Introduction

Up to 40% of patients with acute severe ulcerative colitis (ASUC) do not respond to infliximab (IFX)(1) presumably due to insufficient drug exposure (1, 2). We investigated whether personalised IFX induction using predefined serum concentrations was superior to standard dosing.

Aims & Methods

In this prospective, multi-centre trial, adult IFX-naive steroid-refractory ASUC patients were randomised 1:1 to standard (SD) or personalised IFX dosing (PD). After an initial 5 mg/kg IFX infusion, SD was 5 mg/kg IFX at week 2 and 6. In PD, additional 5 mg/kg IFX infusions were administered guided by a Bayesian pharmacokinetic algorithm (iDose™) aiming at IFX serum concentrations >28 ug/mL day 0-28 and >15 ug/mL day 29-42 (3). The primary composite endpoint was clinical and endoscopic response at day 42 (Lichtiger score <10 and ≥3 points drop and UCEIS ≥2 points drop from baseline). Video-endoscopies were performed at baseline, day 42 and 182 and scored by 2 expert readers (XR) with adjudication by a third XR and post hoc also by the DovaVision UC AI tool (AI-R)(4). Key secondary endpoints were day 42 clinical response, day 42 endoscopic response, day 182 clinical remission (Lichtiger ≤3), day 182 endoscopic remission (UCEIS ≤1 on all components), and safety.

Results

48 patients were randomised (23 PD/25 SD) and 31 completed the 26-week study (19 PD/12 SD). Patient characteristics were comparable. Median cumulative IFX dose until day 42 was 18.41 mg/kg [1.77, 20.27] for PD vs 13.79 mg/kg [10.38, 14.82] for SD. The primary composite endpoint at day 42 was not met with XR (57% in PD vs 44% in SD; p=0.564). However, AI-R showed a significantly higher composite response rate in PD (74% in PD vs 32% in SD; p=0.0047). PD showed higher day 42 clinical response vs SD (91% vs 64%; p=0.039). Day 42 endoscopic response was observed in 57% in PD vs 44% in SD (p=0.564) with XR and 74% in PD vs 32% in SD with AI-R (p=0.0047). The proportion of patients in clinical and endoscopic remission at day 182 was higher in PD than in SD (65% vs 36%; p=0.082). Day 182 endoscopic remission with AI-R was higher in PD (52% in PD and 20% in SD; p=0.0337). SAEs occurred in 9% of patients on PD vs 20% of patients on SD. Following an interim analysis, the trial was discontinued based on futility.

Table 1. Baseline characteristics

Conclusion

Personalised IFX dosing was superior to standard dosing in ASUC when endoscopies were read by AI. This is the first IBD study where the primary endpoint, missed by expert assessment, was overturned and met by AI assessment instead. This demonstrates the potential of AI to fundamentally improve clinical trial methodology.

References

1. Seow CH, Newman A, Irwin SP, Steinhart AH, Silverberg MS, Greenberg GR. Trough serum infliximab: a predictive factor of clinical outcome for infliximab treatment in acute ulcerative colitis. Gut. 2010;59(1):49-54.
2. Papamichael K, Van Stappen T, Vande Casteele N, Gils A, Billiet T, Tops S, et al. Infliximab Concentration Thresholds During Induction Therapy Are Associated With Short-term Mucosal Healing in Patients With Ulcerative Colitis. Clin Gastroenterol Hepatol. 2016;14(4):543-9.
3. Ungar B, Mazor Y, Weisshof R, Yanai H, Ron Y, Goren I, et al. Induction infliximab levels among patients with acute severe ulcerative colitis compared with patients with moderately severe ulcerative colitis. Aliment Pharmacol Ther. 2016;43(12):1293-9.
4. Byrne M, Requa J, Panaccione R, Panes J, Bressler B, East JE, et al. Development and Validation of a novel AI-based computer vision solution for Ulcerative Colitis severity scoring on video for real world using high-volume expert-annotated video frames. United European Gastroenterol J. 2025 Oct.

Disclosure

This project received grant support from Pfizer Inc. and research support from Baysient LLC, Buhlmann Laboratories and Dova Health Intelligence.

Introduction

Small intestinal bacterial overgrowth (SIBO) is a clinical syndrome with abdominal complaints and malabsorption. Despite concerns over cure rates, recurrence, and antibiotic resistance, rifaximin (RIF) remains the primary treatment. Berberine (BBR), an affordable traditional medicine, has demonstrated gut microbiota modulation, making it a promising alternative.

Aims & Methods

We conducted an open-label, non-inferiority randomized controlled trial (BRIEFSIBO) comparing BBR and RIF in SIBO patients. Patients were randomly assigned to receive either RIF or BBR. The primary outcome was breath test (BT) conversion to negative, with symptom scores and the Bristol stool scale as secondary outcomes.

Results

A total of 186 patients completed the study. No significant baseline differences were found between groups in age, gender, BMI, smoking, or alcohol use. BBR demonstrated non-inferior efficacy to RIF for primary outcome (BT eradication) at Week 2 (ITT: BBR 45%, RIF 51%, Z=2.407, P=0.008; PP: BBR 44%, RIF 47%, Z=2.4787, P=0.007) and Week 6 (ITT: BBR 53%, RIF 44%, Z=4.3244, P<0.001; PP: BBR 54%, RIF 45%, Z=4.077, P<0.001). What's more, BBR demonstrated non-inferior efficacy to RIF for secondary outcome (clinical improvement) at Week 2 (ITT: BBR 68%, RIF 75%, Z=2.9209, P=0.0017; PP: BBR 73%, RIF 72%, Z=3.3531, P=0.0004) and Week 6 (ITT: BBR 75%, RIF 80%, Z=2.8514, P=0.0022; PP: BBR 81%, RIF 86%, Z=3.0747, P=0.0011). Following a four-week period of discontinuation, the rate of combined expiratory and symptomatic relapse in patients treated with RIF was 8.57%. In contrast, no such relapses were observed in patients treated with BBR. BT values at 60–90 minutes and AUC decreased in both groups, though RIF showed recurrent peak values during follow-up. A novel breath peak acceleration parameter, reflecting local gut gas load, decreased in both groups. BBR significantly improved bloating at Week 6, whereas RIF improved bowel movement frequency. At Week 6, patients were classified into response, relapse, and nonresponse groups to identify optimal candidates for each drug. RIF responders showed significant improvement in bloating and bowel-related symptoms (P<0.05). Baseline gut microbiota analysis revealed significant β diversity differences between three groups in BBR but not in RIF. Genus-level microbiota composition differed between responders, with BBR responders exhibiting higher baseline proportions of Phascolarctobacterium, Klebsiella, and Haemophilus, and lower Coprobacter. At Week 6, both groups showed enriched Bacteroides, while BBR responders had elevated Phascolarctobacterium, Streptococcus, and Haemophilus, with lower Bifidobacterium.

Conclusion

BBR is non-inferior to RIF for SIBO treatment and offer a promising and cost-effectiveness new option.

References

1. Pimentel M, Saad RJ, Long MD, et al. ACG Clinical Guideline: Small Intestinal Bacterial Overgrowth. Am J Gastroenterol 2020;115(2):165-78. doi: 10.14309/ajg.0000000000000501
2. Bushyhead D, Quigley EMM. Small Intestinal Bacterial Overgrowth-Pathophysiology and Its Implications for Definition and Management. Gastroenterology 2022;163(3):593-607. doi: 10.1053/j.gastro.2022.04.002
3. Quigley EMM, Murray JA, Pimentel M. AGA Clinical Practice Update on Small Intestinal Bacterial Overgrowth: Expert Review. Gastroenterology 2020;159(4):1526-32. doi: 10.1053/j.gastro.2020.06.090
4. Leite G, Rezaie A, Mathur R, et al. Defining Small Intestinal Bacterial Overgrowth by Culture and High Throughput Sequencing. Clin Gastroenterol Hepatol 2024;22(2):259-70. doi: 10.1016/j.cgh.2023.06.001
5. Svedlund J, Sjödin I, Dotevall G. GSRS--a clinical rating scale for gastrointestinal symptoms in patients with irritable bowel syndrome and peptic ulcer disease. Dig Dis Sci 1988;33(2):129-34.
6. Liu ZJ, Wei H, Duan LP, et al. [Clinical features of irritable bowel syndrome with small intestinal bacterial overgrowth and a preliminary study of effectiveness of Rifaximin]. Zhonghua Yi Xue Za Zhi 2016;96(24):1896-902. doi: 10.3760/cma.j.issn.0376-2491.2016.24.005
7. Guo H, Lu S, Zhang J, et al. Berberine and rifaximin effects on small intestinal bacterial overgrowth: Study protocol for an investigator-initiated, double-arm, open-label, randomized clinical trial (BRIEF-SIBO study). Front Pharmacol. 2023;14:1121435. doi:10.3389/fphar.2023.1121435

Introduction

Emerging evidence suggests that poor oral health may play a role in gastrointestinal carcinogenesis through inflammatory and microbiome-mediated mechanisms. However, its association with esophageal cancer remains insufficiently explored.

Aims & Methods

We aimed to assess the association of oral health indicators and oral hygiene behaviors with esophageal cancer risk using both dental health screening and claims-based data. We conducted a population-based case-control study using the Korean National Health Insurance Service (NHIS) database and the National Health Screening (NHS) records. To enhance the reliability of our study, we examined oral hygiene from two complementary perspectives: (1) oral health assessed through dental examinations and questionnaires in the NHS database and (2) periodontal disease status determined based on a claim-based analysis of the NHIS database. Individuals newly diagnosed with esophageal cancer were identified and matched at a 1:4 ratio to cancer-free controls through rigorous propensity score (PS) matching based on sociodemographic factors, comorbidities, lifestyle behaviors, and laboratory parameters. Oral health variables were assessed using national dental screening program data (status of decayed, missing, and filled teeth; gingivitis severity; dental calculus; and self-reported oral hygiene practices) and NHIS claims data identifying periodontal disease using ICD-10 codes and procedure codes. Multivariable-adjusted conditional logistic regression analyses were performed to estimate adjusted odds ratios (aORs) with 95% confidence intervals (CIs).

Results

After PS matching, the oral health analysis included 4,238 cancer cases and 16,904 controls, while the claim-based periodontal disease analysis comprised 18,905 cancer cases and 75,604 matched controls in the final analysis. In multivariable analysis, missing teeth (adjusted OR, 1.16; 95% CI, 1.08–1.25) and inadequate oral hygiene behaviors—including brushing fewer than three times daily (aOR, 1.14; 95% CI, 1.07–1.23), infrequent toothbrushing before bedtime (aOR, 1.08; 95% CI, 1.00–1.16), infrequent use interdental cleaning tools (aOR, 1.10; 95% CI, 1.01–1.19), and dental visits in the past year (aOR, 1.09; 95% CI, 1.02–1.16)—were significantly associated with an increased risk of esophageal cancer. Additionally, claim-based periodontal disease was independently associated with elevated risk (aOR, 1.05; 95% CI, 1.01–1.09). Subgroup analyses revealed consistent associations across smoking and obesity strata, while sex-, age-, and alcohol-stratified analyses demonstrated differential patterns.

Conclusion

This study provides comprehensive, population-based evidence that both clinically assessed dental health indicators and behavioral oral hygiene practices are associated with esophageal cancer risk. The integration of screening-based and claims-based data enhances the validity of the findings and highlights oral health as a potential modifiable risk factor for esophageal cancer prevention.