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Clinical Trials
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A decision rule for sequential monitoring of clinical trials with a primary and supportive outcome

Yanli Zhao

Clinical Biostatistics, Merck Research Laboratories, North Wales, PA 19454, USA, yanli_zhao{at}merck.com

Patricia M. Grambsch

Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA

James D. Neaton

Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA

Background Many clinical trials have multiple outcomes. Formal interim monitoring guidelines that take account of multiple outcomes can be useful to Data Monitoring Committees (DMC). Previous research has focused on marginal criteria that control the overall type I error for bivariate endpoints corresponding to efficacy and safety. Usually, an `or' decision rule is used, that is, the trial is stopped when either the safety or the efficacy endpoint crosses a boundary.

Purpose In many trials there is not a clear difference between what is considered a safety and an efficacy endpoint. Likewise, in some studies there is interest in more than one disease outcome and while there may be a primary efficacy endpoint, interim monitoring might also involve a measure of overall health. For these situations, an `and' decision rule might be more appropriate; that is, the trial is stopped only when both endpoints cross a boundary. Formulation of this new decision rule at the design stage would encourage more discussion among trial investigators of monitoring guidelines and would result in improved guidelines for DMCs.

Methods In this paper, we propose stopping guidelines for such trials with two major outcomes that control the overall type I error and stop early only if both endpoints indicate superiority for the same treatment. Trials with two treatments are considered and we develop sets of paired two-sided boundaries, permitting one endpoint to be primary and the other supportive, with or without pre-specifying which one is primary.

Results The results show that the boundaries depend on the correlation between the two outcomes. The critical values increase as the correlation increases in most cases. For low to moderate correlation and before the last stage, critical values based on the O'Brien Fleming (or Pocock) error spending function that consider the correlation are lower than those which do not.

Limitations Investigators might not want to stop a trial early with the small size of the critical values that result from this decision rule for some situations. For a trial in which the treatment effect for one outcome is large, while for the other it is small, the proposed decision rule has low power to accept this treatment for its superiority on both outcomes. Also, we do not provide a separate P-value for each outcome since type I error is not controlled for individual null hypotheses.

Conclusions For trials involving two major health outcomes these stopping guidelines may be appropriate for DMCs when the trial investigators and sponsor recommend that early termination not be considered unless the findings are consistent for both outcomes. Clinical Trials 2007; 4: 140—153. http://ctj.sagepub.com

Clinical Trials, Vol. 4, No. 2, 140-153 (2007)
DOI: 10.1177/1740774507076936


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ANN INTERN MEDHome page
S. N. Goodman
Stopping at Nothing? Some Dilemmas of Data Monitoring in Clinical Trials
Ann Intern Med, June 19, 2007; 146(12): 882 - 887.
[Abstract] [Full Text] [PDF]



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