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MeSHing molecular sequences and clinical trials: a feasibility study.

ABSTRACT: The centralized and public availability of molecular sequence and clinical trial data presents an opportunity to identify potentially valuable linkages across the bench-to-bedside "T1" translational barrier. In this study, we sought to leverage keyword metadata (Medical Subject Heading [MeSH] descriptors) to infer relationships between molecular sequences and clinical trials, as indexed by GenBank and ClinicalTrials.gov. The results of this feasibility study found that approximately 30% of sequences in GenBank could be linked to trials and over 90% of trials in ClinicalTrials.gov could be linked to sequences through MeSH descriptors. In a cursory evaluation, we were able to consistently identify meaningful linkages between molecular sequences and clinical trials. Based on our findings, there may be promise in subsequent studies aiming to identify linkages across the T1 translational barrier using existing large repositories.

SUBMITTER: Chen ES

PROVIDER: S-EPMC2878930 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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MeSHing molecular sequences and clinical trials: a feasibility study.

Chen Elizabeth S ES Sarkar Indra Neil IN

Journal of biomedical informatics 20091020 3

The centralized and public availability of molecular sequence and clinical trial data presents an opportunity to identify potentially valuable linkages across the bench-to-bedside "T1" translational barrier. In this study, we sought to leverage keyword metadata (Medical Subject Heading [MeSH] descriptors) to infer relationships between molecular sequences and clinical trials, as indexed by GenBank and ClinicalTrials.gov. The results of this feasibility study found that approximately 30% of seque ...[more]

PMID: 19850150

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Project description:BackgroundBlinding is an established approach in clinical trials which aims to minimise the risk of performance and detection bias. There is little empirical evidence to guide UK clinical trials units (CTUs) about the practice of blinding statisticians. Guidelines recommend that statisticians remain blinded to allocation prior to the final analysis. As these guidelines are not based on empirical evidence, this study undertook a qualitative investigation relating to when and how statisticians should be blinded in clinical trials.MethodsData were collected through online focus groups with various stakeholders who work in the delivery and oversight of clinical trials. Recordings of the focus groups were transcribed verbatim and thematic analysis was used to analyse the transcripts.ResultsThirty-seven participants from 19 CTUs participated in one of six focus groups. Four main themes were identified, namely statistical models of work, factors affecting the decision to blind statisticians, benefits of blinding/not blinding statisticians and practicalities. Factors influencing the decision to blind the statistician included available resources, study design and types of intervention and outcomes and analysis. Although blinding of the statistician is perceived as a desirable mitigation against bias, there was uncertainty about the extent to which an unblinded statistician might impart bias. Instead, in most cases, the insight that the statistician offers was deemed more important to delivery of a trial than the risk of bias they may introduce if unblinded. Blinding of statisticians was only considered achievable with the appropriate resource and staffing, which were not always available. In many cases, a standard approach to blinding was therefore considered unrealistic and impractical; hence the need for a proportionate risk assessment approach identifying possible mitigations.ConclusionsThere was wide variation in practice between UK CTUs regarding the blinding of trial statisticians. A risk assessment approach would enable CTUs to identify risks associated with unblinded statisticians conducting the final analysis and alternative mitigation strategies. The findings of this study will be used to design guidance and a tool to support this risk assessment process.

Dataset Information

MeSHing molecular sequences and clinical trials: a feasibility study.

Publications

MeSHing molecular sequences and clinical trials: a feasibility study.

Similar Datasets

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