Background: This phase III study investigated the addition of aflibercept to gemcitabine, in patients with advanced pancreatic cancer. Patients and methods: Patients with metastatic pancreatic cancer were randomly ass...
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Background: This phase III study investigated the addition of aflibercept to gemcitabine, in patients with advanced pancreatic cancer. Patients and methods: Patients with metastatic pancreatic cancer were randomly assigned to receive either intravenous (i.v.) aflibercept, 4 mg/kg every 2 weeks, or matching placebo combined with gemcitabine, 1000 mg/m(2) i.v. weekly for 7 weeks out of 8, then weekly for 3 weeks out of 4 until progressive disease, unacceptable toxicity or withdrawal of consent. The primary objective was to demonstrate an improvement in overall survival (OS) between the treatment arms. results: The study was stopped for futility following a planned interim analysis of OS in 427 randomised patients. With a median follow-up of 7.9 months, based on the 546 patients at study termination, median OS was 7.8 months in the gemcitabine plus placebo arm (n = 275) versus 6.5 months in the gemcitabine plus aflibercept arm (n = 271), which was not significant (hazardratio 1.165, 95% confidence interval (CI) 0.921-1.473, p = 0.2034). Median progression-free survival was 3.7 months in both arms. Treatment discontinuations due to adverse events were more frequent in the aflibercept than in the placebo-containing arm (23% versus 12%). Conclusion: Adding aflibercept to gemcitabine did not improve OS in patients with metastatic pancreatic cancer. (C) 2013 Elsevier Ltd. All rights reserved.
Aims/hypothesis The dIrECT (diabetes research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic...
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Aims/hypothesis The dIrECT (diabetes research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset;(2) predict the response to diabetes therapies;and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paperdescribes two new prospective cohort studies conducted as part of dIrECT. Methods Prediabetic participants (target sample size 2,200-2,700) and patients with newly diagnosed type 2 diabetes (target sample size similar to 1,000) are undergoing detailed metabolic phenotyping at baseline and 18 months and 36 months later. Abdominal, pancreatic and liver fat is assessed using MrI. Insulin secretion and action are assessed using frequently sampled OGTTs in non-diabetic participants, and frequently sampled mixed-meal tolerance tests in patients with type 2 diabetes. Biosamples include venous blood, faeces, urine and nail clippings, which, among other biochemical analyses, will be characterised at genetic, transcriptomic, metabolomic, proteomic and metagenomic levels. Lifestyle is assessed using high-resolution triaxial accelerometry, 24 h diet record, and food habit questionnaires. Conclusinos/interpretation dIrECT will yield an unprecedented array of biomaterials anddata. This resource, available through managed access to scientists within and outside the Consortium, will facilitate the development of new treatments and therapeutic strategies for the prevention and management of type 2 diabetes.
Background Classical monitoring approaches rely on extensive on-site visits and source data verification. These activities are associated with high cost and a limited contribution to data quality. Central statistical ...
Background Classical monitoring approaches rely on extensive on-site visits and source data verification. These activities are associated with high cost and a limited contribution to data quality. Central statistical monitoring is of particular interest to address these shortcomings. Purpose This article outlines the principles of central statistical monitoring and the challenges of implementing it in actual trials. Methods A statistical approach to central monitoring is based on a large number of statistical tests performed on all variables collected in the database, in order to identify centers that differ from the others. The tests generate a high-dimensional matrix of p-values, which can be analyzed by statistical methods and bioinformatic tools to identify extreme centers. results results from actual trials are provided to illustrate typical findings that can be expected from a central statistical monitoring approach, which detects abnormal patterns that were not (or could not have been) detected by on-site monitoring. Limitations Central statistical monitoring can only address problems present in the data. Important aspects of trial conduct such as a lack of informed consent documentation, for instance, require other approaches. The results provided here are empirical examples from a limited number of studies. Conclusion Central statistical monitoring can both optimize on-site monitoring and improve data quality and as such provides a cost-effective way of meeting regulatory requirements for clinical trials. Clinical Trials 2012;9: 705-713. http://***
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