Using Bayes' nomogram to help interpret odds ratios.

In certain scenarios, the odds ratio (OR) provides an unbiased estimate of the rate ratio in case–control studies (1). However, the OR is also frequently used to estimate the risk ratio (relative risk) (RR) of an outcome in the presence of a risk factor. The degree of error in this estimate is frequently small but can sometimes be substantial. The OR as an estimate of the RR always overestimates the effect of the exposure (i.e., results in an estimate farther from 1). The degree of divergence between the OR and the RR depends on the size of the OR and the probability of the outcome of interest (Table) (2–4). Given the value of the baseline risk and the estimate of the OR, the RR can be estimated by the use of a formula (3). However, the formula may be inconvenient and cumbersome for readers and users of epidemiologic information. A nomogram is a graphical calculator that is a useful and convenient way to perform common calculations without the need to remember formulas. The use of the Bayes’ nomogram (5) has simplified the use of diagnostic test information (6, 7) and is now frequently used by physicians who may not be aware of the formula involved in the conversion. In this editorial, we show that the Bayes’ nomogram, typically associated with likelihood ratios, can also be used to calculate the RR given the OR and the baseline risk.