دورية أكاديمية
Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals.
العنوان: | Comparisons of Metabolic Measures to Predict T1D vs Detect a Preventive Treatment Effect in High-Risk Individuals. |
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المؤلفون: | Sims EK; Department of Pediatrics, Wells Center for Pediatric Research, Pediatric Endocrinology and Diabetology, and the Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN 46202, USA., Cuthbertson D; Department of Pediatrics, Pediatrics Epidemiology Center, Morsani College of Medicine, University of South Florida, Tampa, FL 33606, USA., Jacobsen L; Department of Pediatrics, University of Florida College of Medicine, Gainesville, FL 32610, USA., Ismail HM; Department of Pediatrics, Wells Center for Pediatric Research, Pediatric Endocrinology and Diabetology, and the Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine, Indianapolis, IN 46202, USA., Nathan BM; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55455, USA., Herold KC; Division of Diabetes and Endocrinology, Yale University, New Haven, CT 06520, USA.; Departments of Immunobiology and Internal Medicine, Yale University, New Haven, CT 06520, USA., Redondo MJ; Texas Children's Hospital, Baylor College of Medicine, Houston, TX 77030, USA., Sosenko J; Department of Medicine, Division of Diabetes, Metabolism, and Endocrinology, University of Miami, Miami, FL 33136, USA.; Diabetes Research Institute, University of Miami, Miami, FL 33136, USA. |
المصدر: | The Journal of clinical endocrinology and metabolism [J Clin Endocrinol Metab] 2024 Jul 12; Vol. 109 (8), pp. 2116-2123. |
نوع المنشور: | Journal Article; Randomized Controlled Trial; Comparative Study; Multicenter Study |
اللغة: | English |
بيانات الدورية: | Publisher: Oxford University Press Country of Publication: United States NLM ID: 0375362 Publication Model: Print Cited Medium: Internet ISSN: 1945-7197 (Electronic) Linking ISSN: 0021972X NLM ISO Abbreviation: J Clin Endocrinol Metab Subsets: MEDLINE |
أسماء مطبوعة: | Publication: 2017- : New York : Oxford University Press Original Publication: Springfield, Ill. : Charles C. Thomas |
مواضيع طبية MeSH: | Diabetes Mellitus, Type 1*/drug therapy , Diabetes Mellitus, Type 1*/metabolism , Antibodies, Monoclonal, Humanized*/therapeutic use , Antibodies, Monoclonal, Humanized*/administration & dosage , C-Peptide*/blood , Blood Glucose*/analysis , Blood Glucose*/metabolism, Humans ; Male ; Female ; Adult ; Treatment Outcome ; Middle Aged ; Young Adult ; Prognosis ; Biomarkers/analysis |
مستخلص: | 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. (© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society.) |
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معلومات مُعتمدة: | R01 DK121843 United States DK NIDDK NIH HHS; United States NH NIH HHS; United States DK NIDDK NIH HHS; National Institute of Allergy and Infectious Diseases; U01 DK061010 United States DK NIDDK NIH HHS; 2021258 United States DDCF Doris Duke Charitable Foundation; 62288 John Templeton Foundation |
فهرسة مساهمة: | Keywords: C-peptide; endpoint; glucose; insulin secretion; prediction; prevention; trial; type 1 diabetes |
المشرفين على المادة: | 0 (Antibodies, Monoclonal, Humanized) 0 (C-Peptide) 0 (Blood Glucose) S4M959U2IJ (teplizumab) 0 (Biomarkers) |
تواريخ الأحداث: | Date Created: 20240124 Date Completed: 20240712 Latest Revision: 20240714 |
رمز التحديث: | 20240714 |
مُعرف محوري في PubMed: | PMC11244203 |
DOI: | 10.1210/clinem/dgae048 |
PMID: | 38267821 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1945-7197 |
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DOI: | 10.1210/clinem/dgae048 |