New approaches for testing non-inferiority for three-arm trials with Poisson distributed outcomes
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Samiran Ghosh1, Erina Paul2, Shrabanti Chowdhury2
1Family Medicine & Public Health Sciences and Center of Molecular Medicine and Genetics, Wayne State University.
Abstract:
With the availability of limited resources, innovation for improved statistical method for the design and analysis of randomized controlled trials (RCTs) is of paramount importance for newer and better treatment discovery for any therapeutic area. Although clinical efficacy is almost always the primary evaluating criteria to measure any beneficial effect of a treatment, there are several important other factors (e.g., side effects, cost burden, less debilitating, less intensive, etc.), which can permit some less efficacious treatment options favorable to a subgroup of patients. This leads to non-inferiority (NI) testing. The objective of NI trial is to show that an experimental treatment is not worse than an active reference treatment by more than a pre-specified margin. Traditional NI trials do not include a placebo arm for ethical reason; however, this necessitates stringent and often unverifiable assumptions. On the other hand, three-arm NI trials consisting of placebo, reference, and experimental treatment, can simultaneously test the superiority of the reference over placebo and NI of experimental treatment over the reference. In this article, we proposed both novel Frequentist and Bayesian procedures for testing NI in the three-arm trial with Poisson distributed count outcome. RCTs with count data as the primary outcome are quite common in various disease areas such as lesion count in cancer trials, relapses in multiple sclerosis, dermatology, neurology, cardiovascular research, adverse event count, etc. We first propose an improved Frequentist approach, which is then followed by it's Bayesian version. Bayesian methods have natural advantage in any active-control trials, including NI trial when substantial historical information is available for placebo and established reference treatment. In addition, we discuss sample size calculation and draw an interesting connection between the two paradigms.
Insights
This study introduces new statistical methods for non-inferiority (NI) trials with count outcomes. These methods improve the design and analysis of randomized controlled trials (RCTs) for new treatments.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Pharmaceutical Research
Background:
- Randomized controlled trials (RCTs) are crucial for discovering new treatments, but resource limitations necessitate innovative statistical methods.
- Non-inferiority (NI) trials assess if a new treatment is not unacceptably worse than an existing one, considering factors beyond just efficacy.
- Traditional NI trials face ethical challenges and require strong assumptions; three-arm trials offer a robust alternative by including placebo, reference, and experimental arms.
Purpose of the Study:
- To propose novel Frequentist and Bayesian statistical procedures for analyzing three-arm non-inferiority trials with Poisson distributed count outcomes.
- To provide improved methods for the design and analysis of randomized controlled trials (RCTs) when count data is the primary outcome.
- To explore the advantages of Bayesian approaches in active-control trials, particularly when historical data is available.
Main Methods:
- Development of a novel Frequentist approach for non-inferiority testing in three-arm trials with count data.
- Extension of the Frequentist approach to a Bayesian framework, leveraging historical data for improved inference.
- Discussion of sample size calculations for both Frequentist and Bayesian methods in this context.
Main Results:
- The study presents new Frequentist and Bayesian procedures tailored for three-arm non-inferiority trials with count outcomes.
- The proposed methods offer enhanced statistical power and flexibility for analyzing count data in clinical trials.
- Bayesian methods are highlighted for their utility when incorporating prior information from historical studies.
Conclusions:
- The developed Frequentist and Bayesian methods provide valuable tools for the design and analysis of three-arm non-inferiority trials with count outcomes.
- These innovative statistical approaches can aid in the efficient discovery and evaluation of new therapeutic interventions.
- The study emphasizes the practical application of advanced statistical techniques in modern clinical research.
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