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Reading: Risk prediction models for colorectal cancer: A Scoping review

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Risk prediction models for colorectal cancer: A Scoping review

Authors:

Yasara Manori Samarakoon ,

National Cancer Control Programme, Ministry of Health, Sri Lanka, LK
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Arunasalam Pathmeswaran,

Faculty of Medicine, University of Kelaniya, LK
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Nalika Sepali Gunawardena

World Health Organization, Country office for Sri Lanka, LK
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Abstract

Background and objectives

Many risk prediction models have been developed globally to identify specific populations at high risk for colorectal cancer in specific settings. Documentation of available evidence from existing studies will serve as a useful information base. We performed a scoping review, to review and analyse published risk prediction models for colorectal cancer the world over.

Methods

A scoping review was undertaken to address the following question ‘what are the existing risk prediction models to identify the risk of developing colorectal cancer among individuals in different countries and settings?’ using the framework developed by Arksey and O’Malley for scoping reviews. Forty-one articles were included in this review from database searches and from additional searches. The titles and abstracts were reviewed using predetermined screening criteria. We limited our search to existing literature in English language and included both observational and interventional studies.

Results

Out of the 58 risk prediction models identified, most were developed for colorectal cancer followed by advanced colorectal cancer. Most of the articles reviewed were cross sectional studies or cohort studies. Statistical methods such as multiple logistic regression was used by a majority, while few have incorporated non-statistical methods such as consensus method and extracting data from published literature. The authors of the 58 risk prediction models have considered 77 different risk factors excluding the genetic variants.

Conclusions

This comprehensive scoping review demonstrates the capacity of the existing risk models to stratify the general population into risk categories, detailing the studies conducted, location, study design, outcome, overview of the methods, data source and the identified risk predictors. While striving to build on existing knowledge, the review also identifies the research gaps and the need for further improvement.

How to Cite: Samarakoon, Y.M., Pathmeswaran, A. & Gunawardena, N.S., (2017). Risk prediction models for colorectal cancer: A Scoping review. Journal of the Postgraduate Institute of Medicine. 4(2), pp.E56 1–E5624. DOI: http://doi.org/10.4038/jpgim.8168
Published on 30 Dec 2017.
Peer Reviewed

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