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Risk measures are estimates that describe the amount of risk associated with a particular exposure in a sample population. Risk estimates can quantitatively describe the risk associated with a particular exposure and the development or prevention of disease, and they can quantify the association between the exposure to a particular drug and an adverse drug reaction.

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Risk estimates are part of our daily lives. Measures of risk are communicated to patients via newspapers, television, and the Internet daily. Risk measures are communicated to practitioners via studies published in medical journals. These risk measures become important in the clinical decision-making process for both patients and practitioners.

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It is important to have a clear understanding of risk measures to appropriately interpret and apply the estimates. Risk measures are difficult to use for many reasons, including the conflicting results obtained from different studies. For example, early observational studies have reported a positive association1–3 between calcium channel blocker use and cancer, whereas more recent observational studies have reported a negative association.4,5 When conflicting information pertaining to risk is published, it becomes difficult for both practitioners and patients to use risk estimates for clinical decision-making. A clear understanding of study design and the derivation of risk estimates allows practitioners to determine the most reliable risk estimates to use in the midst of conflicting results.

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Additional confusion exists around the actual interpretation of the results of a study regarding risk estimates. Two readers may interpret, communicate, and use the results of a study very differently. Note, for example, the headlines that appeared on January 1, 1998, in two newspapers. Both newspapers reported the results of the same study on their front pages. The study assessed the risk of body weight and death. Interestingly, the two newspaper writers arrived at opposing interpretations of the study results, as evidenced by the titles of their stories. The headline in one newspaper read, “Adding Pounds as the Years Pass Increases Death Risk, Study Finds,” whereas the headline in the second newspaper read, “Study Shows Obesity Poses Less of a Risk Than Thought.” These two reporters read the same study, interpreted the results, and communicated conflicting summaries, leaving the reader to decipher the actual risks of weight gain. When we rely on others to summarize study results involving risk estimates, we are often faced with conflicting results, depending on the writer’s skills and perspective. The more adept a pharmacist becomes in evaluating and interpreting risk estimates, the more effective he or she will be in helping patients to sort through the conflicting information they receive.

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A discussion of measures of risk should include a review of prevalence and incidence. Prevalence (P) is defined as the number of existing cases of disease (or any outcome, e.g., adverse drug reaction, drug use) in a population at a particular point in time.

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Example 6-1

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