Koko Asakura

Sample size determination in group-sequential clinical trials with two co-primary endpoints

We discuss sample size determination in group-sequential designs with two endpoints as co-primary. We derive the power and sample size within two decision-making frameworks. One is to claim the test interventions benefit relative to control when superiority is achieved for the two endpoints at the same interim timepoint of the trial. The other is when superiority is achieved for the two endpoints at any interim timepoint, not necessarily simultaneously. We evaluate the behaviors of sample size and power with varying design elements and provide a real example to illustrate the proposed sample size methods. In addition, we discuss sample size recalculation based on observed data and evaluate the impact on the power and Type I error rate.

Group-Sequential Strategies in Clinical Trials with Multiple Co-Primary Outcomes

We discuss the decision-making frameworks for clinical trials with multiple co-primary endpoints in a group-sequential setting. The decision-making frameworks can account for flexibilities, such as a varying number of analyses, equally or unequally spaced increments of information, and fixed or adaptive Type I error allocation among endpoints. The frameworks can provide efficiency, that is, potentially fewer trial participants, than the fixed sample size designs. We investigate the operating characteristics of the decision-making frameworks and provide guidance on constructing efficient group-sequential strategies in clinical trials with multiple co-primary endpoints.

Sample Size Considerations in Clinical Trials when Comparing Two Interventions using Multiple Co-Primary Binary Relative Risk Contrasts.

The effects of interventions are multidimensional. Use of more than one primary endpoint offers an attractive design feature in clinical trials as they capture more complete characterization of the effects of an intervention and provide more informative intervention comparisons. For these reasons, multiple primary endpoints have become a common design feature in many disease areas such as oncology, infectious disease, and cardiovascular disease. More specifically in medical product development, multiple endpoints are used as co-primary to evaluate the effect of the new interventions. Although methodologies to address continuous co-primary endpoints are well-developed, methodologies for binary endpoints are limited. In this article, we describe power and sample size determination for clinical trials with multiple correlated binary endpoints, when relative risks are evaluated as co-primary. We consider a scenario where the objective is to evaluate evidence for superiority of a test intervention compared with a control intervention, for all of the relative risks. We discuss the normal approximation methods for power and sample size calculations and evaluate how the required sample size, power, and Type I error vary as a function of the correlations among the endpoints. Also we discuss a simple, but conservative procedure for appropriate sample size calculation. We then extend the methods allowing for interim monitoring using group-sequential methods. Supplementary materials for this article are available online.

Group-Sequential Designs When Considering Two Binary Outcomes as Co-Primary Endpoints

We discuss group-sequential designs with two binary endpoints as co-primary. We derive the power and required sample size within two decision-making frameworks: (i) to evaluate whether superiority of a test intervention relative to control has been shown for both endpoints at any interim time point, not necessarily simultaneously and (ii) to evaluate whether superiority has been demonstrated for both endpoints at the same interim time point of the trial. We evaluate the utility of the method in practice using Monte Carlo simulation and investigate the behavior of the sample sizes with varying design characteristics. We provide a real example to illustrate the method. We also discuss sample size recalculation based on observed interim data. Lastly, we discuss a method for hierarchical hypothesis testing with adaptive type I error allocation in group-sequential designs with co-primary endpoints in order to improve the power of the methods.

Group-sequential three-arm noninferiority clinical trial designs.

ABSTRACT We discuss group-sequential three-arm noninferiority clinical trial designs that include active and placebo controls for evaluating both assay sensitivity and noninferiority. We extend two existing approaches, the fixed margin and fraction approaches, into a group-sequential setting with two decision-making frameworks. We investigate the operating characteristics including power, Type I error rate, maximum, and expected sample sizes, as design factors vary. In addition, we discuss sample size recalculation and its impact on the power and Type I error rate via a simulation study.

Design, data monitoring, and analysis of clinical trials with co-primary endpoints: A review

ABSTRACT We review the design, data monitoring, and analyses of clinical trials with co-primary endpoints. Recently developed methods for fixed-sample and group-sequential settings are described. Practical considerations are discussed, and guidance for the application of these methods is provided.

Interim evaluation of efficacy or futility in group‐sequential trials with multiple co‐primary endpoints

We discuss group-sequential designs in superiority clinical trials with multiple co-primary endpoints, that is, when trials are designed to evaluate if the test intervention is superior to the control on all primary endpoints. We consider several decision-making frameworks for evaluating efficacy or futility, based on boundaries using group-sequential methodology. We incorporate the correlations among the endpoints into the calculations for futility boundaries and sample sizes as a function of other design parameters, including mean differences, the number of analyses, and efficacy boundaries. We investigate the operating characteristics of the proposed decision-making frameworks in terms of efficacy/futility boundaries, power, the Type I error rate, and sample sizes, while varying the number of analyses, the correlations among the endpoints, and the mean differences. We provide an example to illustrate the methods and discuss practical considerations when designing efficient group-sequential designs in clinical trials with co-primary endpoints.

Interim Evaluation of Efficacy or Futility in Clinical Trials with Two Co-primary Endpoints

We discuss group-sequential designs for early efficacy or futility stopping in superiority clinical trials with multiple co-primary endpoints. We discuss several decision-making frameworks for evaluating efficacy or futility based on boundaries using group-sequential methodology. We incorporate the correlations among the endpoints into the calculations for futility critical boundaries and evaluate the required sample sizes as a function of design parameters including mean differences, the number of planned analyses, and efficacy critical boundaries. We provide an example to illustrate the methods and discuss practical considerations when designing efficient group-sequential designs in clinical trials with co-primary endpoints.

Japanese Antibacterial Drug Management for Cardiac Sarcoidosis (J-ACNES): A multicenter, open-label, randomized, controlled study

Cardiac sarcoidosis (CS) is a noncaseating granulomatous disease of unknown etiology. Lifelong immunosuppressive therapy, most frequently using corticosteroids, is a standard therapy to control hypersensitivity of immune reactions and prevent inflammation. However, it sometimes causes various systemic adverse effects and requires dose escalation. Thus, additional therapy may be required for the treatment of this disease. Recently, Propionibacterium acnes (P. acnes) was reported as one of the etiologic agents of CS, indicating that antibacterial drugs (ABD) may be effective for the treatment of CS. The objective of this study was to investigate the effect of ABD treatment, in addition to standard corticosteroid therapy, in patients with CS.

Group-Sequential Three-Arm Non-inferiority Clinical Trials

We discuss group-sequential three-arm non-inferiority (NI) clinical trials, i.e., trials that include a test intervention as well as active and placebo controls for evaluating both assay sensitivity and NI. We extend two existing approaches, the fixed margin and fraction approaches, to a group-sequential setting with two decision-making frameworks. We provide an example to illustrate the methods.