Letters

Patient outcomes and population context affect test accuracy

EDITORPublication of the STARD paper, on standards for reporting of studies of diagnostic accuracy, should ensure increased attention to the problems of poor diagnostic research.¹ Increased awareness of reporting of accuracy studies should lead to better study designs and hence improve the evidence base for diagnostic tests.

However, accuracy is but one aspect of assessing diagnostic tests. Other evidence is required for determining the clinical utility of a testreproducibility, effectiveness, and cost effectiveness. A test is not robust if not reproducible, yet evidence is often lacking. The effect of test accuracy on patients' outcomes is crucial, but the size of effect and the optimum balance between sensitivity and specificity depends on the context in which the test is used.

Decisions about patient management may be based on one test alone, as in a screening test, or be part of a battery of tests. For a screening test, in populations with a very low prevalence of disease false negative results are highly undesirable. With additional information about a patient, reducing false positive results may become more important.

Although it may not be possible to provide comprehensive information for established diagnostic tests, thorough appraisal of new tests should include their relation to patient outcomes.

Improved reporting of accuracy studies is an excellent first step since currently new tests can be introduced with little evidence, unlike the rigorous evaluation required for a new drug. However, we should be moving to a staged evaluation for new tests, especially for population screening, that adds evidence of effect on clinical, cost, and personal outcomes to measurement of the basic parameters of sensitivity, specificity, and reproducibility. This demands additional evaluative methods including clinical trials and mathematical modelling beyond the studies discussed by the STARD group.

David Jenkins, professor of pathology. 
david.jenkins{at}nottingham.ac.uk

Elaine Bentley, academic epidemiologist. 
School of Clinical Laboratory Sciences, University of Nottingham, Queen's Medical Centre, Nottingham NG7 2UH