Adaptive Survival Trials

Mid-study design modifications are becoming increasingly accepted in confirmatory clinical trials, so long as appropriate methods are applied such that error rates are controlled. It is therefore unfortunate that the important case of time-to-event endpoints is not easily handled by the standard theory. We analyze current methods that allow design modifications to be based on the full interim data, i.e., not only the observed event times but also secondary endpoint and safety data from patients who are yet to have an event. We show that the final test statistic may ignore a substantial subset of the observed event times. Since it is the data corresponding to the earliest recruited patients that is ignored, this neglect becomes egregious when there is specific interest in learning about long-term survival. An alternative test incorporating all event times is proposed, where a conservative assumption is made in order to guarantee type I error control. We examine the properties of our proposed approach using the example of a clinical trial comparing two cancer therapies.Comment: 22 pages, 7 figure

Sample size reassessment and hypothesis testing in adaptive survival trials

Mid-study design modifications are becoming increasingly accepted in confirmatory clinical trials, so long as appropriate methods are applied such that error rates are controlled. It is therefore unfortunate that the important case of time-to-event endpoints is not easily handled by the standard theory. We analyze current methods that allow design modifications to be based on the full interim data, i.e., not only the observed event times but also secondary endpoint and safety data from patients who are yet to have an event. We show that the final test statistic may ignore a substantial subset of the observed event times. An alternative test incorporating all event times is found, where a conservative assumption must be made in order to guarantee type I error control. We examine the power of this approach using the example of a clinical trial comparing two cancer therapies

CAD/CAM Resin-Based Composites for Use in Long-Term Temporary Fixed Dental Prostheses

The aim of this in vitro study was to analyse the performance of CAD/CAM resin-based composites for the fabrication of long-term temporary fixed dental prostheses (FDP) and to compare it to other commercially available alternative materials regarding its long-term stability. Four CAD/CAM materials [Structur CAD (SC), VITA CAD-Temp (CT), Grandio disc (GD), and Lava Esthetic (LE)] and two direct RBCs [(Structur 3 (S3) and LuxaCrown (LC)] were used to fabricate three-unit FDPs. 10/20 FDPs were subjected to thermal cycling and mechanical loading by chewing simulation and 10/20 FDPs were stored in distilled water. Two FDPs of each material were forwarded to additional image diagnostics prior and after chewing simulation. Fracture loads were measured and data were statistically analysed. SC is suitable for use as a long-term temporary (two years) three-unit FDP. In comparison to CT, SC featured significantly higher breaking forces (SC > 800 N; CT < 600 N) and the surface wear of the antagonists was (significantly) lower and the abrasion of the FDP was similar. The high breaking forces (1100–1327 N) of GD and the small difference compared to LE regarding flexural strength showed that the material might be used for the fabrication of three-unit FDPs. With the exception of S3, all analysed direct or indirect materials are suitable for the fabrication of temporary FDPs

The cognitive and emotional reactions of college gymnasts during competition as a function of success, security of performance, phase of performance and sex of subject.

PsychologyDoctor of Philosophy (PhD

Artificial Intelligence in Multiphoton Tomography: Atopic Dermatitis Diagnosis

The diagnostic possibilities of multiphoton tomography (MPT) in dermatology have already been demonstrated. Nevertheless, the analysis of MPT data is still time-consuming and operator dependent. We propose a fully automatic approach based on convolutional neural networks (CNNs) to fully realize the potential of MPT. In total, 3,663 MPT images combining both morphological and metabolic information were acquired from atopic dermatitis (AD) patients and healthy volunteers. These were used to train and tune CNNs to detect the presence of living cells, and if so, to diagnose AD, independently of imaged layer or position. The proposed algorithm correctly diagnosed AD in 97.0 ± 0.2% of all images presenting living cells. The diagnosis was obtained with a sensitivity of 0.966 ± 0.003, specificity of 0.977 ± 0.003 and F-score of 0.964 ± 0.002. Relevance propagation by deep Taylor decomposition was used to enhance the algorithm’s interpretability. Obtained heatmaps show what aspects of the images are important for a given classification. We showed that MPT imaging can be combined with artificial intelligence to successfully diagnose AD. The proposed approach serves as a framework for the automatic diagnosis of skin disorders using MPT

Adaptive clinical trial designs with blinded selection of binary composite endpoints and sample size reassessment

For randomized clinical trials where a single, primary, binary endpoint would require unfeasibly large sample sizes, composite endpoints (CEs) are widely chosen as the primary endpoint. Despite being commonly used, CEs entail challenges in designing and interpreting results. Given that the components may be of different relevance and have different effect sizes, the choice of components must be made carefully. Especially, sample size calculations for composite binary endpoints depend not only on the anticipated effect sizes and event probabilities of the composite components but also on the correlation between them. However, information on the correlation between endpoints is usually not reported in the literature which can be an obstacle for designing future sound trials. We consider two-arm randomized controlled trials with a primary composite binary endpoint and an endpoint that consists only of the clinically more important component of the CE. We propose a trial design that allows an adaptive modification of the primary endpoint based on blinded information obtained at an interim analysis. Especially, we consider a decision rule to select between a CE and its most relevant component as primary endpoint. The decision rule chooses the endpoint with the lower estimated required sample size. Additionally, the sample size is reassessed using the estimated event probabilities and correlation, and the expected effect sizes of the composite components. We investigate the statistical power and significance level under the proposed design through simulations. We show that the adaptive design is equally or more powerful than designs without adaptive modification on the primary endpoint. Besides, the targeted power is achieved even if the correlation is misspecified at the planning stage while maintaining the type 1 error. All the computations are implemented in R and illustrated by means of a peritoneal dialysis trial.The Ministerio de Ciencia e Innovación (Spain) (PID2019-104830RB-I00); the Departament d’Empresa i Coneixement de la Generalitat de Catalunya under 2017 SGR 622 (GRBIO) to M.B.R. and G.G.M. M.B.R., F.K., and M.P. are members of the EU Patient-centric clinical trial platform (EU-PEARL). EU-PEARL has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 853966. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and Children’s Tumor Foundation, Global Alliance for TB Drug Development non-profit organization, Spring- works Therapeutics Inc. This publication reflects the author’s views. Neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.Peer ReviewedPostprint (published version

Thermoanalytical Investigations on the Influence of Storage Time in Water of Resin-Based CAD/CAM Materials

New resin-based composites and resin-infiltrated ceramics are used to fabricate computer-aided design (CAD) and computer-aided manufacturing (CAM)-based restorations, although little information is available on the long-term performance of these materials. The aim of this investigation was to determine the effects of storage time (24 h, 90 days, 180 days) on the thermophysical properties of resin-based CAD/CAM materials. Thermogravimetric Analysis (TGA), differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) were used in the study. TGA provided insight into the composition of the resin-based materials and the influence of internal plasticization and water sorption. Resin-based composites showed different decomposition, heat energy and mechanical behavior, which was influenced by storage time in water. Individual materials such as Grandio bloc showed lower influence of water storage while maintaining good mechanical properties

\u3ci\u3eIn-situ\u3c/i\u3e-Investigation of Enzyme Immobilization on Polymer Brushes

Herein, we report on the use of a combined setup of quartz-crystal microbalance, with dissipation monitoring and spectroscopic ellipsometry, to comprehensively investigate the covalent immobilization of an enzyme to a polymer layer. All steps of the covalent reaction of the model enzyme glucose oxidase with the poly(acrylic acid) brush by carbodiimide chemistry, were monitored in-situ. Data were analyzed using optical and viscoelastic modeling. A nearly complete collapse of the polymer chains was found upon activation of the carboxylic acid groups with N-(3-Dimethylaminopropyl)-N′-ethylcarbodiimide and N-Hydroxysuccinimide. The reaction with the amine groups of the enzyme occurs simultaneously with re-hydration of the polymer layer. Significantly more enzyme was immobilized on the surface compared to physical adsorption at similar conditions, at the same pH. It was found that the pH responsive swelling behavior was almost not affected by the presence of the enzyme

Rates of agonism among female primates: a cross-taxon perspective

Agonism is common in group-living animals, shaping dominance relationships and ultimately impacting individual tness. Rates of agonism vary considerably among taxa, however, and explaining this variation has been central in ecological models of female social relationships in primates. Early iterations of these models posited a link to diet, with more frequent agonism predicted in frugivorous species due to the presumed greater contestability of fruits relative to other food types. Although some more recent studies have suggested that dietary categories may be poor predictors of contest competition among primates, to date there have been no broad, cross-taxa comparisons of rates of female–female agonism in relation to diet. This study tests whether dietary variables do indeed pre- dict rates of female agonism and further investigates the role of group size (i.e., number of competitors) and substrate use (i.e., degree of arboreality) on the frequency of agonism. Data from 44 wild, unprovisioned groups, including 3 strepsirhine species, 3 platyrrhines, 5 colobines, 10 cercopithecines, and 2 hominoids were analyzed using phylogenetically controlled and uncontrolled methods. Results indicate that diet does not predict agonistic rates, with trends actually being in the opposite direction than predicted for all taxa except cercopithecines. In contrast, agonistic rates are positively associated with group size and possibly degree of terrestriality. Competitor density and perhaps the risk of ghting, thus, appear more important than general diet in predicting agonism among female primates. We discuss the implications of these results for socio-ecological hypotheses