What does a “significant difference” between treatments mean?

Well, this is a trick question, because ‘significant difference’ can have several meanings.

First, it can mean a difference that is actually important to the patient. However, when the authors of research reports state that there is a ‘significant difference’ they are often referring to ‘statistical significance’. And ‘statistically significant differences’ are not necessarily ‘significant’ in the everyday sense of the word. A difference between treatments which is very unlikely to be due to chance – ‘a statistically significant difference’ – may have little or no practical importance.

Take the example of a systematic review of randomized trials comparing the experiences of tens of thousands of healthy men who took an aspirin a day with the experiences of tens of thousands of other healthy men who did not take aspirin. This review found a lower rate of heart attacks among the aspirin takers and the difference was ‘statistically significant’ – that is, it was unlikely to be explained by the play of chance.

But that doesn’t mean that it is necessarily of practical importance. If a healthy man’s chance of having a heart attack is already very low, taking a drug to make it even lower may be unjustified, particularly since aspirin has side-effects, some of which – bleeding, for example – are occasionally lethal. [1]

On the basis of the evidence from the systematic review we can estimate that, if 1,000 men took an aspirin a day for ten years, five of them would avoid a heart attack during that time, but three of them would have a major haemorrhage.

  • Robert42

    The wording here is not inaccurate but it is unfortunate. Saying that a statistically significant result is unlikely to have occurred by chance implies causality of the treatment being tested. That isn’t true. A statistically significant difference is simply one where the measurement system (including sample size, measurement scale, etc.) was capable of detecting a difference (with a defined level of reliability). Just because a difference is detectable, doesn’t make it important, or unlikely.

    • Anonymous

      Hi Robert

      Thanks for your comment, and important clarification. I think here the authors made a trade-off between precision and getting the message across.

      There is a similar comment on the previous page (hit Previous above to see it), to which Paul Glasziou, one of the co-authors, gave a reply which is much better than any I could hope to muster.

      Please check it out and do let us know if you feel it merits further discussion.