Number needed to treat
The number needed to treat (NNT) is an epidemiological measure used in assessing the effectiveness of a health-care intervention, typically a treatment with medication. The NNT is the number of patients who need to be treated in order to prevent one additional bad outcome (i.e. the number of patients that need to be treated for one to benefit compared with a control in a clinical trial). It is defined as the inverse of the absolute risk reduction. It was described in 1988.[1] The ideal NNT is 1, where everyone improves with treatment and no-one improves with control. The higher the NNT, the less effective is the treatment.[2]
Variants are sometimes used for more specialized purposes. One example is number needed to vaccinate.[3][4][5]
NNT values are time-specific. For example, if a study ran for 5 years and it was found that the NNT was 100 during this 5 year period, in one year the NNT would have to be multiplied by 5 to correctly assume the right NNT for only the one year period (in the example the one year NNT would be 500) [6]
Contents
Derivation
In general, NNT is computed with respect to two treatments A and B, with A typically the intervention and B the control (e.g., A might be a 5-year treatment with a drug, while B is no treatment). A defined endpoint has to be specified (e.g., the appearance of colon cancer in a five-year period). If the probabilities pA and pB of this endpoint under treatments A and B, respectively, are known, then the NNT is computed as 1/(pB – pA). NNT is a number between 1 and ∞; effective interventions have a low NNT. A negative number would not be presented as a NNT, rather, as the intervention is harmful, it is expressed as a number needed to harm (NNH). The units of the aforementioned probabilities are expressed as number of events per subject (see worked out example below); therefore, the inverse NNH will be number of subjects (required) per event.
Relevance
The NNT is an important measure in pharmacoeconomics. If a clinical endpoint is devastating enough (e.g. death, heart attack), drugs with a high NNT may still be indicated in particular situations. If the endpoint is minor, health insurers may decline to reimburse drugs with a high NNT. Even though NNT is an important measure in a clinical trial, it is infrequently included in medical journal articles reporting the results of clinical trials.[7]
Example: statins for primary prevention
For example, the ASCOT-LLA manufacturer-sponsored study addressed the benefit of atorvastatin 10 mg (a cholesterol-lowering drug) in patients with hypertension (high blood pressure) but no previous cardiovascular disease (primary prevention). The trial ran for 3.3 years, and during this period the relative risk of a "primary event" (heart attack) was reduced by 36% (relative risk reduction, RRR). The absolute risk reduction (ARR), however, was much smaller, because the study group did not have a very high rate of cardiovascular events over the study period: 2.67% in the control group, compared to 1.65% in the treatment group.[8] Taking atorvastatin for 3.3 years, therefore, would lead to an ARR of only 1.02% (2.67% minus 1.65%). The number needed to treat to prevent one cardiovascular event would then be 99.7 for 3.3 years.[9][10]
Worked example
| Example 1: risk reduction | Example 2: risk increase | ||||
|---|---|---|---|---|---|
| Experimental group (E) | Control group (C) | Total | (E) | (C) | |
| Events (E) | EE = 15 | CE = 100 | 115 | EE = 75 | CE = 100 |
| Non-events (N) | EN = 135 | CN = 150 | 285 | EN = 75 | CN = 150 |
| Total subjects (S) | ES = EE + EN = 150 | CS = CE + CN = 250 | 400 | ES = 150 | CS = 250 |
| Event rate (ER) | EER = EE / ES = 0.1, or 10% | CER = CE / CS = 0.4, or 40% | N/A | EER = 0.5 (50%) | CER = 0.4 (40%) |
| Equation | Variable | Abbr. | Example 1 | Example 2 |
|---|---|---|---|---|
| EER − CER | < 0: absolute risk reduction | ARR | (−)0.3, or (−)30% | N/A |
| > 0: absolute risk increase | ARI | N/A | 0.1, or 10% | |
| (EER − CER) / CER | < 0: relative risk reduction | RRR | (−)0.75, or (−)75% | N/A |
| > 0: relative risk increase | RRI | N/A | 0.25, or 25% | |
| 1 / (EER − CER) | < 0: number needed to treat | NNT | (−)3.33 | N/A |
| > 0: number needed to harm | NNH | N/A | 10 | |
| EER / CER | relative risk | RR | 0.25 | 1.25 |
| (EE / EN) / (CE / CN) | odds ratio | OR | 0.167 | 1.5 |
| EE / (EE + CE) − EN / (EN + CN) | attributable risk | AR | (−)0.34, or (−)34% | 0.095, or 9.5% |
| (RR − 1) / RR | attributable risk percent | ARP | N/A | 20% |
| 1 − RR (or 1 − OR) | preventive fraction | PF | 0.75, or 75% | N/A |
The relative risk (odds ratio) is .25 in the example above. It is always 1-relative risk reduction, or vice versa.
See also
- Number needed to harm — the converse for side-effects
References
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- EBEM's Calculator for NNT
- Online Calculator for NNT (GraphPad Software)
- Centre for Evidence Based Medicine: EBM Tools: Critical Appraisal: NNT
- Table of NNTs for various treatmentsde:Anzahl der notwendigen Behandlungen
- ↑ Laupacis A, Sackett DL, Roberts RS (1988). "An assessment of clinically useful measures of the consequences of treatment". N. Engl. J. Med. 318 (26): 1728–33. doi:10.1056/NEJM198806303182605. PMID 3374545.
- ↑ "Number Needed to Treat". Bandolier. Retrieved 2009-05-30.
- ↑ Lua error in package.lua at line 80: module 'Module:Citation/CS1/Suggestions' not found.
- ↑ Brisson M (2008). "Estimating the number needed to vaccinate to prevent herpes zoster-related disease, health care resource use and mortality". Can J Public Health. 99 (5): 383–6. PMID 19009921.
- ↑ Lua error in package.lua at line 80: module 'Module:Citation/CS1/Suggestions' not found.
- ↑ Palle Mark Christensen; Kristiansen, IS (2006). "Number-Needed-to-Treat (NNT) – Needs Treatment with Care". Basic & Clinical Pharmacology & Toxicology. 99 (1): 12–16. doi:10.1111/j.1742-7843.2006.pto_412.x. PMID 16867164.
- ↑ Lua error in package.lua at line 80: module 'Module:Citation/CS1/Suggestions' not found.
- ↑ Sever PS, Dahlöf B, Poulter NR; et al. (2003). "Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial—Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial". Lancet. 361 (9364): 1149–58. doi:10.1016/S0140-6736(03)12948-0. PMID 12686036.
- ↑ "Bandolier — Statin effectiveness: ASCOT update". Retrieved 2008-03-31.
- ↑ John Carey. "Do Cholesterol Drugs Do Any Good?". Business Week. Retrieved 2008-03-31.
