Table S1. Summary of Progression Endpoints in Incident Progressor Patients. Table S2. Correlation Among Quantitative Image Analysis Features Derived from the Same Candidate Biomarkers. Table S3. Comparison of Predictive Performance of Risk Classes Predicted by Test vs. Clinical Variables in Training Set of BE Patients. Table S4. Comparison of Predictive Performance of Risk Score as a Continuous Variable vs. Clinical Variables in Training Set. Table S5. Comparison of Predictive Performance of Risk Score as a Continuous Variable vs. Clinical Variables in Validation Set. Figure S1. Flowchart of Steps to Train and Validate 3-Tier 15-Feature/Measure Classifier for Risk Prediction in Barrett's Esophagus Biopsies. Figure S2. Multiplexed Biomarker Labeling and Imaging in Incident Progressor BE Cases. Supplementary Methods.
Pennsylvania Department of Health Cure Program Grant, Research on Cancer Diagnostics or Therapeutics with Commercialization Potential
Qualifying Therapeutic Discovery Project Grant, Internal Revenue Service/Affordable Care Act 2010
ARTICLE ABSTRACTBackground: Better methods are needed to predict risk of progression for Barrett's esophagus. We aimed to determine whether a tissue systems pathology approach could predict progression in patients with nondysplastic Barrett's esophagus, indefinite for dysplasia, or low-grade dysplasia.Methods: We performed a nested case–control study to develop and validate a test that predicts progression of Barrett's esophagus to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC), based upon quantification of epithelial and stromal variables in baseline biopsies. Data were collected from Barrett's esophagus patients at four institutions. Patients who progressed to HGD or EAC in ≥1 year (n = 79) were matched with patients who did not progress (n = 287). Biopsies were assigned randomly to training or validation sets. Immunofluorescence analyses were performed for 14 biomarkers and quantitative biomarker and morphometric features were analyzed. Prognostic features were selected in the training set and combined into classifiers. The top-performing classifier was assessed in the validation set.Results: A 3-tier, 15-feature classifier was selected in the training set and tested in the validation set. The classifier stratified patients into low-, intermediate-, and high-risk classes [HR, 9.42; 95% confidence interval, 4.6–19.24 (high-risk vs. low-risk); P < 0.0001]. It also provided independent prognostic information that outperformed predictions based on pathology analysis, segment length, age, sex, or p53 overexpression.Conclusion: We developed a tissue systems pathology test that better predicts risk of progression in Barrett's esophagus than clinicopathologic variables.Impact: The test has the potential to improve upon histologic analysis as an objective method to risk stratify Barrett's esophagus patients. Cancer Epidemiol Biomarkers Prev; 25(6); 958–68. ©2016 AACR.