On Bayesian Sequential Clinical Trial Designs

Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data with the potential for stopping the trial early. We review Bayesian sequential clinical trial designs based on posterior probabilities, posterior predictive probabilities, and decision-theoretic frameworks. A pertinent question is whether Bayesian sequential designs need to be adjusted for the planning of interim analyses. We answer this question from three perspectives: a frequentist-oriented perspective, a calibrated Bayesian perspective, and a subjective Bayesian perspective. We also provide new insights into the likelihood principle, which is commonly tied with statistical inference and decision making in sequential clinical trials. Some theoretical results are derived, and numerical studies are conducted to illustrate and assess these designs

PAM-HC: A Bayesian Nonparametric Construction of Hybrid Control for Randomized Clinical Trials Using External Data

It is highly desirable to borrow information from external data to augment a control arm in a randomized clinical trial, especially in settings where the sample size for the control arm is limited. However, a main challenge in borrowing information from external data is to accommodate potential heterogeneous subpopulations across the external and trial data. We apply a Bayesian nonparametric model called Plaid Atoms Model (PAM) to identify overlapping and unique subpopulations across datasets, with which we restrict the information borrowing to the common subpopulations. This forms a hybrid control (HC) that leads to more precise estimation of treatment effects Simulation studies demonstrate the robustness of the new method, and an application to an Atopic Dermatitis dataset shows improved treatment effect estimation

Parameter identification of the interaction body model using available measurements

This paper determines the parameters of the interaction models based on available published experimental measurements. The masses, damping ratios and stiffnesses of body models are identified by the curve fitting of the measured apparent mass curves from shaking table tests in published biomechanics studies. Then the extracted data are used to identify the parameters of the interaction models. Finally, the eigenvalue analyses of the human-structure models are calculated for comparison. In this identification process, it was identified that the quality of the curve fitting for the interaction model is as good as and even slightly better than the published results. One or two additional conditions for the interaction models would lead to several sets of parameters, but with the result of the continuous model, reasonable parameters have to be applied which can be identified and these parameters could be used in further calculations

The Ci3+3 Design for Dual-Agent Combination Dose-Finding Clinical Trials

We propose a rule-based statistical design for combination dose-finding trials with two agents. The Ci3+3 design is an extension of the i3+3 design with simple decision rules comparing the observed toxicity rates and equivalence intervals that define the maximum tolerated dose combination. Ci3+3 consists of two stages to allow fast and efficient exploration of the dose-combination space. Statistical inference is restricted to a beta-binomial model for dose evaluation, and the entire design is built upon a set of fixed rules. We show via simulation studies that the Ci3+3 design exhibits similar and comparable operating characteristics to more complex designs utilizing model-based inferences. We believe that the Ci3+3 design may provide an alternative choice to help simplify the design and conduct of combination dose-finding trials in practice

Estimation of dynamic characteristics of a spring-mass-beam system

Abstract. This paper presents an approximate solution for the analysis of the dynamic characteristics of a spring-mass-beam system. The spring-mass can be distributed or concentrated on a beam, which can represent a crowd or an individual on a beam. The analysis is based on the fact that a spring-mass-beam system can be modeled approximately as a series of two degree-of-freedom (TDOF) systems and the frequency coupling occurs mainly at the first TDOF system. The Galerkin method is used to derive the frequency equation of the TDOF system. Static beam functions of a beam with distributed and concentrated spring-masses are developed for the solutions, in which the effect of the magnitude and position of the mass of the spring-mass on the beam is considered. Using a set of simple formulae, the first pair of coupled frequencies and the corresponding mode can be obtained. The mass and stiffness factors in the TDOF system are tabled for engineering applications. For verification and use of the proposed method, a case of human-structure interaction is analysed using the proposed method and FE method. Parametric studies show that using the proposed functions, not only the first pair of natural frequencies but also the mode and internal forces of the coupled system can be obtained with high accuracy