Interim analyses in clinical trials: classical vs. Bayesian approaches.

This paper concerns interim analysis in clinical trials involving two treatments from the points of view of both classical and Bayesian inference. I criticize classical hypothesis testing in this setting and describe and recommend a Bayesian approach in which sampling stops when the probability that one treatment is the better exceeds a specified value. I consider application to normal sampling analysed in stages and evaluate the gain in average sample number as a function of the number of interim analyses.

[1]  F. J. Anscombe.  Sequential Medical Trials , 1963 .

[2]  B. Brown.  Comments on the Dupont manuscript , 1983 .

[3]  K McPherson,et al.  On choosing the number of interim analyses in clinical trials. , 1982, Experientia. Supplementum.

[4]  D A Berry,et al.  Statistical inference and the design of clinical trials. , 1980, Biomedicine / [publiee pour l'A.A.I.C.I.G.].

[5]  P. Canner.  Comment on "Statistical inference from clinical trials: choosing the right P value". , 1983, Controlled clinical trials.

[6]  D. J. Finney,et al.  Introduction to Probability and Statistics , 1968 .

[7]  J. Cornfield.  Sequential Trials, Sequential Analysis and the Likelihood Principle , 1966 .

[8]  P. Canner.  Monitoring treatment differences in long-term clinical trials. , 1977, Biometrics.

[9]  L. J. Savage,et al.  The Foundations of Statistics , 1955 .

[10]  S. Pocock.  Group sequential methods in the design and analysis of clinical trials , 1977 .

[11]  R. Madsen,et al.  P values for tests using a repeated significance test design , 1982 .

[12]  P. O'Brien,et al.  A multiple testing procedure for clinical trials. , 1979, Biometrics.

[13]  M C Weinstein,et al.  Allocation of subjects in medical experiments. , 1974, The New England journal of medicine.

[14]  W. Dupont.  Sequential stopping rules and sequentially adjusted P values: does one require the other? , 1983, Controlled clinical trials.

[15]  G A Diamond,et al.  Clinical trials and statistical verdicts: probable grounds for appeal. , 1983, Annals of internal medicine.