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Either your web browser doesn't support Javascript or it is currently turned off. In the latter case, please turn on Javascript support in your web browser and reload this page. Free to read. The OR is one of the most commonly used measures of association in preventive medicine, and yet it is unintuitive and easily misinterpreted by journal authors and readers. This article describes correct interpretations of ORs, explains how ORs are different from risk ratios RRs , and notes potential supplements and alternatives to the presentation of ORs that may help readers avoid confusion about the strength of associations. ORs are often interpreted as though they have the same meaning as RRs i.
Some studies use relative risks RRs to describe results; others use odds ratios ORs. Both are calculated from simple 2x2 tables. The question of which statistic to use is subtle but very important. Probability is the likelihood of an event in relation to all possible events. Relative risk is a ratio of probabilities. It compares the incidence or risk of an event among those with a specific exposure with those who were not exposed eg, myocardial infarctions in those who smoke cigarettes compared with those who do not Figure.
This paper argues that the use of the odds ratio parameter in epidemiology needs to be considered with a view to the specific study design and the types of exposure and disease data at hand. Frequently, the odds ratio measure is being used instead of the risk ratio or the incidence-proportion ratio in cohort studies or as an estimate for the incidence-density ratio in case-referent studies. Therefore, the analyses of epidemiologic data have produced biased estimates and the presentation of results has been misleading. However, the odds ratio can be relinquished as an effect measure for these study designs; and, the application of the case-base sampling approach permits the incidence ratio and difference measures to be estimated without any untenable assumptions. For the Poisson regression, the odds ratio is not a parameter of interest; only the risk or rate ratio and difference are relevant. For the conditional logistic regression in matched case-referent studies, the odds ratio remains useful, but only when it is interpreted as an estimate of the incidence-density ratio.
Show more about author. The odds ratio OR is one of several statistics that have become increasingly important in clinical research and decision-making. It is particularly useful because as an effect-size statistic, it gives clear and direct information to clinicians about which treatment approach has the best odds of benefiting the patient. Typically the data consist of counts for each of a set of conditions and outcomes and are set in table format. In addition to assisting health care providers to make treatment decisions, the information provided by the odds ratio is simple enough that patients can also understand the results and can participate in treatment decisions based on their odds of treatment success. DOI:
What are relative risk, number needed to treat and odds ratio? Risk difference RD is the difference in risk of the outcome event between control and experimental group. Control group is not exposed to the intervention, whereas experimental group is the one that is exposed to intervention. The risk of outcome event in the control group is also called baseline risk. The NNT is the inverse of the risk difference and indicates the number of patients required to be treated to avoid one additional outcome event. Risk difference and NNT are absolute measures of effect.
Well, both measure association between a binary outcome variable and a continuous or binary predictor variable. And unfortunately, the names are sometimes used interchangeably. The relative risk is also called the risk ratio. Suppose you have a school that wants to test out a new tutoring program. At the start of the school year they impose the new tutoring program treatment for a group of students randomly selected from those who are failing at least 1 subject at the end of the 1st quarter.
Relationship of the odds ratio to the risk ratio according to 4 levels of outcome risk cumulative incidence for unexposed subjects:. Relationship of the odds ratio to the risk ratio according to 4 levels of outcome risk cumulative incidence for exposed subjects:. Relationship of the odds ratio to the risk ratio according to 4 levels of outcome risk cumulative incidence for an average exposed and unexposed subject:. Estimates assume the number of exposed subjects is equal to the number unexposed.