Evidence map›Paper›PMID 32265712›Full record

ArticleFrontiers in pharmacology2020

Effect of Protein Binding on Exposure of Unbound and Total Mycophenolic Acid: A Population Pharmacokinetic Analysis in Chinese Adult Kidney Transplant Recipients.

Changcheng Sheng, Qun Zhao, Wanjie Niu, Xiaoyan Qiu, Ming Zhang, Zheng Jiao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

11 citing papers in PubMed, 24 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Changcheng ShengDepartment of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
Qun ZhaoDepartment of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
Wanjie NiuDepartment of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
Xiaoyan QiuDepartment of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
Ming ZhangDepartment of Nephropathy, Huashan Hospital, Fudan University, Shanghai, China.
Zheng JiaoDepartment of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
Fudan University · CNHuashan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe population pharmacokinetic (popPK) characteristics of total mycophenolic acid (tMPA) have been investigated in various ethnic populations. However, investigations of popPK of unbound MPA (uMPA) are few. Thus, a popPK analysis was performed to: (1) characterize the PK of uMPA and tMPA and its 7-O-mycophenolic acid glucuronide (MPAG) metabolite in kidney transplant patients cotreated with cyclosporine (CsA), and (2) identify the clinically significant covariates that explain variability in the dose-exposure relationship.

methodsA total of 740 uMPA, 741 tMPA, and 734 total MPAG (tMPAG) concentration-time data from 58 Chinese kidney transplant patients receiving MPA in combination with CsA were analyzed using NONMEM

resultsThe PK of uMPA and unbound MPAG (uMPAG) were characterized by a two- and one-compartment model with first-order elimination, respectively. A linear protein binding model was used to link uMPA and tMPA. Apparent clearance (CL/F) and central volume of distribution (V

conclusionsThe established model adequately described the popPK characteristics of the uMPA, tMPA, and MPAG. The estimated CL

Indexed as

adult kidney transplant recipientslinear protein bindingnonlinear mixed-effect modelingpopulation pharmacokineticsunbound mycophenolic acid

Identifiers

PMID32265712
PMCPMC7100081
OpenAlexW3011147875

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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.