Jens Neudecker1, Solveig Tenckhoff2, André L Mihaljevic3. 1. Klinik für Allgemein-, Viszeral-, Gefäß- und Thoraxchirurgie, Universitätsmedizin Berlin, Charité Campus Mitte, Berlin, Deutschland. Electronic address: Jens.Neudecker@charite.de. 2. Studienzentrum der Deutschen Gesellschaft für Chirurgie, Koordinierungszentrale CHIR-Net, Heidelberg, Deutschland. 3. Klinik für Allgemein-, Viszeral- und Transplantationschirurgie, Universitätsklinikum Heidelberg, Heidelberg, Deutschland.
Abstract
BACKGROUND: Patient-oriented clinical research in surgery requires prospective randomised multicentre trials (mRCTs) to generate valid evidence. In order to conduct high quality mRCTs, a network of surgical clinical trial centres is necessary. METHODS: The Surgical Trial Network (CHIR-Net), which is funded by the German Federal Ministry of Education and Research (BMBF), was established as a structure of surgical regional centres. Currently, the CHIR-Net comprises 12 regional surgical centres with their associated clinical partner hospitals. The major aim of this network is to generate patient-relevant surgical questions of high clinical impact and to answer these questions in high-quality prospective randomised multicentre trials with well-trained study personnel. RESULTS: Since 2006 32 mRCTs have been initiated in the CHIR-Net. Twelve surgical regional centres - in cooperation with 333 German and European hospitals - have recruited more than 7,500 patients. More than 80 surgeons have successfully completed the CHIR-Net educational curriculum for young surgeons. CONCLUSIONS: The CHIR-Net has successfully established a national clinical trial network to investigate surgical questions in randomised multicentre clinical trials. A nationwide research infrastructure, including university and non-university hospitals as well as the associated clinical coordination centres (KKS), was created to ensure patient-oriented surgical clinical research in a network at the highest methodological level thus implementing evidence-based medicine in daily surgical practice.
BACKGROUND:Patient-oriented clinical research in surgery requires prospective randomised multicentre trials (mRCTs) to generate valid evidence. In order to conduct high quality mRCTs, a network of surgical clinical trial centres is necessary. METHODS: The Surgical Trial Network (CHIR-Net), which is funded by the German Federal Ministry of Education and Research (BMBF), was established as a structure of surgical regional centres. Currently, the CHIR-Net comprises 12 regional surgical centres with their associated clinical partner hospitals. The major aim of this network is to generate patient-relevant surgical questions of high clinical impact and to answer these questions in high-quality prospective randomised multicentre trials with well-trained study personnel. RESULTS: Since 2006 32 mRCTs have been initiated in the CHIR-Net. Twelve surgical regional centres - in cooperation with 333 German and European hospitals - have recruited more than 7,500 patients. More than 80 surgeons have successfully completed the CHIR-Net educational curriculum for young surgeons. CONCLUSIONS: The CHIR-Net has successfully established a national clinical trial network to investigate surgical questions in randomised multicentre clinical trials. A nationwide research infrastructure, including university and non-university hospitals as well as the associated clinical coordination centres (KKS), was created to ensure patient-oriented surgical clinical research in a network at the highest methodological level thus implementing evidence-based medicine in daily surgical practice.
Authors: Pia-Elena Frey; Mirco Friedrich; Lukas Rädeker; Christoph A Fink; Alexander Leuck; Solveig Tenckhoff; Jens Neudecker; André L Mihaljevic Journal: Innov Surg Sci Date: 2017-11-27
Authors: Christoph A Fink; Mirco Friedrich; Pia-Elena Frey; Lukas Rädeker; Alexander Leuck; Thomas Bruckner; Manuel Feisst; Solveig Tenckhoff; Christina Klose; Colette Dörr-Harim; Jens Neudecker; André L Mihaljevic Journal: BMC Surg Date: 2018-10-29 Impact factor: 2.102