News & Events

Meta-analysis is a statistical technique for combining sources of quantitative evidence. It is an example of secondary analysis, which is a subsequent analysis of clinical trial data. The original, or primary analysis of the data was for the purpose that the data was collected – with regards to the data presently shared on Vivli, a now-completed clinical trial.
Meta-analysis, like other forms of secondary analysis, looks back at data to answer a new question. Pairwise meta-analysis compares two sources of quantitative evidence “head-to-head.” For example, with clinical trial data a pairwise meta-analysis could compare directly the interventions in two different clinical studies; or it could compare an intervention and control arm.
Network meta-analysis evaluates more than two interventions against one another. Network meta-analysis can provide an estimate of the relative effectiveness of all interventions in the network – which can be helpful for improving health care decision-making.
Meta-analysis has traditionally been performed with aggregate data, including summary statistics (mean differences, event counts, odds ratios, hazard ratios etc.) extracted from published journal articles, conference abstracts, trial registries (e.g. clinicaltrials.gov), and unpublished documentation such as protocols, statistical analysis plans, and clinical study reports. However, the gold standard in meta-analysis involves the use of not aggregate but individual participant-level data or IPD. In IPD meta-analysis, the original participant level data is requested and re-analysed.
IPD meta-analysis allows a more flexible and complex analysis approach. The advantages are many, and include:

• Researcher can standardise or redefine outcomes
• Researcher can reinstate participants who may have been excluded
• Reduces publication, reporting and ecological biases
• Allows detailed checks of any analysis assumptions (e.g normality or proportional hazards).
• Allows for modelling heterogeneity (within and between studies)
• Consideration of covariates and treatment-covariate interactions
• Allows for modelling of prognostic and diagnostic data in synthesis

While the advantages are many, historically, IPD meta-analysis has been a difficult undertaking for even experienced researchers. However, new tools and platforms are changing the landscape of secondary analysis. If you would like to learn more about IPD meta-analysis, watch our webinar presentation on this topic. The learning objectives for our IPD meta-analysis webinar include:

• An introduction to individual patient data (IPD) meta-analysis
• Explanation of how platforms such as Vivli can facilitate IPD meta-analysis
• Exploration of the differences between IPD meta-analysis and aggregate data meta-analysis, including determining when IPD meta-analysis is the best approach to use.
• Review of examples of IPD meta-analysis.
• Discussion of practical aspects of retrieval of IPD from different sources.
• What to do when not all IPD is available for analysis.

If you have any questions about this blog or the Vivli platform, please email support@vivli.org.

Ida Sim, Technical Lead, Vivli

As increasing numbers of funders introduce requirements for data sharing plans, researchers have to develop a new skill: how to create and fulfill a data sharing plan.

Many data sharing plan requirements from funders have similar requirements. While the specifics vary somewhat based upon the type of data and how the researcher plans to share clinical data once it is completed, the general questions to ask about data sharing mandates are:

• WHO do these requirements apply to?
• WHAT data do you plan to share, and in what format?
• WHEN will it be made available, and for how long?
• WHERE will it be accessible?
• HOW can it be accessed, i.e. under what conditions or restrictions?

Vivli is an innovative new clinical research data sharing platform with a robust search engine that has been created to meet the needs of researchers who use clinical research data worldwide. Using the Vivli platform, researchers can access de-identified data from thousands of completed clinical trials. However, Vivli also has another benefit to researchers: providing them an easy, straightforward means of meeting their data sharing requirements. Unlike many data repositories or registries, Vivli offers a tool for safely sharing individual-level participant data (IPD), rather than just summary results. This helps clinical researchers meet their data sharing requirements from key funders, such as the NIH. For an example of how a researcher could use Vivli to meet NIH requirements, see the chart below:

	NIH Requirements	How can Vivli help?
Who?	Investigators submitting a research application requesting $500,000 or more of direct costs in any single year to NIH on or after October 1, 2003 are expected to include a plan for sharing final research data for research purposes, or state why data sharing is not possible.	Vivli can help researchers meet their NIH data sharing requirements. Learn more about sharing data on Vivli here.
What?	The precise content of the data-sharing plan will vary [but may include]: the format of the final dataset, the documentation to be provided, whether or not any analytic tools also will be provided.	As a neutral platform, Vivli lets data contributors decide which data to share. You can securely share individual de-identified participant data on Vivli. Vivli also allows researchers to store and share study related documents, code and tools.
When?	Applicants who are planning to share data may wish to describe briefly the expected schedule for data sharing.	Vivli will store data and make it available for as long as it retains scientific utility. Once you upload your data in a simple drag-and-drop process, it is made available for sharing.
Where?	The NIH allows researchers to choose the mode of data sharing, including repositories like Vivli.	On the Vivli platform, your data is accessible to everyone globally increasing the visibility and impact of your data. Vivli will manage all requests for your data directly, reducing the administrative burden of data sharing.
How?	Applicants who are planning to share data may wish to describe briefly: whether or not a data-sharing agreement will be required a brief description of such an agreement the criteria for deciding who can receive the data whether or not any conditions will be placed on their use	Vivli can make it possible for your data to be downloadable or can be accessible in a secure research environment. All data shared on Vivli is subject to a Data Use Agreement. The conditions of sharing are made transparent on the Vivli website.

Data sharing plans may be included in the grant proposal. Under Vivli Resources on our website, we have created an NIH Data Sharing Template  to help you meet data sharing requirements. If you have any questions about this blog, or how to use Vivli to meet data sharing requirements, please contact the Vivli team via email to support@vivli.org.

Vivli is an innovative new clinical research data sharing platform with a robust search engine that has been created to meet the needs of researchers worldwide who use clinical research data. Using the Vivli platform, researchers can access anonymized data from more than 7,000 completed clinical trials.

My mission at Vivli is to lead the Operations team. Our team is proud to support our users on the platform in three important ways.

1. Personalized support. We help users from request submission through the analysis process, and all the way to publication. By providing one-to-one interaction throughout, we’re available to answer specific questions regarding the Vivli platform, and to ensure that the experience is positive and efficient.
2. The option to bring in your own statistical tools and data. Vivli allows you to incorporate your own tools and data sets into the platform. The ease and flexibility of Vivli’s platform allows you to spend less time on the process and more time focusing on your research.
3. Streamlined process for Data Use Agreements. We harmonize legal agreements to streamline access to data. The first time your institution signs our Data Use Agreement is the only time they will have to sign it. After that point, only the lead researcher will have to sign the agreement. This should shorten the time between requesting and accessing data. Vivli makes sure you spend more time on science and less time on paperwork.

Sharing data is a critical component of high-quality research. We’ve created a support system for researchers who want to access or share data because we believe scientists should be doing science – not being bogged down by paperwork and processes. Vivli is working closely with our partners to make sure that our processes for sharing and accessing data are effective, responsive, and transparent. Visit our platform, or contact us directly at support@vivli.org, to learn more about how we can help with managing your clinical research data, or requesting data for use in your research.

Julie Wood, Director of Strategy and Operations