Evidence map›Paper›PMID 37968422›Full record

ArticleAnnals of hematology2024

Detection and quantification of JAK2V617F copy number by droplet digital PCR versus real-time PCR.

Sanyun Wu, Yixuan Li, Ruiying Huang, Ting Li, Yalan Yu, Ping Luo, Xuelan Zuo, Li He

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Article in Annals of hematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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.

  1. Review
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4 · The record

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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

8 authors.

Sanyun WuDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China. wusanyun@whu.edu.cn.ORCID http://orcid.org/0000-0001-8075-6841
Yixuan LiDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.
Ruiying HuangDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.
Ting LiDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.
Yalan YuDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.
Ping LuoDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.
Xuelan ZuoDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.
Li HeDepartment of Hematology, Zhongnan Hospital of Wuhan University, Donghu Road, No. 169, Wuhan, China.

Funding

Natural Science Foundation of Hubei Province 2018CFB243
6 · The paper itself

Abstract

Myeloproliferative neoplasm (MPN) usually has an adverse prognosis, progressing to acute leukemia or splanchnic vein thromboses (SVTs). Therefore, early diagnosis and intervention are significantly important. Clinically, the burden of JAK2V617F is a vital diagnostic basis, which can be detected during the early stage of MPN. Thus, an accurate and rapid detective technique is urgently required. In recent years, real-time quantitative PCR (qPCR) has primarily been applied to detect the copies of JAK2V617F, whereas droplet digital PCR (ddPCR), a novel and promising detective tool, can conduct precise and repeatable quantification of nucleic acid copies without relying on the standard curve. In our study, both qPCR and ddPCR are used to evaluate the mutation burden of JAK2V617F in a series of gradient diluted standards and clinical JAK2V617F-positive MPN patients' bone marrow samples collected, while using next-generation sequencing technology (NGS) as a contrast. With the help of statistical methods, our study concluded that ddPCR had a better performance in accuracy, sensitivity, and stability, especially in a low burden. Regarding the accuracy, ddPCR showed a better linearity (Pearson R

Indexed as

DNA Copy Number VariationsMyeloproliferative DisordersHumansLimit of DetectionReal-Time Polymerase Chain ReactionSensitivity and SpecificityDroplet digital PCRMyeloproliferative neoplasmNext-generation sequencingReal-time PCR

Identifiers

PMID37968422

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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.