New technique to statistically analyze results of clinical trials

Statisticians at St. Jude Children's Research Hospital have developed a new technique that allows researchers to statistically analyze results of clinical trials.

In it, all participants receive the new treatment being studied and none are assigned to a control group getting the existing treatment. Instead, the treatment group is compared with a so-called "historical control" composed of patients who got the existing treatment in a previous study.

A report on this new method appears in the August issue of Statistics in Medicine.

The St. Jude report is the first to describe this novel statistical method called sequential interim analysis using a historical control group, the authors said. In an interim analysis, researchers statistically analyze the accumulating results of the clinical trial at several points during the course of the study, rather than wait until the end of the trial in order to determine if the trial should be stopped early.

"This technique lets investigators determine how probable it is that their decision to stop the trial would have changed if they had let the clinical trial continue to the end," said the paper's first author, Xiaoping Xiong, Ph.D., associate member of the St. Jude Department of Biostatistics.

The other authors of this study are James Boyett, Ph.D., chair of the St. Jude Department of Biostatistics; and Ming Tan, formerly of St. Jude, currently Director of Biostatistics for the Greenbaum Cancer Center at the University of Maryland, Baltimore.

This work was supported in part by the National Institutes of Health and ALSAC.