Acta Scientific Gastrointestinal Disorders (ASGIS)(ISSN: 2582-1091)

Research Article Volume 5 Issue 3

Risk Prediction Models for Colorectal Cancer in Middle Income Countries: A Scoping Review Used to Develop a Risk Assessment Tool for South Africa and Brazil

Sphindile Magwaza1*, Guido Van Hal1 and Muhammad Hoque2

1Social Epidemiology and Health Policy, University of Antwerp, Belgium
2Research Department, Management College of Southern Africa, South Africa

*Corresponding Author:Sphindile Magwaza, Social Epidemiology and Health Policy, University of Antwerp, Belgium.

Received: January 24, 2022; Published: February 25, 2022

Abstract

Background: There is evidence that screening for colorectal cancer (CRC) contributes towards early treatment and survival. CRC risk predictive models have been developed to assist with segmenting population by risk category for targeted screening. The models also assist to inform prevention interventions to lower incidence of CRC.

Aim: We conducted a scoping review to map and analyse published CRC risk predictive models for colorectal cancer (CRC) with the purpose to inform the development of a risk assessment tool, for potential use in South Africa (SA) and Brazil (BR), using the risk factors with high discrimination values from these published models.

Methods: We used scoping review technique, to identify and map the scientific publications on CRC risk predictive models related to SA and BR and middle-income countries. We identified the systematic reviews completed and published on the CRC risk predictive models. We reviewed each publication to identify year, countries, authors, gender, risk factors added on the model, data sources, statistical methods used and results and also allocated TRIPOD level based on the analysis of the study. We analysed publications from January 2000 to November 2021 as indexed in the Web of Science Core Collection, PubMed and Cochrane Centre. We documented and analysed each model based on Arksey and O’Malley (2005) framework for scoping reviews.

Findings: One systematic review and one scoping review publications were identified. The reviews included 59 peer-reviewed original research articles on CRC risk predictive models from both high and middle-income countries. Of these, 12 models were included with 10 models published from middle income countries and two models used global data. None of the models were developed from SA or BR. Questionnaires and medical records were used as data sources. Eight models focus on CRC and four models focused on advanced colorectal neoplasia (ACN). All models focused on CRC asymptomatic men and women as part of their study population. The risk factors assessed included demographics, medical, familiar, genetics, biomarkers, environmental and lifestyle/behavioural practices. All models were regarded to have good discrimination for CRC risks.

Conclusions: Scoping the CRC risk predictive models highlighted potential benefits of developing an evidence-based risk assessment tool and identified research gaps due to lack of existing CRC risk predictive models that can be developed to better understand the risk factors in both countries. Having validated risk factors could inform policy and planning; clinical practice particularly, health promotion as well as future research needs for increased CRC research outputs in this area particularly, as all countries strive to implement cost efficiency screening programmes through stratify the general population by risk categories to help prevent and control the CRC burden in both countries.

Keywords: Colorectal Cancer; Risk Prediction Model; Scoping Review; Developing Countries; Assessment Tool

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Citation

Citation: Sphindile Magwaza., et al. “Risk Prediction Models for Colorectal Cancer in Middle Income Countries: A Scoping Review Used to Develop a Risk Assessment Tool for South Africa and Brazil”. Acta Scientific Gastrointestinal Disorders 5.3 (2022): 65-75.

Copyright

Copyright: © 2022 Sphindile Magwaza., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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