Low body mass index and old age are useful in predicting the hemoglobin A1c-lowering effect of switching from sitagliptin to ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-07

AUTHORS

Tomoyuki Iwasaki, Takaomi Kessoku, Takuma Higurashi, Masataka Taguri, Masato Yoneda

ABSTRACT

Aims: The purpose of this study was to clarify the predictive clinical characteristics of therapy switching from sitagliptin to dulaglutide in patients with type 2 diabetes mellitus. Methods: This single-center, open-label, investigator-initiated pilot study was conducted in 40 patients with type 2 diabetes mellitus. The patients, who had been treated with 50 mg sitagliptin daily for at least 6 months were switched to 0.75 mg dulaglutide weekly. Results: A total of 36 patients could be followed for 24 weeks of treatment with dulaglutide. They were assessed for several clinical parameters before the start of and 24 weeks after the study. Multiple linear regression analysis was used to search for independent predictors of reduction of hemoglobin A1c (HbA1c) levels after 24 weeks of treatment switching from sitagliptin to dulaglutide. Dulaglutide administration for 24 weeks resulted in significant reductions in fasting plasma glucose (FPG), HbA1c, and low-density lipoprotein cholesterol (LDL-C) levels. In addition, baseline HbA1c, FPG, body mass index (BMI), and age were significantly correlated with the change in HbA1c levels (ΔHbA1c). Furthermore, multiple linear regression analysis revealed that BMI and age significantly correlated with ΔHbA1c. Conclusion: In summary, our prospective 24-week study showed that baseline low BMI and old age are significantly useful in predicting the HbA1c-lowering effect of switching from sitagliptin to dulaglutide. Trial Registration: UMIN Clinical Trials Registry (UMIN000023245). More... »

PAGES

189-195

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13340-018-0348-0

DOI

http://dx.doi.org/10.1007/s13340-018-0348-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100790801

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30603366


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