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Novel Statistical Methodology for Diagnostic/Prognostic and Therapeutic Studies and Systematic Reviews (MEDIASRES)
Start date: Jan 1, 2012, End date: Dec 31, 2015 PROJECT  FINISHED 

"Novel statistical methodology promises to greatly facilitate development of approaches for personalised medicine. While state-of-the-art statistical techniques have already advanced clinical trials and diagnostic/prognostic studies as the major source of evidence in clinical medicine, increasing availability of molecular techniques holds an even greater promise. However, for leveraging such information for individualised diagnosis/prognosis, and treatment, the corresponding complex structures have to be adequately modelled and results have to be aggregated by corresponding advanced meta-analytic approaches. The main goal of the project is to establish a joint research-training programme by an interdisciplinary and intersectorial network for providing early-stage researchers with deep insight into cutting-edge statistical methodology. The research area of statistical methodology for diagnostic/prognostic and therapeutic studies and systematic reviews is well suited for early-stage training purposes, as it comprises a wide range of theoretical and applied biostatistical tools that need to be mastered, further developed, and translated into clinical research and practice. Europe-wide exchanges will also be ensured to meet the need for mobility in today’s globalised society. Further career relevant knowledge and skills will be provided through a structured design of education. The early-stage researchers will be trained according to an individually supervised, comprehensive and complementary programme. The structure of these activities is based on the training-through-research approach of the network. The collaboration of leading biostatistical experts will stimulate the discovery of promising statistical methodology useful for the design and analysis of clinical research. The integration of full industry partners and clinical advisors in the network enables optimal conditions for research driven by application, which will ensure tangible benefits of the programme."
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