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Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

e16017 Background: Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer and remains one of the deadliest malignancies worldwide, largely due to late-stage diagnosis. Early-stage PDAC is frequently asymptomatic, limiting opportunities for timely detection and intervention. We aimed to develop prognostic models using routinely acquired pre-diagnostic clinical data to identify individuals at high risk for PDAC prior to clinical manifestation. Methods: We conducted a retrospective study of patients treated at Mayo Clinic sites in Rochester, MN; Phoenix, AZ; and Jacksonville, FL between January 2011 and February 2023. The cohort included 1,151 patients with PDAC and 3,745 noncancer controls. CT scans were standardized to axial abdominal acquisitions with slice thickness between 0.8–3.0 mm. Radiology reports were de-identified, normalized, and parsed into structured sections (Indications, Findings, Impression), with an additional pancreas-specific section aggregating pancreas-related sentences. Demographic and clinical variables, e.g., age, sex, race, etc., were encoded using a templated sentence representation. All textual inputs were embedded using a Sentence-BERT model. A multimodal deep learning survival model was developed to integrate CT imaging, radiology report embeddings, and demographic features. The model was trained using a negative log-likelihood loss to estimate patient-specific PDAC risk scores. Model performance was assessed using the concordance index (C-index). Internal validation included patients from MN and AZ sites, while external validation used the FL cohort. Results: We evaluated unimodal (imaging, text, and demographics) and multimodal inputs. Fusion of imaging, radiology report, and demographic features achieved the highest performance, with internal and external validation C-indices of 0.885 (95% CI, 0.856–0.908) and 0.751 (95% CI, 0.719–0.783), respectively. Subgroup analysis by tumor location demonstrated differential performance. For pancreatic head tumors, internal and external C-indices were 0.916 (95% CI, 0.841–0.960) and 0.778 (95% CI, 0.730–0.823). For pancreatic body tumors, C-indices were 0.954 (95% CI, 0.897–0.997) internally and 0.929 (95% CI, 0.897–0.953) externally. For pancreatic tail tumors, internal and external C-indices were 0.903 (95% CI, 0.830–0.974) and 0.789 (95% CI, 0.689–0.874). Conclusions: A multimodal deep survival model leveraging pre-diagnostic CT imaging, radiology report embeddings, and demographic data can effectively identify individuals at high risk for PDAC prior to clinical diagnosis. Differences in performance were observed across pancreatic head, body, and tail tumors. This approach highlights the potential of opportunistic cancer risk stratification from routine imaging to enable earlier detection and targeted intervention strategies.

ABSTRACT Background and Aims Artificial intelligence (AI) is increasingly integrated into gastrointestinal (GI) endoscopy, yet limited data exist on how patients and endoscopists perceive its use. This study aimed to evaluate users' values and preferences regarding AI in endoscopy to support effective implementation and inform guideline development. Methods As part of the World Endoscopy Organization (WEO) AI committee initiatives, two structured international surveys were conducted—one for patients and one for practicing endoscopists. Thirteen AI‐related statements were presented to patients via an established online platform, while 23 statements were shared with endoscopists through professional networks. Responses were captured using 5‐point Likert scales and analyzed with non‐parametric tests, including subgroup comparisons by age, gender, and endoscopic experience. Results A total of 1237 patients and 476 endoscopists participated. Most patients supported AI in image analysis (75.5%) but emphasized the need for endoscopist oversight (92.3%). Among endoscopists, 90.3% believed AI improves endoscopy quality, and 85.3% believed it benefits outcomes. Concerns were raised about liability (47%), operator dependency (34.8%), and procedure time (49%). Most respondents felt primary responsibility for AI‐related errors should rest with the endoscopist. Younger and male patients reported greater trust in AI. Conclusions Patients and endoscopists are generally supportive of AI in GI endoscopy, especially as an adjunct to human expertise. However, key concerns—including accountability, trust, and clinical integration—must be addressed to ensure responsible and effective adoption.

An understanding of regions of endemicity and the spectrum of organ system involvement can improve recognition of the imaging features of coccidioidomycosis, which can overlap with those of other diseases.

PURPOSE To compare patient-reported and clinical outcomes between radical cystectomy (RC) and bladder-sparing therapy (BST) in patients with recurrent high-grade non–muscle-invasive bladder cancer (NMIBC). PATIENTS AND METHODS This pragmatic, prospective observational cohort study was designed with patients, who selected and prioritized outcomes. Eligible adults were candidates for both RC or BST, had previous induction Bacillus Calmette-Guérin (BCG), and received their last treatment within 12 months. The primary outcome was the EORTC-QLQ-C30 physical function scale at 12 months. Secondary outcomes included other EORTC-QLQ-C30 scales, depression, anxiety, bladder cancer–specific quality of life (QOL), financial burden, and cancer-specific outcomes. Targeted maximum likelihood estimation (TMLE) was used to calculate average treatment effect (ATE) estimates between arms. Inverse probability weighted risk ratios (wRR) were calculated using quasi-Poisson regression. RESULTS Of 570 participants (mean age 71.4 years; 21% female), 371 selected BST and 199 selected RC. Physical function was significantly worse in the RC arm at 3 months; by 9 months, there was no difference between arms, and at 12 months, physical function did not differ (ATE, 0.9; 95% CI, –0.6 to 2.4; P = .22). RC was associated with better emotional function, generic health-related QOL, and financial burden, and lower depression and anxiety, while BST was associated with better bowel and sexual health. Cancer-specific survival was 99% for BST versus 96% for RC (wRR, 0.99; 95% CI, 0.97 to 1.01). RC was associated with a higher risk of adverse events and serious adverse events, including a 90-day mortality rate of 2.5%. CONCLUSION Most patient-prioritized outcomes were similar or better among participants who chose RC compared with BST. These findings support the continued role of RC in managing recurrent high-grade NMIBC.

The NCCN Guidelines for Biliary Tract Cancers (BTCs) provide recommendations for the evaluation and comprehensive care of patients with gallbladder cancer, intrahepatic cholangiocarcinoma, and extrahepatic cholangiocarcinoma. The multidisciplinary panel of experts is convened at least once annually to review requests from internal and external entities as well as to evaluate new data on current and emerging therapies. This manuscript focuses on the adjuvant chemotherapy and chemoradiation treatment options for BTCs as well as the systemic treatment recommendations for patients with advanced BTCs.

Multidisciplinary case conferences have been shown to improve patient outcomes. However, such case conferences may be unavailable in some settings. This multidisciplinary discussion of 4 challenging hepatobiliary cases was presented at the 2023 Society of Advanced Body Imaging Annual Meeting in Dallas, TX. The cases include an “imaging occult” pancreatic tumor, a large pancreatic mass, an intraductal biliary mass, and a polypoid intraluminal gallbladder mass.