Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Hampton, James S., Kenny, Ryan P.W., Rees, Colin J., Hamilton, William, Eastaugh, Claire, Richmond, Catherine, Sharp, Linda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541467/
https://www.ncbi.nlm.nih.gov/pubmed/37781155
http://dx.doi.org/10.1016/j.eclinm.2023.102204
_version_ 1785113911094149120
author Hampton, James S.
Kenny, Ryan P.W.
Rees, Colin J.
Hamilton, William
Eastaugh, Claire
Richmond, Catherine
Sharp, Linda
author_facet Hampton, James S.
Kenny, Ryan P.W.
Rees, Colin J.
Hamilton, William
Eastaugh, Claire
Richmond, Catherine
Sharp, Linda
author_sort Hampton, James S.
collection PubMed
description 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: 10.13039/501100000272National Institute for Health and Care Research (NIHR) [10.13039/501100000664Health Technology Assessment Programme (HTA) Programme (Project number 133852).
format Online
Article
Text
id pubmed-10541467
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-105414672023-10-01 The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review Hampton, James S. Kenny, Ryan P.W. Rees, Colin J. Hamilton, William Eastaugh, Claire Richmond, Catherine Sharp, Linda eClinicalMedicine Review 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: 10.13039/501100000272National Institute for Health and Care Research (NIHR) [10.13039/501100000664Health Technology Assessment Programme (HTA) Programme (Project number 133852). Elsevier 2023-09-21 /pmc/articles/PMC10541467/ /pubmed/37781155 http://dx.doi.org/10.1016/j.eclinm.2023.102204 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Hampton, James S.
Kenny, Ryan P.W.
Rees, Colin J.
Hamilton, William
Eastaugh, Claire
Richmond, Catherine
Sharp, Linda
The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
title The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
title_full The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
title_fullStr The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
title_full_unstemmed The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
title_short The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
title_sort performance of fit-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10541467/
https://www.ncbi.nlm.nih.gov/pubmed/37781155
http://dx.doi.org/10.1016/j.eclinm.2023.102204
work_keys_str_mv AT hamptonjamess theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT kennyryanpw theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT reescolinj theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT hamiltonwilliam theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT eastaughclaire theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT richmondcatherine theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT sharplinda theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT theperformanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT hamptonjamess performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT kennyryanpw performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT reescolinj performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT hamiltonwilliam performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT eastaughclaire performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT richmondcatherine performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT sharplinda performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview
AT performanceoffitbasedandotherriskpredictionmodelsforcolorectalneoplasiainsymptomaticpatientsasystematicreview