Application of Number Needed to Treat (NNT) - GOLD

More documents

Recommendations

Info

80 Cazzola THIS MANUSCRIPT IS PROVIDED IN CONFIDENCE TO DETERMINE REPRINT INTEREST ONLY AND SHOULD NOT BE DISTRIBUTED EITHER INTERNALLY OR EXTERNALLY VIA PRINT OR ELECTRONIC MEDIA FOR OTHER THAN THE STATED PURPOSE. 1. Interpreting Clinical Trial Results intervention is identical in both high- and low-risk groups (25%), the absolute risk reduction is considerably higher in the high-risk Absolute and relative risk reductions are used extensively to (10%) than in the low-risk (2.5%) group. summarize the effects of treatment in clinical trials (table I). In a While relative risk reduction can provide a basis for balancing parallel-group study, for instance, the relative risk, or the risk of an benefits and drawbacks of therapy, it should be accompanied by an event in the treatment group relative to that in the control group, is estimate of baseline or untreated risk in individual patients, and defined as the ratio of the risks in the two treatment groups (i.e. the may be subject to differences in interpretation. Absolute risk, as probability of an event in the active treatment group divided by the probability in the control group). [6] Although this concept is straightforward and easily understood, it may not give a clinically meaningful illustration of the difference between treatments, as the value attached to any change will be the same regardless of the baseline severity of disease (see McQuay and Moore [7] and Barratt et al. [8] for further details). A comparison can also be expressed in terms of the relative risk reduction, which is the difference in event rates between the two treatment groups (usually constant across groups with different risks). This measure is obtained by subtracting the relative risk from 1, and is therefore the ratio between the decrease in risk in the group of interest and the risk in the control or comparator group. It is worth noting at this point that although relative risk and relative risk reduction give a good quantitative illustration of clinical effect in proportional terms, they do not tell practitioners anything about effect sizes on an absolute scale. [7] Although absolute risk conveys little information on proportional effects, it is a much better indicator of whether an intervention has effects that are likely to be clinically meaningful. Its chief disadvantage is that it is a dimensionless and abstract number that lacks a direct connection with the particular clinical situation. [7] Absolute risk reduction, or risk difference, is an important alternative expression of comparative results, and is simply the difference in event rates between groups. [8] These concepts are illustrated in figure 1, where an example is used of a hypothetical trial in which interventions are being compared in two groups of patients (high- and low-risk groups). While the relative risk reduction for the Table I. Definitions of measures used to report outcomes in clinical trials [8] Measure Absolute risk reduction Relative risk reduction Number needed to treat Number needed to harm Definition The arithmetic difference between two event rates The difference in event rates between two groups expressed as a proportion of the event rate in the untreated group The inverse of absolute risk reduction, or the number of patients who would have to receive treatment for one of them to benefit The inverse of absolute risk reduction, or the number of patients who would have to receive treatment for one of them to experience an adverse outcome already stated, lacks a direct connection with the clinical setting. Neither of these measures aid clinical decision making. NNT provides a means of achieving this end. 2. Number Needed to Treat (NNT) NNT is the reciprocal of the absolute risk reduction (expressed as a proportion) associated with the treatment or intervention under examination. [9] Thus, NNT is the number of patients who would have to receive treatment in order for one individual to benefit from treatment or to avoid an adverse outcome over a given period of time. As an example, where NNT = 10: • treatment has to be given to 10 patients for improvement/ prevention of adverse outcome in one; or • each patient who receives treatment has a 1 in 10 chance of benefiting from treatment. Table II shows how NNT is calculated from absolute risk reduction (as illustrated for the example in figure 1) in high- and low-risk patients. Only 10 patients in the high-risk group need to receive the intervention for a benefit to be seen in one of them, whereas this number rises to 40 in the low-risk group. This distinction is not evident from relative risk (figure 1); both groups have reductions in risk relative to control of 25%. NNT therefore captures the effect of the baseline condition. NNT values approaching 1 indicate that the outcome under investigation occurs in almost all treated patients and, conversely, in few patients in the comparator group. In practice, low NNT values of this magnitude rarely occur, with the possible exception of interventions such as the use of antibacterials versus placebo. [7] While NNT values of 2–3 indicate that a treatment is quite effective, some prophylactic interventions with NNTs as high as 20–40 may still be regarded as clinically effective. [7] In addition to NNT, the number needed to harm (NNH) can be calculated. This is the number of patients who would have to undergo treatment for one of them to experience an adverse event. NNH is determined as 100 divided by the absolute risk increase expressed as a percentage (or the reciprocal of the risk expressed as a proportion). Several variations of NNT have also been developed. These include NNT at any time after the start of treatment (see Altman and Andersen [10] ) and the number needed to screen (see Rembold [11] ). © 2006 Adis Data Information BV. All rights reserved. Treat Respir Med 2006; 5 (2)
NNT as an Efficacy Measure in Respiratory Medicine 81 THIS MANUSCRIPT IS PROVIDED IN CONFIDENCE TO DETERMINE REPRINT INTEREST ONLY AND SHOULD NOT BE DISTRIBUTED EITHER INTERNALLY OR EXTERNALLY VIA PRINT OR ELECTRONIC MEDIA FOR OTHER THAN THE STATED PURPOSE. Risk of outcome (%) 45 40 35 30 25 20 15 10 5 0 40 30 High-risk patients 10 Low-risk patients Control Intervention Fig. 1. Event rates and risk reduction. The bars represent the probability of an outcome of interest in a clinical trial in which a treatment intervention is being compared with a control group. Results are shown for hypothetical high- and low-risk patients. Note how the relative risk and relative risk reduction remain the same for patients at high or low risk at baseline (see table II). Rates for risk of outcome (i.e. event rates) are 40% and 30% in the control and intervention groups, respectively, in high-risk patients. Corresponding rates in low-risk patients are 10% and 7.5%, respectively. As shown in table II, the rate of absolute risk reduction in the high-risk group is 40% – 30% = 10% and that in the low-risk group is 10% – 7.5% = 2.5%. In addition, as shown in table II, the relative risk in the high-risk group is 30%/ 40% = 0.75 and the relative risk reduction is 1 – 0.75 = 0.25 (i.e. 25%). Similarly, for the low-risk group, the relative risk is 7.5%/10% = 0.75 and the relative risk reduction is 1 – 0.75 = 0.25 (25%). 2.1 Applying Confidence Intervals to NNT 7.5 producing sensible CIs for NNT values have been proposed (see Altman [13] for details). 2.2 Limitations of NNT NNT values are subject to some limitations, and care is needed when applying this method. The NNT for any given intervention should always have a reference or comparator group attached to it, and a particular outcome and period of treatment must be defined. [7] NNTs are also treatment specific, and it is not appropriate to use them for comparisons between different diseases, especially when the outcomes of interest differ. For example, an NNT of 20 for preventing an asthma exacerbation may be valued differently to the same NNT value referring to prevention of COPD exacerbation. The numerical value is a function of disease, intervention, treatment period and outcome, and NNTs should therefore only be compared directly for different interventions if they refer to the same condition and severity with the same outcome. 2.3 Adjusting NNT for Baseline Risk NNT values for a specific intervention depend not only on the treatment being given but also on baseline risk. So any NNT that is obtained from the literature should be adjusted in accordance with the risk profile of the patient(s) being treated. Cook and Sackett [6] describe a simple method which allows adjustment of a trial NNT value for the baseline risk of an individual patient. 2.4 Application to Systematic Reviews As for any point estimate, confidence intervals (CIs) should be and Meta-Analyses quoted for NNT values whenever possible. The 95% CIs for NNT can be simply calculated by inverting the 95% CIs for absolute risk NNT is particularly useful where several treatments are as- reduction. However, when the difference between two treatments sessed for the same outcome measure in patients with the same is not significant, peculiarities can arise, i.e. negative values or CIs disease condition. Treatments can then be ranked according to which include infinity. [12] For example, if the absolute risk reducbalanced against adverse events and costs, and against patient their effectiveness to aid clinical selection, as long as the NNTs are tion is 10%, with 95% CI of –5%, 25%, this gives rise to an NNT characteristics, expectations and preferences. [7] Systematic reof 10 with 95% CI of –20, 4. The CI of –20, 4 will necessarily have views, including the Cochrane database, often include NNT as a to include infinity, which gives rise to two disjointed regions that measure and there are several recent examples of this in respiratocontain values of the NNT from 4 to infinity and from –20 to ry medicine. [12,14-22] minus infinity. For this reason, NNTs are often reported without There is, however, some controversy attached to the use of CIs when they are not significant. [7] Alternative techniques for NNTs derived from meta-analyses. [23] While NNT is recognized as Table II. The number needed to treat (NNT) to observe a benefit in a single individual in high- and low-risk patients undergoing a hypothetical treatment intervention (see also figure 1) Risk category Clinical question Event rate Relative risk Absolute risk NNT control intervention reduction reduction group group High-risk patients What is the reduction in risk of the 40 30 25% or 0.25 10% or 0.1 100/10 or 1/0.1 = 10 event? Low-risk patients What is the reduction in risk of the 10 7.5 25% or 0.25 2.5% or 0.025 100/2.5 or 1/0.025 = 40 event? © 2006 Adis Data Information BV. All rights reserved. Treat Respir Med 2006; 5 (2)
Page 1: Treat Respir Med 2006; 5 (2): 79-84
Page 5 and 6: NNT as an Efficacy Measure in Respi

Application of Number Needed to Treat (NNT) - GOLD

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?