Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 25, 2021
Open Peer Review Period: Mar 24, 2021 - May 19, 2021
Date Accepted: May 23, 2022
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
The Use of Multiple Correspondence Analysis and K-means to Explore Associations between Risk Factors and Patient Characteristics in Colorectal Cancer
ABSTRACT
Background:
Previous works have shown that risk factors are associated with an increased risk of colorectal cancer.
Objective:
The purpose of this study was to detect these associations in the region of Lleida (Catalonia) using Multiple Correspondence Analysis (MCA) and K-means.
Methods:
The cross-sectional study was made up of 1,085 colorectal cancer episodes between 2012 and 2015, extracted from the Population-based Cancer Registry (PCR) for the province of Lleida (Spain), the Primary Care Centers database and the Catalan Health Service Register. The relations between risk factors and patient characteristics were identified using MCA and K-means.
Results:
The combination of these techniques helps to detect clusters of patients with similars risk factors. Risk of death is associated with elderly people and obesity or overweight. Stage III is related with people aged ≥65 and rural/semi-urban population while younger people were related with stage 0.
Conclusions:
MCA and K-means were a significant help for detecting associations between risk factors and patient characteristics. These techniques have proven to be effective tools for analyzing the incidence of some factors in colorectal cancer. The outcomes obtained help to corroborate suspected trends, as well as stimulating new hypotheses about the previous clinical history and how to prevent it.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.