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Using Bayes’ nomogram to help interpret odds ratios
  1. John Page, MBBS, MSc1,
  2. John Attia, MD, PhD, FRCPC2
  1. 1Harvard University School of Public Health
 Boston, Massachusetts, USA
  2. 2University of Newcastle
 Newcastle, New South Wales, Australia

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    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 (results in an estimate further away 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.3,5 However, the formula may be inconvenient and cumbersome for readers and users of epidemiological information. A nomogram is a graphical calculator that is a useful and convenient way to perform common calculations without the need to remember formulae. The use of the Bayes’ nomogram6 has simplified the use of diagnostic test information7–8 and is now frequently used by physicians who may be unaware of the formula involved …

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