A novel prediction model of the risk of pancreatic cancer among diabetes patients using multiple clinical data and machine learning

Shih Min Chen, Phan Thanh Phuc, Phung Anh Nguyen, Whitney Burton, Shwu Jiuan Lin, Weei Chin Lin, Christine Y. Lu, Min Huei Hsu, Chi Tsun Cheng, Jason C. Hsu

研究成果: 雜誌貢獻文章同行評審

1 引文 斯高帕斯(Scopus)

摘要

Introduction: Pancreatic cancer is associated with poor prognosis. Considering the increased global incidence of diabetes cases and that individuals with diabetes are considered a high-risk subpopulation for pancreatic cancer, it is critical to detect the risk of pancreatic cancer within populations of person living = with diabetes. This study aimed to develop a novel prediction model for pancreatic cancer risk among patients with diabetes, using = a real-world database containing clinical features and employing numerous artificial intelligent approach algorithms. Methods: This retrospective observational study analyzed data on patients with Type 2 diabetes from a multisite Taiwanese EMR database between 2009 and 2019. Predictors were selected in accordance with the literature review and clinical perspectives. The prediction models were constructed using machine learning algorithms such as logistic regression, linear discriminant analysis, gradient boosting machine, and random forest. Results: The cohort consisted of 66,384 patients. The Linear Discriminant Analysis (LDA) model generated the highest AUROC of 0.9073, followed by the Voting Ensemble and Gradient Boosting machine models. LDA, the best model, exhibited an accuracy of 84.03%, a sensitivity of 0.8611, and a specificity of 0.8403. The most significant predictors identified for pancreatic cancer risk were glucose, glycated hemoglobin, hyperlipidemia comorbidity, antidiabetic drug use, and lipid-modifying drug use. Conclusion: This study successfully developed a highly accurate 4-year risk model for pancreatic cancer in patients with diabetes using real-world clinical data and multiple machine-learning algorithms. Potentially, our predictors offer an opportunity to identify pancreatic cancer early and thus increase prevention and invention windows to impact survival in diabetic patients.

原文英語
頁(從 - 到)19987-19999
頁數13
期刊Cancer Medicine
12
發行號19
DOIs
出版狀態已發佈 - 10月 2023

ASJC Scopus subject areas

  • 腫瘤科
  • 放射學、核子醫學和影像學
  • 癌症研究

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