This is an archived version of the Handbook. For the current version, please go to or search for this chapter here.

12.6.1  Meta-analyses with continuous outcomes

When outcomes are continuous, review authors have a number of options in presenting pooled results.  If all studies have used the same units, a meta-analysis may generate a pooled estimate in those units, as a difference in mean response (see, for instance, the row summarizing results for oedema in Chapter 11, Figure 11.5.a).  The units of such outcomes may be difficult to interpret, particularly when they relate to rating scales.  ‘Summary of findings’ tables should include the minimum and maximum of the scale of measurement, and the direction (again, see the Oedema column of Chapter 11, Figure 11.5.a).  Knowledge of the smallest change in instrument score that patients perceive is important – the minimal important difference – and can greatly facilitate the interpretation of results.  Knowing the minimal important difference allows authors and users to place results in context, and authors should state the minimal important difference – if known – in the Comments column of their ‘Summary of findings’ table. 


When studies have used different instruments to measure the same construct, a standardized mean difference (SMD) may be used in meta-analysis for combining continuous data (see Chapter 9, Section For clinical interpretation, such an analysis may be less helpful than dichotomizing responses and presenting proportions of patients benefiting. Methods are available for creating dichotomous data out of reported means and standard deviations, but require assumptions that may not be met (Suissa 1991, Walter 2001).


The SMD expresses the intervention effect in standard units rather than the original units of measurement. The SMD is the difference in mean effects in the experimental and control groups divided by the pooled standard deviation of participants’ outcomes (see Chapter 9, Section The value of a SMD thus depends on both the size of the effect (the difference between means) and the standard deviation of the outcomes (the inherent variability among participants). 


Without guidance, clinicians and patients may have little idea how to interpret results presented as SMDs.  There are several possibilities for re-expressing such results in more helpful ways, as follows.