The ECOUTER methodology for stakeholder engagement in translational research.

BACKGROUND: Because no single person or group holds knowledge about all aspects of research, mechanisms are needed to support knowledge exchange and engagement. Expertise in the research setting necessarily includes scientific and methodological expertise, but also expertise gained through the experience of participating in research and/or being a recipient of research outcomes (as a patient or member of the public). Engagement is, by its nature, reciprocal and relational: the process of engaging research participants, patients, citizens and others (the many 'publics' of engagement) brings them closer to the research but also brings the research closer to them. When translating research into practice, engaging the public and other stakeholders is explicitly intended to make the outcomes of translation relevant to its constituency of users. METHODS: In practice, engagement faces numerous challenges and is often time-consuming, expensive and 'thorny' work. We explore the epistemic and ontological considerations and implications of four common critiques of engagement methodologies that contest: representativeness, communication and articulation, impacts and outcome, and democracy. The ECOUTER (Employing COnceptUal schema for policy and Translation Engagement in Research) methodology addresses problems of representation and epistemic foundationalism using a methodology that asks, "How could it be otherwise?" ECOUTER affords the possibility of engagement where spatial and temporal constraints are present, relying on saturation as a method of 'keeping open' the possible considerations that might emerge and including reflexive use of qualitative analytic methods. RESULTS: This paper describes the ECOUTER process, focusing on one worked example and detailing lessons learned from four other pilots. ECOUTER uses mind-mapping techniques to 'open up' engagement, iteratively and organically. ECOUTER aims to balance the breadth, accessibility and user-determination of the scope of engagement. An ECOUTER exercise comprises four stages: (1) engagement and knowledge exchange; (2) analysis of mindmap contributions; (3) development of a conceptual schema (i.e. a map of concepts and their relationship); and (4) feedback, refinement and development of recommendations. CONCLUSION: ECOUTER refuses fixed truths but also refuses a fixed nature. Its promise lies in its flexibility, adaptability and openness. ECOUTER will be formed and re-formed by the needs and creativity of those who use it.

PPAR agonists stimulate adipogenesis at the expense of osteoblast differentiation while inhibiting osteoclast formation and activity.

Drugs used in the treatment of type 2 diabetes and cardiovascular disease, specifically peroxisome proliferator-activated receptor (PPAR) agonists, have been reported to affect bone cell function and fracture risk. In this study, we assessed the direct effects of PPAR-γ agonists (rosiglitazone and troglitazone), used in the treatment of diabetes, and a PPAR-α agonist (fenofibrate), used to treat hyperlipidaemia, on the function of primary osteoblasts and osteoclasts. Formation of 'trabecular' bone structures by rat calvarial osteoblasts was reduced by up to 85% in cultures treated with rosiglitazone and by 45% in troglitazone-treated or fenofibrate-treated cultures; at the same time, lipid droplet formation was increased by 40-70%. The expression of key osteogenic markers was similarly downregulated in cultures treated with PPAR agonists, whereas adipogenesis markers were upregulated. Formation of osteoclasts in cultures derived from mouse marrow diminished with fenofibrate treatment, whereas both glitazones reduced resorptive activity without affecting osteoclast number. Metformin, although not a PPAR agonist, is also commonly used in the treatment of type 2 diabetes. Here, metformin was found to have no effect on bone cell function. Taken together, these data suggest that PPAR-γ agonists may enhance bone loss via increased adipogenesis at the expense of osteoblast formation. In contrast, PPAR-α agonists may prevent bone loss. Given that the prevalence of diabetes and cardiovascular disease is expected to rise significantly, greater attention may need to be paid to the effects of PPAR agonists on bone homeostasis.

Privacy preserving data visualizations.

Data visualizations are a valuable tool used during both statistical analysis and the interpretation of results as they graphically reveal useful information about the structure, properties and relationships between variables, which may otherwise be concealed in tabulated data. In disciplines like medicine and the social sciences, where collected data include sensitive information about study participants, the sharing and publication of individual-level records is controlled by data protection laws and ethico-legal norms. Thus, as data visualizations - such as graphs and plots - may be linked to other released information and used to identify study participants and their personal attributes, their creation is often prohibited by the terms of data use. These restrictions are enforced to reduce the risk of breaching data subject confidentiality, however they limit analysts from displaying useful descriptive plots for their research features and findings. Here we propose the use of anonymization techniques to generate privacy-preserving visualizations that retain the statistical properties of the underlying data while still adhering to strict data disclosure rules. We demonstrate the use of (i) the well-known k-anonymization process which preserves privacy by reducing the granularity of the data using suppression and generalization, (ii) a novel deterministic approach that replaces individual-level observations with the centroids of each k nearest neighbours, and (iii) a probabilistic procedure that perturbs individual attributes with the addition of random stochastic noise. We apply the proposed methods to generate privacy-preserving data visualizations for exploratory data analysis and inferential regression plot diagnostics, and we discuss their strengths and limitations.

Recognizing, reporting and reducing the data curation debt of cohort studies.

Good data curation is integral to cohort studies, but it is not always done to a level necessary to ensure the longevity of the data a study holds. In this opinion paper, we introduce the concept of data curation debt-the data curation equivalent to the software engineering principle of technical debt. Using the context of UK cohort studies, we define data curation debt-describing examples and their potential impact. We highlight that accruing this debt can make it more difficult to use the data in the future. Additionally, the long-running nature of cohort studies means that interest is accrued on this debt and compounded over time-increasing the impact a debt could have on a study and its stakeholders. Primary causes of data curation debt are discussed across three categories: longevity of hardware, software and data formats; funding; and skills shortages. Based on cross-domain best practice, strategies to reduce the debt and preventive measures are proposed-with importance given to the recognition and transparent reporting of data curation debt. Describing the debt in this way, we encapsulate a multi-faceted issue in simple terms understandable by all cohort study stakeholders. Data curation debt is not only confined to the UK, but is an issue the international community must be aware of and address. This paper aims to stimulate a discussion between cohort studies and their stakeholders on how to address the issue of data curation debt. If data curation debt is left unchecked it could become impossible to use highly valued cohort study data, and ultimately represents an existential risk to studies themselves.

PUblications Metadata Augmentation (PUMA) pipeline.

Cohort studies collect, generate and distribute data over long periods of time - often over the lifecourse of their participants. It is common for these studies to host a list of publications (which can number many thousands) on their website to demonstrate the impact of the study and facilitate the search of existing research to which the study data has contributed. The ability to search and explore these publication lists varies greatly between studies. We believe a lack of rich search and exploration functionality of study publications is a barrier to entry for new or prospective users of a study's data, since it may be difficult to find and evaluate previous work in a given area. These lists of publications are also typically manually curated, resulting in a lack of rich metadata to analyse, making bibliometric analysis difficult. We present here a software pipeline that aggregates metadata from a variety of third-party providers to power a web based search and exploration tool for lists of publications. Alongside core publication metadata (i.e. author lists, keywords etc.), we include geocoding of first authors and citation counts in our pipeline. This allows a characterisation of a study as a whole based on common locations of authors, frequency of keywords, citation profile etc. This enriched publications metadata can be useful for generating study impact metrics and web-based graphics for public dissemination. In addition, the pipeline produces a research data set for bibliometric analysis or social studies of science. We use a previously published list of publications from a cohort study as an exemplar input data set to show the output and utility of the pipeline here.

Automation of cleaning and reconstructing residential address histories to assign environmental exposures in longitudinal studies.

BACKGROUND: We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposures to cohort participants. The first application of this algorithm was to construct prenatal and early life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC) in the South West of England, using previously estimated particulate matter ≤10 µm (PM10) concentrations. METHODS: ALSPAC recruited 14 541 pregnant women between 1991 and 1992. We assigned trimester-specific estimated PM10 exposures for 12 752 pregnancies, and first year of life exposures for 12 525 births, based on maternal residence and residential mobility. RESULTS: Average PM10 exposure was 32.6 µg/m3 [standard deviation (S.D.) 3.0 µg/m3] during pregnancy and 31.4 µg/m3 (S.D. 2.6 µg/m3) during the first year of life; 6.7% of women changed address during pregnancy, and 18.0% moved during first year of life of their infant. Exposure differences ranged from -5.3 µg/m3 to 12.4 µg/m3 (up to 26% difference) during pregnancy and -7.22 µg/m3 to 7.64 µg/m3 (up to 27% difference) in the first year of life, when comparing estimated exposure using the address at birth and that assessed using the complete cleaned address history. For the majority of individuals exposure changed by <5%, but some relatively large changes were seen both in pregnancy and in infancy. CONCLUSIONS: ALGAE provides a generic and adaptable, open-source solution to clean addresses stored in a cohort contact database and assign life stage-specific exposure estimates with the potential to reduce exposure misclassification.

Targeting Vascular Endothelial Growth Factor in Oesophagogastric Cancer: A Review of Progress to Date and Immunotherapy Combination Strategies.

In 2014, the survival benefits seen in REGARD and RAINBOW studies led the way for the regulatory approval of ramucirumab in the second line setting in oesophagogastric (OG) cancer. Trials of other drugs targeting the vascular endothelial growth factor (VEGF) pathway have met with mixed results but this remains an important pathway for evaluation in OG cancer. Perhaps the most interesting ongoing trials are those which target VEGF in combination with immunotherapy, which have a sound scientific rationale. Given the emerging role of immunotherapy in OG cancer, this is an important area of innovation. This review aims to outline targeting VEGF in OG cancer, the rationale behind the continued interest in this mechanism and possible future directions in combination with immunotherapy.

Generation of a cleaned dataset listing Avon Longitudinal Study of Parents And Children peer-reviewed publications to 2015.

Birth cohort studies generate huge amounts of data, and as a consequence are a source of many peer reviewed publications. We have taken the list of publications from the Avon Longitudinal Study of Parents and Children UK birth cohort, filtered, de-duplicated and cleaned it to generate a bibliographic research data set. This dataset could be used for accurate reporting and monitoring of the impact of the study as well as bibliometric research.

Digital Methodology to implement the ECOUTER engagement process.

ECOUTER ( Employing COncept ual schema for policy and Translation E in Research - French for 'to listen' - is a new stakeholder engagement method incorporating existing evidence to help participants draw upon their own knowledge of cognate issues and interact on a topic of shared concern. The results of an ECOUTER can form the basis of recommendations for research, governance, practice and/or policy. This paper describes the development of a digital methodology for the ECOUTER engagement process based on currently available mind mapping freeware software. The implementation of an ECOUTER process tailored to applications within health studies are outlined for both online and face-to-face scenarios. Limitations of the present digital methodology are discussed, highlighting the requirement of a purpose built software for ECOUTER research purposes.

DataSHIELD: taking the analysis to the data, not the data to the analysis.

BACKGROUND: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. METHODS: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. RESULTS: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. CONCLUSIONS: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.