Cohort profile: The Swiss Transplant Cohort Study (STCS): A nationwide longitudinal cohort study of all solid organ recipients in Switzerland.

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15 décembre 2021

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info:eu-repo/semantics/altIdentifier/doi/10.1136/bmjopen-2021-051176

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info:eu-repo/semantics/altIdentifier/pmid/34911712

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info:eu-repo/semantics/altIdentifier/eissn/2044-6055

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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_83070D3378752

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info:eu-repo/semantics/openAccess , CC BY-NC 4.0 , https://creativecommons.org/licenses/by-nc/4.0/




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S. Stampf et al., « Cohort profile: The Swiss Transplant Cohort Study (STCS): A nationwide longitudinal cohort study of all solid organ recipients in Switzerland. », Serveur académique Lausannois, ID : 10.1136/bmjopen-2021-051176


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The Swiss Transplant Cohort Study (STCS) is a prospective multicentre cohort study which started to actively enrol study participants in May 2008. It takes advantage of combining data from all transplant programmes in one unique system to perform comprehensive nationwide reporting and to promote translational and clinical post-transplant outcome research in the framework of Swiss transplantation medicine. Over 5500 solid organ transplant recipients have been enrolled in all six Swiss transplant centres by end of 2019, around three-quarter of them for kidney and liver transplants. Ninety-three per cent of all transplanted recipients have consented to study participation, almost all of them (99%) contributed to bio-sampling. The STCS genomic data set includes around 3000 patients. Detailed clinical and laboratory data in high granularity as well as patient-reported outcomes from transplant recipients and activities in Switzerland are available in the last decade. Interdisciplinary contributions in diverse fields of transplantation medicine such as infectious diseases, genomics, oncology, immunology and psychosocial science have resulted in approximately 70 scientific papers getting published in peer-review journals so far. The STCS will deepen its efforts in personalised medicine and digital epidemiology, and will also focus on allocation research and the use of causal inference methods to make complex matters in transplant medicine more understandable and transparent.

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