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Gastrointestinal Disorders
Volume 5
Issue 4
10.3390/gidisord5040045
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Systematic Review

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

by
Deborah Jael Herrera
1,
Wessel van de Veerdonk
1,2,
Daiane Maria Seibert
3,
Moges Muluneh Boke
1,
Claudia Gutiérrez-Ortiz
1,
Nigus Bililign Yimer
1,
Karen Feyen
3,
Allegra Ferrari
1,4 and
Guido Van Hal
1,*
1
Family Medicine and Population Health Department (FAMPOP), Faculty of Medicine and Health Sciences, University of Antwerp, 2610 Antwerp, Belgium
2
Centre of Expertise Care and Well-Being, Campus Zandpoortvest, Thomas More University of Applied Sciences, 2800 Mechelen, Belgium
3
Centre of Expertise Design and Technology, Campus De Nayer, Thomas More University of Applied Sciences, 2800 Mechelen, Belgium
4
Department of Health Sciences (DISSAL), University of Genoa, Via Pastore 1, 16123 Genoa, Italy
*
Author to whom correspondence should be addressed.
Gastrointest. Disord. 2023, 5(4), 549-579; https://doi.org/10.3390/gidisord5040045
Submission received: 18 September 2023 / Revised: 20 October 2023 / Accepted: 7 November 2023 / Published: 11 December 2023
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Abstract

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.
Keywords: risk prediction; risk scores; colorectal cancer; advanced neoplasia; risk factors; model performance; clinical utility risk prediction; risk scores; colorectal cancer; advanced neoplasia; risk factors; model performance; clinical utility

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MDPI and ACS Style

Herrera, D.J.; van de Veerdonk, W.; Seibert, D.M.; Boke, M.M.; Gutiérrez-Ortiz, C.; Yimer, N.B.; Feyen, K.; Ferrari, A.; Van Hal, G. From Algorithms to Clinical Utility: A Systematic Review of Individualized Risk Prediction Models for Colorectal Cancer. Gastrointest. Disord. 2023, 5, 549-579. https://doi.org/10.3390/gidisord5040045

AMA Style

Herrera DJ, van de Veerdonk W, Seibert DM, Boke MM, Gutiérrez-Ortiz C, Yimer NB, Feyen K, Ferrari A, Van Hal G. From Algorithms to Clinical Utility: A Systematic Review of Individualized Risk Prediction Models for Colorectal Cancer. Gastrointestinal Disorders. 2023; 5(4):549-579. https://doi.org/10.3390/gidisord5040045

Chicago/Turabian Style

Herrera, Deborah Jael, Wessel van de Veerdonk, Daiane Maria Seibert, Moges Muluneh Boke, Claudia Gutiérrez-Ortiz, Nigus Bililign Yimer, Karen Feyen, Allegra Ferrari, and Guido Van Hal. 2023. "From Algorithms to Clinical Utility: A Systematic Review of Individualized Risk Prediction Models for Colorectal Cancer" Gastrointestinal Disorders 5, no. 4: 549-579. https://doi.org/10.3390/gidisord5040045

APA Style

Herrera, D. J., van de Veerdonk, W., Seibert, D. M., Boke, M. M., Gutiérrez-Ortiz, C., Yimer, N. B., Feyen, K., Ferrari, A., & Van Hal, G. (2023). From Algorithms to Clinical Utility: A Systematic Review of Individualized Risk Prediction Models for Colorectal Cancer. Gastrointestinal Disorders, 5(4), 549-579. https://doi.org/10.3390/gidisord5040045

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