Data Distortions: When Statistics Can Lead Us Astray In Drug Safety

By James Buchanan, Covilance

In clinical trials and post-marketing evaluations, adverse event (AE) data often invite scrutiny through statistical analysis. But drug safety professionals must proceed with caution: these analyses are exploratory, not confirmatory. Misapplying p values or treating disproportionality algorithms like hard evidence of harm can lead to false positives and misinformed conclusions. Worse yet, confounding variables—like duplicate reports, treatment indications, and bystander medications—can easily skew results.

So what’s the solution? This article explores how to correctly interpret safety data using statistical tools the right way. Learn what to watch for, what to question, and how to make decisions rooted in both science and context. Keep reading for critical insights.