Adaptive Budgets in Clinical Trials

We consider situations where a drug developer gets access to additional financial resources when a promising result has been observed in a preplanned interim analysis during a clinical trial that should lead to the registration of the drug. First, the option that the drug developer completely puts the additional resources into increasing the second-stage sample size has been investigated. If investors invest more the larger the observed interim effect, this may not be a reasonable strategy. Then, additional sample sizes are applied when the conditional power is already very large and hardly any impact on the overall power can be expected. Nevertheless, further reducing the Type II error rate in promising situations may be of interest for a drug developer. In a second step, sample size was based on a utility function including the reward of registration (which was allowed to depend on the observed effect size at the end of the trial) and sampling costs. Utility as a function of the sample size may have more than one local maximum, one of them at the lowest per group sample size. For small effects, an optimal strategy could be to apply the smallest sample size accepted by regulators.

[1]  Cyrus R. Mehta,et al.  Authors' response to “Comment on adaptive increase in sample size when interim results are promising” , 2011 .

[2]  H. Schäfer,et al.  A general statistical principle for changing a design any time during the course of a trial , 2004, Statistics in medicine.

[3]  H. Schäfer,et al.  Adaptive Group Sequential Designs for Clinical Trials: Combining the Advantages of Adaptive and of Classical Group Sequential Approaches , 2001, Biometrics.

[4]  Cyrus R Mehta,et al.  Adaptive increase in sample size when interim results are promising: A practical guide with examples , 2011, Statistics in medicine.

[5]  A. Tsiatis,et al.  On the inefficiency of the adaptive design for monitoring clinical trials , 2003 .

[6]  Martin Posch,et al.  On the efficiency of adaptive designs for flexible interim decisions in clinical trials , 2006 .

[7]  Sue-Jane Wang,et al.  Modification of Sample Size in Group Sequential Clinical Trials , 1999, Biometrics.

[8]  D. DeMets,et al.  Increasing the sample size when the unblinded interim result is promising , 2004, Statistics in medicine.

[9]  M A Proschan,et al.  Designed extension of studies based on conditional power. , 1995, Biometrics.

[10]  P. Bauer,et al.  The reassessment of trial perspectives from interim data—a critical view , 2006, Statistics in medicine.

[11]  Frank Bretz,et al.  Joint EMA, ISBS, and DR‐IBS International Symposium on Biopharmaceutical Statistics: Bridging drug development from research to marketing , 2013, Statistics in medicine.

[12]  Peter Bauer,et al.  Maximum inflation of the type 1 error rate when sample size and allocation rate are adapted in a pre-planned interim look. , 2011, Statistics in medicine.

[13]  HansâHelge Müller,et al.  Adaptive Group Sequential Designs for Clinical Trials: Combining the Advantages of Adaptive and of Classical Group Sequential Approaches , 2001 .

[14]  Christopher Jennison,et al.  Mid‐course sample size modification in clinical trials based on the observed treatment effect , 2002, Statistics in medicine.

[15]  Michael D. Smith,et al.  Adaptive Bayesian Designs for Dose-Ranging Drug Trials , 2002 .

[16]  Martin Posch,et al.  Issues in designing flexible trials , 2003, Statistics in medicine.

[17]  P. Bauer,et al.  Evaluation of experiments with adaptive interim analyses. , 1994, Biometrics.

[18]  C. Burman,et al.  Are Flexible Designs Sound? , 2006, Biometrics.

[19]  Elodie Blondiaux,et al.  A New Method for a One-Shot Unblinded Sample Size Reassessment in Two-Group Trials : How & When ? , 2009 .

[20]  H. Eichler,et al.  Factors associated with success of market authorisation applications for pharmaceutical drugs submitted to the European Medicines Agency , 2009, European Journal of Clinical Pharmacology.

[21]  W. Lehmacher,et al.  Adaptive Sample Size Calculations in Group Sequential Trials , 1999, Biometrics.

[22]  Gregory P Levin,et al.  Comments on 'Adaptive increase in sample size when interim results are promising: a practical guide with examples'. , 2011, Statistics in medicine.

[23]  W. Brannath,et al.  Recursive Combination Tests , 2002 .

[24]  Ekkehard Glimm Comments on 'Adaptive increase in sample size when interim results are promising: a practical guide with examples' by C. R. Mehta and S. J. Pocock. , 2012, Statistics in medicine.

[25]  Keith Dunnigan,et al.  Increasing the sample size at interim for a two-sample experiment without Type I error inflation. , 2010, Pharmaceutical statistics.