A novel semantic representation for eligibility criteria in clinical trials

Chondrogiannis, Efthymios; Andronikou, Vassiliki; Tagaris, Anastasios; Karanastasis, Efstathios; Varvarigou, Theodora; Tsuji, Motomu

doi:10.1016/j.jbi.2017.03.013

Cited by 30 publications

(20 citation statements)

References 24 publications

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“…For instance, if a study had an arm of type “placebo comparator” or an intervention with a name including words “placebo,” “vehicle,” or “sugar pill,” it was annotated as “placebo controlled”; similarly, studies with an arm of type “active comparator” were classified as “comparator controlled” (see supplementary file 2 for details). Finally, we annotated each trial with the number of outcome measures and eligibility criteria following parsing of the unstructured eligibility data field as described by Chondrogiannis et al 28 …”

Section: Methodsmentioning

confidence: 99%

Clinical trial design and dissemination: comprehensive analysis of clinicaltrials.gov and PubMed data since 2005

Zwierzyna

Davies

Hingorani

et al. 2018

BMJ

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ObjectiveTo investigate the distribution, design characteristics, and dissemination of clinical trials by funding organisation and medical specialty.DesignCross sectional descriptive analysis.Data sourcesTrial protocol information from clinicaltrials.gov, metadata of journal articles in which trial results were published (PubMed), and quality metrics of associated journals from SCImago Journal and Country Rank database.Selection criteriaAll 45 620 clinical trials evaluating small molecule therapeutics, biological drugs, adjuvants, and vaccines, completed after January 2006 and before July 2015, including randomised controlled trials and non-randomised studies across all clinical phases.ResultsIndustry was more likely than non-profit funders to fund large international randomised controlled trials, although methodological differences have been decreasing with time. Among 27 835 completed efficacy trials (phase II-IV), 15 084 (54.2%) had disclosed their findings publicly. Industry was more likely than non-profit trial funders to disseminate trial results (59.3% (10 444/17 627) v 45.3% (4555/10 066)), and large drug companies had higher disclosure rates than small ones (66.7% (7681/11 508) v 45.2% (2763/6119)). Trials funded by the National Institutes of Health (NIH) were disseminated more often than those of other non-profit institutions (60.0% (1451/2417) v 40.6% (3104/7649)). Results of studies funded by large drug companies and NIH were more likely to appear on clinicaltrials.gov than were those from non-profit funders, which were published mainly as journal articles. Trials reporting the use of randomisation were more likely than non-randomised studies to be published in a journal article (6895/19 711 (34.9%) v 1408/7748 (18.2%)), and journal publication rates varied across disease areas, ranging from 42% for autoimmune diseases to 20% for oncology.ConclusionsTrial design and dissemination of results vary substantially depending on the type and size of funding institution as well as the disease area under study.

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Section: Methodsmentioning

confidence: 99%

Clinical trial design and dissemination: comprehensive analysis of clinicaltrials.gov and PubMed data since 2005

Zwierzyna

Davies

Hingorani

et al. 2018

BMJ

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“…In [15], the Eligibility Rule Grammar and Ontology (ERGO) is used to annotate free-text criteria and to transform them into a computable form. Chondrogiannis et al [16] proposed a CDISC-compliant schema to organize criteria along with a patientcentric model for their formal expression. The Eligibility Criteria Ontology (EC-O) was developed to cover a wide range of parameters allowing the specification of eligibility criteria in clinical trials.…”

Section: State Of the Artmentioning

confidence: 99%

Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas

Uciteli¹,

Beger²,

Wagner³

et al. 2021

German Medical Data Sciences: Bringing Data to Life

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Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

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“…Care should be taken with clarity of all time-related descriptions, particularly regarding exactly which 'anchor' in time applies. 63,73,74 While publicly available protocol templates give general guidance on writing clear and complete eligibility criteria, [75][76][77] we do not know of any that clearly state the need to include all the elements we have mentioned here. Although they may usually be included in practice, without clear guidance there is a risk they may sometimes be missed, with resulting negative impact on clarity or completeness of criteria.…”

Section: Opportunities For Improvementmentioning

confidence: 99%

Clinical Trial Recruiters’ Experiences Working With Trial Eligibility Criteria: Results of an Exploratory, Cross-sectional, Online Survey

Cragg

McMahon

Oughton

et al. 2021

Preprint

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BackgroundEligibility criteria are a fundamental element of clinical trial design, defining who can and who should not participate in a trial. Problems with the design or application of criteria are known to occur and pose risks to participants' safety and trial integrity, sometimes also negatively impacting on trial recruitment and generalisability. We conducted a short, exploratory survey to gather evidence on UK recruiters' experiences interpreting and applying eligibility criteria and their views on how criteria are communicated and developed.MethodsOur survey included topics informed by a wider programme of work at the Clinical Trials Research Unit, University of Leeds, on assuring eligibility criteria quality. Respondents were asked to answer based on all their trial experience, not only on experiences with our trials. The survey was disseminated to recruiters collaborating on trials run at our trials unit, and via other mailing lists and social media. The quantitative responses were descriptively analysed, with inductive analysis of free-text responses to identify themes.ResultsA total of 823 eligible respondents participated. 79% of respondents reported finding problems with eligibility criteria in some trials, and 9% in most trials. The main themes in the types of problems experienced were criteria clarity (67% of comments), feasibility (34%) and suitability (14%). 27% of those reporting some level of problem said these problems had led to patients being incorrectly included in trials; 40% said they had led to incorrect exclusions. Most respondents (56%) reported accessing eligibility criteria mainly in the trial protocol. Most respondents (74%) supported the idea that they might review eligibility criteria earlier in the protocol development process.ConclusionsOur survey corroborates other evidence about the existence of suboptimal trial eligibility criteria. Problems with clarity were the most often reported, but the number of comments on feasibility and suitability suggest some recruiters feel eligibility criteria and associated assessments can hinder recruitment to trials. Our proposal for more recruiter involvement in protocol development has strong support and some potential benefits, but questions remain about how best to implement this. We invite other trialists to consider our other suggestions for how to assure quality in trial eligibility criteria.

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A novel semantic representation for eligibility criteria in clinical trials

Cited by 30 publications

References 24 publications

Clinical trial design and dissemination: comprehensive analysis of clinicaltrials.gov and PubMed data since 2005

Clinical trial design and dissemination: comprehensive analysis of clinicaltrials.gov and PubMed data since 2005

Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas

Clinical Trial Recruiters’ Experiences Working With Trial Eligibility Criteria: Results of an Exploratory, Cross-sectional, Online Survey

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