The Effective Statistician - in association with PSI RWE demystified
Feb 17, 2020
Imi Dean, a real-world data scientist at Roche with expertise in oncology and machine learning, shares insights on the impact of real-world evidence in healthcare. He discusses his journey from medical science to data science, highlighting the power of real-world data and its contrast to traditional trials. The importance of precise research questions and overcoming biases in data is emphasized, as well as the role of propensity scoring in treatment analysis. Ultimately, Imi reveals how real-world evidence can significantly enhance patient care and decision-making.
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Defining Real-World Data
- Real-world data encompasses patient info generated outside controlled trials under everyday conditions.
- This can include pragmatic trials since they occur in typical clinical settings.
Understand Data Generation First
- Thoroughly understand how your real-world data is generated before analysis.
- Knowing the source reveals potential biases and limitations critical for valid interpretation.
Propensity Score Zero Insight
- A stark example showed patients with a propensity score of zero indicating a 100% probability for one treatment and none for the other.
- This occurred because the alternative treatment was contraindicated, rendering treatment comparisons meaningless for this subgroup.