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Systematic identification of pharmacogenomics information from clinical trials.

ABSTRACT: Recent progress in high-throughput genomic technologies has shifted pharmacogenomic research from candidate gene pharmacogenetics to clinical pharmacogenomics (PGx). Many clinical related questions may be asked such as 'what drug should be prescribed for a patient with mutant alleles?' Typically, answers to such questions can be found in publications mentioning the relationships of the gene-drug-disease of interest. In this work, we hypothesize that ClinicalTrials.gov is a comparable source rich in PGx related information. In this regard, we developed a systematic approach to automatically identify PGx relationships between genes, drugs and diseases from trial records in ClinicalTrials.gov. In our evaluation, we found that our extracted relationships overlap significantly with the curated factual knowledge through the literature in a PGx database and that most relationships appear on average 5 years earlier in clinical trials than in their corresponding publications, suggesting that clinical trials may be valuable for both validating known and capturing new PGx related information in a more timely manner. Furthermore, two human reviewers judged a portion of computer-generated relationships and found an overall accuracy of 74% for our text-mining approach. This work has practical implications in enriching our existing knowledge on PGx gene-drug-disease relationships as well as suggesting crosslinks between ClinicalTrials.gov and other PGx knowledge bases.

SUBMITTER: Li J

PROVIDER: S-EPMC3760158 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Systematic identification of pharmacogenomics information from clinical trials.

Li Jiao J Lu Zhiyong Z

Journal of biomedical informatics 20120424 5

Recent progress in high-throughput genomic technologies has shifted pharmacogenomic research from candidate gene pharmacogenetics to clinical pharmacogenomics (PGx). Many clinical related questions may be asked such as 'what drug should be prescribed for a patient with mutant alleles?' Typically, answers to such questions can be found in publications mentioning the relationships of the gene-drug-disease of interest. In this work, we hypothesize that ClinicalTrials.gov is a comparable source rich ...[more]

PMID: 22546622

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Project description:BackgroundNocebo effects ('negative placebo' effects) experienced by clinical trial participants can arise from an underlying condition or through communication about side effects in the participant information leaflets (or elsewhere). Misattributing nocebo effects to the medicinal intervention can lead to participants experiencing harmful nocebo effects and may result in distortion of adverse effect reporting. However, little is known about how information on potential side effects is provided to trial participants. There is increasing concern that the way in which potential side effects in clinical trials are described to patients in participant information leaflets (PIL) can in itself cause harm by either increased anxiety, poor adherence or inducing the side effect itself. In this study, we aimed to explore these concerns and identify the way in which potential side effects from investigational medicinal products used in trials are presented in written information to potential participants.MethodsTrials were identified from the International Standard Randomised Controlled Trials Number (ISRCTN) clinical trial registry (a primary registry of the WHO International Clinical Trials Registry Platform (ICTRP)). Eligible studies were placebo-controlled clinical trials of investigational medicinal products (IMP) in adults conducted in the UK. We assessed readability using the Flesch Reading Ease scale, Gunning-Fog Index and Flesch-Kincaid Grade. Data extracted from the PILs were divided into 8 predefined qualitative themes for analysis in NVivo11.ResultsMost of the patient information leaflets were ranked as 'fairly difficult to read' or 'difficult to read' according to the Flesch Reading Ease scale. All studies presented information about adverse events, whereas only a third presented information about intervention benefits. Where intervention or study benefits were presented, they were usually after adverse events (21/33, 64%).DiscussionParticipant information leaflets scored poorly on ease of readability and had more content relating to adverse effects than any potential beneficial effects. The way in which adverse events were presented was heterogeneous in terms of their likelihood and severity and the amount and level of detail provided. By comparison, potential benefits from the intervention and/or study were described less often, by shorter text, and only after information about harms.

Project description:BACKGROUND: Poor accrual is a significant barrier to the successful completion of oncology clinical trials; half of all phase 3 oncology trials close due to insufficient accrual. Timely access to accrual data fosters an understanding of successful trial design and can be used to inform the design of new clinical trials prospectively. Accrual statistics are available within research networks, such as the cancer cooperative groups, but comprehensive data reflecting the overall portfolio of cancer clinical trials are lacking. As a demonstration case, the purpose of this study was to quantify the public availability of accrual data across all recent renal cell carcinoma (RCC) trials. METHODS: The database for the Aggregate Analysis of ClinicalTrials.gov (AACT) summarizes all trials registered between October 2007 and September 2010. In total, 108 trials of pharmacologic therapy for RCC were included. Accrual data on these trials were gathered via ClinicalTrials.gov (CTG), a manual review of resulting publications, and online surveys sent to principle investigators or trial coordinators. RESULTS: In total, 26% (20 of 76) of trials listing a government, academic, or cooperative group (GAC) sponsor responded to the survey vs 0% (0 of 32) of those listing only industry sponsors. Across all methods, accrual data were available for only 40% (43 of 108) of trials, including 37% (28 of 76) of GAC trials and 47% (15 of 32) of industry trials. Moreover, 87% (66 of 76) of GAC trials were ongoing (open, actively recruiting, or of unknown status) vs 75% (24 of 32) of industry trials, while 9% (10 of 108) of trials were terminated or suspended. CONCLUSIONS: Despite extensive efforts (surveys, phone calls, CTG abstraction, publication searches), accurate accrual data remained inaccessible for 60% of the RCC trial cohort. While CTG reports trial results, ongoing accrual data are also critically needed. Poor access to accrual data will continue to limit attempts to develop a national summary of clinical trials metrics and to optimize the cancer clinical research portfolio.

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Systematic identification of pharmacogenomics information from clinical trials.

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Systematic identification of pharmacogenomics information from clinical trials.

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