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.
Highlights
Over 50,000 new cases and 40,000 deaths from pancreatic cancer occur annually in the U.S.[1]
We aimed to develop a prediction model for pancreatic cancer based on changes in health captured by healthcare claims data
Models 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 pancreatic ductal adenocarcinoma (PDAC)
Summary
Over 50,000 new cases and 40,000 deaths from pancreatic cancer occur annually in the U.S.[1]. People with new diagnoses of diabetes are at 4 -fold increased risk of pancreatic cancer diagnosis in the two years. Changes in health as manifested in healthcare claims could potentially be used to detect PDAC at earlier stages. Previous prediction models for PDAC that have incorporated data on changes in health have shown modest discriminative power, but have varied applicability to the general population in the U.S [11,12,13] We hypothesize that predictive modeling using healthcare claims from a national insurance program in the U.S can help identify older adults who are at high risk of pancreatic cancer. We aimed to develop a prediction model for pancreatic cancer based on changes in health captured by healthcare claims data
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