Literature DB >> 22162539

Quantitative model of the relationship between dipeptidyl peptidase-4 (DPP-4) inhibition and response: meta-analysis of alogliptin, saxagliptin, sitagliptin, and vildagliptin efficacy results.

John P Gibbs1, Jill Fredrickson, Todd Barbee, Itzela Correa, Brian Smith, Shao-Lee Lin, Megan A Gibbs.   

Abstract

Dipeptidyl peptidase-4 (DPP-4) inhibition is a well- characterized treatment for type 2 diabetes mellitus (T2DM). The objective of this model-based meta-analysis was to describe the time course of HbA1c response after dosing with alogliptin (ALOG), saxagliptin (SAXA), sitagliptin (SITA), or vildagliptin (VILD). Publicly available data involving late-stage or marketed DPP-4 inhibitors were leveraged for the analysis. Nonlinear mixed-effects modeling was performed to describe the relationship between DPP-4 inhibition and mean response over time. Plots of the relationship between metrics of DPP-4 inhibition (ie, weighted average inhibition [WAI], time above 80% inhibition, and trough inhibition) and response after 12 weeks of daily dosing were evaluated. The WAI was most closely related to outcome, although other metrics performed well. A model was constructed that included fixed effects for placebo and drug and random effects for intertrial variability and residual error. The relationship between WAI and outcome was nonlinear, with an increasing response up to 98% WAI. Response to DPP-4 inhibitors could be described with a single drug effect. The WAI appears to be a useful index of DPP-4 inhibition related to HbA1c. Biomarker to response relationships informed by model-based meta-analysis can be leveraged to support study designs including optimization of dose, duration of therapy, and patient population.

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Year:  2011        PMID: 22162539     DOI: 10.1177/0091270011420153

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  17 in total

1.  Population Pharmacokinetic/Pharmacodynamic Modelling of Dipeptidyl Peptidase IV Inhibitors.

Authors:  Cornelia B Landersdorfer
Journal:  Clin Pharmacokinet       Date:  2015-07       Impact factor: 6.447

2.  Longitudinal model-based meta-analysis for survival probabilities in patients with castration-resistant prostate cancer.

Authors:  Wenjun Chen; Liang Li; Shuangmin Ji; Xuyang Song; Wei Lu; Tianyan Zhou
Journal:  Eur J Clin Pharmacol       Date:  2020-01-10       Impact factor: 2.953

3.  Prediction of the effect on antihyperglycaemic action of sitagliptin by plasma active form glucagon-like peptide-1.

Authors:  Akifumi Kushiyama; Takako Kikuchi; Kentaro Tanaka; Tazu Tahara; Toshiko Takao; Yukiko Onishi; Yoko Yoshida; Shoji Kawazu; Yasuhiko Iwamoto
Journal:  World J Diabetes       Date:  2016-06-11

4.  Evaluation of non-linear-mixed-effect modeling to reduce the sample sizes of pediatric trials in type 2 diabetes mellitus.

Authors:  Clémence Rigaux; Bernard Sébastien
Journal:  J Pharmacokinet Pharmacodyn       Date:  2020-01-06       Impact factor: 2.745

5.  Quantitative analysis of efficacy and associated factors of calcium intake on bone mineral density in postmenopausal women.

Authors:  J Wu; L Xu; Y Lv; L Dong; Q Zheng; L Li
Journal:  Osteoporos Int       Date:  2017-03-23       Impact factor: 4.507

Review 6.  Anti-Diabetic Drugs: Cure or Risk Factors for Cancer?

Authors:  Jeny Laskar; Kasturi Bhattacharjee; Mahuya Sengupta; Yashmin Choudhury
Journal:  Pathol Oncol Res       Date:  2018-03-13       Impact factor: 3.201

7.  A Model-Based Meta-analysis to Compare Efficacy and Tolerability of Tramadol and Tapentadol for the Treatment of Chronic Non-Malignant Pain.

Authors:  François Mercier; Laurent Claret; Klaas Prins; René Bruno
Journal:  Pain Ther       Date:  2014-02-13

8.  Utilization of model-based meta-analysis to delineate the net efficacy of taspoglutide from the response of placebo in clinical trials.

Authors:  Han Qing Li; Jia Yin Xu; Liang Jin; Ji Le Xin
Journal:  Saudi Pharm J       Date:  2014-11-24       Impact factor: 4.330

9.  A novel model-based meta-analysis to indirectly estimate the comparative efficacy of two medications: an example using DPP-4 inhibitors, sitagliptin and linagliptin, in treatment of type 2 diabetes mellitus.

Authors:  Jorge Luiz Gross; James Rogers; Daniel Polhamus; William Gillespie; Christian Friedrich; Yan Gong; Brigitta Ursula Monz; Sanjay Patel; Alexander Staab; Silke Retlich
Journal:  BMJ Open       Date:  2013-03-05       Impact factor: 2.692

Review 10.  Alogliptin benzoate for management of type 2 diabetes.

Authors:  Yoshifumi Saisho
Journal:  Vasc Health Risk Manag       Date:  2015-04-10
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