Medical treatment

How to measure the potential harm of medical treatment

As we wrote last week, far fewer people benefit from medical therapies than we tend to think. This fact is quantified in the number of therapies needed to treat, or NNT, which tells you how many people would need to receive medical therapy for one person to benefit. NSTs well above 10 or even 100 are common. But knowing the potential benefits is not enough. We must also take into account the potential damage.

Not everyone who takes a drug will experience side effects, just as not everyone will see benefits. This fact can be expressed by the number needed to harm (NNH), which is the reverse of NNT

For example, the NNT of aspirin to prevent one additional heart attack over two years is 2000. Even if that means you have less than a 0.1% chance of seeing a benefit, you might think it’s worth it. After all, it’s just an aspirin. What harm could he do?

But aspirin can cause a number of problems, including increasing the risk of bleeding in the head or gastrointestinal tract. Not everyone who takes aspirin bleeds. Also, some people bleed whether or not they take aspirin.

The NNH of aspirin for these major bleeding events is 3,333. For every 3,333 people, just over two on average will have a major bleeding event, whether or not they take aspirin. About 3,330 will have no bleeding no matter what they do. But for every 3,333 people who take aspirin for two years, one additional person will have a major bleeding event. It is an expression of the risk of aspirin, in addition to the fact that one in 2,000 will avoid a heart attack.

Admittedly, one in 3,333 is a pretty small risk. But remember that the chances of benefiting are also quite low.

Sometimes, however, the NNH can be much lower or even lower than that of the NNT, suggesting that the risk of harm outweighs the potential benefit. Consider screening mammograms, which are considered so essential that they are the only screening tests specifically mentioned in the Affordable Care Act, and coverage for them without cost sharing is required by law.

If you look at data from all randomized controlled trials of breast cancer screening, the NNT to recommend screening to prevent one death from breast cancer after 13 years of follow-up is 1,477. But further analyzes show that the only woman would probably have died of other causes anyway. There may be no benefit in preventing death from any cause.

However, mammography screening can be harmful. They lead to overdiagnosis, encouraging the provision of therapies that bring no benefit – but carry risks and are therefore seen as harm.

If we look at these same studies, for every 333 women who are assigned a screening mammogram, one additional will undergo a lumpectomy or mastectomy as a result. As a result, one in 390 women scheduled for a screening mammogram will undergo additional radiation therapy. (In these randomized controlled trials, patients are either assigned to have screening mammograms or they are not. The study then generally examines the outcome for all those who were assigned to have the mammogram, whether they actually did or not.)

In other words, for about 1,500 women screened for 10 years, one could be spared death from breast cancer (although she would most likely die of some other cause). But about five other women would undergo surgery and about four others would undergo radiation therapy, both of which can have dangerous or even deadly side effects.

Thus, the NNH, together with the NNT, can be very useful in discussing the relative potential advantages and disadvantages of treatments. As another example, consider antibiotics for ear infections in children. There are many reasons why parents and pediatricians might consider treatment. An oft-cited reason is that we want to prevent serious complications from untreated infections. Unfortunately, antibiotics don’t do this, and NNT is effectively infinite. Antibiotics will also not reduce pain within 24 hours. However, antibiotics have been shown to reduce pain within two to seven days. However, not all children will see this benefit. The NNT is about 20 for this result.

However, antibiotics can cause side effects, including vomiting, diarrhea, or a severe rash. The NNH for side effects in this population is 14.

This means that when a child is prescribed antibiotics for an ear infection, they are more likely to develop vomiting, diarrhea or a rash than to benefit. When patients are presented with treatment options in this way, they are sometimes more likely to be willing to wait carefully to see if the ear infection resolves on its own. For most children with ear infections, observation with close follow-up is recommended by the American Academy of Pediatrics.

A wealth of NNT and NNH data based on clinical trials is available on a website developed by David Newman, director of clinical research at the Icahn School of Medicine at Mount Sinai Hospital, and Graham Walker, assistant clinical professor at the ‘University of California, San Francisco. But it’s important to understand that the results of clinical trials don’t always reflect what happens in the real world. As treatment criteria become more permissive beyond those applied in trials, NNTs may increase. But most importantly, NNHs often don’t. Healthier people are less likely to see a benefit from antibiotics or an aspirin. But they are no less likely to have a side effect or complication.

Indeed, the harms associated with treatment generally have nothing to do with the underlying disease. They are caused by therapy, regardless of the reason for use. Children will develop diarrhea, vomiting, or rashes from antibiotics in the same relative amounts, regardless of what we use them for. In other words, clinical trials are designed to target the category of patients who are most likely to benefit from treatment, but they do not target those who are more or less likely to suffer harm. When treatments are applied in real clinical settings, we generally do not see changes in the proportion of patients harmed by them compared to trials.

When we deviate from the treatment recommendations and expand the population receiving the studied treatments, the NNTs often increase, but the NNHs remain the same. Things are often even worse than the study data would suggest. Fewer people benefit, but just as many are harmed.

We hope that each therapy has a benefit. The NNT shows us that benefits are often far less likely than many realize. NNH can show us the likelihood of harm versus benefit. Considering both, especially in light of how practice often differs from study, can help us make better decisions about how to take care of ourselves and those we love.