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Sidorenkov, Grigory; Nagel, Janny; Meijer, Coby; Duker, Jacko J; Groen, Harry J M; Halmos, Gyorgy B; Oonk, Maaike H M; Oostergo, Rene J; van der Vegt, Bert; Witjes, Max J H; Nijland, Marcel; Havenga, Klaas; Maduro, John H; Gietema, Jourik A; de Bock, Gertruida H
Journal of translational medicine, 11/2019, Letnik: 17, Številka: 1Journal Article
Understanding cancer heterogeneity, its temporal evolution over time, and the outcomes of guided treatment depend on accurate data collection in a context of routine clinical care. We have developed a hospital-based data-biobank for oncology, entitled OncoLifeS (Oncological Life Study: Living well as a cancer survivor), that links routine clinical data with preserved biological specimens and quality of life assessments. The aim of this study is to describe the organization and development of a data-biobank for cancer research. We have enrolled 3704 patients aged ≥ 18 years diagnosed with cancer, of which 45 with hereditary breast-ovarian cancer (70% participation rate) as of October 24th, 2019. The average age is 63.6 ± 14.2 years and 1892 (51.1%) are female. The following data are collected: clinical and treatment details, comorbidities, lifestyle, radiological and pathological findings, and long-term outcomes. We also collect and store various biomaterials of patients as well as information from quality of life assessments. Embedding a data-biobank in clinical care can ensure the collection of high-quality data. Moreover, the inclusion of longitudinal quality of life data allows us to incorporate patients' perspectives and inclusion of imaging data provides an opportunity for analyzing raw imaging data using artificial intelligence (AI) methods, thus adding new dimensions to the collected data.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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