Resources
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Glossary
- Control event rate (CER): proportion of patients who experience an outcome in the control group
- Experimental event rate (EER): proportion of patients who experience an outcome in the experimental group
- Relative risk reduction (RRR): difference in event rates relative to (or proportional to) the control event rate, expressed as a percentage. RRR = (CER - EER) / CER
- Absolute risk reduction (ARR): difference between the control event rate and the experimental event rate, expressed as a percentage. ARR = CER - EER
- Number needed to treat (NNT): the number of patients that would need to be treated in order for ONE of them to have the beneficial outcome. It is calculated by calculating the reciprocal (or inverse) of the ARR. NNT = 1 / ARR
Note: if the ARR is expressed as a percentage (%) then: NNT = 1/ARR x 100 or 100/ARR - Number needed to harm (NNH): the number of patients that would need to be treated in order for ONE on them to experience the adverse outcome. It is calculated by calculating the reciprocal (or inverse) of the absolute risk increase (ARI). NNH = 1/ARI
Note: if the ARI is expressed as a percentage (%) then NNH = 1/ARI x 100 or 100/ARI - Confidence Interval: tells you the range of values within which the true value could feasibly lie, given the size of the difference observed.
Resources
| Title/link | Description |
|---|---|
| Relative Risk Reduction and Absolute Risk Reduction (RLO) | This RLO considers how to measure and interpret the magnitude of effect in clinical trial results using relative risk reduction (RRR) and absolute risk reduction (ARR). |
| Determining the clinical importance of trial results (RLO) | Demonstrates how to interpret and use clinical trial data (ARR, RRR, NNT, NNH, and confidence intervals) in practice. |
| Surrogate Outcomes (RLO) | Considers the type of evidence which should be used when making decisions about patient care. |
| Sensitivity and Specificity (RLO) | Explains how diagnostic test accuracy is described by the terms sensitivity and specificity. Sensitivity describes the accuracy of the test in detecting disease. Specificity describes the accuracy of the test in detecting health. |
| Confidence Intervals (RLO) | Defines the term 'confidence intervals' and demonstrates how they can be used to determine the significance and range of possible sizes of a treatment effect. |
Books and Journals
| Barratt A et al. Tips for learners of evidence-based medicine: 1. Relative risk reduction, absolute risk reduction and number needed to treat.. CMAJ 2004;171 (4):353-358. |
| Watt E, Burrell A. Implementing NNTs. Volume 1, number 7 available at BMJ Journals. |
Numbers needed to treat (NNT) and numbers needed to harm (NNH) - Print summary
This RLO explains numbers needed to treat and numbers needed to harm.
Learning outcomes
By completing this resource you will have learnt about:
- numbers needed to treat (NNT)
- numbers needed to harm (NNH)
- calculating NNH and NNT
Learning outcomes
By completing this resource you will have learnt about:
- numbers needed to treat (NNT)
- numbers needed to harm (NNH)
- calculating NNH and NNT
This resource was developed by:
Briony Leighton - content author
Liz Hilton - developer
The resource was originally funded by RLO-CETL.
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