Citations

Abstract Background Ceftriaxone-resistant Escherichia coli infections are increasingly common, partially because of the emergence of E. coli sequence type 131 (ST131), including its subclade C2/H30Rx, which produce extended-spectrum β-lactamases. Methods A prospective cohort including 14 US sites, which enrolled monomicrobial ceftriaxone-resistant and susceptible E. coli bloodstream infection (BSI) cases in a 1:1 ratio, was used to compare ST131 versus non-ST131 E. coli BSI, with specific attention to E. coli ST131 C2/H30Rx. Desirability of outcome ranking was determined at 30 days after infection onset. Results This analysis included 282 patients with E. coli BSI; 43% (121/282) were E. coli ST131 and 23% (66/282) belonged to the C2/H30Rx subclade. Resistance to ceftriaxone was present in 79% (96/121) ST131, 86% (57/66) E. coli ST131 C2/H30Rx, and 27% (43/161) E. coli non-ST131. Compared to patients with non-ST131 E. coli BSI, patients with ST131 BSI were older (median 70 years, [Q1 62, Q3 76] years vs 65 years, [51, 74]; P = .005) and more often admitted from long-term care facilities (21/121 [17%] vs 7/161 [4%], P < .001). Overall and empiric carbapenem use was more frequent in the treatment of patients with ST131 BSI compared with non-ST131 BSI (overall 89/121 [74%] vs 50/161 [31%]; empiric: 58/121 [48%] vs 31/161 [19%], P < .001). Desirability of outcome ranking outcomes were similar between groups. Conclusions Most ceftriaxone-resistant E. coli from US patients with E. coli BSI belong to ST131, particularly E. coli ST131 C2/H30Rx, serving as an important driver of carbapenem use.

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) is typically detected too late for useful therapeutic interventions; hence, we sought blood biomarkers to detect early-stage disease. Experimental Design: Using mass spectrometry and ELISA on plasma pools from the University of Pennsylvania (Penn) and the Mayo Clinic (Mayo), we identified aminopeptidase N (ANPEP) and polymeric immunoglobulin receptor (PIGR) as increased in early-stage (stage I/II) PDAC plasma compared with controls. We tested ANPEP and PIGR, along with prior data for thrombospondin 2 (THBS2) and carbohydrate antigen 19-9 (CA19-9), in retrospective phase II studies using separate cohorts of PDAC plasmas at different stages versus healthy or nonmalignant disease controls (DC) from Penn (n = 135) and Mayo (n = 537). Results: Comparing healthy controls with stage I/II PDAC, we obtained area under the receiver-operating characteristic curves (AUC) of 0.78 [95% confidence interval (CI), 0.68–0.86]/0.80 (95% CI, 0.74–0.85; ANPEP) and 0.81 (95% CI, 0.70–0.88)/0.86 (95% CI, 0.82–0.90; PIGR) for the Penn/Mayo phase II studies, respectively. In multivariable models, CA19-9/THBS2/ANPEP, CA19-9/THBS2/PIGR, and CA19-9/THBS2/ANPEP/PIGR elicited AUC of 0.94 to 0.96 for Penn and 0.97 for Mayo. Notably, the four-marker panel elicited AUC of 0.87 for the Mayo stage I/II versus DC and 0.91 for stages I to IV versus DC. At a specificity of 95%, a plasma biomarker panel composed of CA19-9 (≥35 U/mL), THBS2 (≥42 ng/mL), ANPEP (≥2,995 ng/mL), and PIGR (≥1,800 ng/mL) yielded a sensitivity of 91.9% for PDAC stages I to IV and 87.5% for PDAC stage I/II. Conclusions: Adding ANPEP and PIGR to a plasma biomarker panel of CA19-9 and THBS2 enhances the detection of early-stage PDAC when comparing cancer versus healthy or nonmalignant DC. Given the concordance of our data in two retrospective phase II studies, assessments in prediagnostic cases are warranted.

Abstract Background Several ovarian cancer studies have suggested that a body mass index (BMI) of 30 or higher is associated with lower compliance with National Comprehensive Cancer Network–recommended chemotherapy but primarily involved treatment before 2012, when dose capping was recommended for patients with higher body surface areas. Updated analyses in the contemporary treatment era are warranted. Methods In a retrospective cohort of patients with newly diagnosed ovarian cancer receiving curative-intent carboplatin plus paclitaxel in the Yale-Smilow Cancer Network (2012-2022), we evaluated BMI at diagnosis in relation to relative dose intensity (RDI)—the ratio of completed chemotherapy dose intensity to the National Comprehensive Cancer Network–recommended dose intensity—which reflects dose modification both before and during treatment. We also assessed starting RDI (which reflects modifications before treatment) and received RDI (which reflects modifications during treatment). Data on hospitalizations and hematological chemotoxicities were collected. We examined the association between BMI (<25, 25-30, ≥30) and chemotherapy completion, hospitalizations, and toxicities using multivariable linear and logistic regressions. Results Among 327 patients, the average RDI was 79.7%, and 44.3% had an RDI below 85%. Mean (SD) starting and received RDI were 97.9% (9.1%) and 81.8% (25.7%), respectively. Higher BMI was associated with higher RDI (Paggregate = .03) and received RDI (Paggregate = .04). Body mass index was not associated with starting RDI, dose reductions, delays, hospitalizations, or hematological toxicities. Conclusions Among patients with ovarian cancer treated since 2012, the overall RDI was low. Relative dose intensity was higher among patients with a BMI of 25 or higher compared with a BMI below 25. Most dose modifications occurred during treatment and not before initiation. Studies with body composition data and interventions that maximize chemotherapy completion during treatment are warranted.

Abstract Background Eligibility criteria for clinical trials are crucial for maintaining safety and study integrity. However, overly restrictive criteria can result in unrepresentative trial populations, leading to gaps in understanding real‐world treatment efficacy. Addressing potentially modifiable exclusions (PMEs) could enhance trial accessibility and participation without compromising safety. Methods The authors retrospectively analyzed screen‐failed patients with biliary tract cancer or pancreatic cancer between August 2019 and November 2024 at The University of Texas MD Anderson Cancer Center. Screen‐failed patients were those who provided informed consent but did not participate for any reason. Clinical data were obtained from screening logs and electronic health records. PMEs were identified and validated by two independent medical oncologists. Results Of 585 screen‐failed patients from 18 trials, 509 were analyzed (367 with pancreatic cancer and 142 with biliary tract cancer) after excluding 76 because of incomplete data. Leading causes of screen failure were declined participation (19%), comorbidities (12%), suboptimal organ function (11%), absence of a biomarker (10%), and insufficient biospecimens (7%). Reasons for declining included preference for standard care (23%), travel (22%), and competing trials (5%). The authors identified 69 patients (13.6%) who had PMEs (primarily borderline laboratory abnormalities), including liver function (23%), kidney function (20%), platelet count (12%), hemoglobin (7%), and white blood cell count (6%) abnormalities. Other PMEs included previous or concurrent malignancies (9%) and viral hepatitis (4%). PMEs were evenly distributed across trials. Conclusions Rigid eligibility criteria exclude stable patients who might benefit from investigational treatments. Easing criteria related to incidental or asymptomatic laboratory abnormalities could broaden trial accessibility and improve enrollment in populations that are more representative of real‐world use.

Abstract Chimeric antigen receptor (CAR) T-cell therapy has demonstrated remarkable response rates in relapsed/refractory aggressive B-cell non-Hodgkin's lymphoma. However, durable remissions occur in only 40% of treated patients, highlighting mechanisms of therapeutic resistance and immune escape. While cytotoxicity is principally executed by CAR T-cells, monocytes shape CAR-T cell efficacy and orchestrate cytokine-driven immunity. In this study, we defined distinct metabolic profiles of T-cell and monocyte subsets based on clinical response. Single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing (scTCR-seq) were performed on peripheral blood mononuclear cells at three timepoints: before lymphodepletion (BL), at peak CAR-T expansion (PK), and one-month post-infusion (M1). Data were processed with CellRanger v7.0.1 and analyzed with the immunopipe pipeline (Wang et al., 2025). Seurat v4.3.0 was utilized for unsupervised hierarchical clustering analysis; subsets identified included classical monocytes (CM), intermediate monocytes (IM), non-classical monocytes (NM), and monocytic myeloid derived suppressor cells (mMDSC). Metabolic profiles were compared across patients achieving ≥6-month complete remission (CR, n=16), primary refractory disease (PD1, n=4), or relapsed after a prior response (PD2, n=12). A total of 107035 T cells and 129981 monocytes from 77 serial samples in 32 patients were analyzed. CR patients had a higher T-cell:monocyte ratio than PD1/PD2 at all time points, especially at BL and PK (BL 1.2 vs 0.4, p=0.011; PK 1.3 vs 0.3, p=0.027). Clinical responses were compared with metabolic pathway analysis and identified oxidative phosphorylation (OXPHOS) as the dominant pathway. OXPHOS was consistently enriched in PD cohorts across T-cell subsets, particularly in PD1 vs CR at BL (mucosal-associated invariant T-cell (MAIT) and T peripheral memory (Tpm)), and at PK (CD4/CD8 memory precursor effector cells (MPEC) and activated MPECs (MPECa), CD4 T-helper 1 proliferating (Th1p), CD4 Th2 activated (Th2a), regulatory T-cell (Treg), CD8 naive senescent (CD8NS), CD8 T effector memory (Tem) tumor recirculating (TR), CD8 Tpm, CD8 T resident memory (Trm) TR and MAIT Tpm). By M1, OXPHOS enrichment in CD4/CD8MPECa, CD4Th2a, CD8NS, CD8TemTR reversed, now predominant in CR although CD8Tpm and CD8TrmTR remained enriched in PD1. In the monocyte subsets at BL, PD2 showed OXPHOS enrichment in CD163+ monocytes (mono), IM IL1, mMDSC SIRPA, mMDSC TGFβ, and CM IL6 subsets compared to PD1 and CR, while PD1 showed OXPHOS enrichment in IM CD38, CM TGFβ, and mMDSC HIF1A vs CR and PD2. This persisted at PK. By M1, the pattern reversed and mirrored that of T-cells, with CR patients showing OXPHOS enrichment in CD163+mono, CM IL6, CM TGFβ, IM CD38, mMDSC HIF1A, mMDSC SIRPA and mMDSC TGFβ, and additionally in CM EMT, CM p53, NM, NM CD36 vs PD1/PD2. Glycolysis/gluconeogenesis (GLY) was also enriched across subsets. In T-cells, PD1 vs CR showed GLY enrichment in CD4Th2a, CD8Tpm, CD8Tpm proliferating and MAIT Tpm at PK. In monocytes, GLY was enriched in PD1/2 vs CR at BL (CD163+mono, CM IL6) and PK (CD163+mono, IM CD18, mMDSC SIRPA). By M1, GLY metabolism was enriched in CR vs PD1/PD2 in CD163+mono, CM IL6, mMDSC SIRPA. Additional GLY enriched subsets at CR vs PD1 included CM, CM p53, EMT, IM CD38, IM IL1, mMDSC HIF1A, NM, NM CD36. Inositol phosphate metabolism (IP) was predominantly enriched in PD2 vs CR at BL (CD8NS, CD8Tcm, CD8Tpm activated), PK (CD4Th2, CD8NS, CD8Tem TR, CD8Tpm proliferating, γδT Tem) and M1 (CD4/CD8 MPECa, CD4 Th1/Th2, CD8NS, CD8Tpm, CD8 Tpm proliferating, Treg and MAIT Tpm). Notably, Treg was the only T-cell subset enriched for IP at PK in CR vs PD1/PD2. Additionally, the TCA cycle was enriched in PD1 Tregs and Th2 cells at BL and PK vs CR/PD2. A higher T-cell:monocyte ratio in CR vs PD1/PD2 supports prior evidence that elevated pre-lymphodepletion lymphocyte:monocyte ratios predict better outcomes. We identified distinct metabolic signatures in T-cells and monocytes between CR and PD1/PD2. OXPHOS enrichment in T-cells and monocytes at M1 in CR patients may reflect oxidative programming as a hallmark of sustained anti-tumor immunity. Conversely, GLY enrichment in PD1 T-cells at PK may reflect short-lived effector states lacking persistence. Overall, these findings highlight metabolic profiling as a promising predictive biomarker and therapeutic programming target to enhance CAR T-cell outcomes.

Abstract Background Primary CNS lymphoma (PCNSL) is a rare, aggressive diffuse large B-cell lymphoma confined to the CNS, with poor outcomes. Virally associated PCNSL, including AIDS-related PCNSL (AR-PCNSL) and CNS post-transplant lymphoproliferative disorder (CNS-PTLD) accounts for ~10% of cases and is strongly linked to EBV infection and poor prognosis. In our prior Blood (Gandhi et al. 2021) study, targeted sequencing showed that EBV⁺ PCNSL lacks canonical MYD88, CD79B, and PIM1 mutations and retains intact HLA class I/II, suggesting distinct immunobiology. However, questions remain regarding the immune microenvironment, broad mutational landscape, and intratumoral heterogeneity. Here, we present the first large-scale comprehensive integrated analysis of virally associated PCNSL to define subtype-specific vulnerabilities and therapeutic implications. Methods FFPE brain biopsies from 72 PCNSL patients (40 EBV- de novo PCNSL, 32 EBV+ PCNSL including 18 AR-PCNSL and 14 CNS-PTLD) were analyzed. Immune gene expression was profiled using the NanoString PanCancer Immune Panel. Whole exome sequencing (WES) defined recurrent driver mutations, tumor mutational burden (TMB), and LymphGen classification (excluding A53 subtype). Single nuclei RNA sequencing (snRNA-seq) using the 10x Genomics Chromium Flex platform characterized cellular heterogeneity. Results WES demonstrated a marked reduction in canonical mutations (MYD88L265P, CD79B, PIM1, CARD11) in CNS-PTLD (0%) and AR-PCNSL (29%) vs. de novo PCNSL (87.5%; p<0.0001). AR-PCNSL had a distinct mutational signature when compared with CNS-PTLD and de novo PCNSL. NOTCH1/2 mutations were significantly enriched in AR-PCNSL (71%) vs. CNS-PTLD (9%) and de novo PCNSL (33%) (p<0.01). NLRC5 mutations were present in 64% of AR-PCNSL cases, higher than the 25% observed in de novo PCNSL and were absent in CNS-PTLD. TMB was significantly elevated in AR-PCNSL (mean 26.27 mutations/Mb) vs. de novo PCNSL (17.22) and CNS-PTLD (11.01; p=0.0018) underscoring pronounced genomic instability and suggesting HIV may exert a mutagenic influence beyond immunosuppression. EBV driven subtypes lacked MCD features and were more often classified as ST2 or unassigned. Despite NOTCH2 mutations, AR-PCNSL cases were not classified under the BN2 subtype, further highlighting limitations in current molecular classification systems to accurately stratify virally associated PCNSL. Immune transcriptomic profiling revealed further distinctions within EBV+ PCNSL. CNS-PTLD showed increased expression of genes related to antigen presentation (p<0.0001), cytotoxicity (p=0.0019), and T cell function (p<0.0001), suggesting retained immune responsiveness. AR-PCNSL exhibited significant suppression of HLA class I/II genes (p=0.0027 and p<0.0001 respectively), despite intact genomic loci, implicating post-transcriptional or epigenetic silencing. Immune cell composition revealed reduced macrophage infiltration and suppressed CD4 expression in AR-PCNSL. CNS-PTLD showed higher expression of checkpoint molecules LAG3, TIM3, and CTLA4, consistent with T cell exhaustion. snRNA-seq profiling of AR-PCNSL identified distinct malignant and non-malignant cell populations, including a reduced CD4⁺ compartment and altered microglial/macrophage populations and cell states compared to de novo PCNSL, corroborating bulk transcriptomic data, amongst other ongoing analysis. Conclusion This study represents the largest and most comprehensive immunogenomic investigation of virally associated PCNSL. AR-PCNSL and CNS-PTLD lack canonical PCNSL driver mutations and instead harbor distinct mutational signatures, including NOTCH pathway alterations in AR-PCNSL. These findings underscore divergent pathogenic mechanisms and support tailored therapies. AR-PCNSL is marked by high TMB, suppressed antigen presentation, and reduced CD4⁺ infiltration, indicating profound immune dysfunction. CNS-PTLD retains immune functionality but shows checkpoint upregulation and T cell exhaustion. Despite both being EBV-driven and CNS-restricted, they display distinct molecular and immunological programs, suggesting context specific EBV mechanisms. These findings challenge existing classification systems and support CNS-specific molecular frameworks to guide therapeutic interventions including BTK inhibition for NOTCH-mutated lymphoma. They lay the foundation for precision approaches in EBV⁺ PCNSL, including immune restoration, antigen-specific T cell therapy, and epigenetic modulation.

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.

Abstract Introduction: Achieving rapid and deep hematological responses is essential for improving organ function and reducing early mortality in AL amyloidosis. While daratumumab has transformed the management of newly diagnosed disease, many daratumumab-treated patients will not clear amyloidogenic serum free light chains or will relapse. Chimeric antigen receptor (CAR) T-cell therapy is a highly active modality in multiple myeloma, capable of inducing deep and durable remissions. Whether this strategy can be safely and effectively adopted in AL amyloidosis remains an important unanswered question. Methods: This multicenter retrospective study involved 8 US academic medical centers within the US Multiple Myeloma Immunotherapy Consortium. We included patients with systemic AL amyloidosis who received BCMA-targeted CAR T therapy to treat AL amyloidosis with concurrent myeloma to investigate the safety, and efficacy of this approach. Results: Between September 2021 and March 2025, we identified 33 patients with AL amyloidosis treated with CAR T (n=9 ide-cel, n=24 cilta-cel). The median age was 69-years (IQR: 60, 72); 48% were female. Most patients were kappa light-chain isotype (61%, n=20), 4 patients (13%) had the t(11;14) translocation. Although baseline plasma cell burden was unknown in 2 cases, all patients had a concurrent diagnosis of myeloma, and 88% of patients had ≥20% bone marrow plasma cells (BPMC) at diagnosis. The median number of prior lines was 6 (range: 3-13), all patients had previous anti-CD38 exposure, and 27 patients (82%) had received previous autologous stem cell transplant. Regarding organ involvement, 11 patients (33%) had cardiac, 9 (27%) renal, 8 (24%) gastrointestinal, 3 (9%) peripheral nerve and 1 (3%) autonomic nerve involvement. Five patients had AL amyloid deposition without known organ involvement. Prior to CAR T, cardiac staging was unavailable or unknown in 19 cases. Of the remaining 14 cases, 6 cases were European Modification of Mayo 2004 stage 3A with no stage 3B cases. Prior to lymphodepletion the median BMPC was 6% (IQR: 1, 20). The overall rate of cytokine release syndrome (CRS) was 64% (Grade 1, G1: n=15, Grade 2, G2: n=4, Grade 3, G3: n=2), and immune cell associated neurological syndrome (ICANS) was 15% (G1: n=3, G3: n=2). The rate of CRS was 56% for ide-cel (G1: 33%, G2: 22%) and 67% for cilta-cel (G1: 50%, G2: 8%, G3: 8%). The median time to CRS onset was 1 day for ide-cel and 6 days for cilta-cel. The median duration of CRS was 1 day for ide-cel and 2 days for cilta-cel. The rate of ICANS was 11% for ide-cel (G1: n=1), and 16% for cilta-cel (G1: n=2, G3: n=2). There were no cases of non-ICANS neurotoxicity. Ten patients (30%) experienced infections (≥Grade 3 = 9%). The overall response rate (ORR) by AL amyloidosis response criteria (Palladini et al. 2012) was 91%, including n=5 very good partial responses (VGPRs) and n=24 complete responses (CRs). The ORR for ide-cel was 78% (n=6 CRs, n=1 VGPR), and for cilta-cel was 96% (n=18 CRs, n=4 VGPRs). Among responders, the median time to VGPR or better was 30 days (IQR: 29, 32). One cilta-cel recipient died of infection on day 17 prior to disease reassessment. At a median follow up of 17.8 months, the 12 and 18-month overall survival rates were 88% (95%CI: 76%-100%) and 83% (95%CI: 68%-100%), respectively. There were 5 deaths; 3 were related to underlying disease, 1 related to infection, and 1 unrelated. Seven patients were eligible for cardiac response assessment (NTproBNP>650 OR BNP>150) at the time of CAR T, and of those, three obtained a cardiac response (2 Cardiac PR, 1 Cardiac VGPR). Three patients were eligible for renal response assessment (>1g proteinuria/day) at the time of CAR T; of those, two obtained a renal PR. Conclusion: We demonstrate that commercial BCMA-targeted CAR T-cell therapy induces deep and rapid hematological responses in a cohort of heavily pretreated patients with AL amyloidosis. Although all patients exhibited overlapping features with concurrent multiple myeloma (≥10% plasma cells at diagnosis), CAR T-cell therapy was feasible to administer, with modest rates of CRS and only isolated cases of severe CRS or ICANS. Nearly all patients achieved a deep hematological response, which appeared to translate into meaningful organ improvement among those who were evaluable.

Abstract Introduction Cila-cel is associated with a 10-15% risk of delayed neurotoxicity (DNT) with rates of cranial nerve palsies (IEC-NP) and parkinsonism (IEC-PKS) seen at a rate of 10% and 1-4% respectively and can occur as early as 3-4 weeks after infusion. We and others have shown that high post-infusion peak absolute lymphocyte count (ALCpeak) of >3x10^9/L is associated with an increased risk of delayed neurotoxicity (Lim et al., ASCO 2025) whilst the risk was negligible (~1%) when ALCpeak fell below that threshold. Since December 2024, we implemented prophylactic administration of dexamethasone (PPX DEX) when ALC was >3x10^9/L (defined as high ALCpeak). Outcome of these patients are described here. Methods Analysis of clinical outcome included 230 pts treated between Feb 2022 and Nov 2024 as a historical cohort and 102 patients treated between Dec 2024 and May 2025 after the introduction of dexamethasone prophylaxis using an oral dose of 10mg twice a day for at least three days in the high ALCpeak cohort. Results No significant differences were seen between the new and historical cohort in pre-lymphodepletion disease burden (bone marrow plasma cell %, involved light chain or M-spike level), and rates of all/high-grade CRS or ICANS, IEC-HS and rates of tocilizumub use. Median follow-up in the new cohort of 102 pts was 3.6 months (95% CI 3.3-4.2). Eleven (10.8%) developed DNT [3 (2.9%) with IEC-PKS, 8 (7.8%) with IEC-NP]. High ALCpeak of >3x10^9/L was observed in 51 (50%) pts. Among pts with high ALCpeak, DNT was observed in 10 (20%) pts [3 (5.9%) with IEC-PKS, 7 (13.7%) with IEC-NP] whereas among 51 pts with ALCpeak <3x10^9/L, DNT was observed in 1 (2%) pt [1 (2%) with IEC-NP]. In the high ALCpeak cohort, 38 (75%) received DEX [6 (12%) for toxicity management, 32 (63%) PPX DEX]. Of the 38 pts treated with DEX, DNT was observed in 6 (16%) pts (2 (5.3%) IEC-PKS, 4 (10.5%) IEC-CNP). We next compared DNT rates between this new cohort of high ALCpeak pts receiving DEX (n=38) against the historical cohort with high ALCpeak (n=98). Estimated 90-day DNT by Kaplan-Meier method was (19.2% vs 20.5%; p=0.53): IEC-PKS (5.8% vs 7.2%; p=0.60) and IEC-NP (11.7% vs 13.3%; p=0.58). In patients with high ALCpeak, the use of DEX did not appear to significantly reduce the risk of DNT compared to historical controls (HR 0.76, 0.33-1.78), IEC-PKS (HR 0.67, 0.14-3.10) or IEC-NP (0.73, 0.24-2.23). We next compared ALC expansion over the first month post CAR-T infusion (area under the curve, AUC). Among the new cohort of 102 patients, no difference was seen in the AUC of pts who received DEX but did not develop DNT vs those who developed DNT (31.0 vs 57.9, p=0.28); No difference in AUC was seen in the new high ALCpeak cohort receiving DEX vs the historical cohort with high ALCpeak (36.0 vs 43.8, p=0.15) Of the eight cases of IEC-NP, 4 received PPX DEX. No noticeable differences were observed in the severity of presentation, laterality of cranial nerve involvement and rates of multiple cranial nerve involvement between these 4 cases who received PPX DEX and the 16 cases from the historical cohort. At the time of database freeze, 3 of the 4 cases had resolved and 1 was improving. Median time to complete symptom resolution was 38 days vs 69 days in the historical cohort. Of the three cases of IEC-PKS, 2 received PPX DEX. Median time to symptom onset for IEC-PKS was 46 days (vs. 24 days in historical cohort). Both cases had severe symptoms non-responsive to first line high-dose methylprednisolone, second line intrathecal chemotherapy and third line high-dose cyclophosphamide. Both pts subsequently died from sepsis 28 and 67 days post-cyclophosphamide. Conclusion While ALCpeak >3x10^9/L predicts risk of DNT in pts treated with cilta-cel, the use of PPX DEX does not appear to significantly reduce ALC expansion and does not appear to significantly reduce the risk of DNT, IEC-PKS or IEC-NP. Other strategies to reduce ALC or alter T cell functions may need to be considered.