Lukas J A Stalpers1, Patty J Nelemans2, Sandra M E Geurts3, Erik Jansen4, Peter de Boer4, André L M Verbeek3. 1. Department of Radiotherapy, Academic Medical Center (AMC), University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands. Electronic address: l.stalpers@amc.nl. 2. Department of Epidemiology, University of Maastricht, Peter Debyeplein 1, Maastricht 6229 HA, The Netherlands. 3. Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein 21, Nijmegen 6525 EZ, The Netherlands. 4. Department of Radiotherapy, Academic Medical Center (AMC), University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands.
Abstract
OBJECTIVES: Test performance is conventionally expressed by gain in diagnostic certainty. We propose net diagnostic gain and indication area as more appropriate measures of test performance; then, the loss in certainty due to misclassification and the information of "no test" would be performed are taken into account. STUDY DESIGN AND SETTING: A decision analytical model was developed in which two alternative strategies were compared: testing and no testing. Correct diagnostic test results received a positive value; undesired test results received a negative value. Within the "no test" scenario, it was assumed that physicians are more prone to treat as the probability of disease is higher. RESULTS: Discounting gain and loss in diagnostic certainty results in a concave function of the prior. The indication area is the range of priors with a net diagnostic gain; testing is deleterious beyond this range. The net diagnostic gain reaches a maximum at a specific prior. A freely available Web site-based calculator was developed for easy calculation of the indication area and the maximum diagnostic gain for each combination of sensitivity and specificity. CONCLUSION: Medical testing is not indicated when the prior disease probabilities are low (as to screening for a condition) or high (for diagnostic confirmation). Published by Elsevier Inc.
OBJECTIVES: Test performance is conventionally expressed by gain in diagnostic certainty. We propose net diagnostic gain and indication area as more appropriate measures of test performance; then, the loss in certainty due to misclassification and the information of "no test" would be performed are taken into account. STUDY DESIGN AND SETTING: A decision analytical model was developed in which two alternative strategies were compared: testing and no testing. Correct diagnostic test results received a positive value; undesired test results received a negative value. Within the "no test" scenario, it was assumed that physicians are more prone to treat as the probability of disease is higher. RESULTS: Discounting gain and loss in diagnostic certainty results in a concave function of the prior. The indication area is the range of priors with a net diagnostic gain; testing is deleterious beyond this range. The net diagnostic gain reaches a maximum at a specific prior. A freely available Web site-based calculator was developed for easy calculation of the indication area and the maximum diagnostic gain for each combination of sensitivity and specificity. CONCLUSION: Medical testing is not indicated when the prior disease probabilities are low (as to screening for a condition) or high (for diagnostic confirmation). Published by Elsevier Inc.
Authors: José V Arcos-Machancoses; Cristina Molera Busoms; Ecaterina Julio Tatis; María V Bovo; Javier Martín de Carpi Journal: J Clin Exp Hepatol Date: 2018-11-08
Authors: José Vicente Arcos-Machancoses; Cristina Molera Busoms; Ecaterina Julio Tatis; María Victoria Bovo; Jesús Quintero Bernabeu; Javier Juampérez Goñi; Vanessa Crujeiras Martínez; Javier Martin de Carpi Journal: Pediatr Gastroenterol Hepatol Nutr Date: 2018-04-13