Home' Australian Pharmacist : Australian Pharmacist December 2013 Contents Australian Pharmacist December 2013 I ©Pharmaceutical Society of Australia Ltd. 39
EVIDENCE BASED MEDICINE IN ACTION
Are the results relevant to your
Is the study population similar to the
patients in your practice?
It is very important to get a good
description of the patients who entered the
study to be able to decide if they are similar
to your own. Enrolment in studies is usually
based on explicit criteria that must be
carefully considered before extrapolating
the results to individual patients.
Is the intervention reproducible and
feasible in your own setting?
The nature and components of the
intervention should be clear enough
to indicate whether the intervention is
feasible. Is it affordable in terms of costs?
Are the likely bene ts worth the potential
harms and costs?
Individual judgment of benefits and
risks may be necessary in many cases.
The best way to approach this situation
is to map out the proposed improvement
in outcomes, other clinical benefits and
any documented harm. Once this process
map is developed, try to best assess
the impact of these changes in your
What alternative interventions are
It is also important to know what
alternative interventions can be
considered in place of the intervention
In summary, this brief review aims to
summarise (Table 2) some of the concepts
that apply when interpreting trial results.
It is always important not to take what is
presented for 'face value', and to ensure
that we have an understanding of what
the results of trials mean to us and more
importantly to our patients.
1. Strauss SE, Richardson WS, Glasziou P, Haynes RB. Evidence-
based medicine: how to practice and teach EBM, third edition.
Edinburgh: Churchill Livingstone: 2005.
2. Centre for Evidence-Based Medicine. At: www.cebm.net/
3. Greenberg P. The Interpretation of clinical trials. Australian
4. Singh AK, Kelley K, Agarwal R. Interpreting results of clinical
trials: a conceptual framework Clin J Am Soc Nephrol,
5. Understanding Statistical Terms: 2. DTB 2009; 47: 35--6.
This is the likelihood of an event happening compared with the total number of possible events
(e.g. If 1 person died out of 100, the risk of death, the mortality rate, is 1%or 0.01).
Absolute risk and absolute risk reduction
The absolute risk (AR) is the possibility that an individual will experience the specified outcome
(risk) during a specified period. It lies in the range 0 (definitely will not occur) to 1 (definitely will
occur), or is expressed as a percentage. In the context of a RCT, absolute risk reduction (ARR) is
the amount by which a treatment reduces the risk of an event. For example, reducing the risk
from 30% to 20% gives an absolute risk reduction of 10%.
Relative risk or risk ratio
In the context of a RCT, the relative risk (RR) is the chance of an outcome (e.g. death) while
on a specific treatment compared with the chance while on an alternative treatment (or no
treatment). It is calculated by dividing the rate of the event (number of events divided by the
total possible) in one group of patients within a study by the rate in another, comparative,
group. The result is a proportion or a fraction. For example, if the risk of mortality on a drug is
1% and the baseline risk without treatment is 4%, the relative risk is 1% divided by 4%, that is ¼
(or 25% or 0.25).
The 'odds' of an event occurring is another way of describing the chance of it happening.
However, odds differ from a risk calculated by dividing the chance of an event by the total
number of possible events. By contrast, the odds are derived by dividing the number of people
with an event by the number who did not have the event.
The odds ratio (OR) is similar to the relative risk but is particularly useful where an outcome
is rare. It is calculated by dividing the odds of an outcome in one group by the odds of the
outcome in another group.
Number needed to treat (NNT)
If a treatment reduces the likelihood of an unwanted outcome (e.g. death), the size of this
benefit can be calculated as the absolute risk reduction (ARR; see above). Calculating the
reciprocal of the absolute risk reduction (1 divided by ARR) gives the number of patients that
would need to be treated for a defined period in order to prevent one unwanted outcome
(e.g. death). For example, if treatment with a drug for 1 year reduces the risk of death from
21%to 17%, this means that the ARR is 4% (0.04); 1 divided by 0.04=25, so 25 patients would
need to be treated for 1 year to prevent 1 death. The NNT can give an indication of the
effectiveness of a treatment - something that gives a large reduction in risk will have a small NNT
(i.e. fewer patients need to be treated to demonstrate benefit). NNT is also sometimes written as
NNTB (where 'B' stands for 'benefit').
• Was the assignment of patients randomised?
• Were the subjects and the assessors blinded to the intervention and was a placebo used?
• Apart from the experimental intervention, were the two groups treated equally?
• Was the follow-up sufficiently long and complete?
• Were all the patients analysed in the groups to which they were allocated?
2. Clinical Importance
• Was the outcome of sufficient importance to recommend treatment to patients?
• Was the treatment effect large enough to be clinically relevant?
• What was the size of the treatment effect?
• Was the treatment effect precise?
• Are the conclusions based on the primary research question being answered?
• Is the study population similar to the patients in your practice?
• Is the intervention reproducible and feasible in your own setting?
• Are the likely benefits worth the potential harms and costs?
• What alternative interventions are available?
Table 1. Key de nitions5
Table 2. Questions to help interpret results from clinical trials
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