Evidence map›Paper›PMID 37726405›Full record

ArticlePharmaceutical research2023

Population Pharmacokinetics and Pharmacogenetics Analyses of Dasatinib in Chinese Patients with Chronic Myeloid Leukemia.

Shiyu He, Jinxia Zhao, Jialu Bian, Yinyu Zhao, Yuanyuan Li, Nan Guo, Lei Hu, Boyu Liu, Qianhang Shao, Huan He and 2 more

Abstract read
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In one paragraph

Article in Pharmaceutical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Observational
  2. Review
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

12 authors at 2 institutions in 1 country.

Shiyu HeDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Jinxia ZhaoDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Jialu BianDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Yinyu ZhaoDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Yuanyuan LiDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Nan GuoDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Lei HuDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Boyu LiuDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Qianhang ShaoDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China.
Huan HeDepartment of Pharmacy, Beijing Children's Hospital of Capital Medical University, Beijing, China.
Lin HuangDepartment of Pharmacy, Peking University People's Hospital, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China. huanglin@pkuph.edu.cn.ORCID http://orcid.org/0000-0003-3264-1374
Qian JiangPeking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, No. 11 Xizhimen South StreetXicheng District, Beijing, 100044, China. jiangqian@medmail.com.cn.
Peking University · CNCapital Medical University · CN

Funding

Natural Science Foundation of Beijing Municipality 7192218
6 · The paper itself

Abstract

aimsDasatinib, a second-generation tyrosine kinase inhibitor of BCR-ABL 1, used for first-line treatment of Philadelphia chromosome-positive chronic myeloid leukemia (CML), exhibits high pharmacokinetic (PK) variability. However, its PK data in Chinese patients with CML remains rarely reported to date. Thus, we developed a population pharmacokinetic (PPK) model of dasatinib in Chinese patients and identified the covariate that could explain the individual variability of PK for optimal individual administration.

methodsPPK modeling for dasatinib was performed based on 754 plasma concentrations obtained from 140 CML patients and analysis of various genetic and physicochemical parameters. Modeling was performed with nonlinear mixed-effects (NLME) using Phoenix NLME. The finally developed model was evaluated using internal and external validation. Monte Carlo simulations were used to predict drug exposures at a steady state for various dosages.

resultsThe PK of dasatinib were well described by a two-compartment with a log-additive residual error model. Patients in the current study had a relatively low estimate of CL/F (126 L/h). A significant association was found between the covariate of age and CL/F of dasatinib, which was incorporated into the final model. None of the genetic factors was confirmed as a significant covariate for dasatinib. The results of external validation with 140 samples from 36 patients were acceptable. Simulation results showed significantly higher exposures in elderly patients.

conclusionsThis study's findings suggested that low-dose dasatinib would be better suited for Chinese patients, and the dosage can be appropriately reduced according to the increase of age, especially for the elderly.

Indexed as

Antineoplastic AgentsLeukemia, Myelogenous, Chronic, BCR-ABL PositiveAgedDasatinibEast Asian PeopleHumansPharmacogeneticsProtein Kinase InhibitorsPyrimidinesAntineoplastic AgentsDasatinibProtein Kinase InhibitorsPyrimidineschronic myeloid leukemiadasatinibindividualized medicinepharmacogeneticspopulation pharmacokinetics

Identifiers

PMID37726405
OpenAlexW4386857331

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.