Browsing by Subject "Type 1"

Now showing 1 - 3 of 3
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    Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals
    (Oxford University Press, 2024) Sims, Emily K.; Cuthbertson, David; Jacobsen, Laura; Ismail, Heba M.; Nathan, Brandon M.; Herold, Kevan C.; Redondo, Maria J.; Sosenko, Jay; Pediatrics, School of Medicine
    Context: Metabolic measures are frequently used to predict type 1 diabetes (T1D) and to understand effects of disease-modifying therapies. Objective: Compare metabolic endpoints for their ability to detect preventive treatment effects and predict T1D. Methods: Six-month changes in metabolic endpoints were assessed for (1) detecting treatment effects by comparing placebo and treatment arms from the randomized controlled teplizumab prevention trial, a multicenter clinical trial investigating 14-day intravenous teplizumab infusion and (2) predicting T1D in the TrialNet Pathway to Prevention natural history study. For each metabolic measure, t-Values from t tests for detecting a treatment effect were compared with chi-square values from proportional hazards regression for predicting T1D. Participants in the teplizumab prevention trial and participants in the Pathway to Prevention study selected with the same inclusion criteria used for the teplizumab trial were studied. Results: Six-month changes in glucose-based endpoints predicted diabetes better than C-peptide-based endpoints, yet the latter were better at detecting a teplizumab effect. Combined measures of glucose and C-peptide were more balanced than measures of glucose alone or C-peptide alone for predicting diabetes and detecting a teplizumab effect. Conclusion: The capacity of a metabolic endpoint to detect a treatment effect does not necessarily correspond to its accuracy for predicting T1D. However, combined glucose and C-peptide endpoints appear to be effective for both predicting diabetes and detecting a response to immunotherapy. These findings suggest that combined glucose and C-peptide endpoints should be incorporated into the design of future T1D prevention trials.
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    ISPAD Clinical Practice Consensus Guidelines 2022: Psychological care of children, adolescents and young adults with diabetes
    (Wiley, 2022) de Wit, Maartje; Gajewska, Katarzyna A.; Goethals, Eveline R.; McDarby, Vincent; Zhao, Xiaolei; Hapunda, Given; Delamater, Alan M.; DiMeglio, Linda A.; Pediatrics, School of Medicine
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    Sources and Valence of Information Impacting Parents' Decisions to Use Diabetes Technologies in Young Children <8 Years Old with Type 1 Diabetes
    (Mary Ann Liebert, Inc., 2020-09) Commissariat, Persis V.; Whitehouse, Amanda L.; Hilliard, Marisa E.; Miller, Kellee M.; Harrington, Kara R.; Levy, Wendy; DeSalvo, Daniel J.; Van Name, Michelle A.; Anderson, Barbara J.; Tamborlane, William V.; DiMeglio, Linda A.; Laffel, Lori M.; Pediatrics, School of Medicine
    There are multiple information sources available to assist families in learning about rapidly advancing diabetes technologies as care options for their children. This study explored where and from whom families of young children with type 1 diabetes get information about diabetes technologies and the valence (positive vs. negative) of that information. Semi-structured interviews were conducted with parents (86% mothers) of 79 youth <8 years old with type 1 diabetes for ≥6 months, ([mean ± standard deviation] age 5.2 ± 1.5 years, diabetes duration 2.4 ± 1.3 years, 77% white, A1c 63 ± 10 mmol/mol [7.9 ± 0.9%], 66% pump-treated, 58% using continuous glucose monitors [CGMs]). Interviews were transcribed and underwent content analysis to derive central themes. Most parents reported learning about new technologies from three direct sources: diabetes care providers, people with diabetes, and caregivers of children with diabetes. Parents also cited three indirect sources of information: online forums, publications, and diabetes-specific conferences. Parents reported hearing primarily positive things about technologies. Families not using pump and/or CGM noted reluctance to use technology due to family-specific concerns (e.g., cost, child's unwillingness to wear device) rather than information from outside sources. In this subset of parents, many still expressed willingness to initiate use once family-specific concerns were resolved. Parents of young children received largely positive information about diabetes technologies, primarily from health care providers and others familiar with using devices personally or for their children. To maximize diabetes technology use in young children, it is incumbent upon providers to ensure families receive balanced realistic information about benefits and barriers.