Terms used in therapeutics

1. When the experimental treatment reduces the risk for a bad event:

RRR (relative risk reduction): the proportional reduction in rates of bad events between experimental (experimental event rate [EER]) and control (control event rate [CER]) patients in a trial, calculated as |EER ­ CER|/CER and accompanied by a 95% confidence interval (CI).

ARR (absolute risk reduction): the absolute arithmetic difference in event rates, |EER ­ CER|.

NNT (number needed to treat): the number of patients who need to be treated to achieve one additional favourable outcome; calculated as 1/ARR, rounded up to the next highest whole number, and accompanied by its 95% CI.

2. When the experimental treatment increases the probability of a good event:

RBI (relative benefit increase): the increase in the rates of good events, comparing experimental and control patients in a trial, also calculated as |EER ­ CER|/CER.

ABI (absolute benefit increase): the absolute arithmetic difference in event rates, |EER ­ CER|.

NNT: calculated as 1/ABI; denotes the number of patients who must receive the experimental treatment to create one additional improved outcome in comparison with the control treatment.

3. When the experimental treatment increases the probability of a bad event:

RRI (relative risk increase): the increase in rates of bad events, comparing experimental patients to control patients in a trial, and calculated as for RBI. RRI is also used in assessing the effect of risk factors for disease.

ARI (absolute risk increase): the absolute difference in rates of bad events, when the experimental treatment harms more patients than the control treatment; calculated as for ABI.

NNH (number needed to harm): the number of patients who, if they received the experimental treatment, would lead to one additional person being harmed compared with patients who receive the control treatment; calculated as 1/ARI.

Confidence interval (CI): the CI quantifies the uncertainty in measurement; usually reported as 95% CI, which is the range of values within which we can be 95% sure that the true value for the whole population lies.

Terms used in diagnosis

Sensitivity: the proportion of patients with the target disorder who have a positive test result (a/[a + c]) (Figure 1).

Specificity: the proportion of patients without the target disorder who have a negative test result (d/[b + d]) (Figure 1).


Pretest probability (prevalence): the proportion of patients who have the target disorder, as determined before the test is carried out ([a + c]/[a + b + c + d]) (Figure 1).

Pretest odds: the odds that the patient has the target disorder before the test is carried out (pretest probability/[1 ­ pretest probability]).

Likelihood ratio (LR): the ratio of the probability of a test result among patients with the target disorder to the probability of that same test result among patients who are free of the target disorder. The LR for a positive test is calculated as sensitivity/(1 ­ specificity). The LR for a negative test is calculated as (1 ­ sensitivity)/specificity.

Post-test odds: the odds that the patient has the target disorder after the test is carried out (pretest odds ¥ LR).

Post-test probability: the proportion of patients with that particular test result who have the target disorder (post-test odds/ [1 + post-test odds]). Use of the nomogram (Figure 2) avoids the need for these calculations: Anchor a straight edge on the left-hand column at the appropriate pretest probability and direct it through the central column at the value of the LR. The approximate post-test probability can be read off the right-hand column.