Bayesian interim analysis of phase II cancer clinical trials.
Many popular sequential phase II clinical trial designs optimize some criterion subject to constraints on the error probabilities at null and alternative values of the response rate. Such designs may forfeit optimality if one fails to conduct analyses strictly according to plan. Moreover, a decision, say, to accept the experimental therapy at one interim analysis does not necessarily imply the same degree of evidence as the same decision when made at another analysis. I propose an alternative design that bases decisions on the ability of the data to persuade either a sceptic or an enthusiast. My standard of evidence, called the persuasion probability, is based on the Bayesian posterior probability that the experimental treatment is superior to the standard. The design calls for termination at any interim analysis at which an observed persuasion probability exceeds its critical value. I investigate the standards of evidence implied by some frequentist procedures and calculate frequentist properties of persuasion-probability designs.
Heitjan
D F
DF
Division of Biostatistics, Columbia School of Public Health, New York, NY 10032, USA.
D000208:Acute Disease; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D001499:Bayes Theorem; D017322:Clinical Trials, Phase II as Topic / Q000379:methods*; D003561:Cytarabine / Q000008:administration & dosage; D006801:Humans; D015255:Idarubicin / Q000008:administration & dosage; D007951:Leukemia, Myeloid / Q000188:drug therapy; D015233:Models, Statistical; D012107:Research Design; D014740:Vidarabine / Q000008:administration & dosage / Q000031:analogs & derivatives
D000970:Antineoplastic Agents; D003561:Cytarabine; D014740:Vidarabine; C024352:fludarabine; D015255:Idarubicin