Insulin Secretion Predicts the Response to Antidiabetic Therapy in Patients With New-onset Diabetes.


Journal

The Journal of clinical endocrinology and metabolism
ISSN: 1945-7197
Titre abrégé: J Clin Endocrinol Metab
Pays: United States
ID NLM: 0375362

Informations de publication

Date de publication:
19 11 2021
Historique:
received: 27 02 2021
pubmed: 4 8 2021
medline: 29 12 2021
entrez: 3 8 2021
Statut: ppublish

Résumé

The results of the present study demonstrate that beta cell function in newly diagnosed T2DM patients is the key predictor of response to glucose lowering medications and provides a practical tool (C-Pep120 /C-Pep0) to guide the choice of glucose lowering agent. This work aims to identify predictors for individualization of antidiabetic therapy in patients with new-onset type 2 diabetes mellitus (T2DM). A total of 261 drug-naive participants in the Efficacy and Durability of Initial Combination Therapy for Type 2 Diabetes (EDICT) study, with new-onset diabetes, were randomly assigned in a single-center study to receive 1) metformin followed by glipizide and then insulin glargine on failure to achieve glycated hemoglobin A1c (HbA1c) less than 6.5%, or 2) initial triple therapy with metformin/pioglitazone/exenatide. Each patient received a 75-g oral glucose tolerance test (OGTT) prior to start of therapy. Factors that predicted response to therapy were identified using the area under the receiver operating characteristic curve method. Thirty-nine patients started and maintained the treatment goal (HbA1c < 6.5%) on metformin only, and did not require intensification of antihyperglycemic therapy; 54 patients required addition of glipizide to metformin; and 47 patients required insulin addition to metformin plus glipizide for glucose control. The plasma C-peptide concentration (C-Pep)120/C-Pep0 ratio during the OGTT was the strongest predictor of response to therapy. Patients with a ratio less than 1.78 were more likely to require insulin for glucose control, whereas patients with a ratio greater than 2.65 were more likely to achieve glucose control with metformin monotherapy. In patients started on initial triple therapy, the HbA1c decreased independently of the C-Pep120/C-Pep0 ratio. The increase in C-Pep above fasting following glucose load predicts the response to antihyperglycemic therapy in patients with new-onset diabetes. C-Pep120/C-Pep0 provides a useful tool for the individualization of antihyperglycemic therapy in patients with new-onset T2DM.

Identifiants

pubmed: 34343296
pii: 6338179
doi: 10.1210/clinem/dgab403
pmc: PMC8787634
doi:

Substances chimiques

Biomarkers 0
Blood Glucose 0
C-Peptide 0
Glycated Hemoglobin A 0
Hypoglycemic Agents 0
Insulin 0
hemoglobin A1c protein, human 0

Types de publication

Clinical Trial Journal Article Randomized Controlled Trial Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3497-3504

Subventions

Organisme : NIDDK NIH HHS
ID : R01 DK107680
Pays : United States
Organisme : NIDDK NIH HHS
ID : DK107680
Pays : United States

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Auteurs

S Abdelgani (S)

Division of Diabetes, University of Texas Health Science Center and Texas Diabetes Institute, San Antonio, Texas, USA.

C Puckett (C)

Division of Diabetes, University of Texas Health Science Center and Texas Diabetes Institute, San Antonio, Texas, USA.

J Adams (J)

Division of Diabetes, University of Texas Health Science Center and Texas Diabetes Institute, San Antonio, Texas, USA.

C Triplitt (C)

Division of Diabetes, University of Texas Health Science Center and Texas Diabetes Institute, San Antonio, Texas, USA.

R A DeFronzo (RA)

Division of Diabetes, University of Texas Health Science Center and Texas Diabetes Institute, San Antonio, Texas, USA.

M Abdul-Ghani (M)

Division of Diabetes, University of Texas Health Science Center and Texas Diabetes Institute, San Antonio, Texas, USA.

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Classifications MeSH