Predictive Factors of Advanced Colonic Adenomas and Cancer Using Data Mining

BACKGROUND Colorectal cancer is the third common cancer in Iran. In this study we aimed to identify factors associated with the prevalence of advanced colonic neoplasms among a high-risk population. METHODS Participants were 474 first degree relatives of patients with colon cancer who underwent a sc...

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Bibliographic Details
Published in:Middle East journal of digestive diseases 2019-10, Vol.11 (4), p.192-199
Main Authors: Fatemian, Atieh Sadat, Abdolvand, Neda, Salimzadeh, Hamideh, Delavari, Alireza
Format: Article
Language:English
Subjects:
Age
Artificial intelligence
Body mass index
Clustering
Colonoscopy
Colorectal cancer
Data mining
Family medical history
Knowledge discovery
Lung cancer
Machine learning
Medical diagnosis
Medical prognosis
Medical screening
Original
Outdoor air quality
Patients
Smoking
Tumors
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Summary:BACKGROUND Colorectal cancer is the third common cancer in Iran. In this study we aimed to identify factors associated with the prevalence of advanced colonic neoplasms among a high-risk population. METHODS Participants were 474 first degree relatives of patients with colon cancer who underwent a screening colonoscopy at Digestive Disease Research Institute, Shariati Hospital affiliated to Tehran University of Medical Sciences. Features examined in this study were age, sex, body mass index, Aspirin use, smoking, and relationship type with patients with cancer in family. Also, patient's age at the time of cancer diagnosis, number and sex of the patients with colon cancer in the family were assessed. Data analysis was performed by data mining methods using K-Medoid clustering and decision tree C4.5. RESULTS Results showed that female sex of the patients with colon cancer and their young age (< 60 years old) at the time of cancer diagnosis were important predictive factors for the prevalence of colorectal advanced neoplasms among their family members. CONCLUSION Data mining methods were found to be applicable in recognizing predictive factors of colorectal advanced neoplasms in each cluster and tree.
ISSN:2008-5230
2008-5249
DOI:10.15171/mejdd.2019.148