Kristin Mühlenbruch1, Tonia Ludwig2, Charlotte Jeppesen1, Hans-Georg Joost3, Wolfgang Rathmann4, Christine Meisinger2, Annette Peters2, Heiner Boeing5, Barbara Thorand2, Matthias B Schulze6. 1. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research, Germany. 2. Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany; German Center for Diabetes Research, Germany. 3. Department of Pharmacology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research, Germany. 4. Institute of Biometry and Epidemiology, German Diabetes Center, Düsseldorf, Germany; German Center for Diabetes Research, Germany. 5. Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany. 6. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany; German Center for Diabetes Research, Germany. Electronic address: mschulze@dife.de.
Abstract
AIMS: Several published diabetes prediction models include information about family history of diabetes. The aim of this study was to extend the previously developed German Diabetes Risk Score (GDRS) with family history of diabetes and to validate the updated GDRS in the Multinational MONItoring of trends and determinants in CArdiovascular Diseases (MONICA)/German Cooperative Health Research in the Region of Augsburg (KORA) study. METHODS: We used data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study for extending the GDRS, including 21,846 participants. Within 5 years of follow-up 492 participants developed diabetes. The definition of family history included information about the father, the mother and/or sibling/s. Model extension was evaluated by discrimination and reclassification. We updated the calculation of the score and absolute risks. External validation was performed in the MONICA/KORA study comprising 11,940 participants with 315 incident cases after 5 years of follow-up. RESULTS: The basic ROC-AUC of 0.856 (95%-CI: 0.842-0.870) was improved by 0.007 (0.003-0.011) when parent and sibling history was included in the GDRS. The net reclassification improvement was 0.110 (0.072-0.149), respectively. For the updated score we demonstrated good calibration across all tenths of risk. In MONICA/KORA, the ROC-AUC was 0.837 (0.819-0.855); regarding calibration we saw slight overestimation of absolute risks. CONCLUSIONS: Inclusion of the number of diabetes-affected parents and sibling history improved the prediction of type 2 diabetes. Therefore, we updated the GDRS algorithm accordingly. Validation in another German cohort study showed good discrimination and acceptable calibration for the vast majority of individuals.
AIMS: Several published diabetes prediction models include information about family history of diabetes. The aim of this study was to extend the previously developed German Diabetes Risk Score (GDRS) with family history of diabetes and to validate the updated GDRS in the Multinational MONItoring of trends and determinants in CArdiovascular Diseases (MONICA)/German Cooperative Health Research in the Region of Augsburg (KORA) study. METHODS: We used data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study for extending the GDRS, including 21,846 participants. Within 5 years of follow-up 492 participants developed diabetes. The definition of family history included information about the father, the mother and/or sibling/s. Model extension was evaluated by discrimination and reclassification. We updated the calculation of the score and absolute risks. External validation was performed in the MONICA/KORA study comprising 11,940 participants with 315 incident cases after 5 years of follow-up. RESULTS: The basic ROC-AUC of 0.856 (95%-CI: 0.842-0.870) was improved by 0.007 (0.003-0.011) when parent and sibling history was included in the GDRS. The net reclassification improvement was 0.110 (0.072-0.149), respectively. For the updated score we demonstrated good calibration across all tenths of risk. In MONICA/KORA, the ROC-AUC was 0.837 (0.819-0.855); regarding calibration we saw slight overestimation of absolute risks. CONCLUSIONS: Inclusion of the number of diabetes-affected parents and sibling history improved the prediction of type 2 diabetes. Therefore, we updated the GDRS algorithm accordingly. Validation in another German cohort study showed good discrimination and acceptable calibration for the vast majority of individuals.
Authors: Roger S McIntyre; Martin Alda; Ross J Baldessarini; Michael Bauer; Michael Berk; Christoph U Correll; Andrea Fagiolini; Kostas Fountoulakis; Mark A Frye; Heinz Grunze; Lars V Kessing; David J Miklowitz; Gordon Parker; Robert M Post; Alan C Swann; Trisha Suppes; Eduard Vieta; Allan Young; Mario Maj Journal: World Psychiatry Date: 2022-10 Impact factor: 79.683
Authors: Felix Teufel; Pascal Geldsetzer; Jennifer Manne-Goehler; Omar Karlsson; Viola Koncz; Andreas Deckert; Michaela Theilmann; Maja-Emilia Marcus; Cara Ebert; Jacqueline A Seiglie; Kokou Agoudavi; Glennis Andall-Brereton; Gladwell Gathecha; Mongal S Gurung; David Guwatudde; Corine Houehanou; Nahla Hwalla; Gibson B Kagaruki; Khem B Karki; Demetre Labadarios; Joao S Martins; Mohamed Msaidie; Bolormaa Norov; Abla M Sibai; Lela Sturua; Lindiwe Tsabedze; Chea S Wesseh; Justine Davies; Rifat Atun; Sebastian Vollmer; S V Subramanian; Till Bärnighausen; Lindsay M Jaacks; Jan-Walter De Neve Journal: Diabetes Care Date: 2020-08-06 Impact factor: 19.112
Authors: Esther Jacobs; Miguel Tamayo; Joachim Rosenbauer; Matthias B Schulze; Oliver Kuss; Wolfgang Rathmann Journal: BMC Endocr Disord Date: 2018-10-16 Impact factor: 2.763
Authors: Rebecca Paprott; Kristin Mühlenbruch; Gert B M Mensink; Silke Thiele; Matthias B Schulze; Christa Scheidt-Nave; Christin Heidemann Journal: BMJ Open Diabetes Res Care Date: 2016-11-21