Introduction

Colorectal cancer (CRC) remains a leading cause of cancer-related deaths in the U.S., with persistent disparities across racial and ethnic groups. Current uniform screening guidelines overlook population differences in risk. Polygenic risk scores (PRS) offer a pathway to personalized, risk-stratified screening, but their cost-effectiveness across diverse populations is unclear.

Aims & Methods

In this study, we estimated the cost-effectiveness of PRS-based, risk-stratified screening across four major U.S. racial and ethnic groups (White, Black, Asian and Hispanic), modelling lifetime costs, quality-adjusted life-years gained (QALYGs), and colonoscopy use to assess both overall and subgroup-specific outcomes.
PRS data from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) were used to stratify individuals into risk 40 groups. The microsimulation model MISCAN-Colon was used to determine the optimal colonoscopy screening strategy for each risk group within the racial and ethnic groups. Investigated strategies varied in terms of starting age (40–60 years), stopping age (70–85 years), and screening interval (5–15 years). Within each racial and ethnic group, the cost-effectiveness of the optimal strategies of the 40 risk groups was compared with uniform colonoscopy screening (ages 45–75, every 10 years).

Results

Risk-stratified screening produced different recommendations across risk levels and populations. For low-risk groups, strategies ranged from no screening in Whites and Blacks to a one-time colonoscopy at age 55 for Asians and at age 60 for Hispanics. In contrast, for high-risk groups, all populations benefited most from intensive screening with colonoscopy every 5 years from ages 40–85. Across all racial and ethnic groups, PRS-guided screening outperformed uniform strategies, preventing more CRC cases and deaths but at the cost of higher colonoscopy use and costs. In constrained analyses, when QALYGs were fixed to the level of uniform screening, risk-stratified screening reduced costs by 6–27% and when costs were fixed to the level of uniform screening QALYGs increased by 8–29% These efficiency gains were most pronounced in Hispanics (–27% costs; +29% QALYGs) and Asians (–14% costs; +13% QALYGs), with smaller but consistent improvements in Whites (-9% costs; +12% QALYGs) and Blacks (-6% costs; +8%QALYGs).

Table 1. Lifetime Effects and Costs per 1,000 40-Year-Old Individuals for No Screening, Uniform Screening, and PRS-Guided Risk-Stratified Screening at a $100,000/QALYG Threshold, With QALYGs- and Cost-Constrained Analyses, Stratified by Racial and Ethnic Group (Results only for Hispanics and Asians)
Asians

Conclusion

PRS-guided screening may offer a pathway to more tailored CRC prevention, with modest overall gains but potentially greater cost savings and health benefits in Hispanics and Asians.

References

1. Carethers JM. Racial and ethnic disparities in colorectal cancer incidence and mortality. Adv Cancer Res. 2021;151:197-229.
2. May FP, Yang L, Corona E, Glenn BA, Bastani R. Disparities in Colorectal Cancer Screening in the United States Before and After Implementation of the Affordable Care Act. Clin Gastroenterol Hepatol. 2020;18(8):1796-804 e2.
3. Dixon P, Keeney E, Taylor JC, Wordsworth S, Martin RM. Can polygenic risk scores contribute to cost-effective cancer screening? A systematic review. Genet Med. 2022;24(8):1604-17.
4. Tamlander M, Jermy B, Seppälä TT, Färkkilä M, FinnGen, Widén E, et al. Genome-wide polygenic risk scores for colorectal cancer have implications for risk-based screening. Br J Cancer. 2024;130(4):651-9.

Disclosure

No conflicts of interest.

Introduction

Colorectal cancer is one of the most prevalent cancers with an estimated 1.8 million newly developed cases and 0.9 million cancer-related deaths in 2020.Resection of adenomatous polyps decreases the incidence and mortality of colorectal cancer. Narrow-band imaging (NBI) and linked color imaging (LCI) are the most predominantly conducted image-enhanced endoscopy using short-wavelength light but their usefulness in screening and surveillance colonoscopy remains controversial.

Aims & Methods

Our aim in this study was to investigate the superiority of LCI over NBI for ADR.
This is an open-label, two-arm, parallel, 1:1, multicenter, randomized, controlled, right-sided colonoscopy study and included patients who underwent colonoscopy at six endoscopy centers in Japan from November 2020 through November 2023. The patients were randomly assigned to undergo a proximal-sided colonoscopy (cecum and ascending colon) with LCI or 2G-NBI followed by WLI. The primary outcome included the ADR and secondary outcomes involved polyp detection rate (PDR), polyp miss rate, and adenoma miss rate. This study was registered on November 4, 2020, in the Japan Registry of Clinical Trials (jRCT1012200007).

Results

During the study period, 1,655 patients were randomly assigned to the LCI group (828 patients, primary LCI followed by secondary WLI) and the 2G-NBI group (827 patients, primary 2G-NBI followed by secondary WLI), and 776 patients in the LCI group and 752 patients in the 2G-NBI groups were finally analyzed. The ADRs were 26.7% and 23.4% and the PDRs were 32.6% and 28.9% in primary LCI and 2G-NBI, respectively, with no statistically significant differences in ADR and PDR between groups (P = 0.14 and P = 0.12). However, multivariate regression analysis revealed primary LCI observation as an independent predictor for reducing PDR in the secondary WLI (Odds ratio [OR]: 0.72, 95% confidence interval [CI]: 0.53−0.97, P = 0.029). Moreover, polyp analysis demonstrated that miss rates of adenomas and polyps were significantly lower in the LCI group than in the NBI group (OR: 0.54, 95% CI: 0.39−0.76 in adenoma; OR: 0.59, 95% CI: 0.44−0.78 in polyp).

Conclusion

LCI is not superior to 2G-NBI in ADR and PDR in a clinical right-sided colonoscopy setting. However, LCI significantly reduced miss rates of adenomas and polyps.

Disclosure

Naohisa Yoshida has received lecture and/or consulting fees from Fujifilm and Olympus; Shoko Ono has received lecture and/or consulting fees from Fujifilm and Olympus; Momoko Tsuda has received lecture and/or consulting fees from Fujifilm; Nobuaki Yagi have received lecture and/or consulting fees from Fujifilm and Olympus; Mototsugu Kato has received lecture and/or consulting fees from Fujifilm. The remaining authors disclose no conflicts.

Introduction

Spasmolytic polypeptide expressing metaplasia (SPEM) is a cell repair lineage and is a very important phenotype of gastric mucosal injury and precancerous lesion.
Previously, parietal cells loss is considered as the first step and followed with chief cells transdiffernation to induce SPEM. But whether chief cells initial loss cause SPEM
needs to be further investigation. Acidic mammalian chitinase (CHIA) belongs to the 18 glycosidase family and is highly expressed in the chief cells. Our previous study showed that CHIA deficiency in the chief cells is the key event to induce SPME to progress to gastric cancer (Liu et al., DDW 2023 and 2024). However, the molecular role of CHIA in the development of SPEM is need further investigated.

Aims & Methods

Electron microscopy, qRT-PCR and single-cell sequencing (scRNA-seq) technology, as well as histopathological and immunofluorescence (IF) stainning with specific markers were performed in chief cells specific CHIA knockout mouse model (CHIA^rox/rox-GIF-Dre) and wild-type mice(CHIA^rox/rox), and in CHIA over - expression mice (CHIA ^rox/rox - GIF - Dre + rAAv - CHIA) and the control group (CHIA ^rox/rox - GIF - Dre + rAAv - control).

Results

Compared with CHIA^rox/rox mice, histological analysis and scRNA-seq technology data showed that loss of chief cells with increased M2 macrophage infiltration and final SPEM formation, but remaining of parietal cells in CHIA^rox/rox-GIF-Dre mice. Electron microscopy showed CHIA deficiency in mice resulted in endoplasmic reticulum was dilated and swollen, as well as the mitochondrial membrane was discontinuous of chief cells, followed with the accumulation of endoplasmic reticulum stress marker, including PERK, XBP-1, eIF2α/P-eIF2α, and GRP78, together with upregulation of pyroptosis-related marker, including NLRP3, ACS, GSDMD, NEK7, Caspase1, Caspase11, IL-1β, and IL-18, which was detected by qRT-PCR. These data indicating that target CHIA deletion caused chief cells pyroptosis. Furthermore, qRT-PCR analysis showed that CHIA deficiency caused the activation of IL33/IL-13 circuit in the mucosa of mice. Moreover, double immunofluorescence staining confirmed that upregulation and colocalization of IL-33 induced M2 macrophage polarization markers, including F4/80 and CD163⁺ with NLRP3 in the base of gastric mucosal of CHIA^rox/rox-GIF-Dre mice when compared with CHIA^rox/rox mice.Notably, CHIA ^rox/rox - GIF - Dre + rAvv - CHIA mice reversed the above process compared with controls.

Conclusion

Chief cells specific CHIA deficiency resulted in endoplasmic reticulum stress mediate NLRP3 inflammasome activation to induce chief cells proptosis.
Chief cells initial loss is sufficient and the key step to activate IL-33/ST2-M2 macrophage polarization axis to induce SPEM, which is independent of parietal cells loss.

Introduction

Corpus atrophic gastritis (CAG) requires endoscopic-histological surveillance due to the risk of developing gastric neoplastic lesions (GNL). This study aimed to identify variables associated with GNL development at long-term follow-up using a feature ranking method based on a novel One-Class Support Vector Machine (SVM) model.

Aims & Methods

A dataset containing clinical, endoscopic, and histological variables from consecutive CAG patients (2001-2023) adhering to a surveillance program was considered. GNL presence at the longest available follow-up was recorded. Gastric biopsies and histological evaluations were conducted according to the updated Sydney system. CAG patients with any missing data or a GNL diagnosis at the baseline gastroscopy were excluded from the final analysis. A Fisher score-based feature ranking method and One-Class SVM were used to select the optimal subset of baseline variables associated with GNL development, aiming to achieve average sensitivity (Se) and specificity (Sp) above 80%.

Results

Overall, 355 CAG patients were initially considered. Of these, 36 were excluded due to the presence of GNL at baseline gastroscopy, and 216 for missing data. Thus, a total of 103 patients were considered and grouped into: CAG patients with [22 patients (F 68.1%), median age 68 (35-83) years] and without GNL at follow-up [81 patients (F 72.8%), median age 59(26-84) years]. After a median follow-up of 60 (12-192) months, 13 epithelial GNL (gastric adenocarcinoma or high/low-grade dysplasia) and nine type-1 gastric-neuroendocrine-tumors (T1gNET) were recorded. Parietal-cell-antibodies and pepsinogen-I < 30 μg/l were associated with both epithelial GNL and T1gNET. Antral inflammation and age > 60 were linked to epithelial GNL, while anti-thyroperoxidase-antibodies, smoking, and dyspeptic symptoms at CAG diagnosis were linked to T1gNET. Low-dose aspirin and H. pylori eradication therapy showed inverse associations with epithelial GNL and T1gNET, respectively.

Conclusion

This is the first study in which an AI model simultaneously considers clinical, endoscopic, and histological characteristics from a dataset of CAG patients, showing good sensitivity and specificity in identifying those variables associated with developing GNL. Nonetheless, we acknowledge the need for improved variable standardization and data balancing between groups to enhance model performance further.

Introduction

Inflammatory Bowel Disease (IBD)^1,2 requires close monitoring to detect flare ups early and guide treatment. While endoscopy is the gold standard, it is invasive, costly, and uncomfortable^1,2. Intestinal Ultrasound (IUS) is a non-invasive alternative with strong correlation to endoscopic findings—especially bowel wall thickness (BWT), a marker of disease activity³. Nevertheless, IUS remains limited due to operator dependence and a steep learning curve⁴.
AI has improved consistency in other domains, e.g. endoscopic evaluation, but its application to IUS in IBD remains underexplored. Prior models lack interpretability and require manual image cropping, or are trained on ideal, selected data, limiting clinical use^5,6.

Aims & Methods

We aim to develop a deep-learning model that automatically identifies and paints the bowel wall and measures BWT directly from raw clinical IUS images.
A training dataset of 570 images from 144 IUS videos and a testing dataset of 55 images from 55 separate exams were created. All images were extracted from previously performed IUS examinations reflecting real-world variation, including e.g. unclear boundaries and artefacts.
All images were annotated by International Bowel Ultrasound Group (IBUS) certified experts, including outline-paintings of the inner and outer bowel wall and two BWT measurements.
The AI consists of a combination of Convolutional neural networks and other image processing algorithms.
Evaluation included BWT error against the expert mean, classification accuracy using the standard IBUS 3 mm threshold³, and a leave-one-out comparison with individual doctors.

Results

The model produced predictions on 54 of 55 test images.
The model deviated from the gold standard mean by 0.98 mm (SD 1.1 mm) per image on the regression task. The average distance to expert-defined bounds was 0.44 mm (SD 0.89 mm), with 59% of predictions inside this range.
For classification (using a 3 mm threshold), the model reached an accuracy of 0.77, sensitivity of 0.69, specificity of 0.94, and Cohen’s Kappa of 0.56.
In the leave-one-out analysis, expert performance ranged from 0.89–0.93 accuracy and 0.79–0.83 Kappa. Depending on which expert was excluded from the gold standard, the model achieved 0.74–0.80 accuracy and 0.49–0.60 Kappa. Experts stayed within expert-defined bounds in 72–81% of cases, while the model did so in 46–55%.

Conclusion

Clinically, the model performed well. An error of 0.5–1 mm is negligible in practice and matches typical variation in manual measurements. Many real-world test images had BWT values near the 3 mm threshold, so small deviations led to misclassifications. In practice, a 2.5 mm reading could still raise concerns based on symptoms³.
While the system alone cannot provide expert-level BWT measurements, it could provide assistance to experts as well as non-expert and junior doctors, especially in locating the bowel, which is an essential part of IUS.
The model works on unprocessed clinical data, with the only selection criteria being that there is an identifiable bowel segment, measurable by an IBUS-certified doctor. Allowing the images to reflect realistic conditions
In summary, we developed an AI model that identifies the bowel and measures BWT with acceptable accuracy. We have already started the processes of collecting video data, to extend the AI’s functionality to a fully clinical setting.

References

1. Torres J, Mehandru S, Colombel JF, Peyrin-Biroulet L. Crohn’s disease. The Lancet. 2017;389(10080):1741-1755. doi:10.1016/S0140-6736(16)31711-1
2. Ungaro R, Mehandru S, Allen PB, Peyrin-Biroulet L, Colombel JF. Ulcerative colitis. Lancet. 2017;389(10080):1756-1770. doi:10.1016/S0140-6736(16)32126-2
3. Novak KL, Group I, Nylund K, et al. Expert Consensus on Optimal Acquisition and Development of the International Bowel Ultrasound Segmental Activity Score [IBUS-SAS]: A Reliability and Inter-rater Variability Study on Intestinal Ultrasonography in Crohn’s Disease. J Crohns Colitis. 2021;15(4):609-616. doi:10.1093/ECCO-JCC/JJAA216
4 Bove L, Meyer J, Collins M, Frampas E, Bourreille A, Le Berre C. Understanding the learning curve of intestinal ultrasound in inflammatory bowel disease: A comparative study between novice, regular, and expert. Clin Res Hepatol Gastroenterol. 2025;49(3):102548. doi:10.1016/J.CLINRE.2025.102548
5. Kumaralingam L, Le May K, Dang VB, Alavi J, Huynh HQ, Le LH. Artificial intelligence-assisted approach to assessing bowel wall thickness in pediatric inflammatory bowel disease using intestinal ultrasound images. J Crohns Colitis. 2025;19(4). doi:10.1093/ECCO-JCC/JJAF037
6. Carter D, Albshesh A, Shimon C, et al. Automatized Detection of Crohn’s Disease in Intestinal Ultrasound Using Convolutional Neural Network. Inflamm Bowel Dis. February 2023:1-6. doi:10.1093/IBD/IZAD014

Introduction

Immune checkpoint inhibitors (ICIs) have marked a breakthrough in the management of a wide range of cancer types, leading to increased overall survival. However, this treatment is frequently associated with the onset of various immune-related adverse events (irAEs), including ICI-related diarrhea and colitis.¹ Current recommendations for patients with diarrhea or colitis grade 2 or higher (graded via CTCAE)² include the discontinuation of ICI and administration of immune suppressants (e.g. steroids or biologics), which may lead to worse outcomes in these patients.³ Therefore, alternative therapeutic strategies to manage irAEs are needed. The gut microbiota plays a pivotal role in the onset of gastrointestinal irAEs, but the role of its therapeutic modulation on these disorders is mostly unknown. ^4,5

Aims & Methods

Our aim was to evaluate the efficacy and safety of therapeutic microbiome modulation for gastrointestinal irAEs in cancer patients. We enrolled cancer patients affected by ICI-related diarrhea/colitis referred to our Microbiome Clinic from January 2023 to March 2025. After clinical evaluation, patients were stratified according to severity of diarrhea (graded via CTCAE)² and then received a microbiome-modulating therapy. Patients were followed-up for at least 8 week after the initiation of therapy. We collected data about patient demographics (age and gender), patient’s overall health status as assessed by the the Charlson Comorbidity Index (CCI)⁶, type of cancer, oncological therapy and its suspension, time in weeks from initiation of cancer therapy to onset of diarrhea, severity of diarrhea (graded via CTCAE)², time in weeks until resolution of diarrhea and resumption of oncological therapy

Results

We enrolled 42 patients in the study period (8 males, 34 females, mean age 58,3 years-old, mean CCI-index 5.8). All patients were treated with ICI (Pembrolizumab: n=25 , Dostarlimab: n=4, Nivolumab: n=4; Atezolizumab: n=3; Novulumab and Ipilumab: n=2, Cemiplimab: n=2; Mogamulizumab: n=1; Pertuzumab: n=1). Ten patients experienced G1 diarrhea (23,8%), 16 (38,1) G2, 15 (35,7%) G3 and one G4 (2,4%). As indicated by current European Guidelines³, 30 patients (71,4%) had to interrupt ICI due to diarrhea. Multi-strain probiotics were administered to 27 (64.3% ) patients, rifaximin to 22 (52,4%). Overall, 21 patients (50%) needed therapy with systemic steroids. Seven patients who experienced ICI-related colitis refractory to steroids and biologics were successfully treated with FMT. Twenty-eight patients (66.7% ) had a resolution of the diarrhea (G0) and 11 patients (26.2%) had diarrhea G1 at a mean time of 8 weeks. Upon resolution of diarrhea, nine of the 30 patients who had interrupted ICI (30%) were able to resume the treatment. None of the patients experienced any adverse event related to gut microbiota modulation as defined by CTCAE².

Conclusion

Therapeutic modulation of gut microbiota appears to be a promising safe and effective approach for treating ICI-related diarrhea and colitis. However, these preliminary findings need confirmation through more consolidated and well-designed studies.

References

1. Dougan M, Wang Y, Rubio-Tapia A, Lim JK. AGA Clinical Practice Update on Diagnosis and Management of Immune Checkpoint Inhibitor Colitis and Hepatitis: Expert Review. Gastroenterology. 2021;160(4):1384-1393. doi:10.1053/j.gastro.2020.08.063
2. Freites-Martinez A, Santana N, Arias-Santiago S, Viera A. Using the Common Terminology Criteria for Adverse Events (CTCAE - Version 5.0) to Evaluate the Severity of Adverse Events of Anticancer Therapies. Actas Dermosifiliogr. 2021;112(1):90-92. doi:10.1016/j.ad.2019.05.009
3. Haanen J, Obeid M, Spain L, et al. Management of toxicities from immunotherapy: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol. 2022;33(12):1217-1238. doi:10.1016/j.annonc.2022.10.001
4. Wang Y, Wiesnoski DH, Helmink BA, et al. Fecal microbiota transplantation for refractory immune checkpoint inhibitor-associated colitis. Nat Med. 2018;24(12):1804-1808. doi:10.1038/s41591-018-0238-9
5. Wang T, Zheng N, Luo Q, et al. Probiotics Lactobacillus reuteri Abrogates Immune Checkpoint Blockade-Associated Colitis by Inhibiting Group 3 Innate Lymphoid Cells. Front Immunol. 2019;10. doi:10.3389/fimmu.2019.01235
6. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8

Disclosure

G.I. has received personal fees for acting as speaker for Biocodex, Danone, Sofar, Malesci, Metagenics and Tillotts Pharma, and for acting as consultant and/or advisor for Ferring Therapeutics, Giuliani, Malesci and Tillotts Pharma. A.G. reports personal fees for consultancy from Eisai Srl, 3PSolutions, Real Time Meeting, Fondazione Istituto Danone, SinergieSrl, Board MRGE and Sanofi SpA personal fees for acting as a speaker for Takeda SpA, AbbVie and Sandoz SpA and personal fees for acting on advisory boards for VSL3 and Eisai. G.C. has received personal fees for acting as advisor for Ferring Therapeutics. All other authors have no conflicts of interest to disclose.