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, Juliana Crook, Colleen S. Thomas, Peter D. Siersema, Douglas K. Rex, Michael B Wallace

Research output: Contribution to journalArticle

2 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)e0185560
JournalPLoS One
Volume12
Issue number9
DOIs
StatePublished - 2017
Externally publishedYes

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colonoscopy
adenoma
Colonoscopy
Adenoma
Screening
physicians
odds ratio
screening
confidence interval
prediction
Odds Ratio
monitoring
Confidence Intervals
Anesthesiology
Physicians
Logistics
Statistics
Hispanic Americans
Aptitude
Sex Ratio

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Development and validation of a prediction model for adenoma detection during screening and surveillance colonoscopy with comparison to actual adenoma detection rates. / Brand, Eelco C.; Crook, Juliana; Thomas, Colleen S.; Siersema, Peter D.; Rex, Douglas K.; Wallace, Michael B.

In: PLoS One, Vol. 12, No. 9, 2017, p. e0185560.

Research output: Contribution to journalArticle

Brand, Eelco C. ; Crook, Juliana ; Thomas, Colleen S. ; Siersema, Peter D. ; Rex, Douglas K. ; Wallace, Michael B. / Development and validation of a prediction model for adenoma detection during screening and surveillance colonoscopy with comparison to actual adenoma detection rates. In: PLoS One. 2017 ; Vol. 12, No. 9. pp. e0185560.
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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.",
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T1 - Development and validation of a prediction model for adenoma detection during screening and surveillance colonoscopy with comparison to actual adenoma detection rates

AU - Brand, Eelco C.

AU - Crook, Juliana

AU - Thomas, Colleen S.

AU - Siersema, Peter D.

AU - Rex, Douglas K.

AU - Wallace, Michael B

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N2 - 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.

AB - 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.

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