Some data quality issues at ClinicalTrials.gov.
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ABSTRACT: Background
Clinical trial registries have been established as a form of public accountability. Sponsors ought to register their trials promptly and accurately, but this is not always done. Some of the problems include non-registration of trials, registration of trials with incomplete information, and non-reporting of trial results on time. In this study we enumerate or quantify some quality issues with respect to Principal Investigator (PI) and Responsible Party data.Methods
We analyzed interventional trials registered with ClinicalTrials.gov. Using certain selection criteria, we started with 112,013 records, and then applied further filters. The trial had to (a) start between 1 January 2005 and 31 December 2014, (b) include a "drug" or "biological" in the "intervention" field, (c) be registered with an American authority, and (d) list a real person's name as investigator and also his or her role in the study.Results
We identified four categories of errors in the ClinicalTrials.gov records. First, some data were missing. The name of the investigator, or his or her role, was missing in 12% of 35,121 trials. In examining 71,359 pairs of names and roles, 17% of the "names" were found to be not those of real persons, but instead junk information. Second, there were variations in a large number of names. We identified 19 categories of variants. We determined that 13% of the names had variants that could not be resolved using a program. Third, some trials listed many PIs each, although only one such person holds overall responsibility for the trial and therefore not more than one person should be listed as PI. Fourth, in examining whether the PI's name was available as part of the Responsible Party tag, we found that in 1221 (3.5%) of 35,121 trials, the Responsible Party tag is absent.Conclusions
We have outlined four categories of problems with data hosted by ClinicalTrials.gov and have quantified three of them. We also suggest how these errors could be prevented in future. It is important to carry out various kinds of audits of trial registries, in order to identify lacunae in the records, that they be addressed.
SUBMITTER: Chaturvedi N
PROVIDER: S-EPMC6591874 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:The ClinicalTrials.gov trial registry was expanded in 2008 to include a database for reporting summary results. We summarize the structure and contents of the results database, provide an update of relevant policies, and show how the data can be used to gain insight into the state of clinical research. METHODS:We analyzed ClinicalTrials.gov data that were publicly available between September 2009 and September 2010. RESULTS:As of September 27, 2010, ClinicalTrials.gov received approximately 330 new and 2000 revised registrations each week, along with 30 new and 80 revised results submissions. We characterized the 79,413 registry and 2178 results of trial records available as of September 2010. From a sample cohort of results records, 78 of 150 (52%) had associated publications within 2 years after posting. Of results records available publicly, 20% reported more than two primary outcome measures and 5% reported more than five. Of a sample of 100 registry record outcome measures, 61% lacked specificity in describing the metric used in the planned analysis. In a sample of 700 results records, the mean number of different analysis populations per study group was 2.5 (median, 1; range, 1 to 25). Of these trials, 24% reported results for 90% or less of their participants. CONCLUSIONS:ClinicalTrials.gov provides access to study results not otherwise available to the public. Although the database allows examination of various aspects of ongoing and completed clinical trials, its ultimate usefulness depends on the research community to submit accurate, informative data.
| S-EPMC3066456 | biostudies-literature
Project description:BackgroundIn recent years, online physician-rating websites have become prominent and exert considerable influence on patients' decisions. However, the quality of these decisions depends on the quality of data that these systems collect. Thus, there is a need to examine the various data quality issues with physician-rating websites.ObjectiveThis study's objective was to identify and categorize the data quality issues afflicting physician-rating websites by reviewing the literature on online patient-reported physician ratings and reviews.MethodsWe performed a systematic literature search in ACM Digital Library, EBSCO, Springer, PubMed, and Google Scholar. The search was limited to quantitative, qualitative, and mixed-method papers published in the English language from 2001 to 2020.ResultsA total of 423 articles were screened. From these, 49 papers describing 18 unique data quality issues afflicting physician-rating websites were included. Using a data quality framework, we classified these issues into the following four categories: intrinsic, contextual, representational, and accessible. Among the papers, 53% (26/49) reported intrinsic data quality errors, 61% (30/49) highlighted contextual data quality issues, 8% (4/49) discussed representational data quality issues, and 27% (13/49) emphasized accessibility data quality. More than half the papers discussed multiple categories of data quality issues.ConclusionsThe results from this review demonstrate the presence of a range of data quality issues. While intrinsic and contextual factors have been well-researched, accessibility and representational issues warrant more attention from researchers, as well as practitioners. In particular, representational factors, such as the impact of inline advertisements and the positioning of positive reviews on the first few pages, are usually deliberate and result from the business model of physician-rating websites. The impact of these factors on data quality has not been addressed adequately and requires further investigation.
| S-EPMC7551103 | biostudies-literature
Project description:ObjectivesHigh-quality data are crucial for guiding decision-making and practising evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese epidemiological surveillance dataset, our study aims to assess COVID-19 data quality issues and suggest possible solutions.SettingsOn 27 April 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On 4 August, an updated dataset (DGSAugust) was also obtained.ParticipantsAll COVID-19-confirmed cases notified through the medical component of National System for Epidemiological Surveillance until end of June.Primary and secondary outcome measuresData completeness and consistency.ResultsDGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (eg, 4075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (eg, the variable 'underlying conditions' had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily.ConclusionsImportant quality issues of the Portuguese COVID-19 surveillance datasets were described. These issues can limit surveillance data usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed-for example, simplification of data entry processes, constant monitoring of data, and increased training and awareness of healthcare providers-as low data quality may lead to a deficient pandemic control.
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Project description:According to several recent studies, an unexpectedly high number of landmark papers seem to be not reproducible by independent laboratories. Nontherapeutic antibodies used for research, diagnostic, food analytical, environmental, and other purposes play a significant role in this matter. Although some papers have been published offering suggestions to improve the situation, they do not seem to be comprehensive enough to cover the full complexity of this issue. In addition, no obvious improvements could be noticed in the field as yet. This article tries to consolidate the remarkable variety of conclusions and suggested activities into a more coherent conception. It is concluded that funding agencies and journal publishers need to take first and immediate measures to resolve these problems and lead the way to a more sustainable way of bioanalytical research, on which all can rely with confidence.
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Project description:BackgroundIndividual case safety reports of suspected harm from medicines are fundamental to post-marketing surveillance. Their value is directly proportional to the amount of clinically relevant information they include. To improve the quality of the data, communication between stakeholders is essential and can be facilitated by a simple score and visualisation of the results.ObjectiveThe objective of this study was to propose a measure of completeness and identify predictors of well-documented reports, globally.MethodsThe Uppsala Monitoring Centre has developed the vigiGrade completeness score to measure the amount of clinically relevant information in structured format, without reflecting whether the information establishes causality between the drug and adverse event. The vigiGrade completeness score (C) starts at 1 for reports with information on time-to-onset, age, sex, indication, outcome, report type, dose, country, primary reporter and comments. For each missing dimension, a penalty is detracted which varies with clinical relevance. We classified reports with C > 0.8 as well-documented and identified all such reports in the WHO global individual case safety report database, VigiBase, from 2007 to January 2012. We utilised odds ratios with statistical shrinkage to identify subgroups with unexpectedly high proportions of well-documented reports.ResultsAltogether, 430,000 (13 %) of the studied reports achieved C > 0.8 in VigiBase. For VigiBase as a whole, the median completeness was 0.41 with an interquartile range of 0.26-0.63. Two out of three well-documented reports come from Europe, and two out of three from physicians. Among the countries with more than 1,000 reports in total, the highest rate of well-documented reports is 65 % in Italy. Tunisia, Spain, Portugal, Croatia and Denmark each have rates above 50 %, and another 20 countries have rates above 30 %. On the whole, 24 % of the reports from physicians are well-documented compared with only 4 % for consumers/non-health professionals. Notably, Denmark and Norway have more than 50 % well-documented reports from consumers/non-health professionals and higher rates than for physicians. The rate of well-documented reports for the E2B format is 11 % compared with 22 % for the older INTDIS (International Drug Information System) format. However, for E2B reports entered via the WHO programme's e-reporting system VigiFlow, the rate is 29 %.ConclusionOverall, only one report in eight provides the desired level of information, but much higher proportions are observed for individual countries. Physicians and e-reporting tools also generate greater proportions of well-documented reports overall. Reports from consumers/non-health professionals in specific regions have excellent quality, which illustrates their potential for the future. vigiGrade has already provided valuable information by highlighting data quality issues both in Italy and the USA.
| S-EPMC6447519 | biostudies-literature
Project description:In June 2017, the International Committee of Medical Journal Editors (ICMJE) announced a requirement that authors reporting the results of clinical trials to journals that follow ICMJE recommendations must include an individual participant data (IPD) sharing statement with manuscripts submitted after 01 July 2018. Additionally, all new clinical trials for which enrollment began on or after 01 January 2019 must include a data sharing statement in the trial's publicly posted registration. This study sought to understand whether IPD sharing statements of clinical trials first registered on ClinicalTrials.gov before 01 January 2019 reflected comprehension of the expectations and a willingness to share. To establish baseline characteristics for the prevalence and quality of IPD sharing statements, we examined IPD sharing statements among 2,040 clinical trials first posted on ClinicalTrials.gov between 01 January 2018 and 06 June 2018. Two independent coders further analyzed the quality of the IPD sharing statements of trials whose registration records indicated the intent to share IPD. The vast majority of trials included in this study did not indicate an intent to share IPD (n = 1,928; 94.5%). Among the trials that did commit to sharing IPD (n = 112, 5.5%), significant variability existed in the content and structure of IPD sharing statements. The results of this study suggest that successful compliance with the IPD sharing statement requirements of the ICMJE will require further clarification, enhanced education, and outreach to investigators.
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Project description:Drug repositioning (i.e., drug repurposing) is the process of discovering new uses for marketed drugs. Historically, such discoveries were serendipitous. However, the rapid growth in electronic clinical data and text mining tools makes it feasible to systematically identify drugs with the potential to be repurposed. Described here is a novel method of drug repositioning by mining ClinicalTrials.gov. The text mining tools I2E (Linguamatics) and PolyAnalyst (Megaputer) were utilized. An I2E query extracts "Serious Adverse Events" (SAE) data from randomized trials in ClinicalTrials.gov. Through a statistical algorithm, a PolyAnalyst workflow ranks the drugs where the treatment arm has fewer predefined SAEs than the control arm, indicating that potentially the drug is reducing the level of SAE. Hypotheses could then be generated for the new use of these drugs based on the predefined SAE that is indicative of disease (for example, cancer).
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Project description:OBJECTIVES:Systematic reviews and meta-analyses are labor-intensive and time-consuming. Automated extraction of quantitative data from primary studies can accelerate this process. ClinicalTrials.gov, launched in 2000, is the world's largest trial repository of results data from clinical trials; it has been used as a source instead of journal articles. We have developed a Web application called EXACT (EXtracting Accurate efficacy and safety information from ClinicalTrials.gov) that allows users without advanced programming skills to automatically extract data from ClinicalTrials.gov in analysis-ready format. We have also used the automatically extracted data to examine the reproducibility of meta-analyses in three published systematic reviews. STUDY DESIGN AND SETTING:We developed a Python-based software application (EXACT) that automatically extracts data required for meta-analysis from the ClinicalTrials.gov database in a spreadsheet format. We confirmed the accuracy of the extracted data and then used those data to repeat meta-analyses in three published systematic reviews. To ensure that we used the same statistical methods and outcomes as the published systematic reviews, we repeated the meta-analyses using data manually extracted from the relevant journal articles. For the outcomes whose results we were able to reproduce using those journal article data, we examined the usability of ClinicalTrials.gov data. RESULTS:EXACT extracted data at ClincalTrials.gov with 100% accuracy, and it required 60% less time than the usual practice of manually extracting data from journal articles. We found that 87% of the data elements extracted using EXACT matched those extracted manually from the journal articles. We were able to reproduce 24 of 28 outcomes using the journal article data. Of these 24 outcomes, we were able to reproduce 83.3% of the published estimates using data at ClinicalTrials.gov. CONCLUSION:EXACT (http://bio-nlp.org/EXACT) automatically and accurately extracted data elements from ClinicalTrials.gov and thus reduced time in data extraction. The ClinicalTrials.gov data reproduced most meta-analysis results in our study, but this conclusion needs further validation.
| S-EPMC6887103 | biostudies-literature
Project description:BackgroundData monitoring committees advise on clinical trial conduct through appraisal of emerging data to ensure participant safety and scientific integrity. While consideration of their use is recommended for trials performed with vulnerable populations, previous research has shown that data monitoring committees are reported infrequently in publications of pediatric randomized controlled trials. We aimed to assess the frequency of reported data monitoring committee adoption in ClinicalTrials.gov registry records and to examine the influence of key trial characteristics.MethodsWe conducted a cross-sectional data analysis of all randomized controlled trials performed exclusively in a pediatric population and registered in ClinicalTrials.gov between 2008 and 2021. We used the Access to Aggregate Content of ClinicalTrials.gov database to retrieve publicly available information on trial characteristics and data on safety results. Abstracted data included reported trial design and conduct parameters, population and intervention characteristics, reasons for prematurely halting, serious adverse events, and mortality outcomes. We performed descriptive analyses on the collected data and explored the influence of clinical, methodological, and operational trial characteristics on the reported adoption of data monitoring committees.ResultsWe identified 13,928 pediatric randomized controlled trial records, of which 39.7% reported adopting a data monitoring committee, 49.0% reported not adopting a data monitoring committee, and 11.3% did not answer on this item. While the number of registered pediatric trials has been increasing since 2008, we found no clear time trend in the reported adoption of data monitoring committees. Data monitoring committees were more common in multicenter trials (50.6% vs 36.9% for single-center), multinational trials (60.2% vs 38.7% for single-country), National Institutes of Health-funded (60.3% vs 40.1% for industry-funded or 37.5% for other funders), and placebo-controlled (47.6% vs 37.5% for other types of control groups). Data monitoring committees were also more common among trials enrolling younger participants, trials employing blinding techniques, and larger trials. Data monitoring committees were more common in trials with at least one serious adverse event (52.6% vs 38.4% for those without) as well as for trials with reported deaths (70.3% vs 38.9% for trials without reported deaths). In all, 4.9% were listed as halted prematurely, most often due to low accrual rates. Trials with a data monitoring committee were more often halted for reasons related to scientific data than trials without a data monitoring committee (15.7% vs 7.3%).ConclusionAccording to registry records, the use of data monitoring committees in pediatric randomized controlled trials was more frequent than previously reported in reviews of published trial reports. The use of data monitoring committees varied across key clinical and trial characteristics based on which their use is recommended. Data monitoring committees may still be underutilized in pediatric trials, and reporting of this item could be improved.
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Project description:In Poland there are only Regional Bioethical Committees. Unlike most EU countries Poland has no coordinating centre on bioethics for human research. However, the Ministry of Health and Welfare has established a Bioethics Appeals Committee.The functioning of the Bioethical Committees in Poland is regulated in detail by the Regulation of the Ministry of Health and Welfare of 1999. All regulations comply with important guidelines such as: the Helsinki Declaration, The Rules of Good Clinical Practice, EU Directives and legal regulations binding in Poland, mainly the Act of the Medical Doctor Profession and the Dentist Profession, as well as the Act of Pharmaceutical Law.In the framework of the Human Biomonitoring Programme, the application for bioethical evaluation will be submitted to the Bioethical Committee at the Nofer Institute of Occupational Medicine in Lodz.The data protection legislation in Poland according to the Act of the Protection of Personal Data of 29th of August 1997 with latest amendments fulfils EU regulations. The Act also contains detailed provisions regarding the duties of the Inspector General for Data Protection. The paper presents data on the activities of the Bureau of the Inspector General for Personal Data Protection in 2005, 2006 and 2007.
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