An adaptive group sequential design for phase II/III clinical trials that select a single treatment from several

There is increasing interest in combining Phases II and III of clinical development into a single trial in which one of a small number of competing experimental treatments is ultimately selected and where a valid comparison is made between this treatment and the control treatment. Such a trial usually proceeds in stages, with the least promising experimental treatments dropped as soon as possible. In this paper we present a highly flexible design that uses adaptive group sequential methodology to monitor an order statistic. By using this approach, it is possible to design a trial which can have any number of stages, begins with any number of experimental treatments, and permits any number of these to continue at any stage. The test statistic used is based upon efficient scores, so the method can be easily applied to binary, ordinal, failure time, or normally distributed outcomes. The method is illustrated with an example, and simulations are conducted to investigate its type I error rate and power under a range of scenarios.

Analyse en composantes indépendantes avec une matrice de mélange éparse

L'analyse en composantes indépendantes (ACI) est une méthode d'analyse statistique qui consiste à exprimer les données observées (mélanges de sources) en une transformation linéaire de variables latentes (sources) supposées non gaussiennes et mutuellement indépendantes. Dans certaines applications, on suppose que les mélanges de sources peuvent être groupés de façon à ce que ceux appartenant au même groupe soient fonction des mêmes sources. Ceci implique que les coefficients de chacune des colonnes de la matrice de mélange peuvent être regroupés selon ces mêmes groupes et que tous les coefficients de certains de ces groupes soient nuls. En d'autres mots, on suppose que la matrice de mélange est éparse par groupe. Cette hypothèse facilite l'interprétation et améliore la précision du modèle d'ACI. Dans cette optique, nous proposons de résoudre le problème d'ACI avec une matrice de mélange éparse par groupe à l'aide d'une méthode basée sur le LASSO par groupe adaptatif, lequel pénalise la norme 1 des groupes de coefficients avec des poids adaptatifs. Dans ce mémoire, nous soulignons l'utilité de notre méthode lors d'applications en imagerie cérébrale, plus précisément en imagerie par résonance magnétique. Lors de simulations, nous illustrons par un exemple l'efficacité de notre méthode à réduire vers zéro les groupes de coefficients non-significatifs au sein de la matrice de mélange. Nous montrons aussi que la précision de la méthode proposée est supérieure à celle de l'estimateur du maximum de la vraisemblance pénalisée par le LASSO adaptatif dans le cas où la matrice de mélange est éparse par groupe.

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Evolutionary and biogeographic history of the subfamily Neoplecostominae (Siluriformes: Loricariidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Grouped sparsity algorithm for multichannel intracardiac ECG synchronization

In this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a three-stage algorithm. We first compute a robust estimate of the derivative of the data to remove low-frequency perturbations. Then we provide a grouped-sparse representation of the data, by means of the Group LASSO, to ensure that all the electrical spikes are simultaneously detected. Finally, a post-processing step, based on a variance analysis, is performed to discard false alarms. Preliminary results on real data for sinus rhythm and atrial fibrillation show the potential of this approach.

Coherence loss and recovery of an electron spin coupled inhomogeneously to a one-dimensional interacting spin bath: An adaptive time-dependent density-matrix renormalization group study

Coherence evolution and echo effect of an electron spin, which is coupled inhomogeneously to an interacting one-dimensional finite spin bath via hyperfine-type interaction, are studied using the adaptive time-dependent density-matrix renormalization group method. It is found that the interplay of the coupling inhomogeneity and the transverse intrabath interactions results in two qualitatively different coherence evolutions, namely, a coherence-preserving evolution characterized by periodic oscillation and a complete decoherence evolution. Correspondingly, the echo effects induced by an electron-spin flip at time tau exhibit stable recoherence pulse sequence for the periodic evolution and a single peak at root 2 tau for the decoherence evolution, respectively. With the diagonal intrabath interaction included, the specific feature of the periodic regime is kept, while the root 2 tau-type echo effect in the decoherence regime is significantly affected. To render the experimental verifications possible, the Hahn echo envelope as a function of tau is calculated, which eliminates the inhomogeneous broadening effect and serves for the identification of the different status of the dynamic coherence evolution, periodic versus decoherence.

A co-operative formation-based collision avoidance approach for a group of autonomous vehicles (Special Issue on Adaptive Control and Signal Processing in Marine System)

This paper employs a unique decentralised cooperative control method to realise a formation-based collision avoidance strategy for a group of autonomous vehicles. In this approach, the vehicles' role in the formation and their alert and danger areas are first defined, and the formation-based intra-group and external collision avoidance methods are then proposed to translate the collision avoidance problem into the formation stability problem. The extension–decomposition–aggregation formation control method is next employed to stabilise the original and modified formations, whilst manoeuvring, and subsequently solve their collision avoidance problem indirectly. Simulation study verifies the feasibility and effectiveness of the intra-group and external collision avoidance strategy. It is demonstrated that both formation control and collision avoidance problems can be simultaneously solved if the stability of the expanded formation including external obstacles can be satisfied.

An adaptive approach to implementing bivariate group sequential clinical trial designs

In clinical trials, situations often arise where more than one response from each patient is of interest; and it is required that any decision to stop the study be based upon some or all of these measures simultaneously. Theory for the design of sequential experiments with simultaneous bivariate responses is described by Jennison and Turnbull (Jennison, C., Turnbull, B. W. (1993). Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. Biometrics 49:741-752) and Cook and Farewell (Cook, R. J., Farewell, V. T. (1994). Guidelines for monitoring efficacy and toxicity responses in clinical trials. Biometrics 50:1146-1152) in the context of one efficacy and one safety response. These expositions are in terms of normally distributed data with known covariance. The methods proposed require specification of the correlation, ρ between test statistics monitored as part of the sequential test. It can be difficult to quantify ρ and previous authors have suggested simply taking the lowest plausible value, as this will guarantee power. This paper begins with an illustration of the effect that inappropriate specification of ρ can have on the preservation of trial error rates. It is shown that both the type I error and the power can be adversely affected. As a possible solution to this problem, formulas are provided for the calculation of correlation from data collected as part of the trial. An adaptive approach is proposed and evaluated that makes use of these formulas and an example is provided to illustrate the method. Attention is restricted to the bivariate case for ease of computation, although the formulas derived are applicable in the general multivariate case.

A practical comparison of group-sequential and adaptive designs

Sequential methods provide a formal framework by which clinical trial data can be monitored as they accumulate. The results from interim analyses can be used either to modify the design of the remainder of the trial or to stop the trial as soon as sufficient evidence of either the presence or absence of a treatment effect is available. The circumstances under which the trial will be stopped with a claim of superiority for the experimental treatment, must, however, be determined in advance so as to control the overall type I error rate. One approach to calculating the stopping rule is the group-sequential method. A relatively recent alternative to group-sequential approaches is the adaptive design method. This latter approach provides considerable flexibility in changes to the design of a clinical trial at an interim point. However, a criticism is that the method by which evidence from different parts of the trial is combined means that a final comparison of treatments is not based on a sufficient statistic for the treatment difference, suggesting that the method may lack power. The aim of this paper is to compare two adaptive design approaches with the group-sequential approach. We first compare the form of the stopping boundaries obtained using the different methods. We then focus on a comparison of the power of the different trials when they are designed so as to be as similar as possible. We conclude that all methods acceptably control type I error rate and power when the sample size is modified based on a variance estimate, provided no interim analysis is so small that the asymptotic properties of the test statistic no longer hold. In the latter case, the group-sequential approach is to be preferred. Provided that asymptotic assumptions hold, the adaptive design approaches control the type I error rate even if the sample size is adjusted on the basis of an estimate of the treatment effect, showing that the adaptive designs allow more modifications than the group-sequential method.

Apply response adaptive randomization to group sequential with early stopping

Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.^

Adaptive radiotherapy for virally mediated head and neck cancer : predicting which patients may benefit most

Background: Recent clinical studies have demonstrated an emerging subgroup of head and neck cancers that are virally mediated. This disease appears to be a distinct clinical entity with patients presenting younger and with more advanced nodal disease, having lower tobacco and alcohol exposure and highly radiosensitive tumours. This means they are living longer, often with the debilitating functional side effects of treatment. The primary objective of this study was to determine how virally mediated nasopharyngeal and oropharyngeal cancers respond to radiation therapy treatment. The aim was to determine risk categories and corresponding adaptive treatment management strategies to proactively manage these patients. Method/Results: 121 patients with virally mediated, node positive nasopharyngeal or oropharyngeal cancer who received radiotherapy treatment with curative intent between 2005 and 2010 were studied. Relevant patient demographics including age, gender, diagnosis, TNM stage, pre-treatment nodal size and dose delivered was recorded. Each patient’s treatment plan was reviewed to determine if another computed tomography (re-CT) scan was performed and at what time point (dose/fraction) this occurred. The justification for this re-CT was determined using four categories: tumour and/or nodal regression, weight loss, both or other. Patients who underwent a re-CT were further investigated to determine whether a new plan was calculated. If a re-plan was performed, the dosimetric effect was quantified by comparing dose volume histograms of planning target volumes and critical structures from the actual treatment delivered and the original treatment plan. Preliminary results demonstrated that 25/121 (20.7%) patients required a re-CT and that these re-CTs were performed between fractions 20 to 25 of treatment. The justification for these re-CTs consisted of a combination of tumour and/or nodal regression and weight loss. 16/25 (13.2%) patients had a replan calculated. 9 (7.4%) of these replans were implemented clinically due to the resultant dosimetric effect calculated. The data collected from this assessment was statistically analysed to identify the major determining factors for patients to undergo a re-CT and/or replan. Specific factors identified included nodal size and timing of the required intervention (i.e. how when a plan is to be adapted). This data was used to generate specific risk profiles that will form the basis of a biologically guided adaptive treatment management strategy for virally mediated head and neck cancer. Conclusion: Preliminary data indicates that virally mediated head and neck cancers respond significantly during radiation treatment (tumour and/or nodal regression and weight loss). Implications of this response are the potential underdosing or overdosing of tumour and/or surrounding critical structures. This could lead to sub-optimal patient outcomes and compromised quality of life. Consequently, the development of adaptive treatment strategies that improve organ sparing for this patient group is important to ensure delivery of the prescribed dose to the tumour volume whilst minimizing the dose received to surrounding critical structures. This could reduce side effects and improve overall patient quality of life. The risk profiles and associated adaptive treatment approaches developed in this study will be tested prospectively in the clinical setting in Phase 2 of this investigation.

Adaptive radiotherapy for virally mediated head and neck cancer

Introduction: Clinical investigation has revealed a subgroup of head and neck cancers that are virally mediated. The relationship between nasopharyngeal cancer and Epstein Barr Virus (EBV) has long been established and more recently, the association between oropharyngeal cancer and Human Papillomavirus (HPV) has been revealed1,2 These cancers often present with nodal involvement and generally respond well to radiation treatment, evidenced by tumour regression1. This results in the need for treatment plan adaptation or re-planning in a subset of patients. Adaptive techniques allow the target region of the radiotherapy treatment plan to be altered in accordance with treatment-induced changes to ensure that under or over dosing does not occur3. It also assists in limiting potential overdosing of surrounding critical normal tissues4. We sought to identify a high-risk group based on nodal size to be evaluated in a future prospective adaptive radiotherapy trial. Method: Between 2005-2010, 121 patients with virally mediated, node positive nasopharyngeal (EBV positive) or oropharyngeal (HPV positive) cancers, receiving curative intent radiotherapy treatment were reviewed. Patients were analysed based on maximum size of the dominant node at diagnosis with a view to grouping them in varying risk categories to determine the need of re-planning. The frequency and timing of the re-planning scans were also evaluated. Results: Sixteen nasopharyngeal and 105 oropharyngeal tumours were reviewed. Twenty-five (21%) patients underwent a re-planning CT at a median of 22 (range, 0-29) fractions with 1 patient requiring re-planning prior to the commencement of treatment. Based on the analysis, patients were subsequently placed into risk categories; ≤35mm (Group 1), 36-45mm (Group 2), ≥46mm (Group 3). Re-planning CT’s were performed in Group 1- 8/68 (11.8%), Group 2- 4/28 (14.3%), Group 3- 13/25 (52%). Conclusion: In this series, patients with virally mediated head and neck cancer and nodal size > 46mm appear to be a high-risk group for the need of re-planning during a course of curative radiotherapy. This finding will now be tested in a prospective adaptive radiotherapy study. ‘Real World’ Implications: This research identifies predictive factors for those patients with virally mediated head and neck cancer that will benefit most from treatment adaptation. This will assist in minimising the side effects experienced by these patients thereby improving their quality of life after treatment.

Adaptive radiotherapy for virally mediated head and neck cancer

Purpose: Virally mediated head and neck cancers (VMHNC) often present with nodal involvement, and are generally considered radioresponsive, resulting in the need for a re-planning CT during radiotherapy (RT) in a subset of patients. We sought to identify a high-risk group based on nodal size to be evaluated in a future prospective adaptive RT trial. Methodology: Between 2005-2010, 121 patients with virally-mediated, node positive nasopharyngeal (EBV positive) or oropharyngeal (HPV positive) cancers, receiving curative intent RT were reviewed. Patients were analysed based on maximum size of the dominant node with a view to grouping them in varying risk categories for the need of re-planning. The frequency and timing of the re-planning scans were also evaluated. Results: Sixteen nasopharyngeal and 105 oropharyngeal tumours were reviewed. Twenty-five (21%) patients underwent a re-planning CT at a median of 22 (range, 0-29) fractions with 1 patient requiring re-planning prior to the commencement of treatment. Based on the analysis, patients were subsequently placed into 3 groups; ≤35mm (Group 1), 36-45mm (Group 2), ≥46mm (Group 3). Re-planning CT’s were performed in Group 1- 8/68 (11.8%), Group 2- 4/28 (14.3%), Group 3- 13/25 (52%). Sample size did not allow statistical analysis to detect a significant difference or exclusion of a lack of difference between the 3 groups. Conclusion: In this series, patients with VMHNC and nodal size > 46mm appear to be a high-risk group for the need of re-planning during a course of definitive radiotherapy. This finding will now be tested in a prospective adaptive RT study.