Data sharing platforms for de-identified data from human clinical trials

Huser, Vojtech; Shmueli-Blumberg, Dikla

doi:10.1177/1740774518769655

Cited by 21 publications

(17 citation statements)

References 32 publications

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“…Knowledge of how to establish and maintain contact with study stakeholders, negotiate data sharing agreements, and manage clinical study data is required. Broader issues including designing trials for secondary analysis, participant confidentiality, data sharing models, data sharing platforms, data request review panels and recognition of primary study investigators must also be understood to ensure an IPDMA is conducted to appropriate scientific, ethical, and legal standard [128,[198][199][200][201][202][203][204][205][206]. We hope that a shift away from peer-to-peer requesting procedures towards data repository requests will help [207].…”

Section: Discussionmentioning

confidence: 99%

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

Ventresca

Schünemann

Macbeth

et al. 2020

BMC Med Res Methodol

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Background: Shifts in data sharing policy have increased researchers' access to individual participant data (IPD) from clinical studies. Simultaneously the number of IPD meta-analyses (IPDMAs) is increasing. However, rates of data retrieval have not improved. Our goal was to describe the challenges of retrieving IPD for an IPDMA and provide practical guidance on obtaining and managing datasets based on a review of the literature and practical examples and observations. Methods: We systematically searched MEDLINE, Embase, and the Cochrane Library, until January 2019, to identify publications focused on strategies to obtain IPD. In addition, we searched pharmaceutical websites and contacted industry organizations for supplemental information pertaining to recent advances in industry policy and practice. Finally, we documented setbacks and solutions encountered while completing a comprehensive IPDMA and drew on previous experiences related to seeking and using IPD. Results: Our scoping review identified 16 articles directly relevant for the conduct of IPDMAs. We present short descriptions of these articles alongside overviews of IPD sharing policies and procedures of pharmaceutical companies which display certification of Principles for Responsible Clinical Trial Data Sharing via Pharmaceutical Research and Manufacturers of America or European Federation of Pharmaceutical Industries and Associations websites. Advances in data sharing policy and practice affected the way in which data is requested, obtained, stored and analyzed. For our IPDMA it took 6.5 years to collect and analyze relevant IPD and navigate additional administrative barriers. Delays in obtaining data were largely due to challenges in communication with study sponsors, frequent changes in data sharing policies of study sponsors, and the requirement for a diverse skillset related to research, administrative, statistical and legal issues.

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Section: Discussionmentioning

confidence: 99%

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

Ventresca

Schünemann

Macbeth

et al. 2020

BMC Med Res Methodol

View full text Add to dashboard Cite

show abstract

“…Knowledge of how to establish and maintain contact with study stakeholders, negotiate data sharing agreements, and manage clinical study data is required. Broader issues including designing trials for secondary analysis, participant confidentiality, data sharing models, data sharing platforms, data request review panels and recognition of primary study investigators must also be understood to ensure an IPDMA is conducted to appropriate scientific, ethical, and legal standard [150][151][152][153][154][155][156][157][158][159]. We hope that a shift away from peer-to-peer requesting procedures towards data repository requests will help [160].…”

Section: Discussionmentioning

confidence: 99%

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

Ventresca

Macbeth

Clarke

et al. 2019

Preprint

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Background Shifts in data sharing policy have increased researchers’ access to individual participant data (IPD) from clinical studies. Simultaneously the number of IPD meta-analyses (IPDMAs) is increasing. However, rates of data retrieval have not improved. Our goal was to describe the challenges of retrieving IPD for an IPDMA and provide practical guidance based on a review of the literature and practical examples and observations. Methods We systematically searched MEDLINE, Embase, and the Cochrane Library to identify publications focused on strategies to obtain IPD. In addition, we searched pharmaceutical websites and contacted industry organizations for supplemental information pertaining to recent advances in industry policy and practice. Finally, we documented setbacks and solutions encountered while completing a comprehensive IPDMA and drew on previous experiences related to seeking and using IPD. Results Our scoping review identified 16 articles directly relevant for the conduct of IPDMAs. We present short descriptions of these articles alongside overviews of IPD sharing policies and procedures of pharmaceutical companies which display certification of Principles for Responsible Clinical Trial Data Sharing via Pharmaceutical Research and Manufacturers of America or European Federation of Pharmaceutical Industries and Associations websites. Advances in data sharing policy and practice affected the way in which data is requested, obtained, stored and analyzed For our IPDMA it took 6.5 years to collect and analyze relevant IPD and navigate additional administrative barriers. Delays in obtaining data were largely due to challenges in communication with study sponsors, frequent changes in data sharing policies of study sponsors, and the requirement for a diverse skillset related to research, administrative, statistical and legal issues. Conclusions Knowledge of current data sharing practices and platforms as well as anticipation of necessary tasks and potential obstacles may reduce time and resources required for an IPDMA. Sufficient project funding and timeline flexibility are pre-requisites for successful collection and analysis of IPD. IPDMA researchers must acknowledge the additional and unexpected responsibility they are placing on study authors or data sharing administrators and should offer assistance in readying data for sharing.

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“…We searched clinical study data sharing platforms [5] for HIV studies that shared IPD. We defined HIV studies as any study relating to HIV, which includes any study with HIV positive participants, or any study relating to HIV infection (i.e.…”

Section: Trials Acquisitionmentioning

confidence: 99%

“…When data is shared, a data dictionary is typically provided to describe individual data elements used in a study. In recent decades, tens of new data sharing platforms with the aim of facilitating secondary research have emerged [5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of data dictionary formats of HIV clinical trials

2020

Self Cite

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Background Efforts to define research Common Data Elements try to harmonize data collection across clinical studies. Objective Our goal was to analyze the quality and usability of data dictionaries of HIV studies. Methods For the clinical domain of HIV, we searched data sharing platforms and acquired a set of 18 HIV related studies from which we analyzed 26 328 data elements. We identified existing standards for creating a data dictionary and reviewed their use. To facilitate aggregation across studies, we defined three types of data dictionary (data element, forms, and permissible values) and created a simple information model for each type. Results An average study had 427 data elements (ranging from 46 elements to 9 945 elements). In terms of data type, 48.6% of data elements were string, 47.8% were numeric, 3.0% were date and 0.6% were date-time. No study in our sample explicitly declared a data element as a categorical variable and rather considered them either strings or numeric. Only for 61% of studies were we able to obtain permissible values. The majority of studies used CSV files to share a data dictionary while 22% of the studies used a non-computable, PDF format. All studies grouped their data elements. The average number of groups or forms per study was 24 (ranging between 2 and 124 groups/forms). An accurate and well formatted data dictionary facilitates error-free secondary analysis and can help with data de-identification. Conclusion We saw features of data dictionaries that made them difficult to use and understand. This included multiple data dictionary files or non-machine-readable documents, data elements included in data but not in the dictionary or missing data types or descriptions. Building on

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Data sharing platforms for de-identified data from human clinical trials

Cited by 21 publications

References 32 publications

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

Obtaining and managing data sets for individual participant data meta-analysis: scoping review and practical guide

Analysis of data dictionary formats of HIV clinical trials

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