Dataset Information

This DAC is to control access to data contained within dataset EGAS00001001147, for Myeloma XI clinical trial patients.

ABSTRACT: Data Access Committee EGAC00001000307

PROVIDER: EGAC00001000307 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Publications

APOBEC family mutational signatures are associated with poor prognosis translocations in multiple myeloma.

Walker Brian A BA Wardell Christopher P CP Murison Alex A Boyle Eileen M EM Begum Dil B DB Dahir Nasrin M NM Proszek Paula Z PZ Melchor Lorenzo L Pawlyn Charlotte C Kaiser Martin F MF Johnson David C DC Qiang Ya-Wei YW Jones John R JR Cairns David A DA Gregory Walter M WM Owen Roger G RG Cook Gordon G Drayson Mark T MT Jackson Graham H GH Davies Faith E FE Morgan Gareth J GJ

Nature communications 20150423

We have sequenced 463 presenting cases of myeloma entered into the UK Myeloma XI study using whole exome sequencing. Here we identify mutations induced as a consequence of misdirected AID in the partner oncogenes of IGH translocations, which are activating and associated with impaired clinical outcome. An APOBEC mutational signature is seen in 3.8% of cases and is linked to the translocation-mediated deregulation of MAF and MAFB, a known poor prognostic factor. Patients with this signature have ...[more]

PMID: 25904160

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Project description:BACKGROUND:Population surveillance sites generate many datasets relevant to disease surveillance. However, there is a risk that these data are underutilized because of the volumes of data gathered and the lack of means to quickly disseminate analysis. Data visualization offers a means to quickly disseminate, understand, and interpret datasets, facilitating evidence-driven decision making through increased access to information. OBJECTIVES:This paper describes the development and evaluation of a framework for data dashboard design, to visualize datasets produced at a demographic health surveillance site. The aim of this research was to produce a comprehensive, reusable, and scalable dashboard design framework to fit the unique requirements of the context. METHODS:The framework was developed and implemented at a demographic surveillance platform at the Africa Health Research Institute, in KwaZulu-Natal, South Africa. This context represents an exemplar implementation for the use of data dashboards within a population health-monitoring setting. Before the full launch, an evaluation study was undertaken to assess the effectiveness of the dashboard framework as a data communication and decision-making tool. The evaluation included a quantitative task evaluation to assess usability and a qualitative questionnaire exploring the attitudes to the use of dashboards. RESULTS:The evaluation participants were drawn from a diverse group of users working at the site (n=20), comprising of community members, nurses, scientific and operational staff. Evaluation demonstrated high usability for the dashboard across user groups, with scientific and operational staff having minimal issues in completing tasks. There were notable differences in the efficiency of task completion among user groups, indicating varying familiarity with data visualization. The majority of users felt that the dashboards provided a clear understanding of the datasets presented and had a positive attitude to their increased use. CONCLUSIONS:Overall, this exploratory study indicates the viability of the data dashboard framework in communicating data trends within population surveillance setting. The usability differences among the user groups discovered during the evaluation demonstrate the need for the user-led design of dashboards in this context, addressing heterogeneous computer and visualization literacy present among the diverse potential users present in such settings. The questionnaire highlighted the enthusiasm for increased access to datasets from all stakeholders highlighting the potential of dashboards in this context.

Dataset Information

This DAC is to control access to data contained within dataset EGAS00001001147, for Myeloma XI clinical trial patients.

Publications

APOBEC family mutational signatures are associated with poor prognosis translocations in multiple myeloma.

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