Sharing of Individual Patient-Level Data by Trialists of Randomized Clinical Trials of Pharmacological Treatments for COVID-19.
Ontology highlight
ABSTRACT:
SUBMITTER: Esmail LC
PROVIDER: S-EPMC10071396 | biostudies-literature | 2023 May
REPOSITORIES: biostudies-literature
Publications
Sharing of Individual Patient-Level Data by Trialists of Randomized Clinical Trials of Pharmacological Treatments for COVID-19.
Esmail Laura C LC Kapp Philipp P Assi Rouba R Wood Julie J Regan Gabriela G Ravaud Philippe P Boutron Isabelle I
JAMA 20230501 19
Similar Datasets
Project description:There are numerous benefits to the research community from data sharing, and yet the open sharing of participant level data is not without potential pitfalls. In addition to the scientific community, the interests of study participants who volunteered their data must be considered, along with the interests of study investigators who expend a substantial amount of effort into the design, conduct, and analytical plans for the study. The National Heart, Lung, and Blood Institute (NHLBI) has developed a data-sharing protocol focused on balancing the interests of study participants, study investigators, and the research community with independent oversight by the NHLBI IRB. The data repository presently includes individual level data on more than 560,000 participants from 100 Institute-supported clinical trials and observational studies.
| S-EPMC3750470 | biostudies-literature
Project description:ObjectivesMeta-analysis based on individual patient data (IPD) from randomised trials is superior to using published summary data since it facilitates subgroup and multiple variable analyses. Guidelines and funders expect that researchers share IPD for bona fide analyses, but in practice, this is done variably. Here, we report the experience of obtaining IPD for two collaborative analysis studies.SettingTwo linked studies required IPD from published randomised trials. The leading researchers for eligible trials were approached and asked to share IPD including trial characteristics, patient demographics, baseline clinical data and outcome measures.ParticipantsParticipants in eligible randomised controlled trials included patients with or at risk of cognitive decline/vascular events.Primary and secondary outcome measuresNumbers (%) of trials where the leading researcher responded favourably/negatively or did not respond. If negative, reasons behind the response were collected. If positive, methods used to share IPD were recorded.ResultsAcross the two studies, 391 completed trials were identified. Email addresses for researchers were found for 313 (80%) of the trials. One hundred and forty-eight (47%) researchers did not respond despite being sent multiple emails. Following contact, positive initial responses were received from 92 researchers, resulting in IPD being shared for 78 trials. Eighty-seven (28%) researchers declined to share data; justifications were recorded. The median time from first request to accessing data in one study was 241 (IQR 383.3) days. IPD sources included: direct from researcher, via academic trial funders repository and a website requiring remote analysis of commercial data. Where data were shared, a variety of methods were used to transfer data.ConclusionSharing of IPD from trials is desirable and a requirement of many funding bodies. However, accessing IPD faces multiple challenges including refusals to share, delays in access to data and having to perform analyses on a remote website.Trial registrationNot applicable.
| S-EPMC7482449 | biostudies-literature
Project description:ObjectiveTo investigate clinical trialists' opinions and experiences of sharing of clinical trial data with investigators who are not directly collaborating with the research team.Design and settingCross sectional, web based survey.ParticipantsClinical trialists who were corresponding authors of clinical trials published in 2010 or 2011 in one of six general medical journals with the highest impact factor in 2011.Main outcome measuresSupport for and prevalence of data sharing through data repositories and in response to individual requests, concerns with data sharing through repositories, and reasons for granting or denying requests.ResultsOf 683 potential respondents, 317 completed the survey (response rate 46%). In principle, 236 (74%) thought that sharing de-identified data through data repositories should be required, and 229 (72%) thought that investigators should be required to share de-identified data in response to individual requests. In practice, only 56 (18%) indicated that they were required by the trial funder to deposit the trial data in a repository; of these 32 (57%) had done so. In all, 149 respondents (47%) had received an individual request to share their clinical trial data; of these, 115 (77%) had granted and 56 (38%) had denied at least one request. Respondents' most common concerns about data sharing were related to appropriate data use, investigator or funder interests, and protection of research subjects.ConclusionsWe found strong support for sharing clinical trial data among corresponding authors of recently published trials in high impact general medical journals who responded to our survey, including a willingness to share data, although several practical concerns were identified.
| S-EPMC3502744 | biostudies-literature
Project description:Inhaled nitric oxide (iNO) is an effective therapy for pulmonary hypertension and hypoxic respiratory failure in term infants. Fourteen randomized controlled trials (n = 3430 infants) have been conducted on preterm infants at risk for chronic lung disease (CLD). The study results seem contradictory.Individual-patient data meta-analysis included randomized controlled trials of preterm infants (<37 weeks' gestation). Outcomes were adjusted for trial differences and correlation between siblings.Data from 3298 infants in 12 trials (96%) were analyzed. There was no statistically significant effect of iNO on death or CLD (59% vs 61%: relative risk [RR]: 0.96 [95% confidence interval (CI): 0.92-1.01]; P = .11) or severe neurologic events on imaging (25% vs 23%: RR: 1.12 [95% CI: 0.98-1.28]; P = .09). There were no statistically significant differences in iNO effect according to any of the patient-level characteristics tested. In trials that used a starting iNO dose of >5 vs ? 5 ppm there was evidence of improved outcome (interaction P = .02); however, these differences were not observed at other levels of exposure to iNO. This result was driven primarily by 1 trial, which also differed according to overall dose, duration, timing, and indication for treatment; a significant reduction in death or CLD (RR: 0.85 [95% CI: 0.74-0.98]) was found.Routine use of iNO for treatment of respiratory failure in preterm infants cannot be recommended. The use of a higher starting dose might be associated with improved outcome, but because there were differences in the designs of these trials, it requires further examination.
| S-EPMC3387905 | biostudies-other
Project description:BackgroundThe purpose of clinical trials of acupuncture is to help clinicians and patients make decisions about treatment. Yet this is not straightforward: some trials report acupuncture to be superior to sham (placebo) acupuncture while others show evidence that acupuncture is superior to usual care but not sham, and still others conclude that acupuncture is no better than usual care. Meta-analyses of these trials tend to come to somewhat indeterminate conclusions. This appears to be because, until recently, acupuncture research was dominated by small trials of questionable quality. The Acupuncture Trialists' Collaboration, a group of trialists, statisticians and other researchers, was established to synthesize patient-level data from several recently published large, high-quality trials.MethodsThere are three distinct phases to the Acupuncture Trialists Collaboration: a systematic review to identify eligible studies; collation and harmonization of raw data; statistical analysis. To be eligible, trials must have unambiguous allocation concealment. Eligible pain conditions are osteoarthritis; chronic headache (tension or migraine headache); shoulder pain; and non-specific back or neck pain. Once received, patient-level data will undergo quality checks and the results of prior publications will be replicated. The primary analysis will be to determine the effect size of acupuncture. Each trial will be evaluated by analysis of covariance with the principal endpoint as the dependent variable and, as covariates, the baseline score for the principal endpoint and the variables used to stratify randomization. The effect size for acupuncture from each trial--that is, the coefficient and standard error from the analysis of covariance--will then be entered into a meta-analysis. We will compute effect sizes separately for comparisons of acupuncture with sham acupuncture, and acupuncture with no acupuncture control for each pain condition. Other analyses will investigate the impact of different sham techniques, styles of acupuncture or frequency and duration of treatment sessions.DiscussionIndividual patient data meta-analysis of high-quality trials will provide the most reliable basis for treatment decisions about acupuncture. Above all, however, we hope that our approach can serve as a model for future studies in acupuncture and other complementary therapies.
| S-EPMC2955653 | biostudies-literature
Project description:BackgroundThere are an estimated 200,000 to 400,000 cases of visceral leishmaniasis (VL) annually. A variety of factors are taken into account when considering the best therapeutic options to cure a patient and reduce the risk of resistance, including geographical area, malnourishment and HIV coinfection. Pooled analyses combine data from many studies to answer specific scientific questions that cannot be answered with individual studies alone. However, the heterogeneity of study design, data collection, and analysis often makes direct comparison difficult. Individual Participant Data (IPD) files can be standardised and analysed, allowing detailed analysis of this merged larger pool, but only a small fraction of systematic reviews and meta-analyses currently employ pooled analysis of IPD. We conducted a systematic literature review to identify published studies and studies reported in clinical trial registries to assess the feasibility of developing a VL data sharing platform to facilitate an IPD-based analysis of clinical trial data. Studies conducted between 1983 to 2015 that reported treatment outcome were eligible.Principal findingsFrom the 2,271 documents screened, 145 published VL clinical trials were identified, with data from 26,986 patients. Methodologies varied for diagnosis and treatment outcomes, but overall the volume of data potentially available on different drugs and dose regimens identified hundreds or possibly thousands of patients per arm suitable for IPD pooled meta-analyses.ConclusionsA VL data sharing platform would provide an opportunity to maximise scientific use of available data to enable assessment of treatment efficacy, contribute to evidence-based clinical management and guide optimal prospective data collection.
| S-EPMC5600407 | biostudies-literature
Project description:BackgroundIncreasingly, biomedical researchers are encouraged or required by research funders and journals to share their data, but there's very little guidance on how to do that equitably and usefully, especially in resource-constrained settings. We performed an in-depth case study of one data sharing pioneer: the WorldWide Antimalarial Resistance Network (WWARN).MethodsThe case study included a records review, a quantitative analysis of WAARN-related publications, in-depth interviews with 47 people familiar with WWARN, and a witness seminar involving a sub-set of 11 interviewees.ResultsWWARN originally aimed to collate clinical, in vitro, pharmacological and molecular data into linked, open-access databases intended to serve as a public resource to guide antimalarial drug treatment policies. Our study describes how WWARN navigated challenging institutional and academic incentive structures, alongside funders' reluctance to invest in capacity building in malaria-endemic countries, which impeded data sharing. The network increased data contributions by focusing on providing free, online tools to improve the quality and efficiency of data collection, and by inviting collaborative authorship on papers addressing policy-relevant questions that could only be answered through pooled analyses. By July 1, 2016, the database included standardised data from 103 molecular studies and 186 clinical trials, representing 135,000 individual patients. Developing the database took longer and cost more than anticipated, and efforts to increase equity for data contributors are on-going. However, analyses of the pooled data have generated new methods and influenced malaria treatment recommendations globally. Despite not achieving the initial goal of real-time surveillance, WWARN has developed strong data governance and curation tools, which are now being adapted relatively quickly for other diseases.ConclusionsTo be useful, data sharing requires investment in long-term infrastructure. To be feasible, it requires new incentive structures that favour the generation of reusable knowledge.
| S-EPMC5627501 | biostudies-literature
Project description:We created a database of reconstructed patient-level data from published clinical trials that includes multiple time-to-event outcomes such as overall survival and progression-free survival. Outcomes were extracted from Kaplan-Meier (KM) curves reported in 153 oncology Phase III clinical trial publications identified through a PubMed search of clinical trials in breast, lung, prostate and colorectal cancer, published between 2014 and 2016. For each trial that met our search criteria, we curated study-level information and digitized all reported KM curves with the software Digitizelt. We then used the digitized KM survival curves to estimate (possibly censored) patient-level time-to-event outcomes. Collections of time-to-event datasets from completed trials can be used to support the choice of appropriate trial designs for future clinical studies. Patient-level data allow investigators to tailor clinical trial designs to diseases and classes of treatments. Patient-level data also allow investigators to estimate the operating characteristics (e.g. power and type I error rate) of candidate statistical designs and methods. Database URL: https://10.6084/m9.figshare.14642247.v1.
| S-EPMC8234134 | biostudies-literature
Project description:Background: In recent years, a cultural change in the handling of research data has resulted in the promotion of a culture of openness and an increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services and tools to support data sharing are becoming available, but what is missing is a detailed, structured and comprehensive list of processes and subprocesses involved and the tools and services needed. Methods: Principles and recommendations from a published consensus document on data sharing were analysed in detail by a small expert group. Processes and subprocesses involved in data sharing were identified and linked to actors and possible supporting services and tools. Definitions adapted from the business process model and notation (BPMN) were applied in the analysis. Results: A detailed and comprehensive tabulation of individual processes and subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools and services to support these processes are identified and grouped according to the major type of support. Conclusions: The identification of the individual processes and subprocesses and supporting tools and services, is a first step towards development of a generic framework or architecture for the sharing of data from clinical trials. Such a framework is needed to provide an overview of how the various actors, research processes and services could interact to form a sustainable system for data sharing.
| S-EPMC5861517 | biostudies-literature
Project description:Open clinical trial data offer many opportunities for the scientific community to independently verify published results, evaluate new hypotheses and conduct meta-analyses. These data provide valuable opportunities for scientific advances in medical research. Herein we present the comparative meta-analysis of different standard of care treatments from newly available comparator arm data from several prostate cancer clinical trials. Comparison of survival rates following treatment with mitoxantrone or docetaxel in combination with prednisone as well as prednisone alone, validated the previously demonstrated superiority of treatment with docetaxel. Additionally, comparison of four testosterone suppression treatments in hormone-refractory prostate cancer revealed that subjects who had undergone surgical castration had significantly lower survival rates than those treated with LHRH, anti-androgen or LHRH plus anti-androgen, suggesting that this treatment option is less optimal. This study illustrates how the use of patient-level clinical trial data enables meta-analyses that can provide new insights into clinical outcomes of standard of care treatments and thus, once validated, has the potential to help optimize healthcare delivery.
| S-EPMC4862324 | biostudies-literature