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Numbers needed to treat (NNTs) - calculation, interpretation, advantages and disadvantages


We are currently in the process of updating this chapter and we appreciate  your patience whilst this is being completed.


First described in 19881, the number needed to treat (NNT) can be thought of as the number of patients that need to be treated in order for one to benefit. It provides an attractive means of summarising the results of a clinical trial in a single figure, because the meaning of a sentence such as ‘20 patients need to be treated to avoid one additional death over a five-year period’ is easily understood by both doctors and patients.2 Similar measures are reported in vaccination and screening studies (number needed to vaccinate/screen) and their values are derived in a similar fashion to the NNT.


The NNT is the reciprocal of the absolute risk reduction – the difference between the proportion (or rate) of events in the active treatment intervention group (Pa), and the proportion (or rate) of events in the control group (Pc):

Insert Equation re Absolute Risk Reduction here:


Insert Equation re Number needed to treat here:


The worked example below is taken from the examiners’ comments from the June 2001 sitting of the MFPH Part A Examination.


The following 2×2 contingency table was obtained in a randomised controlled trial:

Insert 2 x 2 Contingency Table here:




The number needed to treat from this trial is calculated as follows:

Insert Equation re Number needed to treat 



There are also methods available for deriving NNT using odds ratios and relative risk reduction.3,4


The ideal NNT would be 1, where all the patients in the treatment group have benefitted, but no one has in the control arm. In theory, the higher the NNT, the less effective the treatment, because more people need to receive the treatment for one person to benefit. However, the value of an NNT should be interpreted in light of the clinical context. For example, an NNT of between 2 and 5 would normally indicate an effective therapy, such as a pain killer for acute pain. On the other hand, an NNT of 1 might be seen when treating a sensitive bacterial infection with antibiotics, whilst an NNT of 40+ might still be beneficial in other situations where the clinical endpoint is severe, such as using aspirin to prevent a heart attack. All NNTs are time-specific, as the effects of treatment may continue beyond the timeframe of a study. For example, in studies looking at the effect of statin therapy in preventing strokes, the NNT from a study running for 1 year will not be directly comparable to that from a study with a 5-year follow-up.

When reporting NNTs, the control treatment and intervention should be outlined, as well as the dose and duration of the intervention, the outcome, and the period over which observations were made.


NNT can be used to help us choose between two treatment options. If, for example, the NNT for drug A is lower than that for drug B, it suggests that drug A may be more effective and – all other things being equal – choosing A rather than B would make sense. Note that confidence intervals for NNTs can be calculated, and these should be used when comparing two or more treatments.

If the drug or intervention is harmful the NNT will be negative. This is sometimes referred to as the ‘Number Needed to Harm’ (NNH). This can also be used to describe adverse effects, for example as a result of the treatment under study.

Preventive measures

It is important to distinguish between treatments and preventative (prophylactic) measures. In trials of prophylactic treatments, ideally fewer events will occur in the treatment arm versus the control group, so (Pa – Pc) and the NNT will be negative. The calculated NNT value, without the sign, can still be presented.

Alternatively, in the case of preventive measures, the denominator of the formula can be rearranged to provide an NNT with a positive sign, i.e. 1/(Pc – Pa)


  • Useful summary of trial results that is easy to interpret
  • Useful to inform decision-making about individual patients and treatment options
  • Relatively easy to calculate


  • The NNT is dependent on a number of factors including baseline risk and duration of follow-up, so care must be taken when generalising to populations and when comparing NNTs between studies.
  • NNT is based on the most probable value in a normally distributed population – it does not take into account an individual patient’s baseline risk.
  • The clinical meaning of an NNT is subject to interpretation. For example, an NNT of 100 over five years to avoid one clinical event might be seen by some doctors as a health benefit, whereas others will consider the benefit as only moderate or even slight.


  1. Laupacis A, Sackett DL, Roberts RS. An assessment of clinically useful measures of the consequences of treatment. NEJM 2988;318:1728-33.
  2. Cook RJ, Sackett DL. The number needed to treat: a clinically useful measure of treatment effect. BMJ 1995;310:452-4.
  3. - Accessed 20/12/16
  4. Chatellier G, ZapletalE, Lemaitre D, Menard J, Degoulet P. The number needed to treat: a clinically useful nomogram in its proper context BMJ 1996; 312:426 - 429




© Helen Barratt 2009, Saran Shantikumar 2018