The general objective of the proposed research is to develop sequential statistical methods for the data monitoring of complex clinical trials in cancer. In many of these clinical trials, the principal outcomes include immediate responses that can be completely measured soon after a patient enters the study; or in many others, time to an event, responses recorded periodically over time, or events that recur over time. Sequential monitoring of responses of these types usually fit into a unified framework. In a large clinical trial when data are monitored, a test statistic computed sequentially over time forms a stochastic process which is approximately Gaussian. In many practical situations, this process has independent increments and can be rescaled to become the Brownian motion process. The applicant proposes to investigate the monitoring of the Brownian motion process from different points of view. Each of the proposed research topics is directly motivated by current and anticipated statistical needs for the design and data monitoring of clinical trials. The three specific topics of research proposed are : (1) two-sample sequential comparisons of changes in repeated measures; (2) sequential analysis of Poisson data under a random effects model; and (3) occasional or continuous data monitoring in clinical trials. Additional research topics will be identified as work proceeds on these projects and in response to discussions with Dr. David DeMets of the University of Wisconsin Clinical Cancer Center and Dr. Timothy Chen of the National Cancer Institutes.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA055098-05
Application #
2769737
Study Section
Special Emphasis Panel (ZRG7-SSS-0 (02))
Program Officer
Erickson, Burdette (BUD) W
Project Start
1991-07-01
Project End
2000-08-30
Budget Start
1998-09-01
Budget End
1999-08-31
Support Year
5
Fiscal Year
1998
Total Cost
Indirect Cost
Name
George Washington University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
City
Washington
State
DC
Country
United States
Zip Code
20052
Lan, K K Gordon; Lachin, John M; Bautista, Oliver (2003) Over-ruling a group sequential boundary--a stopping rule versus a guideline. Stat Med 22:3347-55
Hu, M; Lachin, J M (2001) Application of robust estimating equations to the analysis of quantitative longitudinal data. Stat Med 20:3411-28
Bautista, O M; Bain, R P; Lachin, J M (2000) A flexible stochastic curtailing procedure for the log-rank test. Control Clin Trials 21:428-39
Lan, K K; Lachin, J M (1995) Martingales without tears. Lifetime Data Anal 1:361-75
Lan, K K; Rosenberger, W F; Lachin, J M (1995) Sequential monitoring of survival data with the Wilcoxon statistic. Biometrics 51:1175-83
Wu, M C; Lan, K K; Connett, J E (1994) Use of surrogate information time for monitoring the effect of treatment on the change in a response variable in clinical trials. Stat Med 13:945-53
Lan, K K; Rosenberger, W F; Lachin, J M (1993) Use of spending functions for occasional or continuous monitoring of data in clinical trials. Stat Med 12:2219-31
Lan, K K; Zucker, D M (1993) Sequential monitoring of clinical trials: the role of information and Brownian motion. Stat Med 12:753-65