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

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.

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.