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This Man's Simple System Could Transform American Medicine

Katherine Carpenter couldn’t sleep. For more than a week she’d been coughing herself awake every night and then hacking until she retched. Finally, she decided to see a doctor. The physician suspected bronchitis and wrote Carpenter a prescription for heavy-duty cough medicine. She also suggested antibiotics. That’s pretty standard: Up to 80 percent of people who go to a physician for acute bronchitis are prescribed antibiotics. But Carpenter, an import entry agent for UPS, didn’t want antibiotics. She thought they’d stop working if you take them too often, and she suspected her symptoms were caused by a virus, which antibiotics don’t affect anyway. She didn’t know it, but her hesitation had science on its side: A meta-analysis in the Cochrane Database of Systematic Reviews looked at 17 trials on antibiotics for people with acute bronchitis, and concluded that they only slightly shorten the duration of the illness—if they have any benefit at all. (And of course there’s the issue of antibiotic resistance to consider.) In the end, Carpenter refused the prescription, and her bronchitis eventually cleared up. But the experience left her with the distinct impression that she was just one more patient on the medical assembly line. “I felt like a number,” she says. Instead of being a number, Carpenter might have preferred to see a number, one that can help us weigh the benefits (or lack thereof) of a treatment. That number exists, and it’s called the number needed to treat. Developed by a trio of epidemiologists back in the ’80s, the NNT describes how many people would need to take a drug for one person to benefit. (The NNT for antibiotics in a case of acute bronchitis is effectively infinity, because the medicine is no better at curing the illness than a placebo.) Consider a couple other examples: If your kid is throwing up and you take her to the hospital, she might get a drug called Zofran. The NNT for that is 5, meaning that only five kids need to take Zofran for one of them to stop throwing up. And if you look at Zofran’s “number needed to harm” (the number of people who would need to take a drug for one to have a bad side effect) the answer is … well, there really isn’t one—no one has a significant side effect. Now, say you’re pushing 50. You’re healthy, but your doctor suggests you start taking a baby aspirin. Just in case, you know? That NNT is 2,000. That’s how many people have to take a daily aspirin for one (nonfatal) heart attack to be prevented. Statistically speaking: Not especially helpful. It’s unfortunate, then, that the NNT is not a statistic that’s routinely conveyed to either doctors or patients. But you can look it up on a site that you’ve probably never heard of: TheNNT.com. Started by David Newman, a director of clinical research at Icahn School of Medicine at Mount Sinai hospital, the site’s dozens of contributors analyze the available studies, crunch the numbers on benefits and harms, and then post the results. While a low NNT is generally “good” and a high NNT is “bad,” you also have to consider the severity of both the illness and the drug’s side effects. Which is why the team added a color-coding system: Green for when a treatment makes sense, yellow for when more study is needed, red for when the harms and the benefits cancel each other out, and black when the harms outweigh the benefits. Newman’s goal for the site is nothing short of a revolution in medical practice. He wants doctors to base their treatments on good scientific evidence, not tradition, hunch, and the fear that patients will see them as doing nothing. And he wants patients to start demanding such care. That’s the big picture, anyway. For now, he’d be happy if he could just get people looking at medicine in a different way. “People tend to think that if it’s a medical intervention, there’s science behind it,” he says. Unfortunately, that’s often not the case. “It is a lie to tell patients to do something without telling them, ‘You should know we’ve done lots of research on this and we can’t find any benefit to it.’” More via WIRED.

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