Development and validation of a prediction model for adenoma detection during screening and surveillance colonoscopy with comparison to actual adenoma detection rates

Eelco C Brand; Julia E Crook; Colleen S Thomas; Peter D Siersema; Douglas K Rex; Michael B Wallace

doi:10.1371/journal.pone.0185560

Development and validation of a prediction model for adenoma detection during screening and surveillance colonoscopy with comparison to actual adenoma detection rates

PLoS One. 2017 Sep 28;12(9):e0185560. doi: 10.1371/journal.pone.0185560. eCollection 2017.

Authors

Eelco C Brand^{1

2}, Julia E Crook³, Colleen S Thomas³, Peter D Siersema⁴, Douglas K Rex⁵, Michael B Wallace¹

Affiliations

¹ Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, Florida, United States of America.
² Department of Gastroenterology and Hepatology, University Medical Center Utrecht, Utrecht, the Netherlands.
³ Division of Biomedical Statistics and Informatics, Mayo Clinic, Jacksonville, Florida, United States of America.
⁴ Department of Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, The Netherlands.
⁵ Department of Gastroenterology and Hepatology, Indiana University Medical Center, Indianapolis, Indiana, United States of America.

Abstract

Objective: The adenoma detection rate (ADR) varies widely between physicians, possibly due to patient population differences, hampering direct ADR comparison. We developed and validated a prediction model for adenoma detection in an effort to determine if physicians' ADRs should be adjusted for patient-related factors.

Materials and methods: Screening and surveillance colonoscopy data from the cross-sectional multicenter cluster-randomized Endoscopic Quality Improvement Program-3 (EQUIP-3) study (NCT02325635) was used. The dataset was split into two cohorts based on center. A prediction model for detection of ≥1 adenoma was developed using multivariable logistic regression and subsequently internally (bootstrap resampling) and geographically validated. We compared predicted to observed ADRs.

Results: The derivation (5 centers, 35 physicians, overall-ADR: 36%) and validation (4 centers, 31 physicians, overall-ADR: 40%) cohort included respectively 9934 and 10034 patients (both cohorts: 48% male, median age 60 years). Independent predictors for detection of ≥1 adenoma were: age (optimism-corrected odds ratio (OR): 1.02; 95%-confidence interval (CI): 1.02-1.03), male sex (OR: 1.73; 95%-CI: 1.60-1.88), body mass index (OR: 1.02; 95%-CI: 1.01-1.03), American Society of Anesthesiology physical status class (OR class II vs. I: 1.29; 95%-CI: 1.17-1.43, OR class ≥III vs. I: 1.57; 95%-CI: 1.32-1.86), surveillance versus screening (OR: 1.39; 95%-CI: 1.27-1.53), and Hispanic or Latino ethnicity (OR: 1.13; 95%-CI: 1.00-1.27). The model's discriminative ability was modest (C-statistic in the derivation: 0.63 and validation cohort: 0.60). The observed ADR was considerably lower than predicted for 12/66 (18.2%) physicians and 2/9 (22.2%) centers, and considerably higher than predicted for 18/66 (27.3%) physicians and 4/9 (44.4%) centers.

Conclusion: The substantial variation in ADRs could only partially be explained by patient-related factors. These data suggest that ADR variation could likely also be due to other factors, e.g. physician or technical issues.

Publication types

Comparative Study
Multicenter Study
Randomized Controlled Trial
Validation Study

MeSH terms

Adenoma / diagnosis*
Aged
Cohort Studies
Colonoscopy / statistics & numerical data*
Colorectal Neoplasms / diagnosis*
Cross-Sectional Studies
Female
Humans
Male
Middle Aged
Models, Theoretical*

Grants and funding

Eelco C. Brand received an unrestricted scientific internship (16-03S) abroad grant from The Dutch Digestive Foundation (Maag Lever Darm Stichting). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.