Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: general concepts

Exploring changes in treatment effects across design stages in adaptive trials

The recently published Committee for Medicinal Products for Human Use reflection paper on flexible designs highlights a controversial issue regarding the interpretation of adaptive trials. The guideline suggests that a test for heterogeneity should be preplanned and if treatment effect estimates differ significantly between design stages then data collected before and after the interim analysis might not be combined in a formal analysis. In this paper we investigate error rates for such a procedure in the presence of calendar-time effects. Furthermore, we present an alternative testing strategy based on change point methods. In a simulation study we demonstrate that our procedure performs well in comparison to that suggested by the guideline.

Dose selection in seamless phase II/III clinical trials based on efficacy and safety

Seamless phase II/III clinical trials are attractive in development of new drugs because they accelerate the drug development process. Seamless phase II/III trials are carried out in two stages. After stage 1 (phase II stage), an interim analysis is performed and a decision is made on whether to proceed to stage 2 (phase III stage). If the decision is to continue with further testing, some dose-selection procedure is used to determine the set of doses to be tested in stage 2. In this paper, we propose a dose-selection procedure for binary outcomes in adaptive seamless phase II/III clinical trials that incorporates the dose-response relationship when the experimental treatments are different dose levels of the same drug, and explicitly incorporates both efficacy and safety. The choice of the doses to continue to stage 2 is made by comparing the predictive power of the potential sets of doses, which might continue.

Adaptive clinical trials: progress and challenges

Adaptive designs promise the flexibility to redesign clinical trials at interim stages. This flexibility would provide greater efficiency in drug development. However, despite this promise, many hesitate to implement such designs. Here we explore three possible reasons for the hesitation: (i) confusion with respect to the definition of an 'adaptive design'; (ii) controversy surrounding the use of sample size re-estimation methods; and (iii) logistical barriers that must be overcome in order to use adaptive designs within existing trial frameworks.The large volume of recent work has created confusion with respect to the definition of an 'adaptive design'. Unfortunately, this has resulted in reduced usage of many acceptable methods because of guilt by association with the more controversial methods. This review attempts to clarify the differences among many common types of proposed adaptive designs. Once the differences are noted, it becomes apparent that some adaptive designs are well accepted while others remain very controversial. In fact, much of the controversy and criticism surrounding adaptive designs has focused on their use for sample size re-estimation. Hence, this review also examines the different types of adaptive designs for sample size re-estimation in order to clarify the controversy surrounding the use of these methods. Specifically, separating the controversial from good practice requires clarifying differences between adaptive designs with sample size re-estimation based on a revised treatment effect and re-estimation based only on nuisance parameters (internal pilot designs). Finally, many logistical barriers must be overcome in order to use adaptive designs within existing trial frameworks.If the promise of adaptive designs is to be achieved, it will be important to bring together large groups of individuals from funding sources and regulatory agencies to address these limitations. Very few discussions of these issues have appeared in journals that are targeted to clinical audiences. In fact, current use of adaptive designs is not really hindered by the lack of statistical methods to accommodate the adaptations. Rather, there is a need for education as to which adaptive designs are acceptable and which are not acceptable. These discussions will require the involvement of many individuals outside the statistical community. In this review, we summarize the existing methods and current controversies with the intent of providing a clarification that will enable these individuals to participate in these much-needed discussions.

Group sequential and adaptive designs - a review of basic concepts and points of discussion

In recent times, group sequential and adaptive designs for clinical trials have attracted great attention from industry, academia and regulatory authorities. These designs allow analyses on accumulating data - as opposed to classical, "fixed-sample" statistics. The rapid development of a great variety of statistical procedures is accompanied by a lively debate on their potential merits and shortcomings. The purpose of this review article is to ease orientation in both respects. First, we provide a concise overview of the essential technical concepts, with special emphasis on their interrelationships. Second, we give a structured review of the current controversial discussion on practical issues, opportunities and challenges of these new designs.

Dose finding - a challenge in statistics

A good understanding and characterization of the dose response relationship of any new compound is an important and ubiquitous problem in many areas of scientific investigation. This is especially true in the context of pharmaceutical drug development, where it is mandatory to launch safe drugs which demonstrate a clinically relevant effect. Selecting a dose too high may result in unacceptable safety problems, while selecting a dose too low may lead to ineffective drugs. Dose finding studies thus play a key role in any drug development program and are often the gate-keeper for large confirmatory studies. In this overview paper we focus on definitive and confirmatory dose finding studies in Phase II or III, reviewing relevant statistical design and analysis methods. In particular, we describe multiple comparison procedures, modeling approaches, and hybrid methods combining the advantages of both. An outlook to adaptive dose finding methods is also given. We use a real data example to illustrate the methods, together with a brief overview of relevant software.

Adaptive Dunnett tests for treatment selection

Clinical trials incorporating treatment selection at pre-specified interim analyses allow to integrate two clinical studies into a single, confirmatory study. In an adaptive interim analysis, treatment arms are selected based on interim data as well as external information. The specific selection rule does not need to be pre-specified in advance in order to control the multiple type I error rate. We propose an adaptive Dunnett test procedure based on the conditional error rate of the single-stage Dunnett test. The adaptive procedure uniformly improves the classical Dunnett test, which is shown to be strictly conservative if treatments are dropped at interim. The adaptive Dunnett test is compared in a simulation with the classical Dunnett test as well as with adaptive combination tests based on the closure principle. The method is illustrated with a real-data example.

Simple sequential boundaries for treatment selection in multi-armed randomized clinical trials with a control

In situations when many regimens are possible candidates for a large phase III study, but too few resources are available to evaluate each relative to the standard, conducting a multi-armed randomized selection trial is a useful strategy to remove inferior treatments from further consideration. When the study has a relatively quick endpoint such as an imaging-based lesion volume change in acute stroke patients, frequent interim monitoring of the trial is ethically and practically appealing to clinicians. In this article, I propose a class of sequential selection boundaries for multi-armed clinical trials, in which the objective is to select a treatment with a clinically significant improvement upon the control group, or to declare futility if no such treatment exists. The proposed boundaries are easy to implement in a blinded fashion, and can be applied on a flexible monitoring schedule in terms of calendar time. Design calibration with respect to prespecified levels of confidence is simple, and can be accomplished when the response rate of the control group is known only up to an interval. One of the proposed methods is applied to redesign a selection trial with an imaging endpoint in acute stroke patients, and is compared to an optimal two-stage design via simulations: The proposed method imposes smaller sample size on average than the two-stage design; this advantage is substantial when there is in fact a superior treatment to the control group.

Bayesian predictive power for interim adaptation in seamless phase II/III trials where the endpoint is survival up to some specified timepoint

Integration of a phase II and a phase III clinical trial into a single confirmatory study aims to shorten the development time without compromising the chance of success for a development program. These seamless phase II/III trials involve complex adaptations at the interim analysis, such as treatment selection, sample size reassessment, and stopping for futility. Bayesian methods can support these interim adaptations, and make this decision process more transparent. Use of a frequentist combination test for the final evaluation ensures that the type I error is controlled regardless of the adaptation rule employed at the interim analysis. In this paper, an adaptive seamless phase II/III trial design is proposed for studies where the endpoint is survival up to some specified timepoint and where Bayesian predictive power (PP) guides interim adaptations. For the evaluation of PP at the interim analysis, the event time is modelled as a piecewise exponential distribution, with informative priors for the hazard rates. As an illustrative example, regimen selection at interim in a four-arm trial with an active control is considered, where both non-inferiority and superiority to the control arm are tested. Frequentist properties of the adaptation criterion based on Bayesian PP are assessed by simulations.

Multiplicity and flexibility in clinical trials

Flexible designs offer a large amount of flexibility in clinical trials with control of the type I error rate. This allows the combination of trials from different clinical phases of a drug development process. Such combinations require designs where hypotheses are selected and/or added at interim analysis without knowing the selection rule in advance so that both flexibility and multiplicity issues arise. The paper reviews the basic principles and some of the common methods for reaching flexibility while controlling the family-wise error rate in the strong sense. Flexible designs have been criticized because they may lead to different weights for the patients from the different stages when reassessing sample sizes. Analyzing the data in a conventional way avoids such unequal weighting but may inflate the multiple type I error rate. In cases where the conditional type I error rates of the new design (and conventional analysis) are below the conditional type I error rates of the initial design the conventional analysis may, however, be done without inflating the type I error rate. Focusing on a parallel group design with two treatments and a common control, we use this principle to investigate when we can select one treatment, reassess sample sizes and test the corresponding null hypotheses by the conventional level alpha z-test without compromising on the multiple type I error rate.

How practical are adaptive designs likely to be for confirmatory trials?

This is a discussion of the following papers appearing in this special issue on adaptive designs: 'Confirmatory Seamless Phase II/III Clinical trials with Hypotheses Selection at Interim: General Concepts' by Frank Bretz, Heinz Schmidli, Franz König, Amy Racine and Willi Maurer; and 'Confirmatory Seamless Phase II/III Clinical Trials with Hypotheses Selection at Interim: Applications and Practical Considerations' by Heinz Schmidli, Frank Bretz, Amy Racine and Willi Maurer.

Plan to be flexible: a commentary on adaptive designs

This is a discussion of the following three papers appearing in this special issue on adaptive designs: 'Nested repeated confidence intervals and switching between noninferiority and superiority' by Joachim Hartung and Guido Knapp; 'Confirmatory Seamless Phase II/III Clinical trials with Hypotheses Selection at Interim: General Concepts' by Frank Bretz, Heinz Schmidli, Franz König, Amy Racine and Willi Maurer; and 'Confirmatory Seamless Phase Il/III Clinical Trials with Hypotheses Selection at Interim: Applications and Practical Considerations' by Heinz Schmidli, Frank Bretz, Amy Racine and Willi Maurer.

Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: applications and practical considerations

Adaptive seamless phase II/III designs combine a phase II and a phase III study into one single confirmatory clinical trial. Several examples of such designs are presented, where the primary endpoint is binary, time-to-event or continuous. The interim adaptations considered include the selection of treatments and the selection of hypotheses related to a pre-specified subgroup of patients. Practical aspects concerning the planning and implementation of adaptive seamless confirmatory studies are also discussed.

Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: opportunities and limitations

This is a discussion of the following two papers in this special issue on adaptive designs: 'Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: General concepts' by Frank Bretz, Heinz Schmidli, Franz König, Amy Racine and Willi Maurer, and 'Confirmatory seamless phase II/III clinical trials with hypotheses selection at interim: Applications and practical considerations' by Heinz Schmidli, Frank Bretz, Amy Racine and Willi Maurer.

An Adaptive Hierarchical Test Procedure for Selecting Safe and Efficient Treatments

We consider the situation where during a multiple treatment (dose) control comparison high doses are truncated because of lack of safety and low doses are truncated because of lack of efficacy, e.g., by decisions of a data safety monitoring committee in multiple interim looks. We investigate the properties of a hierarchical test procedure for the efficacy outcome in the set of doses carried on until the end of the trial, starting with the highest selected dose group to be compared with the placebo at the full level alpha. Left truncation, i.e., dropping doses in a sequence starting with the lowest dose, does not inflate the type I error rate. It is shown that right truncation does not inflate the type I error if efficacy and toxicity are positively related and dose selection is based on monotone functions of the safety data. A positive relation is given e.g. in the case where the efficacy and toxicity data are normally distributed with a positive pairwise correlation. A positive relation also applies if the probability for an adverse event is increasing with a normally distributed efficacy outcome. The properties of such truncation procedures are investigated by simulations. There is a conflict between achieving a small number of unsafely treated patients and a high power to detect safe and efficient doses. We also investigated a procedure to increase power where a reallocation of the sample size to the truncated treatments and the control remaining at the following stages is performed.

A 25-year review of sequential methodology in clinical studies

This paper explores the theoretical developments and subsequent uptake of sequential methodology in clinical studies in the 25 years since Statistics in Medicine was launched. The review examines the contributions which have been made to all four phases into which clinical trials are traditionally classified and highlights major statistical advancements, together with assessing application of the techniques. The vast majority of work has been in the setting of phase III clinical trials and so emphasis will be placed here. Finally, comments are given indicating how the subject area may develop in the future.