Overestimated Sensitivity of Fecal Immunochemical Tests in Screening Cohorts With Registry-Based Follow-up

Am J Gastroenterol. 2019 Nov;114(11):1795-1801. doi: 10.14309/ajg.0000000000000412.

Abstract

Objectives: Several recent studies have reported very high estimates of sensitivity and specificity of fecal immunochemical tests (FITs) at seemingly high levels of precision using registry-based follow-up of participants in very large FIT-based screening programs. We aimed to assess the validity of estimates of diagnostic performance parameters derived by this indirect approach.

Methods: We modeled expected values of sensitivity and specificity of colorectal cancer detection in studies using the indirect approach and their deviation from true values under a broad range of plausible assumptions, and we compared these expected values with recently reported estimates of FIT sensitivity and specificity from such studies.

Results: Using a sensitivity of 75% and specificity of 93.6% (from studies using a direct approach, i.e., colonoscopy follow-up of all participants), the indirect approach would be expected to yield sensitivities between 84.5% and 91.1% and specificities between 93.4% and 93.6% under a range of realistic assumptions regarding colonoscopic follow-up rates of positive FITs and clinical manifestation rates of preclinical colorectal cancer.

Discussion: Very high sensitivities of FITs recently reported with seemingly very high levels of precision by several large-scale registry-based studies, which are in line with expected results based on our model calculations, are likely to be strongly overestimated and need to be interpreted with due caution.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Colonoscopy / statistics & numerical data
  • Colorectal Neoplasms / diagnosis*
  • Early Detection of Cancer* / methods
  • Early Detection of Cancer* / standards
  • Feces / chemistry*
  • Humans
  • Immunohistochemistry* / methods
  • Immunohistochemistry* / standards
  • Medical Overuse / prevention & control
  • Medical Overuse / statistics & numerical data
  • Models, Theoretical
  • Reproducibility of Results
  • Sensitivity and Specificity