Data-sharing and re-analysis for main studies assessed by the European Medicines Agency-a cross-sectional study on European Public Assessment Reports

Data management and sharing

Guided by the FAIR principles (Findable, Accessible, Interoperable, Reusable), responsible data sharing requires well-organized, high-quality datasets. However, researchers often struggle with implementing Data Management and Sharing Plans due to lack of knowledge on how to do this, time constraints, and legal, technical, and financial challenges, particularly concerning data ownership and privacy. While patients support data sharing, researchers and funders may hesitate, fearing the loss of intellectual property or competitive advantage. Although some journals and institutions encourage or mandate data sharing, further progress is needed. Additionally, global solutions are vital to ensure equitable participation from low- and middle-income countries. Ultimately, responsible data sharing requires strategic planning, cultural shifts in research, and coordinated efforts from all stakeholders to become standard practice in biomedical research.

Learning from European regulator-initiated studies for regulatory decision making

Drug developers have displayed a growing interest in using real-word evidence (RWE) in the pre-marketing phase. Together with initiatives like DARWIN EU®, this interest encourages regulators to initiate their own observational clinical studies, which could be included in regulatory decision making. The Regulatory Science Network Netherlands (RSNN) organised an expert meeting in 2022 to discuss scenarios and learnings related to these regulator-initiated studies, of which the main points (e.g., transparency, independency and stakeholder interaction) have been published previously. In this review, the authors add their own views, underlining the importance of reproducibility and stakeholder interaction. Stakeholders should collaborate to embrace regulator-initiated studies in a timely and transparent manner to realise an optimal European framework for generating RWE to be included in the regulatory decision-making process.

Health-related quality of life in trials with high rates of early censoring: Caution advised

Health-related quality-of-life (HRQoL) data are central to capturing the quality of patients' life, while endpoints like overall survival (OS) focus on the quantity of life. When analyzing HRQoL data gathered from patients in a randomized trial, a key consideration is the completion rate - indicating the proportion of patients remaining in the trial and with completed questionnaires. When completion rates are disproportionately low in one treatment arm, one likely explanation is that patients who did not complete questionnaires suffered more from toxicities, negatively impacting their HRQoL. This is likely the case when low completion rates occur in the more toxic arm within a randomized trial. If the HRQoL analysis is run as a complete-case analysis - only considering patients without missing data - a decrement in HRQoL can be missed. Conversely, when completion rates are high, the HRQoL data are thought to be more reliable, and informative censoring is less likely. We describe why this reasoning can be inadequate. In trials where high and imbalanced rates of early censoring affect progression-free survival or OS endpoints, the completion rates only apply to the fraction of patients remaining in the trial. In those, HRQoL results should be considered with caution, and reasons for censoring in the primary time-to-event analyses should be explored before making definite conclusions about HRQoL. This is even more relevant in trials with non-inferiority design, where a benefit in HRQoL could be used as a justification to modify practice.

Expanding the data Ark: an attempt to make the data from highly cited social science papers publicly available

Access to scientific data can enable independent reuse and verification; however, most data are not available and become increasingly irrecoverable over time. This study aimed to retrieve and preserve important datasets from 160 of the most highly-cited social science articles published between 2008-2013 and 2015-2018. We asked authors if they would share data in a public repository-the Data Ark-or provide reasons if data could not be shared. Of the 160 articles, data for 117 (73%, 95% CI [67%-80%]) were not available and data for 7 (4%, 95% CI [0%-12%]) were available with restrictions. Data for 36 (22%, 95% CI [16%-30%]) articles were available in unrestricted form: 29 of these datasets were already available and 7 datasets were made available in the Data Ark. Most authors did not respond to our data requests and a minority shared reasons for not sharing, such as legal or ethical constraints. These findings highlight an unresolved need to preserve important scientific datasets and increase their accessibility to the scientific community.

Lifting of Embargoes to Data Sharing in Clinical Trials Published in Top Medical Journals

This study assesses data sharing status and lifting of embargoes in randomized clinical trials from top medical journals 3 to 5 years after publication.

Published registered reports are rare, limited to one journal group, and inadequate for randomized controlled trials in the clinical field

OBJECTIVE

Registered reports (RR) are a publication format implying a peer-review of the protocol before the start of the study, followed by an in-principle acceptance (IPA) by the journal before the study starts. We aimed to describe randomized controlled trials (RCTs) in the clinical field published as RR.

STUDY DESIGN AND SETTING

This cross-sectional study included RR results for RCTs, identified on PubMed/Medline and on a list compiled by the Center for Open Science. It explored the proportion of reports that received IPA (and/or published a protocol before inclusion of the first patient) and changes in the primary outcome.

RESULTS

A total of 93 RCTs publications identified as RR were included. All but one were published in the same journal group. The date of the IPA was never documented. For most of these reports (79/93, 84.9%), a protocol was published after the date of inclusion of the first patient. A change in the primary outcome was noted in 40/93 (44%) of them. Thirteen of the 40 (33%) mentioned this change.

CONCLUSIONS

RCTs in the clinical field identified as RR were rare, originated from a single journal group, and did not comply with the basic features of this format.

Omission of Critical Information From Clinical Trial Reports-What to Do About Uninterpretable Results

This Viewpoint identifies incomplete and missing data in 3 clinical trials to highlight the need for improved data reporting and to propose possible solutions.

Rethinking clinical study data: why we should respect analysis results as data

The development and approval of new treatments generates large volumes of results, such as summaries of efficacy and safety. However, it is commonly overlooked that analyzing clinical study data also produces data in the form of results. For example, descriptive statistics and model predictions are data. Although integrating and putting findings into context is a cornerstone of scientific work, analysis results are often neglected as a data source. Results end up stored as "data products" such as PDF documents that are not machine readable or amenable to future analyses. We propose a solution to "calculate once, use many times" by combining analysis results standards with a common data model. This analysis results data model re-frames the target of analyses from static representations of the results (e.g., tables and figures) to a data model with applications in various contexts, including knowledge discovery. Further, we provide a working proof of concept detailing how to approach standardization and construct a schema to store and query analysis results.

Sharing study materials in health and medical research

Making study materials available allows for a more comprehensive understanding of the scientific literature. Sharing can take many forms and include a wide variety of outputs including code and data. Biomedical research can benefit from increased transparency but faces unique challenges for sharing, for instance, confidentiality concerns around participants' medical data. Both general and specialised repositories exist to aid in sharing most study materials. Sharing may also require skills and resources to ensure that it is done safely and effectively. Educating researchers on how to best share their materials, and properly rewarding these practices, requires action from a variety of stakeholders including journals, funders and research institutions.