9.4.12 Measures of Treatment Impact
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Calculates and Interprets Measures of Treatment Impact: Odds Ratios, Absolute Risk Reduction, Absolute Benefit Increase, Relative Risk Reduction, Relative Benefit Increase, Number-Needed to Treat and Number-Needed to Harm
When evaluating the effectiveness of a treatment, there are several measures that can be calculated and interpreted. These include odds ratios, absolute risk reduction, absolute benefit increase, relative risk reduction, relative benefit increase, number-needed to treat (NNT), and number-needed to harm (NNH).
Remember the 2×2 table from earlier on:
Odd ratios:
Odds ratios are used to compare the odds of an outcome between two groups, such as a treatment group and a control group. An odds ratio of 1 indicates no difference between the groups, while an odds ratio greater than 1 indicates higher odds of the outcome in the treatment group, and an odds ratio less than 1 indicates lower odds of the outcome in the treatment group.
Absolute risk reduction and absolute benefit increase:
Absolute risk reduction (ARR) and absolute benefit increase (ABI) both measure the difference in the risk or benefit of an outcome between two groups. ARR is calculated by subtracting the risk of the outcome in the control group from the risk in the treatment group, while ABI is calculated by subtracting the benefit of the outcome in the control group from the benefit in the treatment group.
Relative risk reduction and relative benefit increase:
Relative risk reduction (RRR) and relative benefit increase (RBI) are expressed as percentages and measure the proportional difference in risk or benefit between two groups. RRR is calculated by subtracting the risk of the outcome in the treatment group from the risk in the control group, dividing that by the risk in the control group, and then multiplying by 100%. RBI is calculated in a similar way, but using the benefit of the outcome.
Number-Needed to Treat/Harm:
NNT and NNH are both used to provide a measure of the clinical significance of treatment. NNT represents the number of patients that need to be treated in order for one additional patient to benefit from the treatment, while NNH represents the number of patients that need to be treated in order for one additional patient to experience harm from the treatment.
| Measure of Treatment Impact | Formula | Interpretation |
| Odds Ratio | (a/b) / (c/d) | The odds of the outcome in the treatment group compared to the control group |
| Absolute Risk Reduction | c/d – a/b | The absolute difference in risk between the treatment and control groups |
| Absolute Benefit Increase | a/b – c/d | The absolute difference in benefit between the treatment and control groups |
| Relative Risk Reduction | (c/d – a/b) / (c/d) | The relative reduction in risk in the treatment group compared to the control group |
| Relative Benefit Increase | (a/b – c/d) / (c/d) | The relative increase in benefit in the treatment group compared to the control group |
| Number-Needed to Treat (NNT) | 1 / ARR | The number of patients who need to be treated for one additional patient to benefit |
| Number-Needed to Harm (NNH) | 1 / ARI | The number of patients who need to be exposed to treatment for one additional patient to be harmed |
- a = True Positive (TP): People with the disease who tested positive for it.
- b = False Negative (FN): People with the disease who tested negative for it.
- c = False Positive (FP): People without the disease who tested positive for it.
- d = True Negative (TN): People without the disease who tested negative for it.
When interpreting measures of treatment impact, it is important to consider the clinical context and the statistical significance of the results.
References:
- Higgins, J. P. T., & Green, S. (Eds.). (2011). Cochrane handbook for systematic reviews of interventions (Version 5.1. 0). The Cochrane Collaboration. Available from https://training.cochrane.org/handbook.
- Altman, D. G. (1998). Statistics in medical journals: developments in the 1980s. Statistics in medicine, 7(1‐2), 205-213.