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The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review

Lookup NU author(s): Dr James Hampton, Dr Ryan KennyORCiD, Professor Colin Rees, Claire EastaughORCiD, Catherine Richmond, Professor Linda Sharp



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2023 The Authors. Background: Colorectal cancer (CRC) incidence and mortality are increasing internationally. Endoscopy services are under significant pressure with many overwhelmed. Faecal immunochemical testing (FIT) has been advocated to identify a high-risk population of symptomatic patients requiring definitive investigation by colonoscopy. Combining FIT with other factors in a risk prediction model could further improve performance in identifying those requiring investigation most urgently. We systematically reviewed performance of models predicting risk of CRC and/or advanced colorectal polyps (ACP) in symptomatic patients, with a particular focus on those models including FIT. Methods: The review protocol was published on PROSPERO (CRD42022314710). Searches were conducted from database inception to April 2023 in MEDLINE, EMBASE, Cochrane libraries, SCOPUS and CINAHL. Risk of bias of each study was assessed using The Prediction study Risk Of Bias Assessment Tool. A narrative synthesis based on the guidelines for Synthesis Without Meta-Analysis was performed due to study heterogeneity. Findings: We included 62 studies; 23 included FIT (n = 22) or guaiac Faecal Occult Blood Testing (n = 1) combined with one or more other variables. Twenty-one studies were conducted solely in primary care. Generally, prediction models including FIT consistently had good discriminatory ability for CRC/ACP (i.e. AUC >0.8) and performed better than models without FIT although some models without FIT also performed well. However, many studies did not present calibration and internal and external validation were limited. Two studies were rated as low risk of bias; neither model included FIT. Interpretation: Risk prediction models, including and not including FIT, show promise for identifying those most at risk of colorectal neoplasia. Substantial limitations in evidence remain, including heterogeneity, high risk of bias, and lack of external validation. Further evaluation in studies adhering to gold standard methodology, in appropriate populations, is required before widespread adoption in clinical practice. Funding: National Institute for Health and Care Research (NIHR) [ Health Technology Assessment Programme (HTA) Programme (Project number 133852).

Publication metadata

Author(s): Hampton JS, Kenny RPW, Rees CJ, Hamilton W, Eastaugh C, Richmond C, Sharp L

Publication type: Review

Publication status: Published

Journal: eClinicalMedicine

Year: 2023

Volume: 64

Print publication date: 01/10/2023

Online publication date: 21/09/2023

Acceptance date: 28/08/2023

ISSN (electronic): 2589-5370

Publisher: Elsevier Ltd


DOI: 10.1016/j.eclinm.2023.102204