Pancpro: Risk Assessment for Individuals with a Family History of Pancreatic Cancer.
From: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
- Publish Date: Apr 2007
- ISSN: 1527-7755
- Volume: 25
- Issue: 11
- Pages: 1417-22
- Medium: Internet
- Language: English
- Citation (JAMA): Wang Wenyi, Chen Sining, Brune Kieran A, et al. Pancpro: Risk Assessment for Individuals with a Family History of Pancreatic Cancer.. J. Clin. Oncol. Apr 2007;25:1417-22
Abstract
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.
Mesh Headings (Keywords): Bayes Theorem, Female, Genetic Predisposition to Disease, Humans, Male, Pancreatic Neoplasms, Pedigree, ROC Curve, Registries, Risk Assessment, Risk Factors
Check for Full Text / PubMed Unique Identifier (PMID): 17416862
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