Efficacy and safety of ixekizumab through 52 weeks in two phase 3, randomised, controlled clinical trials in patients with active radiographic axial spondyloarthritis (COAST-V and COAST-W).

OBJECTIVES: To investigate the efficacy and safety of ixekizumab for up to 52 weeks in two phase 3 studies of patients with active radiographic axial spondyloarthritis (r-axSpA) who were biological disease-modifying antirheumatic drug (bDMARD)-naive (COAST-V) or tumour necrosis factor inhibitor (TNFi)-experienced (COAST-W). METHODS: Adults with active r-axSpA were randomised 1:1:1:1 (n=341) to 80 mg ixekizumab every 2 (IXE Q2W) or 4 weeks (IXE Q4W), placebo (PBO) or 40 mg adalimumab Q2W (ADA) in COAST-V and 1:1:1 (n=316) to IXE Q2W, IXE Q4W or PBO in COAST-W. At week 16, patients receiving ixekizumab continued their assigned treatment; patients receiving PBO or ADA were rerandomised 1:1 to IXE Q2W or IXE Q4W (PBO/IXE, ADA/IXE) through week 52. RESULTS: In COAST-V, Assessment of SpondyloArthritis international Society 40 (ASAS40) responses rates (intent-to-treat population, non-responder imputation) at weeks 16 and 52 were 48% and 53% (IXE Q4W); 52% and 51% (IXE Q2W); 36% and 51% (ADA/IXE); 19% and 47% (PBO/IXE). Corresponding ASAS40 response rates in COAST-W were 25% and 34% (IXE Q4W); 31% and 31% (IXE Q2W); 14% and 39% (PBO/IXE). Both ixekizumab regimens sustained improvements in disease activity, physical function, objective markers of inflammation, QoL, health status and overall function up to 52 weeks. Safety through 52 weeks of ixekizumab was consistent with safety through 16 weeks. CONCLUSION: The significant efficacy demonstrated with ixekizumab at week 16 was sustained for up to 52 weeks in bDMARD-naive and TNFi-experienced patients. bDMARD-naive patients initially treated with ADA demonstrated further numerical improvements after switching to ixekizumab. Safety findings were consistent with the known safety profile of ixekizumab. TRIAL REGISTRATION NUMBER: NCT02696785/NCT02696798

Exponential-Krylov methods for ordinary differential equations

This paper develops a new class of exponential-type integrators where all the matrix exponentiations are performed in a single Krylov space of low dimension. The new family, called Lightly Implicit Krylov-Exponential (LIKE), is well suited for solving large scale systems of ODEs or semi-discrete PDEs. The time discretization and the Krylov space approximation are treated as a single computational process, and the Krylov space properties are an integral part of the new LIKE order condition theory developed herein. Consequently, LIKE methods require a small number of basis vectors determined solely by the temporal order of accuracy. The subspace size is independent of the ODE under consideration, and there is no need to monitor the errors in linear system solutions at each stage. Numerical results illustrate the favorable properties of new family of methods

Pack Factor Measurements for Corn in Grain Storage Bins

Shelled yellow corn is commonly stored in concrete or corrugated steel bins. Granular materials compact under their own weight, primarily due to particle rearrangement, leading to an increase in bulk density and a change in volume when stored. Reliable grain pack factors are needed to estimate storage capacities and to accurately monitor grain inventories. A science-based model (WPACKING) of pack factors is available that uses the differential form of Janssen’s equation and takes into account the variation in density caused by pressure variation with height and moisture content of the grain and accounts for the effects of grain type, test weight, bin geometry, and bin material. However, this model needs to be compared to field data over a wide range of conditions to ensure robust prediction accuracy. The objective of this research was to determine the field pack factors and bin capacities for on-farm and commercial bins used to store corn in the U.S. and compare them to predictions of the WPACKING program. Bin inventory measurements were conducted in concrete bins with depths up to 31.4 m (114.8 ft) and corrugated steel bins with diameters up to 32.8 m (156Â ft). These values were also compared to the techniques used by the USDA Risk Management Agency (RMA) and the USDA Farm Service Agency, Warehouse Branch (FSA-W). The differences between predicted and reported mass were -4.54% (maximum underprediction) to +4.53% (maximum overprediction) for WPACKING, -2.69% to 4.97% for the RMA method, and -3.33% to + 5.67% for the FSA-W method. The absolute average difference was lowest for the WPACKING model (0.90%) compared to the RMA and FSA-W methods (1.61% and 1.86%, respectively). WPACKING had less than half as many prediction differences above 1% (13 out of 51 bins) as did the RMA and FSA-W methods, which had 29 out of 51 and 33 out of 51, respectively. The RMA and FSA-W methods do not take into account the variations in pack factor due to bin type and moisture content of the stored grain

Impact of region-of-interest delineation methods, reconstruction algorithms, and intra- and inter-operator variability on internal dosimetry estimates using PET

Purpose Human dosimetry studies play a central role in radioligand development for positron emission tomography (PET). Drawing regions of interest (ROIs) on the PET images is used to measure the dose in each organ. In the study aspects related to ROI delineation methods were evaluated for two radioligands of different biodistribution (intestinal vs urinary). Procedures PET images were simulated from a human voxel-based phantom. Several ROI delineation methods were tested: antero-posterior projections (AP), 3D sub-samples of the organs (S), and a 3D volume covering the whole-organ (W). Inter- and intra-operator variability ROI drawing was evaluated by using human data. Results The effective dose estimates using S and W methods were comparable to the true values. AP methods overestimated (49 %) the dose for the radioligand with intestinal biodistribution. Moreover, the AP method showed the highest inter-operator variability: 11 ± 1 %. Conclusions The sub-sampled organ method showed the best balance between quantitative accuracy and inter- and intra-operator variability.Postprint (author's final draft

Lambert W random variables - a new family of generalized skewed distributions with applications to risk estimation

Originating from a system theory and an input/output point of view, I introduce a new class of generalized distributions. A parametric nonlinear transformation converts a random variable $X$ into a so-called Lambert $W$ random variable $Y$, which allows a very flexible approach to model skewed data. Its shape depends on the shape of $X$ and a skewness parameter $\gamma$. In particular, for symmetric $X$ and nonzero $\gamma$ the output $Y$ is skewed. Its distribution and density function are particular variants of their input counterparts. Maximum likelihood and method of moments estimators are presented, and simulations show that in the symmetric case additional estimation of $\gamma$ does not affect the quality of other parameter estimates. Applications in finance and biomedicine show the relevance of this class of distributions, which is particularly useful for slightly skewed data. A practical by-result of the Lambert $W$ framework: data can be "unskewed." The $R$ package http://cran.r-project.org/web/packages/LambertWLambertW developed by the author is publicly available (http://cran.r-project.orgCRAN).Comment: Published in at http://dx.doi.org/10.1214/11-AOAS457 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Symbolic Manipulation of Flows of Nonlinear Evolution Equations, with Application in the Analysis of Split-Step Time Integrators

We describe a package realized in the Julia programming language which performs symbolic manipulations applied to nonlinear evolution equations, their flows, and commutators of such objects. This tool was employed to perform contrived computations arising in the analysis of the local error of operator splitting methods. It enabled the proof of the convergence of the basic method and of the asymptotical correctness of a defect-based error estimator. The performance of our package is illustrated on several examples

Peer Methods for the Solution of Large-Scale Differential Matrix Equations

We consider the application of implicit and linearly implicit (Rosenbrock-type) peer methods to matrix-valued ordinary differential equations. In particular the differential Riccati equation (DRE) is investigated. For the Rosenbrock-type schemes, a reformulation capable of avoiding a number of Jacobian applications is developed that, in the autonomous case, reduces the computational complexity of the algorithms. Dealing with large-scale problems, an efficient implementation based on low-rank symmetric indefinite factorizations is presented. The performance of both peer approaches up to order 4 is compared to existing implicit time integration schemes for matrix-valued differential equations.Comment: 29 pages, 2 figures (including 6 subfigures each), 3 tables, Corrected typo