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Optimizing Interim Looks in Group Sequential Adaptive Study Designs

What are group sequential study designs?

Group sequential study designs include predetermined interim analyses (interim looks) in an ongoing clinical trial, to allow researchers the potential for stopping the trial earlier than the planned final analysis due to overwhelming evidence for success (efficacy), failure (futility), or safety concerns that arise from accumulating study data. Special considerations must be given to the preservation of Type-I error with the implementation of such interim looks, and several approaches have been developed over the years to control Type-I error, including those by Stuart Pocock, Peter O’Brien, and Thomas Fleming.

 

What are key considerations of group sequential designs?

There are several advantages for incorporating an interim look or looks in a study design, including the potential for more limited patient exposure, more efficient use of resources, time savings, and increased probability of success. Study design teams must weigh these considerations and agree on their strategic priorities before implementing group sequential design features. Specific points for consideration include the number and timing of interim analyses, and the stopping rules or thresholds used to declare early efficacy or futility.

 

Interim look timing

The timing of an interim look can be critical for the success of the group sequential approach. Performing the analysis too early may mean not enough information is available to make an informed decision; too late, and the benefits of the approach diminish significantly. Running extensive simulations across a variety of potential analysis time points can prove beneficial in selecting the optimal timeframe, balancing the team’s strategic priorities. Adding more than one interim look may prevail as a preferred approach, allowing for early stopping for futility only, with later look, or looks, focused on gains in early efficacy stopping (see schematic 1 below).

 

Schematic 1: A study with two interim looks: An early futility and later efficacy assessment

 

Early stopping rules

Setting the correct stopping rules for early efficacy and/or futility is also paramount in designing a robust clinical trial. If an early stopping threshold for futility is set incorrectly, it can lead to the termination of a promising treatment due to limited data. Conversely, setting a stopping rule for efficacy which is too aggressive, may lead to premature trial termination with inaccurate results. Here too, extensive simulation of trials with a variety of stopping rules for both efficacy and futility can help optimize these thresholds and the potential savings from these trial designs.

 

Schematic 2: Stopping boundaries for efficacy and futility: An interim look at 50% information fraction

 

A closer look at the benefits of implementing group sequential designs

Group sequential designs offer several key benefits in clinical trial practice:

  • Design trials that are more ethical: accurate decision rules for early stopping either for futility or efficacy can reduce the number of patients required for enrollment in a clinical trial and reduce unnecessary exposure of patients to potentially ineffective or harmful treatments.
  • Design trials with more efficient resource use: including interim looks in a study can lead to savings in both the timing and cost of clinical trials. Adaptive designs with interim analyses are shorter in overall average duration and average cost when compared to similar fixed study designs with no interim analyses. These savings are gained through the thoughtful implementation of early stopping rules.
  • Design trials with a higher probability of success: adaptive designs with interim analyses demonstrate and a higher average probability of success compared to fixed study designs. These benefits is especially pronounced when the true underlying treatment effect is clear at an early study stage (either beneficial or inefficacious).

 

Overall, interim analyses are an important feature in adaptive clinical trial design, and when well planned and executed, can lead to benefits and savings in clinical trial execution.

 

Group sequential designs now available in the East HorizonTM platform

Cytel’s East Horizon platform now includes a Group Sequential module. This module offers statisticians the ability to compute and simulate single-arm and two-arm study designs with interim looks. The module allows users to select and optimize the number and timing of interim looks and the boundaries for efficacy and futility through advanced simulation and analysis tools.

Cytel’s East Horizon Group Sequential Module is the second in a series of six revamped cornerstone components of Cytel’s new cloud-based trial design platform. In combination with other platform components, the module provides statisticians with the tools needed for design, optimization, and selection of adaptive clinical trials with interim analyses.

Understanding Group Sequential Designs

Group sequential clinical trial designs‚ a type of adaptive clinical trial design, have emerged as a powerful tool in enhancing the efficiency and ethical conduct of clinical trials, due to the ability to stop the trial early based on accumulating data. Here, I expand on the intricacies of group sequential designs, key design features, applications in clinical trials, their advantages, challenges, and impact on the landscape of clinical trials.

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Negative Binomial Distribution in Group Sequential Designs

In clinical trials based on count data, the aim is to compare independent treatment groups in terms of the rate of occurrence of a particular outcome, such as number of times a subject responds to a therapy, develops a certain adverse experience, requires specialized care, or takes medication to achieve a particular response — for example, the number of migraines, seizures, recurrent infections, hospitalizations, episodes of diarrhea, and so on.

Negative binomial probability distribution can be used to model the number of times a particular outcome occurs during a clinical trial. Here, I explain this statistical methodology and its application in adaptive group sequential clinical trial designs.

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Measuring Estimates and Confidence Intervals in Adaptive settings?

As the use of advanced and innovative clinical trial designs continue to rise, sponsors often wonder which estimation methods are best used for measuring treatment effects with novel trial designs. A variety of estimation methods exist, and it is essential to understand their strengths and limitations. However, the FDA’s most recent guidance on adaptive designs only mentions controlling Type I error, not estimation. More research is needed to evaluate methods for point estimates and confidence intervals within adaptive settings.

Cytel statisticians and colleagues at Harvard University and Vertex Pharmaceuticals, recently employed extensive simulations to examine the strengths and weaknesses of various estimation methods for adaptive settings. Their findings place sponsors on the path to preparing even stronger evidence packages for regulatory submissions involving complex designs.

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