The evidence-based journals (Evidence Based Medicine and
ACP Journal Club) have achieved consensus on some terms
they use to describe both the good and bad effects of
therapy. We will bring them to life with a synthesis of
three randomized trials in diabetes which individually
showed that several years of intensive insulin therapy
reduced the proportion of patients with worsening
retinopathy to 13% from 38%, raised the proportion of
patients with satisfactory hemoglobin A1c levels to 60%
from about 30%, and increased the proportion of patients
with at least one episode of symptomatic hypoglycemia to
57% from 23%. Note that in each case the first number
constitutes the “experimental event rate” (EER) and the
second number the “control event rate” (CER). We will
use the following terms and calculations to describe
these effects of treatment:
When the
experimental treatment reduces the probability of a bad
outcome (worsening diabetic retinopathy)
RRR (relative risk reduction). The
proportional reduction in rates of bad outcomes between
experimental and control participants in a trial,
calculated as |EER – CER|/CER, and accompanied by a 95%
confidence interval (CI). In the case of worsening
diabetic retinopathy, |EER – CER|/CER = |13% – 38%|/38%
= 66%.
ARR (absolute risk reduction). The absolute
arithmetic difference in rates of bad outcomes between
experimental and control participants in a trial,
calculated as |EER – CER|, and accompanied by a 95% CI.
In this case, |EER – CER| =|13% – 38%| = 25%. (This is
sometimes called the risk difference)
NNT (number needed to treat). The number of
patients who need to be treated to achieve one
additional favorable outcome, calculated as 1/ARR and
accompanied by a 95% CI. In this case, 1/ARR = 1/25% =
4.
When the
experimental treatment increases the probability of a
good outcome (satisfactory hemoglobin A1c levels):
RBI (relative benefit increase). The
proportional increase in rates of good outcomes between
experimental and control patients in a trial, calculated
as |EER – CER|/CER, and accompanied by a 95% confidence
interval (CI). In the case of satisfactory hemoglobin
A1c levels, |EER – CER|/CER =|60% – 30%|/30% = 100%.
ABI (absolute benefit increase). The absolute
arithmetic difference in rates of good outcomes between
experimental and control patients in a trial, calculated
as |EER – CER|, and accompanied by a 95% confidence
interval (CI). In the case of satisfactory hemoglobin
A1c levels, |EER – CER| = |60% – 30%| =30%
NNT (number needed to treat). The number of
patients who need to be treated to achieve one
additional good outcome, calculated as 1/ARR and
accompanied by a 95% CI. In this case, 1/ARR = 1/30% =
3.
When the
experimental treatment increase the probability of a bad
outcome (episodes of hypoglycemia):
RRI (relative risk increase). The proportional
increase in rates of bad outcomes between experimental
and control patients in a trial, calculated as |EER –
CER|/CER, and accompanied by a 95% confidence interval
(CI). In the case of hypoglycemic episodes, |EER – CER|/CER
= |57% – 23%|/23% = 148%. (RRI is also used in assessing
the impact of “risk factors” for disease.)
ARI (absolute risk increase). The absolute
arithmetic difference in rates of bad outcomes between
experimental and control patients in a trial, calculated
as |EER – CER|, and accompanied by a 95% confidence
interval (CI). In the case of hypoglycemic episodes, |EER
– CER| = |57% – 23%| = 34%. (ARI is also used in
assessing the impact of “risk factors” for disease.)
NNH (number needed to harm). The number of
patients who, if they received the experimental
treatment, would result in one additional patient being
harmed, compared with patients who received the control
treatment, calculated as 1/ARR and accompanied by a 95%
CI.
In this case, 1/ARR = 1/34% = 3.