On the almost sure convergence of adaptive allocation procedures

In this paper, we provide some general convergence results for adaptive designs for treatment comparison, both in the absence and presence of covariates. In particular, we demonstrate the almost sure convergence of the treatment allocation proportion for a vast class of adaptive procedures, also including designs that have not been formally investigated but mainly explored through simulations, such as Atkinson's optimum biased coin design, Pocock and Simon's minimization method and some of its generalizations. Even if the large majority of the proposals in the literature rely on continuous allocation rules, our results allow to prove via a unique mathematical framework the convergence of adaptive allocation methods based on both continuous and discontinuous randomization functions. Although several examples of earlier works are included in order to enhance the applicability, our approach provides substantial insight for future suggestions, especially in the absence of a prefixed target and for designs characterized by sequences of allocation rules.Comment: Published at http://dx.doi.org/10.3150/13-BEJ591 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Simulated Clinical Trias: some design issues

Simulation is widely used to investigate real-world systems in a large number of fields, including clinical trials for drug development, since real trials are costly, frequently fail and may lead to serious side effects. This paper is a survey of the statistical issues arising in these simulated trials. We illustrate the broad applicability of this investigation tool by means of examples selected from the literature. We discuss the aims and the peculiarities of the simulation models used in this context, including a brief mention of the use of metamodels. Of special interest is the topic of the design of the virtual experiments, stressing similarities and differences with the design of real life trials. Since it is important for a computerized model to possess a satisfactory range of accuracy consistent with its intended application, real data provided by physical experiments are used to confirm the simulator : we illustrate validating techniques through a number of examples. We end the paper with some challenging questions on the scientificity, ethics and effectiveness of simulation in the clinical research, and the interesting research problem of how to integrate simulated and physical experiments in a clinical context.Simulation models; pharmacokinetics; pharmacodynamics; model validation; experimental design, ethics. Modelli di simulazione; farmacocinetica; farmacodinamica; validazione; disegno degli esperimenti; etica.

Multi-objective optimal designs in comparative clinical trials with covariates: The reinforced doubly adaptive biased coin design

The present paper deals with the problem of allocating patients to two competing treatments in the presence of covariates or prognostic factors in order to achieve a good trade-off among ethical concerns, inferential precision and randomness in the treatment allocations. In particular we suggest a multipurpose design methodology that combines efficiency and ethical gain when the linear homoscedastic model with both treatment/covariate interactions and interactions among covariates is adopted. The ensuing compound optimal allocations of the treatments depend on the covariates and their distribution on the population of interest, as well as on the unknown parameters of the model. Therefore, we introduce the reinforced doubly adaptive biased coin design, namely a general class of covariate-adjusted response-adaptive procedures that includes both continuous and discontinuous randomization functions, aimed to target any desired allocation proportion. The properties of this proposal are described both theoretically and through simulations.Comment: Published in at http://dx.doi.org/10.1214/12-AOS1007 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Simulated Clinical Trias: some design issues

Simulation is widely used to investigate real-world systems in a large number of fields, including clinical trials for drug development, since real trials are costly, frequently fail and may lead to serious side effects. This paper is a survey of the statistical issues arising in these simulated trials. We illustrate the broad applicability of this investigation tool by means of examples selected from the literature. We discuss the aims and the peculiarities of the simulation models used in this context, including a brief mention of the use of metamodels. Of special interest is the topic of the design of the virtual experiments, stressing similarities and differences with the design of real life trials. Since it is important for a computerized model to possess a satisfactory range of accuracy consistent with its intended application, real data provided by physical experiments are used to confirm the simulator: we illustrate validating techniques through a number of examples. We end the paper with some challenging questions on the scientificity, ethics and effectiveness of simulation in the clinical research, and the interesting research problem of how to integrate simulated and physical experiments in a clinical context

Simulated annealing for balancing covariates

Covariate balance is one of the fundamental issues in designing experiments for treatment comparisons, especially in randomized clinical trials. In this article, we introduce a new class of covariate-adaptive procedures based on the Simulated Annealing algorithm aimed at balancing the allocations of two competing treatments across a set of pre-specified covariates. Due to the nature of the simulated annealing, these designs are intrinsically randomized, thus completely unpredictable, and very flexible: they can manage both quantitative and qualitative factors and be implemented in a static version as well as sequentially. The properties of the suggested proposal are described, showing a significant improvement in terms of covariate balance and inferential accuracy with respect to all the other procedures proposed in the literature. An illustrative example based on real data is also discussed

New insights into adaptive enrichment designs

The transition towards personalized medicine is happening and the new experimental framework is raising several challenges, from a clinical, ethical, logistical, regulatory, and statistical perspective. To face these challenges, innovative study designs with increasing complexity have been proposed. In particular, adaptive enrichment designs are becoming more attractive for their flexibility. However, these procedures rely on an increasing number of parameters that are unknown at the planning stage of the clinical trial, so the study design requires particular care. This review is dedicated to adaptive enrichment studies with a focus on design aspects. While many papers deal with methods for the analysis, the sample size determination and the optimal allocation problem have been overlooked. We discuss the multiple aspects involved in adaptive enrichment designs that contribute to their advantages and disadvantages. The decision-making process of whether or not it is worth enriching should be driven by clinical and ethical considerations as well as scientific and statistical concerns

A simple solution to the inadequacy of asymptotic likelihood-based inference for response-adaptive clinical trials

The present paper discusses drawbacks and limitations of likelihood-based inference in sequential clinical trials for treatment comparisons managed viaResponse-Adaptive Randomization. Taking into account the most common statistical models for the primary outcome—namely binary, Poisson, exponential and normal data—we derive the conditions under which (i) the classical confidence intervals degenerate and (ii) the Wald test becomes inconsistent and strongly affected by the nuisance parameters, also displaying a non monotonic power. To overcome these drawbacks, we provide a very simple solution that could preserve the fundamental properties of likelihood-based inference. Several illustrative examples and simulation studies are presented in order to confirm the relevance of our results and provide some practical recommendations

Peptidergic modulation of motor neuron output via CART signaling at C bouton synapses

Funding: This work was supported by the General Secretariat for Research and Technology (ARISTEIA II 4257, L.Z.), Fondation SANTE (L.Z.), a Marie Curie Re-Integration Grant (268323, L.Z.), the Hellenic Foundation for Research and Innovation (spinMNALS, 4013, L.Z.) and by a St. Andrews Restarting Research Fund (S.A.S. and G.B.M.). S.A.S. was funded by a Royal Society Newton International Fellowship (NIF/R1/180091) and a Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowship (NSERC-PDF-517295-2018) and M.M. by the National Scholarship Foundation (IKY).The intensity of muscle contraction, and therefore movement vigour, needs to be adaptable to enable complex motor behaviors. This can be achieved by adjusting the properties of motor neurons, which form the final common pathway for all motor output from the central nervous system. Here we identify novel roles for a neuropeptide, Cocaine and Amphetamine Regulated Transcript (CART), in the control of movement vigour. We reveal distinct, but parallel mechanisms by which CART and acetylcholine, both released at C bouton synapses on motor neurons, selectively amplify the output of subtypes of motor neurons that are recruited during intense movement. We find that mice with broad genetic deletion of CART or selective elimination of acetylcholine from C boutons exhibit deficits in behavioral tasks that require higher levels of motor output. Overall, these data uncover novel spinal modulatory mechanisms that control movement vigour to support movements that require a high degree of muscle force.Publisher PDFPeer reviewe

Pitx2 cholinergic interneurons are the source of C bouton synapses on brainstem motor neurons

IR and LZ were funded by the European Union, Seventh Framework Programme (FP7/2007–2013), by the European Union and Greek National Funds through the operational program “Education and Lifelong Learning” of the National Strategic Reference Framework, funding program: ARISTEIA II, and by Fondation Santé.Cholinergic neuromodulation has been described throughout the brain and has been implicated in various functions including attention, food intake and response to stress. Cholinergic modulation is also thought to be important for regulating motor systems, as revealed by studies of large cholinergic synapses on spinal motor neurons, called C boutons, which seem to control motor neuron excitability in a task-dependent manner. C boutons on spinal motor neurons stem from spinal interneurons that express the transcription factor Pitx2. C boutons have also been identified on the motor neurons of specific cranial nuclei. However, the source and roles of cranial C boutons are less clear. Previous studies suggest that they originate from Pitx2+ and Pitx2− neurons, in contrast to spinal cord C boutons that originate solely from Pitx2 neurons. Here, we address this controversy using mouse genetics, and demonstrate that brainstem C boutons are Pitx2+ derived. We also identify new Pitx2 populations and map the cholinergic Pitx2 neurons of the mouse brain. Taken together, our data present important new information about the anatomical organization of cholinergic systems which impact motor systems of the brainstem. These findings will enable further analyses of the specific roles of cholinergic modulation in motor control.Publisher PDFPeer reviewe