Haematological Malignancy Research Network (HMRN; 349, 89.0%), B-cell state (320, 100%), Lymphoma Ecotype (320, 100%), Lymphoma Microenvironment (LME; 320, 100%), Tumor microenvironment (TME26; 320, 100%), SubLymE (312, 97.5%), LymphGen (358, 91.3%), and DLBclass (223, 58.2%). OS was defined as time from diagnosis to all-cause death while EFS was defined as time from diagnosis to disease progression, initiation of second-line treatment, or all-cause death. We calculated Harrell's c-statistics for each Cox proportional hazards model evaluating the discriminative performance of each classifier in predicting OS/EFS. Using bootstrap validation, we obtained optimism-corrected c-statistics, which we report in the results. We performed likelihood ratio tests (LRT) comparing a univariable Cox model with IPI alone and models including both IPI and a given classifier to assess if a classifier provided independent prognostic information beyond the IPI. All patients were treated with immunochemotherapy (IC) with curative intent, 247 (57%) were male, median age at diagnosis was 65 years (IQR 55-72 years), 390 (96%) were White, 209 (60%) had GCB subtype by Hans, 22 (5.1%) had MYC double-hit by FISH (MYC and BCL2 or BCL6), and 162 (37.9%) had an IPI ≥ 3. The median follow-up was 7.0 years, 167 (39%) experienced an event, and 137 (32%) died. In a univariable Cox model, the c-statistic for IPI predicting OS was 0.66 (95% confidence interval [CI] 0.61-0.70). All other classifiers had c-statistics of ≤0.56. The c-statistic for IPI predicting EFS was 0.64 (95% CI 0.60-0.69), and all other classifiers had c-statistics of ≤0.58. The univariate DLBclass results for OS and EFS were not significantly impacted when restricted to cases with confidence >0.7 (n=136). In Cox models of IPI alone versus IPI plus an individual classifier, the only classifier that provided statistically significant, independent information for OS was TME26 (LRT p=0.02). Adjusting for IPI, patients who were TME26-negative had significantly inferior OS compared to TME26-positive cases (HR 1.63, 95% CI 1.07-2.47; p=0.02). For EFS, DLBclass (restricted to confidence >0.7) added significant prognostic information beyond IPI (LRT p=0.02). This finding was largely driven by C5 subtype; relative to C1 subtype and adjusting for IPI, C5 subtype had significantly inferior EFS (HR 5.53, 95% CI 1.81-17.0; p=0.003). In summary, we compared prognostic performance of multiple DLBCL molecular classifiers with respect to OS and EFS in a single real-world, prospective cohort of newly diagnosed, IC-treated DLBCL. Our data supports two key findings: all classifiers had modest performance for prognosis, and none individually outperformed the IPI in predicting OS nor EFS. Second, only TME26 and DLBclass (confidence >0.7) provided additional prognostic information beyond that captured by the IPI for OS and EFS, respectively. This finding suggests that the tumor immune microenvironment and characteristics of C5 DLBCLs (ABC-subtype, CD79B mutations) can potentially offer significant independent information for predicting survival and response to front-line immunochemotherapy. If replicated, these findings could inform risk-adapted treatment approaches and aid in identifying high-risk patients for enrollment in genomically-informed clinical trials.

Abstract Chimeric antigen receptor T (CART) cell therapy has shown unprecedented success in the treatment of hematological malignancies. However, the immunosuppressive tumor microenvironment of both solid and liquid tumors is a major barrier for CART efficacy. Immunosuppressive myeloid cells inhibit CART efficacy. Colony-stimulating factor 1 receptor (CSF1R) promotes macrophage proliferation, survival, and anti-inflammatory response and is upregulated on myeloid cells in many cancers, making CSF1R an appealing therapeutic target. We aimed to test the interactions between CSF1R, myeloid cells, and CART response, and to study CSF1R targeting in the context of CART cell therapy. We utilized CD19-targeted CART cell therapy (CART19) in lymphoma preclinical models and thyroid-stimulating hormone receptor (TSHR)-targeting CART cell therapy (TSHR-CART) in thyroid cancer models. We first measured CSF1R expression on myeloid cells in vitro. Suppressive myeloid cells, polarized from healthy donor monocytes using an anaplastic thyroid cancer (ATC) cell line, 8505c, or mantle cell lymphoma cell line, JeKo-1, significantly upregulate CSF1R (p=0.0002) compared to media control. After polarization, myeloid cells significantly inhibit TSHR-CART and CART19 antigen-specific proliferation compared to freshly isolated monocytes (p=0.012, p<0.01, respectively) indicating that suppressive myeloid cells contribute to CART failure in multiple tumor types. We then performed single cell RNA sequencing on peripheral blood taken at baseline from patients with mantle cell lymphoma treated with CART19. We found a significant increase of CSF1R on monocyte subsets in CART19 non-responders vs responders (padj=0.0037). Next, we determined the impact of CSF1R blockade on CART cell therapy in vivo. Using lymphoma models, B6 mice were engrafted with the luciferase+ CD19+ murine lymphoma cell line TBL-12 (1x106 cells i.v. 1 day after 250 mg/kg cyclophosphamide). Tumor burden was significantly reduced after 7 days of treatment with low dose CART19 (0.5x106 i.v.) + anti-mouse CSF1R antibody (16mg/kg i.p. twice weekly) vs CART19 + IgG control (p=0.0146). We then tested the impact of CSF1R blockade in mice experiencing tumor relapse. After TBL-12 engraftment, mice were treated with anti-mouse CSF1R or IgG control antibody followed two days later with high dose CART19 (1x106 i.v.) to induce remission. Mice were re-challenged with TBL-12 14 days later. Mice treated with anti-mouse CSF1R antibody showed increased tumor control and significantly higher survival (p=0.0416). Using thyroid cancer models, first we identified high macrophage infiltration in biopsy specimens of patients with ATC compared to normal thyroid tissue and benign thyroid tumors through immunohistochemistry (IHC) of patient samples (p<0.01, p<0.0001, respectively). To test if macrophages are associated with CART failure in ATC, NSG mice were subcutaneously engrafted with 1x106 TSHR+ THJ529 tumors, an ATC cell line derived from patient biopsy samples from the Mayo Clinic thyroid cancer biobank, followed by i.v. treatment with 1x107 TSHR-CART or untransduced T cell control (UTD). IHC staining of tumor tissue collected at experimental endpoints revealed a dose-dependent, significant infiltration of human CD3+ T cells into the tumors which inversely correlated with murine F4/80+ myeloid cell and murine YM-1+ M2 macrophage infiltration. This led us to hypothesize that myeloid cell targeting with CSF1R blockade can improve TSHR-CART efficacy. We utilized the same ATC model described above to test CSF1R targeting. When TSHR+ THJ529 tumors reached approximately 100 mm3, mice were randomized by tumor volume and treated with CSF1R inhibitor PLX5622 (600mg/kg) or vehicle control, followed by either UTD or TSHR-CART cells 5x106 i.v. Mice treated with TSHR-CART + PLX5622 showed significantly improved tumor control vs TSHR-CART + vehicle control (p<0.0001) or UTD + PLX5622 (p<0.0001). Together, our results highlight immunosuppressive myeloid cells which express CSF1R as a major cell type limiting CART efficacy in both solid and liquid tumors. We also identified a strategy to overcome myeloid-mediated suppression of CART cells by targeting CSF1R with antibody or small molecule inhibitors.

Abstract Background: Older adults with newly diagnosed ALL treated with conventional chemotherapy have poor survival due to high rates of toxic death and disease relapse. The Alliance A041703 trial (NCT0373981) tested chemotherapy-free treatment with the anti-CD22 antibody-drug conjugate inotuzumab ozogamicin (InO) followed by the anti-CD19-CD3 bifunctional T-cell engager blinatumomab (blina) without maintenance in older adults to reduce toxicity and increase efficacy of therapy for this patient (pt) population. We previously reported with 22-month (mo) median follow-up that the study met its primary endpoint with a 1-year (yr) event-free survival (EFS) of 75% (90% confidence interval [CI] 63-89% lower bound exceeding null rate of 10%; JCO 2023 41, 7006). Here we report secondary outcomes with 45-mo median follow-up: 3-yr EFS, 3-yr overall survival (OS), response, and relapse characteristics. Methods: Eligible pts were ≥60 yrs old with newly diagnosed, Ph-negative, CD22-positive (≥20% of blasts) B-cell ALL without planned allogeneic HCT (alloHCT), liver disease, or CNS involvement at enrollment. Induction IA was InO 0.8 mg/m2 day (d) 1, 0.5 mg/m2 d8, d15 IV on a 21d cycle. Pts with adequate cytoreduction (marrow blasts reduced ≥50% or marrow cellularity ≤20%) after IA went to IB if in CR/CRi (InO 0.5 mg/m2 d1, d8, d15 IV; 28d cycle) or IC if no CR/CRi (InO 0.8 mg/m2 on d1 and 0.5 mg/m2 on d8 and d15 IV; 28d cycle). Those without cytoreduction to IA started course II blina. Pts without events in IA/B/C received course II blina continuous IV (9 mcg/d x 7d then 28 mcg/d x 21d; 14d break; 28 mcg/d x28d). Pts with CR/CRi to InO received 2 more 28d cycles of blina; others received 3 more. CNS prophylaxis was methotrexate 15 mg intrathecal x 8 doses. EFS was time from therapy start to failure to achieve CR/CRh/CRi by the end of course II, progression, relapse, or death, whichever occurred first, censored at last follow up. OS was time from registration to death from any cause censored at the last known alive date. Results: The median age of the 33 treated pts was 71 yrs (range 60-84). Eight pts had prior therapy for alternate malignancy in CR for >2 yrs prior to enrollment (6 multiple myeloma, 1 non-Hodgkin lymphoma, 1 breast cancer). Median CD22 expression was 92% (range 21-100%) and 49% had NCCN poor-risk genetics. Five pts underwent alloHCT in first CR/CRi and 2 pts received POMP maintenance after early discontinuation of blina (1 toxicity, 1 physician choice). The CR/CRi rate after InO was 85% (1 early death/refractory, 2 refractory, 2 undetermined due to low marrow cellularity on remission assessment marrow) with CR/CRi rate of 97% by completion of course II blina. With 45 mo median follow-up, the estimated 3-yr EFS was 48% (95% CI 33-70%) with a median EFS of 31 mo (95% CI 17.4-not reached [NR]) and no events after 31 mo. Sixteen events occurred: 12 relapses, 1early death, and 3 deaths in remission (1 encephalopathy, 1 relapse of multiple myeloma, 1 pulmonary complications after alloHCT). No isolated CNS relapse has been reported. Among relapses, 10 had immunophenotyping. Four (40%) were CD19-negative, one of which was also CD22-negative. Among CD19-negative relapses, genetics were hypodiploid (2), Pax5alt (1), and ZNF384-like (1, also CD22-negative). TP53 mutation or loss was observed in 5/12 (42%) relapses. Thirteen pts died. The estimated 3-yr OS was 59% (95% CI 44-79%) with median OS NR (95% CI 32-NR) with no deaths after 36 mo. In univariate analysis, EFS and OS were not impacted by age, gender, genetic risk (NCCN), prior therapy for alternate malignancy, or alloHCT in first remission. EFS was better with higher CD22 expression at diagnosis (≥90% vs <90%, 3-yr EFS 60% vs 25%, P=0.044). EFS and OS were worse for detectable minimal residual disease (MRD) at any timepoint by ASO-PCR. Undetectable MRD after course IA (1 cycle InO induction) was associated with EFS with a 3-yr EFS of 52% vs 0% for detectable MRD (median NR vs 8 mo, hazard ratio [HR] 0.07, P=0.004) and a 3-yr OS of 100% vs 0% for detectable MRD (median NR vs 20 mo, HR 0.00, P=0.0014). Conclusions: Longer follow-up of chemotherapy-free treatment with InO and blina for older pts with newly diagnosed, Ph-negative, CD22-positive, B-cell ALL reveals durable remissions and survival. The A041703 regimen is a compelling option for first-line treatment of this pt population. Support: U10CA180821, U10CA18088; https://acknowledgments.alliancefound.org.

Abstract Background Nodal peripheral T-cell lymphomas (nPTCLs) are a challenging group of non-Hodgkin lymphomas that frequently recur after or are refractory to first line (1L) treatment. Chemotherapy options in the relapsed or refractory (R/R) setting are limited. The incorporation of non-cytotoxic agents including antibody drug conjugates, immune checkpoint inhibitors, epigenetic modifiers, and phosphatidylinositol 3-kinase inhibitors offers new therapeutic potential and possibly better outcomes. We report on outcomes for patients (pts) with R/R nPTCL enrolled in the multi-center LEO-MER prospective cohort study (NCT02736357) who received second line (2L) therapy. Methods Six hundred and three adult pts with newly diagnosed nPTCL were prospectively enrolled in the University of Iowa/Mayo Clinic MER observational cohort (2002-2015) or the expanded LEO cohort (2015-2020). Secondary overall survival (sOS) was calculated from date of 2L treatment initiation to date of death or last follow-up. Secondary event-free survival (sEFS) was calculated from date of 2Ltreatment initiation to disease progression, initiation of 3rd line therapy, or death from any cause. sEFS and sOS were evaluated using Cox model and Kaplan-Meier estimator. Log-rank test was used to test the significance of difference between groups. Pts with concomitant B-cell lymphomas were excluded from this analysis. Results Thus far, 169 pts with nPTCL initiating 2L therapy were evaluated. Of these, 75 (44.4%) had PTCL-NOS, 63 (37.3%) had angioimmunoblastic T-cell lymphoma (AITL, inclusive of nodal T-follicular helper cell lymphoma), 20 (11.8%) had ALK-negative anaplastic large cell lymphoma (ALCL), and 11 (6.5%) had ALK-positive ALCL. At 2L treatment initiation, the median age was 64 with 86.1% of pts having advanced stage disease. Of the 108 pts with available international prognostic index (IPI) scoring, 46.3% had an IPI of ≥3. Thirty-four (20.1%) pts had received a consolidative autologous stem cell transplant (ASCT) in the 1L. A total of 86 pts (50.1%) had primary refractory disease (partial response, stable or progressive disease as best response to 1L therapy), 45 (26.6%) experienced early relapsing disease within 6 months of 1L therapy, and 38 (22.5%) had relapsed disease >6 months from 1L therapy. After a median follow-up of 7.1 years (yrs), median sOS was 1.52 yrs, and sEFS was 3.2 months (mos). There was no difference in sOS or sEFS regardless of timing of relapse. In keeping with other studies, ALK-positive ALCL pts had the best 5-year OS (70.1%) compared to other subgroups (ALK-negative ALCL 45.0%, AITL 30.4%; PTCL-NOS 21.3%). Lymphoma was the leading cause of death following 2L therapy, with a 2-year cumulative incidence of 49.2%. Eighty pts (47.3%) received only cytotoxic chemotherapy as second line (2L) therapy; ICE (41 (51.3%)) and gemcitabine-containing regimens were most common (14 (17.5%)). Seventy-five pts (44.4%) were treated with non-cytotoxic agents given as monotherapy or in combination with chemotherapy. The most common non-cytotoxic therapies were brentuximab vedotin (33 (44.0%)), romidepsin (17 (22.7%)) and immune checkpoint inhibitors (9 (12.0%)). Fourteen pts (8.3%) underwent palliative interventions involving radiation, steroids, or cyclosporine alone. Intent to proceed to transplant in the 2L was known in 158 pts (101 (63.9%) not intended, 57 (36.1% intended)). Following 2L treatment, 18 (10.7%) pts proceeded to consolidative ASCT and 10 (5.9%) to allogeneic transplant. Only 21 (12.9%) were treated on a clinical trial. Pts who received a non-cytotoxic agent had superior outcomes compared to pts receiving only chemotherapy; the median sOS was 30.4 mos (95% confidence interval [CI] 15.3, 53.52 mos) vs 11.7 mos ((95% CI 7.95,19.58); p=0.04; HR 0.67) and the median sEFS was 4.83 mos (95% CI 3.38, 10.09) vs 2.33 mos ((95% CI 1.71,3.02); p=0.02; HR=0.65). Conclusions We report here one of the largest prospective cohorts in R/R nPTCL. The LEO-MER cohort, despite its association with academic centers, shows poor outcomes regardless of refractory or relapsed disease, frequent inability to proceed to intended consolidative transplant, and low clinical trial participation in 2L, which corroborates findings from other registries (Jain 2025, Stuver 2019). Outcomes improved for pts treated with non-cytotoxic agents. Updated data including additional pts and subgroup analyses will be reported at the meeting.

Abstract Background: Despite advances in LBCL treatment, 35–45% of patients relapse or have refractory disease highlighting an unmet clinical need. Clinical trials are essential to advancing lymphoma treatment, yet participation remains low – especially among certain populations. We hypothesized that participation in clinical trials as part of first-line therapy is associated with improved survival outcomes and conducted this retrospective study in a multi-center cohort. Methods: The LEO cohort prospectively enrolled newly diagnosed patients with LBCL between 2015 and 2020 at 8 academic medical centers in the United States. LBCL histology's included T-cell/histiocyte rich LBCL, Primary mediastinal LBCL, high grade B-cell lymphoma and DLBCL NOS. Pathology was reviewed and classified by a LEO pathologist. Clinical and treatment data (including trial participation) were abstracted from medical records. The primary outcome endpoint is overall survival (OS) defines as the time from diagnosis to death from any cause or last follow up. Univariable and multivariable Cox proportional hazards models were used to evaluate the association between OS and therapeutic trial participation. Univariable models assessed each baseline covariate, with and without interaction with trial participation. The multivariable model adjusted for age, sex, race/ethnicity, diagnosis to treatment interval [DTI], and IPI, including an interaction between IPI and trial participation which was justified per minimal Akaike information criteria. All models clustered on institution. Results: Among the 2636 patients with LBCL, the median age was 63 (range 18 – 99), 57% were male, 75% non-Hispanic white (NHW), 12% Hispanic (H) and 7.3% African American (AA), 62% had Stage III/IV disease, and 214 (8.0%) participated in a clinical trial as part of first line therapy. Overall, between ages 18 – 80, clinical trial participation increased with age (55 % in ages 18-30 vs 11% in ages 71-80) but dropped significantly for patients > 80 (3.4%). There were no significant differences in the rate of trial participation by sex (male 8.6 % vs female 7.5%; p=0.35), race/ethnicity (NHW 8.9% vs H 5.5% vs AA 6.3%; p=0.061), body mass index (underweight [<18.5] 4.5% vs normal [18.5-24.9] 7.7% vs overweight [25-29] 8.3% vs obese (>30) 8.5; p = 0.75) or Rural-Urban Continuum Codes (Metro[1-3] 8.5% vs non-metro Urban [4-6] 7.6% vs non-metro Rural [7-9] 5.4 %; p=0.49). Patients with advanced disease more commonly participated in a trial. Most patients received systemic treatment (98%), with 94% of patients receiving an anti-CD20 antibody and 91% of patients receiving anthracycline-based therapy. Importantly, there was no difference in anthracycline use in trial participants vs nonparticipants (92 vs 91%; p=0.53). Patients with high IPI scores [3-5] were more likely to participate on trials compared to those with low scores [1-2] (8% vs 5.9% respectively, p= 0.012). Patients who participated in clinical trials had significantly longer median DTI (26 days vs 21 days; p <0.0001) and had a significantly lower number of comorbidities compared to non-participants (mean 0.55 vs. 0.69; p=0.032). Among patients with low IPI (0–2), 5-year OS was 89% trial participants (CTP) compared to 82% for non-participants (CTNP). Among patients with high IPI (3–5), 5-year OS was 78% for CTP vs 60%for CTNP. The multivariable Cox model demonstrated a significant interaction between trial participation and IPI, with trial participation with low IPI having a non-significant hazard ratio (HR) of 0.87 with 95% CI (0.57,1.32), while trial participation with high IPI had a significant HR of 0.57 (0.44, 0.74). Additionally, increased age, male sex, black race, and lower DTI were associated with increased hazard. Conclusion: Patients at high risk of poor outcomes such as those with advanced age (80+), higher comorbidities burden, and those needing more urgent therapy (shorter DTI) were less likely to participate in clinical trials. In this multi-institutional cohort of patients with LBCL treated at academic centers, frontline trial participants had outcomes that were equivalent or better than those receiving standard care. These finding underscore the value of clinical trial participation even in the frontline setting and support trial designs that expand inclusion- allowing participation of patients who are older, medically complex or in need urgent therapy.

Abstract Introduction: THRLBCL is a rare disease accounting for less than 10% of all diffuse large B-cell lymphoma (DLBCL) subtypes. THRLBCL was associated with poor outcomes in the pre-rituximab era, with limited contemporaneous data. Optimal frontline treatment remains unclear with some studies advocating for intensive regimens. The goal of this international study is to analyze the survival and treatment-related outcomes in patients with newly diagnosed THRLBCL treated with rituximab-containing chemotherapy and to compare with a DLBCL, not otherwise specified (NOS) cohort. Methods: THRLBCL and DLBCL patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) (NCT02736357) (7/2015 to 5/2020), Molecular Epidemiology Resource (1/2010 to 6/2015), and Czech Lymphoma Study Group project (NiHiL) (NCT03199066) (2/2010 to 11/2023) were analyzed. Diagnosis was made in dedicated hematopathology centers in both registries. We excluded patients with prior nodular lymphocyte-predominant Hodgkin lymphoma, central nervous system involvement, and not treated with rituximab-containing therapy. Event-free survival (EFS) and overall survival (OS) were estimated by Kaplan-Meier.Univariate associations were derived via Cox model and multivariate models were constructed by forward selection of significant variables with P≤0.05. Propensity score matching (1:5, caliper 0.2) between THRLBCL and DLBCL NOS patients was performed using IPI score components and treatment as covariates. Results: We identified 158 patients (LEO: 67 and NiHiL: 91) with THRLBCL. Among them, 140 patients received rituximab-containing regimens and were included in this analysis. Median age was 58 years (range, 19-89) with 57% aged ≤60 years. Most patients were male (n= 88; 63%) and had ECOG performance status (PS) of 0-1 (n= 111; 79%), stage III-IV (n= 111; 79%), elevated LDH (n= 92; 66%), and B symptoms (n= 84; 60%). Fifty (36%) patients had ≥2 extranodal (EN) sites, mostly liver (n= 39; 28%) and lung (n= 16; 11%), bone marrow (BM) involvement was observed in 26% (n= 37). Bulky disease (≥7.5cm) was present in 50 (36%) and IPI score ≥3 in 68 (48%) patients. The median diagnosis-to-treatment interval was 23 days (IQ range, 13-38.5). Frequent regimens were R-CHOP (n= 106; 75.7%), followed by intensive regimens such as R-MegaCHOP/ESHAP, R-HyperCVAD/MA, and R-CODOX-M/IVAC (n= 15; 10.7%), and R-CHOEP/EPOCH-R (n= 10; 7.14%). With a median follow-up of 3.92 years, the 4-year EFS & OS were 71% and 80%, respectively. Lymphoma was the main cause of death (n= 15; 11%) among 30 events. No difference in 4-year EFS (70% vs. 76%; P= 0.55) & OS (80% vs 82%; P= 0.96) were observed between R-CHOP and intensive regimens. Factors associated with shorter EFS and OS in univariate analysis for THRLBCL were ECOG PS 2-4: (HR= 3.3; P<.001 & HR= 5.97, P<.001, respectively); ≥2 EN sites (HR= 1.85, P= 0.043 & HR= 2.54, P= 0.014, respectively); B symptoms (HR= 2.35, P= 0.014 & HR= 2.84, P= 0.023) and IPI score (HR= 1.5, P= 0.002 & HR= 2.16, P<.001). Stage III-IV and BM involvement were associated with shorter OS only (HR= 7.36, P= 0.05 & HR= 2.18, P= 0.036, respectively). Among them, only ECOG PS 2-4 (OS: HR= 3.6, P= 0.003) and B symptoms (EFS: HR= 2.3, P= 0.046) were independent predictors of survival in multivariate analysis. Finally, we compared baseline characteristics and survival between THRLBCL (n= 140) and DLBCL NOS (n= 6099; LEO/MER: 2069 & NiHiL: 4030) treated with rituximab-containing regimens. Patients with THRLBCL were younger (≤60 years: 57% vs. 38%; P<.001), more frequently had ECOG PS 0-1 (79% vs 76%; P= 0.012), stage III-IV (79% vs 63%; P<.001), B symptoms (60% vs 38%; P<.001), and liver involvement (28% vs 7%; P<.001), compared to DLBCL NOS. Subtype was not associated with survival (OS HR= 0.79, P= 0.262 & EFS HR= 0.93, P= 0.662) when adjusted for IPI score. With a median follow-up of 4.89 years in the DLBCL NOS cohort, we observed similar 4-year EFS (71% vs 67%; P= 0.197) & OS between histologies (80% vs 77%; P= 0.125). These results were confirmed in propensity matching for EFS (HR= 0.98, P= 0.897) and OS (HR= 1.07, P= 0.732). Conclusions: In this large international analysis of patients with newly diagnosed THRLBCL contemporaneously treated, we observed similar survival rates compared to DLBCL NOS treated with R-CHOP and intensive regimens. ECOG PS and the presence of B symptoms were independent factors associated with survival.

Abstract Introduction: The Duffy null variant (genotype or phenotype) is associated with lower circulating absolute neutrophil counts (ANC) without increased risk for infection. It is found in ~66% of people identifying as Black or African American vs <1% of people of Asian or European ancestry. Many ANC reference intervals (RI) are not representative of the Duffy null population. There are no adult Duffy null WBC RI and no pediatric Duffy null ANC or WBC RI. Thus, we aimed to assess Duffy null ANC and WBC distributions as well as develop WBC and ANC RI for adults and pediatrics. Methods: Twenty-three sites across the United States collected samples with all sites excluding participants with conditions or medications that could impact ANC or WBC. Only Duffy null participants were included. Sex, race, ethnicity, age, sample collection type, practice setting, Duffy testing method, ANC, and WBC were recorded. The non-parametric method for determining lower limit of normal (LLN), upper limit of normal (ULN), and 90% confidence intervals (CI) around the limits was performed according to the Clinical and Laboratory Standards Institute guidelines. Specific ULN and LLN are not reported as these are preliminary data. The Mann-Whitney U test was used to compare sex and prior data; differences by age groups were assessed with Kruskal-Wallis test. Results: 316 participants 18+ years-old (y/o) were assessed of whom 62.3% (n=197) are female, 97.5% (n=308) identified as Black or African American, and 94.9% (n=300) identified as non-Hispanic. Median age was 47 y/o (IQR: 32-60.5). Median ANC was 2600/uL (IQR: 1860-3530; range: 400-7400); 28.6% (n=90) of participants had ANC <2000/uL, 13.6% (n=43) had ANC <1500/uL, and 2.5% (n=8) had <1000/uL. The 90% CI around the LLN was 810-1070/uL and 5570-7130/uL around the ULN. Consistent with prior data, there was a difference in median ANC by sex (male: 2400/uL; female: 2710/uL; p=0.02). There was no significant difference between this ANC data and previously published Duffy null ANC data (p=0.28). Median WBC was 5.4x109/L (IQR: 4.4-6.5; range: 2.10-11.64) with 4.1% (n=13) of participants with WBC <3.0x109/L. The 90% CI around the LLN is 3.68-4.30x109/L and 11.02-12.97x109/L around the ULN. 515 participants between 0-17 y/o were assessed with 51.8% (n=267) females, 94.8% (n=488) identified as Black or African American, and 94.0% (n=484) identified as non-Hispanic. Among pediatric participants, 56.8% (n=291) had ANC <2000/uL, 38.7% (n=198) had ANC <1500/uL, and 14.4% (n=74) had ANC <1000/uL. For those <1 y/o (n=29), median ANC was 950/uL (IQR: 840-1360; range: 111-3910). There are currently too few samples to predict ULN and LLN. Median WBC was 8.85x109/L (IQR: 7.03-10.16; range: 4.17-13.53). For those 1-5 y/o (n=143), median ANC was 1735/uL (IQR: 1100-2550; range: 207-5810) with a 90% CI around the LLN of 207-820/uL and 4020-5810/uL around the ULN. Median WBC was 6.72x109/L (IQR: 5.64-8.25; range: 3.68-12.97). For those 6-11 y/o (n=128), median ANC was 1590/uL (IQR: 1090-2470; range: 420-5490) with a 90% CI around the LLN of 420-910/uL and 4340-5490/uL around the ULN. Median WBC was 5.42x109/L (IQR: 4.45-6.70; range: 2.80-10.50). For those 12-17 y/o (n=215), median ANC was 2190/uL (IQR: 1460-2930; range: 204-5850) with a 90% CI around the LLN of 540-930/uL and 4350-5510/uL around the ULN. Median WBC was 5.06x109/L (IQR: 4.26-6.20; range of 2.04-9.91). There is a significant difference in ANC by age category (p<0.0001). Conclusion: This is the first report of healthy pediatric Duffy null ANC and WBC data and the first large-scale verification of adult Duffy null ANC and WBC data. Final RI are expected in September 2025. Among adults with the Duffy null phenotype, ANC LLN are likely between 810-1070/uL. Pediatric ANC LLN are likely as low as 207-820/uL (1-5 y/o), 420-910/uL (6-11 y/o), and 540-930/uL (12-17 y/o). These findings redefine “normal” as a significant proportion of healthy participants have ANC or WBC below current RI or below thresholds typically defined as disease. Limitations include heterogeneous sample populations and collection methods. Future analyses will assess differences between collection sites or methods. Ultimately, this work lays the foundation for a more scientifically sound and equitable approach to medical care by ensuring that RI accurately reflects health for the entire community. Healthcare systems are strongly encouraged to adopt Duffy null-specific ANC and WBC RI.

Abstract Introduction: Reporting patient outcomes by CAR-T treatment centers is part of the accreditation requirement under the FACT (Foundation for Accreditation of Cell Therapy) Immune Effector Cell (IEC) Program standard. Currently, this is a time-consuming and manual process, making it increasingly difficult to sustain with the growing CAR-T applications and patient volume. The objective of this study is to evaluate how a Large Language Model (LLM) can be used to automate the abstraction and summarization of medical record for CAR-T toxicities. Methods: Clinical data from patients treated with CAR-T between January 2018 and June 2025, including hematology clinical notes, lab results, flowsheets, vital signs, and medication administration record, were used as the source of patient information. The American Society of Transplant and Cell Therapy (ASTCT) CAR-T toxicity grading guideline for cytokine release syndrome (CRS) and immune effector cell associated neurologic syndrome (ICANS) were used to define these toxicities. With the large context window of the LLM (Gemini 2.5 pro), we created a prompt by embedding both the patient data and the ASTCT guidelines for CRS and ICANS, along with an outline of specific information we aimed to abstract from the data. Additionally, the LLM was instructed to provide contextual justification for the data it extracted from patient information. The LLM-generated output included event onset date, resolution date, maximum grade, date of maximum grade, and medications given for management. The CRS and ICANS outcome reports generated by the LLM were then compared to the IEC compliance program data. Any discrepancies identified were reviewed manually. Results: Among patients (pt) treated with CAR-T in the specified timeframe, 47 were selected as training cohort. This cohort included pt with toxicities events, no events, and a mix of events of varying grades. For the test cohort, 66 pts who received CAR-T from March to June 2025 were included. Demographics for the training and test cohorts are reflective of evolving clinical practice (training, test cohorts: median age 69, 65; male 55%, 74%; lymphoma/leukemia 66%, 48%; multiple myeloma 34%, 52%; CD19 CAR-T 46%, 50%). Compared to data from the IEC compliance program, the LLM-generated summaries for CRS events demonstrated an accuracy of 90%, precision 95%, sensitivity 100%, specificity 80%, F1 score 97%, and Matthew's correlation coefficient 87%. For ICANS event, the LLM achieved an accuracy of 91%, precision 92%, sensitivity 92%, specificity 90%, F1 score 92%, Matthew's correlation coefficient 83%. Maximum grade, for both CRS and ICANS, were identified with >90% accuracy. However, dates for CRS and ICANS were less accurate, with the lowest accuracy noted in identifying the event resolution date, 45% for CRS and 67% for ICANS. Medical records were reviewed for all discrepancies between the LLM and the IEC Compliance Program data. The most common discrepancy was a mismatch in event resolution date, determined to be due to differing criteria used by the compliance team and the LLM prompt. Of note, a few discrepancies were attributed to missed information by the IEC Compliance Team, which was correctly identified and categorised by the LLM. An updated LLM prompt (LLMv2) was developed and applied to the test cohort. In version 2, the prompt was revised to include clearer instructions on how to summarize CRS and ICANS events, as well as new instructions on additional data elements to be summarized. The performance of LLMv2 on this cohort for CRS event identification was 100% across all categories (accuracy, precision, sensitivity, specificity, F1 score, and Matthew's correlation coefficient). For ICANS the LLMv2 achieved accuracy of 96%, precision 69%, sensitivity 100%, specificity 93%, F1 score 82%, Matthew's correlation coefficient 80%. Accuracy in identifying event resolution date improved significantly from 64% to 99%. Conclusions: Our study demonstrates that LLMs can significantly reduce the time required to abstract and summarize CAR-T toxicities, while maintaining high accuracy. One limitation of our study is that it is based on data from a single institution. However, plans are already underway to evaluate the use of LLMs in a multi-institutional setting.