Citations

Abstract Background Inflammatory bowel disease (IBD) can lead to a hypercoagulable state, particularly at initial diagnosis. Consequently, venous thromboembolism (VTE) represents a serious complication associated with IBD. For children, the risk of VTE near the time of IBD diagnosis has not yet been quantified, and guidance for VTE prophylaxis remains unclear. Methods This multisite matched case-control study examined pediatric patients with a new diagnosis of IBD from 2019-2024. Cases were those who developed VTE ≤30 days prior or ≤90 days post IBD diagnosis. Controls were newly diagnosed IBD patients without VTE. Each case was matched to 2-6 controls based on IBD subtype and age at IBD diagnosis. Demographics, laboratory values, prothrombotic risk factors and treatments were compared between matched cases and controls using conditional logistic regression stratified, by case sets. Results Study subjects included 15 cases and 52 controls, resulting in 70 matched pairs. Factors associated with early VTE included lower hemoglobin (P = .003), lower albumin (P = .002), corticosteroids use (P = .01), central line (P = .002), and any surgery ≤90 days post IBD diagnosis (P = .001). No association with VTE was detected for platelets, C-reactive protein, fecal calprotectin, family history of IBD or body mass index. Conclusions Albumin, hemoglobin, steroid use, central line, and any surgery ≤90 days post IBD diagnosis were associated with early VTE. These risk factors may be used in a future prediction model to stratify newly diagnosed pediatric IBD patients by their risk for early VTE development.

Abstract Introduction: There is growing focus on community-engaged research (CEnR) in the clinical and translational sciences, supportive policies, environments, and processes within academic medical centers. The purpose of this evaluation was to gather academic and community member perspectives on key actionable strategies for supporting CEnR in an academic medical center. Materials and Methods: We used a sequential mixed method design by first conducting qualitative in-depth interviews with academic leaders, investigators, and staff (total, n = 54) and focus group discussions with community members ( n = 33). Themes from these qualitative data informed the adaptation of an institutional survey that gathered perspectives from a broader group of academic and community members affiliated with the institution ( n = 85). Both qualitative and quantitative data were integrated to inform actionable strategies. Results: Survey findings revealed that the institution was perceived as committed to health equity and CEnR, but institutional respondents expressed more concerns than community members about instrumental support of the work. Interviews and focus groups highlighted the opportunity to better align research efforts with community needs through more robust CEnR infrastructure and through interface with the clinical practice to promote patient access. Academic and community members emphasized the need for authentic, sustained engagement beyond federal mandates, including financial investment, capacity-building, and fostering trust. Leaders acknowledged structural challenges, siloed efforts, and the necessity for stronger coordination to increase integration of community engagement into the institutional mission. Conclusion: Findings suggest that aligning academic leaders, researchers, staff perspectives, and community members is essential to support and promote CEnR at an institutional level.

7532 Background: BsAbs are highly effective, off-the-shelf T-cell engagers recently approved for relapsed/refractory multiple myeloma (MM) but remain underutilized in real-world settings. In partnership with the Florida Society of Clinical Oncology (FLASCO), a statewide initiative was launched to expand BsAb access through peer-led regional discussions focused on operational barriers, care transitions, and therapy management strategies. This study assessed the real-world impact of these interventions on BsAb utilization in FL. Methods: Multidisciplinary discussion forums were held in 4 FL metropolitan areas (Jan-Apr 2024). We conducted single and controlled interrupted time series (ITS) analyses using IQVIA eLAAD claims data (Apr 2023 - Sep 2025) including adult patients with a diagnosis of MM, evidence of claim activity, and provider state information. Fifth line or later (5L+) status was estimated as 3.3% of MM prevalence (Nikolaou et al.) BsAb utilization (% of MM 5L+ patients receiving a BsAb) was evaluated using segmented regression to estimate pre- and post-intervention trends, excluding the intervention period. We reported BsAb utilization by comparing FL with all other states, between community versus academic settings, and assessing the number of sites administering BsAb. Results: Before the intervention, BsAb utilization among MM 5L+ patients in FL rose from 8.2% (Apr 2023) to 11.2% (Dec 2023) (0.3 pp/mo; p=0.23), compared with a rise from 6.7% to 16.3% (1.3 pp/mo; p<0.0001) across all other states over the same time period. Post-intervention, BsAb utilization in FL increased from 22.8% (May 2024) to 35.9% (Sep 2025), reflecting a 7.0% immediate increase and 0.8 pp/mo sustained growth, exceeding the post-intervention trend observed across all other states (23.5% to 30.3%; 0.5 pp/mo). Overall, although pre-intervention BsAb utilization in FL was lower than all other states, FL demonstrated a 1.2 pp/month higher post-intervention utilization trend (p<0.001; Table). Post-intervention, FL community sites showed a 0.13 pp/mo higher BsAb utilization trend than academic sites, and the number of community sites administrating BsAb increased from 5 to 9, with no change among academic sites. Conclusions: This study suggests that the FLASCO-led, collaborative model increased BsAb utilization in FL community oncology sites and offers a framework for broader community adoption across other states. Parameter estimates from ITS model(s). FL (%) p-value Other US States (%) p-value Difference CITS:FL - Other US States (%) p-value Intercept (Apr 2023) 8.6 <.0001 7.7 <.0001 0.9 0.52 Monthly change pre-intervention 0.3 0.23 1.3 <.0001 -0.9 0.002 (Apr - Dec 2023) Immediate change post-intervention 7 0.01 0.2 0.87 6.8 0.01 (May 2024) Monthly change post-intervention 0.8 <.0001 0.5 <.0001 1.2 0.0003 (May 2024 – Sep 2025)

11059 Background: Payments from the drug industry to oncologists are common and influence physicians’ prescribing decisions. However, whether payments affect the likelihood that patients receive optimal cancer treatment has not been assessed. Methods: This was a population-based cohort study. We used fee-for-service Medicare claims to identify patients with incident cancer diagnosis (new cancer diagnosis code after >= 1 year with no cancer diagnosis codes) from 2014-2020. We used National Comprehensive Cancer Network (NCCN) Guidelines to identify treatment scenarios (e.g., metastatic melanoma, stage III colon adjuvant therapy) with variation in the clinical benefit among recommended treatment options. The patient cohort corresponding to each scenario was identified using claims. We used NCCN Guidelines to identify the “optimal” treatment for each scenario (defined as the designated “preferred” treatment, with NCCN Evidence Blocks scores used for tiebreaks) at each time point across the study period. The primary outcome was whether a patient received the treatment that was, as of their diagnosis date, the optimal treatment for their cancer (vs. any non-optimal treatment). The primary exposure[s] were whether a patient’s medical oncologist received personal (“general”) payments (source: linked Open Payments data) related to 1) optimal treatment or 2) any non-optimal treatment, during the year prior to the patient’s cancer diagnosis. We fit Poisson-family generalized estimating equations, with physician-level clustering and adjustment for scenario, year, and patient characteristics, to estimate the relative risk (RR) of optimal treatment. Results: There were 14 clinical scenarios comprising 15,835 patients. There were 3,429 (21.7%) patients whose oncologist received payment for the optimal treatment, 4,891 (30.9%) for non-optimal payments, and 1,993 (12.6%) to both payment types. Oncologist receipt of payment for optimal treatment was associated with a greater likelihood (RR=1.07, 95%CI:1.01-1.13), and payment for non-optimal treatment was associated with lower likelihood (RR= 0.94, 95%CI:0.89-0.98) of patients receiving optimal treatment. Associations became stronger as payment dollar value increased; for optimal payments ≥$10,000, RR=1.26 (95%CI:1.02-1.57), and for non-optimal payments ≥$10,000, RR=0.70 (95%CI: 0.49-1.00). An estimated 41.6% of unexposed patients received optimal treatment; versus 52.6%, 29.3%, and 33.8% among patients exposed to ≥$10,000 of payments for optimal treatment only, ≥$10,000 non-optimal payments only, and ≥$10,000 of both payment types, respectively. Conclusions: Industry payments related to the optimal cancer treatment were associated with increased use of the optimal treatment. However, payments related to non-optimal treatments were more common and were associated with decreased use of optimal treatment.

Over the past three decades, the emergence of recombinant antibodies has positioned them as the fastest-growing class of therapeutic proteins and as well as crucial reagents for both diagnostics and specific research applications. The industrial production of most therapeutic antibodies currently relies on mammalian cell lines, primarily Chinese Hamster Ovary (CHO) cells, which remain the gold standard in biopharmaceutical manufacturing due to their exceptionally high production yields, robustness, regulatory acceptance, and consistent product quality. Nevertheless, new approaches using specifically adapted expression systems are emerging. These new host organisms enable the production of antibodies with posttranslational modifications that closely resemble those found in the human system, without the need for animal-derived source materials. For diagnostic and research purposes, a broad range of production systems has been developed. These include Gram-negative and Gram-positive bacteria, yeasts, filamentous fungi, insect cell lines, and transgenic plants. Additionally, smaller single domain antibodies and bispecific fragments that do not require glycosylation can be successfully produced in bacteria for therapeutic applications. Some of these molecules have already been approved by regulatory authorities in the European Union and the United States, and several more are currently in clinical trials. This review therefore focuses on the broad and evolving landscape of recombinant antibody production systems and their applicability across various fields.

Abstract Background The Global Bipolar Cohort (GBC) was established to identify existing bipolar disorder (BD) cohorts worldwide and foster collaborations focused on descriptive and analytic outcomes relevant to BD. A distributed analytic framework has been implemented to engage multiple sites without the need for central data pooling. This report describes the GBC endeavor and global functional impairment patterns. Cross-cohort comparisons of functional correlates are limited by heterogeneous measures and data-sharing constraints. Large, culturally diverse comparisons are needed to distinguish broadly reproducible correlates from cohort-specific effects. Participating sites completed a 28-item descriptive survey covering diagnostic methods, cognition, genetics, treatment, functioning, and follow-up strategies. We implemented a harmonized local logistic regression model of dichotomized functional outcome and shared summary statistics only. Results We identified 69 cohorts across five continents. Thirty-seven cohorts contributed functional outcome analyses from 17,130 participants. Outcome measures included clinician-rated disability scales and social indicators such as employment and marital status. The proportion classified with poor functioning ranged from 16% to 77% (mean 50%). In 32 of 37 cohorts, the overall regression model significantly explained variance in functioning. Current depressive symptoms were the most robust and reproducible correlate of poor functional outcome: they were assessed in 29 cohorts, significant in 22 (75.8%), ranked among the top three correlates in 22, and were the top-ranked correlates in 19. Associations between depressive burden and poor functioning were observed across clinician-rated disability scales and work or social indicators, and across geographically diverse cohorts. Comorbid substance use disorder and medication-related variables were associated with poorer functioning in subsets of cohorts, whereas sex, ancestry, bipolar subtype, psychosis history, and premorbid IQ showed weak or inconsistent associations. Cognitive measures, available in a minority of regression models, showed modest and non-uniform effects. Conclusions Across heterogeneous international cohorts, current depressive symptom burden emerged as the most consistent correlate of poor functioning in bipolar disorder. These findings replicate earlier multisite work at a larger scale, show that protocol-based distributed analyses can identify reproducible clinical signals without sharing individual-level data, and support prioritizing detection and treatment of depressive symptoms when aiming to improve real-world functioning. Future work should expand longitudinal harmonization and representation of under-studied populations.

Background Photophobia is experienced by most individuals with migraine, and it is frequently the most bothersome symptom other than headache. Light is not perceived uniformly; spectral composition and intensity influence discomfort and can exacerbate symptoms. While monochromatic green light shows therapeutic potential, it appears visually unnatural and is impractical for daily use. This study aimed to determine whether spectrally tailored white light, more visually acceptable in everyday environments, reduces light sensitivity among those with migraine. Methods Twenty adults (18–44 years) with episodic migraine completed two research sessions: one during an acute migraine attack and one between migraine attacks. Participants were exposed to four spectrally distinct white light conditions (red-, green-, cyan-, and blue-enriched) in a randomized order delivered at ten intensity levels (50–590 lux). After each exposure, visual discomfort was rated on a 0–10 scale. Pupil size was measured using a pupillometer. Repeated-measures ANOVAs examined the effects of light spectrum, intensity, and migraine state on visual discomfort and pupil response. Results Migraine attack status significantly increased visual discomfort ( F (1,19) = 25.84, p < .001, η 2 = .576). White light spectrum ( F (3,57) = 12.47, p < .001, η 2 = .396) and light intensity ( F (9171) = 124.30, p < .001, η 2 = .867) were associated with intensity of visual discomfort. Post-hoc analyses indicated that visual discomfort increased with increasing light intensity, especially at higher light intensities. Among all tested spectra, green-enriched white light resulted in the least visual discomfort; blue-, red-, and cyan-enriched white light produced significantly higher discomfort (all p < .001). Pupil size varied by spectrum ( F (3,57) = 14.13, p < .001, η 2 = .426), with green-enriched white light producing the largest pupil size. Conclusion Spectral composition, light intensity, and migraine state jointly influence both subjective and physiological responses to light. Across lighting spectra, lower light intensity was consistently associated with reduced visual discomfort, indicating greater visual comfort at lower intensities. These results identify green-enriched white light at lower intensities as a visually acceptable, migraine-conscious lighting option with potential for real-world application.