The results of comparative clinical studies can be expressed using various intervention effect measures. Examples are absolute risk reduction (ARR), relative risk reduction (RRR), odds ratio (OR), number needed to treat (NNT), and effect size. The appropriateness of using these to express an intervention effect, and whether probabilities, means, or medians are used to calculate them, depend upon the type of outcome variable used to measure health outcomes. For example, ARR, RRR and NNT are used for dichotomous variables and effect sizes are normally used for continuous variables.
The diagnostic odds ratio is a single value that provides one way of representing the power of the diagnostic test. It is applicable when we have a single cut point for a test, and classify tests results as positive and negative. The diagnostic odds ratio is calculated as the product of the true positive and true negative divided by the product of the false positives and false negatives. The relative diagnostic odds ratio is the ratio of one diagnostic odds ratio to another.
The odds reduction expresses, for odds, what relative risk reduction expresses for risks. Just as the relative risk reduction is (1 – relative risk) the odds reduction is (1 – relative odds) (the relative odds and odds ratio being synonymous). Thus, if a treatment results in an odds ratio of 0.6 for a particular outcome, the treatment reduces the odds for that outcome by 0.4.