Evidence map›Paper›PMID 25500866›Full record

ArticleActa pharmacologica Sinica2015

A population pharmacokinetic study of tacrolimus in healthy Chinese volunteers and liver transplant patients.

Yan-xia Lu, Qing-hong Su, Ke-hua Wu, Yu-peng Ren, Liang Li, Tian-yan Zhou, Wei Lu

Open access · bronzeAbstract read
In one paragraph

Article in Acta pharmacologica Sinica, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 4 pooled it
1.2field-weighted citation impact, top 20% 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

27 citing papers in PubMed, 4 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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  20. Population pharmacokinetic analysis of tacrolimus in Chinese cardiac transplant recipients.European journal of hospital pharmacy : science and practice · 2020
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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

7 authors at 2 institutions in 1 country.

Yan-xia Lu1] General Hospital of Armed Police Forces, Beijing 100039, China [2] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [3] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Qing-hong Su1] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [2] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Ke-hua Wu1] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [2] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Yu-peng Ren1] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [2] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Liang Li1] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [2] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Tian-yan Zhou1] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [2] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Wei Lu1] Department of Pharmaceutics, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China [2] State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing 100191, China.
Peking University · CNChinese People's Armed Police General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo develop a population pharmacokinetic (PopPK) model of tacrolimus in healthy Chinese volunteers and liver transplant recipients for investigating the difference between the populations, and for potential individualized medication.

methodsA set of 1100 sparse trough concentration data points from 112 orthotopic liver transplant recipients, as well as 851 dense data points from 40 healthy volunteers receiving a single dose of tacrolimus (2 mg, p.o.) were collected. PopPK model of tacrolimus was constructed using the program NONMEM. Related covariates such as age, hepatic and renal functions that were potentially associated with tacrolimus disposition were evaluated. The final model was validated using bootstrapping and a visual predictive check.

resultsA two-compartment model of tacrolimus could best describe the data from the two populations. The final model including two covariates, population (liver transplant recipients or volunteers) and serum ALT (alanine aminotransferase) level, was verified and adequately described the pharmacokinetic characteristics of tacrolimus. The estimates of V2/F, Q/F and V3/F were 22.7 L, 76.3 L/h and 916 L, respectively. The estimated CL/F in the volunteers and liver transplant recipients was 32.8 and 18.4 L/h, respectively. Serum ALT level was inversely related to CL/F, whereas age did not influence CL/F. Thus, the elderly (≥65 years) and adult (<65 years) groups in the liver transplant recipients showed no significant difference in the clearance of tacrolimus.

conclusionCompared with using the sparse data only, the integrating modeling technique combining sparse data from the patients and dense data from the healthy volunteers improved the PopPK analysis of tacrolimus.

Indexed as

AdultAgedAsian PeopleFemaleHumansLiverLiver TransplantationMaleMiddle AgedModels, BiologicalRetrospective StudiesTacrolimusVolunteersYoung AdultTacrolimus

Identifiers

PMID25500866
PMCPMC4326784
OpenAlexW2063338463

What OpenQuestion holds

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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.