Update of the German Diabetes Risk Score and external validation in the German MONICA/KORA study
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.
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Potential confounders were a priori selected based on the literature on red meat intake and diabetes risk and prior investigations in EPIC-Potsdam.
“Potential confounders to be included as covariates were a priori selected based on the literature on the association between red meat intake and diabetes risk (2, 3) and prior investigations in EPIC-Potsdam regarding risk factors of type 2 diabetes (5), dietary patterns (27), and determinants of metabolic profiles (28,29).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [5]
In EPIC-Potsdam, a 150-g/d portion of red meat had a predictive value for type 2 diabetes risk similar to smoking 20 cigarettes/d, having a 7.6-cm higher waist circumference, or having one parent with diabetes.
“We have previously reported from the European Prospective Investigation into Cancer and Nutrition (EPIC) 5 -Potsdam study that with regard to type 2 diabetes risk assessment, a 150-g/d portion of red meat had a predictive value similar to smoking .20 cigarettes/d, having a 7.6-cm higher waist circumference, or having one parent with diabetes (5).”
From Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes (2015) · cites this paper as [5]
Cites
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649 · see citing works
Prediction of coronary heart disease using risk factor categories
Wilson, P. W. F., D’Agostino, R. B., Levy, D., Belanger, A. M., Silbershatz, H., & Kannel, W. B. (1998) · Circulation · doi:10.1161/01.cir.97.18.1837 · Cited by 9,581 · see citing works
Pencina, M. J., D' Agostino, R. B., D' Agostino, R. B., & Vasan, R. S. (2008) · Statistics in Medicine · doi:10.1002/sim.2929 · Cited by 6,493 · see citing works
Greenland, P. (2007) · Statistics in Medicine · doi:10.1002/sim.2976 · Cited by 1,300 · see citing works
Clinical risk factors, DNA variants, and the development of type 2 diabetes
Lyssenko, V., Jonsson, A., Almgren, P., Pulizzi, N., Isomaa, B., Tuomi, T., Berglund, G., Altshuler, D., Nilsson, P., & Groop, L. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0801869 · Cited by 938 · see citing works
Risk models and scores for type 2 diabetes: systematic review
Noble, D., Mathur, R., Dent, T., Meads, C., & Greenhalgh, T. (2011) · BMJ · doi:10.1136/bmj.d7163 · Cited by 551 · see citing works
D, M. P. S. M., Williams, K., & Haffner, S. M. (2002) · Annals of Internal Medicine · doi:10.7326/0003-4819-136-8-200204160-00006 · Cited by 506 · see citing works
Identifying Individuals at High Risk for Diabetes
Schmidt, M. I., Duncan, B. B., Bang, H., Pankow, J. S., Ballantyne, C. M., Golden, S. H., Folsom, A. R., Chambless, L. E., & for the Atherosclerosis Risk in Communities Investigators (2005) · Diabetes Care · doi:10.2337/diacare.28.8.2013 · Cited by 455 · see citing works
Chen, L., Magliano, D., Balkau, B., Colagiuri, S., Zimmet, P., Tonkin, A., Mitchell, P., Phillips, P., & Shaw, J. (2010) · Medical Journal of Australia · doi:10.5694/j.1326-5377.2010.tb03478.x · Cited by 387 · see citing works
Schulze, M. B., Hoffmann, K., Boeing, H., Linseisen, J., Rohrmann, S., Möhlig, M., Pfeiffer, A. F. H., Spranger, J., Thamer, C., Häring, H., et al. (2007) · Diabetes Care · doi:10.2337/dc06-2089 · Cited by 374 · see citing works
Hippisley‐Cox, J., Coupland, C. A. C., Robson, J. P., Sheikh, A., & Brindle, P. M. (2009) · BMJ · doi:10.1136/bmj.b880 · Cited by 370 · see citing works
Misuse of DeLong test to compare AUCs for nested models
Demler, O., Pencina, M. J., & D’Agostino, R. B. (2012) · Statistics in Medicine · doi:10.1002/sim.5328 · Cited by 313 · see citing works
Recruitment Procedures of EPIC-Germany
Boeing, H., Korfmann, A., & Bergmann, M. M. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012787 · Cited by 303 · see citing works
Risk assessment tools for identifying individuals at risk of developing type 2 diabetes
Buijsse, B., Simmons, R. K., Griffin, S. J., & Schulze, M. B. (2011) · Epidemiologic Reviews · doi:10.1093/epirev/mxq019 · Cited by 297 · see citing works
Chen, L., Magliano, D. J., Balkau, B., Colagiuri, S., Zimmet, P., Tonkin, A. M., Mitchell, P., Phillips, P. J. J., & Shaw, J. E. (2010) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.2010.tb03507.x · Cited by 288 · see citing works
A Risk Score for Predicting Incident Diabetes in the Thai Population
Aekplakorn, W., Bunnag, P., Woodward, M., Sritara, P., Cheepudomwit, S., Yamwong, S., Yipintsoi, T., & Rajatanavin, R. (2006) · Diabetes Care · doi:10.2337/dc05-2141 · Cited by 275 · see citing works
Fasting proinsulin concentrations predict the development of type 2 diabetes.
Wareham, N. J., Byrne, C. D., Williams, R., Day, N., & Hales, C. N. (1999) · Diabetes Care · doi:10.2337/diacare.22.2.262 · Cited by 172 · see citing works
A prediction model for type 2 diabetes risk among Chinese people
Chien, K., Cai, T., Hsu, H., Su, T., Chang, W., Chen, M., Lee, Y.-C., & Hu, F. B. (2008) · Diabetologia · doi:10.1007/s00125-008-1232-4 · Cited by 157 · see citing works
Follow-Up Procedures in EPIC-Germany – Data Quality Aspects
Bergmann, M. M., Bussas, U., & Boeing, H. (1999) · Annals of Nutrition and Metabolism · doi:10.1159/000012789 · Cited by 141 · see citing works
Bozorgmanesh, M., Hadaegh, F., & Azizi, F. (2010) · Lipids in Health and Disease · doi:10.1186/1476-511x-9-45 · Cited by 116 · see citing works
Sato, K. K., Hayashi, T., Harita, N., Yoneda, T., Nakamura, Y., Endo, G., & Kambe, H. (2009) · Diabetes Care · doi:10.2337/dc08-1631 · Cited by 112 · see citing works
Hadaegh, F., Hatami, M., Tohidi, M., Sarbakhsh, P., Saadat, N., & Azizi, F. (2010) · Lipids in Health and Disease · doi:10.1186/1476-511x-9-85 · Cited by 99 · see citing works
Wagner, R. J., Thorand, B., Osterhoff, M. A., Müller, G., Böhm, A., Meisinger, C., Kowall, B., Rathmann, W., Kronenberg, F., Staiger, H., et al. (2013) · Diabetologia · doi:10.1007/s00125-013-3002-1 · Cited by 88 · see citing works
Detecting Undiagnosed Type 2 Diabetes: Family History as a Risk Factor and Screening Tool
Valdez, R. A. (2009) · Journal of Diabetes Science and Technology · doi:10.1177/193229680900300417 · Cited by 86 · see citing works
Bozorgmanesh, M., Hadaegh, F., Ghaffari, S., Harati, H., & Azizi, F. (2010) · European Journal of Public Health · doi:10.1093/eurpub/ckq074 · Cited by 82 · see citing works
Wannamethee, S. G., Papacosta, O., Whincup, P. H., Carson, C., Thomas, M. C., Lawlor, D. A., Ebrahim, S. B. J., & Sattar, N. A. (2010) · Diabetologia · doi:10.1007/s00125-010-1670-7 · Cited by 76 · see citing works
Alssema, M., Vistisen, D., Heymans, M. W., Nijpels, G., Glümer, C., Zimmet, P., Shaw, J. E., Eliasson, M., Stehouwer, C. D. A., Tabák, Á. G., et al. (2010) · Diabetologia · doi:10.1007/s00125-010-1990-7 · Cited by 73 · see citing works
Sun, F., Tao, Q., & Zhan, S. (2009) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2009.05.005 · Cited by 67 · see citing works
Hariri, S., Yoon, P. W., Moonesinghe, R., Valdez, R. A., & Khoury, M. J. (2006) · Genetics in Medicine · doi:10.1097/01.gim.0000250205.73963.f3 · Cited by 60 · see citing works
Incidence of and risk factors for type-2 diabetes in a general population: The Tromsø Study
Joseph, J., Svartberg, J. B., Njølstad, I., & Schirmer, H. (2010) · Scandinavian Journal of Public Health · doi:10.1177/1403494810380299 · Cited by 57 · see citing works
Ten‐year incidence of diabetes in older Australians: the Blue Mountains Eye Study
Cugati, S., Wang, J. J., Rochtchina, E., & Mitchell, P. L. R. (2007) · The Medical Journal of Australia · doi:10.5694/j.1326-5377.2007.tb00836.x · Cited by 43 · see citing works
Wannamethee, S. G., Papacosta, O., Whincup, P. H., Thomas, M. C., Carson, C., Lawlor, D. A., Ebrahim, S. B. J., & Sattar, N. A. (2010) · Diabetic Medicine · doi:10.1111/j.1464-5491.2010.03171.x · Cited by 41 · see citing works
Stranges, S., Rafalson, L. B., Dmochowski, J., Rejman, K., Tracy, R. P., Trevisan, M., & Donahue, R. P. (2008) · Obesity · doi:10.1038/oby.2008.59 · Cited by 37 · see citing works
Yang, Q., Liu, T., Valdez, R. A., Moonesinghe, R., & Khoury, M. J. (2010) · American Journal of Epidemiology · doi:10.1093/aje/kwq026 · Cited by 37 · see citing works
Schulze, M. B., & Hoffmann, K. (2007) · Diabetes Care · doi:10.2337/dc07-0859 · Cited by 35 · see citing works
Mühlenbruch, K., Heraclides, A., Steyerberg, E. W., Joost, H., Boeing, H., & Schulze, M. B. (2012) · European Journal of Epidemiology · doi:10.1007/s10654-012-9744-0 · Cited by 34 · see citing works
Diabetes Family History: A Metabolic Storm You Should Not Sit Out
Franks, P. (2010) · Diabetes · doi:10.2337/db10-0768 · Cited by 26 · see citing works
Peterson, W. L. (1990) · Gastrointestinal Endoscopy · Cited by 23 · see citing works
Schwarz, P. E. H., Li, J., Wegner, H., Bornstein, S. R., Lindström, J., & Tuomilehto, J. O. (2007) · Diabetes Care · doi:10.2337/dc07-0682 · Cited by 19 · see citing works
Chien, K. (2007) · Diabetes Care · doi:10.2337/dc07-0814 · Cited by 6 · see citing works
Prediction of Incident Diabetes Mellitus in Middle-aged Adults: The Framingham Offspring Study
Wilson, P. W. F. (2007) · Archives of Internal Medicine · doi:10.1001/archinte.167.10.1068 · Cited by 4 · see citing works
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Sorted by citations
McIntyre, R. S., Alda, M., Baldessarini, R. J., Bauer, M., Berk, M., Correll, C. U., Fagiolini, A., Fountoulakis, K., Frye, M. A., Grunze, H., et al. (2022) · World Psychiatry · doi:10.1002/wps.20997 · Cited by 171 · see citing works
Wittenbecher, C., Mühlenbruch, K., Kröger, J., Jacobs, S., Kuxhaus, O., Floegel, A., Fritsche, A., Pischon, T., Prehn, C., Adamski, J., et al. (2015) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.099150 · Cited by 120 · see citing works
Eckel, N., Mühlenbruch, K., Meidtner, K., Boeing, H., Stefan, N., & Schulze, M. B. (2015) · Metabolism · doi:10.1016/j.metabol.2015.03.009 · Cited by 104 · see citing works
Wittenbecher, C., Štambuk, T., Kuxhaus, O., Rudman, N., Vučković, F., Štambuk, J., Schiborn, C., Rahelić, D., Dietrich, S., Gornik, O., et al. (2020) · Diabetes Care · doi:10.2337/dc19-1507 · Cited by 89 · see citing works
Wittenbecher, C., Kuxhaus, O., Boeing, H., Stefan, N., & Schulze, M. B. (2019) · Diabetologia · doi:10.1007/s00125-019-04978-8 · Cited by 62 · see citing works
Wittenbecher, C., Cuadrat, R. R. C., Johnston, L., Eichelmann, F., Jäger, S., Kuxhaus, O., Prada, M., Fabiola Del Greco, M., Hicks, A. A., Hoffman, P., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28496-1 · Cited by 62 · see citing works
Opposing Associations of NT-proBNP With Risks of Diabetes and Diabetes-Related Complications
Birukov, A., Eichelmann, F., Kuxhaus, O., Polemiti, E., Fritsche, A., Wirth, J., Boeing, H., Weikert, C., & Schulze, M. B. (2020) · Diabetes Care · doi:10.2337/dc20-0553 · Cited by 53 · see citing works
Zhang, M., Zhang, H., Wang, C., Ren, Y., Wang, B., Zhang, L., Yang, X., Zhao, Y., Han, C., Pang, C., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152054 · Cited by 53 · see citing works
Paprott, R., Mühlenbruch, K., Mensink, G., Thiele, S., Schulze, M. B., Scheidt‐Nave, C., & Heidemann, C. (2016) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2016-000280 · Cited by 50 · see citing works
Prognostic Modeling and Prevention of Diabetes Using Machine Learning Technique
Perveen, S., Shahbaz, M., Keshavjee, K., & Guergachi, A. (2019) · Scientific Reports · doi:10.1038/s41598-019-49563-6 · Cited by 51 · see citing works
Tajdar, D., Lühmann, D., Fertmann, R., Steinberg, T., van den Bussche, H., Scherer, M., & Schäfer, I. (2021) · BMC Public Health · doi:10.1186/s12889-021-10508-2 · Cited by 48 · see citing works
Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards
Edlitz, Y., & Segal, E. (2022) · eLife · doi:10.7554/elife.71862 · Cited by 39 · see citing works
Perry, B. I., Upthegrove, R., Crawford, O., Jang, S.-H., Lau, E., McGill, I., Carver, E., Jones, P. B., & Khandaker, G. M. (2020) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13212 · Cited by 34 · see citing works
Modifying effect of metabotype on diet–diabetes associations
Riedl, A., Wawro, N., Gieger, C., Meisinger, C., Peters, A., Rathmann, W., Köenig, W., Strauch, K., Quante, A. S., Thorand, B., et al. (2019) · European Journal of Nutrition · doi:10.1007/s00394-019-01988-5 · Cited by 26 · see citing works
Mühlenbruch, K., Joost, H., Boeing, H., & Schulze, M. B. (2014) · Cited by 22 · see citing works
Paprott, R., Scheidt‐Nave, C., & Heidemann, C. (2018) · Journal of Diabetes Research · doi:10.1155/2018/5703652 · Cited by 21 · see citing works
Paprott, R., Mensink, G., Schulze, M. B., Thiele, S., Mühlenbruch, K., Scheidt‐Nave, C., & Heidemann, C. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-013058 · Cited by 17 · see citing works
Mühlenbruch, K., Zhuo, X., Bardenheier, B. H., Shao, H., Laxy, M., Icks, A., Zhang, P., Gregg, E. W., & Schulze, M. B. (2019) · Acta Diabetologica · doi:10.1007/s00592-019-01451-1 · Cited by 15 · see citing works
Differential associations between diet and prediabetes or diabetes in the KORA FF4 study
Breuninger, T. A., Riedl, A., Wawro, N., Rathmann, W., Strauch, K., Quante, A. S., Peters, A., Thorand, B., Meisinger, C., & Linseisen, J. (2018) · Journal of Nutritional Science · doi:10.1017/jns.2018.25 · Cited by 14 · see citing works
Schiborn, C., Kuhn, T. E., Mühlenbruch, K., Kuxhaus, O., Weikert, C., Fritsche, A., Kaaks, R., & Schulze, M. B. (2021) · Scientific Reports · doi:10.1038/s41598-021-99103-4 · Cited by 13 · see citing works
Mühlenbruch, K., Paprott, R., Joost, H., Boeing, H., Heidemann, C., & Schulze, M. B. (2018) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2018-000524 · Cited by 13 · see citing works
Ayensa-Vazquez, J. A., Leiva, A., Tauler, P., López‐González, Á. A., Aguiló, A., Salvá, M. T., & Bennasar‐Veny, M. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9051546 · Cited by 13 · see citing works
Mühlenbruch, K., Kuxhaus, O., di Giuseppe, R., Boeing, H., Weikert, C., & Schulze, M. B. (2017) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2016.12.019 · Cited by 13 · see citing works
Screening strategies for adults with type 2 diabetes mellitus: a systematic review protocol
Mearns, H., Kuodi, P., Shelton, M., Kredo, T., Kagina, B. M. N., & Schmidt, B. (2020) · Systematic Reviews · doi:10.1186/s13643-020-01417-3 · Cited by 12 · see citing works
Schweda, S., Munz, B., Burgstahler, C., Niess, A. M., Roesel, I., Sudeck, G., & Krauß, I. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19159469 · Cited by 10 · see citing works
Mühlenbruch, K., Menzel, J., Dörr, M., Ittermann, T., Meisinger, C., Peters, A., Kluttig, A., Medenwald, D., Bergmann, M. M., Boeing, H., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-72361-4 · Cited by 10 · see citing works
Sung, J., Lee, K., Song, Y., Lee, M. K., & Kim, J. (2014) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.2619 · Cited by 8 · see citing works
Nübel, J., Truthmann, J., Heidemann, C., Du, Y., Paprott, R., Hapke, U., Kruse, J., Scheidt‐Nave, C., & Baumert, J. J. (2021) · Diabetic Medicine · doi:10.1111/dme.14767 · Cited by 8 · see citing works
Recalibration in Validation Studies of Diabetes Risk Prediction Models: A Systematic Review
Masconi, K. L., Matsha, T. E., Erasmus, R. T., & Kengne, A. P. (2015) · International Journal of Statistics in Medical Research · doi:10.6000/1929-6029.2015.04.04.5 · Cited by 7 · see citing works
Jacobs, E. M. G., Tamayo, M., Rosenbauer, J., Schulze, M. B., Kuß, O., & Rathmann, W. (2018) · BMC Endocrine Disorders · doi:10.1186/s12902-018-0299-2 · Cited by 7 · see citing works
Epidemiology in Germany—general development and personal experience
Wichmann, H. ‐. (2017) · European Journal of Epidemiology · doi:10.1007/s10654-017-0290-7 · Cited by 6 · see citing works
Seidel‐Jacobs, E., Kohl, F., Tamayo, M., Rosenbauer, J., Schulze, M. B., Kuß, O., & Rathmann, W. (2022) · Acta Diabetologica · doi:10.1007/s00592-022-01895-y · Cited by 5 · see citing works
Schwedhelm, C., Nimptsch, K., Ahrens, W., Hasselhorn, H. M., Jöckel, K., Katzke, V. A., Kluttig, A., Linkohr, B., Mikolajczyk, R., Nöthlings, U., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02726-7 · Cited by 5 · see citing works
Prediabetes Risk and Diagnostic Methods in the Community: A Review of Current Measuring Models
Topuz, İ., & Gözüm, S. (2021) · Kafkas Journal of Medical Sciences · doi:10.5505/kjms.2021.11298 · Cited by 4 · see citing works
Adapting Diabetes Risk Scores for Jordan
Shdaifat, A. A., Khader, Y. S., Hyari, M., Shatnawi, O., & Banat, M. (2021) · International Journal of General Medicine · doi:10.2147/ijgm.s321063 · Cited by 4 · see citing works
Katoh, S., Peltonen, M., Zeniya, M., Kaji, M., Sakamoto, Y., Utsunomiya, K., & Tuomilehto, J. (2016) · Primary Care Diabetes · doi:10.1016/j.pcd.2015.07.006 · Cited by 4 · see citing works
Mühlenbruch, K., & Schulze, M. B. (2014) · Der Diabetologe · doi:10.1007/s11428-014-1209-5 · Cited by 3 · see citing works
Utility of nonblood-based risk assessment for predicting type 2 diabetes mellitus: A meta-analysis
Yoshizawa, S. M., Kodama, S., Fujihara, K., Ishiguro, H., Ishizawa, M., Matsubayashi, Y., Matsunaga, S., Yamada, T., Shimano, H., Kato, K., et al. (2016) · Preventive Medicine · doi:10.1016/j.ypmed.2016.07.026 · Cited by 3 · see citing works
Teufel, F., Geldsetzer, P., Manne‐Goehler, J., Karlsson, O., Koncz, V., Deckert, A., Theilmann, M., Marcus, M. E., Ebert, C. L., Seiglie, J. A., et al. (2020) · Diabetes Care · doi:10.2337/dc20-0019 · Cited by 3 · see citing works
Färber, F., Alonso-Pérez, E., Heidemann, C., Du, Y., Stadler, G., Gellert, P. R., & O’Sullivan, J. L. (2024) · BMC Public Health · doi:10.1186/s12889-024-17903-5 · Cited by 2 · see citing works
Schiborn, C., Paprott, R., Heidemann, C., Kuhn, T. E., Fritsche, A., Kaaks, R., & Schulze, M. B. (2022) · Deutsches Ärzteblatt international · doi:10.3238/arztebl.m2022.0268 · Cited by 2 · see citing works
Katoh, S., Peltonen, M., Zeniya, M., Sakamoto, Y., Utsunomiya, K., Nishimura, R., & Tuomilehto, J. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9103161 · Cited by 1 · see citing works
Seidel‐Jacobs, E., Kohl, F., Rosenbauer, J., Schulze, M. B., Kuß, O., & Rathmann, W. (2025) · Primary care diabetes · doi:10.1016/j.pcd.2024.12.009 · Cited by 1 · see citing works
Valenta, V., Sailer, C., Mühlenbruch, K., Fritz, J., Roller, G., Kaiserauer, A., Müller, G. H., Häring, H., Schulze, M. B., & Fritsche, A. (2019) · Diabetologie und Stoffwechsel · doi:10.1055/a-0829-0273 · Cited by 1 · see citing works
Schulze, M. B. (2019) · Der Diabetologe · doi:10.1007/s11428-018-0434-8
Diabetesrisikoscores: Einsatz in der Diabetesprävention
Schiborn, C., & Schulze, M. B. (2020) · Der Diabetologe · doi:10.1007/s11428-020-00592-0
Relationship Between HbA1c and Serum Magnesium Levels in Patients with Type 2 Diabetes Mellitus
Arslan, S., Erdoğdu, H. İ., & Atalay, E. (2021) · Kafkas Journal of Medical Sciences · doi:10.5505/kjms.2021.68878
Der Deutsche Diabetes Risiko Test
Schiborn, C., & Schulze, M. B. (2023) · Diabetes aktuell · doi:10.1055/a-2072-5441
Tajdar, D., Lühmann, D., Fertmann, R., Steinberg, T., van den Bussche, H., Scherer, M., & Schäfer, I. (2021) · Figshare · doi:10.6084/m9.figshare.14228086
Mearns, H., Otiku, P. K., Shelton, M., Kredo, T., Kagina, B. M., & Schmidt, B.-M. (2020) · Figshare · doi:10.6084/m9.figshare.12650590
Färber, F., Alonso-Pérez, E., Heidemann, C., Du, Y., Stadler, G., Gellert, P., & O’Sullivan, J. L. (2024) · Figshare · doi:10.6084/m9.figshare.25237259
Färber, F., Alonso-Pérez, E., Heidemann, C., Du, Y., Stadler, G., Gellert, P., & O’Sullivan, J. L. (2024) · Figshare · doi:10.6084/m9.figshare.25237431
- Authors
- Mühlenbruch, K., Ludwig, T., Jeppesen, C., Joost, H.-G., Rathmann, W., Meisinger, C., Peters, A., Boeing, H., Thorand, B., & Schulze, M. B.
- Affiliations
- German Center for Diabetes Research (DE)
- Helmholtz Munich (DE)
- Deutsches Diabetes-Zentrum e.V. (DE)
- German Institute of Human Nutrition (DE)
- Corresponding author
- Schulze, Matthias B.
- ORCID
- Venue
- Diabetes Research and Clinical Practice
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 104
- Issue
- 3
- Pages
- 459-466
- ISSN
- 0168-8227 (ISSN-L)
- OpenAlex
- W2127629134
- Cited by
- 52
- References
- 41
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 2 · 2022: 6 · 2021: 7 · 2020: 10 · 2019: 6 · 2018: 4 · 2017: 3 · 2016: 3 · 2015: 4 · 2014: 3
- FWCI
- 3.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Research and Clinical Practice (publishedVersion)
- PubMed (publishedVersion)
- Site cant be reached (submittedVersion)
- OPUS (Augsburg University) (submittedVersion)
- Funders
- Bundesministerium für Bildung und Forschung
- Deutsche Krebshilfe
- Bundesministerium für Wissenschaft und Forschung
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- type 2 diabetes, diabetes risk prediction, family history of diabetes, parental history, sibling history, external validation, risk reclassification, risk calibration
- MeSH terms
- Adult, Aged, Blood Glucose, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Female, Germany, Glycated Hemoglobin, Humans, Male, Middle Aged, Prospective Studies, Risk Factors, ROC Curve, Prevalence, Risk Assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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