A Review of: “Analysis of Clinical Trials Using SAS: A Practical Guide,by A. Dmitrienko,G. Molenberghs,C. Chuang-Stein,and W. Offen”

A testing procedure is proposed to assess the consistency of noninferiority from a collection of trials based on simultaneous t lower confidence bounds or Scheffé's lower confidence bounds. Methods for simultaneous inferences on pairwise or many-to-one comparisons among multiple noninferiority trials are also discussed. To avoid bias due to subjective trial exclusion a tuning parameter k is embedded into the testing procedure to provide flexibility to quantify the “consistency of noninferiority” when the total number of trials is large. The size and power of the proposed test are discussed. The method is illustrated using simulations and real data analysis.     

A Review of: “Statistics: Concepts and Controversies,Sixth Edition,by D. S. Moore and W. I. Notz (Eds.)”

Contrasts were evaluated for the maximum blood or plasma concentration (C _max) of drugs measured after repeated and single oral administrations. Variances C _max of were calculated and also simulated for a single drug as well as the comparison of two formulations, i.e., for the analysis of investigations of both bioavailability and bioequivalence. The coefficient of variation (C V) of C _max was higher in the steady state than after a single drug administration when the variability of the disposition rate constant (k) was substantially larger than that of the absorption rate constant (k_a )In turn, the CV of C _max was substantially lower following repeated than after single drug administration when the variability of k_a dominated that of k.The latter condition often prevails in practice since the relative variation of absorption rates generally substantially exceeds that of clearance (the latter being proportional to k) The statistical insensitivity is superimposed on the low kinetic sensitivity exhibited by C _maxfollowing repeated drug administrations. Consequently, bioequivalence trials conducted in the steady state generally permit a declaration of equivalence even between drug products that have very different absorption rates     

A Review of: “Interpreting and Reporting Clinical Trials: A Guide to the CONSORT Statement and the Principles of Randomised Controlled Trials,by A. Keech,V. Gebski,and R. Pike (eds.)”

Traditionally, Phase II trials have been conducted as single-arm trials to compare the response probabilities between an experimental therapy and a historical control. Historical control data, however, often have a small sample size, are collected from a different patient population, or use a different response assessment method, so that a direct comparison between a historical control and an experimental therapy may be severely biased. Randomized Phase II trials entering patients prospectively to both experimental and control arms have been proposed to avoid any bias in such cases. The small sample sizes for typical Phase II clinical trials imply that the use of exact statistical methods for their design and analysis is appropriate. In this article, we propose two-stage randomized Phase II trials based on Fisher’s exact test, which does not require specification of the response probability of the control arm for testing. Through numerical studies, we observe that the proposed method controls the type I error accurately and maintains a high power. If we specify the response probabilities of the two arms under the alternative hypothesis, we can identify good randomized Phase II trial designs by adopting the Simon’s minimax and optimal design concepts that were developed for single-arm Phase II trials.