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Browsing by Author "Haller, Michael J."
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Item Clinical trial data validate the C-peptide estimate model in type 1 diabetes(SpringerLink, 2020-04) Wentworth, John M.; Bediaga, Naiara G.; Gitelman, Stephen E.; Evans-Molina, Carmela; Gottlieb, Peter A.; Colman, Peter G.; Haller, Michael J.; Harrison, Leonard C.; Medicine, School of MedicineItem Effect of Metformin Added to Insulin on Glycemic Control Among Overweight/Obese Adolescents With Type 1 Diabetes: A Randomized Clinical Trial(AMA, 2015-12) Libman, Ingrid M.; Miller, Kellee M.; DiMeglio, Linda A.; Bethin, Kathleen E.; Katz, Michelle L.; Shah, Avni; Simmons, Jill H.; Haller, Michael J.; Raman, Sripriya; Tamborlane, William V.; Coffey, Julie K.; Saenz, Ashleigh M.; Beck, Roy W.; Nadeau, Kristen J.; Department of Pediatrics, IU School of MedicineImportance Previous studies assessing the effect of metformin on glycemic control in adolescents with type 1 diabetes have produced inconclusive results. Objective To assess the efficacy and safety of metformin as an adjunct to insulin in treating overweight adolescents with type 1 diabetes. Design, Setting, and Participants Multicenter (26 pediatric endocrinology clinics), double-blind, placebo-controlled randomized clinical trial involving 140 adolescents aged 12.1 to 19.6 years (mean [SD] 15.3 [1.7] years) with mean type 1 diabetes duration 7.0 (3.3) years, mean body mass index (BMI) 94th (4) percentile, mean total daily insulin 1.1 (0.2) U/kg, and mean HbA1c 8.8% (0.7%). Interventions Randomization to receive metformin (n = 71) (≤2000 mg/d) or placebo (n = 69). Main Outcomes and Measures Primary outcome was change in HbA1c from baseline to 26 weeks adjusted for baseline HbA1c. Secondary outcomes included change in blinded continuous glucose monitor indices, total daily insulin, BMI, waist circumference, body composition, blood pressure, and lipids. Results Between October 2013 and February 2014, 140 participants were enrolled. Baseline HbA1c was 8.8% in each group. At 13-week follow-up, reduction in HbA1c was greater with metformin (−0.2%) than placebo (0.1%; mean difference, −0.3% [95% CI, −0.6% to 0.0%]; P = .02). However, this differential effect was not sustained at 26-week follow up when mean change in HbA1c from baseline was 0.2% in each group (mean difference, 0% [95% CI, −0.3% to 0.3%]; P = .92). At 26-week follow-up, total daily insulin per kg of body weight was reduced by at least 25% from baseline among 23% (16) of participants in the metformin group vs 1% (1) of participants in the placebo group (mean difference, 21% [95% CI, 11% to 32%]; P = .003), and 24% (17) of participants in the metformin group and 7% (5) of participants in the placebo group had a reduction in BMI z score of 10% or greater from baseline to 26 weeks (mean difference, 17% [95% CI, 5% to 29%]; P = .01). Gastrointestinal adverse events were reported by more participants in the metformin group than in the placebo group (mean difference, 36% [95% CI, 19% to 51%]; P < .001). Conclusions and Relevance Among overweight adolescents with type 1 diabetes, the addition of metformin to insulin did not improve glycemic control after 6 months. Of multiple secondary end points, findings favored metformin only for insulin dose and measures of adiposity; conversely, use of metformin resulted in an increased risk for gastrointestinal adverse events. These results do not support prescribing metformin to overweight adolescents with type 1 diabetes to improve glycemic control.Item Simplifying prediction of disease progression in pre-symptomatic type 1 diabetes using a single blood sample(SpringerLink, 2021-11) Bediaga, Naiara G.; Li-Wai-Suen, Connie S.N.; Haller, Michael J.; Gitelman, Stephen E.; Evans-Molina, Carmella; Gottlieb, Peter A.; Hippich, Markus; Ziegler, Anette-Gabriele; Lernmark, Ake; DiMeglio, Linda A.; Wherrett, Diane K.; Colman, Peter G.; Harrison, Leonard C.; Wentworth, John M.; Pediatrics, School of MedicineAims/hypothesis: Accurate prediction of disease progression in individuals with pre-symptomatic type 1 diabetes has potential to prevent ketoacidosis and accelerate development of disease-modifying therapies. Current tools for predicting risk require multiple blood samples taken during an OGTT. Our aim was to develop and validate a simpler tool based on a single blood draw. Methods: Models to predict disease progression using a single OGTT time point (0, 30, 60, 90 or 120 min) were developed using TrialNet data collected from relatives with type 1 diabetes and validated in independent populations at high genetic risk of type 1 diabetes (TrialNet, Diabetes Prevention Trial-Type 1, The Environmental Determinants of Diabetes in the Young [1]) and in a general population of Bavarian children who participated in Fr1da. Results: Cox proportional hazards models combining plasma glucose, C-peptide, sex, age, BMI, HbA1c and insulinoma antigen-2 autoantibody status predicted disease progression in all populations. In TrialNet, the AUC for receiver operating characteristic curves for models named M60, M90 and M120, based on sampling at 60, 90 and 120 min, was 0.760, 0.761 and 0.745, respectively. These were not significantly different from the AUC of 0.760 for the gold standard Diabetes Prevention Trial Risk Score, which requires five OGTT blood samples. In TEDDY, where only 120 min blood sampling had been performed, the M120 AUC was 0.865. In Fr1da, the M120 AUC of 0.742 was significantly greater than the M60 AUC of 0.615. Conclusions/interpretation: Prediction models based on a single OGTT blood draw accurately predict disease progression from stage 1 or 2 to stage 3 type 1 diabetes. The operational simplicity of M120, its validity across different at-risk populations and the requirement for 120 min sampling to stage type 1 diabetes suggest M120 could be readily applied to decrease the cost and complexity of risk stratification.