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Surrogate Markers: Lessons from the Next Gen?

Brian J Reid1

  • 1Divisions of Human Biology and Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington. Departments of Genome Sciences and Medicine, University of Washington, Seattle, Washington. bjr@fredhutch.org.

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A randomized trial of ursodeoxycholic acid (UDCA) for Barrett esophagus showed no benefit, possibly due to surrogate endpoints. This highlights challenges in cancer prevention research and diagnosis.

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Area of Science:

  • Gastroenterology
  • Cancer Prevention Research
  • Genomics

Background:

  • Barrett esophagus is a precursor to esophageal adenocarcinoma.
  • Recent calls for a Pre-Cancer Genome Atlas (PCGA) aim to understand early cancer initiation.
  • Cancer prevention trials face challenges including surrogate endpoint selection and diagnostic biases.

Purpose of the Study:

  • To discuss the null outcome of a randomized control trial of ursodeoxycholic acid (UDCA) in Barrett esophagus.
  • To explore reasons for null outcomes in prevention research, focusing on surrogate endpoints.
  • To examine the implications of diagnostic biases and study designs for cancer prevention research and initiatives like the PCGA.

Main Methods:

  • Review of a randomized control prevention trial of ursodeoxycholic acid (UDCA) in Barrett esophagus.
  • Discussion of concepts in prevention research, including branched evolution and length bias sampling.
  • Exploration of study designs and surrogate endpoints in Barrett esophagus trials.

Main Results:

  • A well-designed randomized trial of UDCA for Barrett esophagus yielded a null outcome.
  • The commentary suggests surrogate endpoints may explain the null result.
  • Length bias sampling is discussed as a factor in overdiagnosis and underdiagnosis of cancers.

Conclusions:

  • Null outcomes in well-designed trials can occur, necessitating careful consideration of surrogate endpoints.
  • Understanding cancer initiation through initiatives like the PCGA requires addressing diagnostic biases.
  • Optimizing study designs and endpoint selection is crucial for effective cancer prevention research.