A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes

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dc.contributor University of Helsinki, Clinicum en
dc.contributor.author Awad, Susanne F.
dc.contributor.author Dargham, Soha R.
dc.contributor.author Toumi, Amine A.
dc.contributor.author Dumit, Elsy M.
dc.contributor.author El-Nahas, Katie G.
dc.contributor.author Al-Hamaq, Abdulla O.
dc.contributor.author Critchley, Julia A.
dc.contributor.author Tuomilehto, Jaakko
dc.contributor.author Al-Thani, Mohamed H. J.
dc.contributor.author Abu-Raddad, Laith J.
dc.date.accessioned 2021-09-14T13:07:01Z
dc.date.available 2021-09-14T13:07:01Z
dc.date.issued 2021-01-19
dc.identifier.citation Awad , S F , Dargham , S R , Toumi , A A , Dumit , E M , El-Nahas , K G , Al-Hamaq , A O , Critchley , J A , Tuomilehto , J , Al-Thani , M H J & Abu-Raddad , L J 2021 , ' A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes ' , Scientific Reports , vol. 11 , no. 1 , 1811 . https://doi.org/10.1038/s41598-021-81385-3 en
dc.identifier.issn 2045-2322
dc.identifier.other PURE: 168453379
dc.identifier.other PURE UUID: 90c7baba-db51-4759-ab52-10e3e4f088f8
dc.identifier.other WOS: 000676336800057
dc.identifier.uri http://hdl.handle.net/10138/334363
dc.description.abstract We developed a diabetes risk score using a novel analytical approach and tested its diagnostic performance to detect individuals at high risk of diabetes, by applying it to the Qatari population. A representative random sample of 5,000 Qataris selected at different time points was simulated using a diabetes mathematical model. Logistic regression was used to derive the score using age, sex, obesity, smoking, and physical inactivity as predictive variables. Performance diagnostics, validity, and potential yields of a diabetes testing program were evaluated. In 2020, the area under the curve (AUC) was 0.79 and sensitivity and specificity were 79.0% and 66.8%, respectively. Positive and negative predictive values (PPV and NPV) were 36.1% and 93.0%, with 42.0% of Qataris being at high diabetes risk. In 2030, projected AUC was 0.78 and sensitivity and specificity were 77.5% and 65.8%. PPV and NPV were 36.8% and 92.0%, with 43.0% of Qataris being at high diabetes risk. In 2050, AUC was 0.76 and sensitivity and specificity were 74.4% and 64.5%. PPV and NPV were 40.4% and 88.7%, with 45.0% of Qataris being at high diabetes risk. This model-based score demonstrated comparable performance to a data-derived score. The derived self-complete risk score provides an effective tool for initial diabetes screening, and for targeted lifestyle counselling and prevention programs. en
dc.format.extent 10
dc.language.iso eng
dc.relation.ispartof Scientific Reports
dc.rights en
dc.subject FASTING PLASMA-GLUCOSE en
dc.subject TYPE-2 en
dc.subject PREVALENCE en
dc.subject VALIDATION en
dc.subject BURDEN en
dc.subject BIAS en
dc.subject TOOL en
dc.subject 3142 Public health care science, environmental and occupational health en
dc.title A diabetes risk score for Qatar utilizing a novel mathematical modeling approach to identify individuals at high risk for diabetes en
dc.type Article
dc.description.version Peer reviewed
dc.identifier.doi https://doi.org/10.1038/s41598-021-81385-3
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion
dc.contributor.pbl
dc.contributor.pbl

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