Dataset Information

Taiwan Biobank: making cross-database convergence possible in the Big Data era.

ABSTRACT: The Taiwan Biobank (TWB) is a biomedical research database of biopsy data from 200 000 participants. Access to this database has been granted to research communities taking part in the development of precision medicines; however, this has raised issues surrounding TWB's access to electronic medical records (EMRs). The Personal Data Protection Act of Taiwan restricts access to EMRs for purposes not covered by patients' original consent. This commentary explores possible legal solutions to help ensure that the access TWB has to EMR abides with legal obligations, and with governance frameworks associated with ethical, legal, and social implications. We suggest utilizing "hash function" algorithms to create nonretrospective, anonymized data for the purpose of cross-transmission and/or linkage with EMR.

SUBMITTER: Lin JC

PROVIDER: S-EPMC5774504 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Taiwan Biobank: making cross-database convergence possible in the Big Data era.

Lin Jui-Chu JC Fan Chien-Te CT Liao Chia-Cheng CC Chen Yao-Sheng YS

GigaScience 20180101 1

The Taiwan Biobank (TWB) is a biomedical research database of biopsy data from 200 000 participants. Access to this database has been granted to research communities taking part in the development of precision medicines; however, this has raised issues surrounding TWB's access to electronic medical records (EMRs). The Personal Data Protection Act of Taiwan restricts access to EMRs for purposes not covered by patients' original consent. This commentary explores possible legal solutions to help en ...[more]

PMID: 29149267

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Project description:BackgroundTo drive translational medicine, modern day biobanks need to integrate with other sources of data (clinical, genomics) to support novel data-intensive research. Currently, vast amounts of research and clinical data remain in silos, held and managed by individual researchers, operating under different standards and governance structures; a framework that impedes sharing and effective use of data. In this article, we describe the journey of British Columbia's Gynecological Cancer Research Program (OVCARE) in moving a traditional tumour biobank, outcomes unit, and a collection of data silos, into an integrated data commons to support data standardization and resource sharing under collaborative governance, as a means of providing the gynecologic cancer research community in British Columbia access to tissue samples and associated clinical and molecular data from thousands of patients.ResultsThrough several engagements with stakeholders from various research institutions within our research community, we identified priorities and assessed infrastructure needs required to optimize and support data collections, storage and sharing, under three main research domains: (1) biospecimen collections, (2) molecular and genomics data, and (3) clinical data. We further built a governance model and a resource portal to implement protocols and standard operating procedures for seamless collections, management and governance of interoperable data, making genomic, and clinical data available to the broader research community.ConclusionsProper infrastructures for data collection, sharing and governance is a translational research imperative. We have consolidated our data holdings into a data commons, along with standardized operating procedures to meet research and ethics requirements of the gynecologic cancer community in British Columbia. The developed infrastructure brings together, diverse data, computing frameworks, as well as tools and applications for managing, analyzing, and sharing data. Our data commons bridges data access gaps and barriers to precision medicine and approaches for diagnostics, treatment and prevention of gynecological cancers, by providing access to large datasets required for data-intensive science.

Project description:BackgroundOsteoporosis, obesity, and fatty liver are increasingly common chronic diseases that seriously threaten people's health. Low-dose chest computed tomography (LDCT) scan is frequently used for lung cancer screening in health screenings and checkups. Quantitative computed tomography (QCT) enables the accurate measurement of volumetric bone mineral density (vBMD), liver fat content, and abdominal fat area using the existing LDCT data without extra radiation. We initiated a new project, the China Health Big Data (China Biobank), which combines the LDCT scan images from lung cancer screening of participants in health checkup with QCT to investigate the added value of QCT to LDCT, in order to establish the normative reference database and diagnosis criteria for the three aforementioned conditions.MethodsThe China Biobank project is a prospective nationwide multicenter cohort study that will combine QCT technology with LDCT scans to measure bone mineral density (BMD), intra-abdominal fat distribution, and liver fat content of the generally healthy checkup participants. Mindways QCT calibration phantom (Mindways Software Inc., Austin, TX, USA) and analysis software QCT PRO v6.0 will be used for all centers. Before data collection begins, the European Spine Phantom (ESP) will be used for quality control analysis at each collaborating center. The inclusion criteria are a healthy checkup participant aged 30-90 years, with LDCT as a part of his/her health checkup protocol. Exclusion criteria are pregnant women or participants with a metal implant in the CT scan area. The LDCT images will be transferred to the Mindways workstation for analysis, and vBMD in the L1 and L2 vertebrae, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and liver fat content will be measured. As part of the health checkup, the demographic, anthropometric parameters, blood pressure, and a routine blood laboratory test will be collected. The estimated sample size will be about 30,000.ResultsThe combination of QCT with LDCT of the chest was validated in this project. The vBMD of spine, visceral fat and liver fat can be measured with a LDCT chest scan.ConclusionsThe China Biobank project will assess the added value of QCT to LDCT, and enable accurate evaluation of the prevalence of osteoporosis, obesity, and fatty liver disease in a very large Chinese cohort.

Dataset Information

Taiwan Biobank: making cross-database convergence possible in the Big Data era.

Publications

Taiwan Biobank: making cross-database convergence possible in the Big Data era.

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