Interactive decision support for esophageal adenocarcinoma screening and surveillance

Evolution and progression of Barrett's oesophagus to oesophageal cancer

Cancer cells are shaped through an evolutionary process of DNA mutation, cell selection and population expansion. Early steps in this process are driven by a set of mutated driver genes and structural alterations to the genome through copy number gains or losses. Oesophageal adenocarcinoma (EAC) and the pre-invasive tissue, Barrett's oesophagus (BE), provide an ideal example in which to observe and study this evolution. BE displays early genomic instability, specifically in copy number changes that may later be observed in EAC. Furthermore, these early changes result in patterns of progression (that is, 'born bad', gradual or catastrophic) that may help to describe the evolution of EAC. As only a small proportion of patients with BE will go on to develop cancer, a better understanding of these patterns and the resulting genomic changes should improve early detection in EAC and may provide clues for the evolution of cancer more broadly.

Best Practices in Surveillance for Barrett's Esophagus

Barrett's esophagus is the precursor lesion for esophageal adenocarcinoma. The goals of endoscopic surveillance are to detect dysplasia and early esophageal adenocarcinoma in order to improve patient outcomes. Despite the ongoing debate regarding the efficacy of surveillance, all current gastrointestinal societies recommend surveillance at this time. Optimal surveillance technique includes adequate inspection time, evaluation using high-definition white light and chromoendoscopy, appropriate documentation of the metaplastic segment using the Prague C & M criteria as well as the Paris classification should lesions be found, utilization of the Seattle biopsy protocol, and endoscopic resection of visible lesions.

Epidemiology of Barrett's Esophagus and Esophageal Adenocarcinoma: Implications for Screening and Surveillance

In the United States, the incidence of esophageal adenocarcinoma increased markedly since the 1970s with a recent stabilization. Despite evolving screening and surveillance strategies to diagnose, risk triage, and intervene in Barrett's esophagus patients to prevent esophageal adenocarcinoma, most cases present with advanced disease and poor resultant survival. Epidemiologic studies have identified the main risk factors for these conditions, including increasing age, male sex, white race, gastroesophageal reflux disease, abdominal obesity, cigarette smoking, and lack of infection with Helicobacter pylori. This review summarizes the current epidemiologic evidence with implications for screening and surveillance in Barrett's esophagus and esophageal adenocarcinoma.

G. H, Macleod A, Prasanth M, Zafar M, Hemadasa N, Neagle G, Rosindell I, Apollos J. A predictive Bayesian network that risk stratifies patients undergoing Barrett's surveillance for personalized risk of developing malignancy

BACKGROUND

Barrett's esophagus is strongly associated with esophageal adenocarcinoma. Considering costs and risks associated with invasive surveillance endoscopies better methods of risk stratification are required to assist decision-making and move toward more personalised tailoring of Barrett's surveillance.

METHODS

A Bayesian network was created by synthesizing data from published studies analysing risk factors for developing adenocarcinoma in Barrett's oesophagus through a two-stage weighting process.

RESULTS

Data was synthesized from 114 studies (n = 394,827) to create the Bayesian network, which was validated against a prospectively maintained institutional database (n = 571). Version 1 contained 10 variables (dysplasia, gender, age, Barrett's segment length, statin use, proton pump inhibitor use, BMI, smoking, aspirin and NSAID use) and achieved AUC of 0.61. Version 2 contained 4 variables with the strongest evidence of association with the development of adenocarcinoma in Barrett's (dysplasia, gender, age, Barrett's segment length) and achieved an AUC 0.90.

CONCLUSION

This Bayesian network is unique in the way it utilizes published data to translate the existing empirical evidence surrounding the risk of developing adenocarcinoma in Barrett's esophagus to make personalized risk predictions. Further work is required but this tool marks a vital step towards delivering a more personalized approach to Barrett's surveillance.