PETER CALHOUN, CHARLEY SPANBAUER, ANDREA STECK, BRIGITTE I. FROHNERT, MARK A. HERMAN, BART KEYMEULEN, RIITTA VEIJOLA, JORMA TOPPARI, ASTER DESOUTER, FRANS K. GORUS, MARK A. ATKINSON, DARRELL M. WILSON, SUSAN PIETROPAOLO, ROY BECK
{"title":"74-OR: 美国糖尿病协会主席精选摘要：从五项研究中得出的 CGM 指标可识别出 1 型糖尿病 (T1D) 发病风险高的参与者","authors":"PETER CALHOUN, CHARLEY SPANBAUER, ANDREA STECK, BRIGITTE I. FROHNERT, MARK A. HERMAN, BART KEYMEULEN, RIITTA VEIJOLA, JORMA TOPPARI, ASTER DESOUTER, FRANS K. GORUS, MARK A. ATKINSON, DARRELL M. WILSON, SUSAN PIETROPAOLO, ROY BECK","doi":"10.2337/db24-74-or","DOIUrl":null,"url":null,"abstract":"Introduction & Objective: We assessed if continuous glucose monitoring (CGM) metrics accurately identify imminent stage 3 T1D diagnosis in those with islet autoantibody (IAb) positivity. Methods: Baseline CGM data were collected from participants with ≥1 positive IAb type from five studies: ASK (N=79), BDR (N=22), DAISY (N=18), DIPP (N=8), and TrialNet (N=91). Median follow-up time was 2.6 y (IQR: 1.5 to 3.6 y). A CGM and baseline factor model and a baseline-only model were compared. CGM model classified participants as low (N=97), medium (N=74), or high (N=47) risk of stage 3 T1D based on <10%, 10-<30%, and ≥30% probability by year 2. Results: CGM model found % time >140 mg/dL (TA140), area under the curve 140 mg/dL (AUC140), glucose SD, sex, first degree relative, IA2A, and GADA status were more predictive of T1D progression compared to the baseline-only model (C-statistic: 0.76 vs. 0.62). The probability of developing T1D by 2 years was 4%, 17%, and 51% in the low, medium, and high risk groups (Figure). Compared to low risk participants, high risk participants had higher TA140 (median: 10% vs 2%), AUC140 (mean: 2.9 vs. 1.1 mg/dL), and glucose SD (mean: 24 vs. 18 mg/dL). Conclusion: CGM metrics can help predict T1D progression and classify participant’s risk of impending T1D diagnosis. CGM can be used to better monitor the risk of T1D progression and define eligibility for potential prevention trials. Disclosure P. Calhoun: None. C. Spanbauer: None. A. Steck: None. B.I. Frohnert: None. M.A. Herman: Research Support; Eli Lilly and Company. B. Keymeulen: None. R. Veijola: Advisory Panel; Sanofi. J. Toppari: None. A. Desouter: None. F.K. Gorus: None. M.A. Atkinson: None. D.M. Wilson: Advisory Panel; Enable Biosciences, Inc. S. Pietropaolo: None. R. Beck: Consultant; Insulet Corporation. Research Support; Insulet Corporation. Consultant; Tandem Diabetes Care, Inc. Research Support; Tandem Diabetes Care, Inc. Consultant; Beta Bionics, Inc. Research Support; Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc. Consultant; Novo Nordisk. Research Support; Novo Nordisk, Eli Lilly and Company. Consultant; embecta, Vertex Pharmaceuticals Incorporated, Hagar, Ypsomed AG, Sanofi, Zucara Therapeutics, Sequel. Funding JDRF","PeriodicalId":11376,"journal":{"name":"Diabetes","volume":"5 1","pages":""},"PeriodicalIF":6.2000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"74-OR: ADA Presidents' Select Abstract: CGM Metrics from Five Studies Identify Participants at High Risk of Imminent Type 1 Diabetes (T1D) Development\",\"authors\":\"PETER CALHOUN, CHARLEY SPANBAUER, ANDREA STECK, BRIGITTE I. FROHNERT, MARK A. HERMAN, BART KEYMEULEN, RIITTA VEIJOLA, JORMA TOPPARI, ASTER DESOUTER, FRANS K. GORUS, MARK A. ATKINSON, DARRELL M. WILSON, SUSAN PIETROPAOLO, ROY BECK\",\"doi\":\"10.2337/db24-74-or\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction & Objective: We assessed if continuous glucose monitoring (CGM) metrics accurately identify imminent stage 3 T1D diagnosis in those with islet autoantibody (IAb) positivity. Methods: Baseline CGM data were collected from participants with ≥1 positive IAb type from five studies: ASK (N=79), BDR (N=22), DAISY (N=18), DIPP (N=8), and TrialNet (N=91). Median follow-up time was 2.6 y (IQR: 1.5 to 3.6 y). A CGM and baseline factor model and a baseline-only model were compared. CGM model classified participants as low (N=97), medium (N=74), or high (N=47) risk of stage 3 T1D based on <10%, 10-<30%, and ≥30% probability by year 2. Results: CGM model found % time >140 mg/dL (TA140), area under the curve 140 mg/dL (AUC140), glucose SD, sex, first degree relative, IA2A, and GADA status were more predictive of T1D progression compared to the baseline-only model (C-statistic: 0.76 vs. 0.62). The probability of developing T1D by 2 years was 4%, 17%, and 51% in the low, medium, and high risk groups (Figure). Compared to low risk participants, high risk participants had higher TA140 (median: 10% vs 2%), AUC140 (mean: 2.9 vs. 1.1 mg/dL), and glucose SD (mean: 24 vs. 18 mg/dL). Conclusion: CGM metrics can help predict T1D progression and classify participant’s risk of impending T1D diagnosis. CGM can be used to better monitor the risk of T1D progression and define eligibility for potential prevention trials. Disclosure P. Calhoun: None. C. Spanbauer: None. A. Steck: None. B.I. Frohnert: None. M.A. Herman: Research Support; Eli Lilly and Company. B. Keymeulen: None. R. Veijola: Advisory Panel; Sanofi. J. Toppari: None. A. Desouter: None. F.K. Gorus: None. M.A. Atkinson: None. D.M. Wilson: Advisory Panel; Enable Biosciences, Inc. S. Pietropaolo: None. R. Beck: Consultant; Insulet Corporation. Research Support; Insulet Corporation. Consultant; Tandem Diabetes Care, Inc. Research Support; Tandem Diabetes Care, Inc. Consultant; Beta Bionics, Inc. 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74-OR: ADA Presidents' Select Abstract: CGM Metrics from Five Studies Identify Participants at High Risk of Imminent Type 1 Diabetes (T1D) Development
Introduction & Objective: We assessed if continuous glucose monitoring (CGM) metrics accurately identify imminent stage 3 T1D diagnosis in those with islet autoantibody (IAb) positivity. Methods: Baseline CGM data were collected from participants with ≥1 positive IAb type from five studies: ASK (N=79), BDR (N=22), DAISY (N=18), DIPP (N=8), and TrialNet (N=91). Median follow-up time was 2.6 y (IQR: 1.5 to 3.6 y). A CGM and baseline factor model and a baseline-only model were compared. CGM model classified participants as low (N=97), medium (N=74), or high (N=47) risk of stage 3 T1D based on <10%, 10-<30%, and ≥30% probability by year 2. Results: CGM model found % time >140 mg/dL (TA140), area under the curve 140 mg/dL (AUC140), glucose SD, sex, first degree relative, IA2A, and GADA status were more predictive of T1D progression compared to the baseline-only model (C-statistic: 0.76 vs. 0.62). The probability of developing T1D by 2 years was 4%, 17%, and 51% in the low, medium, and high risk groups (Figure). Compared to low risk participants, high risk participants had higher TA140 (median: 10% vs 2%), AUC140 (mean: 2.9 vs. 1.1 mg/dL), and glucose SD (mean: 24 vs. 18 mg/dL). Conclusion: CGM metrics can help predict T1D progression and classify participant’s risk of impending T1D diagnosis. CGM can be used to better monitor the risk of T1D progression and define eligibility for potential prevention trials. Disclosure P. Calhoun: None. C. Spanbauer: None. A. Steck: None. B.I. Frohnert: None. M.A. Herman: Research Support; Eli Lilly and Company. B. Keymeulen: None. R. Veijola: Advisory Panel; Sanofi. J. Toppari: None. A. Desouter: None. F.K. Gorus: None. M.A. Atkinson: None. D.M. Wilson: Advisory Panel; Enable Biosciences, Inc. S. Pietropaolo: None. R. Beck: Consultant; Insulet Corporation. Research Support; Insulet Corporation. Consultant; Tandem Diabetes Care, Inc. Research Support; Tandem Diabetes Care, Inc. Consultant; Beta Bionics, Inc. Research Support; Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc. Consultant; Novo Nordisk. Research Support; Novo Nordisk, Eli Lilly and Company. Consultant; embecta, Vertex Pharmaceuticals Incorporated, Hagar, Ypsomed AG, Sanofi, Zucara Therapeutics, Sequel. Funding JDRF
期刊介绍：
Diabetes is a scientific journal that publishes original research exploring the physiological and pathophysiological aspects of diabetes mellitus. We encourage submissions of manuscripts pertaining to laboratory, animal, or human research, covering a wide range of topics. Our primary focus is on investigative reports investigating various aspects such as the development and progression of diabetes, along with its associated complications. We also welcome studies delving into normal and pathological pancreatic islet function and intermediary metabolism, as well as exploring the mechanisms of drug and hormone action from a pharmacological perspective. Additionally, we encourage submissions that delve into the biochemical and molecular aspects of both normal and abnormal biological processes.
However, it is important to note that we do not publish studies relating to diabetes education or the application of accepted therapeutic and diagnostic approaches to patients with diabetes mellitus. Our aim is to provide a platform for research that contributes to advancing our understanding of the underlying mechanisms and processes of diabetes.
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