The overall scientific goal of this ambitious program project is to develop highly innovative methods for cancer clinical trials that can hasten successful introduction of effective new therapies into practice. The method of approach is to leverage recent advances in statistical and computational science to create new clinical trial designs and data analysis tools that resolve many of the key scientific limitations of current clinical trial methodology. The projects focus on practical design and analysis problems in Phase II and Phase 111 clinical trials, the problem of missing data and efficient use of prognostic information, postmarketing surveillance and comparative effectiveness research using clinical trial data, pharmacogenetics and individualized therapies, and the potential of dynamic treatment regimens to improve cancer treatment. The proposed clinical trial design and analysis innovations have the potential to change the prevailing clinical trial paradigm and greatly increase the rate of discovery and translation of new treatments into clinical practice. Our multi-institutional approach includes an effective and energetic process for intense, coordinated implementation, communication and dissemination of results, including developing new software for practical implementation of the newly developed methods. Our comprehensive and novel approach will lead to significant improvements in cancer clinical trial practice that will result in improved health of cancer patients.

Public Health Relevance

The proposed program project aims to dramatically improve the efficiency of the cancer clinical trial process in order to improve the health and longevity of cancer patients. This is extremely important to public health since almost all biomedical advances in cancer treatment must pass through the clinical trial process before becoming accepted clinical practice.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA142538-05
Application #
8643480
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Wu, Roy S
Project Start
2010-04-01
Project End
2015-03-31
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
5
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Liang, Shuhan; Lu, Wenbin; Song, Rui et al. (2018) Sparse concordance-assisted learning for optimal treatment decision. J Mach Learn Res 18:
Wang, Yu-Bo; Chen, Ming-Hui; Kuo, Lynn et al. (2018) A New Monte Carlo Method for Estimating Marginal Likelihoods. Bayesian Anal 13:311-333
Laber, Eric B; Wu, Fan; Munera, Catherine et al. (2018) Identifying optimal dosage regimes under safety constraints: An application to long term opioid treatment of chronic pain. Stat Med 37:1407-1418
Diao, Guoqing; Dong, Jun; Zeng, Donglin et al. (2018) Biomarker threshold adaptive designs for survival endpoints. J Biopharm Stat 28:1038-1054
Davenport, Clemontina A; Maity, Arnab; Sullivan, Patrick F et al. (2018) A Powerful Test for SNP Effects on Multivariate Binary Outcomes using Kernel Machine Regression. Stat Biosci 10:117-138
Chen, Stephanie T; Xiao, Luo; Staicu, Ana-Maria (2018) A Smoothing-based Goodness-of-Fit Test of Covariance for Functional Data. Biometrics :
Chen, Kun; Mishra, Neha; Smyth, Joan et al. (2018) A Tailored Multivariate Mixture Model for Detecting Proteins of Concordant Change Among Virulent Strains of Clostridium Perfringens. J Am Stat Assoc 113:546-559
Wang, Lan; Zhou, Yu; Song, Rui et al. (2018) Quantile-Optimal Treatment Regimes. J Am Stat Assoc 113:1243-1254
Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie (2018) Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data. Biometrics :
Lachos, Victor H; A Matos, Larissa; Castro, Luis M et al. (2018) Flexible longitudinal linear mixed models for multiple censored responses data. Stat Med :

Showing the most recent 10 out of 549 publications