External control arms - how to get to a good one
The Effective Statistician - in association with PSI
Big‑picture focus over perfection
Deepa's final advice: prioritize causal question clarity and overall robustness rather than ticking every box.
Why Listen
✔ You want a clearer understanding of when and why ECAs make sense.
✔ You’re dealing with real-world data and need a practical framework for selecting the right source.
✔ You’ve heard the term target trial emulation, but want to understand how it’s applied in real projects.
✔ You want to strengthen the causal credibility of your studies without relying solely on randomized trials.
✔ You want simple, actionable principles for handling confounding and unmeasured bias.
Episode Highlights:
[00:00] – Setting the stage
I introduce the topic of external control arms and why they’re more widely relevant than many statisticians think.
[01:35] – Introducing Deepa
Deepa shares her path from social epidemiology into designing and supporting ECA studies at Cytel.
[03:00] – Why ECAs are fascinating
We talk about how methods used to study policies without RCTs translate into clinical research.
[04:00] – Where ECAs show up
I walk through common scenarios—from rare diseases to extension studies—where external controls add value.
[07:30] – Choosing the right real-world data
Deepa explains how she approaches data selection depending on disease, outcomes, and feasibility.
[10:20] – Target trial emulation
We discuss how designing the “ideal RCT” guides everything that follows when constructing an ECA.
[16:30] – Handling confounding
Deepa explains the role of expert knowledge, DAGs, and standard adjustment approaches.
[21:20] – Thinking about unmeasured confounding
We talk about assessing robustness and understanding how much bias it would take to overturn your results.
[24:20] – Final takeaways
Deepa highlights the importance of focusing on the big causal question and overall robustness—not perfection.
Links:
🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician.
🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills.
🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine.
🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities.
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**Episode Highlights: ** [00:00] – Setting the stage I introduce the topic of external control arms and why they’re more widely relevant than many statisticians think.
[01:35] – Introducing Deepa Deepa shares her path from social epidemiology into designing and supporting ECA studies at Cytel.
[03:00] – Why ECAs are fascinating We talk about how methods used to study policies without RCTs translate into clinical research.
[04:00] – Where ECAs show up I walk through common scenarios—from rare diseases to extension studies—where external controls add value.
[07:30] – Choosing the right real-world data Deepa explains how she approaches data selection depending on disease, outcomes, and feasibility.
[10:20] – Target trial emulation We discuss how designing the “ideal RCT” guides everything that follows when constructing an ECA.
[16:30] – Handling confounding Deepa explains the role of expert knowledge, DAGs, and standard adjustment approaches.
[21:20] – Thinking about unmeasured confounding We talk about assessing robustness and understanding how much bias it would take to overturn your results.
[24:20] – Final takeaways
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