Active clinical trials for "Metaplasia"

Since much is unknown about factors that lead to progression of the pre-neoplastic lesions and cancer. In addition, there is ongoing debate on the optimal surveillance intervals and techniques. To solve these important clinical questions, the establishment of a registry for a longitudinal study is planned.

The project will aim to identify and determine subgroups of patients with different risks of progression to gastric cancer and to assess appropriate follow-up intervals. Implementing risk stratification only high risk individuals will be offered and performed endoscopic surveillance.

Patients with suspected extra-esophageal manifestations of gastro-esophageal reflux disease (GERD), such as cough, hoarseness, and globus, are often referred for pH testing. However, many of these symptoms may actually be due to an esophageal inlet patch. We aim to evaluate patients referred for pH testing to see if they have an inlet patch, to perform ablation of the inlet patch if detected, and then compare the outcomes of patients with an inlet patch who underwent ablation versus those without an inlet patch.

Detection of Volatile Organic Compounds (VOC) directly from tissue by headspace analysis (skin, surgery material, other tissue) and exhaled breath is feasible using affordable user-friendly novel nano-chemo sensors that can accurately be used for screening and monitoring purpose

To establish a prospective cohort of individuals diagnosed with gastric pre-malignant conditions (chronic gastritis, atrophic gastritis, autoimmune gastritis, intestinal metaplasia, intestinal dysplasia) to monitor and study disease progression. The Investigators will like to survey cohort participants for lifestyle behaviors and environmental exposures associated with gastric pre-malignancy and cancer. Analyzing patient biospecimens to identify and characterize host and microbiome biomarkers associated with initiation and progression of gastric pre-malignancies.

The goal of this observational study is to learn about the key bacterial flora and metabolites associated with appendicitis in children. The main questions it aims to answer are: To screen out the key biomarkers of pediatric appendicitis. What are the microbial differences in different parts of pediatric appendicitis patients. Participants will detect feces using 16s ribosomal RiboNucleicAcid (16S rRNA) gene sequencing technology and differences of the fecal metabolites between healthy children and appendicitis children were analyzed using untargeted metabolomics based on Liquid chromatography-tandem mass spectrometry(LC-M S/MS) platform.Through the analysis of intestinal bacterial flora and metabolomics association and the differential analysis of intestinal bacterial flora in different parts of the case group, the key bacterial flora and metabolites were excavated.

Gastric cancer afflicts 27,000 Americans annually and carries a dismal prognosis. One reason for poor outcomes is late diagnosis, as the majority of gastric cancers in the United States are diagnosed at a relatively advanced stage where curative resection is unlikely. Gastric intestinal metaplasia (GIM) is a precancerous change of the stomach which increases risk for subsequent gastric cancer multiple-fold. The Gastric Precancerous Conditions Study (GAPS) is an observational study with two over-arching objectives: 1) improve the non-invasive identification of patients with GIM, and 2) develop biological markers to predict the subset of GIM which will progress onto gastric cancer. To achieve Aim 1, a case-control study (N=300 pairs) matching cases of GIM with age-/gender-matched controls will be recruited form the population of subjects undergoing clinically-indicated endoscopy. Determination of gastric pathology will be made by two, independent gastrointestinal pathologists. At time of endoscopy, a detailed clinical questionnaire is administered by face-to-face interview. Saliva and blood is collected prior to endoscopy. At time of endoscopy, protocoled clinical biopsies (per Revised Sydney Protocol) as well as additional research specimens are collected. Scoring of GIM will be performed based on the Operative Link for GIM scoring system. To achieve Aim 2, patients with histologically-confirmed GIM (N=300) will be followed longitudinally. Biennial endoscopic surveillance will be performed, with repeat biopsies, specimen collection, and histologic scoring. Progression of GIM will be defined as upstaging of GIM score, or development of either dysplasia or carcinoma on any biopsy.

This is a multi-center prospective case control study aiming to compare different methods of risk stratification models in predicting the risk of gastric cancer development.

Currently, the Correa cascade is a widely accepted model of gastric carcinogenesis. Intestinal metaplasia is a high risk factor for gastric cancer. According to Sydney criteria, mild intestinal metaplasia was not associated with gastric cancer, while moderate to severe intestinal metaplasia was strongly associated with the development of gastric cancer. Because intestinal metaplasia is distributed in various forms, the use of white light endoscopy lacks specificity, and the consistency with histopathological diagnosis is poor; Pathological biopsy is still needed to make a diagnosis. At present, national guidelines suggest that OLGIM score should be used to evaluate the risk of gastric cancer, and patients with OLGIM grade III/IV should be monitored by close gastroscopy. However, it requires at least four biopsies, which is clinically infeasible. Confocal laser endomicroscopy allows real-time observation of living tissue, comparable to pathological findings.

Gastric intestinal metaplasia(GIM) is an important stage in the gastric cancer(GC). With technical advance of image-enhanced endoscopy (IEE), studies have demonstrated IEE has high accuracy for diagnosis of GIM. The endoscopic grading system (EGGIM), a new endoscopic risk scoring system for GC, have been shown to accurately identify a wide range of patients with GIM. However, the high diagnostic accuracy of GIM using IEE and EGGIM assessments performed all require much experience, which limits the application of EGGIM. The investigators aim to design a computer-aided diagnosis program using deep neural network to automatically evaluate the extent of IM and calculate the EGGIM scores.