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, Julia E.; Thomas, Colleen S.; Siersema, Peter D.; Rex, Douglas K.; Wallace, Michael B.

doi:10.1371/journal.pone.0185560

Cited by 9 publications

(9 citation statements)

References 40 publications

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“…In literature, conflicting results are reported regarding the association between ASA I vs. ASA II and polyp detection. [15,22,26] This study discloses several new case-mix factors to be associated with higher CIR, higher ABPR and higher PDR and confirms the association of earlier described case-mix factors with these outcomes. Adjustment for age, sex, ASA classification and indication influences the interpretation of performance variation between endoscopy centres.…”

Section: Discussionsupporting

confidence: 85%

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Case-mix adjustment to compare colonoscopy performance between endoscopy centers: a nationwide registry study

et al. 2021

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Background: Non-modifiable patient and endoscopy characteristics might influence colonoscopy performance. Differences in these so-called case-mix factors are likely to exist between endoscopy centres. This study aims to examine the importance of case-mix adjustment when comparing performance between endoscopy centres. Methods: Prospectively collected data recorded in the Dutch national colonoscopy registry between 2016-2019 were retrospectively analyzed. Performance on cecal intubation rate (CIR) and adequate bowel preparation rate (ABPR) were studied. Additionally, polyp detection rate (PDR) was studied in fecal immunochemical test (FIT)-positive screening colonoscopies. Variation in case-mix factors between endoscopy centres and expected outcomes for each performance measure were calculated per endoscopy centre, based on their case-mix factors (sex, age, ASA score, indication), using multivariable logistic regression. Results: In total, 363,840 colonoscopies were included from 51 endoscopy centres. The mean percentages per endoscopy centre were significantly different for age > 65 years, male patients, ASA > III and diagnostic colonoscopies (all p < 0.001). In the FIT-positive screening population, significant differences were observed per endoscopy centre for age > 65 years, male patients and ASA > III (all p value < 0.001). The expected CIR, ABPR and PDR ranged from 95.0% to 96.9%, from 93.6% to 96.4% and from 76.2% to 79.1%, respectively. Age, sex, ASA classification and indication were significant case-mix factors for CIR and ABPR. In the FIT-positive screening population, age, sex and ASA classification were significant case-mix factors for PDR. Conclusion: Our findings emphasize that when comparing colonoscopy performance measures between endoscopy centres, case-mix adjustment should be considered.

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Section: Discussionsupporting

confidence: 85%

“…This association remained statistically significant after adjusting for sex and age in multivariable analysis. In the literature, conflicting results are reported regarding the association between ASA I vs. ASA II and polyp detection [15,22,26].…”

Section: Discussionmentioning

confidence: 99%

Case-mix adjustment to compare colonoscopy performance between endoscopy centers: a nationwide registry study

et al. 2021

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“…Although ADR represents the most robust quality indicator of colonoscopy, it still has its own weaknesses[28-30] and thus a plethora of other quality indicators are also used in order to ameliorate the limitations of ADR. Among these metric quality indicators, adenoma miss rates (AMR) has been used extensively in tandem studies, as it is consistent to the back-to-back study design[31].…”

Section: Discussionmentioning

confidence: 99%

Effect of Endocuff use on colonoscopy outcomes: A systematic review and meta-analysis

Triantafyllou

Gkolfakis

Tziatzios

et al. 2019

WJG

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BACKGROUND Endocuff - a plastic device with flexible projections - mounted on the distal tip of the colonoscope, promises improved colonic mucosa inspection. AIM To elucidate the effect of Endocuff on adenoma detection rate (ADR), advanced ADR (AADR) and mean number of adenomas per colonoscopy (MAC). METHODS Literature searches identified randomized-controlled trials evaluating Endocuff-assisted colonoscopy (EAC) vs conventional colonoscopy (CC) in terms of ADR, AADR and MAC. The effect size on study outcomes was calculated using fixed or random effect model, as appropriate, and it is shown as relative risk (RR) [95% confidence interval (CI)] and mean difference (MD) (95%CI). The rate of device removal in EAC arms was also calculated. RESULTS We identified nine studies enrolling 6038 patients. All studies included mixed population (screening, surveillance and diagnostic examinations). Seven and two studies evaluated the first and the second-generation device, respectively. EAC was associated with increased ADR compared to CC [RR (95%CI): 1.18 (1.05-1.32); Ι 2 = 71%]; EAC benefits more endoscopists with ADR ≤ 35% compared to those with ADR > 35% [RR (95%CI): 1.37 (1.08-1.74); Ι 2 = 49% vs 1.10 (0.99-1.24); Ι 2 = 71%]. In terms of AADR and MAC, no difference was detected between EAC and CC [RR (95%CI): 1.03 (0.85-1.25); Ι 2 = 15% and MD (95%CI): 0.30 (-0.17-0.78); Ι 2 = 99%]. Subgroup analysis did not show any difference between the two device generations regarding all three endpoints. In EAC arms, the device had to be removed in 3% (95%CI: 2%-5%) of the cases mainly due to tortuous sigmoid or presence of diverticula along it. CONCLUSION EAC increases ADR compared to CC, especially for endoscopists with lower ADR. On the other hand, no significant effect on AADR and MAC was detected.

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“…Among the 41 studies appraised, 10 showed an overall unclear risk of bias [36][37][38][39][40][41][42][43][44], while 30 exhibited an overall high risk of bias . Interestingly, only one study emerged with an overall low risk of bias [76] (Figure 3).…”

Section: Risk Of Bias and Applicability Of The Included Studiesmentioning

confidence: 99%

“…There are two main categories of risk models for predicting CRC or AN based on their predictor features: (1) conventional risk model, which uses known and well-established risk factors for CRC; and (2) composite model, which combines well-established risk factors with more advanced features, such as test/laboratory findings and genetic factors. Among the 41 included studies, we identified 22 original conventional risk models, [36][37][38]40,45,48,50,51,53,54,58,59,61,[63][64][65][67][68][69][70]72,74] and 13 composite models [39,[41][42][43][44]47,56,57,62,71,73,75,76]. Of these, three conventional risk models have undergone external validation in separate studies: (1) the Asia-Pacific Colorectal Screening (APCS) model [45], validated in four other studies [46,49,66,70];…”

Section: Characteristics Of Risk Prediction Models For Crcmentioning

confidence: 99%

From Algorithms to Clinical Utility: A Systematic Review of Individualized Risk Prediction Models for Colorectal Cancer

Herrera,

van de Veerdonk,

Seibert

et al. 2023

Gastrointestinal Disorders

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Individualized risk prediction models for colorectal cancer (CRC) play a pivotal role in shaping risk-based screening approaches, garnering attention for use in informed decision making by patients and clinicians. While the incorporation of new predictors and the development of advanced yet complex prediction models can enhance model performance, their practical implementation in clinical settings remains challenging. This systematic review assessed individualized CRC risk prediction models for their validity and potential clinical utility. Utilizing the Cochrane Collaboration methods and PROBAST tool, we conducted comprehensive searches across key databases and risk of bias assessment, respectively. Out of 41 studies included evaluating 44 risk prediction models, 12 conventional and 3 composite models underwent external validation. All risk models exhibited varying discriminatory accuracy, with the area under the curve (AUCs) ranging from 0.57 to 0.90. However, most studies showed an unclear or high risk of bias, with concerns about applicability. Of the five models with promising clinical utility, only two underwent external validation and one employed a decision curve analysis. These models demonstrated a discriminating and well-calibrated performance. While high-performing CRC risk prediction models exist, a need for transparent reporting of performance metrics and their clinical utility persists. Further research on this area is needed to facilitate the integration of these models into clinical practice, particularly in CRC screening.

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

Cited by 9 publications

References 40 publications

Case-mix adjustment to compare colonoscopy performance between endoscopy centers: a nationwide registry study

Case-mix adjustment to compare colonoscopy performance between endoscopy centers: a nationwide registry study

Effect of Endocuff use on colonoscopy outcomes: A systematic review and meta-analysis

From Algorithms to Clinical Utility: A Systematic Review of Individualized Risk Prediction Models for Colorectal Cancer

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