Continuous event monitoring via a Bayesian predictive approach.

In clinical trials, continuous monitoring of event incidence rate plays a critical role in making timely decisions affecting trial outcome. For example, continuous monitoring of adverse events protects the safety of trial participants, while continuous monitoring of efficacy events helps identify early signals of efficacy or futility. Because the endpoint of interest is often the event incidence associated with a given length of treatment duration (e.

Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls.

'Multistage testing with adaptive designs' was the title of an article by Peter Bauer that appeared 1989 in the German journal Biometrie und Informatik in Medizin und Biologie. The journal does not exist anymore but the methodology found widespread interest in the scientific community over the past 25 years. The use of such multistage adaptive designs raised many controversial discussions from the beginning on, especially after the publication by Bauer and Köhne 1994 in Biometrics: Broad enthusiasm about potential applications of such designs faced critical positions regarding their statistical efficiency.

Adaptive Design Applied to Identification of the Minimum Effective Dose in Schizophrenia: Simulations of Scientific and Commercial Value.

The International Society for CNS Clinical Trials and Methodology (ISCTM) Adaptive Design Working Group (IADWG) designed a case study simulation exercise to compare the value of traditional versus adaptive design approaches to phase II clinical trial design in schizophrenia in statistical and economic terms. Operational characteristics of both designs were compared across 7 likely dose-response curves. Based on IADWG members' recent research experience in schizophrenia, estimates of expected net present value (eNPV) for the molecule were compared for the traditional and adaptive designs.

Adaptive Clinical Trials: Overview of Phase III Designs and Challenges.

Adaptive designs use accruing data to make changes in an ongoing trial according to a prespecified plan and potentially offer great efficiencies for clinical development. There are many types of adaptive designs and many trial aspects that could in theory be adapted. However, the scope of adaptive designs with relevance in confirmatory trials is narrower, and in addition, extensive pre-planning is needed and various types of challenges need to be addressed in order to use these designs in this stage of development.

Views on Emerging Issues Pertaining to Data Monitoring Committees for Adaptive Trials.

In this paper, the authors express their views on a range of topics related to data monitoring committees (DMCs) for adaptive trials that have emerged recently. The topics pertain to DMC roles and responsibilities, membership, training, and communication. DMCs have been monitoring trials using the group sequential design (GSD) for over 30 years.

Confidence intervals for confirmatory adaptive two-stage designs with treatment selection.

The construction of adequate confidence intervals for adaptive two-stage designs remains an area of ongoing research. We propose a conditional likelihood-based approach to construct a Wald confidence interval and two confidence intervals based on inverting the likelihood ratio test, one of them using first-order inference methods and the second one using higher order inference methods. The coverage probabilities of these confidence intervals, and also the average bias and mean square error of the corresponding point estimates, compare favorably with other available techniques.

A bivariate Bayesian dose-finding procedure applied to a seamless phase I/II trial in rheumatoid arthritis.

We describe a dose escalation procedure for a combined phase I/II clinical trial. The procedure is based on a Bayesian model for the joint distribution of the occurrence of a dose limiting event and of some indicator of efficacy (both considered binary variables), making no assumptions other than monotonicity. Thus, the chances of each outcome are assumed to be non-decreasing in dose level.

A bayesian dose-finding design adapting to efficacy and tolerability response.

We propose a new adaptive Bayesian design, explicitly modeling the trade-off between efficacy and tolerability in dose-finding studies. This design incorporates a continuous efficacy variable and a dichotomous tolerability variable. This adaptive design was developed in the context of a drug under development for treatment of major depression, but is easily extended to any setting with a continuous efficacy and a dichotomous tolerability or safety variable.

How Adaptive Trial Designs can Increase Efficiency in Psychiatric Drug Development: A Case Study.

This paper uses a recently completed study to illustrate how adaptive trial designs can increase efficiency of psychiatric drug development. The design employed allowed a continuous reassessment of the estimated dose-response such that patients were randomized in a double-blind fashion to one of seven doses of the investigational drug, placebo, or active comparator. The study design also permitted early detection of futility allowing for early study termination.

Viewpoints on the FDA draft adaptive designs guidance from the PhRMA working group.

The US Food and Drug Administration has recently released a draft guidance document on adaptive clinical trials. We comment on the document from the particular perspective of the authors as members of a PhRMA working group on this topic, which has interacted with FDA personnel on adaptive trial issue during recent years. We describe the activities and prior work of our working group, and use this as a basis to discuss the content of the guidance document as it relates to several issues of current relevance, such as data monitoring processes, adaptive dose finding, so-called seamless trial designs, and sample size reestimation.

Adaptive Dc-optimal designs for dose finding based on a continuous efficacy endpoint.

We introduce a new optimal design for dose finding with a continuous efficacy endpoint. This design is studied in the context of a flexible model for the mean of the dose-response. The design incorporates aspects of both D- and c-optimality and can be used when the study goals under consideration include dose-response estimation, followed by identification of the target dose.

An introduction to adaptive designs and adaptation in CNS trials.

Adaptive designs learn from accumulating trial data in real time and apply this knowledge to optimize subsequent study execution. A set of design rules define a priori which modifications may be incorporated into the trial design. Judicious use of adaptive designs may increase the information value per resource unit invested by avoiding allocation of patients to non-efficacious/unsafe therapies and allowing stopping decisions to be made at the earliest possible time point.

Likelihood inference for a two-stage design with treatment selection.

A conditional likelihood-based approach is proposed to construct confidence intervals for the parameters of interest in a two-stage design with treatment selection after the first stage. Both a Wald confidence interval and a confidence interval based on inverting the likelihood ratio test are proposed. The operating characteristics of these confidence intervals: the coverage probabilities and average confidence interval lengths, as well as the average bias and mean-square error of the corresponding point estimates, compare favorably with other available techniques.

Two-stage design for dose-finding that accounts for both efficacy and safety.

We introduce a two-stage design for dose-finding in the context of Phase I/II studies, where two binary correlated endpoints are available, for instance, one for efficacy and one for toxicity. The bivariate probit model is used as a working model for the dose-response relationship. Given a 'desirable point' for the marginal probabilities of efficacy and toxicity, the goal is to find the target dose that is 'closest' to the desirable point.

Adaptive designs for dose-finding studies based on sigmoid Emax model.

We propose an adaptive procedure for dose-finding in clinical trials when the primary efficacy endpoint is continuous. We model the mean of the efficacy endpoint, given the dose, as a four-parameter logistic function. The efficacy endpoint at each dose is distributed according to either a normal or a gamma distribution.

Adaptive designs in clinical drug development: opportunities, challenges, and scope reflections following PhRMA's November 2006 workshop.

This paper provides reflections on the opportunities, scope and challenges of adaptive design as discussed at PhRMA's workshop held in November 2006. We also provide a status report of workstreams within PhRMA's working group on adaptive designs, which were triggered by the November workshop. Rather than providing a comprehensive review of the presentations given, we limit ourselves to a selection of key statements.

Implementation of an adaptive group sequential design in a bioequivalence study.

The study design was a multi-center, multiple-dose, randomized, open-label, 2 x 2 crossover study in patients with advanced solid tumors. Each patient was randomized to receive the test formulation or the reference formulation of the drug. The primary objective of the study was to demonstrate the bioequivalence of the test formulation T relative to the reference formulation R.

Adaptive designs in clinical drug development--an Executive Summary of the PhRMA Working Group.

A PhRMA Working Group on adaptive clinical trial designs has been formed to investigate and facilitate opportunities for wider acceptance and usage of adaptive designs and related methodologies. A White Paper summarizing the findings of the group is in preparation; this article is an Executive Summary for that full White Paper, and summarizes the findings and recommendations of the group. Logistic, operational, procedural, and statistical challenges associated with adaptive designs are addressed.

Design of multi-centre trials with binary response.

We propose a correlated beta-binomial model for the binary response in multi-centre trials. The likelihood function in this case has a closed-form and we avoid multivariate numerical integrations in determining the maximum likelihood estimator. Based on derived asymptotic variance-covariance matrix of the MLE, we obtain relatively simple formulae that relate the number of centres, the total number of patients and the precision of the parameter estimate.

Kullback-Leibler divergence for evaluating bioequivalence.

In this paper we propose a methodology for evaluating the bioequivalence of two formulations of a drug that encompasses not only average bioequivalence (ABE), but also the more recently introduced measures of population bioequivalence (PBE) and individual bioequivalence (IBE). The latter two measures are concerned with prescribability (PBE) and switchability (IBE). The main idea is to use the Kullback-Leibler divergence (KLD) as a measure of discrepancy between the distributions of the two formulations.

Statistical approaches to establishing vaccine safety.

In a vaccine safety trial, the primary interest is to demonstrate that the vaccine is sufficiently safe, rejecting the null hypothesis that the relative risk of an adverse event attributable to the new vaccine is above a prespecified value, greater than one. We evaluate the exact probability of type I error of the likelihood score test, with sample size determined by normal approximation, by enumeration of the binomial outcomes in the rejection region and show that it exceeds the nominal level. In the case of rare adverse events, we recommend the Poisson approximation as an alternative and develop the corresponding conditional and unconditional tests.