Number Needed to Treat with a Psychiatric Drug to Benefit One Patient Is an Illusion


When doctors and patients make decisions about drugs, it can be useful for them to know how many patients need to be treated to benefit one of them. If you are a patient and your doctor recommends a statin to prevent heart attacks, you may be told that it prevents one heart attack if 200 people with a similar risk as yours take it for five years.

This means that the number needed to treat to benefit one patient is 200. When given this information, you might decline to take the statin. Perhaps you have already tried a statin, and developed muscular weakness and muscle pain that prevented you from walking 18 holes of golf, as a golfer once told me. Or perhaps you are so old that you think this extra precaution is unnecessary.

In psychiatry, the number needed to treat with a psychiatric drug to benefit one patient is largely an illusion. There are several reasons for this, but the most important one is that, for virtually all psychiatric drugs and clinical situations, more patients are harmed than those who benefit.

Illustration of a box labeled "BITTER Pills" with some small capsules beside itHarms and benefits are rarely measured on the same scale, but when patients in a placebo-controlled trial decide whether it is worthwhile to continue in the trial, they make a judgement about if the benefits they perceive exceed the harms. My research group did such an analysis based on clinical study reports we had obtained from drug regulators. We found out that 12% more patients dropped out on a depression pill than on placebo (P < 0.00001).

This means that there cannot be an NNT for depression pills, only a number needed to harm (NNH). Our meta-analysis showed that this number is about 25.

Psychiatrists constantly tell the world how effective their drugs are by referring to NNTs. Technically, NNT is calculated as the inverse of the benefit difference. If, for example, 60% have improved on drug and 50% on placebo, NNT = 1/(0.6-0.5) = 10. But that is just the mathematics. The data such NNTs are derived from are highly flawed.

Here are the main problems:

1) NNT is virtually always derived from trials where the patients were already in treatment before they were randomised to drug or placebo. This means that many of those switched from a previous drug to placebo will experience withdrawal symptoms, which the psychiatrists interpret erroneously as disease symptoms. Therefore, the infallible recipe in the drug industry is that if you harm patients in the placebo group, you may conclude your drug works.

When the top among UK psychiatrists in 2014 tried to convince their readers that depression pills are highly effective, they claimed that they have an impressive effect on recurrence, with an NNT of around three to prevent one recurrence. But it was not recurrence these trials assessed but withdrawal symptoms in the placebo group. As only two patients are needed to get one with withdrawal symptoms when a drug is stopped, there cannot exist an NNT to prevent recurrence, only an NNH, which is two.

2) As psychiatric drugs have conspicuous adverse effects, the blinding in placebo-controlled trials is inadequate, which tends to exaggerate the measured benefit, as this judgment is highly subjective.

3) By far most trials are industry-sponsored, and fraud and other manipulations with the data are very common. We therefore cannot trust published trial reports. This became abundantly clear after one of my PhD students and I in 2010 opened up the archives at the European Drug Agency after we had complained to the European Ombudsman. Based on the regulators’ clinical study reports, we recently showed that fluoxetine in minors is unsafe and ineffective, in marked contrast to the claims in published trial reports.

4) The NNT only takes those patients into account that have improved by a certain amount. If a similar number of patients have deteriorated, there can be no NNT, as there is no benefit. Thus, a totally useless drug, which only makes the condition after treatment more variable, so that more patients improve and more patients deteriorate than in the placebo group, will seem effective based on NNT.

5) The NNT opens the door to additional bias. If the chosen cut-off for improvement does not yield the desired result, other cut-offs can be tried till the data confess under torture. Such manipulations with the data during the statistical analysis, where the prespecified outcomes and the statistical methods are changed after company employees have seen the data, are very common.

In psychiatry, NNT is so misleading that it should be abandoned altogether. We might instead use NNH. Since depression pills harm the sex life of about half the patients, the NNH is only two. Thus, by not using depression pills, we will preserve the normal sex life in one out of every two patients we do not treat.

This leads to the conclusion that NNT in psychiatry—if used at all—should not mean number needed to treat but number not to treat in order to preserve the well-being of one patient.

The reasoning I have outlined above applies to all psychiatric drugs.


Mad in America hosts blogs by a diverse group of writers. These posts are designed to serve as a public forum for a discussion—broadly speaking—of psychiatry and its treatments. The opinions expressed are the writers’ own.


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  1. Thank you Gøtzsche. I truly appreciate these articles that analyze science behind biases in easy to understand way. If psychiatry text books are one day to be corrected, that must happen using scientific method by pointing out mistakes that had been made and not just telling about awful experiences we have that can always be dismissed as subjective opinions.

    The one thing I find horrifying is that why science is not correcting itself like it should do? Are there some cases where wishes of those who do it overwrite the way how it should work?

    When one of your books was published here in Finland, local Psychiatry Union made it look bad calling it sensational and telling that it was full of mistakes and half truths and was one sided and had anecdotes with no way to check if they were true. They called psychiatry you described as a fictional.

    That makes me wonder. It is not hard to watch people and make notes and not all research is made by private organizations seeking for profit. Harms those drugs do are not some hard to see entities requiring years of training to see. They are not hidden behind enormous benefits. Unlike modern physics or mathematics, they do not require complex machines to measure.

    I like idea of calculating that number needed to harm. But there is that constant problem that if one side does not care about knowledge, but pursues something else, how can any fact change anything? Everything can be denied with simply calling it with bad names and ignoring it. That is not how it should be. If those that research physics can solve complex questions like whether the light is the wave or the particle then why are those majoring psychiatry not alike?

    I am not scientist like you, but I once made experiment, that I still find so important that it should be repeated in proper environment using patients that are thought needing the medication. Can I tell you a story? I was 25 years old and I had used antipsychotic medicine 10 years against my will. Anytime I tried to lower the dose at first there were three days of elevated mood and lack of sleep and then I completely lost my ability to think and move after four days.

    I started measuring how much I could lower my dose without causing losing ability think and move. I was using 10 mg / day. The next pill was 7.5 mg so they went with 2.5 mg intervals. Using that smaller pill made my life horrible after four days. After lots of testing I invented a method to adjust my daily amount with 0.1 mg accuracy. It required lots of work every day to first dissolve pill at least half a day before in exactly 100 ml of water and then mix it and remove the amount I wanted before drinking.

    Results of my test were that I could subtract 0.2 mg of my daily amount (2 ml of water) without any problems. Limit was 0.5 mg (5 ml of water). That was too much for me to endure. Later I found that by lowering that 0.2 mg I had to wait two weeks until I could lower again. After half a year I was easily using that 7.5 mg that was impossible for me before.

    Feelings I got after succesful experiment were not simply a joy. I felt rage. It was such a simple experiment that any high schooler could do: Using that method it could be tested whether the depedency of medicines is caused by psychosis or caused by medicine. Using that method one could also test if psychosis after lowering medication is caused by medication or something else.

    Testing that with simply one person is not much of an experiment, but I do not really understand why that experiment is not already made with larger group. It would be really important to know how much drug can be safely adjusted and what are individual boundaries. That experiment repeated with different variations would remove lots of superstition that is currently written in psychiatry text books. It could also be used to research how to get off drugs safely. Currently those working at hospitals operate without that basic knowledge.

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    • Science has been contaminated by the profit motive. There have always been concerns regarding authoritarian approaches to science, which is why a lot of new discoveries come from people not in the field of the discovery. But since they started allowing professors to profit from their work, and allow drug companies and others to fund fellowships and chairmanships, the situation has become far, far worse, to the point that someone estimated over half of recent scientific “discoveries” are actually false. The news media also contribute to this by blasting the commercially favorable results they are given in a press release when some new “discovery” is made, but never bothering to publish a correction or retraction when the original researcher had to “eat crow.”

      Science is at this point highly corrupted, especially where pharmaceuticals are concerned.

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