Absolute Risk Reduction

The arithmetic difference between the absolute risk of an outcome in a control group and in a treatment group.

Source: Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd ed. Lippincott Williams & Wilkins; 2008.

Absolute risk reduction is the plain difference between the risk of an outcome in an untreated group and the risk in a treated group. It tells us how much a treatment lowers the chance of the event in real terms, for instance cutting risk from six in a hundred to four, a reduction of two per hundred treated. This absolute figure conveys the tangible benefit better than a ratio, and it leads directly to the number of patients who must be treated for one to benefit. The real drop in risk is what it measures. Rothman and colleagues (2008) describe this.

Source: Rothman et al. 2008

Absolute risk reduction is calculated by subtracting the absolute risk of the outcome in the treatment group from the absolute risk in the control group. Each absolute risk is the proportion experiencing the outcome in that group, and their difference is the absolute risk reduction. So absolute risk reduction is calculated as the control-group risk minus the treatment-group risk, giving the reduction in risk attributable to the treatment in absolute terms, which directly conveys how much the treatment lowers the outcome's probability, and from which the number needed to treat is obtained as its reciprocal.

Source: Rothman, Greenland & Lash 2008

Absolute risk reduction is useful because it conveys the practical size of a treatment's benefit, showing the actual reduction in risk, which relative measures such as the relative risk reduction can obscure when the baseline risk is low. It reflects the baseline risk and translates into the number needed to treat, aiding decisions. So absolute risk reduction is useful for judging and communicating the real-world benefit of a treatment, since a large relative reduction may correspond to a small absolute one, and knowing the absolute reduction is what allows patients and clinicians to weigh the benefit meaningfully against harms and costs.

Source: Rothman, Greenland & Lash 2008

Absolute risk reduction relates to the number needed to treat as its reciprocal: the number needed to treat is one divided by the absolute risk reduction, giving the number of patients who must be treated to prevent one additional adverse outcome. A larger absolute risk reduction gives a smaller number needed to treat, indicating greater benefit. So absolute risk reduction and the number needed to treat are two expressions of the same information, with the absolute risk reduction giving the difference in risk and the number needed to treat translating it into how many must be treated for one to benefit, both conveying practical benefit.

Source: Rothman, Greenland & Lash 2008

Absolute risk reduction is the arithmetic difference in risk between control and treatment groups, while relative risk reduction is that difference expressed as a proportion of the control-group risk. The absolute measure conveys the actual reduction, whereas the relative measure conveys the proportional reduction. The same relative risk reduction can correspond to very different absolute reductions depending on the baseline risk. So the two differ in scale: absolute risk reduction gives the practical magnitude of benefit and relative risk reduction its proportional size, and reporting the absolute reduction alongside the relative one prevents the benefit from appearing larger than it is in practice.

Source: Rothman, Greenland & Lash 2008