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Family Practice Advance Access published online on September 1, 2008

Family Practice, doi:10.1093/fampra/cmn051
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© The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Spectrum bias—why clinicians need to be cautious when applying diagnostic test studies

Brian H Willis

Health Methodology Group, University of Manchester, Block 3, First Floor, University Place, Oxford Road, Manchester M13 9PL, UK

Email: Brian.Willis{at}manchester.ac.uk

Received 24 September 2007; Revised 28 June 2008; Accepted 29 July 2008.


   Abstract

When applying study results to their practice, the clinician is constrained by a number of factors, perhaps none more important than spectrum bias, which describes the effect a change in patient case mix may have on the performance of a test. Although the literature contains notable examples of spectrum bias, the emphasis has been to demonstrate its existence and its implications on study design rather than how it affects the clinician. Here a definition is proposed before considering it from a GP's perspective. As a patient's probability of disease is in part determined by the test's result, having reliable estimates of a test's performance is imperative to making good decisions on patient management. Knowing how the test performs on a patient usually means knowing its performance within a particular subgroup. Unfortunately, studies tend to report weighted average estimates of performance across broad populations. Such estimates may be inaccurate at an individual level and at a population level with the overall performance of the test in practice varying significantly from the average estimate reported, owing to differing case mixes. To avert such problems, investigators should design studies to evaluate tests over all relevant subgroups, and where this is not possible, to be explicit about the case mix in the study sample. Furthermore, GPs should endeavour to know both individual patients and practice populations as a whole in terms of demographics and co-morbidities before applying study results to their patients.

Keywords. Diagnostic tests, decision science, epidemiology, post-graduate education, sensitivity and specificity, likelihood ratio.


Willis BH. Spectrum bias—why clinicians need to be cautious when applying diagnostic test studies. Family Practice 2008; Pages 1–7 of 7.


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