Data sharing in clinical trials: An experience with two large cancer screening trials.
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ABSTRACT:
SUBMITTER: Zhu CS
PROVIDER: S-EPMC5441574 | biostudies-literature | 2017 May
REPOSITORIES: biostudies-literature
Publications
Data sharing in clinical trials: An experience with two large cancer screening trials.
Zhu Claire S CS Pinsky Paul F PF Moler James E JE Kukwa Andrew A Mabie Jerome J Rathmell Joshua M JM Riley Tom T Prorok Philip C PC Berg Christine D CD
PLoS medicine 20170523 5
Paul Pinsky of the US National Cancer Institute and colleagues describe the implementation and outcomes of web-based data sharing from the PLCO and NLST cancer screening trials. ...[more]
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Project description:Numerous arguments have been advanced for broadly sharing de-identified, participant-level clinical trials data, and trial sponsors and journals are increasingly requiring it. However, data sharing in pragmatic clinical trials presents ethical challenges related to the use of waivers or alterations of informed consent for some pragmatic clinical trials and corresponding limitations of informed consent to guide sharing decisions; the potential for data sharing in pragmatic clinical trials to present risks not only for individual patient-subjects, but also for health systems and the clinicians within them; sharing of data from electronic health records instead of data newly collected for research purposes; and researchers' limited capacity to control sensitive data within an electronic health record and potential implications of such limits for meeting obligations inherent to Certificates of Confidentiality. These challenges raise questions about the extent to which traditional research ethics governance structures are capable of guiding decisions about pragmatic clinical trial data sharing. This article identifies and examines these ethical challenges for pragmatic clinical trial data sharing. We suggest several areas for future empirical scholarship, including the need to identify patient and public attitudes regarding pragmatic clinical trial data sharing as well as to assess the demand for pragmatic clinical trial data and the correspondingly likely benefit of such sharing. Further conceptual work is also needed to explore how requirements to respect patient-subjects about whom data are shared in the context of pragmatic clinical trials should be understood, particularly in the absence of informed consent for initial research activities, and the appropriate balance between promoting the generation of socially valuable knowledge and respecting autonomy.
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Project description:Thyroid cancer incidence has increased significantly over the past three decades due, in part, to incidental detection. We examined the association between randomization to screening for lung, prostate, colorectal and/or ovarian cancers and thyroid cancer incidence in two large prospective randomized screening trials.We assessed the association between randomization to low-dose helical CT scan versus chest x-ray for lung cancer screening and risk of thyroid cancer in the National Lung Screening Trial (NLST). In the Prostate Lung Colorectal and Ovarian Cancer Screening Trial (PLCO), we assessed the association between randomization to regular screening for said cancers versus usual medical care and thyroid cancer risk. Over a median 6 and 11 years of follow-up in NLST and PLCO, respectively, we identified 60 incident and 234 incident thyroid cancer cases. Cox proportional hazards regression was used to calculate the cause specific hazard ratios (HR) and 95% confidence intervals (CI) for thyroid cancer.In NLST, randomization to lung CT scan was associated with a non-significant increase in thyroid cancer risk (HR = 1.61; 95% CI: 0.96-2.71). This association was stronger during the first 3 years of follow-up, during which participants were actively screened (HR = 2.19; 95% CI: 1.07-4.47), but not subsequently (HR = 1.08; 95% CI: 0.49-2.37). In PLCO, randomization to cancer screening compared with usual care was associated with a significant decrease in thyroid cancer risk for men (HR = 0.61; 95% CI: 0.49-0.95) but not women (HR = 0.91; 95% CI: 0.66-1.26). Similar results were observed when restricting to papillary thyroid cancer in both NLST and PLCO.Our study suggests that certain medical encounters, such as those using low-dose helical CT scan for lung cancer screening, may increase the detection of incidental thyroid cancer.
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Project description:BACKGROUND:There is an increasing demand by non-commercial funders that trialists should provide access to trial data once the primary analysis is completed. This has to take into account concerns about identifying individual trial participants, and the legal and regulatory requirements. METHODS:Using the good practice guideline laid out by the work funded by the Medical Research Council Hubs for Trials Methodology Research (MRC HTMR), we anonymised a dataset from a recently completed trial. Using this example, we present practical guidance on how to anonymise a dataset, and describe rules that could be used on other trial datasets. We describe how these might differ if the trial was to be made freely available to all, or if the data could only be accessed with specific permission and data usage agreements in place. RESULTS:Following the good practice guidelines, we successfully created a controlled access model for trial data sharing. The data were assessed on a case-by-case basis classifying variables as direct, indirect and superfluous identifiers with differing methods of anonymisation assigned depending on the type of identifier. A final dataset was created and checks of the anonymised dataset were applied. Lastly, a procedure for release of the data was implemented to complete the process. CONCLUSIONS:We have implemented a practical solution to the data anonymisation process resulting in a bespoke anonymised dataset for a recently completed trial. We have gained useful learnings in terms of efficiency of the process going forward, the need to balance anonymity with data utilisation and future work that should be undertaken.
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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.
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Project description:ObjectivesWe examined major issues associated with sharing of individual clinical trial data and developed a consensus document on providing access to individual participant data from clinical trials, using a broad interdisciplinary approach.Design and methodsThis was a consensus-building process among the members of a multistakeholder task force, involving a wide range of experts (researchers, patient representatives, methodologists, information technology experts, and representatives from funders, infrastructures and standards development organisations). An independent facilitator supported the process using the nominal group technique. The consensus was reached in a series of three workshops held over 1 year, supported by exchange of documents and teleconferences within focused subgroups when needed. This work was set within the Horizon 2020-funded project CORBEL (Coordinated Research Infrastructures Building Enduring Life-science Services) and coordinated by the European Clinical Research Infrastructure Network. Thus, the focus was on non-commercial trials and the perspective mainly European.OutcomeWe developed principles and practical recommendations on how to share data from clinical trials.ResultsThe task force reached consensus on 10 principles and 50 recommendations, representing the fundamental requirements of any framework used for the sharing of clinical trials data. The document covers the following main areas: making data sharing a reality (eg, cultural change, academic incentives, funding), consent for data sharing, protection of trial participants (eg, de-identification), data standards, rights, types and management of access (eg, data request and access models), data management and repositories, discoverability, and metadata.ConclusionsThe adoption of the recommendations in this document would help to promote and support data sharing and reuse among researchers, adequately inform trial participants and protect their rights, and provide effective and efficient systems for preparing, storing and accessing data. The recommendations now need to be implemented and tested in practice. Further work needs to be done to integrate these proposals with those from other geographical areas and other academic domains.
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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.
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