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It's time to look at health risks in a new light, authors say

ted with Bouwer on projects for 20 years, and the two decided to train their science skills on data from medical studies. I can read scientific articles, and Ive had experience handling epidemiological data, Bouwer said. You can look at the data in medical studies the same way you look at environmental data. We did, and we found that the there was a lot of uncertainly in these studies, but it often wasnt being communicated to people.

Much of this misinformation, the researchers said, comes from the way risks are explained to a patient or described in a news story. One measure, called absolute risk reduction, looks at the difference in death rates between two groups, such as one group that received a medication and one that did not. If one person died among 100 people who took medication, the death rate would be 1 percent. If two people died among 100 people who did not take medication, that death rate for that group would be 2 percent. The difference between these death rates, found by subtracting 1 percent from 2 percent, would yield the absolute risk reduction: 1 percentage point.

But the authors learned that drugs companies, journalists and some medical professionals often rely on a different measure: relative risk reduction. This term compares only the raw numbers of people who died in each instance. In the above example, because half as many people (one versus two) died in the group that took the medication, the relative risk reduction is 50 percent. By this measure, the patient can be told that his or her chance of dying is cut in half by taking the drug, instead of being told that there was only a 1 percentage point difference in the treated group.

Its as if, in hearing about a baseball game between the Orioles and the Yankees, youre told that the Orioles scored twice as many runs as the Yankees, Rifkin said. But if you dont know the actual numbers involved, you dont know whether this was a close 2-1 game or a 20-10 rout. If you
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Contact: Phil Sneiderman
prs@jhu.edu
443-287-9960
Johns Hopkins University
6-Aug-2007


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