Citations

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.

Background: Thyroid eye disease (TED) is a debilitating autoimmune disorder linked to thyroid dysfunction. There is limited knowledge of TED in Asian populations. This multicenter study characterizes the clinical features and treatment response of TED in a large Chinese cohort. Methods: A retrospective multicenter study included 4157 patients with TED from nine Chinese hospitals from February 2016 to July 2023. Disease severity and activity were evaluated according to the European Group on Graves’ Orbitopathy standards. We examined associations of variables including sex, age, smoking status, I 131 treatment, consultation department, and geographical region with clinical outcomes. Logistic regression and nomogram models were developed to examine associations with sight-threatening TED and, in a subgroup analysis ( n = 126), patients’ responsiveness to intravenous glucocorticoid (IVGC) therapy. Results: We included 4157 patients with mean age and standard deviation (SD) 45.96 ± 16.44 years. Of these, 63.6% ( n = 2644) were females. Over half (55.6%, n = 2310) of participants were in the inactive phase, with a mean clinical activity score of 2.19 ± 1.61 (SD) for all patients. TED severity was categorized as mild (9.3%, n = 385), moderate-to-severe (82.5%, n = 3428), and sight-threatening (8.2%, n = 344). The average degree of exophthalmos was 20.04 ± 5.27 mm, and 48.8% ( n = 2029) of patients had diplopia. Patients treated with I 131 had higher disease activity (47.5%, n = 468, vs. 43.5%, n = 1379, p < 0.05). Coastal region patients exhibited more severe TED (sight-threatening cases: 10.1%, n = 195, vs. 7.2%, n = 147) and higher diplopia scores (1.00 ± 1.10 vs. 0.86 ± 1.09, p < 0.001) than inland counterparts. TED severity was also greater in patients treated in Ophthalmology departments (mild cases: 6.0%, n = 213; moderate-to-severe cases: 85.6%, n = 3055) compared with Endocrinology departments (mild cases: 29.3%, n = 172; moderate-to-severe cases: 63.5%, n = 373). Nomograms had an area under the receiver operating curve of 0.742 (confidence interval [CI] 0.716–0.768) for sight-threatening TED and 0.759 (CI 0.674–0.843) for IVGC therapy responsiveness. Conclusions: We characterized the clinical features and treatment response of TED in a large Chinese cohort. These findings offer valuable insights informing TED risk stratification in Asian patients and forming a foundation for future prospective studies.

Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications. This survey aims to address this need by providing a thorough review of BioLMs, focusing on their evolution, classification, and distinguishing features, alongside a detailed examination of training methodologies, datasets, and evaluation frameworks. We explore the wide‐ranging applications of BioLMs in critical areas such as disease diagnosis, drug discovery, and vaccine development, highlighting their impact and transformative potential in bioinformatics. We identify key challenges and limitations inherent in BioLMs, including data privacy and security concerns, interpretability issues, biases in training data and model outputs, and domain adaptation complexities. Finally, we highlight emerging trends and future directions, offering valuable insights to guide researchers and clinicians toward advancing BioLMs for increasingly sophisticated biological and clinical applications.

ABSTRACT Objectives Patients requiring long‐term enteral nutrition or continuous infusion of carbidopa/levodopa can benefit from jejunostomy tube placement. Recently, directly placed percutaneous transgastric jejunal tubes (TGJs) have been used instead of gastrostomy tubes with jejunal extensions (PEG‐Js) for enteral access. We aim to compare patient characteristics and outcomes after placement of TGJs placed via the introducer technique compared to PEG‐Js. Methods We performed a retrospective study of 141 patients (TGJ = 58, PEG‐J = 83) assessed at Mayo Clinic between 2010 and 2024. Patients were identified using a prospectively maintained procedure data registry. Demographic data, patient characteristics, procedural indications, complications, and first‐replacement date were gathered. Statistical analysis included the Wilcoxon rank sum test, chi‐square test, Fisher's exact test, and Kaplan‐Meier estimates. Patients receiving carbidopa/levodopa were excluded from complications analysis due to the carbidopa/levodopa tube's proprietary structure. A p ‐value of <0.05 was set as a threshold for significance. Results Our results demonstrated no difference in cumulative incidence of complications within 1 year for TGJs and PEG‐Js, p ‐value 0.48. Regarding time to first replacement, treating death as a competing risk factor, there was no statistically significant difference in cumulative incidence of replacement within 1 year for TGJs and PEG‐Js, p ‐value 0.389. Conclusions Our study demonstrates that both direct TGJs and PEG‐Js are safe options for long‐term jejunal feeding. More studies are needed to compare endoscopic to radiologically placed percutaneous transgastric jejunal feeding tubes.

PURPOSE Large language models (LLMs) have demonstrated remarkable versatility in oncology applications, such as cancer staging and survival analysis. Despite their potential, ethical concerns such as data privacy breaches, bias in training data, lack of transparency, and risks associated with erroneous outputs pose significant challenges to their adoption in high-stakes oncology settings. Therefore, we aim to explore the ethical challenges associated with LLM-based applications in oncology and evaluate emerging techniques designed to address these issues. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, a systematic review was conducted to evaluate publications related to ethical issues of LLMs in oncology across eight academic databases (eg, PubMed, Web of Science, and Embase) between January 1, 2019, and December 31, 2024. RESULTS The search retrieved 4,319 published articles, of which 65 publications were preserved and included in our analysis. We identified six prevalent ethical challenges in oncology, including trust, equity, privacy, transparency, nonmaleficence, and accountability. We then evaluated emerging technical solutions to mitigate ethical challenges and summarized evaluation metrics used to assess these solutions' effectiveness. CONCLUSION This review provides actionable recommendations for responsibly deploying LLMs in oncology, ensuring adherence to ethical guidelines, and fostering improved patient outcomes. By bridging technical and clinical perspectives, this review offers a foundational framework for advancing ethical artificial intelligence applications in oncology and highlights areas for future research.

Abstract Introduction: Advances in treatment have led to significant increases in survival rates, with over 90% of men diagnosed with prostate cancer (CaP) living at least five years. However, surviving cancer and its treatment often weigh a hefty survivorship burden. Men from the at-risk, vulnerable populations have the greatest burden. This study aims to understand distress among Black CaP survivors (CaPS) who bear the heaviest CaP burden. Method: We conducted key informant interviews with Motivational Interviewing techniques to collect CaPS demographic information, medical history, and multilevel distress evaluation. Descriptive analyses were conducted using SAS. Results: A total of 22 CaPS (aged from 48 to 72) were involved in the study. The majority of CaPS were African American (90.9%) and were diagnosed with stage 2 (31.8%) or stage 3 (36.4%). Over half of them (68.2%) were treated by surgery; most CaPS (90.9%) experienced side effects from prostate cancer treatments. CaPS reported distress in the following domains: Emotional well-being (e.g., Feeling sad, depressed or anxious, mental health) – 40.9%, Death of someone very close to you (e.g., family) – 36.4%, Alcohol use in close family – 36.4%, Experiences of discrimination or racism – 36.4%, Healthcare costs and coverage (e.g., medication, medical services, copay, insurance premium) – 31.8%, Loneliness and isolation – 27.3%, Serious injury/illness in close family (e.g., being a caregiver) – 27.3%, Money and finance – 22.7%, Using telehealth (e.g., using a smartphone or tablet for telephone or over the computer, clinic visit, patient portal, completing online forms, virtual classes) – 22.7%, Marriage, romantic relationships – 22.7%. Discussion: Black CaP survivors (CaPS) who bear the heaviest CaP burden are considered a priority population for research and care. These CaPS identified that their psychological distress was related to both familial and socioeconomic issues. The most endorsed life-stresses included emotional wellbeing, experiences of discrimination/racism, loneliness and isolation, healthcare cost/finance, family health, personal relationship, and telehealth use. The distress data as measured by the life-stress scale are invaluable in better documenting and addressing distress in interventions responsive to specific priority communities. Our novel findings suggest the relevance of grief and loss for these men. 36% reported death of someone close, and 27% indicated distress due to loneliness and isolation. Though the sample size was small, the distress data obtained may inform the science and practice of whole-person survivorship that consider distress emphasizing emotional wellbeing. The study is ongoing, and this abstract presents preliminary results; further muti-variate analyses will be conducted for the conference presentation. Citation Format: Kimlin Ashing, Floyd Willis, Chris Williams, John Mccall, Gaole Song, Fornati Bedell, Cassandra Moore, Ewan Cobran, Che Ngufor, Timethia Bonner, Getachew Dagne, Arnold Merriweather, Ernie Kaninjing, Rotimi Oladapo, Roxana Dronca, Fullwood Dottington, Folakemi Odedina. Whole person survivorship: Multilevel distress in prostate cancer survivors from priority communities [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr A024.

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

AbstractBackgroundInfants born via Cesarean section (C‐section) often have a distinct gut microbiome and higher risks of atopic and immune‐related conditions than vaginally delivered infants. We evaluated whether a microbiome‐based program could shift gut microbiome composition and improve microbiome‐associated health outcomes in C‐section born infants.MethodsThis open‐label, randomized, controlled trial included full‐term C‐section‐born infants aged 0–3 months, randomized to an intervention (n = 25) or control arm (n = 29). Over 6 months, the intervention arm received two microbiome reports, personalized recommendations based on their microbiome, educational materials, and coaching calls focused on microbiome health. Parents reported health conditions via surveys. Primary outcome: Difference between study arms in relative abundance of key gut microbiome taxa and functional genes. Other outcomes: Changes in a C‐section index—a taxonomy‐based metric comparing C‐section‐associated taxa to vaginally‐associated taxa—and prevalence of atopic conditions.ResultsCompared to controls, the intervention arm had higher Bifidobacterium (p = .025, q = .121) and higher abundance of genes associated with human milk oligosaccharide degradation (e.g., α‐L‐fucosidase, p = .019, q = .046) at timepoint 2. In the intervention arm, the C‐section index decreased to a level similar to vaginally born infants (p = .807, q = .807). At the end of the intervention, atopic dermatitis prevalence was lower in the intervention arm than in controls (odds ratio, 0.17 [95% CI, 0.023–0.723], p = .031).ConclusionA personalized microbiome‐based program can modulate the gut microbiome of C‐section‐born infants and may reduce the risk of atopic conditions (ClinicalTrials.gov: NCT06424691).

Background/Objectives: Coronavirus disease 2019 (COVID-19) is associated with gastrointestinal (GI) symptoms. Small intestinal bacterial overgrowth (SIBO) is emerging as a significant GI sequela post-COVID-19 infection. This study aimed to evaluate the prevalence and incidence of SIBO post-COVID-19 infection across different age groups and to identify associated risk factors in a global cohort. Methods: A retrospective study utilized the TriNetX database and included adult patients (≥18 years) diagnosed with SIBO following COVID-19 infection (1 January 2022–30 May 2024). A propensity score matching (1:1) was used to adjust for demographics and SIBO risk factors. Kaplan–Meier survival analysis assessed the SIBO incidence within 12 months. Results: Among 1,660,092 COVID-19 patients and 42,322,017 controls, SIBO was diagnosed in 353 COVID-19 patients without hydrogen breath tests (BT) and 78 with BT, compared to 3368 controls without BT and 871 with BT. Age-specific analysis demonstrated a clear, progressive increase in the SIBO incidence, becoming distinctly significant by 6 months and highest at 12 months post-infection. The highest risks were noted in ages 60–69 (0.011% vs. 0.004%, OR 2.6, p = 0.0003) and 70–79 (0.011% vs. 0.005%, OR 2.0, p = 0.0004), with younger age groups (30–49 years) also showing significantly increased risks. The medication analysis revealed strong associations with chronic opioid, proton pump inhibitor, and antidiarrheal medication. Conclusions: COVID-19 significantly increased the risk of SIBO, particularly within the first 12 months post-infection, across various age groups and, notably, in association with certain chronic medications. Clinical vigilance and targeted management strategies are recommended to mitigate long-term GI consequences.