Introduction

Guselkumab (GUS), a dual-acting interleukin-23p19 subunit inhibitor, demonstrated efficacy in participants (pts) with ulcerative colitis (UC) treated with intravenous (IV) or subcutaneous (SC) induction. Here, we report the efficacy and safety of SC induction followed by SC maintenance through Week (W) 48 in ASTRO, a phase 3, randomized, double-blind, placebo (PBO)-controlled, treat-through study in pts with moderately to severely active UC.

Aims & Methods

Eligible pts had modified Mayo scores of 5 to 9, rectal bleeding subscore of ≥1, and Mayo endoscopic subscore (MES) ≥2. Pts also had documented inadequate response/intolerance to biologics, Janus kinase (JAK) inhibitors, and/or sphingosine-1-phosphate (S1P) inhibitors (BIO/JAKi/S1Pi-IR) or to corticosteroids, 6-mercaptopurine, or azathioprine. Randomization was stratified by baseline BIO/JAKi/S1Pi-IR status and MES with 418 pts allocated 1:1:1 to GUS 400 mg SC every 4 weeks (q4w) (×3)→GUS 200 mg SC q4w (N=140), GUS 400 mg SC q4w (×3)→GUS 100 mg SC every 8 weeks (q8w) (N=139), or PBO SC (N=139). PBO pts who met rescue criteria were switched to GUS at W16; GUS pts who met rescue criteria stayed on their assigned GUS dose regimen (sham rescue).

Results

At W48, greater proportions of pts in the GUS groups achieved clinical remission compared with PBO (36.7% for GUS 100 mg q8w [Δ 29.5%], 42.9% for GUS 200 mg q4w [Δ 35.6%], 7.2% for PBO) (Table). Endoscopic remission proportions were 25.9% for GUS 100 mg q8w (Δ 20.9%), 26.4% for GUS 200 mg q4w (Δ 21.4%), and 5.0% for PBO. Clinical response, symptomatic remission, endoscopic improvement, histologic improvement, and histologic remission proportions were also greater for GUS vs PBO. Consistent with the results of the overall population, efficacy was also observed for subpopulations of BIO/JAKi/S1Pi-naïve and BIO/JAKi/S1Pi-IR pts. Safety events per 100 pts-years were not greater in the GUS groups compared with the PBO group: adverse events (AE) (GUS 100 mg q8w and 200 mg q4w vs PBO: 308.3 and 310.7 vs 357.1), serious AEs (6.5 and 8.2 vs 38.4), serious infections (0.8 and 2.5 vs 3.7), and AEs leading to treatment discontinuation (4.9 and 4.1 vs 19.8).
Table. Efficacy endpoints at Week 48 in the overall population and by biologic, JAK inhibitor, and/or S1P inhibitor history

Conclusion

GUS SC induction followed by SC maintenance was efficacious through 1 year in pts with moderately to severely active UC, and the safety profile is consistent with GUS in its approved indications including UC.

Disclosure

ML reports research support from Lilly, Pfizer, and Takeda; consulting for AbbVie, Bristol Myers Squibb, Intercept, Janssen (Johnson & Johnson), Lilly, Pfizer, Prometheus, Roivant, Takeda, and Target RWE.
JRA reports grant support from Janssen, Merck, and Pfizer; consultancy fees from AbbVie, Adiso, Bristol Myers Squibb, Ferring, Genentech, GlaxoSmithKline, Janssen, Merck, Pfizer, Roivant, Celltrion, TrexBio, Shattuck Labs and Seres Therapeutics; payments for speaking from AbbVie, Bristol Myers Squibb, and Janssen; and is a steering committee member and investigator for Janssen.
SD reports consultancy fees from AbbVie, Alimentiv, Allergan, Amgen, AstraZeneca, Athos, Biogen, Boehringer Ingelheim, Celgene, Celltrion, Eli Lilly, Enthera, Ferring, Gilead, Hospira, Inotrem, Janssen, Johnson & Johnson, MSD, Mundipharma, Mylan, Pfizer, Roche, Sandoz, Sublimity, Takeda, TiGenix, UCB, and Vifor; and reports lecture fees from AbbVie, Amgen, Ferring, Gilead, Janssen, Mylan, Pfizer, and Takeda.
MG, TB, YA, KH, SJ, LJ, and HZ are employees of and may own stock in Johnson & Johnson.
TH reports research grants from AbbVie GK, Boston Scientific Corporation, EA Pharma Co. Ltd., JIMRO Co. Ltd., Kissei Pharmaceutical Co. Ltd., Kyorin Pharmaceutical Co. Ltd., Mitsubishi Tanabe Pharma Corporation, Mochida Pharmaceutical Co. Ltd., Nippon Kayaku Co. Ltd., Pfizer Inc., Takeda Pharmaceutical Co. Ltd., and Zeria Pharmaceutical Co. Ltd.; consulting fees from AbbVie GK, Abivax, Bristol Myers Squibb, EA Pharma Co. Ltd., Gilead Sciences, Janssen Pharmaceutical K.K., Lilly, Mitsubishi Tanabe Pharma Corporation, and Pfizer Inc.; and lecture fees from AbbVie GK, EA Pharma Co. Ltd., Janssen Pharmaceutical K.K., JIMRO Co., Kissei Pharmaceutical Co. Ltd., Kyorin Pharmaceutical Co. Ltd., Mitsubishi Tanabe Pharma Corporation, Mochida Pharmaceutical Co., Ltd., Pfizer Inc., and Takeda Pharmaceutical Co. Ltd.
DTR reports consulting and/or speaker fees and/or advisory board participation for AbbVie, Altrubio, Apex, Avalo, Bristol Myers Squibb, Buhlmann Diagnostics, Celgene, Connect BioPharma, Intouch Group, Iterative Health, Janssen (Johnson & Johnson), Lilly, Pfizer, Samsung Neurologica, and Takeda; Altrubio, Datos Health, and Iterative Health stock options; grants from Takeda; and membership on the Board of Directors of Cornerstones Health, Inc. and on the Crohn’s & Colitis Foundation’s Board of Trustees.
LPB reports grants or contracts from Celltrion, Fresenius Kabi, Medac, MSD, and Takeda; consulting and/or payment or honoraria and/or data safety monitoring board or advisory board participation for AbbVie, Abivax, Adacyte, Alfasigma, Alimentiv, Amgen, Applied Molecular Transport, Arena, Banook, Biogen, Bristol Myers Squibb, Celltrion, Connect Biopharm, Cytoki Pharma, Enthera, Ferring, Fresenius Kabi, Galapagos, Genentech, Gilead, Gossamer Bio, GlaxoSmithKline, IAC Image Analysis, Index Pharmaceuticals, Inotrem, Janssen, Kern Pharma, Lilly, Medac, Mopac, Morphic, MSD, Nordic Pharma, Novartis, Oncodesign Precision Medicine, ONO Pharma, OSE Immunotherapeutics, Pandion Therapeutics, Par' Immune, Pfizer, Prometheus, Protagonist, Roche, Samsung, Sandoz, Sanofi, Satisfay, Takeda, Telavant, Theravance, Thermo Fischer, Tigenix, Tillots, Viatris, Vectivbio, Ventyx, and Ysopia; and meeting attendance/travel support from AbbVie, Alfasigma, Amgen, Celltrion, Connect Biopharm, Ferring, Galapagos, Genentech, Gilead, Gossamer Bio, Janssen, Lilly, Medac, Morphic, MSD, Pfizer, Sandoz, Takeda, Thermo Fischer, and Tillots.

Introduction

Microscopic colitis (MC) refers to two pathologies – Collagenous colitis (CC) and Lymphocytic colitis (LC) that cause chronic watery diarrhoea, urgency, incontinence leading to significantly decreased quality of life¹. It is thought that MC develops due to a pathological immune response to intestinal luminal antigens in genetically predisposed individuals, with microbiota playing an important role^{2, 3}. However, the pathogenesis of MC is still unclear.

Aims & Methods

The aim of this study was to identify and characterize changes in bacterial composition of MC patients in terminal ileum and different colonic segments and determine its relation to the clinical course of disease. Biopsies from terminal ileum and six segments of the colon were collected during diagnostic colonoscopies. DNA extraction was performed using AllPrep DNA/RNA Micro Kit (Qiagen) following the manufacturer’s instructions. To determine bacterial composition, sequencing of the 16S rRNA variable region V3-V4 was conducted using the 27F and 338R polymerase chain reaction primers and sequenced on a MiSeq (2×250 bp; Illumina, Hayward, CA). Bioinformatic analysis was performed using DADA2, and taxonomic classification was carried out with the RDP classifier.

Results

Biopsy samples from 20 active CC patients, 20 active LC patients, and 50 controls demonstrated distinct microbial profiles across different intestinal segments, as revealed by beta-diversity and differential compositional analyses. Compared with controls, CC patients had consistent alterations in three bacterial families throughout the entire colon, with Erysipelatoclostridiaceae and Coriobacteriaceae decreased and Pasteurellaceae increased. Additionally, 35 families had segment-specific changes, and 25 families displayed altered abundance in the terminal ileum.
LC patients exhibited a consistent increase in Erisypelotrichaceae across the entire colon, with 38 other families showing segmental changes, and 12 families displaying altered abundance in the terminal ileum. Comparing LC and CC revealed a significantly different bacterial profile. LC showed lower abundance across many families, particularly in the right colon and terminal ileum. After sample collection, 15 CC patients and 12 LC patients received budesonide, with 3 CC and 2 LC patients having incomplete response. Beta diversity analysis revealed significant differences in the ascending colon and left side of the colon of CC patients based on response to budesonide. Patients with incomplete response to budesonide had an increased abundance of the genus Paucibacter. Similar tendencies were not observed in LC.
1 CC patient exhibited a quiescent disease course, 6 reached a sustained remission after treatment, 7 had a relapsing and 6 had a chronic active disease. Significant differences in beta diversity were observed in transverse, descending colon and rectum. Beta diversity of the descending colon had a medium correlation with disease behaviour. In the LC group 6 patients had a quiescent disease, 8 had a sustained remission after treatment, 3 exhibited a relapsing and 4 had a chronic active disease. No significant correlation between microbiota and disease behaviour was observed in LC.

Conclusion

This study showed significant differences in bacterial composition between CC, LC and controls in the terminal ileum and colon. In both CC and LC, bacterial alterations were not consistent throughout the entire colon but varied between different colonic segments. Microbiome differences based on response to budesonide and disease behaviour were observed in CC, but not LC.

References

1. Verhaegh BPM, Münch A, Guagnozzi D, et al. Course of Disease in Patients with Microscopic Colitis: A European Prospective Incident Cohort Study. J Crohns Colitis. 2021;15(7):1174-1183.
2. Miehlke S, Guagnozzi D, Zabana Y, et al. European guidelines on microscopic colitis: United European Gastroenterology (UEG) and European Microscopic Colitis Group (EMCG) statements and recommendations. United European Gastroenterol J. Published online 2020.
3. Burke KE, D’Amato M, Ng SC, Pardi DS, Ludvigsson JF, Khalili H. Microscopic colitis. Nat Rev Dis Primers. 2021;7(1).

Introduction

Endoscopic ultrasound (EUS) is the gold standard for evaluating pancreatic lesions, allowing for real-time imaging and biopsy sampling. Nevertheless, the differentiation between solid pancreatic lesions — such as pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine tumors (PNETs) — as well as cystic lesions is often troublesome. Specifically, identifying intraductal papillary mucinous neoplasms (IPMNs) with varying degrees of dysplasia is crucial for guiding clinical management. However, the diagnostic accuracy of current methods remains suboptimal. This multicenter study aimed to develop and validate convolutional neural networks (CNNs) to characterize solid and cystic pancreatic lesions and stratify IPMNs into high-grade dysplasia/carcinoma (HGD/C) and low-grade dysplasia (LGD).

Aims & Methods

This multicenter study included EUS images from 12 centers in Spain, Brazil, the United Kingdom and the United States of America. Solid lesion differentiation (PDAC vs. PNET) was achieved using a CNN trained on 49034 images from 95 patients (n=69 for PDAC and n=26 for PNET), with diagnoses confirmed via EUS-guided fine-needle biopsy or surgical specimen analysis. A second CNN was trained on 79395 images from 82 patients (n=64 for mucinous cystic lesions and n=18 for non-mucinous cystic lesions). Finally, a third model used the subset of IPMNs (n=51046 frames, 30 patients) to distinguish between HGD/C (n=5 patients) and LGD (n=25 patients). Histological confirmation was used as the gold standard. Performance metrics included sensitivity, specificity, accuracy, and area under the precision-recall curve (AUC-PR). To comprehensively determine the model's performance, we evaluated multiple thresholds for the confidence score and the IoU, between 0.45 and 0.55 with a step of 0.02 ([0.45, 0.47, 0.50, 0.52, 0.55]). The datasets were split into training (70%), validation (20%), and testing (10%) subsets.

Results

For solid lesions, the model differentiated PDAC from PNETs with an accuracy of 91.8%, with sensitivities of 96.2% and 97.8%, respectively. The AUC-PR was 0.982 for PDAC and 0.977 for PNET. Regarding cystic lesions the model detected mucinous cystic lesions with a sensitivity of 97.5%, an overall accuracy of 89.7% and an AUC-PR of 0.977. When the subset of IPMNs was specifically analyzed, the model distinguished IPMNs with HGD/C from those with LGD with a sensitivity of 97.5%, specificity of 94.3%, and an overall accuracy of 89.8%. The AUC was 0.988.

Conclusion

This is the first multicenter, transatlantic AI study aiming to provide a holistic approach to both solid and cystic pancreatic lesions, focusing on those with a significantly higher malignant potential. Our models achieved high accuracy in identifying and differentiating these conditions. Furthermore, to our knowledge this is the first integrative model to include the ability to stratify IPMNs into LGD and HGD/C, which has significant clinical implications, potentially reducing unnecessary surgeries and ensuring timely intervention for high-risk patients. The inclusion of data from diverse regions reduces demographic bias and enhances model generalizability. Real-time implementation of these solutions could significantly improve decision-making in EUS and optimize patient outcomes.