The Impact of Uncertainty in Barrett's Esophagus Progression Rates on Hypothetical Screening and Treatment Decisions

High rate of missed Barrett's esophagus when screening with forceps biopsies

BACKGROUND

Screening for Barrett's esophagus (BE) with endoscopy plus forceps biopsy (FB) has poor compliance with the recommended Seattle protocol and fails to sample large areas of mucosa. This statistical modeling study estimates, for the first time, the actual frequency of missed BE cases by FB.

METHODS

Published, calibrated models in the literature were combined to calculate the age-specific prevalence of BE in white males with gastroesophageal reflux disease (GERD). We started with estimates of the prevalence of BE and GERD, and applied the relative risk for BE in patients with GERD based on the literature. This created estimates of the true prevalence of BE in white males with GERD by decade of life. The proportion of BE missed was calculated as the difference between the prevalence and the proportion with a positive screen.

RESULTS

The prevalence of BE in white males with GERD was 8.9%, 12.1%, 15.3%, 18.7% and 22.0% for the third through eighth decades of life. Even after assuming no false positives, missed cases of BE were about 50% when estimated for patients of ages 50 or 60 years, and over 60% for ages of 30, 40 or 70 years. Sensitivity analysis was done for all variables in the model calculations. For ages 50 and 60 years, this resulted in values from 30.3 to 57.3% and 36.4 to 60.9%.

CONCLUSION

Screening for BE with endoscopy and FB misses approximately 50% of BE cases. More sensitive methods of BE detection or better adherence to the Seattle protocol are needed.

The path(ology) from reflux oesophagitis to Barrett oesophagus to oesophageal adenocarcinoma

This review seeks to summarise the steps in the path from reflux oesophagitis to Barrett oesophagus to oesophageal adenocarcinoma. The epidemiology, clinical presentation, definitions, pathological features, diagnostic pitfalls, and emerging concepts are reviewed for each entity. The histological features of reflux oesophagitis can be variable and are not specific. Cases of reflux oesophagitis with numerous eosinophils are difficult to distinguish from eosinophilic oesophagitis and other oesophagitides with eosinophils (Crohn's disease, medication effect, and connective tissue disorders). In reflux oesophagitis, the findings are often most pronounced in the distal oesophagus, the eosinophils are randomly distributed throughout the epithelium, and eosinophilic abscesses and degranulated eosinophils are rare. For reflux oesophagitis with prominent lymphocytes, clinical history and ancillary clinical studies are paramount to distinguish reflux oesophagitis from other causes of lymphocytic oesophagitis pattern. For Barrett oesophagus, the definition remains a hotly debated topic for which the requirement for intestinal metaplasia to make the diagnosis is not applied unanimously across the globe. Assessing for dysplasia is a challenging aspect of the histological interpretation that guides clinical management. We describe the histological features that we find useful in making this evaluation. Oesophageal adenocarcinoma has been steadily increasing in incidence and has a poor prognosis. The extent of invasion can be overdiagnosed due to a duplicated muscularis mucosae. We also describe the technical factors that can lead to challenges in distinguishing the mucosal and deep margins of endoscopic resections. Lastly, we give an overview of targeted therapies with emerging importance and the ancillary tests that can identify the cases best suited for each therapy.

Predicting colorectal cancer risk from adenoma detection via a two-type branching process model

Despite advances in the modeling and understanding of colorectal cancer development, the dynamics of the progression from benign adenomatous polyp to colorectal carcinoma are still not fully resolved. To take advantage of adenoma size and prevalence data in the National Endoscopic Database of the Clinical Outcomes Research Initiative (CORI) as well as colorectal cancer incidence and size data from the Surveillance Epidemiology and End Results (SEER) database, we construct a two-type branching process model with compartments representing adenoma and carcinoma cells. To perform parameter inference we present a new large-size approximation to the size distribution of the cancer compartment and validate our approach on simulated data. By fitting the model to the CORI and SEER data, we learn biologically relevant parameters, including the transition rate from adenoma to cancer. The inferred parameters allow us to predict the individualized risk of the presence of cancer cells for each screened patient. We provide a web application which allows the user to calculate these individual probabilities at https://ccrc-eth.shinyapps.io/CCRC/. For example, we find a 1 in 100 chance of cancer given the presence of an adenoma between 10 and 20mm size in an average risk patient at age 50. We show that our two-type branching process model recapitulates the early growth dynamics of colon adenomas and cancers and can recover epidemiological trends such as adenoma prevalence and cancer incidence while remaining mathematically and computationally tractable.

Colorectal cancer is a major public health burden. The development of colorectal cancer starts with the mutational initiation of non-cancerous growths in the form of benign adenomatous polyps. These adenomas grow over time with the potential to develop into carcinomas. Many mathematical and simulation-based models have been used to gain insight into this process. We aimed to understand rates of adenoma growth and transition into carcinomas, to enable better planning of colorectal cancer screening strategies. To this end, we expand the two-type branching process model, and fit it on data describing the frequency of sizes of adenomas and carcinomas. The results provide new, data-based, estimates of the rates of development for colorectal cancer.

hERG1 behaves as biomarker of progression to adenocarcinoma in Barrett's esophagus and can be exploited for a novel endoscopic surveillance

Barrett's esophagus (BE) is the only well-known precursor lesion of esophageal adenocarcinoma (EA). The exact estimates of the annual progression rate from BE to EA vary from 0.07% to 3.6%. The identification of BE patients at higher risk to progress to EA is hence mandatory, although difficult to accomplish. In search of novel BE biomarkers we analyzed the efficacy of hERG1 potassium channels in predicting BE progression to EA. Once tested by immunohistochemistry (IHC) on bioptic samples, hERG1 was expressed in BE, and its expression levels increased during progression from BE to esophageal dysplasia (ED) and EA. hERG1 was also over-expressed in the metaplastic cells arising in BE lesions obtained in different BE mouse models, induced either surgically or chemically. Furthermore, transgenic mice which over express hERG1 in the whole gastrointestinal tract, developed BE lesions after an esophago-jejunal anastomosis more frequently, compared to controls. A case-control study was performed on 104 bioptic samples from newly diagnosed BE patients further followed up for at least 10 years. It emerged a statistically significant association between hERG1 expression status and risk of progression to EA. Finally, a novel fluorophore- conjugated recombinant single chain variable fragment antibody (scFv-hERG1-Alexa488) was tested on freshly collected live BE biopsies: it could recognize hERG1 positive samples, perfectly matching IHC data.Overall, hERG1 can be considered a novel BE biomarker to be exploited for a novel endoscopic surveillance protocol, either in biopsies or through endoscopy, to identify those BE patients with higher risk to progress to EA.

Genomic similarity between gastroesophageal junction and esophageal Barrett's adenocarcinomas

The current high mortality rate of esophageal adenocarcinoma (EAC) reflects frequent presentation at an advanced stage. Recent efforts utilizing fluorescent peptides have identified overexpressed cell surface targets for endoscopic detection of early stage Barrett's-derived EAC. Unfortunately, 30% of EAC patients present with gastroesophageal junction adenocarcinomas (GEJAC) and lack premalignant Barrett's metaplasia, limiting this early detection strategy. We compared mRNA profiles from 52 EACs (tubular EAC; tEAC) collected above the gastroesophageal junction with 70 GEJACs, 8 normal esophageal and 5 normal gastric mucosa samples. We also analyzed our previously published whole-exome sequencing data in a large cohort of these tumors. Principal component analysis, hierarchical clustering and survival-based analyses demonstrated that GEJAC and tEAC were highly similar, with only modest differences in expression and mutation profiles. The combined expression cohort allowed identification of 49 genes coding cell surface targets overexpressed in both GEJAC and tEAC. We confirmed that three of these candidates (CDH11, ICAM1 and CLDN3) were overexpressed in tumors when compared to normal esophagus, normal gastric and non-dysplastic Barrett's, and localized to the surface of tumor cells. Molecular profiling of tEAC and GEJAC tumors indicated extensive similarity and related molecular processes. Identified genes that encode cell surface proteins overexpressed in both Barrett's-derived EAC and those that arise without Barrett's metaplasia will allow simultaneous detection strategies.

An Accurate Cancer Incidence in Barrett's Esophagus: A Best Estimate Using Published Data and Modeling

BACKGROUND & AIMS

Published estimates for the rate of progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) vary. We used simulation modeling to reconcile published data and more accurately estimate the incidence of EAC among people with BE.

METHODS

We calibrated the ERASMUS/UW model (a collaboration between Erasmus Medical Center, Rotterdam, the Netherlands and the University of Washington, Seattle) for EAC to match the 0.18% annual rate of progression from population-based studies. This model was then used to simulate the design of prospective studies, introducing more endoscopic surveillance. We used the model to predict rates of progression for both types of studies and for different periods of follow-up, and compared the predicted rates with published data.

RESULTS

For the first 5 years of follow-up, the model reproduced the 0.19% mean annual rate of progression observed in population-based studies; the same disease model predicted a 0.36% annual rate of progression in studies with a prospective design (0.41% reported in published articles). After 20 years, these rates each increased to 0.63% to 0.65% annually, corresponding with a 9.1% to 9.5% cumulative cancer incidence. Between these periods, the difference between the progression rates of both study designs decreased from 91% to 5%.

CONCLUSIONS

In the first 5 years after diagnosis, the rate of progression from BE to EAC is likely to more closely approximate the lower estimates reported from population-based studies than the higher estimates reported from prospective studies in which EAC is detected by surveillance. Clinicians should use this information to explain to patients their short-term and long-term risks if no action is taken, and then discuss the risks and benefits of surveillance.