title: How Much Overtesting Is Needed to Safely Exclude a Diagnosis? A Different Perspective on Triage Testing Using Bayes' Theorem.
abstract: Ruling out disease often requires expensive or potentially harmful confirmation testing. For such testing, a less invasive triage test is often used. Intuitively, few negative confirmatory tests suggest success of this approach. However, if negative confirmation tests become too rare, too many disease cases could have been missed. It is therefore important to know how many negative tests are needed to safely exclude a diagnosis. We quantified this relationship using Bayes' theorem, and applied this to the example of pulmonary embolism (PE), for which triage is done with a Clinical Decision Rule (CDR) and D-dimer testing, and CT-angiography (CTA) is the confirmation test. For a maximum proportion of missed PEs of 1% in triage-negative patients, we calculate a 67% 'mandatory minimum' proportion of negative CTA scans. To achieve this, the proportion of patients with PE undergoing triage testing should be appropriately low, in this case no higher than 24%. Pre-test probability, triage test characteristics, the proportion of negative confirmation tests, and the number of missed diagnoses are mathematically entangled. The proportion of negative confirmation tests--not too high, but definitely not too low either--could be a quality benchmark for diagnostic processes.
authors.affiliation: Department of Internal Medicine, VU university medical centre, 1081HV Amsterdam, the Netherlands.
authors.forename: Jonne J
authors.initials: JJ
authors.lastname: Sikkens
authors.affiliation: Department of Internal Medicine, VU university medical centre, 1081HV Amsterdam, the Netherlands.
authors.forename: Djoeke G
authors.initials: DG
authors.lastname: Beekman
authors.affiliation: Department of Internal Medicine, VU university medical centre, 1081HV Amsterdam, the Netherlands.
authors.forename: Abel
authors.initials: A
authors.lastname: Thijs
authors.affiliation: Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre Amsterdam, 1105 AZ Amsterdam, the Netherlands.
authors.forename: Patrick M
authors.initials: PM
authors.lastname: Bossuyt
authors.affiliation: Department of Internal Medicine, VU university medical centre, 1081HV Amsterdam, the Netherlands.
authors.forename: Yvo M
authors.initials: YM
authors.lastname: Smulders
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001499:Bayes Theorem; D003661:Decision Support Techniques; D003937:Diagnosis, Differential; D005338:Fibrin Fibrinogen Degradation Products / Q000032:analysis; D006801:Humans; D000069342:Medical Overuse; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D011336:Probability; D011655:Pulmonary Embolism / Q000628:therapy*; D012306:Risk; D012680:Sensitivity and Specificity; D036542:Tomography, Spiral Computed / Q000379:methods*
chemical_list: D005338:Fibrin Fibrinogen Degradation Products; C036309:fibrin fragment D