Literature DB >> 21153531

The Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) update of the Finnish diabetes risk score for prediction of incident type 2 diabetes.

M Alssema1, D Vistisen, M W Heymans, G Nijpels, C Glümer, P Z Zimmet, J E Shaw, M Eliasson, C D A Stehouwer, A G Tabák, S Colagiuri, K Borch-Johnsen, J M Dekker.   

Abstract

AIMS/HYPOTHESIS: The Finnish diabetes risk questionnaire is a widely used, simple tool for identification of those at risk for drug-treated type 2 diabetes. We updated the risk questionnaire by using clinically diagnosed and screen-detected type 2 diabetes instead of drug-treated diabetes as an endpoint and by considering additional predictors.
METHODS: Data from 18,301 participants in studies of the Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) project with baseline and follow-up information on oral glucose tolerance status were included. Incidence of type 2 diabetes within 5 years was used as the outcome variable. Improvement in discrimination and classification of the logistic regression model was assessed by the area under the receiver-operating characteristic (ROC) curve and by the net reclassification improvement. Internal validation was by bootstrapping techniques.
RESULTS: Of the 18,301 participants, 844 developed type 2 diabetes in a period of 5 years (4.6%). The Finnish risk score had an area under the ROC curve of 0.742 (95% CI 0.726-0.758). Re-estimation of the regression coefficients improved the area under the ROC curve to 0.766 (95% CI 0.750-0.783). Additional items such as male sex, smoking and family history of diabetes (parent, sibling or both) improved the area under the ROC curve and net reclassification. Bootstrapping showed good internal validity. CONCLUSIONS/
INTERPRETATION: The predictive value of the original Finnish risk questionnaire could be improved by adding information on sex, smoking and family history of diabetes. The DETECT-2 update of the Finnish diabetes risk questionnaire is an adequate and robust predictor for future screen-detected and clinically diagnosed type 2 diabetes in Europid populations.

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Year:  2010        PMID: 21153531     DOI: 10.1007/s00125-010-1990-7

Source DB:  PubMed          Journal:  Diabetologia        ISSN: 0012-186X            Impact factor:   10.122


  37 in total

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2.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

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3.  A simple risk score using routine data for predicting cardiovascular disease in primary care.

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4.  Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria.

Authors: 
Journal:  Arch Intern Med       Date:  2001-02-12

5.  Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study.

Authors:  Jaana Lindström; Pirjo Ilanne-Parikka; Markku Peltonen; Sirkka Aunola; Johan G Eriksson; Katri Hemiö; Helena Hämäläinen; Pirjo Härkönen; Sirkka Keinänen-Kiukaanniemi; Mauri Laakso; Anne Louheranta; Marjo Mannelin; Merja Paturi; Jouko Sundvall; Timo T Valle; Matti Uusitupa; Jaakko Tuomilehto
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6.  The diabetes risk score: a practical tool to predict type 2 diabetes risk.

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7.  A prediction model for type 2 diabetes risk among Chinese people.

Authors:  K Chien; T Cai; H Hsu; T Su; W Chang; M Chen; Y Lee; F B Hu
Journal:  Diabetologia       Date:  2008-12-05       Impact factor: 10.122

8.  Prevalences of diabetes and impaired glucose regulation in a Danish population: the Inter99 study.

Authors:  Charlotte Glümer; Torben Jørgensen; Knut Borch-Johnsen
Journal:  Diabetes Care       Date:  2003-08       Impact factor: 19.112

9.  Family history and prevalence of diabetes in the U.S. population: the 6-year results from the National Health and Nutrition Examination Survey (1999-2004).

Authors:  Rodolfo Valdez; Paula W Yoon; Tiebin Liu; Muin J Khoury
Journal:  Diabetes Care       Date:  2007-07-18       Impact factor: 19.112

10.  Stepwise screening for diabetes identifies people with high but modifiable coronary heart disease risk. The ADDITION study.

Authors:  A Sandbaek; S J Griffin; G Rutten; M Davies; R Stolk; K Khunti; K Borch-Johnsen; N J Wareham; T Lauritzen
Journal:  Diabetologia       Date:  2008-04-29       Impact factor: 10.122

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  27 in total

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Authors:  Christian Herder; Bernd Kowall; Adam G Tabak; Wolfgang Rathmann
Journal:  Diabetologia       Date:  2014-01       Impact factor: 10.122

2.  Risk scores for predicting type 2 diabetes: using the optimal tool.

Authors:  M Alssema; D Vistisen; M W Heymans; G Nijpels; C Glümer; P Z Zimmet; J E Shaw; M Eliasson; C D A Stehouwer; A G Tabák; S Colagiuri; K Borch-Johnsen; J M Dekker
Journal:  Diabetologia       Date:  2011-06-10       Impact factor: 10.122

3.  Risk scores for predicting type 2 diabetes: comparing axes and spades.

Authors:  N J Wareham; S J Griffin
Journal:  Diabetologia       Date:  2011-03-05       Impact factor: 10.122

Review 4.  Metabolic syndrome and lifestyle modification.

Authors:  Mitsuyoshi Takahara; Iichiro Shimomura
Journal:  Rev Endocr Metab Disord       Date:  2014-12       Impact factor: 6.514

5.  Evaluation of the Finnish Diabetes Risk Score (FINDRISC) as a screening tool for the metabolic syndrome.

Authors:  Mohsen Janghorbani; Hoseinali Adineh; Masoud Amini
Journal:  Rev Diabet Stud       Date:  2014-02-10

6.  Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes.

Authors:  Antonio Martinez-Millana; Jose-Luis Bayo-Monton; María Argente-Pla; Carlos Fernandez-Llatas; Juan Francisco Merino-Torres; Vicente Traver-Salcedo
Journal:  Sensors (Basel)       Date:  2017-12-29       Impact factor: 3.576

7.  Factors affecting the decline in incidence of diabetes in the Diabetes Prevention Program Outcomes Study (DPPOS).

Authors:  Richard F Hamman; Edward Horton; Elizabeth Barrett-Connor; George A Bray; Costas A Christophi; Jill Crandall; Jose C Florez; Sarah Fowler; Ronald Goldberg; Steven E Kahn; William C Knowler; John M Lachin; Mary Beth Murphy; Elizabeth Venditti
Journal:  Diabetes       Date:  2014-10-02       Impact factor: 9.461

8.  Development of a new scoring system for predicting the 5 year incidence of type 2 diabetes in Japan: the Toranomon Hospital Health Management Center Study 6 (TOPICS 6).

Authors:  Y Heianza; Y Arase; S D Hsieh; K Saito; H Tsuji; S Kodama; S Tanaka; Y Ohashi; H Shimano; N Yamada; S Hara; H Sone
Journal:  Diabetologia       Date:  2012-09-07       Impact factor: 10.122

9.  Family history of diabetes is associated with higher risk for prediabetes: a multicentre analysis from the German Center for Diabetes Research.

Authors:  Robert Wagner; Barbara Thorand; Martin A Osterhoff; Gabriele Müller; Anja Böhm; Christa Meisinger; Bernd Kowall; Wolfgang Rathmann; Florian Kronenberg; Harald Staiger; Norbert Stefan; Michael Roden; Peter E Schwarz; Andreas F Pfeiffer; Hans-Ulrich Häring; Andreas Fritsche
Journal:  Diabetologia       Date:  2013-08-24       Impact factor: 10.122

10.  Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study.

Authors:  Ali Abbasi; Linda M Peelen; Eva Corpeleijn; Yvonne T van der Schouw; Ronald P Stolk; Annemieke M W Spijkerman; Daphne L van der A; Karel G M Moons; Gerjan Navis; Stephan J L Bakker; Joline W J Beulens
Journal:  BMJ       Date:  2012-09-18
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