scholarly journals A review of available software for adaptive clinical trial design

2020 ◽  
Vol 17 (3) ◽  
pp. 323-331
Author(s):  
Michael John Grayling ◽  
Graham Mark Wheeler
Keyword(s):  
Trial Design ◽  
Adaptive Design ◽  
Clinical Trial Design ◽  
Adaptive Designs ◽  
Group Sequential Design ◽  
Group Sequential ◽  
Adaptive Trial Design ◽  
Code Distribution ◽  
User Friendly ◽  
Adaptive Trial

Background/aims: The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design. Methods: We review articles from 31 journals published in 2013–2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals’ policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest. Results: Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs. Conclusions: There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.

scholarly journals The FDA adaptive trial design guidance in a nutshell - A review in Q&A format for decision makers

2016 ◽  
Author(s):  
Klaus Gottlieb
Keyword(s):  
Trial Design ◽  
Adaptive Design ◽  
Decision Makers ◽  
Development Programs ◽  
Fda Guidance ◽  
Regulatory Affairs ◽  
Frequent Use ◽  
Adaptive Trial Design ◽  
Adaptive Trial ◽  
Design Guidance

The FDA adaptive trial design guidance (1) is a thoughtful but lengthy document that explains on 50 pages wide-ranging and important topics “such as ... what aspects of adaptive design trials (i.e., clinical, statistical, regulatory) call for special consideration, ... when to interact with FDA while planning and conducting adaptive design studies, ... what information to include in the adaptive design for FDA review, and ... issues to consider in the evaluation of a completed adaptive design study.” [20-24]. The advice in the guidance is often misinterpreted, misquoted or ignored. This is unfortunate because an appropriate use of adaptive designs could increase the chances of success in drug development programs. Decision makers rely on the advice of regulatory affairs professionals and statisticians to interpret the guidance. Unfortunately, many clinical trial statisticians and regulatory professionals only have a rudimentary understanding of the guidance, presumably because the document is somewhat inscrutable for both audiences, too ‘regulatory’ for statisticians, too ‘statistical’ for regulatory people. This digest was therefore written with three goals in mind: 1) Make the content of the guidance more accessible through a question & answer format, 2) shorten the content from 50 to 10 pages by excerpting the most important dictums, and 3) keep fidelity to the original guidance by frequent use of direct quotes with reference to the respective lines in the original FDA guidance where the quote can be found in square brackets.

scholarly journals The FDA adaptive trial design guidance in a nutshell - A review in Q&A format for decision makers

2016 ◽  
Author(s):  
Klaus Gottlieb
Keyword(s):  
Trial Design ◽  
Adaptive Design ◽  
Decision Makers ◽  
Development Programs ◽  
Fda Guidance ◽  
Regulatory Affairs ◽  
Frequent Use ◽  
Adaptive Trial Design ◽  
Adaptive Trial ◽  
Design Guidance

The FDA adaptive trial design guidance (1) is a thoughtful but lengthy document that explains on 50 pages wide-ranging and important topics “such as ... what aspects of adaptive design trials (i.e., clinical, statistical, regulatory) call for special consideration, ... when to interact with FDA while planning and conducting adaptive design studies, ... what information to include in the adaptive design for FDA review, and ... issues to consider in the evaluation of a completed adaptive design study.” [20-24]. The advice in the guidance is often misinterpreted, misquoted or ignored. This is unfortunate because an appropriate use of adaptive designs could increase the chances of success in drug development programs. Decision makers rely on the advice of regulatory affairs professionals and statisticians to interpret the guidance. Unfortunately, many clinical trial statisticians and regulatory professionals only have a rudimentary understanding of the guidance, presumably because the document is somewhat inscrutable for both audiences, too ‘regulatory’ for statisticians, too ‘statistical’ for regulatory people. This digest was therefore written with three goals in mind: 1) Make the content of the guidance more accessible through a question & answer format, 2) shorten the content from 50 to 10 pages by excerpting the most important dictums, and 3) keep fidelity to the original guidance by frequent use of direct quotes with reference to the respective lines in the original FDA guidance where the quote can be found in square brackets.

Abstract WP25: A Novel Adaptive Trial Design Increases the Power of Endovascular Stroke Studies

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Maarten Lansberg ◽  
Ninad Bhat ◽  
Joseph P Broderick ◽  
Yuko Y Palesch ◽  
Philip W Lavori ◽  
...  
Keyword(s):  
Treatment Effect ◽  
Interim Analysis ◽  
Trial Design ◽  
Adaptive Design ◽  
Type I ◽  
Vessel Occlusion ◽  
Patient Subgroup ◽  
Traditional Design ◽  
Subgroup Selection ◽  
Adaptive Trial

Introduction: It is difficult to choose trial enrollment criteria that will yield a robust treatment effect. To address this problem, we developed a novel trial design that restricts enrollment criteria to the patient subgroup most likely to show benefit, if an interim analysis indicates futility in the overall sample. Future recruitment, and the population in which the primary hypothesis is tested, is limited to the selected subgroup. Hypothesis: A design with adaptive subgroup selection increases the power of endovascular stroke studies. Methods: We ran simulations to compare the power of the adaptive design with that of a traditional design. Trial parameters were: type I error 0.025, type II error 0.1, analysis after 450, 675 and 900 patients (interim and final analyses in IMS III). Outcome data were based on 90 day mRS scores observed in IMS III among patients with a vessel occlusion on baseline CTA (n=289). Subgroups were defined a priori according to vessel occlusion (ICA ± distal occlusion vs M1 vs M2-4), onset-to-randomization time (early vs late), and treatment allocation (IA+IV vs IV alone). The treatment effect in the overall cohort was a mean mRS improvement of 0.15 (2.41 for IV+IA vs 2.56 for IV alone; SD 1.45). The subgroup treatment effects were: early ICA = 0.54, late ICA = 0.60, early M1 = 0.33, late M1 = 0.07, early M2-4 = -0.66, and late M2-4 = -0.35. Results: The traditional design showed a treatment benefit in 31% of simulations. The adaptive design showed benefit in 91%, failed to show benefit after enrollment of the maximum sample in 1%, and stopped early for futility in 8% of simulations. The adaptive trial stopped early for benefit in 84% of simulations. Due to early stopping, the mean number of patients randomized is 590±140 with the adaptive design vs 900 with a traditional design. Of the adaptive trial simulations that showed benefit, 91% occur after subgroup selection. The subgroup selected most often (31% of all simulations) includes early and late ICA patients. Conclusions: A trial with adaptive subgroup selection can efficiently test the effect of endovascular stroke treatment. Simulations suggest that with this design, IMS III would have 91% power and would typically stop early after interim analysis shows benefit in a patient subgroup.

scholarly journals Bayesian adaptive trial design in acute heart failure syndromes: Moving beyond the mega trial

2012 ◽  
Vol 164 (2) ◽  
pp. 138-145 ◽  
Author(s):  
Sean P. Collins ◽  
Christopher J. Lindsell ◽  
Peter S. Pang ◽  
Alan B. Storrow ◽  
W. Frank Peacock ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Trial Design ◽  
Adaptive Trial Design ◽  
Acute Heart Failure Syndromes ◽  
Adaptive Trial
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