In
biostatistics
Biostatistics (also known as biometry) are the development and application of statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experimen ...
, spectrum bias refers to the phenomenon that the performance of a
diagnostic test
A medical test is a medical procedure performed to detect, diagnose, or monitor diseases, disease processes, susceptibility, or to determine a course of treatment. Medical tests such as, physical and visual exams, diagnostic imaging, genetic ...
may vary in different clinical settings because each setting has a different mix of patients.
Because the performance may be dependent on the mix of patients, performance at one clinic may not be predictive of performance at another clinic.
These differences are interpreted as a kind of ''bias''. Mathematically, the spectrum bias is a
sampling bias
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human f ...
and not a traditional
statistical bias
Statistical bias is a systematic tendency which causes differences between results and facts. The bias exists in numbers of the process of data analysis, including the source of the data, the estimator chosen, and the ways the data was analyzed. ...
; this has led some authors to refer to the phenomenon as ''spectrum effects'',
whilst others maintain it is a bias if the true performance of the test differs from that which is 'expected'.
Usually the performance of a diagnostic test is measured in terms of its
sensitivity and
specificity and it is changes in these that are considered when referring to spectrum bias. However, other performance measures such as the
likelihood ratios may also be affected by spectrum bias.
Generally spectrum bias is considered to have three causes.
The first is due to a change in the case-mix of those patients with the target disorder (disease) and this affects the
sensitivity. The second is due to a change in the case-mix of those without the target disorder (disease-free) and this affects the
specificity. The third is due to a change in the prevalence, and this affects both the
sensitivity and
specificity.
[ ] This final cause is not widely appreciated, but there is mounting
empirical evidence
Empirical evidence for a proposition is evidence, i.e. what supports or counters this proposition, that is constituted by or accessible to sense experience or experimental procedure. Empirical evidence is of central importance to the sciences ...
[Leeflang MM, Bossuyt PM, Irwig L., Diagnostic test accuracy may vary with prevalence: implications for evidence-based diagnosis, J Clin Epidemiol. 2009 Jan;62(1) 5–12.] as well as theoretical arguments
which suggest that it does indeed affect a test's performance.
Examples where the
sensitivity and
specificity change between different sub-groups of patients may be found with the
carcinoembryonic antigen
Carcinoembryonic antigen (CEA) describes a set of highly related glycoproteins involved in cell adhesion. CEA is normally produced in gastrointestinal tissue during fetal development, but the production stops before birth. Consequently, CEA is u ...
test
and
urinary dipstick tests.
Diagnostic test performances reported by some studies may be artificially overestimated if it is a case-control design where a healthy population ('fittest of the fit') is compared with a population with advanced disease ('sickest of the sick'); that is two extreme populations are compared, rather than typical healthy and diseased populations.
[Rutjes AWS, Reitsma JB, Vandenbroucke JP, Glas AS, Bossuyt PMM, Case-control and two-gate designs in diagnostic accuracy studies, Clin Chem 2005;51(8):1335–41.]
If properly analyzed, recognition of
heterogeneity of subgroups can lead to insights about the test's performance in varying populations.
See also
*
Simpson's paradox
Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science st ...
*
Biased sample
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample of a population (or non-human fa ...
*
Reporting bias
In epidemiology, reporting bias is defined as "selective revealing or suppression of information" by subjects (for example about past medical history, smoking, sexual experiences). In artificial intelligence research, the term reporting bias is ...
*
Reference class problem
In statistics, the reference class problem is the problem of deciding what class to use when calculating the probability applicable to a particular case.
For example, to estimate the probability of an aircraft crashing, we could refer to the fr ...
References
{{DEFAULTSORT:Spectrum Bias
Biostatistics
Bias
Design of experiments
Medical statistics