Hilal, Talal

Purpose Neutropenic diet (ND) has historically been recommended to reduce infectious complications in patients with cancer. Although its use has declined over the past decade, recent studies, particularly in patients undergoing hematopoietic stem-cell transplantation (HSCT), have renewed concern regarding the safety of a liberalized diet (LD). We performed a meta-analysis of studies comparing ND with LD in patients with cancer. Methods We searched MEDLINE, Embase, and Cochrane databases from inception through January 2026. Comparative studies evaluating ND versus LD in adults or children with cancer were included. Primary outcomes were major infections and bacteremia/fungemia; secondary outcomes were pneumonia, diarrhea, and mortality. Random-effects meta-analyses were performed to calculate pooled relative risks (RRs) with 95% CIs. Results Fifteen studies including 4,320 patients met criteria for analysis. ND was not associated with significant differences in major infections (RR, 1.02 [95% CI, 0.88 to 1.18]; P = .795), bacteremia/fungemia (RR, 0.97 [95% CI, 0.78 to 1.22]; P = .805), pneumonia (RR, 0.98 [95% CI, 0.59 to 1.63]; P = .933), diarrhea (RR, 1.12 [95% CI, 0.96 to 1.31]; P = .159), or mortality (RR, 0.94 [95% CI, 0.77 to 1.15]; P = .632). Sensitivity analyses restricted to randomized controlled trials (RCTs) were consistent. In hematologic malignancy/HSCT studies (9 studies; 1,769 patients), no differences were observed across outcomes. In RCTs limited to these patients (6 studies; 855 patients), ND was associated with lower bacteremia/fungemia risk (RR, 0.67 [95% CI, 0.47 to 0.95]; P = .023), with no differences in other outcomes. Conclusion ND was not associated with reductions in major infections, pneumonia, diarrhea, or mortality compared with LD. These findings do not support routine implementation of ND for patients with short-term neutropenia or lower-risk cancer populations although selected high-risk patients, particularly those undergoing HSCT or experiencing prolonged neutropenia related to hematologic malignancies, may still warrant cautious dietary practices.

Brexucabtagene-autoleucel (brexu-cel) produces high rates of measurable residual disease-negative (MRD-) complete response (CR) in adults with Philadelphia-chromosome positive (Ph+) acute lymphoblastic leukemia (ALL); however, subsequent relapses remain frequent. It is unclear whether maintenance with tyrosine kinase inhibitors (TKIs) can enhance remission durability. We evaluated outcomes among adults with relapsed/refractory Ph+ ALL who received commercial brexu-cel and achieved MRD- CR across 19 U.S. institutions. Considering TKI maintenance as a time-varying covariate, we analyzed outcomes based on receipt of subsequent TKI maintenance versus no maintenance. Patients receiving consolidative transplantation or non-TKI maintenance were excluded. Fifty-one patients were included: 20 received TKI maintenance and 31 received no maintenance. The use of TKI maintenance was associated with a significantly lower 1-year cumulative incidence of relapse (HR 0.12; 95% CI, 0.02-0.88; p=0.037) which translated into improved progression-free survival (PFS, HR 0.19; 95% CI, 0.04-0.85; p=0.029) and a trend towards improved overall survival (OS, HR 0.34; 95% CI, 0.07-1.62; p=0.18). There was no difference in non-relapse mortality (NRM, HR 0.83; 95% CI, 0.12-5.87; p=0.85). This real-world analysis supports the administration of TKI maintenance in Ph+ ALL following achievement of MRD- CR with brexu-cel as a strategy to improve PFS following chimeric antigen receptor T cell therapy.

e19023 Background: Undetectable measurable residual disease (uMRD) is associated with prolonged progression free survival in patients with chronic lymphocytic leukemia (CLL) (Rios-Olais et al., 2024). Peripheral blood (PB) MRD testing is less invasive and allows more frequent MRD monitoring than bone marrow (BM) MRD testing. As MRD testing and MRD-guided time-limited therapies become more common, there is a need to determine the concordance between rates of uMRD in the PB and BM. Methods: We performed a systematic review and meta-analysis of studies in CLL to determine the concordance between rates of uMRD in the PB and BM. Prospective clinical trials evaluating first-line, time-limited treatment of CLL with targeted agents or anti-CD20 monoclonal antibodies (mAbs) were identified via searches of PubMed, Embase, Scopus, and Web of Science from inception until December 15 th , 2025. Studies were included if they reported rates of BM and PB uMRD at the same timepoint using the same method of MRD testing. Study arms evaluating chemotherapy, single-agent targeted therapy or single-agent anti-CD20 mAbs were excluded. Study sample size, number of patients receiving MRD testing, rates of uMRD in PB and BM, time and method of MRD testing, depth of MRD testing, and treatment arm were extracted. The agreement of uMRD rates between PB and BM was assessed using intraclass correlation coefficients (ICC). Results: 3128 studies were identified on initial search. After study selection criteria were applied, 24 timepoints across 12 prospective clinical trials were analyzed. Across all timepoints, 3121 PB and 2782 BM MRD measurements were included. All timepoints defined uMRD at a depth of under 0.01% CLL cells (10^-4). 20/24 timepoints utilized flow cytometry for MRD testing, 3 utilized allele-specific oligonucleotide PCR (ASO-PCR), and one utilized next-generation sequencing (NGS). 8 timepoints evaluated patients treated with a BTK inhibitor + venetoclax, 10 evaluated patients treated with venetoclax + an anti-CD20 mAb, and 6 evaluated patients treated with triplet therapy. The ICC between rates of uMRD in PB and BM was 0.925 (95% CI: 0.89, 0.95), indicating an excellent degree of agreement between the two methods of testing.(Koo & Li, 2016) The mean uMRD rates in PB and BM were 70.1% and 64.3%, respectively. The mean rate of uMRD in the PB was 5.87% (95% CI: -7.05, 18.80%) higher than in the BM; indicating a consistent slight bias of higher PB uMRD rates compared to BM across timepoints. Conclusions: Overall, we demonstrate that in patients with CLL treated with modern, time-limited therapy, there is high concordance in uMRD rates between PB and BM. Rates of uMRD in the PB are typically slightly higher than in BM.

e18574 Background: ND has historically been recommended to reduce infectious complications in cancer patients (pts). While the adoption of ND has declined over the last decade, recent studies - particularly in pts undergoing hematopoietic stem cell transplantation (HSCT) - have raised uncertainty regarding the safety of LD. Herein, we performed a meta-analysis of studies directly comparing ND with LD in pts with cancer. Methods: We conducted a systematic search of MEDLINE, Embase, and Cochrane databases from inception through January 2026. Comparative retrospective and prospective studies were included if they were comparing ND with LD in adults or children with cancer. Primary outcomes were major infections and bacteremia/fungemia. Secondary outcomes were pneumonia, diarrhea, and all-cause mortality. Random-effects meta-analyses were performed to calculate pooled risk ratios (RR) with 95% confidence intervals (CI). The review followed PRISMA 2020 guidelines. Results: Fifteen studies enrolling 4,320 patients were included in the primary analysis. Six studies enrolled only adult patients, three were restricted to pediatric populations, and six included mixed adult and pediatric cohorts. Across these studies, ND was not associated with a significant reduction in major infections (RR 1.02, 95% CI 0.88–1.18; p=0.795), bacteremia/fungemia (RR 0.97, 95% CI 0.78–1.22; p=0.805), pneumonia (RR 0.98, 95% CI 0.59–1.63; p=0.933), diarrhea (RR 1.12, 95% CI 0.96–1.31; p=0.159), or all-cause mortality (RR 0.94, 95% CI 0.77–1.15; p=0.632). Sensitivity analyses restricted to RCTs showed consistent results. Subgroup analysis of hematological/HSCT studies (9 studies; 1,769 pts) also showed no differences across outcome. Analysis restricted to RCTs in hematologic/HSCT pts (6 studies; 855 pts) showed no differences in major infections, pneumonia, diarrhea, or mortality; however, ND was associated with a lower risk of bacteremia/fungemia (RR 0.67, 95% CI 0.47–0.95; p=0.023). Heterogeneity across studies was low to moderate. Conclusions: ND was not associated with reductions in major infections, pneumonia, diarrhea, or mortality compared with LD. A reduction in bacteremia/fungemia was observed in RCTs of hematologic malignancy and HSCT pts. Overall, these findings suggest that routine ND implementation is unnecessary for most cancer pts, although cautious dietary practices may remain reasonable in selected high-risk hematologic malignancy/HSCT populations.

7041 Background: CD20×CD3 bispecific antibodies and CD19-directed CAR T-cell therapies are increasingly used in relapsed/refractory DLBCL. CAR T therapy is associated with higher rates of CRS,ICANS, and cytopenias, whereas bispecific antibodies are often perceived as less toxic and more outpatient-friendly. Methods: We conducted a retrospective cohort study using the TriNetX Global Collaborative Network. Adult patients with DLBCL treated with bispecific antibodies (glofitamab, epcoritamab) were compared with those receiving commercial CAR T-cell therapy (tisa, liso, axi). Propensity score matching was performed on demographics, comorbidities, baseline laboratory values, and corticosteroid exposure, yielding 468 patients per cohort. Outcomes included CRS, ICANS, severe neutropenia (ANC <500/µL), and thrombocytopenia (platelets <50×10³/µL), as well as hospitalization and ICU admission at 1, 3, 6, and 12 months. Overall survival (OS) was assessed using Kaplan–Meier analysis with log-rank testing. Results: After matching, CAR T therapy was associated with significantly higher immune-mediated toxicity. CRS occurred more frequently with CAR T at 1 month (37.4% vs 22.4%), 3 months (39.3% vs 27.6%), 6 months (40.6% vs 28.8%), and 12 months (41.2% vs 29.7%) (all p<0.001). ICANS was also more common with CAR T across all timepoints (1 month: 10.5% vs 4.9%; 12 months: 12.6% vs 7.5%). Severe neutropenia and thrombocytopenia were markedly more frequent in the CAR T cohort, with neutropenia affecting 66.7% vs 12.8% at 1 month and 71.6% vs 32.7% at 12 months (all p<0.001). Despite higher toxicity, healthcare utilization was comparable. Hospitalization rates were similar between groups at 1 and 3 months (61.8% vs 66.7% and 67.1% vs 75.9%), and ICU admission rates did not differ meaningfully at any timepoint. Importantly, overall survival consistently favored CAR T therapy. Survival differences emerged early and persisted over time, with lower mortality in the CAR T cohort at 1 month (2.1% vs 9.0%), 3 months (7.7% vs 18.6%), 6 months (15.8% vs 26.7%), and 12 months (26.5% vs 35.3%), corresponding to significantly improved OS by log-rank testing at all timepoints (p<0.001). Conclusions: In this large, real-world, propensity-matched analysis of relapsed/refractory DLBCL, CAR T-cell therapy was associated with substantially higher rates of CRS, ICANS, and severe cytopenias compared with bispecific antibodies. However, these toxicities did not translate into higher hospitalization or ICU utilization. Despite a less favorable early toxicity profile, CAR T therapy conferred a consistent and clinically meaningful survival advantage from early to late follow-up. Early toxicity alone should not preclude CAR T referral in appropriate candidates, underscoring the need for optimized patient selection, sequencing strategies, and supportive care.

Abstract The use of chimeric antigen receptor (CAR) T-cell therapy is increasing for adult B-cell acute lymphoblastic leukemia (B-ALL), with 3 CD19 CAR T-cell products commercially available. Several key clinical questions related to best practices for CAR T-cell administration in this population exist, and limited prospective randomized trials have been conducted to fill these knowledge gaps. Thus, to help guide clinical practice, we conducted a modified Delphi study to develop and validate consensus recommendations on the administration of commercially available CAR T-cell therapy for adults with B-ALL. Consensus panelists (n = 9) included principal investigators (PIs) from Real World Outcomes Collaborative of CAR T-Cell Therapy in Adult ALL (ROCCA) consortium sites and were selected based on expertise and CAR T-cell center volume. Final panel consensus recommendations were distributed for rating by the remaining PIs from ROCCA consortium sites, which served as the validation group (n = 27). Consensus topics included patient selection, bridging and pre–CAR T-cell leukemia staging, lymphodepletion, and CAR T-cell treatment setting, specific toxicity prevention and management, post–CAR T-cell response assessment and disease monitoring, and the role of consolidation and/or maintenance therapies after CAR T-cell therapy. Initially, 58 recommendation statements were evaluated for consensus. After 2 panel meetings, a total of 34 statements achieved consensus rating among the expert panel. After rating by the validation group, all but 1 recommendation statement continued to meet consensus, for a total of 33 consensus recommendation statements on the administration of CAR T-cell therapy in adult B-ALL.

Abstract Large Language Models (LLM) are being widely adopted into the medical field for their impressive ability to analyze and summarize large amounts of text data. These models enable clinicians and researchers to extract meaningful insights from complex datasets and may assist with decision making. Here we present our workflows and application of LLM for the interpretation and summarization of clinical data related to CAR-T cell therapy. Using an LLM (Gemini 2.5 pro) in the Google Cloud Computing (GCP) environment, two applications were developed to analyze CAR-T cell therapy clinical data: 1) extracting and summarizing CRS and ICANS event-related data to streamline the compliance team workflow, and 2) identifying features available at time of CAR-T infusion able to classify patients into high- or low-monitoring needs 14 days post CAR-T. Patient data (vitals, labs, hematology notes, and EKGs) were extracted from the electronic medical record (EMR) using Google BigQuery into SQL tables in GCP. For each application, relevant data fields were retrieved, formatted into JSON objects, and embedded in the LLM prompt for context-aware processing. Both applications have undergone iterative prompt engineering after analyzing the LLM output against ground truth data in the EMR. For the application extracting and summarizing CRS and ICANS events, the LLM was optimized on Mayo Clinic Rochester data. When compared to the IEC compliance database, the LLM achieved 100% accuracy and F1 score for CRS events, and 96% accuracy and 82% F1 score for ICANS events. The match rate for CRS and ICANS grades were 83% and 89% respectively. We applied the same LLM to Mayo Clinic Arizona (MCA) and Mayo Clinic Florida (MCF) cases, who document clinical notes and toxicity flowsheet differently, and achieved an accuracy (MCA: 93%, MCF:93%) and F1 score (MCA: 96%, MCF: 96%) for CRS and accuracy (MCA: 81%, MCF:82%) and F1 score (MCA: 76%, MCF: 75%) for ICANS. LLM was able to capture events missed by manual reviews. For most of the discrepancies where compliance team final adjudication is needed, LLM will be updated to flag discrepancies for review by the compliance team. For the application related to the monitoring needs 14 days post CAR-T, the LLM identified 5 categories predictive of high or low monitoring needs post CAR-T infusion (disease status, inflammatory and tumor burden markers, hematologic status, renal function and performance status). Our model achieved a sensitivity of 85.7%, specificity of 23.8%, and F1 score of 65.5% for our first cohort, compared with data extracted by the LLM from the EMR. For our second cohort, with demographics statistically similar to cohort 1 and using the same 5 categories, the LLM achieved a sensitivity of 83.3%, a specificity of 28.6%, and F1 score of 65.4%. Our workflow and applications of LLM’s provide examples and guidance to others interested in applying LLM’s for clinical and research applications. Citation Format: Emmanuel Contreras Guzman, Matthew Jankowski, Andre De Menezes Silva Corraes, Malvika Gupta, Monica L. Shaw, Madiha Iqbal, Talal Hilal, Saurabh Chhabra, Ricardo Daniel Parrondo, Jody K. Mclean, Kim R. Riester, Kayla Joseph, Melinda Tan, Holly Ross, Cleyonia Barnett, Sylvia Carter, Semy Girmay, Rachel Wolan, Milana Ramsey, Christian Downhour, Kristy Morgan, Shae Sibley, Erica Rushing, Lucy Holmes, Allison Burgstahler, Stephen M. Ansell, Hassan Alkhateeb, Matthew Hathcock, Ramona Bruno, Allison C. Rosenthal, Hemant Murthy, Patrick B. Johnston, Jonas Paludo, Yi Lin. Applications of large language models to CAR-T cell therapy clinical data using Google cloud computing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2740.