How to Read a Paper by Trisha Greenhalgh;

Author:Trisha Greenhalgh; [Greenhalgh, Trisha]
Language: eng
Format: epub
ISBN: 9781119484721
Publisher: John Wiley & Sons, Inc.
Published: 2019-04-08T00:00:00+00:00

Figure 9.2 Forest plot showing long‐term effects of cognitive behaviour therapy (CBT) compared with no active treatment and discontinuation of pharmacotherapy (PHA).

Source: Cuijpers et al. [16]. Reproduced with permission from BMJ.

The eight trials, each represented by the surname of the first author and the year that paper was published (e.g. ‘Blackburn 1986’) are listed, one below the other on the left‐hand side of the figure. The horizontal line corresponding to each trial shows the likelihood of relapse by 1 year in patients randomised to CBT compared to patients randomised to PHA. The ‘blob’ in the middle of each line is the point estimate of the difference between the groups (the best single estimate of the benefit in improved relapse rate by offering CBT rather than PHA), and the width of the line represents the 95% confidence interval of this estimate (see Chapter 5 ‘Have confidence intervals been calculated, and do the authors’ conclusions reflect them?’). The key vertical line to look at, known as the line of no effect, is the one marking the relative risk (RR) of 1.0. Note that if the horizontal line for any trial does not cross the line of no effect, there is a 95% chance that there is a ‘real’ difference between the groups.

As I argued in Chapter 5, if the confidence interval of the result (the horizontal line) does cross the line of no effect (i.e. the vertical line at RR = 1.0), which can mean either that there is no significant difference between the treatments, and/or that the sample size was too small to allow us to be confident where the true result lies. The various individual studies give point estimates of the odds ratio of CBT compared to PHA (of between 0.5 and 9.6), and the confidence intervals of some studies are so wide that they don’t even fit on the graph.

Now, here comes the fun of meta‐analysis. Look at the tiny diamond below all the horizontal lines. This represents the pooled data from all eight trials (overall RR CBT : PHA = 2.61, meaning that CBT has 2.61 times the odds of preventing relapse), with a new, much narrower, confidence interval of this RR (1.58–4.31). Because the diamond does not overlap the line of no effect, we can say that there is a statistically significant difference between the two treatments in terms of the primary end‐point (relapse of depression in the first year). Now, in this example, seven of the eight trials suggested a benefit from CBT, but in none of them was the sample size large enough for that finding to be statistically significant.

Note, however, that this neat little diamond does not mean that you should offer CBT to every patient with depression. It has a much more limited meaning – that the average patient in the trials presented in this meta‐analysis is likely to benefit in terms of the primary outcome (relapse of depression within a year) if they receive CBT. The choice of treatment should, of course, take into account how the patient

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