Individual Participant Data Meta-Analysis. Группа авторов

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Individual Participant Data Meta-Analysis - Группа авторов

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      Based on the relevant data transfer guidance supplied by the central research team, secure data transfer can be achieved using a suitable file transfer site, for example, an institutional or suitable commercial file share service. Where a data file needs to be sent via email, ideally it should be end‐to‐end encrypted or otherwise password protected, with passwords sent separately (and ideally via a different communication medium, such as by post or by telephone). Although rare these days, if data need to be transferred using physical storage media, such as external disc drives or memory sticks, these should also be encrypted and sent using a delivery service that allows the package to be tracked and signed for upon delivery.

      4.4.4 Storing Trial IPD Securely

      Once transferred, IPD need to be stored securely by the central research team, with access limited to those members responsible for data management, checking and analysis, or overall conduct. They should have appropriate expertise in the handling of participant data, as well as training in data protection, and also should be prohibited from copying data to any mobile devices, laptops, memory sticks or cloud servers that have not been set up for the secure storage of confidential data.

      It is recommended that the central research team retain the original version of each trial data file exactly as supplied. This can be used for cross checking, and provides a back‐up should any errors arise, for example, if the data file that the meta‐analysis team are working on becomes corrupted. A copy of the file should be made prior to any changes, such as re‐formatting, re‐coding or re‐defining variables (Section 4.5), being carried out. Firstly, the copy should be converted to the preferred software format (such as Stata, R or SAS) for the IPD meta‐analysis project, which nowadays is a fairly straightforward process, because statistical packages can recognise or import data from multiple other sources, and if they do not, a specialist transfer package such as StatTransfer can be utilised. It is useful to add a numeric trial identifier and label to the trial data file, so that when IPD are being checked, harmonised, merged and analysed subsequently, each trial can be easily identified in the outputs, analyses and forest plots.

      4.4.5 Making Best Use of IPD from Repositories

      It may be possible or necessary to access IPD for one or more trials via a data‐sharing repository or platform. For example, there is a reasonable likelihood that trial investigators conducting trials of newer therapies, or that have published results more recently, might have to comply with a funder‐mandated data‐sharing policy requiring that IPD are uploaded to a repository. As described in detail in Section 3.2.2, repositories may not include all trials of relevance to a particular meta‐analysis, or the trials may be distributed across multiple platforms. Therefore, accessing trial IPD in this way can present challenges for the central collection, management, checking and analysis of data, and thereby potentially limit the ability to realise all the advantages generally associated with IPD meta‐analysis projects.45 The central research team may need to find ways to work around the issues.

      The IPD from a repository may not contain all the variables required to conduct the planned analyses, or these may not be defined in a standard way across different repositories, making data harmonisation difficult. In such circumstances, it may be possible to get an investigator to upload a more appropriate dataset, if the IPD research team can persuade them of the value of doing so. For example, they might emphasise that this is important not only for the current IPD meta‐analysis, but also for subsequent projects that may make use of their trial IPD, and therefore may ultimately prevent data providers receiving repeated requests for further data. However, this would take additional time and resource on the part of both the data provider and the central IPD meta‐analysis research team.

      Provided appropriate data are available, are more or less in the same format across trials, and can be downloaded from the relevant repository to use locally, there should not be any restrictions to the analyses of IPD. However, if access to IPD (and therefore data management and analyses) are confined to within a platform, it will only be possible to download results (e.g. regression model parameter estimates and confidence intervals), and this will restrict the meta‐analysis to a two‐stage approach (Part 2).

      Checking IPD, and harmonisation across trials, are integral and necessary components of an IPD meta‐analysis project. The checking process ensures that any missing data, or major errors in the supplied IPD, can be identified and brought diplomatically to the attention on the trial investigators. Often, the problems that arise turn out to be simple errors or reflect misunderstandings, which can be resolved readily, with major problems being rare. As well as preventing serious issues in the meta‐analysis, checking the IPD also promotes a better understanding of each trial by the central research team, and their independent scrutiny of the IPD can enhance the IPD project’s credibility.

      Often trials will have collected and defined data items in a variety of ways, and it will be necessary to re‐code or re‐define certain variables to a common format, in preparation for meta‐analysis. Depending on how data have been provided, and whether trial teams have followed the supplied data dictionary, this can be an involved process, as described next. Checking and harmonising data requires care and meticulous attention to detail, in order to avoid misunderstandings and the introduction of errors. Contact with those supplying data may be needed to resolve any uncertainties or sanction particular changes.

      4.5.1 The Process and Principles

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