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      Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice

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          Abstract

          Within the context of screening tests, it is important to avoid misconceptions about sensitivity, specificity, and predictive values. In this article, therefore, foundations are first established concerning these metrics along with the first of several aspects of pliability that should be recognized in relation to those metrics. Clarification is then provided about the definitions of sensitivity, specificity, and predictive values and why researchers and clinicians can misunderstand and misrepresent them. Arguments are made that sensitivity and specificity should usually be applied only in the context of describing a screening test’s attributes relative to a reference standard; that predictive values are more appropriate and informative in actual screening contexts, but that sensitivity and specificity can be used for screening decisions about individual people if they are extremely high; that predictive values need not always be high and might be used to advantage by adjusting the sensitivity and specificity of screening tests; that, in screening contexts, researchers should provide information about all four metrics and how they were derived; and that, where necessary, consumers of health research should have the skills to interpret those metrics effectively for maximum benefit to clients and the healthcare system.

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          Most cited references22

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          QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

          In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
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            Understanding and using sensitivity, specificity and predictive values

            In this article, we have discussed the basic knowledge to calculate sensitivity, specificity, positive predictive value and negative predictive value. We have discussed the advantage and limitations of these measures and have provided how we should use these measures in our day-to-day clinical practice. We also have illustrated how to calculate sensitivity and specificity while combining two tests and how to use these results for our patients in day-to-day practice.
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              Sensitivity and specificity of the ankle--brachial index to diagnose peripheral artery disease: a structured review.

              The ankle-brachial index (ABI) is a simple, inexpensive diagnostic test for peripheral artery disease (PAD). However, it has shown variable accuracy for identification of significant stenosis. The authors performed a structured review of the sensitivity and specificity of ABI ≤ 0.90 for the diagnosis of PAD. MEDLINE, EMBASE, Cochrane databases, Science Citation Index database, and Biological Abstracts database were searched for studies of the sensitivity and specificity of using ABI ≤ 0.90 for the diagnosis of PAD. Eight studies comprising 2043 patients (or limbs) met the inclusion criteria. The result indicated that, although strict inclusion criteria on studies were formulated, different reference standards were found in these studies, and methods of ABI determination and characteristics of populations varied greatly. A high level of specificity (83.3-99.0%) and accuracy (72.1-89.2%) was reported for an ABI ≤ 0.90 in detecting ≥ 50% stenosis, but there were different levels of sensitivity (15-79%). Sensitivity was low, especially in elderly individuals and patients with diabetes. In conclusion, the test of ABI ≤ 0.90 can be a simple and useful tool to identify PAD with serious stenosis, and may be substituted for other non-invasive tests in clinical practice.
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                Author and article information

                Contributors
                URI : http://frontiersin.org/people/u/453128
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                20 November 2017
                2017
                : 5
                : 307
                Affiliations
                [1] 1Independent academic researcher and author , Albury, NSW, Australia
                Author notes

                Edited by: Aaron A. Alford, National Network of Public Health Institutes, United States

                Reviewed by: Alessandra Nicoletti, Università degli Studi di Catania, Italy; Dafna Merom, Western Sydney University, Australia; James Harris Derzon, RTI International, United States

                *Correspondence: Robert Trevethan, robertrevethan@ 123456gmail.com

                Specialty section: This article was submitted to Epidemiology, a section of the journal Frontiers in Public Health

                Article
                10.3389/fpubh.2017.00307
                5701930
                29209603
                42789cf7-b766-43a1-b345-ba9408707fc0
                Copyright © 2017 Trevethan.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 September 2017
                : 03 November 2017
                Page count
                Figures: 1, Tables: 1, Equations: 1, References: 21, Pages: 7, Words: 5972
                Categories
                Public Health
                Perspective

                screening tests,sensitivity,specificity,positive predictive values,negative predictive values,clinical decision making

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