Decision-Theoretic Designs for Pre-Phase II Screening Trials in Oncology

A Bayesian decision-theoretic method is proposed for conducting small, randomized pre-phase II selection trials. The aim is to improve on the design of Thall and Estey (1993, Statistics in Medicine 12, 1197-1211). Designs are derived that optimize a gain function accounting for current and future patient gains, per-patient cost, and future treatment development cost. To reduce the computational burden associated with backward induction, myopic versions of the design that consider only one, two, or three future decisions at a time are also considered. The designs are compared in the context of a screening trial in acute myelogenous leukemia.     

Optimal adaptive two‐stage designs for phase II cancer clinical trials

In oncology, single‐arm two‐stage designs with binary endpoint are widely applied in phase II for the development of cytotoxic cancer therapies. Simon's optimal design with prefixed sample sizes in both stages minimizes the expected sample size under the null hypothesis and is one of the most popular designs. The search algorithms that are currently used to identify phase II designs showing prespecified characteristics are computationally intensive. For this reason, most authors impose restrictions on their search procedure. However, it remains unclear to what extent this approach influences the optimality of the resulting designs. This article describes an extension to fixed sample size phase II designs by allowing the sample size of stage two to depend on the number of responses observed in the first stage. Furthermore, we present a more efficient numerical algorithm that allows for an exhaustive search of designs. Comparisons between designs presented in the literature and the proposed optimal adaptive designs show that while the improvements are generally moderate, notable reductions in the average sample size can be achieved for specific parameter constellations when applying the new method and search strategy.     

Adaptive Two Stage Designs and the Conditional Error Function

Proschan and Hunsberger (1995) suggest the use of a conditional error function to construct a two stage test that meets the α level and allows a very flexible reassessment of the sample size after the interim analysis. In this note we show that several adaptive designs can be formulated in terms of such an error function. The conditional power function defined similarly provides a simple method for sample size reassessment in adaptive two stage designs.     

Utility‐Based Optimization of Combination Therapy Using Ordinal Toxicity and Efficacy in Phase I/II Trials

Summary An outcome‐adaptive Bayesian design is proposed for choosing the optimal dose pair of a chemotherapeutic agent and a biological agent used in combination in a phase I/II clinical trial. Patient outcome is characterized as a vector of two ordinal variables accounting for toxicity and treatment efficacy. A generalization of the Aranda‐Ordaz model (1981, Biometrika 68 , 357–363) is used for the marginal outcome probabilities as functions of a dose pair, and a Gaussian copula is assumed to obtain joint distributions. Numerical utilities of all elementary patient outcomes, allowing the possibility that efficacy is inevaluable due to severe toxicity, are obtained using an elicitation method aimed to establish consensus among the physicians planning the trial. For each successive patient cohort, a dose pair is chosen to maximize the posterior mean utility. The method is illustrated by a trial in bladder cancer, including simulation studies of the method's sensitivity to prior parameters, the numerical utilities, correlation between the outcomes, sample size, cohort size, and starting dose pair.     

A Hierarchical Bayesian Design for Phase I Trials of Novel Combinations of Cancer Therapeutic Agents

Summary We propose a hierarchical model for the probability of dose‐limiting toxicity (DLT) for combinations of doses of two therapeutic agents. We apply this model to an adaptive Bayesian trial algorithm whose goal is to identify combinations with DLT rates close to a prespecified target rate. We describe methods for generating prior distributions for the parameters in our model from a basic set of information elicited from clinical investigators. We survey the performance of our algorithm in a series of simulations of a hypothetical trial that examines combinations of four doses of two agents. We also compare the performance of our approach to two existing methods and assess the sensitivity of our approach to the chosen prior distribution.     

Optimizing the concentration and bolus of a drug delivered by continuous infusion

We consider treatment regimes in which an agent is administered continuously at a specified concentration until either a response is achieved or a predetermined maximum infusion time is reached. Response is an event defined to characterize therapeutic efficacy. A portion of the maximum planned total amount administered is given as an initial bolus. For such regimes, the amount of the agent received by the patient depends on the time to response. An additional complication when response is evaluated periodically rather than continuously is that the response time is interval censored. We address the problem of designing a clinical trial in which such response time data and a binary indicator of toxicity are used together to jointly optimize the concentration and the size of the bolus. We propose a sequentially adaptive Bayesian design that chooses the optimal treatment for successive patients by maximizing the posterior mean utility of the joint efficacy-toxicity outcome. The methodology is illustrated by a trial in which tissue plasminogen activator is infused intraarterially as rapid treatment for acute ischemic stroke.     

Adaptive dose-finding: Proof of concept with type I error control

We consider an adaptive dose‐finding study with two stages. The doses for the second stage will be chosen based on the first stage results. Instead of considering pairwise comparisons with placebo, we apply one test to show an upward trend across doses. This is a possibility according to the ICH‐guideline for dose‐finding studies (ICH‐E4). In this article, we are interested in trend tests based on a single contrast or on the maximum of multiple contrasts. We are interested in flexibly choosing the Stage 2 doses including the possibility to add doses. If certain requirements for the interim decision rules are fulfilled, the final trend test that ignores the adaptive nature of the trial (naïve test) can control the type I error. However, for the more common case that these requirements are not fulfilled, we need to take the adaptivity into account and discuss a method for type I error control. We apply the general conditional error approach to adaptive dose‐finding and discuss special issues appearing in this application. We call the test based on this approach Adaptive Multiple Contrast Test. For an example, we illustrate the theory discussed before and compare the performance of several tests for the adaptive design in a simulation study.     

Sequential Designs for Genetic Epidemiological Linkage or Association Studies A Review of the Literature

Objectives. The cost of a genetic linkage or association study is largely determined by the number of individuals to be recruited, phenotyped, and genotyped. The efficiency can be increased by using a sequential procedure that reduces time and cost on average. Two strategies for sequential designs in genetic epidemiological studies can be distinguished: One approach is to increase the sample size sequentially and to conduct multiple significance tests on accumulating data. If significance or futility can be assumed with a certain probability, the study is stopped. Otherwise, it is carried on to the next stage. The second approach is to conduct early linkage analyses on a coarse marker grid, and to increase marker density in later stages. Interim analyses are performed to select interesting genomic areas for follow up. The aim of this article is to give a review on sequential procedures in the context of genetic linkage and association studies. Methods. A systematic literature search was performed in the Medline and the Linkage Bibliography databases. Articles were defined as relevant if a sequential design was proposed or applied in genetic linkage or association studies. Results. The majority of proposed study designs is developed to meet the demands of specific studies and lacks a theoretical foundation. A second group of procedures is based on simulation results and principally restricted to the specific simulated situations. Finally, some theoretically founded procedures have been proposed that are discussed in detail. Conclusions. Although interesting and promising procedures have been suggested, they still lack realizations for practical purposes. In addition, further developments are required to adapt sequential strategies for optimal use in genetic epidemiological studies.     

Adaptive Modifications of Hypotheses After an Interim Analysis

It is investigated how one can modify hypotheses in a trial after an interim analysis such that the type I error rate is controlled. If only a global statement is desired, a solution was given by Bauer (1989). For a general multiple testing problem, Kieser , Bauer and Lehmacher (1999) and Bauer and Kieser (1999) gave solutions, by means of which the initial set of hypotheses can be reduced after the interim analysis. The same techniques can be applied to obtain more flexible strategies, as changing weights of hypotheses, changing an a priori order, or even including new hypotheses. It is emphasized that the application of these methods requires very careful planning of a trial as well as a critical discussion of the scientific aims in order to avoid every manipulation.     

Drop-the-losers design: normal case

Drop-the-losers designs are statistical designs which have two stages of a trial separated by a data based decision. In the first stage k experimental treatments and a control are administered. During a transition period, the empirically best experimental treatment is selected for continuation into the second phase, along with the control. At the study's end, inference focuses on the comparison of the selected treatment with the control using both stages' data. Traditional methods used to make inferences based on both stages' data can yield tests with higher than advertised levels of significance and confidence intervals with lower than advertised confidence. For normally distributed data, methods are provided to correct these deficiencies, providing confidence intervals with accurate levels of confidence. Drop-the-losers designs are particularly applicable to biopharmaceutical clinical trials where they can allow Phase II and Phase III clinical trials to be conducted under a single protocol with the use of all available data.     

Multiple Comparisons of Treatments with Stable Multivariate Tests in a Two‐Stage Adaptive Design,Including a Test for Non‐Inferiority

The application of stabilized multivariate tests is demonstrated in the analysis of a two‐stage adaptive clinical trial with three treatment arms. Due to the clinical problem, the multiple comparisons include tests of superiority as well as a test for non‐inferiority, where non‐inferiority is (because of missing absolute tolerance limits) expressed as linear contrast of the three treatments. Special emphasis is paid to the combination of the three sources of multiplicity – multiple endpoints, multiple treatments, and two stages of the adaptive design. Particularly, the adaptation after the first stage comprises a change of the a‐priori order of hypotheses.     

Optimal conditional error functions for the control of conditional power

Ethical considerations and the competitive environment of clinical trials usually require that any given trial have sufficient power to detect a treatment advance. If at an interim analysis the available data are used to decide whether the trial is promising enough to be continued, investigators and sponsors often wish to have a high conditional power, which is the probability to reject the null hypothesis given the interim data and the alternative of interest. Under this requirement a design with interim sample size recalculation, which keeps the overall and conditional power at a prespecified value and preserves the overall type I error rate, is a reasonable alternative to a classical group sequential design, in which the conditional power is often too small. In this article two-stage designs with control of overall and conditional power are constructed that minimize the expected sample size, either for a simple point alternative or for a random mixture of alternatives given by a prior density for the efficacy parameter. The presented optimality result applies to trials with and without an interim hypothesis test; in addition, one can account for constraints such as a minimal sample size for the second stage. The optimal designs will be illustrated with an example, and will be compared to the frequently considered method of using the conditional type I error level of a group sequential design.     

Potential Aqueous Two‐Phase Processes for the Primary Recovery of Colored Protein from Microbial Origin

The primary recovery of c‐phycocyanin and b‐phycoerythrin from Spirulina maxima and Porphyridium cruentum, respectively, using an established extraction strategy was selected as a practical model system to study the generic application of polyethylene glycol (PEG)‐phosphate aqueous two‐phase systems (ATPS). The generic practical implementation of ATPS extraction was evaluated for the recovery of colored proteins from microbial origin. A comparison of the influence of system parameters, such as PEG molecular mass, concentration of PEG as well as salt, system pH and volume ratio, on the partition behavior of c‐phycocyanin and b‐phycoerythrin was carried out to determine under which conditions target colored protein and contaminants concentrate to opposite phases. One‐stage processes are proposed for the primary recovery of the colored proteins. PEG1450‐phosphate ATPS extraction (volume ratio (V_R) equal to 0.3, tie‐line length (TLL) of 34 % w/w and system pH 7.0) for the recovery of c‐phycocyanin from Spirulina maxima resulted in a primary recovery process that produced a protein purity of 2.1 ± 0.2 (defined as the relationship of 620 nm to 280 nm absorbance) and a product yield of 98 % [w/w]. PEG1000‐phosphate ATPS extraction (i.e., V_R = 1.0, PEG 1000, TLL 50 % w/w and system pH 7.0) was preferred for the recovery of b‐phycoerythrin from Porphyridium cruentum, which resulted in a protein purity of 2.8 ± 0.2 (defined as the relationship of 545 nm to 280 nm absorbance) and a product yield of 82 % [w/w]. The purity of c‐phycocyanin and b‐phycoerythrin from the crude extract increased 3‐ and 4‐fold, respectively, after ATPS. The results reported herein demonstrated the benefits of the practical generic application of ATPS for the primary recovery of colored proteins from microbial origin as a first step for the development of purification processes.     

Adaptive group sequential designs for clinical trials: combining the advantages of adaptive and of classical group sequential approaches

A general method is presented integrating the concept of adaptive interim analyses into classical group sequential testing. This allows the researcher to represent every group sequential plan as an adaptive trial design and to make design changes during the course of the trial after every interim analysis in the same way as with adaptive designs. The concept of adaptive trial designing is thereby generalized to a large variety of possible sequential plans.     

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.     

An end-to-end postal audit test to examine the coincidence between the imaging isocenter and treatment beam isocenter of the IGRT linac system for Japan Clinical Oncology Group (JCOG) clinical trials

PurposeThe aim of this study was to develop an end-to-end postal audit test to examine the coincidence between the imaging isocenter and treatment beam isocenter of the image guided radiotherapy (IGRT) linac system for Japan Clinical Oncology Group (JCOG) trials, as a part of IGRT credentialing of institutions participating in JCOG trials.MethodsWe developed an end-to-end postal audit test to verify radiation positional errors associated with IGRT techniques. This test is intended for simulating a clinical IGRT flow and uses a static cubic phantom measuring 15 × 15 × 15 cm³ and weighing approximately 3.4 kg. The phantom has four gold fiducial markers and a spherical dummy target for setup, with known shift values from the phantom center. Two pairs of Gafchromic RTQA2 films were inserted 5 mm from the phantom’s anterior-posterior and right-left surfaces. Radiation positional errors at the isocenter were determined by analyzing the center of the radiation field on the films and the known shift values of the dummy target. The test was performed on 47 IGRT devices at 35 institutions.ResultsRadiation positional errors were within acceptance levels (1 mm/1°) for 42 IGRT devices (89.4%) in the first check. Median time to complete IGRT credentialing was 11.5 days. This audit method was applicable for any radiotherapy machine with an IGRT device.ConclusionsA postal audit test to verify radiation positional errors for JCOG trials was successfully developed. In the postal audit, all but one institution passed this credentialing item within two trials.