Clinical Trial Registries, Results Databases, and Research Data Repositories

2019 ◽  
pp. 453-480
Author(s):  
Karmela Krleža-Jerić
Keyword(s):  
Clinical Trial ◽  
Research Data ◽  
Data Repositories ◽  
Clinical Trial Registries

scholarly journals Reporting of harms in oncological clinical study reports submitted to the European Medicines Agency compared to trial registries and publications—a methodological review

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Asger S. Paludan-Müller ◽  
Perrine Créquit ◽  
Isabelle Boutron
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Study ◽  
Primary Source ◽  
European Medicines Agency ◽  
Clinical Trial Registries ◽  
Number Of Patients ◽  
Journal Publications ◽  
Clinical Study Reports ◽  
Completeness Of Reporting

Abstract Background An accurate and comprehensive assessment of harms is a fundamental part of an accurate weighing of benefits and harms of an intervention when making treatment decisions; however, harms are known to be underreported in journal publications. Therefore, we sought to compare the completeness of reporting of harm data, discrepancies in harm data reported, and the delay to access results of oncological clinical trials between three sources: clinical study reports (CSRs), clinical trial registries and journal publications. Methods We used the EMA clinical data website to identify all trials submitted to the EMA between 2015 and 2018. We retrieved all CSRs and included all phase II, II/III or III randomised controlled trials (RCTs) assessing targeted therapy and immunotherapy for cancer. We then identified related records in clinical trial registries and journals. We extracted harms data for eight pre-specified variables and determined the completeness of reporting of harm data in each of the three sources. Results We identified 42 RCTs evaluating 13 different drugs. Results were available on the EMA website in CSRs for 37 (88%) RCTs, ClinicalTrials.gov for 36 (86%), the European Clinical Trials Register (EUCTR) for 20 (48%) and in journal publications for 32 (76%). Harms reporting was more complete in CSRs than other sources. We identified marked discrepancies in harms data between sources, e.g. the number of patients discontinuing due to adverse events differed in CSRs and clinical trial registers for 88% of trials with data in both sources. For CSRs and publications, the corresponding number was 90%. The median (interquartile range) delay between the primary trial completion date and access to results was 4.34 (3.09–7.22) years for CSRs, 2.94 (1.16–4.52) years for ClinicalTrials.gov, 5.39 (4.18–7.33) years for EUCTR and 2.15 (0.64–5.04) years for publications. Conclusions Harms of recently approved oncological drugs were reported more frequently and in more detail in CSRs than in trial registries and journal publications. Systematic reviews seeking to address harms of oncological treatments should ideally use CSRs as the primary source of data; however, due to problems with access, this is currently not feasible.

Improvements for research data repositories: The case of text spam

2021 ◽  
pp. 016555152199863
Author(s):  
Ismael Vázquez ◽  
María Novo-Lourés ◽  
Reyes Pavón ◽  
Rosalía Laza ◽  
José Ramón Méndez ◽  
...  
Keyword(s):  
Web Application ◽  
Research Data ◽  
Data Sets ◽  
Data Repositories ◽  
Software Applications ◽  
Public Data ◽  
Protection Mechanisms ◽  
Experimental Protocols ◽  
Learning Research ◽  
Processing Steps

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for the development of experimental protocols and test benches. This study has analysed a significant number of CS/ML ( Computer Science/ Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2) facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms for licencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application which implements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in the URL https://rdata.4spam.group to facilitate understanding of this study.

scholarly journals GAMS – An infrastructure for the long-term preservation and publication of research data from the Humanities

2018 ◽  
Vol 71 (1) ◽  
pp. 207-216 ◽  
Author(s):  
Johannes Hubert Stigler ◽  
Elisabeth Steiner
Keyword(s):  
System Architecture ◽  
Academic Research ◽  
Research Data ◽  
Data Repository ◽  
Data Repositories ◽  
Domain Specific ◽  
Preservation Policy ◽  
Long Term Preservation ◽  
Data Centres

Research data repositories and data centres are becoming more and more important as infrastructures in academic research. The article introduces the Humanities’ research data repository GAMS, starting with the system architecture to preservation policy and content policy. Challenges of data centres and repositories and the general and domain-specific approaches and solutions are outlined. Special emphasis lies on the sustainability and long-term perspective of such infrastructures, not only on the technical but above all on the organisational and financial level.

scholarly journals Results availability and timeliness of registered COVID-19 clinical trials: interim cross-sectional results from the DIRECCT study

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e053096
Author(s):  
Maia Salholz-Hillel ◽  
Peter Grabitz ◽  
Molly Pugh-Jones ◽  
Daniel Strech ◽  
Nicholas J DeVito
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Journal Article ◽  
Cross Sectional Study ◽  
Sensitivity Analyses ◽  
Cross Sectional ◽  
Registration Data ◽  
Clinical Trial Registries ◽  
Treatment And Prevention

ObjectiveTo examine how and when the results of COVID-19 clinical trials are disseminated.DesignCross-sectional study.SettingThe COVID-19 clinical trial landscape.Participants285 registered interventional clinical trials for the treatment and prevention of COVID-19 completed by 30 June 2020.Main outcome measuresOverall reporting and reporting by dissemination route (ie, by journal article, preprint or results on a registry); time to reporting by dissemination route.ResultsFollowing automated and manual searches of the COVID-19 literature, we located 41 trials (14%) with results spread across 47 individual results publications published by 15 August 2020. The most common dissemination route was preprints (n=25) followed by journal articles (n=18), and results on a registry (n=2). Of these, four trials were available as both a preprint and journal publication. The cumulative incidence of any reporting surpassed 20% at 119 days from completion. Sensitivity analyses using alternate dates and definitions of results did not appreciably change the reporting percentage. Expanding minimum follow-up time to 3 months increased the overall reporting percentage to 19%.ConclusionCOVID-19 trials completed during the first 6 months of the pandemic did not consistently yield rapid results in the literature or on clinical trial registries. Our findings suggest that the COVID-19 response may be seeing quicker results disclosure compared with non-emergency conditions. Issues with the reliability and timeliness of trial registration data may impact our estimates. Ensuring registry data are accurate should be a priority for the research community during a pandemic. Data collection is underway for the next phase of the DIssemination of REgistered COVID-19 Clinical Trials study expanding both our trial population and follow-up time.

scholarly journals Connecting Data Publication to the Research Workflow: A Preliminary Analysis

2017 ◽  
Vol 12 (1) ◽  
pp. 88-105 ◽  
Author(s):  
Sünje Dallmeier-Tiessen ◽  
Varsha Khodiyar ◽  
Fiona Murphy ◽  
Amy Nurnberger ◽  
Lisa Raymond ◽  
...  
Keyword(s):  
Working Group ◽  
Research Data ◽  
Data Publishing ◽  
Data Repository ◽  
Research Activity ◽  
Data Repositories ◽  
Data Publication ◽  
Loosely Coupled ◽  
Definition Of ◽  
Data Documentation

The data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation. Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society. Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers. Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository. This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process. We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream. These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data. We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves.

scholarly journals A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question"

2019 ◽  
Vol 5 ◽  
Author(s):  
Matthew Murray ◽  
Megan O'Donnell ◽  
Mark Laufersweiler ◽  
John Novak ◽  
Betty Rozum ◽  
...  
Keyword(s):  
United States ◽  
Academic Libraries ◽  
The United States ◽  
Research Data ◽  
The State ◽  
Executive Summary ◽  
Data Repositories ◽  
Data Services ◽  
Survey Questions ◽  
State Of Research

This report shares the results of a Spring 2018 survey of 35 academic libraries in the United States in regard to the research data services (RDS) they offer. An executive summary presents key findings while the results section provides detailed information on the answers to specific survey questions related to data repositories, metadata, workshops, and polices.

scholarly journals DataverseNO: A National, Generic Repository and its Contribution to the Increased FAIRness of Data from the Long Tail of Research

Ravnetrykk ◽  
2020 ◽  
Author(s):  
Philipp Conzett
Keyword(s):  
Open Source Software ◽  
Crucial Role ◽  
Research Data ◽  
Background Information ◽  
Data Repositories ◽  
Long Tail ◽  
Open Research ◽  
Research Organizations ◽  
Digital Objects ◽  
Organizational Features

Research data repositories play a crucial role in the FAIR (Findable, Accessible, Interoperable, Reusable) ecosystem of digital objects. DataverseNO is a national, generic repository for open research data, primarily from researchers affiliated with Norwegian research organizations. The repository runs on the open-source software Dataverse. This article presents the organization and operation of DataverseNO, and investigates how the repository contributes to the increased FAIRness of small and medium sized research data. Sections 1 to 3 present background information about the FAIR Data Principles (section 1), how FAIR may be turned into reality (section 2), and what these principles and recommendations imply for data from the so-called long tail of research, i.e. small and medium-sized datasets that are often heterogenous in nature and hard to standardize (section 3). Section 4 gives an overview of the key organizational features of DataverseNO, followed by an evaluation of how well DataverseNO and the repository application Dataverse as such support the FAIR Data Principles (section 5). Section 6 discusses how sustainable and trustworthy the repository is. The article is rounded up in section 7 by a brief summary including a look into the future of the repository.

scholarly journals A Content Analysis of Indian Research Data Repositories Prospects and Possibilities

2019 ◽  
Vol 39 (06) ◽  
pp. 280-289 ◽  
Author(s):  
Raj Kumar Bhardwaj
Keyword(s):  
Application Programming Interface ◽  
Research Data ◽  
Identification System ◽  
Microsoft Excel ◽  
Data Repositories ◽  
Data Formats ◽  
Author Identification ◽  
Metadata Standards ◽  
Application Programming ◽  
Content Coverage

The study aims to trace the development of Indian research data repositories (RDRs) and explore their content with the view of identifying prospects and possibilities. Further, it analyses the distribution of data repositories on the basis of content coverage, types of content, author identification system followed, software and the application programming interface used, subject wise number of repositories etc. The study is based on data repositories listed on the registry of data repositories accessible at http://www.re3data.org.The dataset was exported in Microsoft Excel format for analysis. A simple percentage method was followed in data analyses and results are presented through Tables and Figures. The study found a total of 2829 data repositories in existence worldwide. Further, it was seen that 1526 (53.9 %) are open and 924 (32.4 %) are restricted data repositories. Also, there are embargoed data repositories numbering 225 (8.0 %) and closed ones numbering 154 (5.4 %). There are 2829 RDRs covering 72 countries in the world. The study found that out of total 45 Indian RDRs, only 30 (67 %) are open, followed by restricted 12 (27 %) and 3 (6 %) that are closed. Majority of Indian RDRs (20) were developed in the year 2014. The study found that the majority of Indian RDRs (17) are‘disciplinary’. Further, the study also revealed that statistical data formats are available in a maximum of 31 (68.9 %) Indian RDRs. It was also seen that the majority of Indian RDRs (28) has datasets relating to ‘Life Sciences’. It was identified that only 20% of data repositories have been using metadata standards in metadata; the remaining 80% do not use any standards in metadata entry. This study covered only the research data repositories in India registered on the registry of data repositories. RDRs not listed in the registry of data repositories are left out.

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