Evidence map›Paper›PMID 32166619›Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2020

Model-based Prediction of the Long-term Glucose-Lowering Effects of Ipragliflozin, a Selective Sodium-Glucose Cotransporter 2 (SGLT2) Inhibitor, in Patients with Type 2 Diabetes Mellitus.

Masako Saito, Atsunori Kaibara, Takeshi Kadokura, Junko Toyoshima, Satoshi Yoshida, Kenichi Kazuta, Eiji Ueyama

Open access · goldAbstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 51% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Masako SaitoAstellas Pharma Inc., Tokyo, Japan. masako.saito@astellas.com.ORCID http://orcid.org/0000-0001-5062-9905
Atsunori KaibaraAstellas Pharma Inc., Tokyo, Japan.
Takeshi KadokuraAstellas Pharma Inc., Tokyo, Japan.
Junko ToyoshimaAstellas Pharma Inc., Tokyo, Japan.
Satoshi YoshidaAstellas Pharma Inc., Tokyo, Japan.
Kenichi KazutaAstellas Pharma Inc., Tokyo, Japan.
Eiji UeyamaAstellas Pharma Inc., Tokyo, Japan.
Astellas Pharma (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSodium-dependent glucose cotransporter 2 (SGLT2) inhibitors inhibit the reabsorption of glucose from the kidneys and increase urinary glucose excretion (UGE), thereby lowering the blood glucose concentration in people suffering from type 1 and type 2 diabetes mellitus (T2DM). In a previous study, we reported a pharmacokinetics/pharmacodynamics model to estimate individual change in UGE (ΔUGE), which is a direct pharmacological effect of SGLT2 inhibitors. In this study, we report our enhancement of the previous model to predict the long-term effects of ipragliflozin on clinical outcomes in patients with T2DM.

methodsThe time course of fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) in patients with T2DM following ipragliflozin treatment that had been observed in earlier clinical trials was modeled using empirical models combined with the maximum drug effect (E

resultsThe developed models that included UGE as a dependent variable of response were found to well describe observed time courses in FPG and HbA1c. Baseline blood glucose level and renal function had significant effects on the glucose-lowering effect of ipragliflozin, and these models enabled quantification of these impacts on clinical outcomes. Simulated median changes in HbA1c in T2DM patients with mild and moderate renal impairment were 25 and 63% lower, respectively, than those in T2DM patients with normal renal function. These results are consistent with the observed clinical data from a previous renal impairment study.

conclusionsEmpirical models established based on the effect of UGE well predicted the renal function-dependent long-term glucose-lowering effects of ipragliflozin in patients with T2DM.

Indexed as

Antidiabetic effectDisease progressionExposure–responseIpragliflozinSGLT2 inhibitorSuglatType 2 diabetes mellitus

Identifiers

PMID32166619
PMCPMC7136367
OpenAlexW3010755218

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.