Development, Application, and Evaluation of Prediction Models for Cancer Risk and Prognosis issued by the National Cancer Institute (NCI) supports research on innovative statistical methods for developing and evaluating new and existing cancer risk prediction models. Predictive accuracy is a key factor for determining clinical applicability of cancer risk prediction models in identifying high-risk individuals for ealy prevention. With continuously emerging risk factors for cancer, there is a pressing need for timely assessment of their added values for prediction. But study designs that balance cost and statistical efficiency and accompanying statistical methods are mostly lacking. This proposal responds to this PA by developing and evaluating cost-effective two-phase stratified case-control study designs and statistical inference methods for developing and evaluating absolute risk prediction models for cancer. Our proposed work is built on a popular method that integrates case-control data and external hazard rates of cancer and mortality to predict cancer absolute risk. As a showcase example for our statistical methods and accompanying software, we explore the added value of volumetric breast density for predicting breast cancer risk.

Public Health Relevance

This project proposes to develop efficient study designs and statistical inference methods for developing and evaluating cancer absolute risk prediction models. Our methods, accompanied by a comprehensive and user-friendly software, will offer cancer researchers a rich arsenal of statistical tools for assessing the predictive potential of expensive candidate predictors under cost constraints.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA164305-01A1
Application #
8503712
Study Section
Epidemiology of Cancer Study Section (EPIC)
Program Officer
Dunn, Michelle C
Project Start
2013-04-01
Project End
2017-03-31
Budget Start
2013-04-01
Budget End
2014-03-31
Support Year
1
Fiscal Year
2013
Total Cost
$353,473
Indirect Cost
$115,223
Name
University of Pennsylvania
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Chai, Xinglei; Friebel, Tara M; Singer, Christian F et al. (2014) Use of risk-reducing surgeries in a prospective cohort of 1,499 BRCA1 and BRCA2 mutation carriers. Breast Cancer Res Treat 148:397-406