Citations

e16335 Background: Splanchnic vein thrombosis (SVT) is a rare but serious complication in gastrointestinal (GI) cancer patients. This study investigated its features and outcomes in U.S. hospitalizations. Methods: Hospitalizations (≥18 years old) with a GI malignancy (ICD-10-CM C15–C26) and portal vein thrombosis (PVT) (I81), hepatic vein thrombosis (HVT) (I82.0), or mesenteric/splenic vein thrombosis (MSVT) (I82.890 + K55) in any of the 40 diagnosis fields were found in 2022 National Inpatient Sample. Exclusions: non-GI cancers (C00-C14, C27-C96), thrombophilia (D68.5, D68.6, D45, D47.1, D59.5), or cirrhosis (K74, K70.3). Demographics and outcomes (in-hospital mortality, length of stay [LOS], and total hospital charges [TOTCHG]) were compared between SVT and non-SVT groups using unweighted descriptive statistics (medians, IQRs), χ², and Mann-Whitney U tests. Multivariable regression of mortality, LOS, and TOTCHG were adjusted for age, sex, race, income quartile, insurance type, hospital region and bed size, and comorbidity burden (elixsum). Stata 17.0 was used. Results: Among 51,940 GI cancer hospitalizations (mean age 68.37 ± 12.79 years; 44.46% female), 833 (1.60%) had SVT. SVT group was younger (66.60 ± 11.76 vs. 68.40 ± 12.80 years; p < 0.001). Sex distribution was similar (58.34% vs. 55.50% male; p = 0.101). Common cancers in SVT: liver (n=427; 51.26%), pancreas (n=310; 37.21%), and colorectal (n=42; 5.04%). SVT prevalence was highest in liver (7.10%), pancreatic (3.14%), gallbladder (2.65%), and biliary (2.13%) cancers. PVT was the predominant subtype (n=788; 94.60%), followed by HVT (n=21; 2.52%), MSVT (n=4; 0.48%), and multiple SVT sites (n=20; 2.40%). SVT subtype distribution was: PVT (n=788; 94.60%), HVT (n=21; 2.52%), MSVT (n=4; 0.48%), and multiple sites (n=20; 2.40%). SVT had longer median LOS (5 [3–10] vs. 4 [3–8] days; z = -6.666, p < 0.001), similar median charges ($65,053 [I33,560–130,026] vs. $66,433 [35,897–121,038]; z = -0.76, p = 0.447), and higher mortality (9.48% vs. 4.41%; χ² = 49.042, p < 0.001). In adjusted analyses, SVT had higher mortality (aOR = 2.23, 95% CI 1.74–2.85, p < 0.001), longer LOS by 1.50 days (95% CI 0.99–2.02, p < 0.001), and 14.63% higher TOTCHG (coefficient 0.136, 95% CI 0.051–0.222, p = 0.002). Conclusions: SVT affects ~1.6% of GI cancer hospitalizations, is most prevalent in liver cancer, and associated with longer stays and higher mortality, underscoring the need for proactive monitoring. Multivariable regression analyses of SVT on clinical outcomes (unweighted sample). Outcome SVT Effect 95% CI P-value Interpretation In-hospital mortality OR 2.23 1.74–2.85 <0.001 SVT doubles odds of in-hospital death Length of stay (days) +1.50 0.99–2.02 <0.001 SVT associated with ~1.5 extra hospital days Total hospital charges ($) +0.136 (log scale) 0.051–0.222 0.002 SVT increases hospital costs by ~14.63%

e16334 Background: Liver cancer remains a leading cause of cancer-related mortality in the United States. Although overall mortality has increased over the past two decades, age-specific patterns and demographic disparities are not fully characterized. Here, we analyzed U.S. liver cancer mortality trends from 1999 to 2023, with a focus on age-related, racial and ethnic, and geographic differences. Methods: Mortality data for U.S. adults aged ≥25 years from 1999 to 2023 were obtained from the CDC WONDER database (ICD-10 codes C22.0–C22.9). Age-adjusted mortality rates (AAMRs) were standardized to the 2000 U.S. population. Joinpoint regression was used to estimate annual percent change (APC) and average annual percent change (AAPC) across age groups, sex, race/ethnicity, U.S. census regions, and levels of urbanization. Results: From 1999 to 2023, overall liver cancer AAMRs increased from 6.95 to 10.1 per 100,000. Marked age-specific differences were observed. Mortality among adults aged 45–54 and 55–64 years peaked in the mid-2010s and subsequently experienced significant declines through 2023 (recent APCs < −4.5% for both groups; P < 0.001). Specifically, while the overall AAPC for the 55–64 age group was +1.89%, mortality significantly reversed after 2016 (APC, −4.59%). In contrast, mortality continued to rise among older adults, including those aged 65–74 years (AAPC, +2.26%), 75–84 years (AAPC, +1.69%), and aged ≥85 years (AAPC, +1.77%) (all P < 0.001). Differences in mortality trends were also identified across racial and ethnic groups. Sustained increases were observed among Non-Hispanic White individuals (AAPC, +1.89%; P < 0.001), while Hispanic/Latino populations experienced declines after 2013 (APC, −0.67%; P = 0.003). Non-Hispanic Black individuals demonstrated a significant decrease in mortality between 2017 and 2020 (APC, −3.82%; P = 0.03). Regionally, liver cancer mortality declined in the Northeast after 2013 (APC, −0.66%; P < 0.001), whereas no significant post-peak declines were observed in the South or West. Conclusions: U.S. liver cancer mortality trends exhibit substantial heterogeneity by age, race and ethnicity, and geographic region. The recent, sharp declines among middle-aged adults (APCs < −4.5%) likely reflect the success of large-scale viral hepatitis screenings and highly effective antiviral therapies, whereas continued increases among older adults may relate to the cumulative impact of metabolic risk factors and delayed diagnosis. Persistent racial and regional disparities highlight the need for targeted, age-specific prevention and surveillance strategies.

e16102 Background: Esophageal cancer remains a significant cause of cancer mortality in the United States. While overall trends have been reported, less is known regarding contemporary long-term patterns and specific disparities across demographic and geographic strata. We aimed to characterize esophageal cancer mortality trajectories and identify populations with divergent outcomes by age, race/ethnicity, geographic region, and urbanization status. Methods: We analyzed esophageal cancer mortality data from 1999 to 2023 using the Centers for Disease Control and Prevention (CDC) WONDER database. Age-adjusted mortality rates (AAMRs) were standardized to the 2000 U.S. standard population. Joinpoint regression analysis was utilized to estimate the annual percent change (APC) and average annual percent change (AAPC) with 95% confidence intervals (CIs). Analyses were stratified by age, sex, race/ethnicity, census region, state, and urbanization level. Results: Overall esophageal cancer mortality in the U.S. declined significantly from 1999 to 2023 (AAPC, -0.81%; 95% CI, -0.97% to -0.65%; P < 0.001). Declines were observed across most age groups, with the steepest reductions among adults aged 45-54 years (AAPC, -1.68%; 95% CI, -2.01% to -1.35%) and 55-64 years (AAPC, -1.25%; 95% CI, -1.51% to -0.99%). Marked racial and ethnic disparities were identified. Non-Hispanic (NH) Black individuals experienced the most rapid decline (AAPC, -4.07%; 95% CI, -4.42% to -3.72%). Conversely, trends among NH White individuals remained stable overall (AAPC, -0.05%; P = 0.59), characterized by an initial increase from 1999 to 2005 (APC, 1.14%; P = 0.002) followed by a modest decline from 2005 to 2023 (APC, -0.44%; P < 0.001). Regionally, the West demonstrated the largest decline (AAPC, -1.13%; 95% CI, -1.26% to -0.99%), followed by the Northeast (AAPC, -1.05%). West Virginia was the only state to exhibit a significant increase in mortality (AAPC, 1.01%; 95% CI, 0.38% to 1.64%; P = 0.003). Mortality declined significantly in metropolitan areas (AAPC, -1.09%; P < 0.001), while trends in nonmetropolitan areas remained stagnant (AAPC, 0.48%; P = 0.12). Conclusions: Despite a national decline in esophageal cancer mortality, substantial disparities persist across racial, geographic, and urbanization groups. The dramatic improvement among NH Black populations contrasts with the relative stability in NH White populations and the lack of progress in nonmetropolitan areas. The significant rise in mortality in West Virginia warrants targeted investigation. These findings underscore the critical need for population-tailored strategies to ensure equitable progress in cancer prevention and care.

e13663 Background: Artificial intelligence (AI) in oncology, including computer vision and radiomics, has expanded rapidly with substantial federal support. However, the extent to which growth in funding and publications is accompanied by growth in prospective interventional evaluation is not well quantified. We conducted an ecosystem-level analysis to compare temporal trends in federal awards, peer-reviewed publications, and interventional clinical trial registrations in AI-oncology. Methods: We performed a cross-sectional landscape analysis spanning 2015–2025 using three public data sources: (1) federally funded extramural awards indexed in NIH RePORTER (including NIH/NCI and other agencies where available); (2) interventional studies registered on ClinicalTrials.gov; and (3) PubMed-indexed publications. Records were identified using a consistent Boolean query requiring AI-related terms (“artificial intelligence,” “machine learning,” “deep learning,” “neural network,” “large language model,” “computer vision,” “natural language processing,” “radiomics”) AND oncology-related terms (“cancer,” “oncology,” “tumor,” “neoplasm,” “carcinoma,” “melanoma,” “leukemia,” “lymphoma”). Annual absolute counts were extracted (without normalization) to preserve volume differences across the ecosystem. We summarized growth over time and calculated publication-to-trial and grant-to-output ratios. Results: Between 2015 and 2025, AI-oncology federal awards totaled 11,503. PubMed-indexed AI-oncology publications increased 38-fold from 558 (2015) to 21,414 (2025), totaling 81,782. Interventional AI-oncology trial registrations increased from 2 (2015) to 84 (2025), totaling 372 across the period. Overall, the publication-to-interventional-trial ratio was 220:1; interventional trial registrations represented 0.45% of publication volume. For every federal award, approximately 7 publications were produced, but only 0.03 interventional trials were registered. Conclusions: Across 2015–2025, AI-oncology funding and publications increased dramatically, while interventional trial registrations remained comparatively sparse. This persistent publication-to-trial gap highlights a translational bottleneck and supports targeted initiatives to accelerate prospective validation, such as dedicated funding mechanisms, multi-center evaluation networks, and trial-ready implementation infrastructure, to realize clinical benefit from AI in cancer care.

e12691 Background: Breast cancer prognosis is influenced not only by tumor-specific factors but also by systemic inflammatory responses. Elevated circulating neutrophils after surgery may reflect one such systemic inflammatory response that promotes a pro-tumorigenic environment. Neutrophil extracellular traps (NETs) have been recognized as promoters of cancer activity. However, there have been no studies looking at neutrophil count alone as an independent inflammatory marker in cancer. Clinical prognostic significance of post-operative neutrophil counts remains incompletely understood. If proven significant, neutrophil count is a simple, widely available measure to predict post-operative outcomes in patients with breast cancer. Methods: Data from the Mayo Clinic Platform were retrospectively analyzed, including only breast cancer patients with normal BMI and neutrophil counts recorded within one week after breast surgery. Patients who underwent radical mastectomy were excluded. Patients were stratified into two groups based on neutrophil count: high (>7×10⁹/L) and normal (1.7–7×10⁹/L). Clinical outcomes assessed included age distribution and 5-year overall survival. Age differences were evaluated using Cohen’s D, and Kaplan-Meier survival curves and hazard ratio estimation were performed using the Mayo Clinic Platform's tool. Results: A total of 899 patients were included in the study cohort: 303 in the high neutrophil group (Cohort A) and 596 in the normal neutrophil group (Cohort B). Age distributions were comparable between groups (Cohort A mean 59.2 ± 13.1 years; Cohort B mean 59.1 ± 14.3 years; Cohen's d = 0.0079). High neutrophil counts were significantly associated with reduced 5-year survival (77.8% vs. 84.5%) and an increased risk of mortality (HR 1.63; 95% CI: 1.16–2.29; P = 0.0041). Conclusions: Recent literature supports that surgery-induced NET formation may drive metastatic progression. Findings from this retrospective analysis at Mayo Clinic suggest that elevated neutrophil counts after breast cancer surgery are associated with poorer survival and may reflect systemic inflammation. While markers like NLR and NPAR have prognostic value, neutrophil count alone is a practical, accessible biomarker for clinical use. Limitations of this study include potential confounding factors such as lifestyle and comorbidities, and lack of subgroup analysis by breast cancer type, stage, and other treatments in addition to surgery. Further prospective studies are still needed for validation. Five-year survival rate comparison. Statistic High Neutrophil counts Normal Neutrophil counts Patient Count 303 596 1 Month Survival 99% 99.8% 5 Month Survival 97% 99.3% 10 Month Survival 94.4% 97.3% 30 Month Survival 85.4% 91.9% 60 Month Survival 77.8% 84.5% Hazard Ratio* 1.63 (95% CI: 1.16–2.29) P = 0.0041.

1110 Background: CDK4/6 inhibitors with endocrine therapy are widely used for HR+/HER2– metastatic breast cancer (BC). While studies have shown similar progression-free outcomes across agents, overall survival (OS) data are limited. Since OS is a definitive endpoint and BMI may influence outcomes, this study examines BMI-dependent OS differences among CDK4/6 inhibitors. Methods: A retrospective cohort study was conducted using the Mayo Clinic Platform full AMC1 dataset. Postmenopausal women with BC receiving palbociclib/ribociclib/abemaciclib plus aromatase inhibitor (AI) were included. Patients with prior use of fulvestrant, anthracyclines, radiation therapy, GnRH agonists, or history of MACE, heart failure, myocardial infarction, or stroke before BC diagnosis were excluded. Patients were stratified by BMI and CDK4/6 inhibitor. The primary outcome was 5-year OS. Results: Among 1,989 patients (palbociclib: 868; ribociclib: 465; abemaciclib: 656), palbociclib was associated with significantly worse OS compared to ribociclib in BMI <25 (HR 2.91; 95% CI: 1.76–4.79; P < 0.01) and BMI ≥30 (HR 1.91; 95% CI: 1.21–3.01; P < 0.01). Compared to abemaciclib, palbociclib showed worse OS: BMI <25 (HR 1.73; P < 0.01), BMI 25–30 (HR 1.56; P < 0.01), and BMI ≥30 (HR 1.82; P < 0.01). No significant OS differences were observed between ribociclib and abemaciclib. Palbociclib patients were older, particularly in BMI <25 (Cohen's D = 0.39 vs. ribociclib; 0.27 vs. abemaciclib) and BMI ≥30 (0.28 vs. ribociclib; 0.23 vs. abemaciclib). In the BMI 25–30 group, palbociclib group was also older than ribociclib group (Cohen's D = 0.26). Conclusions: In postmenopausal BC patients on AIs and CDK4/6 inhibitors, palbociclib was associated with worse OS in BMI < 25 and BMI ≥ 30 groups, while ribociclib and abemaciclib showed similar outcomes across BMI groups. Palbociclib patients were older than those on other drugs, which may partially confound results; however, in the BMI 25–30 group, despite similar age differences, no survival difference was observed between palbociclib and ribociclib, suggesting age alone may have limited impact. These findings indicate a potential interaction between BMI and drug choice, and highlight the need for prospective studies to confirm and adjust for these variables. Limitations include the observational design and inability to perform multivariable regression analyses to adjust for confounders. Overall survival comparisons by CDK4/6 inhibitor and BMI subgroup. Comparison BMI Group Hazard Ratio (95% CI) P-value Palbociclib vs Ribociclib <25 2.91 (1.76 – 4.79) < 0.01 25 – 30 1.34 (0.87 – 2.071) 0.17 ≥30 1.91 (1.21 – 3.01) < 0.01 Palbociclib vs Abemaciclib <25 1.73 (1.29 – 2.32) < 0.01 25 – 30 1.56 (1.09 – 2.23) < 0.01 ≥30 1.82 (1.15 – 2.88) < 0.01 Ribociclib vs Abemaciclib <25 1.27 (0.81 – 1.99) 0.29 25 – 30 0.87 (0.54 – 1.43) 0.59 ≥30 1.05 (0.63 – 1.75) 0.85

10585 Background: Prior studies suggest that thyroid cancer (TC) survivors may have an elevated risk of secondary malignancies. However, whether this risk differs by TC histology, specifically with breast cancer (BC), remains unclear. We aimed to investigate the association between TC subtype—papillary thyroid carcinoma (PTC) versus medullary thyroid carcinoma (MTC)—and subsequent BC risk, adjusting for demographic factors. Methods: We conducted a retrospective cohort study using the SEER (2000–2022), including adults with a primary, microscopically confirmed PTC or MTC. Subsequent BC occurrence was defined as a binary outcome (yes/no). Multivariable logistic regression was used to estimate adjusted odds ratios (aORs) for MTC versus PTC, controlling for age (<50 vs ≥50 years), sex, and race. Stratified analyses by age and race were also performed. Stata 15 was used for statistical analyses. Results: 14,840 patients (14,563 PTC, 277 MTC) were included. MTC patients were older (mean 59.08±12.66 vs 56.16±12.98 years, p<0.001) and had a higher proportion of males (44.4% vs 29.4%, p<0.001). The overall incidence of secondary BC was lower in MTC patients (7.6% vs 22.5%, p<0.001). In unadjusted logistic regression, MTC was associated with significantly lower BC risk (OR=0.28, 95% CI: 0.18–0.44, p<0.001). After adjustment, MTC remained significantly protective (aOR=0.34, 95% CI: 0.22–0.55, p<0.001). Stratified analyses demonstrated consistent findings across age groups (<50: aOR=0.10, 95% CI: 0.03–0.42; ≥50: aOR=0.34, 95% CI: 0.21–0.54), , as well as white and Hispanic patients. Conclusions: Survivors of MTC have a substantially lower risk of developing secondary BC compared to PTC survivors. This association persists after adjustment for age, sex, and race, and is consistent across age and most racial subgroups. However, different BC types were not assessed due to limited number of BC patients among MTC survivors, and the small MTC sample size and potential survival differences between groups may affect the results. These findings highlight a possible effect of TC subtype on BC risk, suggesting the potential influence of underlying biological or genetic mechanisms. Baseline demographic characteristics of patients with papillary and medullary thyroid carcinoma. Characteristic Papillary Thyroid Carcinoma (PTC) (N=14,563) Medullary Thyroid Carcinoma (MTC) (N=277) P-value Age at Diagnosis 0.0002* Mean ± SD, years 56.16 ± 12.98 59.08 ± 12.66 Median, years 57 61 Sex, n (%) <0.001† Female 10,288 (70.6) 154 (55.6) Male 4,275 (29.4) 123 (44.4) Race, n (%) 0.015† White 10,263 (70.5) 197 (71.1) Black 921 (6.3) 15 (5.4) American Indian 77 (0.5) 1 (0.4) Asian 1,379 (9.5) 13 (4.7) Hispanic 1,903 (13.1) 50 (18.1) SD: Standard Deviation. *P-value from two-sample t-test (equal variances assumed). †P-value from chi-square test for the overall distribution across categories.

BACKGROUND: Atherothrombosis, which underlies most acute coronary syndromes and is driven by intraplaque thrombosis, preferentially occurs in regions of disturbed blood flow (d-flow). Although LATS1/2 (large tumor suppressor kinases 1 and 2) are known regulators of endothelial mechanotransduction, the mechanisms by which d-flow connects endothelial senescence, proliferation, and intraplaque thrombosis remain poorly understood. METHODS: We investigated endothelial cell (EC)-specific roles of Lats1/2 using inducible EC-specific knockout mice in a partial carotid ligation model. Spatial multiomics of human and mouse plaques was performed using imaging mass cytometry, COMET sequential immunofluorescence, and spatial metabolomics. RESULTS: Tamoxifen-induced deletion of both Lats1 and Lats2 (homozygous) in ECs caused fatal edema and increased vascular permeability. In contrast, Lats1 het ( ± ) / Lats2 homo ( −/−) -EC-specific knockout mice survived and developed spontaneous atherothrombotic plaques with neovascularization. Spatial proteomics revealed that LATS1/2 loss induced a senescence-associated stemness phenotype driven by CD38 upregulation. Spatial metabolomics showed sulfite and taurine accumulation, indicating SUOX (sulfite oxidase) deficiency. CD38 suppressed SUOX, demonstrated a switch into the reverse mode of mitochondrial complex V, increased succinate dehydrogenase activity, and promoted ATP consumption. Despite ATP depletion, glutamate metabolism and the citric acid cycle flux increased, sustaining EC proliferation under energetic stress. This senescence-associated stemness state promoted both proliferation and senescence, leading to fragile, leaky neovessels and intraplaque thrombotic lesions. Pharmacological CD38 inhibition attenuated these phenotypes. Similar EC states were observed in human plaques. CONCLUSIONS: Loss of Lats1/2 in ECs induces a CD38-associated senescence-associated stemness-like phenotype that promotes intraplaque thrombosis through mitochondrial metabolic reprogramming, including changes consistent with reverse-mode operation of mitochondrial complex V. These findings define a mechanistic link between disturbed flow, endothelial metabolic reprogramming, and intraplaque thrombosis and hemorrhage.

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