Introduction

Low-volume polyethylene glycol plus ascorbic acid (PEG-Asc) reduces the dosage of colonoscopic bowel preparation (BP) solution, but is still poorly tolerated. Recent studies reported that adding laxatives to the BP solution reduced the volume of fluid required, without affecting the quality. Senna, one of the anthraquinone stimulant laxatives commonly used for chronic constipation, is reported to be useful as a BP adjunctive agent. However, the appropriate dose and combination of senna and BP solutions are unclear.

Aims & Methods

This study aimed to compare 1-L PEG-Asc plus 24 mg senna (1L-PEG/AS) and conventional 2-L PEG-Asc (2L-PEG/A) regimens on BP quality and patient tolerability. A single-center, randomized, investigator-blinded, non-inferiority trial was performed between June and August 2022. Outpatients scheduled for colonoscopy were randomized (1:1) to the 1L-PEG/AS or 2L-PEG/A group. Boston Bowel Preparation Scale (BBPS) was used to evaluate the quality of BP, and adequate BP was defined as a total score ≥6 and each segmental score ≥2. The rate of adequate BP was assumed as 90% in both groups with a noninferiority margin of 10%. Compliance, adverse events and tolerability were surveyed using questionnaires. Exploratory subgroup analyses were conducted based on the potential predictor of inadequate BP (with Bonferroni correction to adjust for multiple comparisons, P<0.05/20=0.0025 was considered significant).

Results

Overall, 344 patients received either 1L-PEG/AS or 2L-PEG/A regimens. The baseline characteristics of the two groups were comparable. The 1L-PEG/AS group showed non-inferior adequate BP rates compared with the 2L-PEG/A group (88% vs. 89%, P=1.00); the overall BBPS was 7.1±1.5 and 7.2±1.5, respectively (P=0.39). More patients in the 2L-PEG/A group took <80% of solution compared to those in the 1L-PEG/AS group (17% vs. 3%, P<0.01). Nausea, vomiting, abdominal pain and discomfort, and quality of sleep, were comparable between the two groups. Higher willingness to repeat the BP was observed in the 1L-PEG/AS group (85% vs. 62%, P<0.01), and more patients in the 2L-PEG/A were unwilling to repeat BP than those in the 1L-PEG/AS group due to larger volumes of PEG-Asc consumed (49% vs. 18%, P<0.01). Exploratory subgroup analyses for adequate BP found no significant difference between the two regimens for all subgroups.

Conclusion

The 1L-PEG/AS regimen was comparable to the 2L-PEG/A regimen in terms of BP adequacy, requiring lesser BP solution volumes, with better patient tolerance. Thus, it may be a suitable alternative to the conventional BP solution for colonoscopy.

Disclosure

Nothing to disclose.

Introduction

Mirikizumab, a p19-directed interleukin-23 monoclonal antibody, is efficacious in inducing clinical remission at Week (W) 12 and maintaining clinical remission through W152 in patients with moderately-to-severely active ulcerative colitis (UC; LUCENT-1: W0-W12, NCT03518086; LUCENT-2: W12-W52, NCT03524092; LUCENT-3: W52-W212, NCT03519945). Here we present efficacy and safety results through W212 of mirikizumab treatment from the open-label extension LUCENT-3 study.

Aims & Methods

Symptomatic, clinical, endoscopic, histologic, corticosteroid-free (CSF), bowel urgency, quality-of-life, and adverse event (AE) outcomes are reported for mirikizumab induction responders, including patients with biologic failure, who entered LUCENT-3, with data shown for W52 maintenance remitters. Discontinuations or missing data were handled by nonresponder imputation (NRI), modified NRI (mNRI), and observed case (OC). mNRI uses multiple imputation for missing data and balances bias of NRI and OC. Table 1 provides endpoint and population definitions and abbreviations for maintenance remitters. Efficacy population N=179. Safety population N=339.

Results

Using mNRI among W52 mirikizumab maintenance remitters demonstrated clinical response in 79% at W212. Rates at W212 among W52 clinical remitters were 77% for symptomatic, 62% for clinical, 66% for endoscopic, 53% for histologic-endoscopic mucosal, 62% for CSF, and 60% for bowel urgency remission, 78% for Inflammatory Bowel Disease Questionnaire (IBDQ) response, and 73% IBDQ remission. Histologic-endoscopic mucosal improvement and bowel urgency clinically meaningful improvement at W212 were achieved in 54% and 75% of patients, respectively. Biologic Failed/Not Biologic Failed subgroup data also demonstrated maintenance of efficacy (Table 1). Stool frequency, rectal bleeding, bowel urgency, and abdominal pain symptom score reductions from induction baseline at W52 were sustained through W212. For W0-160 of LUCENT-3, serious AEs were reported in 12% of patients, while 7% discontinued treatment due to an AE; AEs of special interest included opportunistic infection (4%), cerebrocardiovascular events (2%), and malignancy (2%). Liver enzymes ≥3 upper limit of normal (ULN) included alanine aminotransferase (2%) and aspartate aminotransferase (1%); total bilirubin level was ≥2 ULN (2%).

Conclusion

Mirikizumab provides sustained long-term symptomatic, clinical, endoscopic, histologic, corticosteroid-free, and quality-of-life remission up to 4 years in patients with UC, including for biologic failed patients, with no new safety concerns.

References

Sands BE, D’Haens G, Clemow DB, Irving PM, Johns JT, Gibble TH, Abreu MT, Lee SD, Hisamatsu T, Kobayashi T, Dubinsky MC, Vermeire S, Siegel CA, Peyrin-Biroulet L, Moses RE, Milata J, Panaccione R, Dignass A. Three-Year Efficacy and Safety of Mirikizumab Following 152 Weeks of Continuous Treatment for Ulcerative Colitis: Results From the LUCENT-3 Open-Label Extension Study. Inflamm Bowel Dis. 2024:izae253

Disclosure

Bruce Sands reports consulting fees from AbbVie, Alimentiv, Amgen, Arena Pharmaceuticals, Artugen Therapeutics, AstraZeneca, Boehringer Ingelheim, Boston Pharmaceuticals, Calibr, Celgene, Celltrion, ClostraBio, Equillium, Enthera, Evommune, Fresenius Kabi, Galapagos, Genentech (Roche), Gilead Sciences, GlaxoSmithKline, Gossamer Bio, Index Pharmaceuticals, Innovation Pharmaceuticals, Inotrem, Kaleido, Kallyope, Merck, Morphic Therapeutics, MRM Health, Progenity, Prometheus Biosciences, Prometheus Laboratories, Protagonist Therapeutics, Q32 Bio, Sun Pharma, Surrozen, Target RWE, Teva, TLL Pharmaceutical, and Ventyx Biosciences; consulting and speaking fees will be disclosed in the final presentation.
David Clemow, Karen Samaan, Anil Guar, Jerine Paulissen, Sarah Folian, Ravneet Arora, and Richard Moses report being Eli Lilly and Company employees and stockholders.
Geert D’Haens reports advisor fees from AbbVie, Alimentiv, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Celltrion, Eli Lilly and Company, Galapagos, GlaxoSmithKline, Gossamer Bio, Pfizer, Immunic, Johnson and Johnson, Takeda, Prometheus Biosciences, Prometheus Laboratories, Protagonist, Samsung, Seres, Tillotts, and Ventyx.
Severine Vermeire reports grants from AbbVie, Johnson and Johnson, Pfizer, Takeda, and Galapagos; consulting and/or speaking fees from AbbVie, Abivax, AbolerIS Pharma, AgomAb, Alimentiv, Arena Pharmaceuticals, AstraZeneca, Avaxia, BMS, Boehringer Ingelheim, Celgene, CVasThera, Cytoki Pharma, Dr Falk Pharma, Ferring, Galapagos, Genentech-Roche, Gilead, GSK, Hospira, IMIdomics, Janssen, Johnson and Johnson, Eli Lilly and Company, Materia Prima, Mestag Therapeutics, MiroBio, Morphic, MRM Health, Mundipharma, MSD, Pfizer, Prodigest, Progenity, Prometheus, Robarts Clinical Trials, Second Genome, Shire, Surrozen, Takeda, Theravance Biopharma, Tillots Pharma AG, VectivBio, Ventyx, and Zealand Pharma.
Peter Irving reports research grants from Celltrion, Pfizer, Takeda, and Galapagos; consulting fees from AbbVie, Arena, Boehringer Ingelheim, BMS, Celltrion, Elasmogen, Gilead, Janssen, Eli Lilly and Company, Pfizer, Prometheus, and Sandoz; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from AbbVie, BMS, Celgene, Celltrion, Falk Pharma, Galapagos, Gilead, Janssen, Eli Lilly and Company, Pfizer, Takeda, and Tillotts Pharma AG; and support for attending meetings and/or travel from AbbVie and Tillotts Pharma AG.
Taku Kobayashi reports serving as a speaker, a consultant, or an advisory board member for AbbVie, Alfresa Pharma, Bristol Myers Squibb, Celltrion, Covidien, EA Pharma, Eiken, Eli Lilly and Company, Ferring Pharmaceuticals, Galapagos, Gilead Sciences, Janssen, JIMRO, Kissei, Kyorin Pharmaceutical, Mitsubishi Tanabe Pharma, Mochida Pharmaceutical, Nippon Kayaku, Pfizer, Sekisui Medical, Takeda Pharmaceutical, and Zeria Pharmaceutical and has received research funding from AbbVie, Alfresa Pharma, EA Pharma, Gilead Sciences, Kyorin Pharmaceutical, Mochida Pharmaceutical, Nippon Kayaku, Otsuka Holdings, Pfizer, Sekisui Medical, and Zeria Pharmaceutical.
Laurent Peyrin-Biroulet reports personal fees from AbbVie, Adacyte, Alimentiv, Alma Bio Therapeutics, Amgen, Applied Molecular Transport, Arena, Biogen, BMS, Celltrion, CONNECT Biopharma, Cytoki Pharma, Enthera, Ferring, Fresenius Kabi, Galapagos, Genentech, Gilead, Gossamer Bio, GSK, H.A.C. Pharma, IAG, Index Pharmaceuticals, Inotrem, Janssen, Eli Lilly and Company, Medac, Mopac, Morphic, MSD, Norgine, Nordic Pharma, Novartis, OM Pharma, ONO Pharma, OSE Immunotherapeutics, Pandion Therapeutics, Par’Immune, Pfizer, Prometheus, Protagonist, Roche, Sanofi, Sandoz, Takeda, Theravance, Thermo Fisher, TiGenix, Tillots, Viatris, Vifor, Ysopia, Abivax, Samsung, Ventyx, Roivant, and VectivBio.
Axel Dignass reports fees received for participation in clinical trials, review activities such as data monitoring boards, statistical analysis, and end point committees from Abivax, AbbVie, Bristol Myers Squibb, Dr Falk Foundation, Galapagos, Gilead, Janssen, and Pfizer; consultancy fees from AbbVie, Amgen, Arena Pharmaceuticals, Biogen, Boehringer Ingelheim, Bristol Myers Squibb/Celgene, Celltrion, Dr Falk Foundation, Ferring Pharmaceuticals, Fresenius Kabi, Galapagos, Janssen, Eli Lilly and Company, MSD, Pfizer, Pharmacosmos, Roche, Sandoz, Stada, Takeda, Tillotts, and Vifor Pharma; payment for lectures including service on speakers bureaus from AbbVie, Biogen, CED Service GmbH, Celltrion, Dr Falk Foundation, Ferring, Galapagos, Gilead, High5MD, Janssen, Materia Prima, MedToday, MSD, Pfizer, Sandoz, Takeda, Tillotts, and Vifor Pharma; and payment for manuscript preparation from AbbVie, Dr. Falk Foundation, Janssen, Takeda, Thieme, and UNI-MED Verlag.

Introduction

Clostridioides difficile infection (CDI) is among of the most common causes of nosocomial diarrhea with high morbidity and mortality. Recurrent and refractory disease courses in particular represent a special challenge in the management of these patients. The identification of patients at risk for recurrent courses could improve management, e.g. through the use of new and effective therapies in patients with CDI.

Aims & Methods

The aim of this study was to investigate the relationship between the presence of different comorbidities and the course of CDI.
In a retrospective, monocentric cohort study of a tertiary centre over a period of 10 years, patients with CDI-related hospitalizations were examined. The study included 336 patients with available information on comorbidities (diverticulosis, biliary diseases (cholecysto-, docholithiasis, cholecystitis, cholangitis or cholangiectasis) inflammatory bowel diseases (IBD), liver cirrhosis and malignancies) and the diagnosis of the recurrent CDI (rCDI) vs. non-recurrent course of CDI (nrCDI). Patients on dialysis or immunosuppressed patients were also considered as comorbid.

Results

Among 336 patients included in the study, 227 (67.6%) presented with at least one comorbidity. The most common were malignancy (30.4%), biliary diseases (19.4%), diverticulosis (15.8%), liver cirrhosis (14.3%), and inflammatory bowel disease (IBD, 8.9%). rCDI occurred more frequently in patients with diverticulosis and biliary disease. Diverticulosis was present in 24.4% of rCDI cases vs. 12.6% in nrCDI cases (OR 2.24, 95% CI 1.22–4.17). Biliary diseases were observed in 26.7% of rCDI vs. 16.7% of nrCDI patients (OR 1.82, 95% CI 1.01–3.26). No significant associations with rCDI were found for IBD (OR 0.66, 95% CI 0.27–1.65), malignancy (OR 1.13, 95% CI 0.67–1.88), or liver cirrhosis (OR 0.79, 95% CI 0.38–1.61).

Conclusion

These findings suggest diverticulosis and biliary disease may be independent risk factors for rCDI, whereas other common comorbidities are not significantly associated with recurrence. Structured assessment of risk conditions may help to select patients for tailored management to prevent rCDI disease course.

Introduction

Endoscopy is essential for the early detection and management of upper gastrointestinal (UGI) tumors, yet variability in diagnostic expertise and workload-related fatigue often compromise the quality of report documentation. These challenges underscore the urgent need for innovative technological approaches to assist endoscopists in optimizing the report generation process.
Multimodal large language models (MLLMs) enable the synergistic integration of visual and semantic representations, demonstrating significant clinical value in medical text generation. This study introduces MERGS, an innovative endoscopy report generation system powered by MLLM. MERGS annotates medical terminology and generates natural language descriptions based on endoscopic images, ultimately producing structured reports that conform to clinical standards.

Aims & Methods

MERGS is built on the pre-trained MLLM Qwen-VL-2.5-7B. It adopts a multimodal architecture integrating visual encoding and cross-modal alignment to enable medical term annotation and natural language generation from endoscopic images. A pathological classification module further enhances lesion characterization. The language model synthesizes image-derived descriptions to generate a comprehensive report with a diagnostic conclusion.
UGI endoscopy reports were collected from the Sun Yat-sen University Cancer Center between 2019 and 2021. A standardized terminology dictionary was developed based on clinical guidelines, supporting a three-tier annotation framework: endoscopic image → standardized medical terminology → natural language text. Model-assisted pre-annotation combined with expert validation substantially reduced manual effort. The resulting dataset was split into training and test sets at an 8:2 ratio.
Model performance was assessed via multi-label classification metrics (accuracy, specificity, F1-score), as well as semantic similarity measures (Jaccard index) to evaluate its ability to recognize anatomical sites and endoscopic features. Natural language generation quality was assessed using BLEU-2 and ROUGE-L scores, and expert satisfaction ratings were collected for 100 randomly sampled outputs to assess readability and clinical relevance. A human–AI comparison was conducted on 50 test reports, comparing system-generated outputs with those authored by experienced endoscopists.

Results

A multimodal dataset was constructed after quality control, comprising 22,373 reports and 135,503 associated images from 21,619 patients. Internal validation demonstrated that MERGS achieved robust performance in automated image interpretation, with 97.3% accuracy and 98.6% specificity for standard anatomical site recognition. In feature identification, it showed high clinical relevance (F1 scores: smooth mucosa 0.915, polyp 0.857, tumor 0.878, erythematous mucosa 0.766).
Generated reports showed strong alignment with reference reports (BLEU-2 = 0.587, ROUGE-L = 0.661) and received high expert satisfaction ratings (mean score: 4.34 ± 0.63 on a 5-point scale). In a human–AI comparison, MERGS-generated reports were considered non-inferior to those authored by endoscopists (scores: MERGS 4.52 ± 0.81 vs. manual 4.68 ± 0.72), with the upper limit of the one-sided 95% CI (0.37) below the non-inferiority margin (0.5, p = 0.0045).

Conclusion

This study developed an automated system for UGI endoscopy reporting powered by an MLLM. Both internal and clinical validation demonstrated the system's high performance in endoscopic image feature recognition and report generation, underscoring its strong potential for clinical deployment.

References

Luo H, Xu G, Li C, He L, Luo L, Wang Z, Jing B, Deng Y, Jin Y, Li Y, Li B, Tan W, He C, Seeruttun S R, Wu Q, Huang J, Huang D W, Chen B, Lin S B, Chen Q M, Yuan C M, Chen H X, Pu H Y, Zhou F, He Y, Xu R H. Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study[J]. Lancet Oncol, 2019,20(12):1645-1654.