Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany

Anette-Gabriele Ziegler; Kerstin Kick; Ezio Bonifacio; Florian Haupt; Markus Hippich; Desiree Dunstheimer; Martin Lang; Otto Laub; Katharina Warncke; Karin Lange; Robin Assfalg; Manja Jolink; Christiane Winkler; Peter Achenbach

doi:10.1001/jama.2019.21565

. 2020 Jan 28;323(4):339–351. doi: 10.1001/jama.2019.21565

Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany

Anette-Gabriele Ziegler ^1,^2,^3,^✉, Kerstin Kick ^1,³, Ezio Bonifacio ^4,^5,⁶, Florian Haupt ^1,³, Markus Hippich ^1,³, Desiree Dunstheimer ⁷, Martin Lang ⁸, Otto Laub ⁹, Katharina Warncke ¹⁰, Karin Lange ¹¹, Robin Assfalg ^1,³, Manja Jolink ^1,³, Christiane Winkler ^1,³, Peter Achenbach ^1,^2,³, for the Fr1da Study Group

¹Institute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany

²Forschergruppe Diabetes, Technical University Munich, at Klinikum rechts der Isar, Munich, Germany

³German Center for Diabetes Research (DZD), Munich, Germany

⁴DFG Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany

⁵Paul Langerhans Institute Dresden, Helmholtz Center Munich, Faculty of Medicine, University Hospital Carl Gustav Carus, TU Dresden, Germany

⁶Institute for Diabetes and Obesity, Helmholtz Diabetes Center at Helmholtz Zentrum München, Munich-Neuherberg, Germany

⁷Klinikum Augsburg, Klinik für Kinder und Jugendliche, Augsburg, Germany

⁸Berufsverband der Kinder- und Jugendärzte e.V., Landesverband Bayern, Augsburg, Germany

⁹PaedNetz Bayern e.V., Rosenheim, Germany

¹⁰Department of Pediatrics, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany

¹¹Department of Medical Psychology, Hannover Medical School, Hannover, Germany

^✉

Corresponding Author: Anette-Gabriele Ziegler, MD, Institute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany (anette-g.ziegler@helmholtz-muenchen.de).

Group Information: The Fr1da Study Group members appear at the end of this article.

Accepted for Publication: December 12, 2019.

Author Contributions: Dr Ziegler had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Ziegler, Bonifacio, Dunstheimer, Lang, Warncke, Lange, Assfalg, Winkler, Achenbach.

Acquisition, analysis, or interpretation of data: Ziegler, Kick, Bonifacio, Haupt, Hippich, Laub, Lange, Jolink, Winkler, Achenbach.

Drafting of the manuscript: Ziegler, Bonifacio, Hippich, Winkler.

Critical revision of the manuscript for important intellectual content: Ziegler, Kick, Bonifacio, Haupt, Dunstheimer, Lang, Laub, Warncke, Lange, Assfalg, Jolink, Winkler, Achenbach.

Statistical analysis: Ziegler, Bonifacio, Hippich, Lange, Jolink, Winkler.

Obtained funding: Ziegler, Bonifacio.

Administrative, technical, or material support: Ziegler, Bonifacio, Haupt, Hippich, Dunstheimer, Lang, Warncke, Lange, Assfalg, Jolink, Winkler, Achenbach.

Supervision: Ziegler, Bonifacio, Achenbach.

Conflict of Interest Disclosures: Dr Bonifacio reported receiving grants from Deutsche Forschungsgemeinschaft during the conduct of the study. No other disclosures were reported.

Funding/Support: The Fr1da study was supported by grants from LifeScience-Stiftung (HMGU 2014.01 and HMGU 2016.01), Juvenile Diabetes Research Foundation International (1-SRA-2014-310-M-R and 3-SRA-2015-72-M-R), the Bavarian State Ministry of Health and Care (Gesund.Leben.Bayern, LP00228), The Leona M and Harry B Helmsley Charitable Trust (G-1911-03274), Deutsche Diabetes-Stiftung (364/11/14), Landesverband Bayern der Betriebskrankenkassen, B. Braun-Stiftung (BBST-D-15-00016), Deutsche Diabetes Hilfe, and the German Federal Ministry of Education and Research to the German Center for Diabetes Research (DZD e.V.). The DiMelli study was funded by the Competence Network Diabetes Mellitus, the Federal Ministry of Education and Research (FKZ01GI0805), and the German Center for Diabetes Research (DZD e.V.).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

The Fr1da Study Group Members: Fr1da Coordinating Center (Institute of Diabetes Research, Helmholtz Zentrum München): Principle investigator: Anette-Gabriele Ziegler, MD; Study coordination: Kerstin Kick, PhD; Robin Assfalg, PhD; Logistics and database development: Florian Haupt, PhD; Andreas Beyerlein, PhD; Database management: Christiane Winkler, PhD; Manja Jolink, MSc; Nana-Adjoa Kwarteng, MSc. Teaching, metabolic staging, care, and follow-up of children with presymptomatic type 1 diabetes: Anna Hofelich, MD; Franziska Reinmüller, MD; Tiziana Welzhofer, MD; Claudia Ramminger; Joanna Stock, Dipl; Anja Heublein, MSc; Charlotte Koch, BSc; Annette Knopff; Administrative and Scientific Management: Ramona Lickert, PhD; Islet autoantibody determination, sample processing, and methodology development: Peter Achenbach, MD; Ezio Bonifacio, PhD; Susanne Wittich, Katharina Gestrich, Marlon Scholz, Claudia Matzke; Genotyping: Markus Hippich, PhD; Data analysis: Anette-Gabriele Ziegler, MD; Christiane Winkler, PhD; Ezio Bonifacio, PhD; Markus Hippich, PhD; Analytical support: Andreas Weiss, PhD; Peter Achenbach, MD; Manja Jolink, MSc; Nana-Adjoa Kwarteng, MSc. Dissemination, information, and public relations: Peter Achenbach, MD, Cordula Falk, Mona Walter.

Fr1da Clinical Centers: Teaching, metabolic staging, care, and follow-up of children with presymptomatic type 1 diabetes: Susanne Bechtold-Dalla Pozza, MD (Dr. von Hauner Children’s Hospital LMU, Munich); Dominik Böcker, MD (Nuremberg Hospital South, Nuremberg); Sonja Braig, MD (Pediatric Clinic of the Bayreuth Hospital, Bayreuth); Desiree Dunstheimer, MD (Augsburg Hospital, Augsburg); Uwe Ermer, MD (St Elisabeth Klinik, Neuburg/Donau); Antonia Gavazzeni, MD (Munich); Eva-Maria Gerstl, MD (Children’s Hospital Dritter Orden, Passau); Ursula Kuhnle-Krahl, MD (Diabetes Center, Gauting); Herbert Müller, MD (Hospital Kempten, Kempten); Nicole Nellen-Hellmuth, MD (Würzburg); Christian Ockert, MD (RoMed Hospital, Rosenheim); Christian Renner, MD (Deggendorf); Marina Sindichakis, MD (Hospital Traunstein, Traunstein); Stefanie Tretter, MD (Hospital Weiden, Weiden); Katharina Warncke, MD (Department of Pediatrics, Klinikum rechts der Isar, TUM, Munich).

Fr1da Primary Care Pediatricians: Obtaining informed consent of parents, and blood samples from Fr1da study participants: Simon Abendroth, MD (Landsberg am Lech); Renate Abt, MD (Wendelstein); Klaus Adams, MD (Lindau); Melanie Adelhardt, MD; Verena Schuster, MD (Hersbruck); Georg Aderbauer, MD (Weiden); Judith Aderbauer, MD; Frank Scharnowski-Fischer, MD (Weiden); Bettina Aichholzer, MD (Bad Endorf); Ina Albrich, MD (Dorfen); Stephan Arenz, MD (Pfaffenhofen); Imam Arslan, MD (München); Olga Arzberger, MD (Sünching); Ärztezentrum Hammelburg (Hammelburg); Bernd Aulinger, MD (Burglengenfeld); Thomas Autenrieth, MD (Saulgrub); Glenn Averbeck, MD (Pfaffenhofen); Andrea Bachmeyr, MD (München); Erika Bahn, MD (Nürnberg); Georg Baier, MD (Schwabach); Ana-Maria Baitanu, MD (Selb); Elmar Barthel, MD (Gemünden); Susanne Barthel, MD; Katrin Kinzel, MD (Oberstdorf); Marina Bascone-Fricke, MD (Aidenbach); Stefanie Batz, MD; Michael Hubmann, MD (Zirndorf); Rolf Bauer, MD (Roth); Yvonna Bauer, MD (Augsburg); Matthias Bauer, MD (Beilngries); Gunhild Bauer-Niedermaier, MD (Zirndorf); Larissa Baumgärtner, MD (Heilsbronn); Michael Bäzner, MD (Sonthofen); Wolfgang Beck, MD; Albert Baier, MD; Petra Mussar, MD (Donauwörth); Axel Becker, MD (Haar); Christian Becker, MD (Bad Aibling); Elisabeth Beer, MD; Hubert Schirmer, MD (Marktredwitz); Arman Behdjati-Lindner, MD; Christian Rein, MD (Haßfurt); Lutz Bellingrath, MD (Bamberg); Reiner Benckendorff, MD (Augsburg); Julia Berg, MD (Neumarkt); Monika Berger, MD (Haimhausen); Annerose Bergner, MD (München); Alexander Bernhart, MD; Christine Wieland, MD (München); Martina Bertholl, MD (Donaustauf); Florian Berz, MD (München); Oliver Beste, MD; Nikolaus Hosemann, MD (Dachau); Reinhard Beuthan, MD (Dingolfing); Katrin Biebach, MD (München); Matthias Bierler, MD; Jens Keppler, MD; Sabine Beer, MD (Amberg); Helene Biermann-Franke, MD; Michael Trinczek, MD (Erlangen); Klaus Binder, MD; Markus Redenbacher, MD; Stefan Zink, MD (Nürnberg); Georg Black, MD (Dietfurt); Elisabeth Blaettner, MD (Augsburg); Maria-Magdalena Blauditschek, MD (Würzburg); Jörg Blume, MD (Schweinfurt); Waltraud Blümel-Eiber, MD; Manfred Rösch, MD (Nürnberg); Andreas Blüml, MD (Trostberg); Jens Böhm, MD/Nilgün Durmus, MD (Wettstetten); Mirko Böhme, MD (Sulzberg); Sabine Böhm-Vogt, MD (Ottobrunn); Elisabeth Boretzki, MD; Thomas Boretzki, MD (Eichstätt); Karola Börzsönyi, MD (Freising); Nadja Bösel, MD (Neumarkt Opf.); Stephan Böse-O'Reilly, MD (München); Diana Boudova, MD (Neunburg vorm Wald); Michael Brack, MD (Urspringen); Malte Bräutigam, MD (Eichstätt); Walter Breiner, MD (Marktoberdorf); Ulrike Brendel, MD (Parsberg); Michael Brijnen von Oldershausen, MD (München); Christian Brückmann, MD (Brannenburg); Wolfgang Brunnhölzl, MD; Matthias Grimberg, MD (München); Halina Eva Buchalik, MD (Lauf an der Pegnitz); Franz Bundscherer, MD (Geretsried); Anna Bürcky, MD (Ochsenfurt); Edeltraud Burg, MD; Rita Berger, MD (Straubing); Peter Büttner, MD; Petra May, MD (Memmingen); Barbara Capelle, MD (Unterhaching); Mona Castrop, MD (Regensburg); Bernd Chittka, MD; Franz-Josef Kordowich, MD; Thomas Eltermann, MD (Karlstadt); Barbara Christl, MD (Wegscheid); Alina Cocos, MD (Markt Schwaben); Isabel Cordes, MD; Denis Gebhard, MD (Nürnberg); Christoph Daffner, MD (Nürnberg); Claudia Delles, MD (Nürnberg); Arcan Demircioglu, MD (München); Jost Dieckerhoff, MD (Rosenheim); Karolin Diergarten, MD (Germering); Karolin Diergarten, MD (Eching); Peter Dietl, MD (München); Elmar Dietmair, MD (Bobingen); Lutz Dietrich, MD (Hof); Maximilian Dietrich, MD; Thomas Bihler, MD (Aichach); Brigitte Dietz, MD (Taufkirchen); Christian Döbig, MD (Erlangen); Bernadette Donath, MD; Andreas Kammermeier, MD (Passau); Sylvia Döpfer, MD (München); Jürgen Dörrer, MD (Freyung); Ragnar Dörrfuss, MD (Nürnberg); Monika Drexel, MD (Rehau); Bettina Düll, MD (Ippesheim); Elke Düll-Schiller, MD (Neumarkt); Désirée Dunstheimer, MD (Augsburg); Stefan Eber, MD (München); Thomas Ebert, MD (Veitsbronn/Siegelsdorf); Christoph Ebert, MD (Ebersberg); Christina Eder, MD (Bayreuth); Eibl, MD (Beratzhausen); Claudia Eichwald, MD (Ingolstadt); Annette Eiden, MD (Gauting); Hans-Dieter Eisner, MD (Kronach); Claus Engelhardt, MD (Nürnberg); Anja Engelmann, MD (Dinkelscherben); Georg Engl, MD (München); Uta Enzensberger, MD, (Mering); Alois Epp, MD (Kaufbeuren); Petra Erhardt, MD (Bamberg); Patricia Erlinger, MD (Postbauer-Heng); Uwe Ermer, MD (Neuburg a.d. Donau); Kirsten Exl, MD (München); Florian Fackler, MD (Erlangen); Edgar Fath, MD (München); Andreas Fauser, MD; Alexandra Sand, MD; Lothar Karolyi, MD; Dominic Hegele, MD (Dillingen); Peter Feiereisen, MD (München); Daniela Felsl, MD (Wolnzach); Maria Fischer, MD (Lappersdorf); Cordula Fischer-Trüstedt, MD (München); Gudrun Fleck, MD; Alfred Heihoff, MD (Regensburg); Katrin Flögel, MD (Gundelfingen); Katrin Flögel, MD (Günzburg); Anna-Maria Frangoulis, MD (Gilching); Katrin Franke-Augustin, MD (Bayreuth); Harald Frantzmann, MD (Memmingen); Rudolf Franz, MD (München); Alexandra Fraundorfer, MD (Michelsneukirchen); Susanne Freislederer-Caccia, MD (München); Claudia Frey, MD (Augsburg); Karl Fromme, MD (Coburg); Dominik Fürsich, MD (Altdorf); Ulrich Gandela, MD (Furth im Wald); Susanne Gandenberger-Bachem, MD (München); Markus Gauer, MD (Vöhringen); Antonia Gavazzeni, MD (München); Bernhard Geck, MD (Nürnberg); Edeltraud Gerber, MD (Kolbermoor); Martin Gerlich, MD (Dinkelsbühl); Elke Gerlitz, MD (Herzogenaurach); Julia Gerstl, MD (Hauzenberg); Michael Gerstmayr, MD (Ingolstadt); Jürgen Geuder, MD (Freilassing); Johannes Gilles, MD (Gunzenhausen); Rainer Gillessen, MD (Ottobrunn); Elisabeth Gimpl, MD (Schweinfurt); Cornelia Gläßel, MD (Fürth); Judith Glöckner-Pagel, MD (Regensburg); Elke Gloger, MD (Ochsenfurt); Birgit Goldschmitt-Wuttge, MD (München); Michaela Göttler, MD (Muhr am See); Martin Götz, MD (Elisabethzell); Elif Götz, MD; Ulrike Sautier, MD (Pullach); Wolfgang Graser, MD (Nürnberg); Marion Grau, MD (Nürnberg); Martin Griebel, MD (Poing); Anette Groethuysen, MD (München); Wilma Großkopf, MD; Josef Großkopf, MD (Wallerfing); Angelika Gruber-Müller, MD (Ingolstadt); Martin Grundhuber, MD (Bad Tölz); Dietrich Grunert, MD (Kempten); Mehmet Güler, MD (Neuendettelsau); Christian Haas, MD (München); Richard Haaser, MD (Feucht); Hanne Habelt-Bock, MD (Happurg); Caroline Haberl, MD (Starnberg); Ulrich Hagen, MD (Friedberg); Henrik Halboni, MD (München); Verner Hallmen, MD (München); Emma Halwas, MD (Geisenfeld); Stefan Hammann, MD (München); Georg Handwerker, MD (Passau); Matthias Hartig, MD (Vilsbiburg); Marcus Härtle, MD (Krumbach); Conny Hartmann, MD (Bad Wörishofen); Ingrid Hartmann, MD (Lichtenfels); Christian Hartnik, MD (Bad Staffelstein); Matthias Hasenpusch, MD (Schierling); Ulrike Haun, MD (Vilshofen); Gabi Haus, MD (München); Marita Häußlein, MD; Susanne Joha, MD; Michael Deckelmann, MD (Würzburg); Rudolf Havla, MD (Hof); Johannes Havla, MD (Pegnitz); Gabriele Hecht, MD (Peiting); Birgit Heck-Buchhorn, MD; Susanne Willnow, MD (Kösching); Holger Hedderich, MD; Josef Seidl, MD (Füssen); Bernhard Heeren, MD (Langenzenn); Ralph Heidingsfelder, MD (Ansbach); Christine Heinemeyer, MD (Nordheim); Markus Helmreich, MD (Schweinfurt); Tanja Hemmers, MD (Augsburg); Andreas Henning, MD (Lauf); Johannes Herrmann, MD (Schweinfurt); Holger Hertzberg, MD (Schwabach); Sigrid Hesse, MD (Straubing); Daniela Heuschmann, MD; Dominik Ewald, MD (Regensburg); Andreas Hickmann, MD (Schneeberg); Ulrich Hilber, MD (Höchstadt); Bernward Hinkes, MD; Thorsten Fröhlich, MD (Forchheim); Andrea Hinnawi, MD (Großostheim); Ladislaus Hochschau, MD (Regensburg); Cornelia Hoegen, MD (Herrsching); Reinhard Hoffmann, MD (Landshut); Klaus Hoffmann, MD (Niederwerrn); Steffen Hoffmann-Baldus, MD (Haar); Gerhard Hofmann, MD (Würzburg); Meike Hofmann, MD (Mitterteich); Andrea Högl, MD; Gregor Zuj, MD (Schwandorf); Sabina Hohn, MD (Nürnberg); Marie-Luise Holler, MD (Rain am Lech); Martina Hoog, MD (Uffenheim); Kirsten Höper, MD (Augsburg); Gabriele Hopf, MD (Ingolstadt); Jörg Horcher, MD (Straubing); Alexia Horelt-Ernou, MD (München); Michael Horn, MD (Schönau am Königssee); Birgit Hortig-Nevelö, MD (Regenstauf); Annette Hovestadt, MD (München); Gottfried Huber, MD (München); Benedikta Huber-Lederer, MD (Fürstenzell); Irene Hummel, MD (Bamberg); Peter Hußlein, MD (Grassau); Wolfgang Hüttner, MD (Coburg); Anna Maria Iarrapino-Demmel, MD (München); Birgit Indlekofer, MD (Tutzing); Anneliese Intemann, MD (München); Margarete Jäger, MD (München); Christine Janello, MD (Neubiberg); Stephan Jarosch, MD; Manuel Langer, MD (Würzburg); Stefan Jobst, MD (Bayreuth); Janina Joiko, MD (München); Birgit Jork-Käferlein, MD (Prien); Guido Judex, MD (Regensburg); Guido Judex, MD; Monika Corbacioglu, MD; Sabrina Lindner, MD; Bastian Baumgartner, MD (Regensburg); Ronny Jung, MD (Roth); Imme Kaiser, MD (Puchheim); Laura Kallmann, MD; Lyn Kohl, MD (München); Andreas Kalmutzki, MD (Schwabach); Ludwig Kamhuber, MD (Kraiburg am Inn); Vanadis Kamm-Kohl, MD (Nürnberg); Lampros Kampouridis, MD (Baldham); Michael Kandler, MD (Nürnberg); Susanne Kastl, MD (Bayreuth); Walther Kaufmann, MD (Nürnberg); Bernhard Keck, MD (Augsburg); Ursula Keicher, MD (Neubiberg); Peter Kellner, MD (Vilsbiburg); Lars Kellner, MD (Gräfelfing); Beate Kevekordes-Stade, MD (Neunkirchen am Brand); Ghassan Khazim, MD (Hammelburg); Christiane Kiefer, MD (Straßlach); Werner Kienle, MD (Feldkirchen-Westerham); Gunhild Kilian-Kornell, MD (Starnberg); Christa Kitz, MD (Veitshöchheim); Annegret Klein, MD (Oberaudorf); Arno Klein, MD (Vilsbiburg); Wolfgang Klein, MD; Dominik Kutter, MD (Augsburg); Kristina Klemp, MD (Burgkunstadt); Jörg Klepper, MD (Aschaffenburg); Margreth Knebel, MD (München); Harald Knee, MD; Astrid Treude, MD (Peißenberg); Norbert Knieß, MD; Oliver Kolonko, MD (Ingolstadt); Daniela Kober, MD; Irmgard Spannagel, MD (Gmund); Andreas Koch, MD; Christoph Gerdemann, MD; Silke Kimpel, MD (Erlangen); Katalin Köhler-Vajta, MD (Grünwald); Herbert Kollaschinski, MD (Marktredwitz); Cornelia Komm, MD (Waldkraiburg); Nikos Konstantopoulos, MD (München); Cosima Köring, MD (Altötting); Christian Korzinek, MD (Wolnzach9; Renate Kramer, MD (München); Guido Krandick, MD (Deisenhofen); Barbara Krappatsch, MD (Viechtach); Karla Krause, MD; Olga Stepanowa, MD; Cornelia Kiani, MD (Bayreuth); Berndt Kreisberger, MD (Ismaning); Stefan Krell, MD (Tirschenreuth); Gabriela Kreller-Laugwitz, MD (Adelsdorf); Ulrike Kreuels, MD (Nürnberg); Michaela Krieger, MD (Germering); Andreas Kronwitter, MD (München); Matthias Krueger, MD (Klingenberg); Danylo Kubryk, MD; Günther Döring, MD (Aschheim); Thomas Kuchenbauer, MD (München); Lisa Kuchler, MD (Stallwang); Heinrich Küffner, MD (Bad Windsheim); Karl Kugler, MD; Christian Mühe, MD (München); Stephan Küntzer, MD (Kitzingen); Wolfgang Künzer, MD (Regensburg); Beate Kusser, MD (München); Wolfgang Küver, MD (München); Franz Lachner, MD (Ruhpolding); Christof Land, MD (Gauting); Wolfgang Landendörfer, MD (Nürnberg); Martin Lang, MD (Augsburg); Christina Lang, MD (Nürnberg); Carolin Lang, MD; Britta Zötl, MD (Bad Tölz); Bettina Lang-Negretto, MD (München); Otto Laub, MD (Rosenheim); Annette Laub, MD (Bergen); Peter Lautenbach, MD (Herzogenaurach); Gerhard Legat, MD (Amberg); Ulrike Lehnert, MD (Erlangen); Stefan Leidig, MD; Heiko von Goessel, MD (Lauf); Christian Leitner, MD (Pfaffenhofen an der Ilm); Gabriele Lenz, MD; Christian Wander, MD (Piding); Katrin Leuchtenberger, MD (Kelheim); Ildiko Leuthe-Vogel, MD (Neu-Ulm); Karin Leykauf, MD (Bayreuth); Hans Lichtenstern, MD; Monika Muhr, MD; Tobias Busse, MD; Birgit Siegl, MD (Pocking); Werner Lick, MD (Würzburg); Gabriele Lieb, MD (Würzburg); Bärbel Liebezeit, MD (Mühldorf am Inn); Armin Liebscher, MD (Eckental); Katharina Lindel, MD (Rain am Lech); Michaela Lindenau-Maier, MD (Pfaffenhofen); Susanne Linder, MD (Grafrath); Katharina Lindhorst, MD; Daniel Seng, MD; Thomas Schuch, MD (Unterschleißheim); Hubertus Lindner, MD (Pegnitz); Ruth Lindner-Gajek, MD; Soyoun Maisch, MD (München); Janusz Lipinski, MD; Kirsten Mende, MD; Susanne Kirtscher, MD (Lindenberg); Barbara List, MD (Siegsdorf); Harald Lodes, MD; Kathrin Rosenthal, MD (Neumarkt); Markus Loeff, MD (Landsberg am Lech); Andreas Lorenz, MD (Krumbach); Petra Lorenzini, MD (Heideck); Martin Löw, MD (Memmingen); Ulf Lüdicke, MD (Rödental); Anna Elisabeth Lüdtke, MD (Neu-Ulm); Renata Lysy, MD (Möhrendorf); Eva Maas-Doyle, MD (Erlangen-Tennenlohe); Jarmilla Mahlmeister, MD; Anita Conze, MD (Schondra); Peter Maier, MD; Heiko Weerda, MD (Pfaffenhofen); Brigitte Maier-Brandt, MD (Stein); Selma Maierhofer, MD (Adlkofen); Soyoun Maisch, MD (München); Sibylle Manstein-Heueis, MD (Icking); Birgit Marquardt, MD (Oy-Mittelberg); Stefanie Marr, MD (Ingolstadt); Sigrid Martin, MD; Margarete Schilder, MD (Schrobenhausen); Helmuth Mauer, MD (Lichtenberg); Monika Maurus, MD (Memmingen); Peter Mayr, MD (Memmingen); Ernst Georg Mayr, MD (Murnau); Jeanette Mederer, MD (Laaber); Barbara Meiler, MD (Grafrath); Udo Meißner, MD (Bamberg); Norbert Meister, MD (Bindlach); Juan-Carlos Menendez-Castro, MD (Bad Kissingen); Steffi Menzel, MD (München); Susanne Merget, MD (Germering); Manfred Meßmer, MD (Augsburg); Jürgen Messner, MD (Lohr); Roland Metzner, MD (Würzburg); Petra Sibyl Meyer, MD (Augsburg); Oliver Michael, MD (Murnau); Wolfgang Moll, MD (Reichertshausen); Wolfgang Moser, MD (Schondorf); Kathrin Mothes, MD (Schwandorf); Miriam Mrach, MD (München); Sabine Mühlbauer, MD (München); Udo Mulitze, MD (Mainburg); Ulrich Müller, MD (Gauting); Daniel Müller, MD (Amberg); Herbert Müller, MD (Kempten); Wolfgang Müller, MD; Martin Wilken, MD; Andrea Schürmann, MD (Naila); Müller-Ntokas, MD (Sulzbach-Rosenberg); Patrick Muzzolini, MD (Kulmbach); Sabine Nagel, MD (Neustadt/Donau); Dieter Nagel, MD (Freyung); Karsten Naumann, MD (Erlangen); Nicole Nellen-Hellmuth, MD (Würzburg); Klaus Neumann, MD (Höhenkirchen-Siegertsbrunn); Christiane Neumeir, MD (Königsbrunn); Hans-Peter Niedermeier, MD (Erding); Maria Nitsch, MD (Wolnzach); Maike Nordmann, MD (Fürstenfeldbruck); Jochen Noss, MD (München); Andreas Nowack, MD (Siegsdorf); Barbara Nowitzky, MD (Peißenberg); Thomas Nowotny, MD (Stephanskirchen); Marcus Oberkötter, MD (Hohenwarth); Stefan Oberle, MD (Höchstadt); Jutta Oberndorfer, MD (Schonungen); Barbara Oberneder, MD (Gräfelfing); Christine Olbrich, MD (Augsburg); Angela Olze, MD (München); Dilek Önaldi-Gildein, MD (München); Michael Osang, MD; Petra Pudenz, MD (München); Jürgen Pannenbecker, MD; Anette Hein, MD (Gerbrunn); Nicola Pape-Feußner, MD (Berg); Barbara Parhofer, MD; Rüdiger Wiß, MD (Dachau); Michael Pätzold, MD (Marktoberdorf); Christine Pauli, MD; Stephan von Hornstein, MD (Olching); Michaela Pausenberger, MD (Lauf a.d. Pegnitz); Matthias Peisler, MD (Forchheim); Sonja Pemsl, MD (Nürnberg); Josivania Maria Pereira da Silva, MD (Hof); Wolfgang Peter, MD (Zeitlarn); Christine Pfaller, MD (Frasdorf); Angela Pfeffer, MD (Regen); Dominik Pfister, MD (Obing); Bergit Pfleger, MD (Neuendettelsau); Angelika Plank-Wihr, MD (Kallmünz); Stefan Platzer, MD (Osterhofen); Bernhard Pleyer, MD (Rückersdorf); Annette Pohl-Koppe, MD (München); Heike Polster, MD; Judit Kainzinger, MD (Dingolfing); Andreas Pontz, MD; Konrad Wimmer, MD (Passau); Martin Poschenrieder, MD (Vohenstrauß); Rudolf Poschenrieder, MD; Gudrun Korzenietz, MD (Vohenstrauß); Manfred Praun, MD (Gilching); Constanze Preis, MD; Wolfgang Preis, MD (Bischberg); Eberhard Preissler, MD; Zuhal Tomas, MD; Wolfgang Theil, MD (Gersthofen); Verena Printz, MD (Fürstenfeldbruck); Gabriele Prinz, MD; Eva Maria Sedlacek, MD (Burgau); Anke Prothmann, MD (Gröbenzell); Barbara Przyklenk, MD (München); Georg Puchner, MD (Regensburg); Stefan Putz, MD (Iggensbach); Norbert Raabe, MD (Weißenburg); Gertraud Raber-Webhofer, MD (München); Wolfgang Rahner, MD (Friesenried); Marco Ramella Pezza, MD (Meitingen); Udo Rampf, MD; Angela Lautner, MD (Freising); Jürgen Ratay, MD (Freising); Jürgen Ratay, MD (Hallbergmoos); Heribert Rauch, MD (Hengersberg); Angela Rausch, MD (Traunstein); Karla Rauschning-Sikora, MD (Mainaschaff); Christiane Razeghi, MD (Miesbach); Angela Reber, MD (Pfaffenhofen); Anja Regenfus, MD (Nürnberg); Brigitte Reichstein, MD (Ingolstadt); Evelyn Reineke, MD (Karlshuld); Tobias Reinhardt, MD (Feuchtwangen); Gertrud Reiter, MD (Neusäß); Michaela Reitz, MD; Johannes Pawlak, MD (Rosenheim); Christian Renner, MD (Deggendorf); Roland Renz, MD; Claudia Lauterbach, MD (Weiden); Tobias Reploh, MD (Bad Tölz); Volkmar Reschke, MD; Stella Exner, MD (Kaufbeuren); Gert Reutter-Simon, MD (Nürnberg); Michael Richter, MD; Mina Mameghanian, MD (München); Bernhard Riedl, MD (Wenzenbach); Mustafa Rihawi, MD (Kronach); Norbert Rindle, MD (Königsbrunn); Claudia Ringert-Esmaeili, MD; Beate Winters, MD (Alzenau); Carsten Rinker, MD (München); Kristina Risse, MD (Ingolstadt); Isabel Ritz, MD (München); Fritz Robitzsch, MD (Bodenmais); Gisela Rodorff, MD (Ichenhausen); Ingrid Rohland, MD (Erding); Herbert Rohr, MD (Fürstenfeldbruck); Alexander Roithmaier, MD (München); Maria Römmelt, MD (Schwanfeld); Stefanie Rosam, MD; Philip Wintermeyer, MD (München); Mark Rosenthal, MD; Anke Lütkemeyer, MD (Unterschleißheim); Walter Rößler, MD (Weiden); Christian Rothascher, MD; Ursula Shane, MD; Peter Beierlein, MD (Schnaittach); Anne Katrin Rothe, MD (München); Christian Rudolf, MD (Bad Neustadt); Sebastian Rühl, MD (Nürnberg); Irene Rühlemann, MD (München); Ramon Rümler, MD (Dachau); Paulina Ruppel, MD (Hof); Frank Rüßmann, MD; Evagelia Rüßmann-Tzilini, MD (München); Uwe Sack, MD; Silvia Glotzbach-Sack, MD; Margarethe Kozuschek, MD (Würzburg); Renate Sacker, MD (München); Reinhard Sailer, MD; Margit Kosoko, MD (Vilsbiburg); Sirin Salik, MD (Nürnberg); Franziska Schaaff, MD; Jan-Helge Höpner, MD (Eckental-Eschenau); Gabriele Schall, MD (Bad Wörishofen); Sigrid Scharrer-Bothner, MD (Nördlingen); Hans-Ulrich Schatz, MD (München); Carolus Schenke, MD (Neustadt a.d. Aisch); Barbara Scherer, MD (München); Gabriele Scheuerer, MD; Andrea Schimmer-Eidenschink, MD (München); Holger Schiffmann, MD (Feucht); Birgit Schilling, MD (Passau); Ute Schindler, MD (Kelheim); Ralf Schipper, MD (Monheim); Lydia Schlak, MD (Sulzbach-Rosenberg); Josef Schleibinger, MD (Pfaffenhofen); Ewald Schlereth, MD (Oberthulba); Andreas Schlossbauer, MD (Bad Kissingen); Stefan Schmid, MD (Riedenburg); Ludwig Schmid, MD (München); Petra Schmid-Seibold, MD; Georg Leipold, MD (Regensburg); Stefan Schmidt, MD (Rosenheim); Volker Schmidt, MD (Kempten); Wolfram Schmidt, MD (Bad Königshofen); Dorothea Schmidt-Colberg, MD (Erlangen); Annelies Schmölz-Hefele, MD (Kaufbeuren); Stephan Schneider, MD (Schweinfurt); Ulrich Schneider, MD (Biberbach); Klaus Schneider, MD (Hohenthann); Klaus Schnell, MD; Katja Nillies, MD (Coburg); Martin Scholz, MD; Dunja Scholz-Kühn, MD (Deggendorf); Monika Schömig-Spingler, MD (Würzburg); Patric Schön, MD (Oberschleißheim); Volker Schönecker, MD (Kaufering); Martin Schöniger, MD (Weilheim); Roland Schöniger, MD (Rotthalmünster); Philipp Schoof, MD (München); Eduard Schreglmann, MD (Kirchenthumbach); Cristian Schröter, MD (München); Franziskus Schuhböck, MD (Kirchheim); Carola Schum, MD (Parsberg); Brigitte Schwager, MD (Eckental); Kirsten Schwarz, MD (Regenstauf); Axel Schweighart, MD (München); Christine Schweikl, MD (Eggenfelden); Rosemarie Schwertner, MD (Germering); Julia Seemann, MD; Stephanie Bosch, MD; Rudolf Loibl-Keimler, MD (Deggendorf); Christian Seidel, MD; Gabriele Hopf, MD; Stephanie Marr, MD; Brigitte Reichstein, MD (Ingolstadt); Monika Seidt, MD (München); Andrea Seiler, MD; Jasmin Pletl-Maar, MD; Katja Gaßmann, MD (Erlangen); Horst Seithe, MD (Nürnberg); Nina Sellerer, MD; Roman Polanetz, MD (München); Marko Senjor, MD (Wasserburg am Inn); Ursula Shane, MD (Lauf a.d. Pegnitz); Kathrin Simmel, MD (Holzkirchen); Berta Simon, MD (Zwiesel); Marina Sindichakis, MD (Traunstein); Manfred Singer, MD (Forchheim); Cornelia Singer, MD (Wessling); Simon Sitter, MD (Bechhofen); Claudia Söhngen, MD (Traunreut); Anita Sommer, MD; Barbara Domes, MD (Karlsfeld); Bernhard Sondermaier, MD (Ampfing); Wilfried Späth, MD (Weißenhorn); Michael Sperlich, MD (Ampfing); Claudia Spieß, MD; Anke Robert, MD (Neuburg); Claudia Spooren, MD; Nurcan Incekara, MD (Senden); Sabine Sprich, MD; Rudolf Sprich, MD (Biessenhofen); Johannes Stadler, MD (Gerolzhofen); Helmut Stadler, MD (Straubing); Wilhelm Stechl, MD (Raubling); Wolfgang Steck, MD (Immenstadt); Christa Steenpaß, MD (Aschaffenburg); Marko Stein, MD (München); Wolfgang Steinbach, MD (Scheßlitz); Gerhard Steinberg, MD; Christopher Hauser, MD; Gertraude Klötzer, MD (Mittenwald); Gerhard Steinberg, MD; Johanna Wiese, MD; Ulrike Fulda-Rohlfs, MD; Christopher Hauser, MD (Garmisch-Partenkirchen); Constanze Steinborn, MD (Sauerlach); Andreas Steiner, MD (Landsberg); Bernd Steinkirchner, MD (Neufahrn); Paul Steinocher, MD (Augsburg); Stefan Stellwag, MD (München); Frank Steppberger, MD (Oberasbach); Heiko Stern, MD; Ullrich Fakler, MD (Gauting); Rosa Stettner-Gloning, MD; Slim Saadi, MD (München); Anke Steuerer, MD (Augsburg); Elisabeth Stöckhert, MD; Ingeborg Meyer, MD (Fürth); Christoph Stöhr-Sökefeld, MD (Neubiberg); Anette Stratmann, MD; Matthias Ensslen, MD (Holzkirchen); Dominik Stricker, MD (Lappersdorf); Annette Strobel, MD (Erlangen); Michael Strobelt, MD (Bruckmühl); Gesine Strohbach, MD (Nürnberg); Thomas Sturm, MD (Fürstenfeldbruck); Raphael Sturm, MD (Affing); Ursula Tchassem Tagny, MD (Neuburg a.d. Donau); Harald Tegtmeyer-Metzdorf, MD (Lindau); Vita Teichler, MD (München); Hans-Georg Terbrack, MD (Abensberg); Günter Theurer, MD; Günter Steidle, MD (Traunstein); Claus-Dieter Thiem, MD (Salzweg); Barbara Thumann, MD (Dietfurt); Uta Tielker, MD (Eichenau); Achim Timnik, MD; Gertrud Reiter, MD (Neusäß); Michael Torbahn, MD (Nürnberg); Regina Trammer, MD (Planegg); German Tretter, MD (Altenstadt/Waldnaab); Barbara Tröger, MD (Rain); Burkhard Trusen, MD (Bamberg); Martin Ulbrich, MD (Otterfing); Stephan Unkelbach, MD (Volkach); Reiner Valentin, MD (Grafing); Michael Veh-Hölzlein, MD (Fürth); Erhard Vetter, MD (Schönthal); Oliver Viethen, MD (Traunstein); Michael Vogel, MD (München); Hartmut Vogel, MD (Roth); Christian J. Voigt, MD (Stadtbergen); Victor von Arnim, MD (Roding); Eleonore von der Schulenburg, MD (München); Heike von Pigenot, MD (Ottobrunn); Katharina von Saurma, MD (München); Patrik von Schoenaich, MD (Neusäss); Olaf Vorbeck, MD (Moosburg); Christoph Wachenfeld-Wahl, MD (Augsburg); Roland Wagner, MD (Nittendorf); Gabriele Wagner, MD (Haag an der Amper); Alexander Wagner, MD (Kitzingen); Roland Wagner, MD (Regensburg); Hans Josef Wainryb, MD (Jesenwang); Edgar Waldmann, MD (Bamberg); Karin Waldmann, MD (Memmelsdorf); Heike Walessa, MD (Gars am Inn); Irene Walser, MD (Wolnzach); Susanne Wawatschek, MD; Olga Stroh, MD (Diedorf); Helke Weber, MD (Holzkirchen); Annette Weber-Pöhlmann, MD (Selb); Claudia Wegener, MD (München); Stefan Weickardt, MD (Straubing); Josef Weidinger, MD (Nabburg); Johannes Weigel, MD (Augsburg); Christine Weigmann-Popp, MD; Ulrike Ege-Mirzai, MD (Bamberg); Philipp Weinert, MD (Obergünzburg); Benedikt Weiß, MD (Bad Kötzting); Michael Weiß, MD (Kempten); Anika Wels, MD (Stegaurach); Mathias Wendeborn, MD (München); Beatrix Wenzel, MD; Simon Then, MD (Lichtenfels); Joachim Westphal, MD (Taufkirchen/Vils); Oliver Wiese, MD (Landsberg am Lech); Andreas Wiesheu, MD; Matthias Buckl, MD; Elisabeth Paul, MD; Corinna Popp, MD (Landshut); Margit Wiessner-Straßer, MD; Tobias Eisenhut, MD (München); Anke Wilberg, MD (Schwarzenbach am Wald); Martin Wilken, MD; Andrea Schürmann, MD; Lidia Steigerwald, MD (Hof); Karolin Wilman, MD (Friedberg); Jochen Winkler, MD (Schwabmünchen); Tobias Winter, MD (Teisendorf); Christina Wirth, MD; Jürgen Kleinhenz, MD; Jürgen Streit, MD (Brückenau); Christian Wittmann, MD (Fürth); Hermann Wittrock, MD (Mering); Anton Wohlfart, MD (Ehekirchen); Daniela Wohlmann, MD (Garmisch-Partenkirchen); Paul Wolf, MD (Erlangen); Marco Wölfel, MD; Hans Georg Schatz, MD (Bayreuth); Lothar Wurzer, MD (Oberstdorf); Christof Zang, MD (Haibach); Claudia Zapillon, MD (München); Alexander Zeiss, MD (München); Stefan Zeller, MD (Kempten); Roland Zeller, MD (Aschaffenburg); Stephan Zieher, MD (Marktheidenfeld); Sabine Ziemer, MD; Amalia Herineanu, MD (Nürnberg); Mathias Zimmer, MD (Coburg); Thomas Zimmermann, MD (Hirschaid); Thomas Zimmermann, MD (Burgebrach); Lothar Zimmermann, MD (Aichach); Stefan Zink, MD (Nürnberg); Dorothea Zitzmann, MD (Burgheim); Andreas Zurmühl, MD (Penzberg); Kristin Zwenzner, MD (Bayreuth); Kristin Zwenzner, MD (Neudrossenfeld).

Psychological consulting (Hannover Medical School, Hannover, Germany): Developing and performing the psychological assessment analysis: Karin Lange, PhD, Iris Müller, PhD, Rosanna Rodriguez, BSc, Mirjam Bassy, MD.

Data Sharing Statement: The data set analyzed in this paper is available from the corresponding author on reasonable request, and with appropriate additional ethical approvals, where necessary.

Additional Contributions: We thank Minister of State Melanie Huml, MD, who acted as the honorary patron of the Fr1da study.

Additional Information: Fr1da clinical centers received reimbursement for the clinical care of individuals undergoing metabolic staging and follow-up (ranging from 10€ to 130€ per visit). Primary care pediatricians received reimbursement of 10€ per study participant for consenting, collecting the screening sample and completing the questionnaire.

^✉

Corresponding author.

PMCID: PMC6990943 PMID: 31990315

Key Points

Question

What is the yield of primary care–based screening of children for islet autoantibodies?

Findings

In a program that screened 90 632 children aged 2 to 5 years in Bavaria, Germany, during primary care visits, 280 children (0.31%) had 2 or more islet autoantibodies, among whom 62 developed clinical type 1 diabetes and 2 had mild or moderate diabetic ketoacidosis. Mothers of children with presymptomatic type 1 diabetes reported more symptoms of depression at diagnosis than mothers of children without islet autoantibodies (median psychological stress score of 3 vs 2).

Meaning

These findings may inform considerations of population-based screening of children for islet autoantibodies.

Abstract

Importance

Public health screening for type 1 diabetes in its presymptomatic stages may reduce disease severity and burden on a population level.

Objective

To determine the prevalence of presymptomatic type 1 diabetes in children participating in a public health screening program for islet autoantibodies and the risk for progression to clinical diabetes.

Design, Setting, and Participants

Screening for islet autoantibodies was offered to children aged 1.75 to 5.99 years in Bavaria, Germany, between 2015 and 2019 by primary care pediatricians during well-baby visits. Families of children with multiple islet autoantibodies (presymptomatic type 1 diabetes) were invited to participate in a program of diabetes education, metabolic staging, assessment of psychological stress associated with diagnosis, and prospective follow-up for progression to clinical diabetes until July 31, 2019.

Exposures

Measurement of islet autoantibodies.

Main Outcomes and Measures

The primary outcome was presymptomatic type 1 diabetes, defined by 2 or more islet autoantibodies, with categorization into stages 1 (normoglycemia), 2 (dysglycemia), or 3 (clinical) type 1 diabetes. Secondary outcomes were the frequency of diabetic ketoacidosis and parental psychological stress, assessed by the Patient Health Questionnaire-9 (range, 0-27; higher scores indicate worse depression; ≤4 indicates no to minimal depression; >20 indicates severe depression).

Results

Of 90 632 children screened (median [interquartile range {IQR}] age, 3.1 [2.1-4.2] years; 48.5% girls), 280 (0.31%; 95% CI, 0.27-0.35) had presymptomatic type 1 diabetes, including 196 (0.22%) with stage 1, 17 (0.02%) with stage 2, 26 (0.03%) with stage 3, and 41 who were not staged. After a median (IQR) follow-up of 2.4 (1.0-3.2) years, another 36 children developed stage 3 type 1 diabetes. The 3-year cumulative risk for stage 3 type 1 diabetes in the 280 children with presymptomatic type 1 diabetes was 24.9% ([95% CI, 18.5%-30.7%]; 54 cases; annualized rate, 9.0%). Two children had diabetic ketoacidosis. Median (IQR) psychological stress scores were significantly increased at the time of metabolic staging in mothers of children with presymptomatic type 1 diabetes (3 [1-7]) compared with mothers of children without islet autoantibodies (2 [1-4]) (P = .002), but declined after 12 months of follow-up (2 [0-4]) (P < .001).

Conclusions and Relevance

Among children aged 2 to 5 years in Bavaria, Germany, a program of primary care–based screening showed an islet autoantibody prevalence of 0.31%. These findings may inform considerations of population-based screening of children for islet autoantibodies.

This study categorizes the prevalence of 2 or more islet autoantibodies identified in preschool children in a population screening program, and the progression from presymptomatic to clinical symptomatic type 1 diabetes.

Introduction

The identification of patients with a disease prior to its clinical manifestation provides opportunities for prevention and for counseling and preparation of individuals for the changes that arise with the disease. Type 1 diabetes in children is diagnosed following the onset of symptoms, including acutely elevated blood glucose concentrations and potentially life-threatening complications.¹ Diabetic ketoacidosis is observed in more than 20% of children at the onset of type 1 diabetes² and may be severe or even fatal in undiagnosed or misdiagnosed patients.³ Therefore, the possibility of diagnosing type 1 diabetes at an early disease stage could reduce morbidity.^4,5

The preclinical period in patients who develop type 1 diabetes is characterized by the presence of autoantibodies against pancreatic islet cells. Most children with autoantibodies against 2 or more major islet autoantigens will develop overt diabetes,⁶ and the additional assessment of pancreatic islet β cell function enables the staging and stratification of the asymptomatic phase prior to clinical disease onset.^7,8 These prognostic features of islet autoantibodies are used to recruit individuals to prevention trials and as early outcome markers in cohort studies and primary prevention trials.^9,10,11 However, these uses are largely restricted to individuals with increased genetic risk, who represent a minority of future patients. The Fr1da study assessed the prevalence of presymptomatic type 1 diabetes in children participating in a public health screening program for islet autoantibodies, the risk for progression to clinical diabetes and diabetic ketoacidosis, and parental psychological stress.

Methods

Study Design

This study was approved by the institutional review board at Technical University Munich. From February 2015 to May 2019, children in Bavaria, Germany, aged 1.75 to 5.99 years without a previous diagnosis of diabetes were offered screening for multiple islet autoantibodies by primary care pediatricians in the context of well-baby visits (eFigure 1 in the Supplement). Participation by pediatricians and children was voluntary. Written informed consent was obtained from the children’s parents or legal guardians. The study design has been published.¹²

Capillary blood samples were collected by pediatricians and sent to the central laboratory for measurement of islet autoantibodies. Demographic data of the participating children (date of birth, sex, weight, height, date of blood collection, first-degree family history of type 1 diabetes) were collected using a questionnaire at the visit. If the screening sample was positive for multiple autoantibodies, the pediatrician was alerted and a confirmation venous blood sample was requested. At this second visit, the pediatrician often performed a random blood glucose measurement. If multiple islet autoantibodies were confirmed, the family was informed by the pediatrician. Families of children with presymptomatic type 1 diabetes were invited to participate in metabolic staging and an educational program at a pediatric diabetes clinic close to their residence. Depending on the staging outcome, a monitoring plan for future visits at 2- to 6-month intervals was implemented.^12,13 Follow-up continued until July 31, 2019. Children with stage 1 type 1 diabetes (≥2 islet autoantibodies and normal glucose tolerance) were asked to participate in an intervention study (NCT02620072) with 1:1 randomization to receive either 12 months of treatment with oral insulin or placebo.

A control cohort was established from a sample of children whose screening test results were negative for islet autoantibodies between December 2015 and March 2018 and were living in the Munich area. In addition, children from the DiMelli study¹⁴ without prior screening for islet autoantibodies who were diagnosed with type 1 diabetes in the same pediatric clinics between February 2015 and February 2018 were included for the assessment of parental psychological stress.

Assessments

Islet autoantibodies were measured using a stepwise approach.¹² First-line screening was performed with a sensitive enzyme-linked immunosorbent assay (3 Screen; RSR Ltd) to detect glutamic acid decarboxylase autoantibodies (GADAs), islet antigen 2 autoantibodies (IA-2As), and zinc transporter 8 autoantibodies (ZnT8As) in serum prepared from capillary blood.¹⁵ Screening samples positive for islet autoantibodies (>25 units/mL; 98th percentile of children samples) and confirmation venous blood samples were measured for GADAs, IA-2As, ZnT8As, and insulin autoantibodies (IAAs) using reference radiobinding assays.^16,17,18 Oral glucose tolerance tests (OGTTs) were performed for staging using a glucose load containing the equivalent of 1.75 g/kg up to a maximum of 75 g anhydrous glucose dissolved in water.⁸ Blood gas analysis (pH) was performed to detect ketoacidosis in children diagnosed with clinical stage 3 type 1 diabetes. Genotyping on 46 single nucleotide polymorphisms was performed to calculate a genetic risk score¹⁹ if consent for ancillary research was provided. Psychological stress in parents/guardians was measured at the time of metabolic staging and at 6 and 12 months after presymptomatic diagnosis with the Patient Health Questionnaire-9 (PHQ-9; range, 0 [best] to 27 [worst]; scores ≤4 were interpreted as no to minimal depression and >20 as severe depression).²⁰

Outcome Definitions

The primary outcome was presymptomatic type 1 diabetes, defined as positive for 2 or more islet autoantibodies (IAA, GADA, IA-2A, ZnT8A) in both the screening and confirmation samples or in the screening sample plus a diagnosis of diabetes prior to obtaining the second sample. Presymptomatic type 1 diabetes was classified as stage 1, 2, or 3, as previously advocated.^7,8 Stage 1 type 1 diabetes was defined as 2 or more islet autoantibodies and normal glucose tolerance based on OGTT results. Stage 2 was defined as 2 or more islet autoantibodies accompanied by dysglycemia (fasting plasma glucose of 110-125 mg/dL or impaired 2-hour plasma glucose of 140-199 mg/dL and/or plasma glucose ≥200 mg/dL at intermediate time points [30, 60, 90 minutes]) based on OGTT results.⁸ Stage 3 type 1 diabetes was defined by the following American Diabetes Association criteria: fasting plasma glucose at least 126 mg/dL or a 2-hour plasma glucose of at least 200 mg/dL based on OGTT results or hemoglobin A_1C greater than 6.5% or, in children with classic symptoms of hyperglycemia, a random plasma glucose at least 200 mg/dL (in the absence of unequivocal hyperglycemia, the first 3 criteria required confirmation by repeat testing).⁸ Stages 1 and 2 were diagnosed at clinical referral centers and stage 3 was diagnosed at referral centers or by the local pediatrician. Families of children who withdrew from the study or refused to allow OGTTs were contacted by telephone and asked if the child had developed diabetes. If participants were lost to follow-up, the local DiMelli register cohort study¹⁴ was used to obtain information on diabetes development of former study participants. Secondary outcomes of the study were the frequency of diabetic ketoacidosis and an assessment of parental psychological stress associated with a diagnosis of presymptomatic type 1 diabetes.

Statistical Analysis

Data were analyzed using SAS version 9.4 (SAS Institute) and R version 3.5.3 (R Foundation), using the survival and survminer packages. Prior to analysis, the body mass index (BMI) was transformed to a standardized BMI based on SD scores using World Health Organization reference values.²¹ Standardized BMI values less than −5 or greater than 5 were deemed implausible and were excluded. Overweight was defined as standardized BMI of 1 to 2 and obesity as BMI greater than 2, according to World Health Organization recommendations. Data were considered missing at random after examining relative frequency between categories of all analyzed variables and performing sensitivity analyses excluding subgroups with the highest proportion of missing values. Variables with missing values in more than 10% of children were imputed using regression predictions for deterministic imputation.²² For all other variables, missing values were not included in analyses.

Frequencies and relative risks (RRs) were calculated and are presented with 95% CIs. Exploratory bivariable analyses were performed using Pearson χ² tests or Fisher exact tests to identify factors associated with increased RR for presymptomatic type 1 diabetes. Factors with significantly increased RR were tested in a multivariable generalized regression model adjusted for sex. At a prevalence of 0.3%, the study had 80% power to detect an uncorrected significant association at RRs greater than 2.5 for presymptomatic type 1 diabetes for categorical variables with frequencies between 3.4% and 96.6% (obesity), greater than 2.0 for variables with frequencies between 7% and 93% (region), and greater than 1.5 for variables with frequencies between 23% and 77%.

Progression to higher stages of type 1 diabetes was analyzed using Kaplan-Meier plots. The time to event was calculated from the age of screening to the age at diagnosis of stage 3 type 1 diabetes or the age at last follow-up. Time-to-event analyses were also used to examine progression from stage 1 to stage 3 and from stage 2 to stage 3 and, in these instances, follow-up was calculated from the age of metabolic staging. Associations between risk of progression to higher stages of type 1 diabetes and variables were analyzed using bivariable Cox proportional hazards regression models. A sensitivity analysis that excluded the 98 children who participated in the intervention study was performed using a bivariable Cox proportional hazards regression model. The proportional hazards assumption was tested using the Schoenfeld residuals method and no violation was detected. The area under the curve of the OGTT results was calculated as previously described.²³ Genetic risk scores, area under the curve of OGTT results, and 60-minute OGTT results were categorized in tertiles. PHQ-9 psychological scores were compared between groups using the Mann-Whitney U test or Wilcoxon signed rank test. No adjustment was made for multiple comparisons, so analyses should be interpreted as exploratory. Two-sided P values less than .05 were considered statistically significant.

Results

A total of 682 of 1027 (66.4%) primary care pediatricians in Bavaria enrolled 90 632 children (median [interquartile range {IQR}] age, 3.1 [2.1-4.2] years; 48.5% girls) in the study (Table and Figure 1). Approximately 420 000 eligible children aged 1.75 to 5.99 years lived in the respective area during the study period. Compared with a Bavarian preschool population survey of 108 637 children in 2014 to 2015,²⁴ the children in this study were not significantly different in the frequency of boys (51.5% vs 51.3%) or obesity (3.2% vs 3.1%), as defined by German reference values. Sufficient blood for screening was collected from 90 205 children (99.5%; Figure 1).

Table. Description of the Study Population of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany (N = 90 632).

Category	No. (%)	Presymptomatic Type 1 Diabetes
Category	No. (%)	No.	% (95% CI)
Sex	(n = 88 214)
Female	42 815 (48.5)	127	0.30 (0.25-0.35)
Male	45 399 (51.5)	153	0.34 (0.29-0.40)
Age	(n = 90 388)
<3	36 900 (40.8)	82	0.22 (0.18-0.28)
3-3.99	20 909 (23.1)	57	0.27 (0.21-0.36)
4-4.99	15 153 (16.8)	63	0.42 (0.32-0.54)
5-5.99	17 426 (19.3)	78	0.45 (0.36-0.56)
First-degree relative with type 1 diabetes	(n = 88 253)
Yes	3004 (3.4)	32	1.07 (0.74-1.52)
No	85 249 (96.6)	248	0.29 (0.26-0.33)
BMI^a	(n = 87 766)
Normal	72 216 (82.3)	226	0.31 (0.27-0.36)
Overweight	11 968 (13.6)	35	0.29 (0.21-0.41)
Obese	3582 (4.1)	19	0.54 (0.33-0.85)
Region^b	(n = 90 632)
Lower Bavaria	4648 (5.1)	12	0.26 (0.14-0.46)
Upper Bavaria	36 139 (39.9)	108	0.30 (0.25-0.36)
Swabia	13 836 (15.3)	54	0.39 (0.30-0.51)
Upper Palatinate	6365 (7.0)	18	0.28 (0.17-0.46)
Middle Franconia	15 627 (17.2)	45	0.29 (0.21-0.39)
Upper Franconia	7018 (7.7)	25	0.36 (0.24-0.53)
Lower Franconia	6999 (7.7)	18	0.26 (0.16-0.41)

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^{^a}

Standardized body mass index (BMI) was calculated using the World Health Organization Child Growth Standards based on height and weight and age.²¹ The 3 central parameters for the calculation are the Box-Cox power transformation (L), the median (M), and the variation coefficient (S). The formula for calculation is [(BMI/M)^L − 1] / (L × S). Normal BMI is defined as a standardized value <1, overweight as 1 to 2, and obese as >2. There were 17 075 missing BMI values before imputation and for 2531 of these children, imputation of standardized BMI values was not possible due to missing sex or age.

^{^b}

See eFigure 1 in the Supplement for a map of the regions.

Prevalence of Presymptomatic Type 1 Diabetes

In total, 280 of 90 632 (0.31% [95% CI, 0.27-0.35]) children were diagnosed with presymptomatic type 1 diabetes. This included 19 children whose screening sample results were positive for 2 or more islet autoantibodies and were diagnosed with stage 3 type 1 diabetes by the pediatrician before collection of the second blood sample. There were 120 children with 2 antibodies, 91 with 3 antibodies, and 69 with 4 antibodies (eTable 1 in the Supplement). The median (IQR) genetic risk score in 188 of 280 children (67%) was 12.9 (11.7-13.9). Thirteen children had screening sample results positive for islet antibodies but did not provide a second sample to complete the diagnosis. The other 89 912 children had screening sample results negative for multiple islet autoantibodies. Of those children with screening sample results negative for islet autoantibodies, 160 (median [IQR] age, 4.6 [3.3-5.6] years; 78 [48.8%] girls) were included in the study as control individuals.

The unadjusted associations with presymptomatic type 1 diabetes are presented in eFigure 2 in the Supplement and the adjusted associations are shown in Figure 2. The adjusted RR for presymptomatic type 1 diabetes was greater in children with a first-degree relative with type 1 diabetes (RR, 3.69 [95% CI, 2.51-5.24]; P < .001), in obese children (RR, 1.77 [95% CI, 1.08-2.71]; P = .01), in children aged 4.00 to 4.99 years (RR, 1.50 [95% CI, 1.07-2.11]; P = .02), and in children aged 5.00 to 5.99 years (RR, 1.86 [95% CI, 1.37-2.53]; P < .001) (Figure 2). There were no differences in the prevalence of presymptomatic type 1 diabetes between girls and boys or between the 7 regions of Bavaria.

Staging and Follow-up of Children With Presymptomatic Type 1 Diabetes

A total of 220 of 261 children (84.3%) with presymptomatic type 1 diabetes who had not already been diagnosed with stage 3 type 1 diabetes participated in metabolic staging, the diabetes education program, and follow-up at clinical referral centers. After staging, 196 of 90 632 children (0.22%) were diagnosed with stage 1 type 1 diabetes, 17 of 90 632 (0.02%) with stage 2 type 1 diabetes, and 26 of 90 632 (0.03%) with stage 3 type 1 diabetes (Figure 1). Another 36 children progressed to stage 3 and 25 progressed to stage 2 during follow-up (median [IQR] follow-up time of all children with presymptomatic type 1 diabetes, 2.4 [1.0-3.2] years). Stage 2 was detected prior to the diagnosis of stage 3 in 12 of these 36 children. Of the 196 children with stage 1 type 1 diabetes at the time of metabolic staging, 98 (50%) participated in the mechanistic intervention study.

The cumulative risk of developing stage 3 type 1 diabetes for the 280 children with presymptomatic type 1 diabetes was 24.9% (95% CI, 18.5%-30.7%; 54 cases) over 3 years of follow-up, with an annualized risk of 9.0% (Figure 3A and eFigure 3 in the Supplement). There was a significantly greater risk associated with children who had 4 autoantibodies vs 2 autoantibodies (hazard ratio [HR], 1.85 [95% CI, 1.03-3.32]; P = .04) and with children whose screening results were positive for IA-2A (HR, 3.4 [95% CI, 1.81-6.39]; P < .001), and a significantly lower risk associated with children whose screening results were positive for GADA (HR, 0.43; [95% CI, 0.25-0.75]; P = .003; Figure 3B). The lower risk associated with GADA was observed in children with 2 autoantibodies and 3 autoantibodies (eFigure 4 in the Supplement). Sex, age, BMI, first-degree relative with type 1 diabetes, and genetic risk scores were not significantly associated with the development of stage 3 type 1 diabetes. Risk (24.7%) and risk factors were similar in a sensitivity analysis that excluded the 98 children who participated in the intervention study (eFigure 5 in the Supplement).

Figure 3. — A. The curve is truncated at 3.57 years of follow-up from screening as the number at risk reaches 15% (n = 42) of the included children. The median (interquartile range) observation time is 2.4 (1.0-3.3) years. GADA indicates glutamic acid decarboxylase autoantibody; IA-2A, islet antigen 2 autoantibody; IAA, insulin autoantibody; ZnT8A, zinc transporter 8 autoantibody.

Among 196 children with stage 1 type 1 diabetes, the risk of progression to stage 2 or 3 was 28.7% (95% CI, 21.0%-35.6%; 45 cases) by 3 years of follow-up, with an annualized risk of 10.6% (eFigures 6 and 7 in the Supplement). Factors significantly associated with disease stage progression were obesity, 4 autoantibodies, IA-2A, glycated hemoglobin of at least 5.7%, area under the curve of OGTT results, and 60-minute OGTT results. Sex, age, family history of type 1 diabetes, and genetic risk scores were not significantly associated with risk of progression. Loss of islet autoantibody positivity was observed in 1 child during follow-up.

A diagnosis of stage 3 type 1 diabetes was reported in 4 of the 89 912 children who did not have presymptomatic type 1 diabetes; at diagnosis, 3 had 1 autoantibody and 1 had 0 autoantibodies. In total, 66 known cases of stage 3 type 1 diabetes were observed during the 244 069 follow-up years of all children screened in the study, yielding a rate of 27 per 100 000 years (95% CI, 21.3-34.4). The sensitivity of a presymptomatic diagnosis for identifying stage 3 type 1 diabetes within 3 years of follow-up from screening was 54 of 56 (96.4%) and the specificity was 90 350 of 90 576 (99.8%).

Diabetes Severity and Psychological Stress Associated With Presymptomatic Type 1 Diabetes

Of the 62 children with presymptomatic type 1 diabetes who developed stage 3 type 1 diabetes, 2 (3.2%) had a laboratory diagnosis of mild (pH of 7.28) or moderate (pH of 7.14) diabetic ketoacidosis without clinical symptoms, and 60 (96.8%) did not have diabetic ketoacidosis. The children with diabetic ketoacidosis were hospitalized but did not require treatment in an intensive care unit. The family of 1 of these children declined to participate in the educational and staging program.

PHQ-9 questionnaires were administered to 432 parents at staging (76% response rate), 314 at 6 months (61% response rate), and 256 at 12 months (58% response rate). Median [IQR] PHQ-9 scores were significantly greater at the time of metabolic staging in mothers of children with presymptomatic type 1 diabetes than scores in mothers of children with negative results for islet autoantibodies in the control cohort (3 [1-7] vs 2 [1-4]; P = .002) (Figure 4 and eTable 2 in the Supplement). The scores were not significantly greater in fathers of children with presymptomatic type 1 diabetes vs fathers of children without autoantibodies (median [IQR], 2 [0-4] vs 2 [1-4]). The scores declined significantly over time in both in mothers (median [IQR] score at 12 months, 2 [0-4]; P < .001) and fathers (median [IQR] score at 12 months, 0 [0-2]; P < .001) of children with presymptomatic type 1 diabetes. The median (IQR) PHQ-9 score at metabolic staging was lower than in 169 mothers (5 [3-8]; P < .001) and 95 fathers (4 [2-7]; P < .001) of children diagnosed with type 1 diabetes without prior screening in the DiMelli study.¹⁴

Figure 4. — Violin plots of Patient Health Questionnaire 9 (PHQ-9) depression scores of mothers and fathers of children with presymptomatic type 1 diabetes. Scores were assessed at the metabolic staging visit and at 6 and 12 months after diagnosis. Scores for children in the control cohort and children with symptomatic type 1 diabetes enrolled in the DiMelli study¹⁴ are also shown. Scores range from 0 to 27 and were interpreted as no to minimal depression if less than or equal to 4 and as severe depression if greater than 20. The violin plots display the density of PHQ-9 scores. The box plots display the median and interquartile range and extend to the upper and lower adjacent values.

Discussion

Public health screening found a 0.31% prevalence of presymptomatic type 1 diabetes in children aged 2 to 5 years, including 0.02% of children with multiple islet autoantibodies and dysglycemia (stage 2 type 1 diabetes) and 0.03% with previously undiagnosed stage 3 type 1 diabetes.

To our knowledge, this is the first study to introduce preschool screening for autoimmune disease in the general population. Smaller studies have performed screening of school-age children.^25,26,27 The strengths of the current study include the introduction of screening in routine pediatric health care, the large number of children screened, inclusion of children without genetic preselection, systematic follow-up of the majority of children diagnosed with presymptomatic type 1 diabetes and their families, and inclusion of a control cohort of children whose screening results were negative for autoantibodies.

Screening of more than 90 000 children in 4 years was achieved in a period when there was no known effective prevention therapy. The success of a single 14-day course of teplizumab in delaying the progression to stage 3 type 1 diabetes²⁸ may further increase the acceptance of screening. This study identified children with stage 2 diabetes who may benefit from this treatment and shows how primary care screening could rapidly disseminate access to therapies.

A potential clinical benefit of identifying type 1 diabetes in a presymptomatic stage may be a reduction in the prevalence of diabetic ketoacidosis, which is associated with detrimental neurocognitive outcomes, poor long-term glycemic control, and increased medical costs.^5,29,30 Previous studies reported a low frequency of diabetic ketoacidosis at the diagnosis of type 1 diabetes in genetically at-risk individuals with islet autoantibodies in longitudinal natural history studies.^4,31 In this study, the prevalence of diabetic ketoacidosis was less than 5%. The previously reported prevalence in unscreened children is more than 20% in Germany² and 40% in the United States.³²

The transient association with increased psychological stress scores observed in the mothers of children diagnosed with presymptomatic type 1 diabetes in this study is consistent with the findings of children diagnosed in natural history studies, which provided regular care of children whose test results were positive for autoantibodies.^33,34 Also consistent in all studies is that the distress reported by the families of children diagnosed with presymptomatic type 1 diabetes was low or moderate in the majority of families. Therefore, with an appropriate education and care program, islet autoantibody screening and a presymptomatic diagnosis of type 1 diabetes appear unlikely to lead to a level of parental psychological stress that was observed in families of children diagnosed with clinical type 1 diabetes.

A diagnosis of type 1 diabetes in presymptomatic stages should be associated with an elevated risk for progression to stage 3 type 1 diabetes. The 9% annualized risk for progression observed in this study is similar to the 11% annualized risk found in children with multiple islet autoantibodies who have a family history of type 1 diabetes or a genetically defined increased susceptibility.⁶ Although it is possible that a few children may not progress to overt diabetes, it appears that young children with multiple islet autoantibodies identified by the screening strategy in the current study have a genetic susceptibility profile similar to that of children with diagnosed type 1 diabetes, and many are already at an advanced presymptomatic stage. Additional selection of children who rapidly progress to stage 3 type 1 diabetes might be achieved by targeting children with IA-2A and children with elevated hemoglobin A_1c or glucose levels.^35,36,37 Genetic risk was not associated with increased disease stage progression in children with presymptomatic type 1 diabetes, and their genetic risk score (12.9) was similar to that of children with type 1 diabetes in the DiMelli study¹⁴ (median [IQR], 13.1 [12.2-14.1]) and greater than that of the 20 668 infants from the general Bavarian population included in the Freder1k study³⁸ (median [IQR], 10.6 [9.7-11.6]). Therefore, a priori genetic selection is unlikely to substantially increase specificity.

The screening strategy was based on islet autoantibody incidence data, which indicated a peak incidence of islet autoantibodies in the first 3 years of life.^10,39 Screening was restricted to a single point between 2 and 5 years of age. Screening costs were kept low by using a relatively inexpensive and sensitive prescreening method that could exclude 98% of children from more expensive measurements. Further cost reductions could be achieved by screening with point-of-care islet autoantibody tests if they become available. Although the study did not include a measure of type 1 diabetes ascertainment, the screening strategy to identify children with multiple islet autoantibodies identified more than 95% of the reported cases of stage 3 type 1 diabetes among all screened children. These data suggest that public health screening had a high sensitivity for identifying future cases of childhood type 1 diabetes. New cases of presymptomatic type 1 diabetes occur after 5 years of age, but an age-based analysis of the remaining risk for multiple islet autoantibodies in prospectively followed genetically at-risk children suggests that the risk is reduced after the preschool period and may not be large enough to warrant a second screen in adolescence.⁴⁰

Limitations

This study has several limitations. First, although it provides information on evaluating whether public health screening might eventually be of value in some populations, a randomized clinical trial would be required to assess whether screening reduces diabetic ketoacidosis or affects psychological stress. Such a trial should include measures of the number of families who refuse participation in screening and the cost-effectiveness of screening. Second, participation in the study was voluntary and screening was performed in a minority of the eligible children. Although the sex and BMI distribution of the screened children was not significantly different from that of all children of similar age living in Bavaria, the findings may not be representative of all children in Bavaria, other populations, or in children younger than 2 years and older than 5 years. Third, the offer to enroll in an intervention study to children with stage 1 presymptomatic type 1 diabetes may have influenced participation in the metabolic staging and education program and the psychological stress of the families. A sensitivity analysis without the children who participated in the 12-month intervention suggested that the findings on disease progression during follow-up were not substantially changed by the relatively short treatment period in a minority of the participants. Fourth, BMI was missing in more than 10% of participants. Missing values were assessed to be missing at random, but associations observed with BMI should be interpreted with caution. Fifth, 24% to 42% of parents did not return psychological stress questionnaires. More accurate assessment might be achieved if questionnaires could be administered at time points before and after notification of a diagnosis in the setting of a randomized trial.

Conclusions

Among children aged 2 to 5 years in Bavaria, Germany, a program of primary care–based screening demonstrated an islet autoantibody prevalence of 0.31%. These findings may inform considerations of population-based screening of children for islet autoantibodies.

Supplement.

List of Fr1da Study Group

eFigure 1. Regions of Bavaria Participating in the Fr1da Study

eFigure 2. Violin and Box Plots of Type 1 Diabetes Genetic Risk Scores in the Fr1da, DiMelli, and Freder1k Studies

eFigure 3. Unadjusted Relative Risk Ratios for Presymptomatic Type 1 Diabetes

eFigure 4. Risk of Developing Stage 3 Type 1 diabetes

eFigure 5. Risk of Stage 3 Type 1 Diabetes According to GAD Autoantibody Status

eFigure 6. Risk of Stage 3 Type 1 Diabetes with Censoring of Children who Participated in the Fr1da Intervention Trial

eFigure 7. Risk of Developing Stage 2 or Stage 3 Type 1 Diabetes

eFigure 8. Risk of developing Stage 2 or Stage 3 Type 1 Diabetes with Censoring of Children who Participated in the Fr1da Intervention Trial

eTable 1. Combinations of Autoantibodies in Fr1da Children with Presymptomatic Type 1 Diabetes

eTable 2. Patient Health Questionnaire-9 Depression Scores of Mothers and Fathers from Children with Presymptomatic Type 1 Diabetes, Children in the Fr1da Control Cohort, and Children with Symptomatic New-Onset Type 1 Diabetes in the DiMelli Cohort

Click here for additional data file.^{(7.2MB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

List of Fr1da Study Group

eFigure 1. Regions of Bavaria Participating in the Fr1da Study

eFigure 2. Violin and Box Plots of Type 1 Diabetes Genetic Risk Scores in the Fr1da, DiMelli, and Freder1k Studies

eFigure 3. Unadjusted Relative Risk Ratios for Presymptomatic Type 1 Diabetes

eFigure 4. Risk of Developing Stage 3 Type 1 diabetes

eFigure 5. Risk of Stage 3 Type 1 Diabetes According to GAD Autoantibody Status

eFigure 6. Risk of Stage 3 Type 1 Diabetes with Censoring of Children who Participated in the Fr1da Intervention Trial

eFigure 7. Risk of Developing Stage 2 or Stage 3 Type 1 Diabetes

eFigure 8. Risk of developing Stage 2 or Stage 3 Type 1 Diabetes with Censoring of Children who Participated in the Fr1da Intervention Trial

eTable 1. Combinations of Autoantibodies in Fr1da Children with Presymptomatic Type 1 Diabetes

Click here for additional data file.^{(7.2MB, pdf)}

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PERMALINK

Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany

Anette-Gabriele Ziegler, MD

Kerstin Kick, PhD

Ezio Bonifacio, PhD

Florian Haupt, PhD

Markus Hippich, PhD

Desiree Dunstheimer, MD

Martin Lang, MD

Otto Laub, MD

Katharina Warncke, MD

Karin Lange, PhD

Robin Assfalg, PhD

Manja Jolink, MSc

Christiane Winkler, PhD

Peter Achenbach, MD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Design

Assessments

Outcome Definitions

Statistical Analysis

Results

Table. Description of the Study Population of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany (N = 90 632).

Figure 1. Flow of Participants in a Study of the Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany.

Prevalence of Presymptomatic Type 1 Diabetes

Figure 2. Multivariable Analysis of Relative Risks for Presymptomatic Type 1 Diabetes in a Study of the Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany.

Staging and Follow-up of Children With Presymptomatic Type 1 Diabetes

Figure 3. Risk of Stage 3 Type 1 Diabetes in a Study of the Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany.

Diabetes Severity and Psychological Stress Associated With Presymptomatic Type 1 Diabetes

Figure 4. Psychological Stress Scores and Diagnosis of Presymptomatic Type 1 Diabetes in a Study of the Yield of a Public Health Screening of Children for Islet Autoantibodies in Bavaria, Germany.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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