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Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets.

ABSTRACT: Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, performing further analyses on existing research data to generate new hypotheses or developing computational models to support medical decisions (e.g. risk/benefit analysis of treatment options) represent just a fraction of the potential benefits of medical data-pooling. Distributed machine learning and knowledge exchange from federated databases can be considered as one beyond other attractive approaches for knowledge generation within "Big Data". Data interoperability between research institutions should be the major concern behind a wider collaboration. Information captured in electronic patient records (EPRs) and study case report forms (eCRFs), linked together with medical imaging and treatment planning data, are deemed to be fundamental elements for large multi-centre studies in the field of radiation therapy and oncology. To fully utilise the captured medical information, the study data have to be more than just an electronic version of a traditional (un-modifiable) paper CRF. Challenges that have to be addressed are data interoperability, utilisation of standards, data quality and privacy concerns, data ownership, rights to publish, data pooling architecture and storage. This paper discusses a framework for conceptual packages of ideas focused on a strategic development for international research data exchange in the field of radiation therapy and oncology.

SUBMITTER: Skripcak T

PROVIDER: S-EPMC4648243 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets.

Skripcak Tomas T Belka Claus C Bosch Walter W Brink Carsten C Brunner Thomas T Budach Volker V Büttner Daniel D Debus Jürgen J Dekker Andre A Grau Cai C Gulliford Sarah S Hurkmans Coen C Just Uwe U Krause Mechthild M Lambin Philippe P Langendijk Johannes A JA Lewensohn Rolf R Lühr Armin A Maingon Philippe P Masucci Michele M Niyazi Maximilian M Poortmans Philip P Simon Monique M Schmidberger Heinz H Spezi Emiliano E Stuschke Martin M Valentini Vincenzo V Verheij Marcel M Whitfield Gillian G Zackrisson Björn B Zips Daniel D Baumann Michael M

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 20141028 3

Disconnected cancer research data management and lack of information exchange about planned and ongoing research are complicating the utilisation of internationally collected medical information for improving cancer patient care. Rapidly collecting/pooling data can accelerate translational research in radiation therapy and oncology. The exchange of study data is one of the fundamental principles behind data aggregation and data mining. The possibilities of reproducing the original study results, ...[more]

PMID: 25458128

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Project description:IntroductionThere is a lack of evidence on the adverse effects of air pollution on cognition for people with air quality-related health conditions. We propose that educational attainment, as a proxy for cognition, may increase with improved air quality. This study will explore whether asthma and seasonal allergic rhinitis, when exacerbated by acute exposure to air pollution, is associated with educational attainment.ObjectiveTo describe the preparation of individual and household-level linked environmental and health data for analysis within an anonymised safe haven. Also to introduce our statistical analysis plan for our study: COgnition, Respiratory Tract illness and Effects of eXposure (CORTEX).MethodsWe imported daily air pollution and aeroallergen data, and individual level education data into the SAIL databank, an anonymised safe haven for person-based records. We linked individual-level education, socioeconomic and health data to air quality data for home and school locations, creating tailored exposures for individuals across a city. We developed daily exposure data for all pupils in repeated cross sectional exam cohorts (2009-2015).ConclusionWe have used the SAIL databank, an innovative, data safe haven to create individual-level exposures to air pollution and pollen for multiple daily home and school locations. The analysis platform will allow us to evaluate retrospectively the impact of air quality on attainment for multiple cross-sectional cohorts of pupils. Our methods will allow us to distinguish between the pollution impacts on educational attainment for pupils with and without respiratory health conditions. The results from this study will further our understanding of the effects of air quality and respiratory-related health conditions on cognition.HighlightsThis city-wide study includes longitudinal routinely-recorded educational attainment data for all pupils taking exams over seven years;High spatial resolution air pollution data were linked within a privacy protected databank to obtain individual exposure at multiple daily locations;This study will use health data linked at the individual level to explore associations between air pollution, related morbidity, and educational attainment.

Project description:We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from âAAAâ to âDDDâ) to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBA (www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label âChIP-seq gradeâ. The NGS-QC team has setup a certification procedure for Antibodies dedicated to ChIP-seq applications based on (1)a highly reproducible pipeline for performing ChIP-seq assays including the use of an automated liquid handling platform (TECAN EVO75) for ChIP and sequencing library preparation steps and (2) the use of the NGS-QC Generator tool for providing a ChIP-seq quality grade and to evaluate other parameters like the Optimal sequencing depth, the degree of reproducibility among biological replicates and the comparison of the quality grades of the certified antibody with datasets retrieved in the public domain. This quality certification structure makes possible to assign a measured Quality Stamp to ChIP-seq grade Antibodies.

Dataset Information

Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets.

Publications

Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets.

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