Application of a conversion factor to estimate the adenoma detection rate from the polyp detection rate

Gastrointest Endosc. 2011 Mar;73(3):493-7. doi: 10.1016/j.gie.2011.01.005.

Abstract

Background: The adenoma detection rate (ADR) is a quality benchmark for colonoscopy. Many practices find it difficult to determine the ADR because it requires a combination of endoscopic and histologic findings. It may be possible to apply a conversion factor to estimate the ADR from the polyp detection rate (PDR).

Objective: To create a conversion factor that can be used to accurately estimate the ADR from the PDR.

Design: This was a retrospective study of colonoscopies performed by board-certified gastroenterologists to determine the average adenoma to polyp detection rate quotient (APDRQ) for all endoscopists, individually and as a group.

Setting: Academic group practice.

Intervention: The group average APDRQ was used as a conversion factor for the endoscopist's PDR to estimate the ADR.

Main outcome measurements: The strength of the relationship between the estimated ADR and the actual ADR determined by Pearson's correlation coefficient.

Results: A total of 3367 colonoscopies performed by 20 staff gastroenterologists were included. The average ADR for all indications, all patient age groups, and both sexes was 0.17 (range 0.09-0.27, standard deviation 0.05). The average APDRQ was 0.64 (range 0.46-1.00, standard deviation 0.13). The correlation between the estimated ADR and the actual ADR was 0.85 (95% CI, 0.65-0.93, P = .000001).

Limitations: Retrospective study in 1 practice setting with all patient types.

Conclusions: The use of a conversion factor can accurately estimate the ADR from the PDR. Further study is needed to determine whether such a conversion factor can be applied to different practice settings and patient groups.

MeSH terms

  • Adenoma / diagnosis*
  • Algorithms*
  • Colonic Polyps / diagnosis*
  • Colonoscopy / statistics & numerical data*
  • Colorectal Neoplasms / diagnosis*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Retrospective Studies
  • Statistics as Topic / methods