Use of Multiple Correspondence Analysis and K-means to Explore Associations Between Risk Factors and Likelihood of Colorectal Cancer: Cross-sectional Study

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Date
2022
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Florensa Cazorla, DídacFlorensa Cazorla, Dídac - ORCID ID
Mateo Fornés, JordiMateo Fornés, Jordi - ORCID ID
Solsona Tehàs, FrancescSolsona Tehàs, Francesc - ORCID ID
Pedrol, Tere
Mesas, Miquel
Piñol, Ramon
Godoy i García, PereGodoy i García, Pere - ORCID ID
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Abstract
Background: Previous works have shown that risk factors are associated with an increased likelihood of colorectal cancer. Objective: The purpose of this study was to detect these associations in the region of Lleida (Catalonia) by using multiple correspondence analysis (MCA) and k-means. Methods: This cross-sectional study was made up of 1083 colorectal cancer episodes between 2012 and 2015, extracted from the population-based cancer registry for the province of Lleida (Spain), the Primary Care Centers database, and the Catalan Health Service Register. The data set included risk factors such as smoking and BMI as well as sociodemographic information and tumor details. The relations between the 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 similar risk factors. Risk of death is associated with being elderly and obesity or being overweight. Stage III cancer is associated with people aged ≥65 years and rural/semiurban populations, while younger people were associated with stage 0. Conclusions: MCA and k-means were significantly useful 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 corroborate suspected trends and stimulate the use of these techniques for finding the association of risk factors with the incidence of other cancers.
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http://hdl.handle.net/10459.1/83940
DOI
https://doi.org/10.2196/29056
Journal or Serie
Journal of Medical Internet Research, 2022, vol. 24, núm. 7, e29056
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