Binary outcomes
Item 17b - For binary outcomes, presentation of both absolute and relative effect sizes is recommended
Example
“The risk of oxygen dependence or death was reduced by 16% (95% CI 25% to 7%). The absolute difference was -6.3% (95% CI -9.9% to -2.7%); early administration to an estimated 16 babies would therefore prevent 1 baby dying or being long-term dependent on oxygen” (also see table 7).(242)
Table 7 - Example of reporting both absolute and relative effect sizes
(Adpated from table 3 of The OSIRIS Collaborative Group(242))
| Primary outcome | Percentage (No) | Risk ratio (95% CI) | Risk difference (95% CI) | |
|---|---|---|---|---|
| Early administration (n=1344) | Delayed selective administration (n=1346) | |||
| Death or oxygen dependence at “expected date of delivery” | 31.9 (429) | 38.2 (514) | 0.84 (0.75 to 0.93) | -6.3 (-9.9 to -2.7) |
Explanation
When the primary outcome is binary, both the relative effect (risk ratio (relative risk) or odds ratio) and the absolute effect (risk difference) should be reported (with confidence intervals), as neither the relative measure nor the absolute measure alone gives a complete picture of the effect and its implications. Different audiences may prefer either relative or absolute risk, but both doctors and lay people tend to overestimate the effect when it is presented in terms of relative risk.(243) (244) (245) The size of the risk difference is less generalisable to other populations than the relative risk since it depends on the baseline risk in the unexposed group, which tends to vary across populations. For diseases where the outcome is common, a relative risk near unity might indicate clinically important differences in public health terms. In contrast, a large relative risk when the outcome is rare may not be so important for public health (although it may be important to an individual in a high risk category).
Page last edited: 24 March 2010
