intends to develop a series of glossaries about terms used in diagnostic
testing. These are not always intuitive or simple, and are often obtuse and
complicated. So to try and make them easier, we will start to develop
examples behind the definitions with hypertext links to make them easily
available. The fact that these terms are used does not make them useful. We
probably need better terms to describe the results of diagnostic tests. Until
those are developed, we have to work with what is there.
For those who want to learn more, faster,
section you should visit. It has examined most of the helpful books around
the use of evidence in healthcare. The reviews will help starters and those
of us who know something, but want to know more.
This is the tendency of some (poor) study designs systematically to
produce results that are better (rarely if ever worse) than those with a
robust design. Bias for
works in different ways to bias in
trials of treatment
Clinical practice guideline.
A systematically developed statement designed to assist clinician and
patient decisions about appropriate health care for specific clinical
Confidence interval (CI)
. Quantifies the uncertainty in measurement. It is 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. For example, for an NNT of 10
with a 95% CI of 5 to 15, we would have 95% confidence that the true NNT
value was between 5 and 15.
. Assesses whether the cost of an intervention is worth the benefit by
measuring both in the same units; monetary units are usually used.
Measures the net cost of providing a service as well as the outcomes
obtained. Outcomes are reported in a single unit of measurement. An example
is a useful guide.
Cost minimisation analysis.
If health effects are known to be equal, only costs are analysed and the
least costly alternative is chosen.
Cost utility analysis.
Converts effects into personal preferences (or utilities) and describes
how much it costs for some additional quality gain (e.g. cost per
additional quality-adjusted life-year, or QALY).
Decision analysis (or clinical decision analysis)
. The application of explicit, quantitative methods that quantify
prognoses, treatment effects, and patient values in order to analyse a
decision under conditions of uncertainty.
The proportion of new cases of the target disorder in the population at
risk during a specified time interval.
A group of patients who are assembled near the onset of the target
Likelihood ratio (LR)
The likelihood that a given test result would be expected in a patient
with the target disorder compared with the likelihood that the same
result would be expected in a patient without the target disorder.
A systematic review that uses quantitative methods to summarise the
results. This may be achieved in several ways. Examples on diagnosis of
Negative predictive value
. Proportion of people with a negative test who are free of the target
Number needed to treat (NNT)
The inverse of the absolute risk reduction and the number of patients
that need to be treated to prevent one bad outcome.
Table of NNTs
A ratio of the number of people incurring an event to the number
of people who have non-events.
Odds ratio (OR)
The ratio of the odds of having the target disorder in the
experimental group relative to the odds in favour of having the
target disorder in the control group (in cohort studies or
systematic reviews), or the odds in favour of being exposed in
subjects with the target disorder divided by the odds in favour
of being exposed in control subjects (without the target
Positive predictive value
. Proportion of people with a positive test who have the target
The odds that the patient has the target disorder after the test
is carried out (pre-test odds x likelihood ratio).
The proportion of patients with that particular test result who have
the target disorder (post test odds/[1 + post-test odds]).
The odds that the patient has the target disorder before the test is
carried out (pre-test probability/[1 pre-test
The proportion of people with the target disorder in the population
at risk at a specific time (point prevalence) or time interval
(period prevalence). Prevalence may depend on how a disorder is
diagnosed. A good example is
In diagnostic testing, a number of standards for reporting quality
have been set. They define those minimal features that need to be
addressed in any report of a diagnostic test.
Proportion of people with the target disorder who have a
positive test. It is used to assist in assessing and selecting a
When a sign/test/symptom has a high Sensitivity: a Negative result
rules out the diagnosis. For example, the sensitivity of a history
of ankle swelling for diagnosing ascites is 93%; therefore if a
person does not have a history of ankle swelling, it is highly
unlikely that the person has ascites.
Proportion of people without the target disorder who have a
negative test. It is used to assist in assessing and selecting a
An unrecognised (but probably very real) problem is that of
spectrum bias. This is the phenomenon of the sensitivity and/or
specificity of a test varying with different populations tested -
populations which might vary in sex ratios, age, or severity of
disease as three simple examples.
When a sign/test/symptom has a high Specificity; a Positive
result rules in the diagnosis. For example , the specificity of a
fluid wave for diagnosing ascites is 92%; therefore if a person
does have a fluid wave, it rules in the diagnosis of
A summary of the medical literature that uses explicit methods to
perform a thorough literature search and critical appraisal of
individual studies and that uses appropriate statistical techniques
to combine these valid studies. Systematic reviews are not all
equal, and quality issues are important. Guidance for
is worth a read.