Carfilzomib and dexamethasone versus bortezomib and dexamethasone for patients with relapsed or refractory multiple myeloma (ENDEAVOR): And randomised, phase 3, open-label, multicentre study

Background: Bortezomib with dexamethasone is a standard treatment option for relapsed or refractory multiple myeloma. Carfilzomib with dexamethasone has shown promising activity in patients in this disease setting. The aim of this study was to compare the combination of carfilzomib and dexamethasone with bortezomib and dexamethasone in patients with relapsed or refractory multiple myeloma. Methods: In this randomised, phase 3, open-label, multicentre study, patients with relapsed or refractory multiple myeloma who had one to three previous treatments were randomly assigned (1:1) using a blocked randomisation scheme (block size of four) to receive carfilzomib with dexamethasone (carfilzomib group) or bortezomib with dexamethasone (bortezomib group). Randomisation was stratified by previous proteasome inhibitor therapy, previous lines of treatment, International Staging System stage, and planned route of bortezomib administration if randomly assigned to bortezomib with dexamethasone. Patients received treatment until progression with carfilzomib (20 mg/m2 on days 1 and 2 of cycle 1; 56 mg/m2 thereafter; 30 min intravenous infusion) and dexamethasone (20 mg oral or intravenous infusion) or bortezomib (1·3 mg/m2; intravenous bolus or subcutaneous injection) and dexamethasone (20 mg oral or intravenous infusion). The primary endpoint was progression-free survival in the intention-to-treat population. All participants who received at least one dose of study drug were included in the safety analyses. The study is ongoing but not enrolling participants; results for the interim analysis of the primary endpoint are presented. The trial is registered at ClinicalTrials.gov, number NCT01568866. Findings: Between June 20, 2012, and June 30, 2014, 929 patients were randomly assigned (464 to the carfilzomib group; 465 to the bortezomib group). Median follow-up was 11·9 months (IQR 9·3-16·1) in the carfilzomib group and 11·1 months (8·2-14·3) in the bortezomib group. Median progression-free survival was 18·7 months (95% CI 15·6-not estimable) in the carfilzomib group versus 9·4 months (8·4-10·4) in the bortezomib group at a preplanned interim analysis (hazard ratio [HR] 0·53 [95% CI 0·44-0·65]; p<0·0001). On-study death due to adverse events occurred in 18 (4%) of 464 patients in the carfilzomib group and in 16 (3%) of 465 patients in the bortezomib group. Serious adverse events were reported in 224 (48%) of 463 patients in the carfilzomib group and in 162 (36%) of 456 patients in the bortezomib group. The most frequent grade 3 or higher adverse events were anaemia (67 [14%] of 463 patients in the carfilzomib group vs 45 [10%] of 456 patients in the bortezomib group), hypertension (41 [9%] vs 12 [3%]), thrombocytopenia (39 [8%] vs 43 [9%]), and pneumonia (32 [7%] vs 36 [8%]). Interpretation: For patients with relapsed or refractory multiple myeloma, carfilzomib with dexamethasone could be considered in cases in which bortezomib with dexamethasone is a potential treatment option. Funding: Onyx Pharmaceuticals, Inc., an Amgen subsidiary

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA

Purpose: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. Methods: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Results: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0–1.00) and 85.9% (75.4–92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20–2.92) or receiving a written TLD (HR 2.32, CI 1.11–4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Conclusion: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Multi-physics meso-scale finite element simulation of HMX-based solid propellant subjected to thermal insults

A large strain chemo-thermo-mechanical numerical framework has been developed to model the coupled chemical, thermal and mechanical behavior of solid propellant at the meso-scale. The mechanical behavior is modeled using a hyperelastic material model with viscous damage and J2 plasticity. The model admits a general nonlinear coefficient of thermal expansion to capture the thermo-mechanical behavior. The chemical model considers a system of chemical reactions with the rate kinetics being governed by a modified Arrhenius law. The thermal model considers thermodynamically consistent energy contributions from the inelastic mechanical deformations and the chemical reactions. The finite element method has been employed to discretize the continuum equations. Some simulation results will be presented to demonstrate the use of the developed framework in modeling the behavior of HMX-based solid propellant under thermal loads. The developed framework captures the large volumetric strains that are a characteristic of the β-δ phase transition of the HMX crystals and is able to predict locations of potential cracks in the binder. Such a simulation tool may prove to be useful in determining optimal conditions for the safe storage of such materials.by Gaurav Srivastava and K. Matou

Uncertainty quantification of the reverse Taylor impact test and localized asynchronous space-time algorithm

The reverse Taylor impact is a common experiment to investigate the dynamical response of materials at high strain rates. To better understand the physical phenomena and to provide a platform for code validation and Uncertainty Quantification (UQ), a co-designed simulation and experimental paradigm is investigated. For validation under uncertainty, quantities of interest (QOIs) within subregions of the computational domain are introduced. When regions of interest can be identified, the computational cost for UQ can be reduced by confining the random variability within these regions. This observation inspired us to develop an asynchronous space and time computational algorithm with localized UQ. In every region of interest, high resolution space and time discretization schemes are used for a stochastic model. Apart from the regions of interest, low spatial and temporal resolutions are allowed for a stochastic model with low dimensional representation of uncertainty. The approach is exercised on a linear elastodynamics problem and shows a potential in reducing the UQ computational cost

Forget opinion leaders: the role of social network brokers in the adoption of innovative farming practices in North-western Cambodia

It has become accepted that social networks influence farmers’ decisions and agricultural development programs routinely support influential farmers in an effort to disseminate recommended practices through their social networks. We have interviewed (1) 120 heads of farming households in one village in North-western Cambodia about their networks and practices; and (2) representatives of organizations managing agricultural development programs in the region. We have constructed an information-sharing network of the village and computed network centrality measures of each farmer in the village indicating their access to information from peers, opinion leadership, brokerage, and the redundancy among their contacts. We have analysed the relation of farmers’ networks and their practices. While the number of links farmers’ had in the community was mainly unrelated with their adoption decisions, the structure of these links mattered. Farmers who were perceived as influential were not necessarily inclined towards recommended practices. In contrast, farmers who had fewer contacts but were in brokerage positions on main channels of information flows between different groups displayed more progressive practices. The results suggest some limitations of excessive reliance on perceived influential farmers in agricultural programs and highlight the role that network brokers play in adoption of innovative farming practices

A review of predictive nonlinear theories for multiscale modeling of heterogeneous materials

Since the beginning of the industrial age, material performance and design have been in the midst of innovation of many disruptive technologies. Today’s electronics, space, medical, transportation, and other industries are enriched by development, design and deployment of composite, heterogeneous and multifunctional materials. As a result, materials innovation is now considerably outpaced by other aspects from component design to product cycle. In this article, we review predictive nonlinear theories for multiscale modeling of heterogeneous materials. Deeper attention is given to multiscale modeling in space and to computational homogenization in addressing challenging materials science questions. Moreover, we discuss a state-of-the-art platform in predictive image-based, multiscale modeling with co-designed simulations and experiments that executes on the world’s largest supercomputers. Such a modeling framework consists of experimental tools, computational methods, and digital data strategies. Once fully completed, this collaborative and interdisciplinary framework can be the basis of Virtual Materials Testing standards and aids in the development of new material formulations. Moreover, it will decrease the time to market of innovative products