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运用多元对应分析和 K-均值聚类分析探究结直肠癌风险因素与可能性之间的关联:一项横断面研究。

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

机构信息

Department of Computer Science, University of Lleida, Lleida, Spain.

Department of Computer Systems, Santa Maria University Hospital, Lleida, Spain.

出版信息

J Med Internet Res. 2022 Jul 19;24(7):e29056. doi: 10.2196/29056.

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.

摘要

背景

先前的研究表明,风险因素与结直肠癌的发生几率增加有关。

目的

本研究旨在通过多元对应分析(MCA)和 K-均值聚类分析(k-means)检测莱里达(加泰罗尼亚)地区的这些关联。

方法

本横断面研究纳入了 2012 年至 2015 年间莱里达省(西班牙)人群癌症登记处、初级保健中心数据库和加泰罗尼亚卫生服务登记处中提取的 1083 例结直肠癌病例。数据集包括吸烟和 BMI 等风险因素以及社会人口统计学信息和肿瘤详细信息。采用 MCA 和 K-均值聚类分析确定风险因素与患者特征之间的关系。

结果

这些技术的组合有助于发现具有相似风险因素的患者聚类。死亡风险与年龄较大、肥胖或超重有关。III 期癌症与≥65 岁人群和农村/半农村人群有关,而年轻人则与 0 期有关。

结论

MCA 和 K-均值聚类分析在检测风险因素与患者特征之间的关联方面非常有用。这些技术已被证明是分析结直肠癌某些因素发生率的有效工具。所得结果有助于证实可疑趋势,并促进这些技术用于发现风险因素与其他癌症发病率之间的关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ba7/9346563/e263ccbefe67/jmir_v24i7e29056_fig1.jpg

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