Because of the ethical and economic considerations in the design of clinical trials to test the efficacy and possible toxic effects of a newly developed drug or therapy, and because of the inherent sequential nature of the information flow during the course of the trial, there has been increasing interest from the biopharmaceutical industry in group sequential methods that can adapt to information acquired during the course of the trial and reduce the cost and study duration of conventional trials which assume a fixed sample size/study duration. An important objective of this research is to develop a comprehensive methodology for the design and analysis of group sequential trials. Certain long-standing problems in the field will be resolved in this connection, including valid confidence intervals following group sequential tests, calendar time versus information time in the case of failure-time endpoints, and sample size re-estimation during the course of a trial. A closely related objective is the development of nonlinear and nonparametric methods for the analysis of clinical trials with multiple endpoints, particularly those with combined efficacy-toxicity outcomes in cancer, arthritis and rheumatism treatments. Understanding the toxic-therapeutic relationships of these treatments will also help physicians to individualize and adapt the dose for different patients. Another objective of this research is to develop efficient statistical methods for nonlinear mixed effects models in population pharmacokinetics and for other problems in clinical pharmacology.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA088890-03
Application #
6756553
Study Section
Special Emphasis Panel (ZRG1-SNEM-5 (01))
Program Officer
Starks, Vaurice
Project Start
2002-07-01
Project End
2005-12-31
Budget Start
2004-07-01
Budget End
2005-12-31
Support Year
3
Fiscal Year
2004
Total Cost
$103,074
Indirect Cost
Name
Stanford University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Jin, Yuxue; Lai, Tze Leung (2017) A new approach to regression analysis of censored competing-risks data. Lifetime Data Anal 23:605-625
Lai, Tze Leung; Lavori, Philip W; Tsang, Ka Wai (2015) Adaptive design of confirmatory trials: Advances and challenges. Contemp Clin Trials 45:93-102
Shih, Mei-Chiung; Turakhia, Mintu; Lai, Tze Leung (2015) Innovative designs of point-of-care comparative effectiveness trials. Contemp Clin Trials 45:61-8
Lai, Tze Leung; Xing, Haipeng; Zhang, Nancy (2008) Stochastic segmentation models for array-based comparative genomic hybridization data analysis. Biostatistics 9:290-307
Leung Lai, Tze; Shih, Mei-Chiung; Wong, Samuel Po-Shing (2006) Flexible modeling via a hybrid estimation scheme in generalized mixed models for longitudinal data. Biometrics 62:159-67
Lai, Tze Leung; Shih, Mei-Chiung; Zhu, Guangrui (2006) Modified Haybittle-Peto group sequential designs for testing superiority and non-inferiority hypotheses in clinical trials. Stat Med 25:1149-67
Lai, Tze Leung; Shih, Mei-Chiung; Wong, Samuel P (2006) A new approach to modeling covariate effects and individualization in population pharmacokinetics-pharmacodynamics. J Pharmacokinet Pharmacodyn 33:49-74