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Competing Interests: Competing interests: We have read and understood BMJ policy on declaration of interests and declare that FN received funding from the French National Research Agency (ANR-17-CE36-0010), the French ministry of health, and the French ministry of research. He is a work package leader in the OSIRIS project (Open Science to Increase Reproducibility in Science). The OSIRIS project has received funding from the European Union’s Horizon Europe research and innovation program under the grant agreement No. 101094725. He is a work package leader for the doctoral network MSCA-DN SHARE-CTD funded by the EU. Provenance and peer review: Not commissioned; externally peer reviewed.

Clinical trial data-sharing is seen as an imperative for research integrity and is becoming increasingly encouraged or even required by funders, journals, and other stakeholders. However, early experiences with data-sharing have been disappointing because they are not always conducted properly. Health data is indeed sensitive and not always easy to share in a responsible way. We propose 10 rules for researchers wishing to share their data. These rules cover the majority of elements to be considered in order to start the commendable process of clinical trial data-sharing: Rule 1: Abide by local legal and regulatory data protection requirementsRule 2: Anticipate the possibility of clinical trial data-sharing before obtaining fundingRule 3: Declare your intent to share data in the registration stepRule 4: Involve research participantsRule 5: Determine the method of data accessRule 6: Remember there are several other elements to shareRule 7: Do not proceed aloneRule 8: Deploy optimal data management to ensure that the data shared is usefulRule 9: Minimize risksRule 10: Strive for excellence., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Pellen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Data sharing is gradually becoming a requirement across all fields of science, owing to its key benefits in verifying the reproducibility of findings and reusing existent data for new purposes. Although metaresearch studies are complex, time-consuming, and hinge on the availability of data produced and curated by others, there has been little focus on how they make their own data available. This is in stark contrast to the heightened attention data sharing has received in clinical research. Yet, as secondary data users par excellence, metaresearchers are ethically bound to both improving and evaluating data sharing practices and correctly sharing their own data. We contrast particularities of data sharing in metaresearch and clinical research, such as benefits, barriers, and inadequate and potentially pervasive sharing practices. We conclude with an array of concrete and tailored recommendations for improvement., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background/aims: Over the past decade, numerous data sharing platforms have been launched, providing access to de-identified individual patient-level data and supporting documentation. We evaluated the characteristics of prominent clinical data sharing platforms, including types of studies listed as available for request, data requests received, and rates of dissemination of research findings from data requests., Methods: We reviewed publicly available information listed on the websites of six prominent clinical data sharing platforms: Biological Specimen and Data Repository Information Coordinating Center, ClinicalStudyDataRequest.com, Project Data Sphere, Supporting Open Access to Researchers-Bristol Myers Squibb, Vivli, and the Yale Open Data Access Project. We recorded key platform characteristics, including listed studies and available supporting documentation, information on the number and status of data requests, and rates of dissemination of research findings from data requests (i.e. publications in a peer-reviewed journals, preprints, conference abstracts, or results reported on the platform's website)., Results: The number of clinical studies listed as available for request varied among five data sharing platforms: Biological Specimen and Data Repository Information Coordinating Center (n = 219), ClinicalStudyDataRequest.com (n = 2,897), Project Data Sphere (n = 154), Vivli (n = 5426), and the Yale Open Data Access Project (n = 395); Supporting Open Access to Researchers did not provide a list of Bristol Myers Squibb studies available for request. Individual patient-level data were nearly always reported as being available for request, as opposed to only Clinical Study Reports (Biological Specimen and Data Repository Information Coordinating Center = 211/219 (96.3%); ClinicalStudyDataRequest.com = 2884/2897 (99.6%); Project Data Sphere = 154/154 (100.0%); and the Yale Open Data Access Project = 355/395 (89.9%)); Vivli did not provide downloadable study metadata. Of 1201 data requests listed on ClinicalStudyDataRequest.com, Supporting Open Access to Researchers-Bristol Myers Squibb, Vivli, and the Yale Open Data Access Project platforms, 586 requests (48.8%) were approved (i.e. data access granted). The majority were for secondary analyses and/or developing/validating methods (ClinicalStudyDataRequest.com = 262/313 (83.7%); Supporting Open Access to Researchers-Bristol Myers Squibb = 22/30 (73.3%); Vivli = 63/84 (75.0%); the Yale Open Data Access Project = 111/159 (69.8%)); four were for re-analyses or corroborations of previous research findings (ClinicalStudyDataRequest.com = 3/313 (1.0%) and the Yale Open Data Access Project = 1/159 (0.6%)). Ninety-five (16.1%) approved data requests had results disseminated via peer-reviewed publications (ClinicalStudyDataRequest.com = 61/313 (19.5%); Supporting Open Access to Researchers-Bristol Myers Squibb = 3/30 (10.0%); Vivli = 4/84 (4.8%); the Yale Open Data Access Project = 27/159 (17.0%)). Forty-two (6.8%) additional requests reported results through preprints, conference abstracts, or on the platform's website (ClinicalStudyDataRequest.com = 12/313 (3.8%); Supporting Open Access to Researchers-Bristol Myers Squibb = 3/30 (10.0%); Vivli = 2/84 (2.4%); Yale Open Data Access Project = 25/159 (15.7%))., Conclusion: Across six prominent clinical data sharing platforms, information on studies and request metrics varied in availability and format. Most data requests focused on secondary analyses and approximately one-quarter of all approved requests publicly disseminated their results. To further promote the use of shared clinical data, platforms should increase transparency, consistently clarify the availability of the listed studies and supporting documentation, and ensure that research findings from data requests are disseminated.

Florian Naudet and co-authors discuss strengthening requirements for sharing clinical trial data., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: the authors have declared that no competing interests exist. CA received postdoctoral grants from Uppsala University, the Blanceflor Foundation, and the Swedish Society of Medicine. In the past 36 months, JDW received research support through the Collaboration for Research Integrity and Transparency from the Laura and John Arnold Foundation and through the Center for Excellence in Regulatory Science and Innovation (CERSI) at Yale University and the Mayo Clinic (U01FD005938).

Objective: To explore the impact of the Annals of Internal Medicine (AIM) data-sharing policy for randomized controlled trials (RCTs) in terms of output from data-sharing (i.e. publications re-using the data)., Study Design and Setting: Retrospective study. RCTs published in the AIM between 2007 and 2017 were retrieved on PubMed. Publications where the data had been re-used were identified on Web of Science. Searches were performed by two independent reviewers. The primary outcome was any published re-use of the data (re-analysis, secondary analysis, or meta-analysis of individual participant data [MIPD]), where the first, last and corresponding authors were not among the authors of the RCT. Analyses used Cox (primary analysis) models adjusting for RCTs characteristics (registration: https://osf.io/8pj5e/)., Results: 185 RCTs were identified. 106 (57%) mentioned willingness to share data and 79 (43%) did not. 208 secondary analyses, 67 MIPD and no re-analyses were identified. No significant association was found between intent to share and re-use where the first, last and corresponding authors were not among the authors of the primary RCT (adjusted hazard ratio = 1.04 [0.47-2.30])., Conclusion: Over ten years, RCTs published in AIM expressing an intention to share data were not associated with more extensive re-use of the data., (Copyright © 2021. Published by Elsevier Inc.)

Objectives: To explore the impact of data-sharing initiatives on the intent to share data, on actual data sharing, on the use of shared data and on research output and impact of shared data., Eligibility Criteria: All studies investigating data-sharing practices for individual participant data (IPD) from clinical trials., Sources of Evidence: We searched the Medline database, the Cochrane Library, the Science Citation Index Expanded and the Social Sciences Citation Index via Web of Science, and preprints and proceedings of the International Congress on Peer Review and Scientific Publication. In addition, we inspected major clinical trial data-sharing platforms, contacted major journals/publishers, editorial groups and some funders., Charting Methods: Two reviewers independently extracted information on methods and results from resources identified using a standardised questionnaire. A map of the extracted data was constructed and accompanied by a narrative summary for each outcome domain., Results: 93 studies identified in the literature search (published between 2001 and 2020, median: 2018) and 5 from additional information sources were included in the scoping review. Most studies were descriptive and focused on early phases of the data-sharing process. While the willingness to share IPD from clinical trials is extremely high, actual data-sharing rates are suboptimal. A survey of journal data suggests poor to moderate enforcement of the policies by publishers. Metrics provided by platforms suggest that a large majority of data remains unrequested. When requested, the purpose of the reuse is more often secondary analyses and meta-analyses, rarely re-analyses. Finally, studies focused on the real impact of data-sharing were rare and used surrogates such as citation metrics., Conclusions: There is currently a gap in the evidence base for the impact of IPD sharing, which entails uncertainties in the implementation of current data-sharing policies. High level evidence is needed to assess whether the value of medical research increases with data-sharing practices., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: The aims of this survey were to evaluate the percentage of French clinical trial funders with a data sharing policy, to describe their data sharing policies and, more generally, the transparency of the research they fund., Methods: The different funders of clinical trials in France have been identified from 3 lists of tenders for clinical research projects: the internal list of the University Hospital Center (CHU) of Rennes, the list of the Interregional Group for Clinical Research and Innovation (GIRCI EST), the list of the portal for calls for projects in health research. Funders were contacted, first by email and then by phone (at least two email and/or phone reminders) to respond to an online survey via Google form. The questionnaire aimed to assess the existence of a sharing policy or not, as well as the way in which it was set up., Results: Out of 190 funders contacted, 94 did not respond. Sixty-five of the respondents were excluded because they did not fund clinical trials. Of the 31 funders included (including Direction générale de l'offre de soins [DGOS], Institut national contre le cancer [INCa], Groupement Interrégional de Recherche Clinique et d'Innovation [GIRCIs]), only 9 (29%) had implemented a data sharing policy. Among these nine funders, only one had a mandatory sharing policy and eight a policy supporting but not enforcing data sharing. Five allowed the use of budget lines dedicated to data sharing. Three reported granting data sharing incentives. Three had dedicated guidelines indicating a specific mode of sharing data (sharing on request and/or on a specialized platform) and specifying the type of data (individual patient data and/or protocol and amendments). For all three, there were restrictions on sharing data to researchers only. Data sharing policies concerned 19% of the total financial volume (850,032,000 euros) of the 26 funders who reported this information., Conclusion: Despite international interest in clinical trial data sharing practices, clinical trials funders with a strong data-sharing policy remain an exception in France., (Copyright © 2020 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.)

Background: Funders are key players in supporting randomized controlled trial (RCT) data-sharing. This research aimed to describe commercial and non-commercial funders' data-sharing policies and to assess the compliance of funded RCTs with the existing data-sharing policies., Methods and Findings: Funders of clinical research having funded at least one RCT in the years 2016 to 2018 were surveyed. All 78 eligible non-commercial funders retrieved from the Sherpa/Juliet Initiative website and a random sample of 100 commercial funders selected from pharmaceutical association member lists (LEEM, IFPMA, EFPIA) and the top 100 pharmaceutical companies in terms of drug sales were included. Thirty (out of 78; 38%) non-commercial funders had a data-sharing policy with eighteen (out of 30, 60%) making data-sharing mandatory and twelve (40%) encouraging data-sharing. Forty-one (out of 100; 41%) of commercial funders had a data-sharing policy. Among funders with a data-sharing policy, a survey of two random samples of 100 RCTs registered on Clinicaltrial.gov, data-sharing statements were present for seventy-seven (77%, 95% IC [67%-84%]) and eighty-one (81% [72% - 88%]) of RCTs funded by non-commercial and commercial funders respectively. Intention to share data was expressed in 12% [7%-20%] and 59% [49%- 69%] of RCTs funded by non-commercial and commercial funders respectively., Conclusions: This survey identified suboptimal performances of funders in setting up data-sharing policies. For those with a data-sharing policy, the implementation of the policy in study registration was limited for commercial funders and of concern for non-commercial funders. The limitations of the present study include its cross-sectional nature, since data-sharing policies are continuously changing. We call for a standardization of policies with a strong evaluation component to make sure that, when in place, these policies are effective., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: FN received funding from the French National Research Agency for this project. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: In November 2017, the Food and Drug Administration (FDA) approved a version of a second-generation antipsychotic, aripiprazole, embedded with a sensor (Abilify MyCite)., Objective: To systematically review the evidence supporting the FDA's approval of digital aripiprazole and how that evidence was disseminated in the scientific literature and news reports., Study Selection: Prospective, double-blind, randomised controlled trials (RCTs), non-randomised and non-comparative studies were included if they focused on the use of digital aripiprazole. All scientific publications citing the trials were included if written in English. For the news reports, all languages were included if an English translation was available, and all records that were published after FDA approval were included., Findings: In the primary evidence search, no RCT comparing digital aripiprazole with a non-digital formulation, other active comparators or placebo was found. Only three non-comparative uncontrolled cohorts were found. No study provided data on remission, quality of life or any efficacy outcome. Fourteen scientific papers were identified that cited the trials and 70 news stories met the inclusion criteria. Almost 80% (11/14) of the scientific papers and three-fourths (52/70) of the news stories conveyed an unsupported impression of benefit., Conclusions: Regulatory approval for this first-ever digital drug was based on weak evidence, and there was no evidence of better adherence with the digital version of aripiprazole compared with the non-digital version. The possibilities afforded by this technology make room for a new type of evergreening (ie, patenting of older drugs with a sensor as a 'new invention'). Both the scientific literature and news reports conveyed an unsupported impression of benefit., Trial Registration Number: CRD42018089515., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

We conducted an audit of 60 clinical psychology journals, covering the first 2 quartiles by impact factor on Web of Science. We evaluated editorial policies in 5 domains crucial to reproducibility and transparency (prospective registration, data sharing, preprints, endorsement of reporting guidelines and conflict of interest [COI] disclosure). We examined implementation in a randomly selected cross-sectional sample of 201 articles published in 2017 in the "best practice" journals, defined as having explicit supportive policies in 4 out of 5 domains. Our findings showed that 15 journals cited prospective registration, 40 data sharing, 15 explicitly permitted preprints, 28 endorsed reporting guidelines, and 52 had mandatory policies for COI disclosure. Except for COI disclosure, few policies were mandatory: registration in 15 journals, data sharing in 1, and reporting guidelines for randomized trials in 18 and for meta-analyses in 15. Seventeen journals were identified as "best practice." An analysis of recent articles showed extremely low compliance for prospective registration (3% articles) and data sharing (2%). One preprint could be identified. Reporting guidelines were endorsed in 19% of the articles, though for most articles this domain was rated as nonapplicable. Only half of the articles included a COI disclosure. Desired open science policies should become clear and mandatory, and their enforcement streamlined by reducing the multiplicity of guidelines and templates. (PsycINFO Database Record (c) 2019 APA, all rights reserved).