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The Insidious Effect of Diagnostic Creep

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The Neuroskeptic begins this great post on the spat of recent studies claiming antidepressants are of little value in treating depressive disorders:

Imagine there was a nasty disease that affected 1 in 100 people. And imagine that someone invented a drug which treated it reasonably well. Good work, surely.

Now imagine that, for some reason, people decided that 10% of the population need to be taking this drug, instead of 1%. So sales of the drug sky-rocket. Eventually some clever person comes along and asks "This is one of the biggest selling drugs in the world - but does it work?" They look into it, and find that it doesn't work very well at all. For about 9 out of 10 people, it's completely useless! What a crap drug.
Neuroskeptic points out two important points behind these findings.  First, the growth of diagnostic labeling and its effects on efficacy studies; second, the limitations of commonly used psychiatric assessment tools such as the Hamilton Rating Scale for Depression. 

But one other point is worth mentioning.  All of these studies utilize a statistical method known as meta-analysis.  In layman's terms, this technique uses mathematical formulas to quantify the overall effect of numerous studies conducted over time.  The key is that the author's of these studies posses enormous discretion in deciding which studies are included and which are excluded.  True, they must provide a rationale for their decision-trees, but even with explicit and rational reasons, the result can be a study which examines six studies while excluding over 2,000-  while nevertheless claiming to pass judgment on them all.

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