This is a very belated reply to Douglas Altman's comments on Forest Plots. I was mistaken in implying that a log scale could be to log 2, or log 10, or log e. Log scales are identical, whatever the base log may be. The problem with forest plots displayed in any article is the 'visual lie' impact. For example, an x- axis of 0 to 100 will make a confidence interval of 1 to 10 look small, whereas an x- axis of 1 to 10 will make it look large. I believe that articles do misuse this 'visual lie' factor to unfairly massage the appearance of results.
Another problem with forest plots is that the confidence intervals are asymmetrical on a linear scale, although they look symmetrical on a log scale- in other words, the appearance of a forest plot can vary, depending on whether a log or linear scale is used. A log scale will compress results. Again, the appearances of a forest plot can be ambiguous, ambivalent, and so potentially unsafe.
With NNT, the confidence intervals in a forest plot may be considerably distorted, since the value of the null hypothesis of no effect is infinity. The forest plots become highly distorted in this situation.
So what I am questioning is not the mathematics, but rather the appearances, of the forest plot. Appearances have always an element of danger in them...
Competing interests: No competing interests