Version 1
: Received: 12 December 2019 / Approved: 15 December 2019 / Online: 15 December 2019 (13:30:09 CET)
How to cite:
Ting, W.; Chang, H.; Chang, C.; Lu, C. A Novel Prediction Scheme for Risk Factors of Second Colorectal Cancer in Patients with Colorectal Cancer. Preprints2019, 2019120188
Ting, W.; Chang, H.; Chang, C.; Lu, C. A Novel Prediction Scheme for Risk Factors of Second Colorectal Cancer in Patients with Colorectal Cancer. Preprints 2019, 2019120188
Ting, W.; Chang, H.; Chang, C.; Lu, C. A Novel Prediction Scheme for Risk Factors of Second Colorectal Cancer in Patients with Colorectal Cancer. Preprints2019, 2019120188
APA Style
Ting, W., Chang, H., Chang, C., & Lu, C. (2019). A Novel Prediction Scheme for Risk Factors of Second Colorectal Cancer in Patients with Colorectal Cancer. Preprints. https://doi.org/
Chicago/Turabian Style
Ting, W., Chi-Chang Chang and Chi-Jie Lu. 2019 "A Novel Prediction Scheme for Risk Factors of Second Colorectal Cancer in Patients with Colorectal Cancer" Preprints. https://doi.org/
Abstract
In Taiwan, colorectal cancer is ranked second and third in terms of mortality and cancer incidence, respectively. In addition, medical expenditures related to colorectal cancer are considered to be the third highest. While advances in treatment strategies have provided cancer patients with longer survival, potentially harmful second primary cancers can occur. Therefore, second primary colorectal cancer analysis is an important issue with regard to clinical management. In this study, a novel predictive scheme was developed for predicting the risk factors associated with second colorectal cancer in patients with colorectal cancer by integrating five data mining classification techniques, including support vector machine, random forest, multivariate adaptive regression splines, extreme learning machine, and extreme gradient boosting. In total, 4,287 patients in the datasets provided by three hospital tumor registries were used. Our empirical results revealed that this proposed predictive scheme provided promising classification results and the identification of important risk factors for predicting second colorectal cancer based on accuracy, sensitivity, specificity, and area under the curve metrics. Collectively, our clinical findings suggested that the most important risk factors were the combined stage, age at diagnosis, BMI, surgical margins of the primary site, tumor size, sex, regional lymph nodes positive, grade/differentiation, primary site, and drinking behavior. Accordingly, these risk factors should be monitored for the early detection of second primary tumors in order to improve treatment and intervention strategies.
Keywords
risk factors; second primary cancer (SPC); colorectal cancer; classification techniques; extreme gradient boosting
Subject
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
