Clinical Summary

Prediction of progression in Barrett’s esophagus using a tissue systems pathology test: a pooled analysis of international multicenter studies

Iyer PG, Codipilly DC, Chandar AK, Agarwal S, Wang KK, Leggett CL, Latuche LR, Schulte PJ

Clinical Gastroenterolgy and Hepatology 2022

Clinical implications

  1. Treatment plans for patients with BE are based upon risk-stratification (risk of progression). TissueCypher was shown to be the most important predictor of progression.
  2. TissueCypher has an additive impact on existing clinicopathologic factors; e.g. a High Risk TissueCypher test result in a male BE patient, with 3 cm long NDBE, changes risk of IPP from 4.47x to 22.54x (1.02 + 3.45 + 18.07).
  3. Identify high-risk BE patients who are likely to progress and increase endoscopic surveillance or consider endoscopic eradication therapy.
  4. Identify low-risk BE patients who are unlikely to progress and extend surveillance intervals or more optimally administer treatment.
  5. Use adjunctively to inform key clinical management decisions, allowing upstaging/downstaging based on individual patient risk.

Key findings

  • Across all analyses, TissueCypher was the strongest and most significant predictor of progression to HGD or EAC.
  • Predictive performance of clinicopathologic factors was significantly improved by the inclusion of the TissueCypher risk classes.
  • In the NDBE patient cohort, a TissueCypher high risk score predicted an 18-fold increased risk of progression vs. TissueCypher low risk score.
  • TissueCypher identified 52% of the NDBE progressors, all of whom were missed by the standard of care.

Data presentation by Dr. Prasad Iyer from Digestive Disease Week* (DDW)



  1. Background on Barrett’s esophagus
  2. Limitations of dysplasia and surveillance
  3. Implications of predicting progression
  4. TissueCypher Barrett’s Esophagus Assay
  5. The aim of this pooled analysis
  6. Overview of the data sources and methods
  7. Patient characteristics and modeling
  8. Advantages of using TissueCypher
  9. Conclusions from the pooled analysis


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