Citations

ABSTRACT Background Several colorectal cancer (CRC) screening modalities are guideline-recommended in the United States, yet they vary considerably in screening interval and real-world adherence. As a result, single-round test performance may not reflect cumulative effectiveness over time. This study compared the 10-year longitudinal outcomes of two CRC screening strategies— triennial next-generation multitarget stool DNA testing (ng mt-sDNA) and decennial screening colonoscopy. Methods This study used the validated, microsimulation-based Colorectal Cancer and Adenoma Incidence and Mortality (CRC-AIM) model to estimate 10-year cumulative outcomes for two guideline-recommended screening strategies: triennial ng mt-sDNA and decennial colonoscopy. Model inputs included test-specific performance and real-world adherence. Outcomes included CRC and precancerous lesions detected, CRC mortality reductions, and life-years gained (LYG). Sensitivity analyses examined the effects of varying both screening adherence and follow-up colonoscopy adherence. Results Over 10 years per 1,000 individuals offered screening, the ng mt-sDNA screening test detected 13% more precancerous lesions and 11% more CRC cases than colonoscopy, with a greater proportion of CRCs identified through screening rather than symptomatic detection. ng mt-sDNA resulted in greater CRC mortality reduction (33% vs 20%) and 62% more life-years gained, with consistent findings across sensitivity analyses. Conclusions With real-world adherence, screening with triennial ng mt-sDNA demonstrates superior cumulative effectiveness compared with decennial colonoscopy, driven by higher adherence and favorable longitudinal performance. These findings support the expanded use of noninvasive stool-based screening to reduce CRC mortality and alleviate capacity constraints associated with colonoscopy-based screening. Broader adoption of ng mt-sDNA may enhance population-level CRC prevention by increasing participation and improving early detection across the screening eligible population. Plain language summary Colorectal cancer screening tests are recommended at different time intervals and completed at different adherence rates in clinical practice. The analysis used a validated simulation model to compare 10-year outcomes of triennial next-generation multi-target stool DNA test (ng mt-sDNA) with a single colonoscopy, accounting for real-world screening and follow-up colonoscopy adherence. Our findings indicate that repeated ng mt-sDNA provides greater cumulative screening effectiveness than colonoscopy over a 10-year period.

This cohort study evaluates the reduction in risk of high-grade serous carcinoma among women undergoing opportunistic bilateral salpingectomy in Canada.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Background: High-grade intracranial atherosclerosis (ICAS) is associated with an elevated risk of recurrent ischemic stroke, particularly in patients with severe stenosis (70–99%). Identifying predictors of early recurrence can inform risk stratification and guide treatment strategies. Methods: The Biomarkers and Recurrence Risk in Symptomatic Intracranial Arterial Stenosis (BIORISK-ICAS) study is a multicenter, international, retrospective cohort analysis pooling data from 35 comprehensive stroke centers. We included hospitalized adult patients with symptomatic ICAS, defined as 50–99% stenosis of an intracranial artery (intracranial vertebral, basilar, distal ICA, or M1 MCA), confirmed by vascular imaging and associated with a qualifying ischemic event. Patients with only high-grade stenosis (70-99%) were included in this analysis. The primary outcome was to determine predictors of recurrent ischemic stroke in the territory of the symptomatic artery within 90 days of the index event. Baseline demographic, clinical, and imaging characteristics were recorded. Multivariable Cox proportional hazards regression with stepwise selection (p < 0.1) was used to identify independent predictors of recurrence; model discrimination was assessed using Harrell’s C-statistics. Results: Among 2,050 patients, 1,476 had high-grade (70-99%) symptomatic ICAS. The mean age was 67 ± 12.5 years, and 767 (55%) were male. Most patients were non-Hispanic (90.1%), taking dual antiplatelet therapy (77.8%), and statins (94.5%). Recurrent stroke occurred in 160 patients (10.8%) within 90 days. In multivariable Cox model, independent predictors of recurrence included atrial fibrillation (HR 2.05; 95% CI, 1.26–3.33; p = 0.004), hyperlipidemia (HR 1.57; 95% CI, 1.10–2.24; p = 0.014), diabetes mellitus (HR 1.36; 95% CI, 0.98–1.88; p = 0.064), and home use of dual antiplatelet therapy (HR 1.60; 95% CI, 1.01–2.54; p = 0.043)(Harrell’s C-statistic=0.62). In patients who underwent perfusion(n=402), mistmatch >10seconds were associated with increased recurrence (HR 1.80; 95% CI 0.95-3.38, p=0.07) and atrial fibrillation (HR 2.06: 95% CI 0.03-4.60, p=0.78) though did not reach statistical significance. Conclusion: In this population, diabetes, hyperlipidemia, atrial fibrillation, and prior use of dual antiplatelet therapy were associated with increased risk of 90-day recurrent ischemic stroke. Perfusion imaging may help identify high-risk patients who could benefit from intensified secondary prevention.

Background Patient complaints provide a complementary lens on surgical safety, yet prior analyses have been small and specialty specific. We aimed to characterise themes, perioperative processes, system factors and outcomes in surgical complaints using a scalable, large language model (LLM)-assisted approach. Methods We performed a national, retrospective, cross-sectional, sequential methods study of publicly available investigation reports from the Aotearoa New Zealand Health and Disability Commissioner. All reports published since 1998 were retrieved and screened for relevance across all surgical specialties. A fixed-parameter LLM workflow extracted demographics, clinical context, complications, breached patient rights, system factors and outcomes. An inductive LLM-supported thematic synthesis generated complaint themes, followed by rescoring of theme relevance across reports. Human validation supported the LLM-assisted process (Cohen’s κ >0.85). Results Of 1827 reports screened, 650 involved surgical care. Postoperative complications were frequent (84.2%), commonly accompanied by permanent disability (33.2%) or death (24.2%). Delays in recognition of deterioration (76.1%), escalation (58.3%) and definitive management (49.5%) of complications were common and associated with higher mortality. Prominent themes concerned postoperative clinical management/monitoring, communication/informed consent and professional conduct/competence. Technical/procedural errors and medication errors were comparatively less common. Breaches are most often related to reasonable care and skill, and to informed consent, with marked variation across specialties. Conclusions Complaints about surgical care predominantly reflect postoperative monitoring, escalation and communication rather than intraoperative technical errors. System priorities should include robust deterioration recognition and response, reliable handover and escalation pathways, and strengthened consent and communication processes. An LLM-assisted pipeline can scale complaint analysis to support organisational learning and quality improvement.

Background: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide, accounting for approximately 10% of all cancer cases. Despite the proven effectiveness of conventional screening modalities such as colonoscopy and fecal immunochemical testing (FIT), their invasive nature, high cost, and limited patient compliance hinder widespread adoption. Recent advancements in artificial intelligence (AI) and bowel sound-based signal processing have enabled non-invasive approaches for gastrointestinal diagnostics. Among these, bowel sound analysis—historically considered subjective—has reemerged as a promising biomarker using digital auscultation and machine learning. Objective: This review explores the potential of AI-powered bowel sound analytics for early detection, screening, and characterization of colorectal cancer. It aims to assess current methodologies, summarize reported performance metrics, and highlight translational opportunities and challenges in clinical implementation. Methods: A narrative review was conducted across PubMed, Scopus, Embase, and Cochrane databases using the terms colorectal cancer, bowel sounds, phonoenterography, artificial intelligence, and non-invasive diagnosis. Eligible studies involving human bowel sound-based recordings, AI-based sound analysis, or machine learning applications in gastrointestinal pathology were reviewed for study design, signal acquisition methods, AI model architecture, and diagnostic accuracy. Results: Across studies using convolutional neural networks (CNNs), gradient boosting, and transformer-based models, reported diagnostic accuracies ranged from 88% to 96%. Area under the curve (AUC) values were ≥0.83, with F1 scores between 0.71 and 0.85 for bowel sound classification. In CRC-specific frameworks such as BowelRCNN, AI models successfully differentiate abnormal bowel sound intervals and spectral patterns associated with tumor-related motility disturbances and partial obstruction. Distinct bowel sound-based signatures—such as prolonged sound-to-sound intervals and high-pitched “tinkling” proximal to lesions—demonstrate the physiological basis for CRC detection through bowel sound-based biomarkers. Conclusions: AI-driven bowel sound analysis represents an emerging, exploratory research direction rather than a validated colorectal cancer screening modality. While early studies demonstrate physiological plausibility and technical feasibility, no large-scale, CRC-specific validation studies currently establish sensitivity, specificity, PPV, or NPV for cancer detection. Accordingly, bowel sound analytics should be viewed as hypothesis-generating and potentially complementary to established screening tools, rather than a near-term alternative to validated modalities such as FIT, multitarget stool DNA testing, or colonoscopy.

Abstract Background There is an unmet need for ulcerative colitis (UC) treatments that show improved effectiveness while maintaining safety profiles comparable with existing advanced therapies. Dual targeted therapy (DTT) has been proposed as a strategy to combine benefits of different advanced therapies to improve outcomes. The ExiGem study (NCT06095128) aims to assess the efficacy and safety of combined therapy with vedolizumab (VDZ) and tofacitinib (TOF) in adults with UC. We report results for the induction phase from the first 24 patients. Methods ExiGem is an ongoing phase 4, single-arm, multicentre study including adults with moderately to severely active UC (complete Mayo [cMayo] score of 6–12 with a rectal bleeding subscore ≥ 1 and centrally read endoscopic subscore ≥ 2). Eligible patients have previously had an inadequate response, loss of response, or intolerance to 1 or 2 anti-tumour necrosis factor α treatments. Patients receive induction therapy with intravenous (IV) VDZ 300 mg at weeks 0, 2, and 6 plus twice-daily oral TOF 10 mg for 8 weeks and then VDZ 300 mg IV monotherapy as maintenance from week 14. The primary endpoint is the proportion of patients in clinical remission by cMayo score at week 8. Secondary endpoints include clinical response and clinical remission by modified Mayo (mMayo) score at week 8. Changes in faecal calprotectin (FCP) levels and endoscopic improvement were evaluated. Efficacy data were analysed using non-responder imputation. For the final analysis a pre-specified Bayesian approach will be used. The safety profile of DTT was evaluated. Results Patient baseline characteristics are shown in Table 1. At week 8, 12/24 patients (50%) and 14/24 patients (58%) had clinical remission assessed by cMayo and mMayo scores, respectively; these rates were higher than pre-specified benchmark rates (Figure 1). Clinical response was observed in 21/24 patients (88%). At week 8, 14/24 patients (58%) showed endoscopic improvement, and 12/21 patients (57%) had normalization of FCP levels (&lt; 250 µg/g). Treatment-emergent adverse events (TEAEs) were experienced by 10 patients (42%), and 1 serious TEAE was reported (suspected viral infection). One severe adverse event (AE; cough) and 2 moderate AEs (herpes zoster, drug intolerance) were considered related to TOF. No moderate or severe AEs were considered related to VDZ. One patient withdrew from the study before week 8 owing to intolerance to TOF. Conclusion Initial data suggest that induction with a combination of VDZ and TOF can produce improved rates of response and remission in patients with UC with a comparable safety profile to existing advanced monotherapies. Further data, including outcomes of VDZ maintenance as monotherapy, are pending. Conflict of interest: Prof. Dr. Yarur, Andres: Andres Yarur has served as an advisory board member for Boehringer Ingelheim, Bristol Myers Squibb, Eli Lilly, Johnson & Johnson, Merck, Roche/Genentech, and Takeda. This study was funded by Takeda Pharmaceuticals U.S.A., Inc. Medical writing support was provided by Adam Errington PhD of PharmaGenesis Cardiff, Cardiff, UK, and funded by Takeda Pharmaceuticals U.S.A., Inc. Barnes, Edward: Personal Fees: Consultant for Takeda, Pfizer, Roche, Merck, Abbvie, Eli Lilly. Bristol Myers Squibb, Celltrion, Johnson and Johnson. Deepak, Parakkal: Parakkal Deepak has received research support under a sponsored research agreement unrelated to the data in the abstract from AbbVie, Johnson and Johnson, Sanofi, Merck, Teva, Direct Biologics, Tr1x, Boehringer Ingelheim, Bristol Myers Squibb, Pfizer, Prometheus Biosciences, Takeda Pharmaceuticals, Roche Genentech, Eli Lilly, AstraZeneca, Spyre and Agomab, has received consulting fees from Johnson and Johnson, Abbvie, Merck, Sobi, Celltrion, Fresenius Kabi, Asahi Kasei Pharma, Sandoz and CorEvitas, LLC and has served on the board of the Srategic Alliance for Intercultural Advocacy in GI. Ha, Christina: Christina Ha has served as an advisory board member for AbbVie, Bausch Health, Johnson & Johnson, Lilly, Merck, Takeda, and Sanofi has received educational programming support from AbbVie, Celltrion, Johnson & Johnson, Lilly, Pfizer, and Takeda and has received consulting fees from AbbVie. Hudesman, David: Consultant: Abbvie, Abivax, BMS, Biocon, Eli Lilly, Fresenius Kabi, Pfizer, Prometheus, CorEvitas, Takeda, Johnson and Johnson, Sanofi Research Support: Johnson and Johnson, Pfizer Jairath, Vipul: Consulting Fees: Abbvie, Alimentiv, Amgen, Anaptys Bio, Asahi Kasei, Asieris, Astra Zeneca, Attovia, Blackbird Labs, BMS, Boehringer Ingleheim, Biomebank, Caldera, Calluna, Catalytic Health, Celltrion, Ensho, Enthera, Exeliome Biosciences, Ferring, Fresenius Kabi, Gilead, Granite Bio, GSK, Janssen, Lilly, Merck, Mountainfield, MRM Health, Nxera, Organon, OSE Immunotherapeutics, Pendopharm, Pioneering Medicine, Pfizer, Prometheus, Roche/Genentech, Sanofi, SCOPE, Shattuck Labs, Sorriso, Spyre, Synedgen, Takeda, Teva, Tillotts, Union Therapeutics, Ventus, Ventyx, Vividion, Xencor, Zealand Pharma. Lukin, Dana: Dana Lukin has served as a consultant/advisory board member for AbbVie, AltruBio, Boehringer Ingelheim, Eli Lilly, Johnson & Johnson, Palatin, Pfizer, Prime, PSI, Takeda, and Vedanta has received grants from Boehringer Ingelheim and Johnson & Johnson and serves as a speaker for AbbVie and Johnson & Johnson. Rubin, David T.: Grant support: Takeda Pharmaceuticals. Consultant: Abbvie, Abivax SA, Altrubio, Athos Therapeutics, Inc, Bristol-Myers Squibb, Celltrion, Connect BioPharma, Eli Lilly & Co., Genentech (Roche) Inc., Iterative Health, Janssen Pharmaceuticals, Johnson & Johnson, Merck & Co., Mirador, Odyssey Therapeutics, Pfizer, Sanofi, Spyre, Takeda Pharmaceuticals, Vedanta Biosciences, and Ventyx. Schreiber, Stefan Wolfgang: Stefan Schreiber has received consulting fees from AbbVie, Amgen, Arena, Boehringer Ingelheim, Bristol Myers Squibb, Celltrion, Dr Falk Pharma, Eli Lilly, Ferring, Fresenius, Galapagos, Genentech, Gilead, GlaxoSmithKline, I-MAB Biopharma, Janssen, Merck, Novartis/Sandoz, Pfizer, Protagonist, Takeda, and Ventyx Biosciences. Gower, Megan: Megan Gower is an employee and hold stock/stock options at Takeda Pharmaceuticals U.S.A., Inc. Jones, Stephen: Stephen Jones is an independent medical consultant who provides services for Takeda Pharmaceuticals U.S.A., Inc. Robinson, Ian: Ian Robinson is an employee and hold stock/stock options at Takeda Pharmaceuticals U.S.A., Inc. Sanchirico, Marie: Marie Sanchirico is an employee and hold stock/stock options at Takeda Pharmaceuticals U.S.A., Inc. Yajnik, Vijay: Vijay Yajnik is an employee and hold stock/stock options at Takeda Pharmaceuticals U.S.A., Inc.

Objectives: Smoking is a key risk factor for pancreatitis, contributing to pathogenesis and disease progression. Data regarding second-hand smoking, or passive smoking (PS) exposure, are lacking. We therefore aimed to assess the impact of PS exposure across the pancreatitis spectrum. Methods: We analyzed baseline data from the PROCEED study, a multicenter study in the United States including patients with acute (AP), recurrent acute (RAP), and chronic (CP) pancreatitis. Participants detailed their individual smoking history and PS exposure, which was compared between AP, RAP, and CP subgroups. Participant factors and clinical characteristics were compared by level of individual and PS exposure. Results: Among 1369 participants (190 AP, 498 RAP, 681 CP), 346 (25.3%) were current and 409 (29.9%) were former smokers. The CP subgroup had the highest proportion of current smokers (36.7% CP vs 15.1% RAP, 11.1% AP, P < 0.001). PS exposure was also significantly higher in the CP subgroup (68.6% CP vs 58.2% RAP, 55.3% AP, P < 0.001). A minority (16.3%) with CP reported no smoking exposure (by self or passive) while nearly half smoked ≥20 pack-years. The mean PS duration was significantly higher in CP participants (21.8 y) compared with those with AP (17.8 y) or RAP (18.9 y) ( P < 0.0166). Conclusions: In this multicenter study, we affirmed an association with smoking use and intensity with CP-related complications. For the first time, we report a high prevalence of prior exposure to passive smoking in all pancreatitis subtypes, which requires further study to understand the impact on disease outcomes.

TPS259 Background: Despite currently approved therapies, most patients with metastatic colorectal cancer (mCRC) progress through all approved treatments and eventually succumb to their disease. Thus, novel therapies for chemotherapy-refractory mCRC are desperately needed. Inhibition of the DNA unwinding enzyme TOP1 is a well-characterized and clinically successful treatment strategy for mCRC. CBX-12 is a novel peptide-drug conjugate comprised of an exatecan warhead linked to a pH-Low Insertion Peptide (pHLIP). The principle behind this targeting mechanism is based on the Warburg effect, in which tumors establish a low pH extracellular environment. The pHLIP moiety of CBX-12 preferentially forms a unidirectional, transmembrane alpha helix in a low-pH extracellular environment. Thus, CBX-12 delivers its exatecan cytotoxic warhead preferentially into tumor cells. In mouse xenograft models, CBX-12 inhibited the HCT116 CRC xenograft model more potently than an equimolar dose of free exatecan. The phase 1 study of CBX-12 reported cytopenias as the predominant AEs and confirmed responses in several solid tumors including mCRC. Methods: This is a single-arm, phase 2 trial, with a Simon 2-stage design assessing CBX-12 for the treatment of chemotherapy-refractory mCRC. The primary objective is efficacy determined by RECIST v1.1 response rate. Secondary and exploratory objectives include evaluating the PK and PD as well as the progression-free survival (PFS) on CBX-12. Key inclusion criteria include: age ≥18 years, ECOG performance status ≤1, histologically or cytologically confirmed mCRC that is MSS/pMMR based on CLIA-approved testing, and progression on 2 or more lines of chemotherapy. This design requires 17 patients for stage 1, with termination if 1 or fewer objective responses are seen out of 17. If 2 or more patients out of 17 responds, then an additional 18 patients will be enrolled for stage 2. If 5 out of the total of 35 patients (14%) respond, then the trial would be declared successful. Correlative studies will include tumor plus peripheral blood PK to evaluate effectiveness of CBX-12 tumor targeting, ctDNA, and several tumor PD markers including TOP1-DNA trapping, SLFN11 expression, DNA damage, and apoptosis. The trial opened to enrollment on 8/21/25. Clinical trial information: NCT06730100 .

Abstract Background Toxicities to organs at risk adjacent to the target volume represent a critical limitation to dose escalation in radiotherapy. While external beam therapy with accelerated ions allows for a reduced dose to surrounding healthy organs, its biological effectiveness can be markedly higher than that of conventional x‐rays and should be considered during treatment planning. Current biophysical models possess limitations in computing in vivo normal tissue complication probability (NTCP) curves for clinically relevant ion beams. Purpose This study introduces and validates a novel computational framework capable of predicting NTCP curves for serial organs following ion exposures. Methods The proposed framework integrates the linear‐quadratic model, the critical volume NTCP model, a novel two‐stage fitting process of fractionated photon NTCP data, histological data, and the Mayo Clinic Florida Microdosimetric Kinetic Model (MCF MKM) of relative biological effectiveness. The model was applied to predict the NTCP for the spinal cord myelopathy of rats exposed at different depths along the spread‐out Bragg peaks (SOBPs) of protons, helium, carbon, and oxygen ions. Radiation transport simulations were conducted to assess the microdosimetric pattern of energy deposition at the subcellular scale. Results The two‐stage photon fitting process yielded a α photons /β photons ratio of 2.3 ± 0.6 Gy and NTCP model parameters for calculations considering either endothelial or glial cells as the primary targets for the spinal cord myelopathy. Without using any ion data for calibration, the predicted NTCP showed an overall good agreement with the corresponding animal data. The model successfully reproduced the experimentally observed trends in the NTCP dependence with respect to fractionation, ion type, and exposure position along the SOBPs. Conclusions The model's ability to predict the NTCP curves for ion exposures, based solely on photon in vivo data, provides mechanistic insights and can guide preclinical investigations into the biological effects of different ions and fractionation schemes.