Evidence map›Paper›PMID 29559342›Full record

ArticleThe Journal of investigative dermatology2018

MicroRNA Signatures in Diagnosis and Prognosis of Cutaneous T-Cell Lymphoma.

Xiaoyan Shen, Bo Wang, Kejia Li, Lili Wang, Xiaoqing Zhao, Feng Xue, Ruofei Shi, Jie Zheng

Abstract read
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In one paragraph

Article in The Journal of investigative dermatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
6.0field-weighted citation impact, top 3% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Pooled it
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  15. Diagnosis of Early Mycosis Fungoides.Diagnostics (Basel, Switzerland) · 2021
    Review
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  19. Targeting microRNA in hematologic malignancies.Current opinion in oncology · 2020
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

Xiaoyan ShenDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Bo WangDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Laboratory of Dermatoimmunology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Kejia LiDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Lili WangDepartment of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
Xiaoqing ZhaoDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Feng XueDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Laboratory of Dermatoimmunology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Ruofei ShiDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jie ZhengDepartment of Dermatology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. Electronic address: jie-zheng2001@126.com.
Shanghai Jiao Tong University · CNUniversity of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cutaneous T cell lymphoma (CTCL) can have clinical and histological features resembling benign inflammatory dermatosis and can be difficult to diagnose. Very limited biomarkers are available for CTCL prognosis. We aimed to identify microRNA (miR) signatures to facilitate diagnostic and prognostic evaluations of CTCL. A cross-platform miR microarray identified 10 miRs that were differentially expressed between CTCL and benign inflammatory dermatosis patients. Subsequent reverse transcription polymerase chain reaction validation was used to generate a 5-miR-based diagnosing classifier, which showed high diagnostic accuracy in CTCL (area under the curve = 0.985 and 0.956 for training and testing set, respectively). Association between miR expressions and patient prognosis was studied. miR-155 and miR-200b were significantly associated with overall survival in CTCL patients, outperformed Ki-67. miR expressions were combined with Ki-67 to create a classifier for 5-year overall survival in CTCL patients. Our work provided miR signatures to facilitate CTCL diagnosis and prognosis with satisfying accuracy.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorDiagnosis, DifferentialFemaleHumansLymphoma, T-Cell, CutaneousMaleMicroRNAsMiddle AgedPrognosisReproducibility of ResultsSkin NeoplasmsBiomarkers, TumorMicroRNAs

Identifiers

PMID29559342
OpenAlexW2793709937

What OpenQuestion holds

Textmetadata
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.