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      Comparison of four sarcopenia screening questionnaires in community-dwelling older adults from Poland using six sets of international diagnostic criteria of sarcopenia

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          Abstract

          Introduction

          There are four screening sarcopenia questionnaires (SARC-F, SARC-CalF, MSRA-5, MSRA-7). To unambiguously determine which of them is the most effective tool in community-dwelling older adults, we performed a diagnostic accuracy study. The aim of the analysis was to assess the diagnostic values of SARC-F, SARC-CalF, MSRA-5, MSRA-7 and compare their psychometric properties against six criterion standards (EWGSOP1, EWGSOP2, FNIH, AWGS, IWGS, SCWD criteria).

          Materials and methods

          We included 100 community-dwelling volunteers aged ≥ 65yrs. The sensitivity/specificity analyses were performed. Receiver operating characteristic (ROC) curves and area under the ROC curves (AUC) were calculated to compare the overall diagnostic accuracy of the four questionnaires. Ideal screening tools should have reasonably high sensitivity and specificity, and an AUC value above 0.7.

          Results

          With respect to the six criterion standards used, the sensitivity of SARC-F, SARC-CalF, MSRA-5, and MSRA-7 ranged 35.0–90.0%, 20.0–75.0%, 64.7–90.0%, 76.5–91.7%, respectively, whereas the specificity ranged 86.9–91.1%, 80.0–90.0%, 45.8–48.8%, 28.9–31.0% respectively. The AUCs of SARC-F, SARC-CalF, MSRA-5, and MSRA-7 ranged from 0.655–0.882, 0.711–0.874, 0.618–0.782 and 0.588–0.711 respectively. Only SARC-CalF had AUC >0.7 and <0.9 against the six criterion standards but obesity was a confounding factor, which may affect the diagnostic power of SARC-CalF. MSRA-7 had the smallest AUC of all the questionnaires and MSRA-5 had slightly larger AUC than MSRA-7.

          Conclusion

          Based on our analysis, the standard sarcopenia screening questionnaires deliver contradictory results in many practically occurring cases. It appears that SARC-CalF is an optimal choice for screening sarcopenia in community-dwelling older adults.

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          Most cited references25

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            Validating the SARC-F: a suitable community screening tool for sarcopenia?

            Using data from the Hong Kong Mr and Ms Os study, we validated the SARC-F against 3 consensus definitions of sarcopenia from Europe, Asia, and an international group, and compared the ability of all 4 measures to predict 4-year physical limitation, walking speed, and repeated chair stands.
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              Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.

              Diagnostic or predictive accuracy concerns are common in all phases of a disease management (DM) programme, and ultimately play an influential role in the assessment of programme effectiveness. Areas, such as the identification of diseased patients, predictive modelling of future health status and costs and risk stratification, are just a few of the domains in which assessment of accuracy is beneficial, if not critical. The most commonly used analytical model for this purpose is the standard 2 x 2 table method in which sensitivity and specificity are calculated. However, there are several limitations to this approach, including the reliance on a single defined criterion or cut-off for determining a true-positive result, use of non-standardized measurement instruments and sensitivity to outcome prevalence. This paper introduces the receiver operator characteristic (ROC) analysis as a more appropriate and useful technique for assessing diagnostic and predictive accuracy in DM. Its advantages include; testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, easily examined visual and statistical comparisons across tests or scores, and independence from outcome prevalence. Therefore the implementation of ROC as an evaluation tool should be strongly considered in the various phases of a DM programme.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draft
                Role: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 April 2020
                2020
                : 15
                : 4
                : e0231847
                Affiliations
                [1 ] Department of Palliative Medicine, Poznan University of Medical Sciences, Poznan, Poland
                [2 ] Department of Geriatric Medicine and Gerontology, Poznan University of Medical Sciences, Poznan, Poland
                Hong Kong Polytechnic University, HONG KONG
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6770-7321
                Article
                PONE-D-20-01081
                10.1371/journal.pone.0231847
                7170245
                32310992
                6b44aaf1-d041-4dd0-90e2-448833390b59
                © 2020 Krzymińska-Siemaszko et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 January 2020
                : 1 April 2020
                Page count
                Figures: 1, Tables: 5, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100010438, Uniwersytet Medyczny im. Karola Marcinkowskiego w Poznaniu;
                Award ID: grant number: 502-14-11141570-10595
                Award Recipient :
                This study was funded by Poznan University of Medical Sciences (grant number 502-14-11141570-10595). Funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Sarcopenia
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Sarcopenia
                People and Places
                Population Groupings
                Age Groups
                Elderly
                Research and Analysis Methods
                Research Assessment
                Altmetrics
                Article-Level Metrics
                Medicine and Health Sciences
                Health Care
                Quality of Life
                Activities of Daily Living
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Biology and Life Sciences
                Physiology
                Biological Locomotion
                Walking
                Medicine and Health Sciences
                Physiology
                Biological Locomotion
                Walking
                Biology and Life Sciences
                Nutrition
                Malnutrition
                Medicine and Health Sciences
                Nutrition
                Malnutrition
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Custom metadata
                All relevant data are within the manuscript.

                Uncategorized
                Uncategorized

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