The EpiGASTRIC/EDGAR Project: New Strategies for the Early Detection and Prevention of Gastric Cancer

Overview

This study is a multicenter, prospective cohort study, which are planned to enroll at least 600 patients who diagnosed the primary gastric cancer (GC); around 50 patients with premalignant gastric lesions (PGLs) and early gastric neoplasias (EGC) treated by endoscopy resection; and no less than 600 healthy normal cohort participants, for more than 18 months in the Spanish population. All participants who enrolled in this registry will be questioned by the life habits survey; and clinical data and biological samples of these participants were analyzed in order to look for new diagnostic tools. The aim of this study is to evaluate clinical, endoscopic and molecular approaches to identify individuals with high-risk of GC. Thus, it would be allow the adoption of preventive measures to reduce mortality through early detection and/or the reduction of its incidence.

Gastric cancer (GC) is the fifth most common and the third more deadly cancer in the world. In Spain, the incidence is 7.8 cases per 100,000 inhabitants, being twice as frequent in men as in women. During 2020, 7.577 new cases were diagnosed and approximately 5201 deaths occurred (Spanish association against cancer, AECC). Most cases are diagnosed in an advanced stage with a 5-year survival rate lower than 30%, which highlights the great importance of an early diagnosis. Thus, this study aims to evaluate clinical, endoscopic and molecular approaches to identify individuals with high-risk of GC. Methods: Coordinate and prospective project that considers the gender dimension of population-based study within a collaborative network. It includes different but interrelated cohorts: 1. "EDGAR 1": symptomatic patients undergoing a diagnostic gastroscopy to study the prevalence of PGLs; 2. "EDGAR 2": PGLs and EGC with indication for endoscopic resection; 3. "EPIGASTRIC": patients diagnosed with GC; 4. CONTROLS: patients without gastric pathology or a familial history of GC, obtained from the cohort EDGAR1. Although GC diagnosis has been characterized by endoscopy, there has been a strong demand for low or non-invasive methods of GC detection. In this sense, clinical information and biological samples obtained by less invasive methods will be collected prospectively from the participating centers. State-of-the-art high-definition endoscopy and multiomic techniques will be used to perform: * Clinical studies: Study the prevalence of GC and PGLs and genetic and environmental predisposing factors. Evaluation of high-definition endoscopy efficacy in the detection of PGLs and EGC. Concordance between endoscopic and histological classifications of PGLs. Estimate the risk of PGLs progression according to the follow-up of the lesions. Identification of GC-high-risk individuals, based on clinical data, familial factors, PGLs and a life habits survey. * Translational studies: Identify and validate nucleic acids and proteins as new biomarkers of GC and PGLs in biological samples obtained by low or non-invasive methods and comparison with those obtained from histological samples and with the traditional markers used in GC diagnosis. Given the multicenter nature of this project, standard operating procedures (SOPs) have also been established for the collection, processing, storage, and management of biological samples, so that it is carried out in the same way in all participating centers. The data will be collected on the REDCap-AEG online platform, which can be accessed by researchers from each center through an identification code, respecting the current Organic Law on Data Protection. For patient registries, a specific database has been designed for each subproject (EDGAR 1, EDGAR 2 and EPIGASTRIC). This guarantees the quality of the data and allows its verification, as it defines, classifies and illustrates the different parameters to be assessed by the participating researchers. Finally, it allows the codification and anonymization of the data entered, which guarantees compliance with the data protection law of this study. Statistical analysis: The SPSS program (IBM, NY) and/or the R software (https://www.r-project.org/) will be used. The differences between qualitative variables will be compared using Fisher's test. The quantitative variables will be analyzed using a non-parametric test (Mann-Whitney or Kruskall-Wallis for unpaired samples and Wilcoxon for paired samples). A "p" value \<0.05 will be considered statistically significant. All the registered variables will be studied to determine their association with the diagnosis by means of univariate and multivariate logistic regression analysis. In addition, through an interaction study, we will evaluate whether there are risk factors associated with the presence/prognosis of lesions that differentially affect subgroups of patients.