A general inefficacy interim monitoring rule for randomized clinical trials.
BACKGROUND
The ultimate goal of a phase III randomized clinical trial designed to demonstrate superiority of a new versus standard therapy is to provide sufficiently compelling evidence to affect clinical practice. To balance patient interests against the need for acquiring evidence it is desirable to stop a study for inefficacy as soon as convincing evidence that the new therapy is not beneficial becomes available.


OBJECTIVE
To discuss potential deficiencies in some commonly used inefficacy monitoring rules and to propose a comprehensive inefficacy monitoring procedure.


METHODS
The proposed approach is developed using clinical, logistical, and statistical considerations. The new approach is compared to the commonly used inefficacy rules in a simulation study.


RESULTS
Some of the commonly used inefficacy rules are suboptimal with respect to the strength of evidence required for stopping throughout the trial: too conservative in the middle and/or too aggressive at the end. Our approach allows timely stopping (a) if the new therapy is harmful, and (b) if the interim data provides convincing evidence that the new therapy has no tangible benefit. Relative to common inefficacy rules, our procedure is shown to result in potentially fewer treated patients and shorter study duration under the null hypothesis with only a minor loss of power under the alternative hypothesis.


CONCLUSIONS
The proposed procedure is applicable to superiority designs with well-defined clinical objectives.


CONCLUSIONS
The proposed inefficacy approach is attractive from statistical, clinical, and logistical standpoints. By decreasing average stopping times relative to the commonly used boundaries, our rule lessens patient exposure to inactive treatments, improves resource utilization, and accelerates dissemination of important clinical information. At the same time, the proposed rule provides a clear benchmark for providing compelling evidence that the new therapy is not beneficial. Clinical Trials 2010; 7: 197-208. http://ctj.sagepub.com.
Freidlin
Boris
B
Biometric Research Branch, National Cancer Institute, Bethesda, MD, USA. freidlinb@ctep.nci.nih.gov
Korn
Edward L
EL
Gray
Robert
R
D000465:Algorithms; D017326:Clinical Trials, Phase III as Topic / Q000706:statistics & numerical data; D004526:Efficiency; D023381:Endpoint Determination / Q000592:standards*; D006801:Humans; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*