Evidence map›Paper›PMID 29404062›Full record

ArticleJournal of pharmaceutical analysis2017

A validated UPLC-MS/MS method for simultaneous determination of imatinib, dasatinib and nilotinib in human plasma.

Jing Zeng, Hua Lin Cai, Zhi Ping Jiang, Qing Wang, Yan Zhu, Ping Xu, Xie Lan Zhao

Open access · goldAbstract read
In one paragraph

Article in Journal of pharmaceutical analysis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 32 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

7 authors at 2 institutions in 1 country.

Jing ZengDepartment of Pharmacy, the Second Xiangya Hospital, Central South University, NO139, Renmin Road, Changsha, Hunan 410011, China.
Hua Lin CaiDepartment of Pharmacy, the Second Xiangya Hospital, Central South University, NO139, Renmin Road, Changsha, Hunan 410011, China.
Zhi Ping JiangDepartment of Hematology, Xiangya Hospital, Central South University, NO87, Xiangya Road, Changsha, Hunan 410008, China.
Qing WangDepartment of Pharmacy, the Second Xiangya Hospital, Central South University, NO139, Renmin Road, Changsha, Hunan 410011, China.
Yan ZhuDepartment of Pharmacy, the Second Xiangya Hospital, Central South University, NO139, Renmin Road, Changsha, Hunan 410011, China.
Ping XuDepartment of Pharmacy, the Second Xiangya Hospital, Central South University, NO139, Renmin Road, Changsha, Hunan 410011, China.
Xie Lan ZhaoDepartment of Hematology, Xiangya Hospital, Central South University, NO87, Xiangya Road, Changsha, Hunan 410008, China.
Central South University · CNXiangya Hospital Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A sensitive, rapid, simple and economical ultra-performance liquid chromatography-tandem mass spectrometric method (UPLC-MS/MS) was developed and validated for simultaneous determination of imatinib, dasatinib and nilotinib in human plasma using gliquidone as internal standard (IS). Liquid-liquid extraction method with ethyl acetate was used for sample pre-treatment. The separation was performed on an Xtimate Phenyl column using isocratic mobile phase consisting of A (aqueous phase: 0.15% formic acid and 0.05% ammonium acetate) and B (organic phase: acetonitrile) (A:B=40:60, v/v). The flow rate was 0.25 mL/min and the total run time was 6 min. The multiple reaction monitoring (MRM) transitions,

Indexed as

DasatinibImatinibNilotinibPolymorphismUPLC–MS/MS

Identifiers

PMID29404062
PMCPMC5790746
OpenAlexW2740620211

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.