Evaluation of the risk factors associated with rectal neuroendocrine tumors: a big data analytic study from a health screening center.
Journal Article (Journal Article)
BACKGROUND: Rectal neuroendocrine tumor (NET) is the most common NET in Asia. The risk factors associated with rectal NETs are unclear because of the overall low incidence rate of these tumors and the associated difficulty in conducting large epidemiological studies on rare cases. The aim of this study was to exploit the benefits of big data analytics to assess the risk factors associated with rectal NET. METHODS: A retrospective case-control study was conducted, including 102 patients with histologically confirmed rectal NETs and 52,583 healthy controls who underwent screening colonoscopy at the Center for Health Promotion of the Samsung Medical Center in Korea between January 2002 and December 2012. Information on different risk factors was collected and logistic regression analysis applied to identify predictive factors. RESULTS: Four factors were significantly associated with rectal NET: higher levels of cholesterol [odds ratio (OR) = 1.007, 95 % confidence interval (CI), 1.001-1.013, p = 0.016] and ferritin (OR = 1.502, 95 % CI, 1.167-1.935, p = 0.002), presence of metabolic syndrome (OR = 1.768, 95 % CI, 1.071-2.918, p = 0.026), and family history of cancer among first-degree relatives (OR = 1.664, 95 % CI, 1.019-2.718, p = 0.042). CONCLUSION: The findings of our study demonstrate the benefits of using big data analytics for research and clinical risk factor studies. Specifically, in this study, this analytical method was applied to identify higher levels of serum cholesterol and ferritin, metabolic syndrome, and family history of cancer as factors that may explain the increasing incidence and prevalence of rectal NET.
- Pyo, JH; Hong, SN; Min, B-H; Lee, JH; Chang, DK; Rhee, P-L; Kim, JJ; Choi, SK; Jung, S-H; Son, HJ; Kim, Y-H
- December 2016
Volume / Issue
- 51 / 12
Start / End Page
- 1112 - 1121
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)