Sequential monitoring of clinical trials with multiple survival endpoints.
Many clinical trials follow patients for several different types of survival endpoints, such as mortality, disease progression, and time until dose-limiting toxicity. Conduct of such trials often requires that the accumulating data be reviewed periodically to protect the safety of participating patients and possibly identify early treatment differences. This paper proposes a group sequential method for assessing multiple survival endpoints using repeated confidence intervals. Counting processes for each survival endpoint are used to estimate both the correlation between outcomes and between times of interim analysis. The methods are illustrated using a clinical trial comparing two treatments for PCP prevention in AIDS patients. The operating characteristics of three strategies for constructing confidence intervals are assessed and compared in a simulation study.
Williams
P L
PL
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
D017088:AIDS-Related Opportunistic Infections / Q000517:prevention & control; D000163:Acquired Immunodeficiency Syndrome / Q000401:mortality / Q000628:therapy; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D016017:Odds Ratio; D011020:Pneumonia, Pneumocystis / Q000517:prevention & control; D016016:Proportional Hazards Models; D012306:Risk; D016019:Survival Analysis