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Prevalence of primary outcome changes in clinical trials registered on ClinicalTrials.gov: a cross-sectional study.

ABSTRACT: An important principle in the good conduct of clinical trials is that a summary of the trial protocol, with a pre-defined primary outcome, should be freely available before the study commences. The clinical trials registry ClinicalTrials.gov provides one method of doing this, and once the trial is registered, any changes made to the primary outcome are documented. The objectives of this study were: to assess the proportion of registered trials on ClinicalTrials.gov that had the primary outcome changed; to assess when the primary outcome was changed in relation to the listed study start and end dates and to assess whether the primary outcome change had any relation to the study sponsor.A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 25 October 2012 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date.Our analysis showed that 28229 of 89204 (31.7%) registered studies had their primary outcome changed. Industry funding was associated with all primary outcome changes, odds ratio (OR)= 1.36, 95% confidence interval (CI)=1.31-1.41, p<0.001; with primary outcome changes after study start date OR=1.37, 95% CI=1.32-1.42, p<0.001; with primary outcome changes after primary completion date OR=1.84, 95% CI=1.75-1.94, p<0.001 and with primary outcome changes after study completion date OR=1.82, 95% CI=1.73-1.91, p<0.001. Conclusions A significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. These changes are associated with funding source.

SUBMITTER: Ramagopalan S

PROVIDER: S-EPMC4032105 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Prevalence of primary outcome changes in clinical trials registered on ClinicalTrials.gov: a cross-sectional study.

Ramagopalan Sreeram S Skingsley Andrew P AP Handunnetthi Lahiru L Klingel Michelle M Magnus Daniel D Pakpoor Julia J Goldacre Ben B

F1000Research 20140326

<h4>Background</h4>An important principle in the good conduct of clinical trials is that a summary of the trial protocol, with a pre-defined primary outcome, should be freely available before the study commences. The clinical trials registry ClinicalTrials.gov provides one method of doing this, and once the trial is registered, any changes made to the primary outcome are documented. The objectives of this study were: to assess the proportion of registered trials on ClinicalTrials.gov that had th ...[more]

PMID: 25075294

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Project description:Objective: Clinical trials are the most effective way to judge the merits of diagnosis and treatment strategies. The in-depth mining of clinical trial data enables us to grasp the application trend of artificial intelligence (AI) for cancer diagnosis. The aim of this study was to analyze the characteristics of registered trials on AI for cancer diagnosis. Methods: Clinical trials on AI for cancer diagnosis registered on the ClinicalTrials.gov database were searched and downloaded. Statistical analysis was performed by using SPSS 20.0 software. Results: A total of 97 registered trials were included. Of them, only 27 (27.8%) were interventional trials and 70 (72.1%) were observational trials. Fifteen (15.4%) trials had been completed. Fifty trials were in recruitment, and another 18 remained unrecruited. The number of cases included in the clinical trials tended to be large, 31 (32.0%) trials including samples ranging from 100 to 499 cases and 17 (17.5%) trials including samples ranging from 500 to 999 cases. Of the 27 interventional trials, only two trials reported trials' phase. Most (85.2%) interventional trials were for diagnosis, and a few (3.7%) were for the purpose of both the diagnosis and therapy of cancers. For the observational clinical trials, 46 (65.7%) were cohort studies, and 11 (15.7%) were case-only studies. Among the observational trials, 46 (65.7%) were prospective studies and 13 (18.6%) were retrospective studies. Among 97 trials, 37 (38.1%) involved colorectal cancer, 11 (11.3%) involved breast cancer, 43 (44.3%) were for imaging diagnosis, 33 (34.0%) were for endoscopic diagnosis, and 11 (11.3%) were for pathological diagnosis. For the interventional trials, 11 trials were parallel assignment (40.7%), and 14 were single group assignment (51.9%). Among the 27 interventional trials, 18 (66.7%) trials were performed without masking, 6 (22.2%) trials were performed with single masking, only 1 (3.7%) was performed with double masking, and 2 (7.4%) was performed with triple masking. Conclusion: It appears that most registered trials on AI for cancer diagnosis are observational design, and more trials are needed in this field.

Project description:Background:Interventional clinical trials for infectious diseases in old population have arisen much attention in recent years, however, little is known about the characteristics of registered clinical trials regarding this field. This study aimed to investigate the characteristics of registered interventional trials for infectious diseases in old populations on ClinicalTrials.gov. Methods:A cross-sectional study was performed. We used viral OR bacterial OR fungal OR parasitic OR infectious disease to search the ClinicalTrials.gov database and to assess characteristics of included trials. The age of participants was restricted to more than 65 years old. All analyses were performed using the SPSS19.0 software. Results:A total of 138 registered trials were included. Among them, 105(76.1%) trials were completed; however, the results were available in ClinicalTrials.gov for only 44(31.9%) trials. North America was the most frequently identified study location (52.9%), followed by Europe (30.4%) and Asia (11.6%). Seventy-one percent trials focused on viral pathogens, followed by bacterial pathogens (22.5%). A total of 84.1% trials were prevention oriented. A total of 84.1% trials used randomization, 73.2% trials used parallel assignment, and 64.5% used masking. Eighty-six trials were industry-funded and 52 were non-industry-funded. Industry-funded trials had higher percentages than non-industry-funded trials in available results, prevention trial, and phase 2 and phase 3 trial, and lager sample size trial. One hundred eleven trials were vaccine trials and 27 trials were non-vaccine trials. Vaccine trials had higher percentages than non-vaccine trials in available results, leading industry sponsor and viral etiology. Conclusions:The current study is the first study of the landscape of interventional clinical trials for infectious diseases in old populations registered in ClinicalTrials.gov, providing the basis for treatment and prevention of infectious diseases in old populations. Trials in this field are still relatively lacking, and additional and better trials are needed.

Project description:Objective: It is important to register clinical trials before their implementation. There is a lack of study to evaluate registered clinical trials of stem cell therapy for heart diseases. Our study used the registration information at ClinicalTrials.gov to provide an overview of the registered trials investigating stem cell therapy for heart diseases. Methods: We searched ClinicalTrials.gov from inception to October 1, 2020 to identify clinical trials evaluating stem cell therapy for heart diseases. These trials were included in a cross-sectional survey and descriptive analysis. The outcomes included start date, completion date, location, status, study results, funding, phase, study design, conditions, interventions, sex, age, and sample size of those trials, as well as conditions, efficacy, safety and samples of the publications. SPSS 24.0 software was used for the statistical analysis. Results: A total of 241 trials were included. The registration applications for most trials originated from the United States, and the research start date ranged from 2001 to 2025. More than half of the trials have been completed, but few trials have published results (15.62%). The funding source for 81.12% of trials was recorded as "other" because the specific funding source was not indicated. There were 226 (93.78%) interventional studies and 15 (6.22%) observational studies; among all 241 studies, only 2.90% were phase 4 trials. Most interventional studies used randomized allocation, parallel assignment, and blinding. Of the observational studies, 6 were cohort studies (40.00%) and 73.33% were prospective. The most common disease was coronary artery disease (57.68%) and 98.34% included both male and female participants. The sample size included fewer than 50 patients in 58.51% of trials, and only 18 trials (7.47%) lasted more than 121 months. The registered details were illogical for nine trials (3.8%) that included 0 subjects and two trials (0.8%) that had a duration of 0 months (0.8%). In term of publications of the trials, most of the publications of the trials showed efficacy and safety in stem cell therapy for heart disease. Conclusion: The clinical trials investigating stem cell therapy for heart diseases registered at ClinicalTrials.gov are mostly interventional studies, and only a few are phase 4 trials. Most trials have a small sample size, and few have a duration of more than 121 months. Most of the completed trials did not publish their results, and some of the registration information was incomplete and illogical.

Project description:Morbidity and mortality associated with COVID-19 has increased exponentially, and patients with cardiovascular (CV) disease are at risk for poor outcomes. Several lines of evidence suggest a potential role for CV therapies in COVID-19 treatment. Characteristics of clinical trials of CV therapies related to COVID-19 registered on ClinicalTrials.gov have not been described.MethodsClinicalTrials.gov was queried on August 7, 2020 for COVID-19 related trials. Studies evaluating established CV drugs, other fibrinolytics (defibrotide), and extracorporeal membrane oxygenation were included. Studies evaluating anti-microbial, convalescent plasma, non-colchicine anti-inflammatory, and other therapies were excluded. Trial characteristics were tabulated from study-specific entries.ResultsA total of 2,935 studies related to COVID-19 were registered as of August 7, 2020. Of these, 1,645 were interventional studies, and the final analytic cohort consisted of 114 studies evaluating 10 CV therapeutic categories. Antithrombotics (32.5%; n = 37) were most commonly evaluated, followed by pulmonary vasodilators (14.0%; n = 16), renin-angiotensin-aldosterone system-related therapies (12.3%; n = 14), and colchicine (8.8%; n = 10). Trials evaluating multiple CV therapy categories and CV therapies in combination with non-CV therapies encompassed 4.4% (n = 5) and 9.6% (n = 11) of studies, respectively. Most studies were designed for randomized allocation (87.7%; n = 100), enrollment of less than 1000 participants (86.8%; n = 99), single site implementation (55.3%; n = 63), and had a primary outcome of mortality or a composite including mortality (56.1%; n = 64). Most study populations consisted of patients hospitalized with COVID-19 (81.6%; n = 93). At the time of database query, 28.9% (n = 33) of studies were not yet recruiting and the majority were estimated to be completed after December 2020 (67.8%; n = 78). Most lead sponsors were located in North America (43.9%; n = 50) or Europe (36.0%; n = 41).ConclusionsA minority (7%) of clinical trials related to COVID-19 registered on ClinicalTrials.gov plan to evaluate CV therapies. Of CV therapy studies, most were planned to be single center, enroll less than 1000 inpatients, sponsored by European or North American academic institutions, and estimated to complete after December 2020. Collectively, these findings underscore the need for a network of sites with a platform protocol for rapid evaluation of multiple therapies and generalizability to inform clinical care and health policy for COVID-19 moving forward.

Project description:BackgroundThe development of mobile health (mHealth) technologies is progressing at a faster pace than that of the science to evaluate their validity and efficacy. Under the International Committee of Journal Medical Editors (ICMJE) guidelines, clinical trials that prospectively assign people to interventions should be registered with a database before the initiation of the study.ObjectiveThe aim of this study was to better understand the smartphone mHealth trials for high-burden neuropsychiatric conditions registered on ClinicalTrials.gov through November 2018, including the number, types, and characteristics of the studies being conducted; the frequency and timing of any outcome changes; and the reporting of results.MethodsWe conducted a systematic search of ClinicalTrials.gov for the top 10 most disabling neuropsychiatric conditions and prespecified terms related to mHealth. According to the 2016 World Health Organization Global Burden of Disease Study, the top 10 most disabling neuropsychiatric conditions are (1) stroke, (2) migraine, (3) major depressive disorder, (4) Alzheimer disease and other dementias, (5) anxiety disorders, (6) alcohol use disorders, (7) opioid use disorders, (8) epilepsy, (9) schizophrenia, and (10) other mental and substance use disorders. There were no date, location, or status restrictions.ResultsOur search identified 135 studies. A total of 28.9% (39/135) of studies evaluated interventions for major depressive disorder, 14.1% (19/135) of studies evaluated interventions for alcohol use disorders, 12.6% (17/135) of studies evaluated interventions for stroke, 11.1% (15/135) of studies evaluated interventions for schizophrenia, 8.1% (11/135) of studies evaluated interventions for anxiety disorders, 8.1% (11/135) of studies evaluated interventions for other mental and substance use disorders, 7.4% (10/135) of studies evaluated interventions for opioid use disorders, 3.7% (5/135) of studies evaluated interventions for Alzheimer disease or other dementias, 3.0% (4/135) of studies evaluated interventions for epilepsy, and 3.0% (4/135) of studies evaluated interventions for migraine. The studies were first registered in 2008; more than half of the studies were registered from 2016 to 2018. A total of 18.5% (25/135) of trials had results reported in some publicly accessible location. Across all the studies, the mean estimated enrollment (reported by the study) was 1078, although the median was only 100. In addition, across all the studies, the actual reported enrollment was lower, with a mean of 249 and a median of 80. Only about a quarter of the studies (35/135, 25.9%) were funded by the National Institutes of Health.ConclusionsDespite the increasing use of health-based technologies, this analysis of ClinicalTrials.gov suggests that only a few apps for high-burden neuropsychiatric conditions are being clinically evaluated in trials.

Project description:ImportanceSARS-CoV-2 has infected over 200 million people worldwide, resulting in more than 4 million deaths. Randomized controlled trials are the single best tool to identify effective treatments against this novel pathogen.ObjectiveTo describe the characteristics of randomized controlled trials of treatments for COVID-19 in the United States launched in the first 9 months of the pandemic. Design, Setting, and Participants We conducted a cross-sectional study of all completed or actively enrolling randomized, interventional, clinical trials for the treatment of COVID-19 in the United States registered on www.clinicaltrials.gov as of August 10, 2020. We excluded trials of vaccines and other interventions intended to prevent COVID-19. Main Outcomes and Measures We used descriptive statistics to characterize the clinical trials and the statistical power for the available studies. For the late-phase trials (i.e., phase 3 and 2/3 studies), we compared the geographic distribution of the clinical trials with the geographic distribution of people diagnosed with COVID-19.ResultsWe identified 200 randomized controlled trials of treatments for people with COVID-19. Across all trials, 87 (43.5%) were single-center, 64 (32.0%) were unblinded, and 80 (40.0%) were sponsored by industry. The most common treatments included monoclonal antibodies (N=46 trials), small molecule immunomodulators (N=28), antiviral medications (N=24 trials), and hydroxychloroquine (N=20 trials). Of the 9 trials completed by August 2020, the median sample size was 450 (IQR 67-1113); of the 191 ongoing trials, the median planned sample size was 150 (IQR 60-400). Of the late-phase trials (N=54), the most common primary outcome was a severity scale (N=23, 42.6%), followed by a composite of mortality and ventilation (N=10, 18.5%), and mortality alone (N=6, 11.1%). Among these late-phase trials, all trials of antivirals, monoclonal antibodies, or chloroquine/hydroxychloroquine had a power of less than 25% to detect a 20% relative risk reduction in mortality. Had the individual trials for a given class of treatments instead formed a single trial, the power to detect that same reduction in mortality would have been greater than 98%. There was large variability in access to trials with the highest number of trials per capita in the Northeast and the lowest in the Midwest.Conclusions and relevanceA large number of randomized trials were launched early in the pandemic to evaluate treatments for COVID-19. However, many trials were underpowered for important clinical endpoints and substantial geographic disparities were observed, highlighting the importance of improving national clinical trial infrastructure.

Project description:ImportanceFor findings from clinical trials to be actionable, outcomes measured in trials must be fully defined and, when appropriate, defined consistently across trials. Otherwise, it is difficult to compare findings between trials, combine results in meta-analyses, or leverage findings collectively to inform health care decision-making.ObjectiveTo identify and characterize outcomes specified in ClinicalTrials.gov records for publicly funded clinical trials for 3 high-burden, high-prevalence eye conditions.Design, setting, and participantsClinicalTrials.gov, a registry of publicly and privately supported clinical studies, was searched on January 31, 2019, for records of clinical trials for age-related macular degeneration (AMD), dry eye, or refractive error. The search was limited to trials funded by the National Eye Institute but did not impose a date restriction. Five elements of a well-specified outcome were extracted from each outcome stated in each record, including the domain, method of measurement, metric, method of aggregation, and time points.Main outcomes and measuresNumber of outcome domains specified for trials for AMD, dry eye, and refractive error and the number of trial records specifying each unique domain.ResultsA total of 49 unique outcome domains specified across 39 records of trials were identified. The median (interquartile range) number of records specifying each unique outcome domain was 1 (1-3), 1.5 (1-2), and 1 (1-1) for AMD, dry eye, and refractive error, respectively. Even when the same domains were registered across multiple trials, the time point, specific metric, and method of aggregation were specified in multiple ways.Conclusions and relevanceThere were too many outcomes with too little overlap in the sample of trials that were examined. Differences in how outcomes are measured across trials make it difficult to compare results, even for well-established domains, such as visual acuity. To reduce this waste in eye and vision research, the time is ripe for agreeing on what outcomes to measure.

Dataset Information

Prevalence of primary outcome changes in clinical trials registered on ClinicalTrials.gov: a cross-sectional study.

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Prevalence of primary outcome changes in clinical trials registered on ClinicalTrials.gov: a cross-sectional study.

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