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PancPRO: Risk Assessment for Individuals With a Family History of Pancreatic Cancer

Wenyi Wang, Sining Chen, Kieran A. Brune, Ralph H. Hruban, Giovanni Parmigiani, Alison P. Klein

From the Departments of Biostatistics, Environmental Health Sciences, and Epidemiology, Johns Hopkins Bloomberg School of Public Health; and the Departments of Pathology and Oncology, Sol Goldman Pancreatic Cancer Research Center, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD

Address reprint requests to Alison Klein, PhD, MHS, Sol Goldman Pancreatic Cancer Research Center, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, 1550 Orleans St, Rm 303, Baltimore, MD 21231; e-mail: aklein1{at}jhmi.edu

Purpose The rapid fatality of pancreatic cancer is, in large part, the result of an advanced stage of diagnosis for the majority of patients. Identification of individuals at high risk of developing pancreatic cancer is a first step towards the early detection of this disease. Individuals who may harbor a major pancreatic cancer susceptibility gene are one such high-risk group. The goal of this study was to develop and validate PancPRO, a Mendelian model for pancreatic cancer risk prediction in individuals with familial pancreatic cancer, to identify high-risk individuals.

Methods PancPRO was built by extending the Bayesian modeling framework developed for BRCAPRO, trained using published data, and validated using independent prospective data on 961 families enrolled onto the National Familial Pancreas Tumor Registry, including 26 individuals who developed incident pancreatic cancer during follow-up.

Results We developed a risk prediction model, PancPRO, and free software for the estimation of pancreatic cancer susceptibility gene carrier probabilities and absolute pancreatic cancer risk. Model validation demonstrated an observed to predicted pancreatic cancer ratio of 0.83 (95% CI, 0.52 to 1.20) and high discriminatory ability, with an area under the receiver operating characteristic curve of 0.75 (95% CI, 0.68 to 0.81) for PancPRO.

Conclusion PancPRO is the first risk prediction model for pancreatic cancer. When we validated our model using the largest registry of familial pancreatic cancer, our model provided accurate risk assessment. Our findings highlight the importance of detailed family history for clinical cancer risk assessment and demonstrate that accurate genetic risk assessment is possible even when the causative genes are not known.

Supported in part by the Specialized Programs of Research Excellence in Gastrointestinal Cancer Grant No. CA62924 from the National Cancer Institute, the Michael Rolfe Foundation, and Grant No. R01CA105090-01A1.

Presented in part at the 14th Annual Meeting of the International Genetic Epidemiology Society, October 23-24, 2005, Park City, UT; and the 55th Annual Meeting of the American Society of Human Genetics, October 26-29, 2005, Salt Lake City, UT.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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