Why linking data effectively is crucial for analysing clinical trial outcomes

Before joining NHS England, I was a researcher in clinical trials for 30 years. I usually brought data from all participants in a clinical trial in one place for analysis. Even for international trials, where data was collected in separate places to better support the running of the trials, the information was still ultimately brought together for efficient analysis. Using healthcare data, like NHS records, helps us plan and run clinical trials much faster and bring new treatments to patients sooner. We must always ensure the data is used safely, securely and for public benefit. I often wonder when data truly needs to be brought together for analysis and when it matters less.

The SDE Network supports researchers by tackling key challenges, such as public confidence and trust in researchers using NHS data, and difficulties accessing data across a fragmented system with over 7000 entry points.

The 10 regionally based and 1 England-wide SDE in the SDE Network provide secure data and research analysis platforms (see Research Powered by Data). The SDE gives approved researchers with approved projects secure access to NHS data. To ensure patient safety and confidentiality, this data is:

• de-identified (pseudonymised), so that any identifying (or personal) patient information such as names, addresses or NHS numbers are replaced with artificial, or ‘pseudo’, information
• minimised, so that only relevant patient information is provided for research projects

The data in SDEs remains securely under NHS oversight, and researchers can only take away their research findings, not the actual data itself. This approach ensures sensitive health data is accessed safely and securely, and it is being echoed across the UK’s nations and internationally.

My colleagues and I have just published a new study — The Need for Fully-Effective Federated Analytics of Data Sources for Clinical Trials — in the International Journal of Population Data Science (IJPDS). We examined what could happen if information about clinical trial participants is held across geographically separate environments and what if those environments did not allow those data to be brought together for analysis. We compared 2 approaches. First, we used a 1-stage analysis, which assumes that data from all participants could be analysed together within, or as if they all were in, a single environment. This is just like the approach typically used in clinical trials. Second, we used a 2-stage approach, which assumes individual participants could not be brought together and, instead, the data is analysed separately within each environment and then their separate sub-results combined; this approach is effectively a 'meta-analysis'.

Our study found that using a 2-stage approach could introduce limitations. For analyses with quantitative measurements, like haemoglobin or prostate specific antigen (PSA), the results were reassuringly similar to those in a 1-stage approach. However, for analyses that examine how long it takes for participants to experience a specific outcome, such as recovery, relapse, or hospitalisation (known as 'time-to-event data'), the result was more uncertain and less precise. Only being able to work with separated data also makes it tough to investigate whether treatments work differently for particular groups of patients ('sub-group analyses').

These findings are especially timely in light of the changes to make 'data access' (researcher comes to data) the default route to NHS data for research rather than the more familiar 'data sharing' (data goes to researcher) approach. Recognising this important challenge, the SDE Network has been working to ensure its technical and information governance processes can support a single stage approach.

By enabling researchers to analyse data as though it were held in a single location, health systems may be able to support faster and more effective clinical trials, helping new treatments reach patients sooner.

We raised this topic as clinical trialists, who are used to analysing data about all consenting participants in a trial in a single analysis environment. However, our findings apply to any type of project, including retrospective studies that safely use existing data, highlighting the need for secure environments to work together and enable data to be analysed in one place.

Our research, in which NHS England was a collaborator, was co-ordinated from University College London (Innovative Clinical Trials Unit and the Medical Research Council (MRC) Centre of Research Excellence in Clinical Trial Innovation), with funding from Health Data Research UK (HDR UK). 

To find out more about the SDE Network visit Research Powered by Data on the NHS England (Digital) website.

To read the full research paper visit The Need for Fully-Effective Federated Analytics of Data Sources for Clinical Trials — International Journal of Population Data Science.