Citations

e23011 Background: Eligibility criteria for clinical trials are crucial for maintaining safety and study integrity. However, they often exclude patients due to medical conditions that are not relevant, leading to gaps in understanding the real-world effectiveness of treatments. Addressing potentially modifiable exclusions (PMEs) could enhance accessibility and participation in trials without compromising safety, particularly given the low rates of enrollment. Methods: We retrospectively analyzed ‘screen-failed’ patients (those who were excluded after providing consent because they did not meet the eligibility criteria or other protocol requirements) with biliary tract (BTC) or pancreatic cancer (PDAC) between August 2019 and November 2024. Screening logs and electronic health records provided clinical data. PMEs were identified and validated by two independent medical oncologists. Results: Of 585 screen-failed patients from 18 trials, 76 were excluded due to incomplete data. Among the 509 patients analyzed (367-PDAC, 142-BTC), the leading causes of screen failure were declined participation (99, 19%), comorbidities (59, 12%), suboptimal organ function (56, 11%), absence of biomarker (49, 10%), and insufficient biospecimens (36, 7%). Among patients declining participation, reasons included preference for standard care (23%), travel (22%), competing trials (5%), adverse event concerns (4%), financial issues (3%), and unknown reasons (43%). Of the 509 patients deemed ineligible for study entry at screening, we identified 69 patients (13.6%) with PMEs, primarily related to borderline laboratory abnormalities: liver function (16, 23%), kidney function (14, 20%), platelet count (8, 12%), hemoglobin (5, 7%), and white blood cell count (4, 6%). Other PMEs included previous or concurrent malignancies (6, 9%) and viral hepatitis (3, 4%). PMEs were evenly distributed across trials. Notably, all screen-failed patients proceeded to receive standard therapy. Conclusions: This analysis underscores the potential for rigid eligibility criteria to exclude stable patients who might benefit from investigational treatments. Easing specific criteria, particularly those related to laboratory abnormalities, could broaden trial accessibility. Furthermore, examining the reasons for declined participation and addressing PMEs could help develop strategies to enhance trial enrollment.

7522 Background: Movement and neurocognitive treatment emergent adverse events (MNTs), cranial nerve palsies (CNPs) and immune-effector cell enterocolitis (IEC-EC) are late onset toxicities associated with cilta-cel and are associated with significant morbidity and mortality. We aimed to identify predisposing risk factors to allow for formulating risk-reduction strategies. Methods: Retrospective study of MM pts who received FDA approved cilta-cel at Mayo Clinic between Feb 2022-Dec 2024. Interrogated factors included demographics, disease and treatment characteristics, and selected lab values at different time points. In odds ratio (OR) analyses, pts were divided by toxicity type (1) No delayed toxicity (2) MNT (3) IEC-EC without MNT (4) isolated CNP. Differences between pts in the MNT, IEC-EC and CNP groups were compared separately in a pairwise manner vs. those with no delayed toxicity. Results: Of 235 pts, 26 (11%) had delayed toxicity [MNT = 8 (3%), IEC-EC = 9 (4%), CNP = 14 (6%)]; 3 pts had both MNT/IEC-EC and 2 had both CNP/IEC-EC. Median onset from CAR-T infusion for MNT, IEC-EC and CNP was 19 (range 8-96), 106 (35-169) and 21 (7-43) days respectively. Of 164 evaluable pts, those who had ICANS had increased odds for any delayed toxicity (OR 4.7; 95% CI 1.6-13.8). Pts who had ICANS (OR 7.7; 1.6-36.9), HLH/MAS (OR 6.2; 1.1-6.7) and Ferritin >400mcg/L at time of lymphodepletion (OR 6.3; 1.5-32) had increased odds for MNTs. Pts who received alkylator-based bridging therapy had increased odds (OR 6.1; 1.1-35) for IEC-EC. Analysis of serial post-CAR infusion lab values showed that peak ALC was the most significant variable with differences between groups shown in table. Median time to peak ALC was 12 days (IQR 11-13). ROC analysis determined peak ALC >3 x 10 9 /L as a meaningful cut point. Pts with peak ALC >3.0 x 10 9 /L had increased odds of developing any delayed toxicity (OR 9.3; 3.5-29.3), MNT and CNP (table). Absolute risk of any delayed toxicity was 33% in pts with peak ALC >3 x 10 9 /L vs 5% without. At this threshold, number needed to treat was 3.6. Conclusions: Real-world data shows that cilta-cel associated delayed toxicity is seen in ~10% of patients, with specific toxicity rates between 4-8%. Factors associated with these toxicities predominantly occur in the post CAR-T infusion period. Given that ALC expansion in the first 2 weeks correlate with CAR-T expansion, peak ALC is potentially predictive of toxicity and 3 x 10 9 /L may be an interventional threshold for primary prophylaxis. Peak ALC by toxicity groups. No ToxN=138 MNTN=8 CNPN=12 IEC-ECN=6 p value Peak ALC (10 9 /L), median (IQR) 1.8 (1.0-4.1) 6.2 (4.8-14.4) 4.3 (3.2-6.7) 3.6 (1.9-5.2) <0.001 1 ALC >3 x 10 9 /L, n (%) 43 (31%) 7 (88%) 10 (83%) 4 (67%) <0.001 2 Odd Ratios vs no Tox 3 , 95% CI 15.5 (2.6-293.7) 11.0 (2.8-73.9) 4.4 (0.8-25.0) 1 Wilcoxon/Kruskal-Wallis Tests, 2 Chi square test, 3 Logistic regression analysis.

e19008 Background: Cytokine release syndrome (CRS) is typically reversible in CAR-T therapy, while hyperinflammatory syndromes like macrophage activation-like syndrome (MAS-L) and high-grade immune effector cell-associated hemophagocytic syndrome (IEC-HS) are associated with significant morbidity and mortality. Early interventions are critical for improving outcomes. We aim to analyze clinical cytokine assays and cellular phenotypes early in hyperinflammatory syndromes to identify profiles for severe cases to inform management decisions. Methods: This study included 113 CAR-T patients (pt) (September 2019-March 2024) with cytokine profiles (CP) performed at the second tocilizumab dose or with suspected hyperinflammatory states (CP1), followed by assessments at 24 hours (CP24) and 48 hours (CP48). 52 pts consented to blood (PB) and bone marrow (BM) cell immune phenotyping at pre-treatment (pre-LD) and day 1 for PB. Results: Among the 113 pts, CRS pts (N=74), when compared to MAS-L(N=19) & IEC-HS (N=20) at CP1, had lower levels of TNF (median in pg/mL; 31, 62.9, 47.7) , IL-18 (794, 1353, 2011), and MCP-1 (689, 2722, 2485.5). While MAS-L and IEC-HS had similar CP1 profiles, CP24 and CP48 differed between them: TNF & MCP-1 levels decreased in MAS-L but remained elevated or increased in IEC-HS. IL-18 was stable in MAS-L but increased steadily daily in IEC-HS. Infections were more frequent in IEC-HS (CRS: 43%; MAS-L: 58%; IEC-HS: 85%; p=0.002). Notably, patients who died with persistent E. faecium bacteremia had higher IL-18 in CP48. In the 52 pts with cell phenotypes available by flow, 33 had CRS, 18 MAS-L and 8 IEC-HS. The correlation between cell phenotypes and cytokine levels showed that elevated TNF at CP1 correlated with increased non-classical monocytes in pre-LD BM and higher NK and NK-T cells in pre-LD PB. Similarly, elevated IL-18 CP48 levels correlated with increased CD8 T-cells, NK-T cells, and intermediate monocytes in pre-LD PB, as well as increased NK cells at both pre-LD and day 1 (Table). Conclusions: We report distinct cytokine profiles in IEC-HS early in the inflammatory course post-CAR-T therapy. These elevated cytokines correlate with specific immune cell subsets, including BM-resident monocytes, intermediate monocytes with heightened cytokine trafficking and inflammatory capacity. This study demonstrates the feasibility for identifying potential biomarkers for early risk stratification and targeted interventions. Cytokine Sample source Immune cells R P value TNF CP1 BM pre-LD Non-classical monocytes (CD14loCD16+) 0.38 0.025 PB pre-LD Monocytes (All) 0.47 0.022 NK cells (CD56+CD16+) 0.34 0.024 NK-T cells (CD3+CD56+CD16-) 0.29 0.04 IL-18 CP48 PB pre-LD CD8+ T-cells 0.59 0.0093 NK-T cells (CD3+CD56+CD16-) 0.53 0.023 Intermediate monocytes (CD14+CD16+) 0.58 0.012 PB pre-LD NK cells (CD56+CD16+) 0.56 0.49 0.015 0.024

Objectives/Goals: The operation of a clinical trials unit involves multifaceted tasks and stakeholders. A competent information system is critical to daily operations while ensuring smooth conduct of clinical research. We share 15 years of experience in the design and implementation of such a system at Mayo Clinic to inform other institutions with similar interests. Methods/Study Population: The Informatics team collaborated closely with nurse leaders and elicited input from additional stakeholders including nurse unit coordinators, lab managers, schedulers, investigators, study coordinators, and regulatory specialists throughout the phases of system design, development and continuous enhancements, and expansion. The stakeholders offered insights on the corresponding requirements throughout the study life cycle, from engaging with the study sponsor, operational review for protocol execution, development of study budgets, human subject protection and risk mitigation, data management and integration, to outcome monitoring, and regulatory reporting. The activities were then translated into functional components and implemented as a seamless and effective solution. Results/Anticipated Results: Patient safety, scientific rigor, operation automation, efficiency, and regulatory requirements were all considered in developing an integrated system, or the clinical research trials unit (CRTU) Tools. Our institution has leveraged the system for essential tasks from the study start-up, visit scheduling and execution, specimen collection and tracking, to individual protocol metrics and billing. We adopted a measure-as-we-go methodology so that data such as visit census, resource usage, and protocol deviation are tracked and collected during routine use of the system. Specifically, an issues/concerns/exceptions (ICE) tool is used for quality control and patient safety. Moreover, data quality greatly benefits from a task dictionary, standardizing the study activities that can be ordered and executed. Discussion/Significance of Impact: The implementation of a well-rounded clinical trials unit information system not only improves the operation efficiency and team productivity but also ensures scientific rigor and contributes to patient safety. We believe the experience can be informative to other institutions. More details will be shared in the poster.

ABSTRACTPatients with vascular anomalies (VAs) require expert multidisciplinary care. No prior studies have characterized the sociodemographic characteristics across multiple VA centers. We collected data on 5783 patients receiving care at 20 VA centers between July 1, 2020 through December 31, 2022. Male patients were underrepresented compared to the state‐level census data at 17/20 centers. Black and Asian patients were underrepresented at 14/20 and 12/20 centers, respectively. The median distance to the hospital was 48 miles, and median age was 12.0 years. These data suggest that race, sex, age, and distance from the hospital could impede the ability to access expert VA care.

AbstractBackgroundPharmacoepidemiologic studies assessing drug effectiveness for Alzheimer’s disease and related dementias (ADRD) are increasingly popular given the critical need for effective therapies for ADRD. To meet the urgent need for robust dementia ascertainment from real‐world data, we aimed to develop a novel algorithm for identifying incident and prevalent dementia in claims.MethodWe developed algorithm candidates by different timing/frequency of dementia diagnosis/treatment to identify dementia from inpatient/outpatient/prescription claims for 6,515 and 3,997 participants from Visits 5 (2011‐2013; mean age 75.8 (SD 5.3) years) and 6 (2016‐2017; mean age 79.8 (SD 4.8) years) of the ARIC cohort with ≥ 1‐year continuous Medicare Part A & B enrollment prior to each visit. We evaluated algorithm performance (sensitivity/specificity/positive predictive value (PPV)/negative predictive value (NPV)) against the gold standard of the ARIC dementia classification based on an extensive battery of neurocognitive tests administered at each visit. We compared performance of the new algorithm with that of three existing algorithms (Jain, Bynum, Lee) and their relaxed forms (4‐year window, dementia diagnosis plus a depression diagnosis or dementia evaluation procedure, ignoring code position) to identify incident (n = 90 at V6) and prevalent dementia (n = 190 at V5; n = 160 at V6).ResultThe newly developed primary algorithm requires presence of a dementia diagnosis code followed by another diagnosis code within 1 year (under condition that the following non‐specific ICD‐9 diagnostic codes, 290.40, 290.41, 290.11, 290.3, should appear no more than once), or a subsequent dementia treatment prescription within 90 days (requiring Medicare Part D enrollment ≥ 6 months). The PPV of the new algorithm in the identification of incident dementia was PPV of 72.7%, with a specificity of 99.1%, outperforming existing algorithms. Its sensitivity of 38.7% and NPV of 96.2% were comparable to those achieved by existing algorithms. Sensitivity analysis restricting to ICD‐10 diagnostic codes increased the PPV and attenuated its sensitivity by 6%. Similar comparative performance was observed in the identification of prevalent dementia.ConclusionA novel algorithm for identifying dementia from Medicare claims, developed using linked ARIC‐Medicare data, outperforms previous algorithms and stands as a valuable tool in the assessment of ADRD drugs from real‐world data.

Background White matter hyperintensities (WMH) and their progression are associated with risk of dementia and stroke, so are an important target for clinical trials. The cost of broad magnetic resonance imaging (MRI) screening to identify eligible individuals, however, limits the feasibility of designing clinical trials targeting WMH. A low‐cost retinal or clinical screening measure before MRI could reduce recruitment costs versus an MRI‐only screening design in a hypothetical clinical trial. Methods and Results Data from the Atherosclerosis Risk in Communities study with valid retinal and WMH measurements ( N =1311) were used. To identify a population at greater likelihood of significant WMH on MRI and thus reduce the number of screening MRIs required, we evaluated 3 theoretical prescreening measures: (1) retinal, (2) clinical, (3) combined clinical‐retinal. Given a target sample for clinical trials ( N =646), we calculated screening sample sizes based on the proportion within the population having an elevated score for each prescreening measure (separately) multiplied by the proportion of significant WMH among those with that prescreening feature. Recruitment costs were calculated using estimated retinal and MRI cost estimates. Compared with the estimated cost of MRI‐only screening (>$4.24 million, requiring MRI on 6526 participants), prescreening for a high clinical score resulted in total cost of $2.47 million, with an initial screening group of 52 778 participants, with MRI in 3801. A high clinical‐retinal score cutoff resulted in costs of $2.9 million while requiring 13 572 participants, with 3801 completing MRI. Conclusions A 2‐stage design with low‐cost prescreening measures is a promising approach, resulting in reduced theoretical recruitment costs compared with an MRI‐only design.

AbstractIntroductionAcute myeloid leukemia (AML) remains one of the deadliest hematopoietic malignancies. A better understanding of the molecular biology governing AML may lead to improved risk stratification and facilitate the development of novel therapies. Proteins are responsible for much of the biology of cells. Several studies have examined the global proteome in bulk mononuclear cells (MNCs) from AML specimens, which are comprised a heterogenous population of cells at various stages of differentiation.MethodsGiven the potential impact of the nonleukemic cells on protein expression profiles, we applied an integrative proteogenomic approach utilizing next‐generation sequencing and mass spectrometry‐based proteomics to identify novel protein biomarkers in unsorted MNCs and viable leukemic blasts (VLBs) isolated from blood and bone marrow specimens obtained at the time of AML diagnosis.ResultsWe identified significant differences in protein expression between VLBs and MNCs. Subsequent studies (N = 27) focused on proteomic profiling of VLBs that identified novel candidate biomarkers associated with mutational genotypes and clinical outcome, some of which were recapitulated in an independent cohort of patients. Using mass spectrometry, we also detected mutated protein products, some of which were predicted via in silico analyses to be potential neoantigens amenable to adoptive immunotherapy. As previously described, analyses comparing transcript and protein expression showed an overall modest correlation between mRNA and protein dataset, but enriching for genes associated with mutations significantly improved the protein–RNA correlation.ConclusionTogether, the results provide insight into the biology of VLBs and demonstrate the gains derived from examining the proteome in addition to genome and transcriptome.

Importance In 2022, the US House of Representatives passed a bipartisan resolution (House of Representatives Resolution 1118 at the 117th Congress [2021-2022]) calling for meaningful nutrition education for medical trainees. This was prompted by increasing health care spending attributed to the growing prevalence of nutrition-related diseases and the substantial federal funding via Medicare that supports graduate medical education. In March 2023, medical education professional organizations agreed to identify nutrition competencies for medical education. Objective To recommend nutrition competencies for inclusion in medical education to improve patient and population health. Evidence Review The research team conducted a rapid literature review to identify existing nutrition-related competencies published between July 2013 and July 2023. Additional competencies were identified from learning objectives in selected nutrition, culinary medicine, and teaching kitchen curricula; dietetic core competencies; and research team–generated de novo competencies. An expert panel of 22 nutrition subject matter experts and 15 residency program directors participated in a modified Delphi process and completed 4 rounds of voting to reach consensus on recommended nutrition competencies, the level of medical education at which they should be included, and recommendations for monitoring implementation and evaluation of these competencies. Findings A total of 15 articles met inclusion criteria for competency extraction and yielded 187 competencies. Through review of gray literature and other sources, researchers identified 167 additional competencies for a total of 354 competencies. These competencies were compiled and refined prior to voting. After 4 rounds of voting, 36 competencies were identified for recommendation: 30 at both undergraduate and graduate levels, 2 at the undergraduate level only, and 4 at the graduate level only. Competencies fell into the following nutrition-related themes: foundational nutrition knowledge, assessment and diagnosis, communication skills, public health, collaborative support and treatment for specific conditions, and indications for referral. A total of 36 panelists (97%) recommended nutrition competencies be assessed as part of licensing and board certification examinations. Conclusions and Relevance These competencies represent a US-based effort to use a modified Delphi process to establish consensus on nutrition competencies for medical students and physician trainees. These competencies will require an iterative process of institutional prioritization, refinement, and inclusion in current and future educational curricula as well as licensure and certification examinations.