Aprotinin: propensity for confusion
So, once again, Aprotinin is bad.
In the New England Journal of Medicine, the Perioperative Ischaemia Research Group just published the results of a large observational study encouraging readers not to use aprotinin after cardiac surgery. One of the main reasons cited in the paper was a doubling in the risk of renal dysfunction and renal failure.
The study is to be commended on the large sample size, an impressive 4374 patients in 69 institutions across the world. Whilst we, as readers and reviewers are often wary about conclusions based on small sample sizes concluding no difference when a true difference might exist, why don’t we display a similar scepticism about large studies that conclude a difference when none might exist?
Big is not always better, the authors state that in this setting, a randomised trial would be ideal but would be difficult “if not impossible” to conduct, and observational studies when sufficiently large may offer critical insights even in light of recognized limitations.
Unfortunately they are missing the point. A small randomised trial will give you an estimate that is closer to the truth, because baseline differences are balanced, but the results may be imprecise (wide confidence interval) that is progressively narrowed by increasing the sample size.
However, a large observational study may give you a very precise estimate, but it may be far from the truth (influenced by bias arising from differences in the groups compared), that can never be corrected by increasing the sample size.
Precision of the estimate is never more important than a correct estimate!