Predicting Pancreatic Cancer in New‐Onset Diabetes Cohort Using a Novel Model With Integrated Clinical and Genetic Indicators: A Large‐Scale Prospective Cohort Study

作者：Yongji Sun, Chaolu Hu, Sien Hu, Hongxia Xu, Jiali Gong, Yixuan Wu, Yixuan Wu, Yiqun Fan, Changming Lv, Tianyu Song, Jianyao Lou, Kai Zhang, Jian Wu, Xiawei Li, Yulian Wu, Yulian Wu · 发表于：Cancer Medicine · 年份：2024 · DOI：10.1002/cam4.70388 · 被引用次数：9 · 研究领域：Pancreatic and Hepatic Oncology Research、Metabolism, Diabetes, and Cancer、Pancreatitis Pathology and Treatment

INTRODUCTION: Individuals who develop new-onset diabetes have been identified as a high-risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this specific cohort presents a promising opportunity for early pancreatic cancer detection. We aimed to develop and validate a novel model capable of identifying high-risk individuals among those with new-onset diabetes. METHODS: Employing the UK Biobank cohort, we focused on those developing new-onset diabetes during follow-up. Genetic and clinical characteristics available at registration were considered as candidate predictors. We conducted univariate regression analysis to identify potential indicators and used a 5-fold cross-validation method to select optimal predictors for model development. Five machine learning algorithms were used for model development. RESULTS: Among 12,735 patients with new-onset diabetes, 100 (0.8%) were diagnosed with PC within 2 years. The final model (area under the curve, 0.897; 95% confidence interval, 0.865-0.929) included 5 clinical predictors and 24 single nucleotide polymorphisms. Two threshold cut-offs were established: 1.28% and 5.26%. The recommended 1.28% cut-off, based on model performance, reduces definitive testing to 13% of the total population while capturing 76% of PC cases. The high-risk threshold is 5.26%. Utilizing this threshold, only 2% of the population needs definitive testing, captu...