Comparison of Availability of Trial Results in ClinicalTrials.gov and PubMed by Data Source and Funder Type.
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ABSTRACT:
SUBMITTER: Nelson JT
PROVIDER: S-EPMC10064282 | biostudies-literature | 2023 Apr
REPOSITORIES: biostudies-literature
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Comparison of Availability of Trial Results in ClinicalTrials.gov and PubMed by Data Source and Funder Type.
Nelson Julianne T JT Tse Tony T Puplampu-Dove Yvonne Y Golfinopoulos Elisa E Zarin Deborah A DA
JAMA 20230401 16
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Project description:OBJECTIVE:To investigate the distribution, design characteristics, and dissemination of clinical trials by funding organisation and medical specialty. DESIGN:Cross sectional descriptive analysis. DATA SOURCES:Trial 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 CRITERIA:All 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. RESULTS:Industry 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. CONCLUSIONS:Trial design and dissemination of results vary substantially depending on the type and size of funding institution as well as the disease area under study.
| S-EPMC5989153 | biostudies-literature
Project description:ObjectiveIn an effort to understand how results of human clinical trials are made public, we analyze a large set of clinical trials registered at ClinicalTrials.gov, the world's largest clinical trial registry.Materials and methodsWe considered two trial result artifacts: (1) existence of a trial result journal article that is formally linked to a registered trial or (2) the deposition of a trial's basic summary results within the registry.ResultsThe study sample consisted of 8907 completed, interventional, phase 2-or-higher clinical trials that were completed in 2006-2009. The majority of trials (72.2%) had no structured trial-article link present. A total of 2367 trials (26.6%) deposited basic summary results within the registry. Of those, 969 trials (10.9%) were classified as trials with extended results and 1398 trials (15.7%) were classified as trials with only required basic results. The majority of the trials (54.8%) had no evidence of results, based on either linked result articles or basic summary results (silent trials), while a minimal number (9.2%) report results through both registry deposition and publication.DiscussionOur study analyzes the body of linked knowledge around clinical trials (which we refer to as the "trialome"). Our results show that most trials do not report results and, for those that do, there is minimal overlap in the types of reporting. We identify several mechanisms by which the linkages between trials and their published results can be increased.ConclusionOur study shows that even when combining publications and registry results, and despite availability of several information channels, trial sponsors do not sufficiently meet the mandate to inform the public either via a linked result publication or basic results submission.
| S-EPMC3706420 | biostudies-literature
Project description:BackgroundImplementing semi-automated processes to efficiently match patients to clinical trials at the point of care requires both detailed patient data and authoritative information about open studies.ObjectiveTo evaluate the utility of the ClinicalTrials.gov registry as a data source for semi-automated trial eligibility screening.MethodsEligibility criteria and metadata for 437 trials open for recruitment in four different clinical domains were identified in ClinicalTrials.gov. Trials were evaluated for up to date recruitment status and eligibility criteria were evaluated for obstacles to automated interpretation. Finally, phone or email outreach to coordinators at a subset of the trials was made to assess the accuracy of contact details and recruitment status.Results24% (104 of 437) of trials declaring on open recruitment status list a study completion date in the past, indicating out of date records. Substantial barriers to automated eligibility interpretation in free form text are present in 81% to up to 94% of all trials. We were unable to contact coordinators at 31% (45 of 146) of the trials in the subset, either by phone or by email. Only 53% (74 of 146) would confirm that they were still recruiting patients.ConclusionBecause ClinicalTrials.gov has entries on most US and many international trials, the registry could be repurposed as a comprehensive trial matching data source. Semi-automated point of care recruitment would be facilitated by matching the registry's eligibility criteria against clinical data from electronic health records. But the current entries fall short. Ultimately, improved techniques in natural language processing will facilitate semi-automated complex matching. As immediate next steps, we recommend augmenting ClinicalTrials.gov data entry forms to capture key eligibility criteria in a simple, structured format.
| S-EPMC4205089 | biostudies-literature
Project description:BackgroundClinical trials that end prematurely (or "terminate") raise financial, ethical, and scientific concerns. The extent to which the results of such trials are disseminated and the reasons for termination have not been well characterized.Methods and findingsA cross-sectional, descriptive study of terminated clinical trials posted on the ClinicalTrials.gov results database as of February 2013 was conducted. The main outcomes were to characterize the availability of primary outcome data on ClinicalTrials.gov and in the published literature and to identify the reasons for trial termination. Approximately 12% of trials with results posted on the ClinicalTrials.gov results database (905/7,646) were terminated. Most trials were terminated for reasons other than accumulated data from the trial (68%; 619/905), with an insufficient rate of accrual being the lead reason for termination among these trials (57%; 350/619). Of the remaining trials, 21% (193/905) were terminated based on data from the trial (findings of efficacy or toxicity) and 10% (93/905) did not specify a reason. Overall, data for a primary outcome measure were available on ClinicalTrials.gov and in the published literature for 72% (648/905) and 22% (198/905) of trials, respectively. Primary outcome data were reported on the ClinicalTrials.gov results database and in the published literature more frequently (91% and 46%, respectively) when the decision to terminate was based on data from the trial.ConclusionsTrials terminate for a variety of reasons, not all of which reflect failures in the process or an inability to achieve the intended goals. Primary outcome data were reported most often when termination was based on data from the trial. Further research is needed to identify best practices for disseminating the experience and data resulting from terminated trials in order to help ensure maximal societal benefit from the investments of trial participants and others involved with the study.
| S-EPMC4444136 | biostudies-literature
Project description:BackgroundPancreatic cancer (PC) is a highly malignant tumor of the digestive system. As clinical trials involving PC are increasingly being conducted, the transparency of the generated data has become an important issue of concern. In other areas of medicine, clinical trial transparency presents a worrying state of affairs. However, at present, there has been no study examining the transparency of data derived from PC clinical trials.MethodsA comprehensive search was conducted in the ClinicalTrial.gov database for clinical trials investigating pancreatic cancer as of June 2022. We examined the availability of clinical trial results and recorded the characteristics of the trials.ResultsA total of 856 trials were included in this study, of which 668 were completed and 188 were terminated or suspended. The results of 626 trials (73.13%) were available, of these 230 trials (26.87%) did not disclose any information on the trial data in any form. The publication rate for trials with available results was 86.10%, but the report rate on ClinicalTrial.gov was only 39.78%.ConclusionAlthough approximately 90% of clinical trial investigating interventions on patients with PC have published study results, 30% of trials did not report any findings, and the disclosure of trial results from ClinicalTrial.gov was unsatisfactory. In general, there is still room for improvement in the transparency of PC clinical trials.
| S-EPMC9853913 | biostudies-literature
Project description:One of the goals of translational science is to shorten the time from discovery to clinical use. Clinical trial registries were established to increase transparency in completed and ongoing clinical trials, and they support linking trials with resulting publications. We set out to investigate precision and negative predictive value (NPV) of links between ClinicalTrials.gov (CT.gov) and PubMed. CT.gov has been established to increase transparency in clinical trials and the link to PubMed is crucial for supporting a number of important functions, including ascertaining publication bias. We drew a random sample of trials downloaded from CT.gov and performed manual review of retrieved publications. We characterize two types of links between trials and publications (NCT-link originating from MEDLINE and PMID-link originating from CT.gov).The link precision is different based on type (NCT-link: 100%; PMID-link: 63% to 96%). In trials with no linked publication, we were able to find publications 44% of the time (NPV=56%) by searching PubMed. This low NPV shows that there are potentially numerous publications that should have been formally linked with the trials. Our results indicate that existing trial registry and publisher policies may not be fully enforced. We suggest some automated methods for improving link quality.
| S-EPMC3540528 | biostudies-literature
Project description:Growth of the open science movement has drawn significant attention to data sharing and availability across the scientific community. In this study, we tested the ability to recover data collected under a particular funder-imposed requirement of public availability. We assessed overall data recovery success, tested whether characteristics of the data or data creator were indicators of recovery success, and identified hurdles to data recovery. Overall the majority of data were not recovered (26% recovery of 315 data projects), a similar result to journal-driven efforts to recover data. Field of research was the most important indicator of recovery success, but neither home agency sector nor age of data were determinants of recovery. While we did not find a relationship between recovery of data and age of data, age did predict whether we could find contact information for the grantee. The main hurdles to data recovery included those associated with communication with the researcher; loss of contact with the data creator accounted for half (50%) of unrecoverable datasets, and unavailability of contact information accounted for 35% of unrecoverable datasets. Overall, our results suggest that funding agencies and journals face similar challenges to enforcement of data requirements. We advocate that funding agencies could improve the availability of the data they fund by dedicating more resources to enforcing compliance with data requirements, providing data-sharing tools and technical support to awardees, and administering stricter consequences for those who ignore data sharing preconditions.
| S-EPMC6034829 | biostudies-literature
Project description:A substantial proportion of trial registrations are not linked to corresponding published articles, limiting analyses and new tools. Our aim was to develop a method for finding articles reporting the results of trials that are registered on ClinicalTrials.gov when they do not include metadata links. We used a set of 27,280 trial registration and article pairs to train and evaluate methods for identifying missing links in both directions-from articles to registrations and from registrations to articles. We trained a classifier with six distance metrics as feature representations to rank the correct article or registration, using recall@K to evaluate performance and compare to baseline methods. When identifying links from registrations to published articles, the classifier ranked the correct article first (recall@1) among 378,048 articles in 80.8% of evaluation cases and 34.9% in the baseline method. Recall@10 was 85.1% compared to 60.7% in the baseline. When predicting links from articles to registrations, recall@1 was 83.4% for the classifier and 39.8% in the baseline. Recall@10 was 89.5% compared to 65.8% in the baseline. The proposed method improves on our baseline document similarity method to be feasible for identifying missing links in practice. Given a ClinicalTrials.gov registration, a user checking 10 ranked articles can expect to identify the matching article in at least 85% of cases, if the trial has been published. The proposed method can be used to improve the coupling of ClinicalTrials.gov and PubMed, with applications related to automating systematic review and evidence synthesis processes.
| S-EPMC9090946 | biostudies-literature
Project description:Randomized controlled trials are essential for evaluating clinical interventions; however, selective reporting and publication bias in medical journals have undermined the integrity of the clinical evidence system. ClinicalTrials.gov serves as a valuable and complementary repository, yet synthesizing information from it remains challenging. This study introduces a curated dataset that extends beyond the traditional PICO framework. It links efficacy with safety results at the experimental arm group level within each trial, and connects them across all trials through a knowledge graph. This novel representation effectively bridges the gap between generally described searchable information and specifically detailed yet underutilized reported results, and promotes a dual-faceted understanding of interventional effects. Adhering to the "calculate once, use many times" principle, the structured dataset will enhance the reuse and interpretation of ClinicalTrials.gov results data. It aims to facilitate more systematic evidence synthesis and health technology assessment, by incorporating both positive and negative results, distinguishing biomarkers, patient-reported outcomes, and clinical endpoints, while also balancing both efficacy and safety outcomes for a given medical intervention.
| S-EPMC10771511 | biostudies-literature
Project description:BackgroundPharmaceutical companies and other trial sponsors must submit certain trial results to ClinicalTrials.gov. The validity of these results is unclear.PurposeTo validate results posted on ClinicalTrials.gov against publicly available U.S. Food and Drug Administration (FDA) reviews on Drugs@FDA.Data sourcesClinicalTrials.gov (registry and results database) and Drugs@FDA (medical and statistical reviews).Study selection100 parallel-group, randomized trials for new drug approvals (January 2013 to July 2014) with results posted on ClinicalTrials.gov (15 March 2015).Data extraction2 assessors extracted, and another verified, the trial design, primary and secondary outcomes, adverse events, and deaths.ResultsMost trials were phase 3 (90%), double-blind (92%), and placebo-controlled (73%) and involved 32 drugs from 24 companies. Of 137 primary outcomes identified from ClinicalTrials.gov, 134 (98%) had corresponding data at Drugs@FDA, 130 (95%) had concordant definitions, and 107 (78%) had concordant results. Most differences were nominal (that is, relative difference <10%). Primary outcome results in 14 trials could not be validated. Of 1927 secondary outcomes from ClinicalTrials.gov, Drugs@FDA mentioned 1061 (55%) and included results data for 367 (19%). Of 96 trials with 1 or more serious adverse events in either source, 14 could be compared and 7 had discordant numbers of persons experiencing the adverse events. Of 62 trials with 1 or more deaths in either source, 25 could be compared and 17 were discordant.LimitationUnknown generalizability to uncontrolled or crossover trial results.ConclusionPrimary outcome definitions and results were largely concordant between ClinicalTrials.gov and Drugs@FDA. Half the secondary outcomes, as well as serious events and deaths, could not be validated because Drugs@FDA includes only "key outcomes" for regulatory decision making and frequently includes only adverse event results aggregated across multiple trials.Primary funding sourceNational Library of Medicine.
| S-EPMC5028264 | biostudies-literature