ArticlePloS one2019
Do changes in health reveal the possibility of undiagnosed pancreatic cancer? Development of a risk-prediction model based on healthcare claims data.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review and Assessment.The American journal of gastroenterology · 2024Pooled it
- Identifying health conditions associated with an increased risk of pancreatic ductal adenocarcinoma at medium term in nationwide electronic health records of primary care physicians.British journal of cancer · 2025Article
- Development of scoring models to predict early pancreatic cancer risk in new-onset diabetes mellitus patients.Hepatobiliary surgery and nutrition · 2025Article
- Development and validation of an easy-to-use nomogram for predicting pancreatic malignancy in patients with pancreatic mass.Scientific reports · 2025Article
- Exploring the application and future outlook of Artificial intelligence in pancreatic cancer.Frontiers in oncology · 2024Review
- A pancreatic cancer risk prediction model (Prism) developed and validated on large-scale US clinical data.EBioMedicine · 2023Article
- An Integrative Pancreatic Cancer Risk Prediction Model in the UK Biobank.Biomedicines · 2023Article
- A novel prediction model of the risk of pancreatic cancer among diabetes patients using multiple clinical data and machine learning.Cancer medicine · 2023Observational
- Pancreatic cancer is associated with medication changes prior to clinical diagnosis.Nature communications · 2023Article
- Article
- Prediction of Pancreatic Cancer in Diabetes Patients with Worsening Glycemic Control.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022Article
- Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review.Pancreas · 2021Review
- Early detection of pancreatic cancer.The lancet. Gastroenterology & hepatology · 2020Review
- Review
- Screening for pancreatic cancer has the potential to save lives, but is it practical?Expert review of gastroenterology & hepatologyReview
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
BACKGROUND AND
objectiveEarly detection methods for pancreatic cancer are lacking. We aimed to develop a prediction model for pancreatic cancer based on changes in health captured by healthcare claims data.
methodsWe conducted a case-control study on 29,646 Medicare-enrolled patients aged 68 years and above with pancreatic ductal adenocarcinoma (PDAC) reported to the Surveillance Epidemiology an End Results (SEER) tumor registries program in 2004-2011 and 88,938 age and sex-matched controls. We developed a prediction model using multivariable logistic regression on Medicare claims for 16 risk factors and pre-diagnostic symptoms of PDAC present within 15 months prior to PDAC diagnosis. Claims within 3 months of PDAC diagnosis were excluded in sensitivity analyses. We evaluated the discriminatory power of the model with the area under the receiver operating curve (AUC) and performed cross-validation by bootstrapping.
resultsThe prediction model on all cases and controls reached AUC of 0.68. Excluding the final 3 months of claims lowered the AUC to 0.58. Among new-onset diabetes patients, the prediction model reached AUC of 0.73, which decreased to 0.63 when claims from the final 3 months were excluded. Performance measures of the prediction models was confirmed by internal validation using the bootstrap method.
conclusionModels based on healthcare claims for clinical risk factors, symptoms and signs of pancreatic cancer are limited in classifying those who go on to diagnosis of pancreatic cancer and those who do not, especially when excluding claims that immediately precede the diagnosis of PDAC.
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