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UID:20250915T080304EDT-3762cUAUIu@132.216.98.100
DTSTAMP:20250915T120304Z
DESCRIPTION:Jinbo Chen\, PhD\n\nAssociate Professor\, Department of Biostat
 istics and Epidemiology\, Perelman School of Medicine\, University of Penn
 sylvania\n\nStatistical Methods for Quantifying Predictive Accuracy of Abs
 olute Risk Prediction Models\n\nALL ARE WELCOME\n\nABSTRACT:\n\nStatistica
 l models for predicting cancer absolute risk are useful tools for stratify
 ing patients into different risk groups. A popular method to develop these
  models is through integration of data from multiple sources that provide 
 an odds ratio function\, composite cancer hazard rates\, and competing ris
 k of mortality hazard rates. Emerging risk predictors can be incorporated 
 into the odds ratio function to improve predictive accuracy. Age-specific 
 area under the receiver operating characteristic curve (AUC) has been the 
 most commonly used statistic to evaluate the performance of absolute risk 
 prediction models. Alternative statistical measures for evaluating the acc
 uracy of prediction models with binary or time-dependent outcomes have bee
 n well developed. But their application to absolute risk prediction requir
 es extensions to accommodate multiple data sources as well as the time-dep
 endent nature. Here\, we develop appropriate statistical measures for quan
 tifying predictive accuracy of absolute risk prediction models\, consideri
 ng a general scenario where the odds ratio function is developed from a tw
 o-phase stratified case-control study. We demonstrate the performance of o
 ur methods through extensive simulation studies and application to a breas
 t cancer risk prediction model. In the recent literature\, to evaluate the
  predictiveness of risk-associated single neucleotide polymorphisms\, the 
 odds ratio function was approximated by the product of marginal odds ratio
  functions. We evaluate the applicability of our method to this approximat
 ed method for cancer risk prediction.\n\nBIO:\n\nDr. Jinbo Chen is current
 ly a tenured associate professor at the University of Pennsylvania Perelma
 n School of Medicine\, Department of Biostatistics and Epidemiology. She g
 raduated from the University of Washington\, Department of Biostatistics\,
  in 2002\, and subsequently worked at the NCI\, Division of Cancer Epidemi
 ology and Genetics for 3 years before moving to Penn in 2006. Jinbo's area
  of research interest includes design and analysis of two-phase outcome-de
 pendent studies\, the development and assessment of risk prediction models
 \, and statistics genetics.\n\n \n
DTSTART:20160511T150000Z
DTEND:20160511T160000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Special Seminar: 'Statistical Methods for Quantifying Predictive Ac
 curacy of Absolute Risk Prediction Models'
URL:/epi-biostat-occh/channels/event/special-seminar-s
 tatistical-methods-quantifying-predictive-accuracy-absolute-risk-predictio
 n-models-260131
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