The<unk>  is a mathematical<unk>  in epidemiologic case-control studies where the hypothesis tests the association between an exposure and a disease. It is assumed that, if the prevalence of the disease is low, then the odds ratio approaches the relative risk. Case control studies are relatively inexpensive and less time-consuming than cohort studies. Since case control studies don't track patients over time, they can't establish relative risk. The case control study can, however, calculate the exposure-odds ratio, which, mathematically, is supposed to approach the relative risk as prevalence falls. Some authors state that if the prevalence is 10% or less, the disease can be considered<unk>  enough to allow the<unk> . Unfortunately, the magnitude of discrepancy between the odds ratio and the relative risk is dependent not only on the prevalence, but also, to a great degree, on two other factors. The following example will illustrate this difficulty clearly. Consider a standard table showing the association between two binary variables with frequencies a = true positives = 49,005,929, b = false positives = 50,994,071, c = false negatives = 50,994,071 and d = true negatives = 849,005,929. In this case the odds ratio (OR) is equal to 16 and the relative risk (RR) is equal to 8.65. Although the prevalence in our example equals 10% it is very difficult to apply the<unk>  because OR and RR can hardly be considered to be approximately the same. However, in this example the disease is not particularly "rare"; a 10% prevalence value means 1 in 10 people would have it. As the prevalence drops lower and lower, OR approaches the RR much more closely. This is one of the most problematic aspects of the<unk> , since there is no threshold prevalence below which a disease is considered "rare", and thus no strict guideline to determine when the<unk>  applies. Positive Negative True 49,005,929 849,005,929 False 50,994,071 50,994,071
Rare disease assumption
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