Citations

Artificial intelligence (AI) is transforming gastrointestinal (GI) endoscopy into a more standardized, data-driven, and workflow-integrated field. Advances in computer-assisted detection (CADe), diagnosis (CADx), quality assessment (CAQ), natural language processing (NLP), and multimodal deep learning have expanded AI applications across colonoscopy, upper endoscopy, endoscopic ultrasound (EUS), ERCP, cholangioscopy, and capsule endoscopy. These systems have demonstrated improvements in lesion detection, procedural quality assessment, workflow efficiency, and diagnostic support. However, current evidence remains largely focused on surrogate outcomes rather than patient-centered clinical benefits, while challenges related to generalizability, explainability, regulatory oversight, automation bias, and workflow integration continue to limit widespread adoption. Future progress will depend on prospective real-world validation, diverse datasets, explainable AI frameworks, and careful integration of human–AI interaction into clinical practice. Overall, AI is evolving from a supportive adjunct into an increasingly integrated component of gastrointestinal endoscopy with the potential to improve procedural quality, diagnostic consistency, and clinical efficiency.

Abstract Background: Early-onset pancreatic cancer (EOPC; age <50 y at diagnosis) is rare (≈1.3/100,000), biologically distinct, and germline-enriched (BRCA1/2, PALB2, ATM, CDKN2A, Lynch). Despite NCCN and CAPS Consortium recognition, its pre-diagnostic electronic health record (EHR) trajectory is uncharacterized. We sought reproducible signatures to guide subtype-aware surveillance for this under-screened young-adult population, where conventional guidelines do not apply. Methods: We assembled an EOPC cohort from Mayo Clinic (3 sites, 2001–2023; n=169 EOPC, n=3,162 older-onset PDAC), identified by ICD-10 C25.0–C25.3, C25.7, C25.9 or ICD-9 157.x with age <50 at first diagnosis. For each patient, 3-year pre-diagnostic trajectories of 10 routine laboratory analytes (bilirubin, CA 19-9, CEA, lipase, amylase, glucose, HbA1c, ALT, AST, alkaline phosphatase) were summarized over 30/90/180/365-day windows (mean, slope, delta; 1,706 features total; 131 retained at ≥10% non-zero). Features were winsorized (1–99 pct), standardized, and projected onto 15 PCA components capturing 81.7% variance. K-means clustering (k=2–6, min cluster fraction ≥10%) was assessed by silhouette and 100-resample bootstrap Adjusted Rand Index (ARI). Cluster signatures were compared against the older-onset PDAC cohort projected into the same component space. Results: Two reproducible pre-diagnostic clusters emerged (k=2; silhouette 0.469; bootstrap ARI 0.440). Cluster A: "occult prodrome" (87.0%; n=147; mean age 44.9 y) showed no clear signal across the 10 monitored analytes, with all analyte z-scores near zero through the 3-year window. Cluster B: "metabolic-biliary active" (13.0%; n=22; mean age 44.4 y) was characterized by elevated mean HbA1c (z=+1.08), rising bilirubin slope (z=+0.54), and rising ALT/alkaline phosphatase slopes (z=+0.51 each), consistent with combined diabetic-onset and biliary-obstructive prodrome. The two-cluster structure reproduced in older-onset Mayo PDAC at 87.3% / 12.7%, nearly identical to the EOPC distribution, indicating a fundamental pre-diagnostic dichotomy of pancreatic cancer rather than an age-specific phenomenon. The dominant occult phenotype across age strata indicates that lab-trajectory–anchored surveillance can only address the active minority and motivates complementary genetic-, demographic-, or imaging-anchored pathways for the occult majority. Conclusions: EOPC pre-diagnostic trajectories partition into a dominant occult prodrome (∼87%) without detectable signal in the 10 routine labs evaluated and a minority metabolic-biliary active prodrome (∼13%) with combined diabetic and obstructive features. The high occult prevalence motivates germline-guided active surveillance for genetically at-risk young adults rather than symptom-driven workup, anchoring next-generation surveillance trial designs in rare and hereditary pancreatic malignancies. External validation in independent institutional cohorts (Mayo Clinic Platform / MERCI, or comparable EHR networks) is the planned next step. Citation Format: Jianfu Li Li, Yingyun Yang, Wallace MIchael, Yan Bi. Pre-diagnostic clinical-trajectory signatures of early-onset pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Breaking Barriers in the Fight against Rare Cancers; 2026 Jul 18-20; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(14_Suppl):Abstract nr A046.

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Background: Prior studies have reported higher rates of periprosthetic fracture, superficial infection, and neurologic deficit with the direct anterior approach (DAA), and higher rates of dislocation with the posterior approach (PA) for total hip arthroplasty (THA). Despite these differences, the overall clinical burden of complications between approaches remains unclear. The purpose of this study was to compare the profiles, severity, impact, and resolution of 5 clinically important complications between DAA and PA THA. Methods: A retrospective review was conducted of 11,783 consecutive primary THAs performed between 2010 and 2021 across 3 centers within a single healthcare system, using either the DAA (n = 4,451) or the PA (n = 7,332). Complications assessed included dislocation, infection, periprosthetic fracture (PPFx), aseptic loosening, and neurologic deficit. Severity was graded using the Clavien-Dindo classification (I = minor, V = death). Impact was defined by reoperation burden, and outcomes were categorized as resolved or persistent. Kaplan-Meier survivorship and propensity-weighted Cox proportional hazards models were used to compare complication risk. Results: The overall 1-year risk of surgical complications did not differ between DAA and PA (hazard ratio [HR], 0.89; 95% confidence interval [CI], 0.75-1.06; p = 0.208). Dislocation occurred more frequently with PA THA than DAA THA (1.9% vs. 0.4%; HR, 5.20; 95% CI, 3.04-8.90; p < 0.001). Superficial infections were more frequent with the DAA (1.6% vs. 0.8%; HR, 2.43; 95% CI, 1.68-3.53; p < 0.001). The risk of deep infection, PPFx, aseptic loosening, and neurologic deficit did not differ significantly between approaches. Among patients with complications, the proportion classified as severe (Clavien-Dindo III–V) was similar, and adjusted analyses showed no difference in the odds of severe complications (adjusted odds ratio 1.34 for PA vs DAA; 95% CI, 0.95-1.91; p = 0.099). Complication impact and resolution were likewise comparable. Conclusion: Although the profile of complications differed between DAA and PA THA, the severity, early clinical impact, and resolution of complications appeared similar. Notably, DAA was associated with a lower risk of dislocation and a higher risk of superficial infection compared with PA THA. Level of Evidence: Level III , Retrospective Comparative Study. See Instructions for Authors for a complete description of levels of evidence.

Hepatic resection (HR) and liver transplantation (LT) are curative-intent treatments for hepatocellular carcinoma (HCC). Patients without cirrhosis are typically analyzed as a single group, obscuring potentially important differences between those with histologically normal liver and those with non-cirrhotic parenchymal disease. We aimed to characterize long-term outcomes following HR stratified by underlying parenchymal quality, with a contemporary LT cohort as an external benchmark. Retrospective cohort study of 662 adults undergoing curative-intent surgery for HCC at 2 tertiary centers (2010–2024). Resection patients (n=380) were stratified by non-tumor parenchymal histology into HR-Normal (n=84), HR-Diseased non-cirrhotic (n=159), and HR-Cirrhotic (n=137). A total of 282 LT recipients served as an external reference but were not entered into comparative models. Overall survival (OS) was analyzed by Kaplan–Meier and multivariable Cox regression, and recurrence by Fine–Gray competing-risks regression. Ninety-day mortality was low across resection strata (1.2%–3.2%). OS differed significantly across parenchymal groups (log-rank p =0.01), driven by superior outcomes in HR-Normal patients compared with both HR-Cirrhotic ( p =0.008) and HR-Diseased ( p =0.005). HR-Cirrhotic and HR-Diseased did not differ ( p =0.97). Five-year OS was 74.4%, 59.8% and 57.2%, respectively. On multivariable Cox regression, both cirrhosis (HR 2.03, 95% CI 1.16–3.54, p =0.01) and diseased non-cirrhotic parenchyma (HR 2.04, 95% CI 1.21–3.43, p =0.008) independently predicted death versus normal liver. Fine–Gray analysis confirmed higher recurrence risk in cirrhotic (sHR 2.09, p =0.01) and diseased non-cirrhotic (sHR 1.80, p =0.04) groups. The LT benchmark cohort achieved a 5-year OS of 82.4%. Histologically normal liver identifies a distinct HR subgroup with favorable oncologic outcomes. The conventional cirrhotic/non-cirrhotic dichotomy underestimates the prognostic impact of underlying parenchymal disease.

Abstract Background Adults with congenital heart disease (ACHD) represent a rapidly expanding population with complex lifelong clinical and psychosocial needs. Nurses play a pivotal role within multidisciplinary ACHD care, yet internationally their education, scope of practice and professional preparation remain highly variable, with no globally agreed curriculum. This gap has limited role clarity, workforce development and international harmonisation of standards. The aim of this project was to develop the first dedicated, competency-based curriculum for ACHD nursing to support consistent, high-quality, patient-centred care worldwide. Methods An international, multidisciplinary working group led by the Association of Cardiovascular Nurses and Allied Professions of the European Society of Cardiology, in collaboration with the Working Group on Adult Congenital Heart Disease and the International Society for Adult Congenital Heart Disease, developed the curriculum through expert consensus. The development group included nurses, physicians, educators and individuals with lived experience of ACHD, ensuring patient perspectives were embedded throughout the process. Existing international guidance, professional frameworks and evidence on ACHD nursing practice were synthesised. The curriculum was structured around Entrustable Professional Activities (EPAs), mapped to the CanMEDS professional roles and designed to accommodate international variation in regulation, resources and scope of practice. Results The resulting curriculum defines core and specialist competencies across the ACHD lifespan, encompassing clinical care, transition, reproductive health, psychosocial support, prevention, advanced therapies, care coordination and research. EPAs specify required knowledge, skills, attitudes, assessment strategies and levels of entrustment, with a minimum standard for practice. The framework supports career progression from specialist to advanced practice roles and is adaptable for academic, workplace-based and continuing professional development contexts. Conclusions This curriculum represents the first internationally applicable, competency-based framework for ACHD nursing. By standardising expectations while allowing contextual flexibility, it strengthens role clarity, supports workforce development and promotes harmonised, high-quality ACHD care globally.

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Objectives To understand the trade-offs between different statistical modeling approaches, using real world data with small sub-populations, with rare exposures and increasingly rare outcomes. In particular, to compare adjusted regression, inverse probability weighting, and matching. Methods Data for these analyses came from the RADAR (N=1,134) and combined CNICS/JHHCC (N=14,434) cohorts. We estimated prevalence ratios (PRs) for self-reported use of specific substances comparing subpopulations (SP), SP-1 vs SP-3 and SP-2 vs SP-3, where SP-1 was the largest proportion (92% in RADAR, 81% in CNICS/JHHCC), SP2 was moderate proportion (18% in CNICS/JHHCC) and SP-3 was the smallest proportion (8% in RADAR, 1% in CNICS/JHHCC) of the population. We calculated PRs using 1) unadjusted relative risk regression (RR); and adjusted estimates controlling for age, race/ethnicity, study site, and year of interview using: 2) standard adjustment in RR; 3) stabilized inverse probability of treatment weighting (IPTW); and 4) matching with up to 3 matches from SP-1 or SP-2 per SP-3 participant. Results For most substances, all methods yielded consistent estimates. There were large weights in some of the IPTW analyses and in three cases these resulted in substantially divergent estimates. For the comparison between SP-1 and SP-3, the estimate for smoking was 1.3-fold greater in the matched analysis (PR=1.33, 95% CI: 1.02-1.75) than in IPTW (PR=1.03, 95% CI: 0.78-1.37 ATE and PR=1.05, 95% CI: 0.88-1.26 ATT). Even more extreme divergence in estimates was observed for differences between SP-2 and SP-3 with respect to methamphetamine/amphetamine, (IPTW-ATE: PR=1.51, 95% CI: 0.79-2.89; IPTW-ATT: PR=2.36, 95% CI: 1.36-4.12); vs Matching: PR=2.71, 95%CI: 1.47-4.99) and cocaine (IPTW-ATE: PR=1.15, 95% CI: 0.55-2.38; IPTW-ATT: PR=1.81, 95% CI: 1.03-3.18); vs Matching: PR=1.38, 95%CI: 0.76-2.53). Conclusion The combination of a rare exposure and a rare outcome can produce challenges for commonly used confounding adjustment strategies, and it is often best to compare different modeling approaches to gain greater insight.