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Multicentre derivation and validation of a colitis-associated colorectal cancer risk prediction web tool.

Kit Curtius1,2, Misha Kabir3,4, Ibrahim Al Bakir5,4

  • 1Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, UK kcurtius@health.ucsd.edu misha.kabir1@nhs.net.

Gut
|May 15, 2021
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Summary

Patients with ulcerative colitis (UC) and low-grade dysplasia (LGD) at high risk for advanced neoplasia (AN) can now be identified. A validated risk prediction tool, UC-CaRE, helps personalize treatment decisions for UC patients with LGD.

Keywords:
clinical decision makingcolorectal cancerdysplasiaulcerative colitis

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Area of Science:

  • Gastroenterology and Hepatology
  • Oncology
  • Clinical Epidemiology

Background:

  • Ulcerative colitis (UC) patients with low-grade dysplasia (LGD) face an elevated risk of advanced neoplasia (AN), including high-grade dysplasia or colorectal cancer.
  • Accurate risk stratification is crucial for timely intervention and improved patient outcomes.

Purpose of the Study:

  • To develop and validate a predictive model for AN risk in UC patients with LGD.
  • To create a user-friendly web tool for communicating personalized AN risk.

Main Methods:

  • Retrospective, multicentre cohort study involving adult UC patients with an initial LGD diagnosis.
  • Development of a multivariate risk prediction model using Cox regression in a discovery cohort (n=246).
  • Validation of the model in three external centres (n=198) and integration into a web-based risk calculator (UC-CaRE).

Main Results:

  • Four key clinicopathological variables significantly predicted AN progression: large endoscopically visible LGD (>1 cm), unresectable/incomplete resection, moderate/severe histological inflammation within 5 years, and multifocality.
  • The validated four-variable model demonstrated accurate AN prediction with excellent calibration (Observed/Expected=1.01) and 100% specificity for the lowest risk group over 13 years.
  • The UC-CaRE web tool provides personalized risk estimates.

Conclusions:

  • Multicentre validation confirms that specific LGD characteristics (large, unresected, multifocal) and recent inflammation identify high-risk UC patients.
  • Personalized risk prediction via the UC-CaRE tool supports informed treatment decision-making for UC patients with LGD.
  • The study highlights the utility of a dedicated risk estimator for managing UC-associated neoplasia.