Indication benchmarking in feasibility usually means knowing how long similar trials took to complete, how many patients they recruited and how many sites they opened. This data is so important for feasibility experts, yet so hard to get. I’ll tell you what we did at TrialHub in order to illustrate how hard to get the data really is.
On TrialHub you can check Trial Performance stats on an indication basis. What this feature is, is a comparison between the planned vs actual performance of all clinical trials for the indication for which a complete set of data is available.
What this means is that the TrialHub algorithm takes account of all available trial prognoses in the registries and when the trial is complete, compares them to the new set of data. Such a comparison is hard to do manually because the ‘planned outcomes’ or prognoses are not available once the trial is complete.
But even with the power of state-of-the-art technology collecting enough data is still difficult. The reason for that is simple, yet somewhat disappointing – there’s simply missing data in the registries. Data that is not entered timely or ever at all.
Thus, trials with the complete set of data needed for a meaningful comparison are relatively few. How ‘few’ you ask – of 811 completed phase 2 rheumatoid arthritis trials in Canada and the US, there are 234 trials with a complete set of data needed for this analysis.
Then, why is Planned vs Actual trial performance important?
Having this information still matters though. Based on it, you can get an idea of how ‘difficult’ an indication is and if you filter by country, you can get even more granular. You can see how many trials in your indication overperformed vs how many underperformed and even take a look at each individual trial to try and map out the reasons for delays or alternatively – what makes for a faster patient recruitment.
What can I use trial performance stats for?
When we were working on TrialHub’s Trial Performance, we asked feasibility experts what they need to do their job more easily and efficiently. The answer? Benchmarks.
If you’re designing a strategy for how, when and where to conduct your clinical trial, you need to be able to rely on indication benchmarks. A lot of decisions depend on them: from budget to timelines, to number of sites and patient recruitment goals. Planned vs Actual trial performance data can provide such benchmarks and the more trials are diligently described in the registries, the more complete and reliable this analysis can be.
For CROs especially, having indication benchmarks can facilitate better discussions with Sponsors around realistic timelines and budgets. This data can also back up a particular recruitment strategy or the choice of specific sites and countries.
How can I use TrialHub’s Trial Performance?
I recommend checking the stats first and analysing individual trials second. Why? Because if you see there are a lot of trials underperforming you can to an extent draw conclusions about the indication as a whole and/or the countries you’ve selected.
There are many factors affecting recruitment. You can still learn a lot though by taking a look at the bigger picture. Are 80% and more trials suffering delays? Were they conducted in countries with a high standard of care and/or trial competition? How many rescue sites on average did they have to open?
Then you can go more in depth and notice the trials that have a very high RRs (recruitment rates). Are they observational trials (you can exclude them in the Filters)? Did they include decentralized modalities (you can also filter for that)? Which sites did they work with?
TrialHub’s Trial Performance provides a high-level overview. You can explore other factors that impact clinical trial timelines and patient recruitment by including those variables in the analysis or taking a look at each one individually. For example, you can check how Standard-of-Care intersects with Average Recruitment Rates or see how local regulations impact a trial’s duration and recruitment strategy.
A comparison between planned vs actual performance is only one dimension of feasibility but it can provide a good basis for budgeting and planning a trial’s timelines. And together with other components, it can help you choose the most favourable path for the successful completion of your study.