Diagnostic studies as multivariable, prediction research
- Julius Centre for Health Sciences and Primary Care, University Medical Centre, Utrecht, Netherlands
- Correspondence to: Dr D E Grobbee, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, PO Box 80035, 3508 TA Utrecht, Netherlands; www.juliuscenter.nl
Patient outcomes in diagnostic research
Dr Feinstein provides a topical overview of the history and current status of diagnostic research.1 It addresses the various forms of bias that may occur in research aiming to evaluate the accuracy of diagnostic tests. Diagnostic accuracy is defined by the extent to which a test correctly indicates the (“true”) presence or absence of the disease at issue as determined by a particular reference. We largely agree with this overview. However, we would like to discuss in more detail a certain issue raised by Dr Feinstein. Notably, the use of quantitative statistical models in diagnostic research and related to this the practitioners' judgement, and the role of test results in offering prognostic information.
MATHEMATICAL MODELS TO ESTIMATE THE TRUE (ADDED) DIAGNOSTIC ACCURACY OF A TEST
Dr Feinstein argues that diagnostic research is currently unfortunately dictated by mathematical, quantitative models, often ignoring the practitioners' judgement. We, however, believe that these quantitative models are necessary in order to estimate the true, independent (or added) value of a test, just as they are necessary in aetiological studies to estimate the independent association of a particular exposure and the occurrence of a particular outcome.
In medical practice, the diagnostic investigation starts with a patient presenting with a particular symptom or sign indicative for the presence of a particular disease, the so called target disease.2 The diagnostic investigation is a consecutive (hierarchical) process always starting from patient history and physical examination, followed by more invasive, time consuming and costly tests such as …
