654 resultados para Multiple-line insurance


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Purpose: This randomized, multicenter trial compared first-line trastuzumab plus docetaxel versus docetaxel alone in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC). Patients and Methods: Patients were randomly assigned to six cycles of docetaxel 100 mg/m 2 every 3 weeks, with or without trastuzumab 4 mg/kg loading dose followed by 2 mg/kg weekly until disease progression. Results: A total of 186 patients received at least one dose of the study drug. Trastuzumab plus docetaxel was significantly superior to docetaxel alone in terms of overall response rate (61% v 34%; P = .0002), overall survival (median, 31.2 v 22.7 months; P = .0325), time to disease progression (median, 11.7 v 6.1 months; P = .0001), time to treatment failure (median, 9.8 v 5.3 months; P = .0001), and duration of response (median, 11.7 v 5.7 months; P = .009). There was little difference in the number and severity of adverse events between the arms. Grade 3 to 4 neutropenia was seen more commonly with the combination (32%) than with docetaxel alone (22%), and there was a slightly higher incidence of febrile neutropenia in the combination arm (23% v 17%). One patient in the combination arm experienced symptomatic heart failure (1%). Another patient experienced symptomatic heart failure 5 months after discontinuation of trastuzumab because of disease progression, while being treated with an investigational anthracycline for 4 months. Conclusion: Trastuzumab combined with docetaxel is superior to docetaxel alone as first-line treatment of patients with HER2-positive MBC in terms of overall survival, response rate, response duration, time to progression, and time to treatment failure, with little additional toxicity. © 2005 by American Society of Clinical Oncology.

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Background: Findings from the phase 3 First-Line ErbituX in lung cancer (FLEX) study showed that the addition of cetuximab to first-line chemotherapy significantly improved overall survival compared with chemotherapy alone (hazard ratio [HR] 0·871, 95% CI 0·762-0·996; p=0·044) in patients with advanced non-small-cell lung cancer (NSCLC). To define patients benefiting most from cetuximab, we studied the association of tumour EGFR expression level with clinical outcome in FLEX study patients. Methods: We used prospectively collected tumour EGFR expression data to generate an immunohistochemistry score for FLEX study patients on a continuous scale of 0-300. We used response data to select an outcome-based discriminatory threshold immunohistochemistry score for EGFR expression of 200. Treatment outcome was analysed in patients with low (immunohistochemistry score <200) and high (≥200) tumour EGFR expression. The primary endpoint in the FLEX study was overall survival. We analysed patients from the FLEX intention-to-treat (ITT) population. The FLEX study is registered with ClinicalTrials.gov, number NCT00148798. Findings: Tumour EGFR immunohistochemistry data were available for 1121 of 1125 (99·6%) patients from the FLEX study ITT population. High EGFR expression was scored for 345 (31%) evaluable patients and low for 776 (69%) patients. For patients in the high EGFR expression group, overall survival was longer in the chemotherapy plus cetuximab group than in the chemotherapy alone group (median 12·0 months [95% CI 10·2-15·2] vs 9·6 months [7·6-10·6]; HR 0·73, 0·58-0·93; p=0·011), with no meaningful increase in side-effects. We recorded no corresponding survival benefit for patients in the low EGFR expression group (median 9·8 months [8·9-12·2] vs 10·3 months [9·2-11·5]; HR 0·99, 0·84-1·16; p=0·88). A treatment interaction test assessing the difference in the HRs for overall survival between the EGFR expression groups suggested a predictive value for EGFR expression (p=0·044). Interpretation: High EGFR expression is a tumour biomarker that can predict survival benefit from the addition of cetuximab to first-line chemotherapy in patients with advanced NSCLC. Assessment of EGFR expression could offer a personalised treatment approach in this setting. Funding: Merck KGaA. © 2012 Elsevier Ltd.

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Background: The Lung Cancer Cetuximab Study is an open-label, randomized phase II pilot study of cisplatin and vinorelbine combined with the epidermal growth factor receptor (EGFR)-targeted monoclonal antibody cetuximab versus cisplatin and vinorelbine alone, in patients with advanced EGFR-expressing, non-small-cell lung cancer (NSCLC). End points of the study are activity, safety and pharmacokinetics. Patients and methods: Following randomization, for a maximum of eight cycles, patients received three-weekly cycles of cisplatin (80 mg/m2, day 1) and vinorelbine (25 mg/m2 on days 1 and 8) alone or following cetuximab treatment (initial dose 400 mg/m, followed by 250 mg/m2 weekly thereafter). Results: Eighty-six patients were randomly allocated to the study (43 per arm). Confirmed response rates were 28% in the cisplatin/vinorelbine arm (A) and 35% in the cetuximab plus cisplatin/vinorelbine arm (B). Median progression-free survival (PFS) was 4.6 months in arm A and 5.0 months in arm B, with PFS rates at 12 months of 0% and 15%, respectively. Median survival was 7.3 months in arm A and 8.3 months in arm B. The 24-month survival rates were 0% and 16%, respectively. The cetuximab combination was well tolerated. Conclusion: In the first-line treatment of advanced NSCLC, the combination of cetuximab plus cisplatin/vinorelbine demonstrated an acceptable safety profile and the potential to improve activity over cisplatin/vinorelbine alone. © 2007 European Society for Medical Oncology.

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Multiple-time signatures are digital signature schemes where the signer is able to sign a predetermined number of messages. They are interesting cryptographic primitives because they allow to solve many important cryptographic problems, and at the same time offer substantial efficiency advantage over ordinary digital signature schemes like RSA. Multiple-time signature schemes have found numerous applications, in ordinary, on-line/off-line, forward-secure signatures, and multicast/stream authentication. We propose a multiple-time signature scheme with very efficient signing and verifying. Our construction is based on a combination of one-way functions and cover-free families, and it is secure against the adaptive chosen-message attack.

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Sustainability is a key driver for decisions in the management and future development of organisations and industries. However, quantifying and comparing sustainability across the triple bottom line (TBL) of economy, environment and social impact, has been problematic. There is a need for a tool which can measure the complex interactions within and between the environmental, economic and social systems which affect the sustainability of an industry in a transparent, consistent and comparable way. The authors acknowledge that there are currently numerous ways in which sustainability is measured and multiple methodologies in how these measurement tools were designed. The purpose of this book is to showcase how Bayesian network modelling can be used to identify and measure environmental, economic and social sustainability variables and to understand their impact on and interaction with each other. This book introduces the Sustainability Scorecard, and describes it through a case study on sustainability of the Australian dairy industry. This study was conducted in collaboration with the Australian dairy industry.

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To complement the existing treatment guidelines for all tumour types, ESMO organises consensus conferences to focus on specific issues in each type of tumour. The 2nd ESMO Consensus Conference on Lung Cancer was held on 11-12 May 2013 in Lugano. A total of 35 experts met to address several questions on non-small-cell lung cancer (NSCLC) in each of four areas: pathology and molecular biomarkers, first-line/second and further lines in advanced disease, early stage disease and locally-advanced disease. For each question, recommendations were made including reference to the grade of recommendation and level of evidence. This consensus paper focuses on 1st line / 2nd and further lines of treatment in advanced disease. © The Author 2014. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved.

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Increasing population pressures and life-style choices are resulting in more people living in areas that are at risk of inundation from rising sea levels and flooding. However, following natural disaster events, such as the 2011 Queensland floods, many Australians discovered they were uninsured. Either their insurance policies did not cover flood; or multiple (and confusing) water-related definitions led them to believe they had cover when they did not. Several theories are analysed to try to explain what is a world-wide underinsurance problem but these do not provide an answer to the problem. This research focuses on uncovering the reasons consumers fail to adequately insure for flood and other water-related events. Recent Australian legislative attempts to overcome insureds’ confusion of water related definitions are examined for this purpose. The authors conclude that Australian and other) legislators should set a maximum premium for a minimum amount of flood and sea related cover; and restrict the building and style of homes in flood prone areas.

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This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

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Alignment-free methods, in which shared properties of sub-sequences (e.g. identity or match length) are extracted and used to compute a distance matrix, have recently been explored for phylogenetic inference. However, the scalability and robustness of these methods to key evolutionary processes remain to be investigated. Here, using simulated sequence sets of various sizes in both nucleotides and amino acids, we systematically assess the accuracy of phylogenetic inference using an alignment-free approach, based on D2 statistics, under different evolutionary scenarios. We find that compared to a multiple sequence alignment approach, D2 methods are more robust against among-site rate heterogeneity, compositional biases, genetic rearrangements and insertions/deletions, but are more sensitive to recent sequence divergence and sequence truncation. Across diverse empirical datasets, the alignment-free methods perform well for sequences sharing low divergence, at greater computation speed. Our findings provide strong evidence for the scalability and the potential use of alignment-free methods in large-scale phylogenomics.

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Lake Purrumbete maar is located in the intraplate, monogenetic Newer Volcanics Province in southeastern Australia. The extremely large crater of 3000. m in diameter formed on an intersection of two fault lines and comprises at least three coalesced vents. The evolution of these vents is controlled by the interaction of the tectonic setting and the properties of both hard and soft rock aquifers. Lithics in the maar deposits originate from country rock formations less than 300. m deep, indicating that the large size of the crater cannot only be the result of the downwards migration of the explosion foci in a single vent. Vertical crater walls and primary inward dipping beds evidence that the original size of the crater has been largely preserved. Detailed mapping of the facies distributions, the direction of transport of base surges and pyroclastic flows, and the distribution of ballistic block fields, form the basis for the reconstruction of the complex eruption history,which is characterised by alternations of the eruption style between relatively dry and wet phreatomagmatic conditions, and migration of the vent location along tectonic structures. Three temporally separated eruption phases are recognised, each starting at the same crater located directly at the intersection of two local fault lines. Activity then moved quickly to different locations. A significant volcanic hiatus between two of the three phases shows that the magmatic system was reactivated. The enlargement of especially the main crater by both lateral and vertical growth led to the interception of the individual craters and the formation of the large circular crater. Lake Purrumbete maar is an excellent example of how complicated the evolution of large, seemingly simple, circular maar volcanoes can be, and raises the question if these systems are actually monogenetic.

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Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

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Purpose: Physical activity improves the health outcomes of colorectal cancer (CRC) survivors, yet few are exercising at levels known to yield health benefits. Baseline demographic, clinical, behavioral, and psychosocial predictors of physical activity at 12 months were investigated in CRC survivors. Methods: Participants were CRC survivors (n = 410) who completed a 12-month multiple health behavior change intervention trial (CanChange). The outcome variable was 12 month sufficient physical activity (≥150 min of moderate–vigorous physical activity/week). Baseline predictors included demographics and clinical variables, health behaviors, and psychosocial variables. Results: Multivariate linear regression revealed that baseline sufficient physical activity (p < 0.001), unemployment (p = 0.004), private health insurance (p = 0.040), higher cancer-specific quality of life (p = 0.031) and higher post-traumatic growth (p = 0.008) were independent predictors of sufficient physical activity at 12 months. The model explained 28.6 % of the variance. Conclusions: Assessment of demographics, health behaviors, and psychosocial functioning following a diagnosis of CRC may help to develop effective physical activity programs.

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This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.