Michael Joyce is a writer-producer with HealthNewsReview.org and tweets as @mlmjoyce
A key to making an informed medical choice is weighing benefits and harms.
But how do you know how likely you are to benefit from a medical treatment or procedure?
In making these decisions it’s not always easy to decipher the latest research because clinical trial results on drugs and other interventions are communicated in a variety of ways such as P values, odds ratios, and relative or absolute risk. Often times we’re told a study is statistically significant, but we’re left wondering if it’s really clinically significant.
That’s where number needed to treat, or NNT, comes in.
It provides another way to frame the impact of a treatment; more specifically, it tells us how many people need to receive a medication or intervention for just one person to benefit (or to avoid one adverse outcome).
Back in the mid 90s the cholesterol-lowering drug, Lipitor, was released to much fanfare. Advertisements claimed it reduced the risk of heart attacks by 36%. But that was simply the relative risk reduction, a statistic often favored in ads because it’s more eye-catching.
As you can imagine the 36% figure was enticing; so much so that for the next 15 years or so Lipitor became the world’s best-selling drug of all time (up to that point).
But astute media coverage pointed out the absolute risk reduction (ARR) was closer to 1%.
The NNT is simply the inverse of the ARR. In this case the NNT is 100 / 1 = 100. Now it’s possible to frame the drug’s benefits in a whole new way. That is, 100 people would need to be treated with Lipitor for just 1 person to benefit.
Put another way, 99 people would need to take the drug, pay for it, run the risk of side effects, and stand no chance of benefit. Of course, no one knows going in who will be that lucky 1 out of 100 who does benefit.
To help our readers make sense of this statistical concept we’ve updated and expanded our toolkit with this primer:
In it you’ll learn:
You can find more tips for analyzing studies and health care claims in our TOOLKIT section.