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''Number Needed to Treat'': a Tool for Summarizing Treatment Effect, And ARTICLE IN PRESS Current Anaesthesia & Critical Care (2005) 16, 173–179 www.elsevier.com/locate/cacc BASIC SCIENCE ‘‘Number needed to treat’’: A tool for summarizing treatment effect, and its application in anaesthesia and pain management J. Poulosa, P.C.A. Kamb,à aDepartment of Anaesthesia and Pain Management, University of Sydney, Royal North Shore Hospital, St Leonards NSW 2065, Australia bDepartment of Anaesthesia, University of New South Wales, St George Hospital, Kogarah, Sydney NSW 2217 Australia KEYWORDS Summary Number needed to treat (NNT) has become an increasingly used method Number needed to of reporting study outcomes. It incorporates baseline risk as well as relative risk treat; reduction to provide a whole number that indicates the effort which must be Measure of expended to obtain one additional beneficial outcome. Variations of NNT have been treatment effect; developed to account for harmful effects of treatment, and to improve the clinical Number needed to utility of NNT. NNT provides clinicians with a means of comparing efficacy of harm; different treatments which is more clinically useful and can help guide the provision Measures of risks and distribution of health resources. However, NNT has the potential to mislead the clinician if its limitations are not appreciated. NNT has been increasingly used in the reporting of outcomes from trials and systematic reviews in anaesthesia, pain management, and clinical medicine. & 2005 Elsevier Ltd. All rights reserved. Introduction clinical practice. Clinicians also need a readily understandable tool for weighing the risks of various 1–3 The need to express estimates of risk in an under- treatments. Ideally this should be feasible without standable manner is a challenge faced regularly by recourse to complicated statistical concepts. The those who work with the results of epidemiological concept of rate difference is converted into a number research and who need to convey their meaning to of individuals, a more intuitively understandable clinicians. Traditional statistical measures from sys- quantity. This quantity was named ‘‘number needed tematic reviews cannot be immediately applied to to treat’’ (NNT). NNT is becoming a popular measure of treatment effect. This number can be calculated ÃCorresponding author. Tel.: +61 2 9350 2180; easily from raw data or from statistical estimates and fax: +61 2 9350 3959. can be applied to different end points (treatment E-mail address: [email protected] (P.C.A. Kam). efficacy, harm, and other outcomes). 0953-7112/$ - see front matter & 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.cacc.2005.08.003 ARTICLE IN PRESS 174 J. Poulos, P.C.A. Kam The aims of this review are to summarize the over relative risk in terms of sampling distribution, value and limitations of ‘‘NNT’’ as a measure of it is preferred in meta-analyses.3–5 ORs are often treatment effect in randomized controlled trials. been used as approximations of RRs.3 This associa- tion is generally considered valid as long as the event is relatively rare (incidence less than 10%). As Traditional measures of treatment effect the incidence of the event increases, this relation- ship breaks down and OR tends to overestimate 6 The traditional measures of treatment effect are benefits and harms of treatment. relative risk, odds ratio (OR) and absolute risk It is important to note that RR, RRR and OR reduction (ARR). Table 1 summarizes the results of represent measures of treatment effect relative to a study of a new treatment for prevention of the control event rate and do not reflect changes in postoperative nausea and vomiting (PONV) against the baseline risk of an event. A RRR of 40% may be a control (existing treatment). significant, but if the baseline risk of the event in the population is very small, potential toxicity and cost of the treatment may not justify its use. Relative risk (RR) Relative risk (also known as the ‘‘risk ratio’’) is Absolute risk reduction (ARR) defined as the probability of an event in the study group divided by the probability of an event in the ARR is the absolute difference in risk of an event control group.4 Mathematically in the above study between the experimental and control groups.3 In it is the above example, ARR is mathematically equal to: b=ðb þ dÞa=ða þ cÞ. ARR represents the num- a=ða þ cÞ . ber of events (in this case PONV) prevented as a b=ðb þ dÞ proportion of all patients treated. In contrast, the It expresses the relative probability that an event RRR expresses the number of events prevented as a will occur when the two groups of patients are proportion of the number of events expected.7 It compared.1 The complement of relative risk (1-RR) does not reflect the risk of the event without is known as relative risk reduction (RRR). RRR is an treatment, and cannot discriminate large treat- estimate of the percentage of baseline risk that is ment effects from small ones.8 The ARR incorpo- removed by the treatment.5 A RRR of 0 indicates no rates the baseline risk of the event without therapy benefit or harm from the treatment compared to and the risk reduction with therapy.3 It, like RR, the control group, whereas a RRR of 1 indicate a RRR, and OR, is not an intuitively easy means by ‘‘100% benefit’’.4 which clinicians can assess treatment effect in trial reports and apply them at the bedside.3 Odds ratio (OR) Number needed to treat (NNT) ‘‘Odds’’ expresses the probability that a particular event will occur against the probability it will not 1 In the context of randomized trials on the desirable occur. In the above example, the odds of PONV are effects of treatment, Sackett proposed a method of a/c in the study group and b/d in the control group. converting rate differences into a more intuitive The OR is defined as the odds of an event in the quantity called ‘‘NNT’’. NNT is the ‘‘number of study group divided by the odds of an event in the 4 patients one would need to treat with the experi- control group. OR is the traditional epidemiologi- mental therapy in order to prevent one additional cal expression of the relative likelihood of an 3,9 3,6 adverse event or attain one additional benefit’’. outcome. Because OR has statistical advantages Mathematically it is calculated as 1/ARR. NNT is usually expressed as a whole number (as its point estimate) and can be obtained for any trial that has Table 1 Standard 2  2 table demonstrating reported a binary outcome (i.e. event or no occurrence of postoperative nausea and vomiting event).10 Alternatively, NNT may be calculated (PONV) in study and control group. using the risk of the event in the control group and the RRR as follows: PONV No PONV NNT ¼ 1=ðPc  RRRÞ Study group ac Control group bdwhere Pc is the risk of the event (PONV in the above example) in the control group {ie: Pc ¼ b=ðb þ dÞ}. ARTICLE IN PRESS Number needed to treat 175 A nomogram has been proposed to simplify calcula- where OR is the odds ratio provided by the tion of NNT at the bedside for individual patients.11 case–control study, and UER is the unexposed event The NNT defines the treatment-specific effect of rate. NNTH is a measure of absolute risk because it an intervention or therapy. An NNT of 1 means that takes into account the background risk of the the treatment is effective in all patients. Most outcome occurring in unexposed people, unlike the treatments or interventions will have an NNT higher OR that measures relative risk. NNTH is a composite than 1 because they are effective in some but not measure that takes into account the OR and the all the patients. An NNT of 2–3 indicates that a unexposed event rate. Consequently, it provides a treatment or intervention is quite effective. How- better estimate of risk that corresponds with the ever, NNT must not be used in isolation; the data clinical situation (reality). A major limitation of from which it is derived should also be considered NNTH is that it is not always possible to find a study as heterogeneity of data alters NNT; and we need that provides an approximate estimate of the to consider age, epidemiological and others fac- unexposed event rate (which can be estimated tors. In prophylactic interventions, such as adding from the controls in randomized controlled studies aspirin to streptokinase to reduce the reinfarction or the unexposed subjects in cohort studies). rate following acute coronary syndromes, the NNT may be as high as 20–40 but may still be considered clinically effective. Number needed to screen (NNS) Number needed to harm (NNH) NNS is defined as the number of people that need to be screened for disease (for a given duration) to 14 The NNH is a similar concept proposed by Sackett prevent one death or one adverse event. It can be and colleagues to express the probability of calculated in trials that directly test the effective- ness of a screening strategy by finding the additional adverse events occurring in clinical trials 14 because of the treatment. The absolute difference reciprocal of the ARR. It may also be estimated in risk of harm between the experimental group in clinical trials measuring the benefit of treating and control group is known as the Absolute Risk risk factors. In this case, the prevalence of Increase (ARI). The reciprocal of ARI is the ‘‘NNH’’ unrecognized and untreated disease that can be for that therapy. NNH is defined as the number of detected must be known.
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