Sensible Medicine

Yet Another Excellent Explainer About P-Values in Randomized Trials

Apr 4, 2024

Professor Erik Van Zwet from Leiden University discusses P-values in randomized trials, trial power, and trial replication. They explore the significance of P-values in interpreting study outcomes, the challenges of sample size, and understanding effect size. The conversation clarifies the unexpectedness of results and emphasizes the importance of historical data for comprehensive analysis in clinical settings.

44:05

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Erik Van Zwet

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Quick takeaways

Interpreting p-values below 5% signifies statistical significance in clinical trials, crucial for understanding trial results.

Underpowered trials increase the risk of missing true positive results or obtaining false positives, impacting the interpretation of trial outcomes.

Deep dives

Understanding P-Values and Statistical Interpretation in Clinical Trials

P-values play a crucial role in clinical trials, indicating the significance of trial results. In the podcast episode, Dr. Eric Benswett elucidates that a key aspect is whether a p-value is below or above 5%, with values below signifying significance. He compares interpreting p-values to assessing growth charts for children, with extreme deviations highlighting concern. Dr. Benswett’s analogy aids in grasping the importance of statistical significance in medical research.

Introduction

4min

Exploring P-Values in Growth Assessment and Uncertainty

2min

Understanding P Values in Randomized Trials

8min

Exploring Treatment Effects and Trial Power in Clinical Trials

3min

Reevaluating P-Values in the Realm of Clinical Trials

2min

Understanding Trial Power and Sample Size in Research Studies

8min

Understanding and Addressing Low Power in Clinical Trials

17min

Gosh was I lucky to speak with Professor Erik Van Zwet from Leiden University in the Netherlands. He is the first author on a recent NEJM Evidence paper looking at more than 23,000 trials in the Cochrane Database. (I linked to an URL that should get by the paywall.)

There are technical aspects of this paper. We hit on some (not a lot) of them. The gist of it though is really important when we look at evidence. Erik did an excellent job of explaining P-values, trial power, and, at the end, we discuss how this work might inform the ability of trials to replicate.

This discussion also pairs well with one I had with computer scientist Ben Recht.

I hope you enjoy the conversation.

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Sensible Medicine

Yet Another Excellent Explainer About P-Values in Randomized Trials

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Understanding P-Values and Statistical Interpretation in Clinical Trials

Power Levels and Trial Interpretation

Overestimation in P-values and Trial Results

Implications for Clinical Practice and Trial Evaluation

Remember Everything You Learn from Podcasts