Glossary of diagnostic terms


 

Bandolier 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, Bandolier has a book review 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.

 


Bias. 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 diagnostic tests 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 circumstances.


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.


Cost-benefit analysis . Assesses whether the cost of an intervention is worth the benefit by measuring both in the same units; monetary units are usually used.


Cost-effectiveness analysis. 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 for Chlamydia 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.


Incidence. The proportion of new cases of the target disorder in the population at risk during a specified time interval.


Inception cohort. A group of patients who are assembled near the onset of the target disorder.


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.


Meta-analysis. A systematic review that uses quantitative methods to summarise the results. This may be achieved in several ways. Examples on diagnosis of diabetes and head injury are interesting.


Negative predictive value . Proportion of people with a negative test who are free of the target disorder.


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. Bandolier prepareed at Table of NNTs in 1998.


Odds . 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 disorder).


Positive predictive value . Proportion of people with a positive test who have the target disorder.


Post-test odds. The odds that the patient has the target disorder after the test is carried out (pre-test odds x likelihood ratio).


Post-test probability. The proportion of patients with that particular test result who have the target disorder (post test odds/[1 + post-test odds]).


Pre-test odds. The odds that the patient has the target disorder before the test is carried out (pre-test probability/[1 – pre-test probability]).


Pre-test probability/prevalence. 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 dementia .

Reporting quality. 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.


Sensitivity. Proportion of people with the target disorder who have a positive test. It is used to assist in assessing and selecting a diagnostic test/sign/symptom.


SnNout. 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.


Specificity. Proportion of people without the target disorder who have a negative test. It is used to assist in assessing and selecting a diagnostic test/sign/symptom.

 

Spectrum bias . 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.


SpPin. 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 ascites.


Systematic review. 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 reviewing reviews is worth a read.